Miracle-dz/UniFAR-FTUs huggingface dataset:
Larval settlement and metamorphosis of the mussel Mytilus coruscus in response to monospecific bacterial biofilms

The effects of bacterial biofilms (BFs) on larval settlement and metamorphosis of the mussel, Mytilus coruscus, were investigated in the laboratory. Of nine different isolates, Shewanella sp.1 BF induced the highest percentage of larval settlement and metamorphosis, whereas seven other isolates had a moderate inducing activity and one isolate, Pseudoalteromonas sp. 4, had a no inducing activity. The inducing activity of individual bacterial isolates was not correlated either with their phylogenetic relationship or with the surfaces from which they were isolated. Among the eight bacterial species that demonstrated inducing activity, bacterial density was significantly correlated with the inducing activity for each strain, with the exception of Vibrio sp. 1. The Shewanella sp. 1 BF cue that was responsible for inducing larval settlement and metamorphosis was further investigated. Treatment of the BFs with formalin, antibiotics, ultraviolet irradiation, heat, and ethanol resulted in a significant decrease in their inducing activities and cell survival. BF-conditioned water (CW) did not induce larval metamorphosis, but it triggered larval settlement behavior. A synergistic effect of CW with formalin-fixed Shewanella sp. 1 BF significantly promoted larval metamorphosis. Thus, a cocktail of chemical cues derived from bacteria may be necessary to stimulate larval settlement and metamorphosis in this species.
Expertise and perceptual-cognitive performance in soccer: a review Perícia e rendimento perceptivo-cognitivo no futebol: uma revisão da literatura

This review characterizes the importance of game intelligence between soccer players of different competition levels and according to a specific positional field status. However, research evidence on this topic is inconclusive and in some reports the importance of the perceptual-cognitive skills in the anticipation and decision-making performance remains unclear. Our intention is merely informative and indicative of the surrounding literature on the sport expertise, with the particular interest on the perceptual-cognitive performance, than depreciate some researches or taking part of some currents. Obviously that the variance in performance between soccer teams or players is depending of a several factors, like as anthropometric and physiological profiles, but one of the main factor that we want to include in the sport context is the perceptual-cognitive skills, such as visual search behaviour and the knowledge of situational probabilities. The aims of the present article are: (i) to define and to contextualize the different terminology used in this specific domain; (ii) to typify the different perceptual-cognitive skills that seems to bring on soccer players’ performance; and (iii) to provide some future research guidelines. Key-words: expertise, perceptual-cognitive skills, soccer RESUMO Esta revisao caracteriza a importância da inteligencia de jogo entre futebolistas de diferentes niveis competitivos e de acordo com as suas posicoes especificas em campo. No entanto, evidencias cientificas nesta area nao sao de todo conclusivas e em alguns estudos que atribuem importância as habilidades perceptivo-cognitivas no rendimento das accoes de antecipacao e de tomadas de decisao sao algo dispares. A nossa intencao e meramente informativa e indicativa da literatura em volta da excelencia desportiva, com particular interesse para o rendimento perceptivo-cognitivo, do que depreciar algumas investigacoes ou tomar partido por alguma corrente investigacional. Obviamente que a variabilidade do rendimento desportivo tanto entre equipas de Futebol como entre futebolistas e dependente de inumeros factores, como os perfis antropometricos e fisiologicos dos atletas, mas um dos mais importantes factores que intencionamos incluir no contexto desportivo sao as habilidades perceptivo-cognitivas, tais como o comportamento da procura visual e o conhecimento das probabilidades situacionais. Os objectivos do presente artigo sao: (i) definir e contextualizar a diferente terminologia utilizada neste contexto especifico; (ii) tipificar as diferentes habilidades perceptivo-cognitivas que parecem emergir no rendimento desportivo dos futebolistas; e (iii) fornecer algumas orientacoes para futuras investigacoes. Palavras-chave: excelencia, habilidades perceptivo-cognitivas, futebol 4. revista:miolo 8/6/09 12:13 Page 115
Capacity Planning with the Statistical Prediction of on-off Flows

A novel approach to describe the relation, in terms of probability, between the gain obtained by multiplexing the traffics in the packet network and the link capacity for guaranteeing the required quality is proposed. A traffic-flow is defined as the on-off stream described with the probability distribution of the on-off lengths. With the statistical on-off flow description, the loads on a link after aggregating traffic flows can be predicted in terms of probability, and the link capacity design based on the probability of supporting the required quality becomes possible. To have statistical model of a flow with small number of data, an interpolation method is suggested. To find a congestion point with given link capacity and traffic flows, a calculation method to estimate the expected link reservation with traffic flows and the congestion probability is proposed
Understanding the complexity of 3G UMTS network performance

