Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation of wood microanatomy images using multiscale classification

In this work we study wood in detail to understand better its nature, because of wood has a wide range of applications. There are wood laboratories that study microanatomic properties in samples using a microscope. We propose a method based on digital image processing which seeks to improve the analysis of these properties. In this initial proposal, we show a segmentation of wood microanatomy images for identifying microanatomy structures and to quantify their concentration in a sample. The approach consists on the creation of a scale space based on morphological operations and a clustering technique using the fuzzy c-means algorithm. The multiscale space is created by applying open-close and close-open morphological operations over images. The scale space is based on several shapes. Scales are determined through a granulometric study over the image by using Fourier transform. The segmentation is evaluated by considering images segmented by experts.
ConfocalGN: a minimalistic confocal image simulator

We developed a user-friendly software to generate synthetic confocal microscopy images from a ground truth specified as a 3D bitmap with pixels of arbitrary size. The software can analyze a real confocal stack to derivate noise parameters and will use them directly to generate new images with similar noise characteristics. Such synthetic images can then be used to assert the quality and robustness of an image analysis pipeline, as well as be used to train machine-learning image analysis procedures. We illustrate the approach with closed curves corresponding to the microtubule ring present in blood platelets. Availability and implementation ConfocalGN is written in MATLAB but does not require any toolbox. The source code is distributed under the GPL 3.0 licence on https://github.com/SergeDmi/ConfocalGN.
Predictors of high quality clinical practice guidelines: examples in oncology.

OBJECTIVE Clinical practice guidelines are widely used as effective tools for improving the management of patients with cancer. However, there is increasing concern about variation in guideline quality. In this study we identified predictors for high-quality guidelines in oncology. DESIGN The quality scores for 32 oncology guidelines from 13 countries were determined by four independent appraisers using the Appraisal of Guidelines for Research and Evaluation (AGREE) instrument. MAIN MEASURE : The contribution to the quality score of six characteristics of guidelines and three of guideline developing organizations was then assessed using analysis of variance and stepwise linear regression analysis. RESULTS Some guideline and organizational characteristics were shown to be responsible for a large part of the variations in quality scores. The availability of background information was the strongest predictor of quality with an explained variance ranging from 17% ("Applicability") to 67% ("Rigour of development"). High-quality guidelines were more often produced by government-supported organizations and/or within a structured, coordinated programme. The other characteristics (publication year, type of guideline, format, level of care, and scope) were not independent predictors of quality. CONCLUSIONS Guidelines should provide more explicit information about the context of their development and methods used in order to improve their quality and thus encourage their use in clinical practice.
Detection of KPC Carbapenemase in Pseudomonas aeruginosa Isolated From Clinical Samples Using Modified Hodge Test and Boronic Acid Phenotypic Methods and Their Comparison With the Polymerase Chain Reaction

Background Bacterial resistance to antibiotics has become a major source of concern for public health. Pseudomonas aeruginosa strains are important opportunistic pathogens. These bacteria have a high resistance to a wide range of existing antimicrobials and antibiotics. Objectives The present study was performed to evaluate the frequency of KPC in P. aeruginosa isolated from clinical samples of educational hospitals of Arak University of Medical Sciences, using the mentioned phenotypic and genotypic methods. Materials and Methods One hundred and eight non-duplicate clinical isolates of P. aeruginosa were collected from hospitals of Arak University of Medical Sciences, Arak, Iran. Antibacterial susceptibility was determined by the disk diffusion method. KPC production was confirmed by the Modified Hodge Test (MHT), which is a phenotypic test, and combined-disk test with boronic acid and the Polymerase Chain Reaction (PCR). Results In the present study, 13 isolates (12%) of P. aeruginosa were positive for KPC, using PCR. Comparison of the two phenotypic methods used in this study showed that boronic acid is more sensitive than MHT in identification of KPC-producing strains (84.6% vs. 77%). Conclusions Utilization of reliable methods for identifying carbapenemase-producing strains and determining their antibiotic resistance pattern could have a very important role in treatment of infections caused by these strains. A substantial amount of P. aeruginosa isolated from clinical samples of hospitals in Arak (Iran) produce KPC carbapenemase. Due to their low specificity, MHT and boronic acid phenotypic methods could not completely identify KPC-producing P. aeruginosa. However, the sensitivity of boronic acid phenotypic method in detection of KPC was higher than MHT.
Survival with first-line bosentan in patients with primary pulmonary hypertension

