Miracle-dz/UniFAR-FTUs huggingface dataset:
A Histopathological Study of Multi-hormone Producing Proliferative Lesions in Estrogen-induced Rat Pituitary Prolactinoma

Rats with estrogen-induced prolactin-producing pituitary adenoma (E2-PRLoma) have been employed as an animal model of human PRL-producing pituitary adenoma in a large number of studies. Presently, we found that long-term administration of estrogen to SD rats resulted in the development of E2-PRLomas, some of which included multi-hormone producing nodules. We herein report results of histopathological analyses of these lesions. PRLoma models were created in female SD rats by 22 weeks or longer administration of a controlled-release preparation of estradiol at a dose of 10 mg/kg/2 weeks. Ten of the 11 PRLoma model rats had proliferative nodular lesions composed of large eosinophilic cells like gonadotrophs inside the PRLoma. These lesions were positive for PRL, TSHβ, and α subunits and were negative for GH, LHβ, ACTH, and S-100. Double immunostaining revealed that these large eosinophilic cells showed coexpression of PRL and TSHβ, PRL and α subunits, and TSHβ and α subunits. Those results clarified that long-term estrogen administration to female SD rats induced multi-hormone producing neoplastic pituitary nodules that expressed PRL, TSHβ, and α subunits. We studied these neoplastic nodules obtained by laser microdissection to acquire findings similar to those of the immunohistochemical analysis. We consider that this animal model is useful for pathogenesis analyses and therapeutic agent development concerning human multi-hormone producing pituitary adenomas.
Learning distributed deployment and configuration trade-offs for context-aware applications in Intelligent Environments

The Internet of Things (IoT) is rapidly gaining ground as can be witnessed by the pervasive presence of the many things or objects around us that turn our surroundings into Intelligent Environments. These objects interact on a large scale in wired and wireless sensor and actuator networks using advanced communication protocols. Hence, IoT is an open ended and highly dynamic ecosystem with heterogeneous workloads and fluctuating resource availability. Distributed intelligence for smart objects and platforms is a vital enabling factor for IoT, but finding the best strategy to deploy and configure applications - especially those that require contextual intelligence - in a smart environment with dynamic and heterogeneous resource availability is far from straightforward. Our experiments using context-aware applications for Intelligent Environments show that many resource and performance trade-offs exist and that current deployment schemes for these kind of applications are rough around the edges. We illustrate how a modular design philosophy for smart IoT applications enables a more optimal deployments. Furthermore, we present a methodology to inspect and learn the trade-offs of different deployment schemes of IoT applications in order to autonomously optimize their configuration. We validated our methodology on different use cases and scenarios, and the results demonstrate the feasibility of our approach to automate the efficient deployment of IoT applications in the presence of multiple conflicting Quality of Service (QoS) objectives and varying runtime circumstances.
A New Class of LRS Bianchi Type-I Cosmological Models in Lyra's Manifold

LRS Bianchi type-I models have been studied in the cosmological theory based on Lyra's geometry. A new class of exact solutions has been obtained by considering a time dependent displacement field for variable deceleration parameter models of the universe. We have compared our models with those of Einstein's field theory with the cosmological term $\Lambda$. Our frame of reference is restricted to the recent Ia observations of supernovae. Some physical behaviour of the models is also examined in the presence of perfect fluids.
On the Delivery Probability of Two-Hop Relay MANETs with Erasure Coding

This paper focuses on the delivery probability performance in a two-hop relay mobile ad hoc network (MANET) with erasure coding. Available works in this line either considered a simple extreme case of achieving the delivery probability 1, or assumed a simple traffic pattern with only one source-destination pair, or studied a very special MANET scenario (i.e., the sparsely distributed MANET) by assuming that whenever two nodes meet together they can transmit to each other. Obviously, such models cannot be applied for an accurate delivery probability analysis in the general MANETs where the interference, medium contention and traffic contention issues are of significant importance. In this paper, a general finite-state absorbing Markov chain theoretical framework is first developed to model the complicated message spreading process in the challenging MANETs. Based on the theoretical framework, closed-form expressions are further derived for the corresponding message delivery probability under any given message lifetime and message size, where all the above important issues in MANETs are carefully incorporated into analysis. As verified through extensive simulation studies, the new framework can be used to accurately predict the message delivery probability behavior and characterize its relationship with the message size, replication factor and node density there.
Transcription-mediated binding of peptide nucleic acid (PNA) to double-stranded DNA: sequence-specific suicide transcription.