With rapid growth in smart phones and mobile data, effectively managing cellular data networks is important in meeting user performance expectations. However, the scale, complexity and dynamics of a large 3G cellular network make it a challenging task to understand the diverse factors that affect its performance. In this paper we study the RNC (Radio Network Controller)-level performance in one of the largest cellular network carriers in US. Using large amount of datasets collected from various sources across the network and over time, we investigate the key factors that influence the network performance in terms of the round-trip times and loss rates (averaged over an hourly time scale). We start by performing the “first-order” property analysis to analyze the correlation and impact of each factor on the network performance. We then apply RuleFit - a powerful supervised machine learning tool that combines linear regression and decision trees - to develop models and analyze the relative importance of various factors in estimating and predicting the network performance. Our analysis culminates with the detection and diagnosis of both “transient” and “persistent” performance anomalies, with discussion on the complex interactions and differing effects of the various factors that may influence the 3G UMTS (Universal Mobile Telecommunications System) network performance.
Expression of an estrogen receptor agonist in differentiating osteoblast cultures

Osteoblasts respond in direct and indirect ways to estrogens, and age-dependent changes in hormone levels and bone health can be limited by focused hormone replacement therapy. In this study, we report the release and isolation of an estrogen receptor agonist from osteoblast cultures. This entity reprises many aspects of estradiol activity in isolated osteoblasts, but differs from authentic estradiol by several biochemical and physical criteria. At levels that occur in conditioned medium from differentiating osteoblast cultures, the agonist directly drives gene expression through estrogen-sensitive response elements, activates the obligate osteoblast transcription factor Runx2, and potently enhances Smad-dependent gene expression in response to TGF-β, but exhibits relatively lesser suppressive effects on gene expression through C/EBP and AP-1-binding protein transcription factors. Estrogen receptor agonist activity is resistant to heating at 100°C and separable from the bulk of the remaining alcohol- and hexane-soluble molecules by C18 chromatography. MS and molecular fragmentation analyses predict a Mr of 415.2 to 437.2. Therefore, in addition to earlier studies showing that osteoblasts readily respond to and metabolize various sex steroid-like substrates, we find that they also generate a potent estrogen receptor agonist during differentiation in vitro. Changes in the availability of a molecule like this within bone may relate to differences in skeletal integrity with aging or metabolic disease.
Truthful unsplittable flow for large capacity networks

The unsplittable flow problem is one of the most extensively studied optimization problems in the field of networking. An instance of it consists of an edge capacitated graph and a set of connection requests, each of which is associated with source and target vertices, a demand, and a value. The objective is to route a maximum value subset of requests subject to the edge capacities. It is a well known fact that as the capacities of the edges are larger with respect to the maximal demand among the requests, the problem can be approximated better. In particular, it is known that for sufficiently large capacities, the integrality gap of the corresponding integer linear program becomes 1+ε, which can be matched by an algorithm that utilizes the randomized rounding technique. In this paper, we focus our attention on the large capacities unsplittable flow problem in a game theoretic setting. In this setting, there are selfish agents, which control some of the requests characteristics, and may be dishonest about them. It is worth noting that in game theoretic settings many standard techniques, such as randomized rounding, violate certain monotonicity properties, which are imperative for truthfulness, and therefore cannot be employed. In light of this state of affairs, we design a monotone deterministic algorithm, which is based on a primal-dual machinery, which attains an approximation ratio of ε<over>ε-1, up to a disparity of ε away. This implies an improvement on the current best truthful mechanism, as well as an improvement on the current best combinatorial algorithm for the problem under consideration. Surprisingly, we demonstrate that any algorithm in the family of reasonable iterative path minimizing algorithms, cannot yield a better approximation ratio. Consequently, it follows that in order to achieve a monotone PTAS, if exists, one would have to exert different techniques. We also consider the large capacities single-minded multi-unit combinatorial auction problem. This problem is closely related to the unsplittable flow problem since one can formulate it as a special case of the integer linear program of the unsplittable flow problem. Accordingly, we obtain a comparable performance guarantee by refining the algorithm suggested for the unsplittable flow problem.
Theoretical basis of the amplitude source location method for volcano‐seismic signals

