Miracle-dz/UniFAR-FTUs huggingface dataset:
Image denoising and restoration with CNN-LSTM Encoder Decoder with Direct Attention

Image denoising is always a challenging task in the field of computer vision and image processing. In this paper, we have proposed an encoder-decoder model with direct attention, which is capable of denoising and reconstruct highly corrupted images. Our model consists of an encoder and a decoder, where the encoder is a convolutional neural network and decoder is a multilayer Long Short-Term memory network. In the proposed model, the encoder reads an image and catches the abstraction of that image in a vector, where decoder takes that vector as well as the corrupted image to reconstruct a clean image. We have trained our model on MNIST handwritten digit database after making lower half of every image as black as well as adding noise top of that. After a massive destruction of the images where it is hard for a human to understand the content of those images, our model can retrieve that image with minimal error. Our proposed model has been compared with convolutional encoder-decoder, where our model has performed better at generating missing part of the images than convolutional autoencoder.
Serotonin Depletion-Induced Maladaptive Aggression Requires the Presence of Androgens

The sex hormone testosterone and the neurotransmitter serotonin exert opposite effects on several aspects of behavior including territorial aggression. It is however not settled if testosterone exerts its pro-aggressive effects by reducing serotonin transmission and/or if the anti-aggressive effect of serotonin requires the presence of the androgen. Using the resident intruder test, we now show that administration of the serotonin synthesis inhibitor para-chlorophenylalanine (300 mg/kg x 3 days) increases the total time of attack as well as the percentage amount of social behavior spent on attack but not that spent on threat – i.e. that it induces a pattern of unrestricted, maladaptive aggression – in gonadectomized C57Bl/6 male mice receiving testosterone replacement; in contrast, it failed to reinstate aggression in those not given testosterone. Whereas these results suggest the pro-aggressive effect of testosterone to be independent of serotonin, and not caused by an inhibition of serotonergic activity, the pCPA-induced induction of maladaptive aggression appears to require the presence of the hormone. In line with these findings, pCPA enhanced the total time of attack as well the relative time spent on attacks but not threats also in wild-type gonadally intact male C57Bl/6 mice, but failed to reinstate aggression in mice rendered hypo-aggressive by early knock-out of androgen receptors in the brain (ARNesDel mice). We conclude that androgenic deficiency does not dampen aggression by unleashing an anti-aggressive serotonergic influence; instead serotonin seems to modulate aggressive behavior by exerting a parallel-coupled inhibitory role on androgen-driven aggression, which is irrelevant in the absence of the hormone, and the arresting of which leads to enhanced maladaptive aggression.
Cytomegalovirus pneumonitis: spectrum of parenchymal CT findings with pathologic correlation in 21 AIDS patients.

PURPOSE To identify characteristic features of cytomegalovirus (CMV) pneumonitis at computed tomography (CT), particularly markers that may help differentiate CMV from Pneumocystis carinii pneumonia. MATERIALS AND METHODS Bronchoalveolar lavage (BAL) and biopsy results in 21 patients with acquired immunodeficiency syndrome, cytopathologic evidence of CMV infection without other infections, and available CT scans were retrospectively evaluated. CT findings were correlated with radiographic and pathologic findings when available. RESULTS BAL findings were positive for CMV in only six cases, 13 patients had extrathoracic CMV infection, and 10 had Kaposi sarcoma. CT findings included ground-glass attenuation, dense consolidation, bronchial wall thickening or bronchiectasis, and interstitial reticulation without air-space disease (12 patients had discrete pulmonary nodules or masses). Biopsy revealed air-space disease as the dominant process in eight cases. Histopathologic findings correlated well with CT appearances. CONCLUSION CMV pneumonitis should be suspected in patients with either extrathoracic CMV or documented Kaposi sarcoma, especially when radiographic or CT evidence of pulmonary nodules or masses exists.
TIMEX3 and event extraction using recurrent neural networks