Peptide nucleic acid (PNA) forms sequence-specific (PNA)2/DNA triplexes with one strand of double-stranded DNA by strand invasion. When formed with the template strand of DNA such a (PNA)2/DNA triplex can arrest transcription elongation in vitro and can thus act as an anti-gene agent. One of the major obstacles to applying PNA as an anti-gene agent in vivo is that PNA strand invasion occurs at a very slow rate under moderate salt conditions. In the present study we show that transcription can increase the rate of sequence-specific PNA binding dramatically. Such transcription-mediated PNA binding occurs three times as efficiently when the PNA target is situated on the non- template strand as compared with the template strand. Since transcription can mediate template strand-associated (PNA)2/DNA complexes which arrest further elongation, the action of RNA polymerase results in repression of its own activity, i.e. suicide transcription. These findings are highly relevant for the possible future use of PNA as an anti-gene agent.
Patent Document Retrieval and Classification at KAIST

In this paper, we propose a method to retrieve similar patent documents for a given patent and classify a given patent. We focus on the one of patents’ characteristics: “patents are structuralized by claims, purposes, effects, embodiments of the invention and so on. ” In order to retrieve similar documents from target document set, some specific components to denote the so-called ‘semantic elements’ such as “claim”, “purpose” and “application field” are compared instead of the whole texts. Keyword: Patent Retrieval, Patent Classification, Structural Information, kNN, MEM, Hierarchical Classification
An Augmented Reality Presentation System for Remote Cultural Heritage Sites

Museums often lack the possibility to present archaeological or cultural heritage sites in a realistic and interesting way. Thus are proposing a new way to show augmented reality applications of cultural heritage sites at remote places like museums. In the exhibition space large wall-filling photographs of the real site are superimposed with interactive contextual annotations like 3D reconstructions, images and movies. Therefore we are using two different hardware setups for visualization: Standard UMPCs and a custom made revolving display. The setup has been installed and tested at SIGGRAPH 2008, Allard Pierson Museum in Amsterdam and CeBIT 2009. Museum visitors could experience Forum Romanum and Satricum in an informative and intuitive way by pointing the video see through devices on different areas of the photographs. The result is a more realistic and entertaining way for presenting cultural heritage sites in museums. Furthermore our solution is less expensive than comparable installations regarding content and hardware.
Taxes and unofficial economy in developing and developed countries

This paper empirically investigates the relationship between taxes and the size of the unofficial economy. Consistent with the predictions of the recent theoretical works, we find a significant, negative correlation between the tax ratio and the size of the unofficial economy in developing countries, but a close-to-zero correlation in developed countries. We interpret these results as implying that the ‘institution effect’ dominates the ‘incentive effect’ in less developed countries, but that these effects cancel each other out in developed countries. We also find that countries with larger GDP per capita, more competent bureaucrats, less corrupt governments, and lower unemployment rates tend to have a smaller unofficial economy.
Cloud System for Flight Simulation

The visual realism of a computer graphics simulation of outdoor scenery is greatly enhanced by realistic display of clouds. In flight simulation, large amount clouds need to be rendered in real time. In this paper, we present an algorithm that can generate large scale clouds distribution in simulation world based on several cloud templates. We promote Wang's fast cloud rendering method [1]by reducing ambient color calculation cost and adding RGBA sky color to time samples to provide users more control in clouds rendering. We also combine realistic looking sky model to enhance the visual realism of flight scene.
Improving Robot Behavior Optimization by Combining User Preferences

Recently it has been demonstrated that collaboration between automated algorithms and human users can be especially effective in robot behavior optimization tasks. In particular, we recently introduced a Fitness-based Search with Preferencebased Policy Learning (FS-PPL) approach, in which the algorithm models the user based on her preferences and then uses the model, along with the fitness function, to guide search. However, so far only interaction between a single human user and an evolutionary algorithm was considered. If multiple users contribute preferences, the algorithm must determine whether to model them separately or jointly. In this paper we describe an algorithm in which one evolutionary algorithm interacts with two users and determines the best way to model them automatically. We test the algorithm with automated substitutes for human users and show that it performs better for two users working together than for the same users working separately, thus demonstrating the potential for crowdsourcing robot behavior optimization.
International Conference on Intelligent and Advanced Systems 2007 Annotated Disjunct in Link Grammar for Machine Translation

In this paper, a Machine Translation (MT) model using the Link Grammar (LG) formalism is introduced. The contribution to this formalism is by developing a hybrid of direct and rule-based translation model which is suitable for translating a source language text with its parser into target language text with no grammar formalism and corpus yet. This model can theoretically handle one-to-one, many-to-one, and many-to-many word(s) translations.
Molecular epidemiology of quinolone resistance and comparative in vitro activities of new quinolones against European Staphylococcus aureus isolates.