The source location method using high‐frequency seismic amplitudes based on the assumption of isotropic radiation of S waves has been used successfully to locate seismic events and tremor at volcanoes. This amplitude source location (ASL) method overcomes the limitations of traditional hypocenter determination methods that use onset arrival times and has great potential to improve volcano‐seismic monitoring and the investigation of source processes of volcano‐seismic signals. However, theoretical justification of the basic assumption used in the ASL method has not been provided in previous studies. In this study, we tested the ASL method by using seismic waveforms simulated with a finite difference method in realistic heterogeneous volcanic structures with intrinsic attenuation and topography. Our results showed that ASL determinations were successful when using waveforms characterized by multiple scattering that can be approximated by the diffusion model. We found that the energy solution of the diffusion model provided an amplitude‐distance relation that is similar to that used in the ASL method. Our results suggest that the ASL method is applicable to high‐frequency seismograms in highly heterogeneous media with transport mean free paths of 103 m or smaller and strong intrinsic attenuation. These medium parameters are consistent with those estimated at various volcanoes. Our study validates the basic assumption of the ASL method and justifies its use to locate the sources of high‐frequency seismic signals observed at volcanoes.
Lumbar radiculopathy after spinal fusion for scoliosis

In 184 patients with no preoperative neurologic deficit who underwent operation for idiopathic scoliosis, somatosensory evoked potential monitoring was used. Four patients had neurologic deficits postoperatively. Two patients developed mild signs of intraspinal lesions involving upper motor neurons at high lumbar levels that resolved over 3–5 months. These patients and two others developed evidence of unilateral, moderate, lower motor neuron damage that was confirmed on electromyography. No changes in somatosensory evoked potentials occurred in these patients. Lumbar root damage may be difficult to recognize after operation and should be considered in patients with neurologic deficit after scoliosis surgery.
A demand based algorithm for rapid updating of replicas

In many Internet scale replicated system, not all replicas can be dealt with in the same way, since some will be in greater demand than others. In the case of weak consistency algorithms, we have observed that updating first replicas having most demand, a greater number of clients would gain access to updated content in a shorter period of time. In this work we have investigated the benefits that can be obtained by prioritizing replicas with greater demand, and considerable improvements have been achieved. In zones of higher demand, the consistent state is reached up to six times quicker than with a normal weak consistency algorithm, without incurring the additional costs of the strong consistency.
Expression of the Agrobacterium rhizogenes rolC Gene in a Deciduous Forest Tree Alters Growth and Development and Leads to Stem Fasciation

We have altered the growth and development of a deciduous forest tree by transforming hybrid aspen (Populus tremula x Populus tremuloides) with the Agrobacterium rhizogenes rolC gene expressed under the strong cauliflower mosaic virus 35S promoter. We demonstrate that the genetically manipulated perennial plants, after a period of dormancy, maintain the induced phenotypical changes during the second growing period. Furthermore, mass-spectrometrical quantifications of the free and conjugated forms of indole-3-acetic acid and cytokinins and several gibberellins on one transgenic line correlate the induced developmental alterations such as stem fasciation to changes in plant hormone metabolism. We also show that the presence of the RolC protein increases the levels of the free cytokinins, but not by a process involving hydrolysis of the inactive cytokinin conjugates.
Folic acid to reduce neonatal mortality from neural tube disorders

Background Neural tube defects (NTDs) remain an important, preventable cause of mortality and morbidity. High-income countries have reported large reductions in NTDs associated with folic acid supplementation or fortification. The burden of NTDs in low-income countries and the effectiveness of folic acid fortification/supplementation are unclear. Objective To review the evidence for, and estimate the effect of, folic acid fortification/supplementation on neonatal mortality due to NTDs, especially in low-income countries. Methods We conducted systematic reviews, abstracted data meeting inclusion criteria and evaluated evidence quality using adapted Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. Where appropriate, meta-analyses were performed. Results Meta-analysis of three randomized controlled trials (RCTs) of folic acid supplementation for women with a previous pregnancy with NTD indicates a 70% [95% confidence interval (CI): 35–86] reduction in recurrence (secondary prevention). For NTD primary prevention through folic acid supplementation, combining one RCT with three cohort studies which adjusted for confounding, suggested a reduction of 62% (95% CI: 49–71). A meta-analysis of eight population-based observational studies examining folic acid food fortification gave an estimated reduction in NTD incidence of 46% (95% CI: 37–54). In low-income countries an estimated 29% of neonatal deaths related to visible congenital abnormalities are attributed to NTD. Assuming that fortification reduces the incidence of NTDs, but does not alter severity or case-fatality rates, we estimate that folic acid fortification could prevent 13% of neonatal deaths currently attributed to congenital abnormalities in low-income countries. Discussion Scale-up of periconceptional supplementation programmes is challenging. Our final effect estimate was therefore based on folic acid fortification data. If folic acid food fortification achieved 100% population coverage the number of NTDs in low-income countries could be approximately halved. Conclusion The evidence supports both folic acid supplementation and fortification as effective in reducing neonatal mortality from NTDs.
Systematic Review and Evidence-Based Clinical Recommendations for Dosing of Pediatric Supported Standing Programs