This paper investigates the performance of Elman-type and Jordan-type recurrent neural networks (RNN) in extracting temporal information from textual data. The RNN architectures are applied to two tasks of TempEval-2 challenge: (1) extracting the extent of TIMEX3 tags and its TYPE, and (2) extracting the extent of EVENT tags and its CLASS attribute. For the first task, the performances of the RNN models are highly comparable to that of the wining entry for the challenge. For the second task, both models outperform the winning entry, attaining nearly full scores.
Fixing convergence of Gaussian belief propagation

Gaussian belief propagation (GaBP) is an iterative message-passing algorithm for inference in Gaussian graphical models. It is known that when GaBP converges it converges to the correct MAP estimate of the Gaussian random vector and simple sufficient conditions for its convergence have been established. In this paper we develop a double-loop algorithm for forcing convergence of GaBP. Our method computes the correct MAP estimate even in cases where standard GaBP would not have converged. We further extend this construction to compute least-squares solutions of over-constrained linear systems. We believe that our construction has numerous applications, since the GaBP algorithm is linked to solution of linear systems of equations, which is a fundamental problem in computer science and engineering. As a case study, we discuss the linear detection problem. We show that using our new construction, we are able to force convergence of Montanari's linear detection algorithm, in cases where it would originally fail. As a consequence, we are able to increase significantly the number of users that can transmit concurrently.
Encrypted Storage of Medical Data on a Grid

Summary Objectives: In this article we present grids as an architecture for medical image processing and health-care networks. We argue that confidential patient data should not be stored unprotected on a grid and explain why access control systems alone do not offer sufficient protection. The objective of our work is to propose a method that complements access control systems on a grid architecture and thus makes the storage of confidential data more secure. Methods: Effective protection can be achieved by storing confidential data in encrypted form. This raises the problem of how authorized users get access to the data, since they need to have the decryption keys. Results: Our proposal details a key management architecture, that allows encrypted storage and still enables users to access decryption keys for data they are authorized to see. To achieve this functionality we use distributed keyservers storing redundant shares of the keys. Conclusions: The resulting architecture achieves our primary objective of making the storage of confidential data more secure without loosing the data sharing properties of the grid architecture. Furthermore our architecture is robust against breakdowns and denial of service attacks. It scales well with the number of users and does not introduce a single point of failure into the system.
PSK Precoding in Multi-User MISO Systems

We consider the downlink scenario of multiuser multiple-input-single-output (MU-MISO) communication systems with constant envelope (CE) signals emitted from each antenna. This results in energy efficient power amplifiers (PAs). We propose a holistic CE precoding scheme based on the symbol-wise minimum squared error (SMSE) criterion. Additionally, we analyze the distortions introduced by low-resolution quantization to PSK for higher energy efficiency reasons. We present three solution algorithms and examine their performance to decide for the best pick for different quantization resolutions. Our results show that good performance can be achieved with minimal loss compared to an ideal unquantized case. Finally, we analyze and discuss the results and consider the overall complexity of the precoder as well as implementation issues.
Role of references in similarity estimation of publications

Similarity estimation among publications is very important in classification and clustering techniques for grouping, indexing, citation matching and Author Name Disambiguation (AND) purposes. Publication attributes are basic sources of information and play important role in similarity estimation. Most of the works in AND use title, co-authors and venue attributes for estimating similarity among publications. Many other sources of information such as self-citations, shared citations and references, topic of the publications and abstracts have also been employed to estimate optimal similarity among publications. Recently, in the field of Academic Document Clustering (ADC), reference marker contexts have been utilized for this purpose. However, the use of citations and references is less common since only a few databases include this information. In this paper, we propose to use two components of references (co-authors and titles of references) as sources of information and investigate the importance of these components in similarity estimation. To the best of our knowledge, this is the first endeavour to exploit components of references as sources of information. Experiments conducted on real publication datasets reveal that these components of references are significant source of information for similarity estimation among publications.
Global interpersonal inequality Trends and measurement