Primary pulmonary hypertension (PPH) is a progressive disease with high mortality. Administration of i.v. epoprostenol has demonstrated improved exercise tolerance, haemodynamics, and survival. The orally active, dual endothelin receptor antagonist bosentan improves exercise endurance, haemodynamics, and functional class over the short term. To determine the effect of first-line bosentan therapy on survival, this study followed 169 patients with PPH treated with bosentan in two placebo-controlled trials and their extensions. Data on survival and alternative treatments were collected from September 1999 (start of the first placebo-controlled study) to December 31, 2002. Observed survival up to 36 months was reported as Kaplan-Meier estimates and compared with predicted survival as determined for each patient by the National Institutes of Health Registry formula. Kaplan-Meier survival estimates were 96% at 12 months and 89% at 24 months. In contrast, predicted survival was 69% and 57%, respectively. In addition, at the end of 12 and 24 months, 85% and 70% of patients, respectively, remained alive and on bosentan monotherapy. Factors that predicted a worse outcome included World Health Organization Functional Class IV and 6-min walk distance below the median (358 m) at baseline. First-line bosentan therapy was found to improve survival in patients with advanced primary pulmonary hypertension.
Implementing dynamic chaining of Virtual Network Functions in OpenStack platform

Network Function Virtualization (NFV) is gaining a lot of interest as a flexible and cost-effective solution for replacing hardware-based, vendor-dependent middle-boxes with software-based appliances running in a cloud-like network environment. The NFV paradigm is then fundamental to bring the required programmatic capabilities to 5G transport networks. This paper discusses the practical issues of implementing dynamic chaining of virtual network functions running as virtual machines in the industry-standard OpenStack cloud platform. In particular, the focus is on the complexity of the underlying virtual network infrastructure and the design principles of a suitable SDN controller.
Molecular Genetics of the RNA Polymerase II General Transcriptional Machinery

SUMMARY Transcription initiation by RNA polymerase II (RNA pol II) requires interaction between cis-acting promoter elements and trans-acting factors. The eukaryotic promoter consists of core elements, which include the TATA box and other DNA sequences that define transcription start sites, and regulatory elements, which either enhance or repress transcription in a gene-specific manner. The core promoter is the site for assembly of the transcription preinitiation complex, which includes RNA pol II and the general transcription fctors TBP, TFIIB, TFIIE, TFIIF, and TFIIH. Regulatory elements bind gene-specific factors, which affect the rate of transcription by interacting, either directly or indirectly, with components of the general transcriptional machinery. A third class of transcription factors, termed coactivators, is not required for basal transcription in vitro but often mediates activation by a broad spectrum of activators. Accordingly, coactivators are neither gene-specific nor general transcription factors, although gene-specific coactivators have been described in metazoan systems. Transcriptional repressors include both gene-specific and general factors. Similar to coactivators, general transcriptional repressors affect the expression of a broad spectrum of genes yet do not repress all genes. General repressors either act through the core transcriptional machinery or are histone related and presumably affect chromatin function. This review focuses on the global effectors of RNA polymerase II transcription in yeast, including the general transcription factors, the coactivators, and the general repressors. Emphasis is placed on the role that yeast genetics has played in identifying these factors and their associated functions.
Experimental Study of Load Balancing Routing for Improving Lifetime in Sensor Networks

Organizing Wireless Sensor Networks (WSNs) using energy efficient routing tree enables the efficient utilization of the limited energy resources of the deployed sensor nodes. However, the problem of unbalanced energy consumption and the unbalanced workload exists, and it is tightly bound to the role and to the location of a particular node in the network. This paper presents a detailed performance study of a novel load-balancing routing algorithm using a real-world WSN platform. In this routing algorithm, the parent selection process depends on three factors; two potential factors: the residual power in the intermediate sensor node and the channel state; and the hop count as a third tier-break factor. In WSNs, the significant resource constraints of the sensor nodes combined with the irregularity of a many-to-one traffic pattern have encouraged the development of an energy efficient load-balancing wireless routing algorithm. Since the communications overheads are the major energy consumer during a sensor node's operation, the algorithm demonstrates minimal overheads in low power multi-hop communications.
Computationally-Enhanced Construction Kits for Children: Prototype and Principles

Construction kits—toys designed for the building or assembly of physical models—often play an important educational role in children's lives. While such kits have tremendous strengths (e.g., they permit children to build three-dimensional models and to learn through tactile experience), they also have interesting limitations. Traditional construction kits offer little in the way of direct communication with their users—for example, a traditional kit cannot offer a student information or advice about how to proceed in building a model. More generally, traditional constructions—i.e., the models produced—tend to be aesthetically and behaviorally limited. This paper argues that through the use of embedded computation, pieces within a construction kit may communicate with each other, with desktop machines, and with their users; and overall, by integrating construction kits with computation, the educational power and expressiveness of these kits can be greatly increased. As an example of many of the ideas presented here, we describe a prototype of a computationally-enhanced construction kit: a set of speech-enabled alphabet blocks. We conclude by discussing a variety of related research efforts and directions for future work.
Superoptimization in LLVM