UNLABELLED New fluoroquinolones (FQ) may possibly be used as alternative therapeutic options for Staphylococcus aureus infections. Our objectives were: (1) to define the in vitro activities of seven FQs in a collection of 434 methicillin-susceptible and 457 methicillin-resistant S. aureus from 23 European university hospitals; (2) to characterise the prevalence of mutations in the grlA and gyrA genes in all ciprofloxacin-resistant (n=433) isolates of S. aureus; (3) to determine the percentage of ciprofloxacin-resistant S. aureus strains with measurable quinolone efflux. METHODS (1) The in vitro activities of different FQs were determined by microdilution tests. (2) PCR-amplified DNA was sequenced. (3) Ciprofloxacin minimum inhibitory concentrations (MIC) were determined in the presence and absence of reserpine, which inhibits efflux pumps. RESULTS (1) Irrespective of the methicillin resistance of the isolates, sitafloxacin and clinafloxacin showed the best in vitro activities. (2) All ciprofloxacin-resistant isolates exhibited GrlA alterations, namely Ser-80-->Phe or Tyr or Glu-84-->Lys or Ala-116-->Glu or Pro or a combination of Ser-80-->Phe and Glu-84-->Val. These alterations in GrlA were combined with alterations in GyrA, namely Ser-84-->Leu or Lys or Glu-88-->Lys or Val. (3) Reserpine reduced ciprofloxacin MIC values in ca. 30% of the clinical isolates tested. CONCLUSIONS (1) This current European overview of mutations involved in FQ resistance demonstrates that only a limited number of classical mutations in grlA and gyrA contributed to resistance in clinical isolates. (2) An efflux pump is involved in ca. 30% of ciprofloxacin-resistant S. aureus isolates. (3) Sitafloxacin and clinafloxacin are two very promising new FQs with good anti-staphylococcal activity. New FQs, perhaps in combination with efflux pump inhibitors, might play a role in the treatment of S. aureus infections.
Probabilistic Distributional Semantics with Latent Variable Models

We describe a probabilistic framework for acquiring selectional preferences of linguistic predicates and for using the acquired representations to model the effects of context on word meaning. Our framework uses Bayesian latent-variable models inspired by, and extending, the well-known Latent Dirichlet Allocation (LDA) model of topical structure in documents; when applied to predicate–argument data, topic models automatically induce semantic classes of arguments and assign each predicate a distribution over those classes. We consider LDA and a number of extensions to the model and evaluate them on a variety of semantic prediction tasks, demonstrating that our approach attains state-of-the-art performance. More generally, we argue that probabilistic methods provide an effective and flexible methodology for distributional semantics.
Rights-based approaches to public health

Many public health practitioners and students struggle with the true meaning and practical application of rights-based approaches in their work. This volume presents examples of public health programs utilizing right-based approaches so health services can reach those that are in most need. This book helps readers appreciate public health programs utilizing rights-based approaches and adapt those approaches for use in their own careers. Although evidence-based best practices for right-based approaches have not been documented until now, the tools and case studies presented in this book will provide the best models available. Case studies will include public health programs employing participatory methods, with an emphasis on the principles of evidence and results, non-discrimination, dignity and correlation to international human rights documents. Examples are taken from both domestic and international programs. The book outlines broad issues involved in health and human rights, including women's rights, environmental issues such as the right to healthy food, air, and water. Additionally, the book examines professional obligations and roles, and offers specific case studies from organizations and practitioners around the world. Finally, the book looks at systemic and policy implications of a rights-based approach to public health.
Bottle packaged wine product detection by UHF RFID systems

A new invention of wine closure is introduced. By means of this closure, a UHF RFID application for a bottle packaged wine product detection is realized. The application is realized by designing a tag based on a meander line dipole antenna, according to the shape of the new wine closure, so that the tag can be inserted into the closure with good radiation performance. Moreover, this is the first RFID tag using the meander line monopole antenna. The experiment shows that the bottle packaged wine product labeled by the tag can be detected at about 1.5m distance, which is much longer than previously reported on wine product detection.
Semi-Automatically Modeling Web APIs to Create Linked APIs