This paper discusses different approaches to the measurement of global interpersonal in equality. Trends in global interpersonal inequality during 1975-2005 are measured using data from UNU-WIDER’s World Income Inequality Database. In order to better understand the trends, global interpersonal inequality is decomposed into within-country and between-country inequality. The paper illustrates that the relationship between global interpersonal inequality and these constituent components is a complex one. In particular, we demonstrate that the changes in China's and India's income distributions over the past 30 years have simultaneously caused inequality to rise domestically in those countries, while tending to reduce global inter-personal inequality. In light of these findings, we reflect on the meaning and policy relevance of global vis-a- vis domestic inequality measures.
Estimating Body Pose from A Single Image

Previous Work: There are a number of systems that tackle the specific problem defined here, the latest one being [2]. They use fairly generic machine learning techniques to find a mapping from image silhouettes to body pose. Our work takes a more geometric approach by modeling the body as an articulated model. There are a number of techniques for matching articulated models to images, see [1] for a brief overview.
Psycho-Socio-Cultural Risk Factors for Breech Presentation

ix CHAPTER ONE: INTRODUCTION 1 Statement of the Problem 1 Purpose of the Research 3 Research Questions 3 Significance of the Study 4 Complementariness of Anthropology and Epidemiology 4 Role of Applied Anthropology in Study 5 Role of Epidemiology in Study 8 Relevance of Study to Applied Anthropology 8 Relevance of Study to Epidemiology 8 CHAPTER TWO: LITERATURE REVIEW 10 Explanatory Models of Adverse Pregnancy Outcomes 10 Biomedicine & Epidemiology 10 Western History of Childbirth 10 Risk Factors for Breech Presentation 18 Maternal Socio-Demographic Characteristics 19 Fetal Characteristics 19 Breech Delivery 21 Chinese Medicine 23 Ayurvedic Medicine 24 Direct Entry Midwifery & Breech Delivery 24 Ethnographic Record 25 Emotions 25 ` Work 26 Malpresentation 27 Dominant Explanatory Model Themes for Breech Presentation 28 Mechanical Explanatory Model 28 Psycho-Social-Cultural Explanatory Model 29 Physiological Aspects of Gestation, Development and Delivery 30 Fetal Neurobehavioral Development 30
OILSW: A New System for Ontology Instance Learning

The Semantic Web is expected to extend the current Web by providing structured content via the addition of annotations. Because of the large amount of pages in the Web, manual annotation is very time consuming. Finding an automatic or semiautomatic method to change the current Web to the Semantic Web is very helpful. In a specific domain, Web pages are the instances of that domain ontology. So we need semiautomatic tools to find these instances and fill their attributes. In this article, we propose a new system named OILSW for instance learning of an ontology from Web pages of Websites in a common domain. This system is the first comprehensive system for automatically populating the ontology for websites. By using this system, any Website in a certain domain can be automatically annotated.
A Measurement-Driven Comparison of Server Bandwidth Controllers for Client-assisted Content Delivery

A key challenge in client-assisted content delivery is determining how to allocate limited server bandwidth across a large number of files being concurrently served so as to optimize global performance and cost objectives. In this paper, we present a comprehensive experimental evaluation of strategies to control server bandwidth allocation. As part of this effort, we introduce a new model-based control approach that relies on an accurate yet concise “cheat sheet” based on a priori offline measurement to predict swarm performance as a function of the server bandwidth and other swarm parameters. Our evaluation using a prototype system, SwarmServer, instantiating static, dynamic, and modelbased controllers shows that static and dynamic controllers can both be suboptimal due to different reasons. In comparison, a model-based approach consistently outperforms both static and dynamic approaches provided it has access to detailed measurements in the regime of interest. Nevertheless, the broad applicability of a model-based approach may be limited in practice because of the overhead of developing and maintaining a comprehensive measurement-based model of swarm performance in each regime of interest.
The Determinants of the Overnight Interest Rate in the Euro Area