Superoptimization is a known technique to integrate the analyses and transformations of a number of separate optimizations in order to obtain an optimization that is more expressive than the sequential and iterative application of the original optimizations. This paper describes the elaboration of this technique within the Low Level Virtual Machine (LLVM) Compiler Infrastructure. A framework supporting the integration of modular optimizations into superoptimization is presented. Some LLVM-specific implementation considerations are also discussed. Finally, a brief introduction to the use of the framework is provided.
Short survey Feet first: object exploration in young infants

In this study, infants reached for toys with their feet weeks before using their hands. These results suggest that, contrary to long-held beliefs, early leg movements can be precisely controlled, the development of skilled reaching need not involve lengthy practice, and that early motor behaviors need not develop in a strict cephalocaudal pattern. © 2004 Elsevier Inc. All rights reserved.
Multimodal Approaches for Regenerative Stroke Therapies: Combination of Granulocyte Colony-Stimulating Factor with Bone Marrow Mesenchymal Stem Cells is Not Superior to G-CSF Alone

Attractive therapeutic strategies to enhance post-stroke recovery of aged brains include methods of cellular therapy that can enhance the endogenous restorative mechanisms of the injured brain. Since stroke afflicts mostly the elderly, it is highly desirable to test the efficacy of cell therapy in the microenvironment of aged brains that is generally refractory to regeneration. In particular, stem cells from the bone marrow allow an autologous transplantation approach that can be translated in the near future to the clinical practice. Such a bone marrow-derived therapy includes the grafting of stem cells as well as the delayed induction of endogenous stem cell mobilization and homing by the stem cell mobilizer granulocyte colony-stimulating factor (G-CSF). We tested the hypothesis that grafting of bone marrow-derived pre-differentiated mesenchymal cells (BM-MSCs) in G-CSF-treated animals improves the long-term functional outcome in aged rodents. To this end, G-CSF alone (50 μg/kg) or in combination with a single dose (106 cells) of rat BM MSCs was administered intravenously to Sprague-Dawley rats at 6 h after transient occlusion (90 min) of the middle cerebral artery. Infarct volume was measured by magnetic resonance imaging at 3 and 48 days post-stroke and additionally by immunhistochemistry at day 56. Functional recovery was tested during the entire post-stroke survival period of 56 days. Daily treatment for post-stroke aged rats with G-CSF led to a robust and consistent improvement of neurological function after 28 days. The combination therapy also led to robust angiogenesis in the formerly infarct core and beyond in the “islet of regeneration. ” However, G-CSF + BM MSCs may not impact at all on the spatial reference-memory task or infarct volume and therefore did not further improve the post-stroke recovery. We suggest that in a real clinical practice involving older post-stroke patients, successful regenerative therapies would have to be carried out for a much longer time.
Percepção sobre queda como fator determinante desse evento entre idosos residentes na comunidade

factors to that, including intrinsic and extrinsic risk factors, as well as the awareness about falls, assessed by the Falls Risk Awareness Questionnaire (FRAQ-Brazil). METHOD: It consisted of a quantitative, transversal, and descriptive study, performed with 472 elderly persons through interview. Data were analyzed by the chi-squared test with a confidence interval of 95%. RESULTS: The average age of the sample was 70.6 years and most of them were female. Among the sample, 55.2% referred previous episodes of fall. The majority of them self-reported having diseases associated with gait disturbance and used medicines that could cause falls. It was observed less falls among elderly with higher level of awareness about risk factors. CONCLUSION: A high prevalence of accidental falls and exposure of the elderly persons to several independent and concomitant risk factors were observed. Greater awareness level about falls seems to be a preventive factor, presenting a higher association with falls than level of education and income.
Quantifying The Incidence of Novice Programmers ’ Errors

Existing research shows that students learning to program for the first time often make the same types of errors. Tools have been written to give students useful feedback when they make these errors, but no research has been done to determine the effectiveness of these tools. This paper is the preliminary result of a long-term study to answer the research question: will timely reporting of novice programming errors in an understandable format reduce the incidence of these errors? We report on a tool called Arjen which is designed to quantify the errors made by novice programmers. We give the results of a pilot study where first programming students used Arjen as part of their learning environment.
A New Web Text Clustering Algorithm Based on DFSSM