The objective of new service modeling approaches introduced by recent work on linked services is to integrate Linked Data and service APIs. Building these models is time consuming and difficult, which is an obstacle preventing wide adoption of these modeling approaches. We introduce an approach to semi-automatically build semantic models of the Web APIs by using examples of input values. We use these values to invoke the service and then use the input and output values to learn a semantic model of an API. These models enable a system to easily integrate data and services and to export the models as Linked APIs.
Magnetized Accretion-Ejection Structures: 2.5-dimensional Magnetohydrodynamic Simulations of Continuous Ideal Jet Launching from Resistive Accretion Disks

We present numerical magnetohydrodynamic (MHD) simulations of a magnetized accretion disk launching trans-Alfvénic jets. These simulations, performed in a 2.5-dimensional time-dependent polytropic resistive MHD framework, model a resistive accretion disk threaded by an initial vertical magnetic field. The resistivity is only important inside the disk and is prescribed as η = αmVAH exp(-2Z2/H2), where VA stands for Alfvén speed, H is the disk scale height, and the coefficient αm is smaller than unity. By performing the simulations over several tens of dynamical disk timescales, we show that the launching of a collimated outflow occurs self-consistently and the ejection of matter is continuous and quasi-stationary. These are the first ever simulations of resistive accretion disks launching nontransient ideal MHD jets. Roughly 15% of accreted mass is persistently ejected. This outflow is safely characterized as a jet since the flow becomes superfast magnetosonic, well collimated, and reaches a quasi-stationary state. We present a complete illustration and explanation of the "accretion-ejection" mechanism that leads to jet formation from a magnetized accretion disk. In particular, the magnetic torque inside the disk brakes the matter azimuthally and allows for accretion, while it is responsible for an effective magnetocentrifugal acceleration in the jet. As such, the magnetic field channels the disk angular momentum and powers the jet acceleration and collimation. The jet originates from the inner disk region where equipartition between thermal and magnetic forces is achieved. A hollow, superfast magnetosonic shell of dense material is the natural outcome of the inward advection of a primordial field.
Bi‐Criteria Scheduling of Surgical Services for an Outpatient Procedure Center

Uncertainty in the duration of surgical procedures can cause long patient wait times, poor utilization of resources, and high overtime costs. We compare several heuristics for scheduling an Outpatient Procedure Center. First, a discrete event simulation model is used to evaluate how 12 different sequencing and patient appointment time‐setting heuristics perform with respect to the competing criteria of expected patient waiting time and expected surgical suite overtime for a single day compared with current practice. Second, a bi‐criteria genetic algorithm (GA) is used to determine if better solutions can be obtained for this single day scheduling problem. Third, we investigate the efficacy of the bi‐criteria GA when surgeries are allowed to be moved to other days. We present numerical experiments based on real data from a large health care provider. Our analysis provides insight into the best scheduling heuristics, and the trade‐off between patient and health care provider‐based criteria. Finally, we summarize several important managerial insights based on our findings.
Learning Mental Models

The process of learning is not always as simple as mapping inputs to the best outputs. Often internal state is needed to distinguish between observably identical states of the world. Genetic programming has concentrated on solving problems in the functional/reactive arena, in part because of the absence of a natural way to incorporate memory into the paradigm. This paper presents a simple addition to the genetic programming paradigm that seamlessly incorporates the evolution of the effective gathering, storage, and retrieval of arbitrarily complicated state information. Experimental results show that the effective production and use of complex state structures can be evolved and that agents evolving the use of memory quickly and permanently displace purely reactive and non-deterministic functions. These results may not only aid future research into the causes and constituents of mental models but may expand the types of problems that can be practically tackled by genetic programming.
Exact simulation of diffusions

We describe a new, surprisingly simple algorithm, that simulates exact sample paths of a class of stochastic differential equations. It involves rejection sampling and, when applicable, returns the location of the path at a random collection of time instances. The path can then be completed without further reference to the dynamics of the target process.
Off line signature recognition based on contourlet transform

In this paper, we propose new offline Persian signature recognition based on the contourlet transform (CT). We utilize Support vector machine (SVM) as a tool to evaluate the performance of the proposed method. In proposed method, first signature image is normalized by size then image is enhanced to remove noise. After pre-processing, signature image is divided into four regions, contourlet coefficients are computed on each region. Next the histogram of orientation and direction of each region are computed so we have four histograms that are fed to a layer of SVM classifiers as feature vector. Our Persian dataset include 400 genuine images and 200 forgery images. Recognition rate is 98%.