The overnight interest rate is the price paid for one day loans and defines the short end of the yield curve. It is the equilibrium outcome of supply and demand for bank reserves. This paper models the intertemporal decision problems in the reserve market for both central and commercial banks. All important institutional features of the euro area reserve market are included. The model is then estimated with euro area data. A permanent change in reserve supply of one billion euro moves the overnight rate by eight basis points into the opposite direction, hence, there is a substantial liquidity effect. Most of the predictable patterns for the mean and the volatility of the overnight rate are related to monetary policy implementation, but also some calendar day effects are present. Banks react sluggishly to new information. Implications for market efficiency, endogeneity of reserve supply and underbidding are studied.
Effects of tetrahydroxystilbene glucoside on mouse liver cytochrome P450 enzyme expressions

Abstract 1. To investigate the effects of tetrahydroxystilbene glucoside (TSG), the main active component of Polygonum multiflorum, on mouse liver cytochrome P450 (Cyp) enzyme protein expressions. Male mice were randomly divided into the control, TSG low (10 mg/kg) and high dose (40 mg/kg) groups. After TSG intragastrical administration for 3, 5 and 7 d, mice were sacrificed and the mouse body and liver weight were detected. The Cyp enzymes and various transcription factors such as AhR, PXR and PPARα protein expressions in mouse livers were measured by Western blotting assay. 2. No significant difference of mouse body and liver weight between the control and TSG treatment groups was detected. Additionally, TSG decreased Cyp1a2 and Cyp2e1 protein expressions after TSG treatment for 3, 5 and 7 d, respectively. Moreover, TSG suppressed Cyp3a11 protein expression after TSG treatment for 5 and 7 d. Furthermore, TSG high dose inhibited AhR and PXR protein expressions after TSG treatment for 5 and 7 d, while both TSG low dose and high dose obviously decreased PPARα protein level from TSG treatment for 3 d. 3. TSG has inhibitory effects on mouse liver Cyp1a2, Cyp2e1 and Cyp3a11 protein expressions through the suppression of AhR, PXR and PPARα activation.
A robust initialization scheme for the Remez exchange algorithm

A well-known least squares optimum approximation method is proposed as an efficient initialization scheme for the Remez exchange algorithm. More specifically, we theoretically demonstrate that the "don't care" least squares optimum solution guarantees, inside the bands of interest, the correct number of alternating in-sign extrema of the error function, thus satisfying one of the two basic conditions that are sufficient for obtaining the L/sub /spl infin// optimum solution. Although convergence of Remez: is theoretically assured, its practical implementations may fail to converge in "difficult" design problems when classical initialization is used. In particular, Matlab's realization of Remez, when initialized with the proposed scheme, exhibits a significantly better overall performance that translates into faster convergence and more robust behavior, especially in difficult design problems.
Reconciling Deep Calibration and Demographic History: Bayesian Inference of Post Glacial Colonization Patterns in Carcinus aestuarii (Nardo, 1847) and C. maenas (Linnaeus, 1758)

A precise inference of past demographic histories including dating of demographic events using Bayesian methods can only be achieved with the use of appropriate molecular rates and evolutionary models. Using a set of 596 mitochondrial cytochrome c oxidase I (COI) sequences of two sister species of European green crabs of the genus Carcinus (C. maenas and C. aestuarii), our study shows how chronologies of past evolutionary events change significantly with the application of revised molecular rates that incorporate biogeographic events for calibration and appropriate demographic priors. A clear signal of demographic expansion was found for both species, dated between 10,000 and 20,000 years ago, which places the expansions events in a time frame following the Last Glacial Maximum (LGM). In the case of C. aestuarii, a population expansion was only inferred for the Adriatic-Ionian, suggestive of a colonization event following the flooding of the Adriatic Sea (18,000 years ago). For C. maenas, the demographic expansion inferred for the continental populations of West and North Europe might result from a northward recolonization from a southern refugium when the ice sheet retreated after the LGM. Collectively, our results highlight the importance of using adequate calibrations and demographic priors in order to avoid considerable overestimates of evolutionary time scales.
The Language ENvironment Analysis (LENA) system: A literature review