A new algorithm of Web text clustering mining is presented, which is based on the Discovery Feature Sub-space Model (DFSSM). This algorithm includes the training stage of SOM and the clustering stage, which characterizes self-stability and powerful antinoise ability. It can distinguishes the most meaningful features from the Concept Space without the evaluation function. we have applied the algorithm to the modern long-distance education. Through the analysis of the experimental results, it is obvious that this algorithm can effective help users to get valuable information from WWW quickly.
A key management scheme for dividing/merging cluster based wireless sensor networks

Wireless sensor networks are one of the pioneer technologies of the new century. The low cost of these networks makes them applicable to a variety of areas from battlefields and environment monitoring to health and house applications. A sensor network is composed of a large number of low cost sensor nodes densely deployed for a specific application inside a usually small environment. Due to its dynamic nature, it might be necessary to change the objective of the network or enhance its total configuration with adding or deleting some nodes after any deployment. Dividing a sensor network into two or merging two networks is examples of these modifications. The aim of this paper is to consider these modifications in a cluster based sensor network. In this paper, we propose two methods, one for dividing a network into two independent networks and the other for merging two independent ones into a whole network. In order to divide a network, we assign a new command node for the network and transfer the information of keys, gateways and nodes to be used for a series of messages exchanged between these elements. Then, the new command node is responsible for a portion of the first network, which is in fact a separate network. Also for merging two networks, we transfer the data base of command node of one network into another and eliminate the said command node and inform its gateways of the existence of a new manager. Simulation results show the applicability of the proposed method. We simulate the network division and combination for different number of gateways transferred or added to a cluster based sensor network consisting of sensor nodes and gateways.
CTO: concept tree based semantic overlay for pure peer-to-peer information retrieval

Inspired by how search behavior works in human society, we propose CTO, a self-organized semantic overlay based on concept tree for P2P IR infrastructure, which is efficient for full text search in pure P2P environment without any central control or powerful peer as hub node. Especially, CTO performs very well on searching the unpopular resources shared by a few peers. In our experiment, while searching for the scarce documents shared by the peers, CTO achieves about 80% recall rate when the search covers less than 5% peers in the overlay. The search latency of CTO is also very low, which is controlled in the range about 5~12 hops.
Modelling the McGurk effect

The current study investigates the McGurk effect by modelling it with neural networks. The simulations are designed to test the two main theories about the moment at which the auditory-visual integration happens. To further analyze the causes behind the McGurk illusion, the neural network that best models the effect is used to simulate the influence of language and the frequency of phonemes on auditory-visual speech perception, using two phonetic distribution from English and Japanese, with different empirical results in the McGurk effect.
Psychiatric Disorder in Detained Male Adolescents as Risk Factor for Serious Recidivism

Objective: A growing body of research consistently shows that detained minors bear substantial mental health needs. However, the relation between mental disorder and criminal recidivism has largely remained unexplored. Our study examines whether psychiatric disorders increase the likelihood of recidivism after controlling for time at risk, criminal history, and the presence of other disorders. Method: Participants (n = 232) were detained male adolescents from all 3 youth detention centres in Flanders, Belgium, who were interviewed with the Diagnostic Interview Schedule for Children, Version IV. Two to 4 years later, information on serious recidivism was retrieved from the official judicial registration system. Serious recidivism was defined as having at least one arrest charge for violent, severe property crime, or substance-related offences. Results: Serious recidivism was high, with 81% (n = 191) of the participants being rearrested. Psychiatric disorders predicted neither serious recidivism in general nor violent and severe property recidivism. However, other drug use disorder (OR 2.41; 95% CI 1.22 to 4.75) and general comorbidity (OR 2.64; 95% CI 1.40 to 4.99) were significantly predictive of substance-related recidivism. Conclusion: Common psychiatric disorders in detained male adolescents do not significantly increase the likelihood of subsequent arrests, with the exception that substance use disorders appear to increase the risk of later substance-related recidivism. Effective treatment of these disorders may prevent detained juveniles to experience the detrimental outcomes associated with substance-related crimes as adults (for example, mental illness).
Palmprint Recognition Using Directional Representation and Compresses Sensing

In this study, based on directional representation for palmprint images and compressed sensing, we propose a novel approach for palmprint recognition. Firstly, the directional representation for appearance based approaches is obtained by the anisotropy filter to efficiently capture the main palmprint image characters. Compared with the traditional Gabor representations, the new representations is robust to drastic illumination changes and preserves important discriminative information for classification. Then, in order to improve the robustness of palmprint identification, the compressed sensing is used to distinguish different palms from different hands. As a result, the palmprint recognition performance of representative appearance based approaches can be improved. Experimental results on the PolyU palprint database show that the proposed algorithm has better performance and with good robustness.