The Language ENvironment Analysis (LENA) System is a relatively new recording technology that can be used to investigate typical child language acquisition and populations with language disorders. The purpose of this paper is to familiarize language acquisition researchers and speech-language pathologists with how the LENA System is currently being used in research. The authors outline issues in peer-reviewed research based on the device. Considerations when using the LENA System are discussed.
Proof of plaintext knowledge for code-based public-key encryption revisited

In a recent paper at Asiacrypt'2012, Jain et al point out that Veron code-based identification scheme is not perfect zero-knowledge. In particular, this creates a gap in security arguments of proof of plaintext knowledge (PPK) and verifiable encryption for the McEliece public key encryption (PKE) proposed by Morozov and Takagi at ACISP'2012. We fix the latter result by showing that PPK for the code-based Niederreiter and McEliece PKE's can be constructed using Stern zero-knowledge identification scheme, which is unaffected by the above mentioned problem. Since code-based verifiable encryption uses PPK as a main ingredient, our proposal presents a fix for the McEliece verifiable encryption as well. In addition, we present the Niederreiter verifiable encryption.
New triterpenoids from Morus alba L. stem bark

Two lupeol-type pentacyclic triterpenoids characterised as lup-20(29)-en-3β-ol-27-oic acid (moruslupenoic acid A) and lup-12, 20(29)-dien-3β-ol-26-oic acid (moruslupenoic acid B) and lanst-5, 24-dien-3β-yl acetate (moruslanosteryl acetate) along with the known triterpenoidal phytoconstituents α-amyrin acetate, β-amyrin-β-D-glucopyranoside and betulinic acid have been isolated from the stem bark of Morus alba L. (Moraceae). The structures of the isolated phytoconstituents were established on the basis of spectral data analysis and chemical means.
Visual Comparison of Images Using Multiple Kernel Learning for Ranking

Ranking is the central problem for many applications such as web search, recommendation systems, and visual comparison of images. In this paper, the multiple kernel learning framework is generalized for the learning to rank problem. This approach extends the existing learning to rank algorithms by considering multiple kernel learning and consequently improves their effectiveness. The proposed approach provides the convenience of fusing different features for describing the underlying data. As an application to our approach, the problem of visual image comparison is studied. Several visual features are used for describing the images and multiple kernel learning is adopted to find an optimal feature fusion. Experimental results on three challenging datasets show that our approach outperforms the state-of-the art and is significantly more efficient in runtime.
Volumetric modeling with diffusion surfaces

The modeling of volumetric objects is still a difficult problem. Solid texture synthesis methods enable the design of volumes with homogeneous textures, but global features such as smoothly varying colors seen in vegetables and fruits are difficult to model. In this paper, we propose a representation called diffusion surfaces (DSs) to enable modeling such objects. DSs consist of 3D surfaces with colors defined on both sides, such that the interior colors in the volume are obtained by diffusing colors from nearby surfaces. A straightforward way to compute color diffusion is to solve a volumetric Poisson equation with the colors of the DSs as boundary conditions, but it requires expensive volumetric meshing which is not appropriate for interactive modeling. We therefore propose to interpolate colors only locally at user-defined cross-sections using a modified version of the positive mean value coordinates algorithm to avoid volumetric meshing. DSs are generally applicable to model many different kinds of objects with internal structures. As a case study, we present a simple sketch-based interface for modeling objects with rotational symmetries that can also generate random variations of models. We demonstrate the effectiveness of our approach through various DSs models with simple non-photorealistic rendering techniques enabled by DSs.