Purpose: There is a lack of evidence-based recommendations for effective dosing of pediatric supported standing programs, despite widespread clinical use. Methods: Using the International Classification of Functioning, Disability, and Health (Child and Youth Version) framework, we searched 7 databases, using specific search terms. Results: Thirty of 687 studies located met our inclusion criteria. Strength of the evidence was evaluated by well-known tools, and to assist with clinical decision-making, clinical recommendations based on the existing evidence and the authors’ opinions were provided. Conclusions and recommendations for clinical practice: Standing programs 5 days per week positively affect bone mineral density (60 to 90 min/d); hip stability (60 min/d in 30° to 60° of total bilateral hip abduction); range of motion of hip, knee, and ankle (45 to 60 min/d); and spasticity (30 to 45 min/d).
Confusion-Matrix-Based Kernel Logistic Regression for Imbalanced Data Classification

There have been many attempts to classify imbalanced data, since this classification is critical in a wide variety of applications related to the detection of anomalies, failures, and risks. Many conventional methods, which can be categorized into sampling, cost-sensitive, or ensemble, include heuristic and task dependent processes. In order to achieve a better classification performance by formulation without heuristics and task dependence, we propose confusion-matrix-based kernel logistic regression (CM-KLOGR). Its objective function is the harmonic mean of various evaluation criteria derived from a confusion matrix, such criteria as sensitivity, positive predictive value, and others for negatives. This objective function and its optimization are consistently formulated on the framework of KLOGR, based on minimum classification error and generalized probabilistic descent (MCE/GPD) learning. Due to the merits of the harmonic mean, KLOGR, and MCE/GPD, CM-KLOGR improves the multifaceted performances in a well-balanced way. This paper presents the formulation of CM-KLOGR and its effectiveness through experiments that comparatively evaluated CM-KLOGR using benchmark imbalanced datasets.
Statistical assessment and neural network modeling of stream water quality observations of Green River watershed, KY, USA

The measurement and statistical modeling of water quality data are essential to developing a region-based stream-wise database that would be of great use to the EPA's needs. Such a database would also be useful in bio-assessment and in the modeling of processes that are related to riparian vegetation surrounding a water body such as a stream network. With the help of easily measurable data, it would be easier to come up with database-intensive numerical and computer models that explain the stream water quality distribution and biological integrity and predict stream water quality patterns. Statistical assessments of nutrients, stream water metallic and non-metallic pollutants, organic matter, and biological species data are needed to accurately describe the pollutant effects, to quantify health hazards, and in the modeling of water quality and its risk assessment. The study details the results of statistical nonlinear regression and artificial neural network models for Upper Green River watershed, Kentucky, USA. The neural network models predicted the stream water quality parameters with more accuracy than the nonlinear regression models in both training and testing phases. For example, neural network models of pH, conductivity, salinity, total dissolved solids, and dissolved oxygen gave an R2 coefficient close to 1.0 in the testing phase, while the nonlinear regression models resulted in less than 0.6. For other parameters also, neural networks showed better generalization compared with nonlinear regression models.
Assessing the Effects of Climate Change and Fuel Treatments on Forest Dynamics and Wildfire in Dry Mixed-Conifer Forests of the Inland West: Linking Landscape and Social Perspectives

This Dissertation is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. For more information, please contact pdxscholar@pdx.edu. Recommended Citation Cassell, Brooke Alyce, "Assessing the Effects of Climate Change and Fuel Treatments on Forest Dynamics and Wildfire in Dry MixedConifer Forests of the Inland West: Linking Landscape and Social Perspectives" (2018). Dissertations and Theses. Paper 4226.
Combined denoising and demosaicing of CFA images

Color Filter Arrays (CFA) used by single sensor cameras captures single color information at each pixel location. The process of estimating the missing color samples to reconstruct a full color image is called color filter array interpolation or demosaicing. Demosaicing the CFA images without denoising leads to demosaicing artifacts that will reduce the perceptual quality of the image. This paper presents a denoising before demosaicing strategy for denoising of CFA images captured by single sensor cameras. The images captured by the camera using the Bayer pattern are first denoised by Principal Component Analysis and followed by multiscale gradient based demosaicing to preserve the edges and details. The demosaicing strategy is followed by a false color suppression method to remove the residual demosaicing artifacts.
Exploitation of OpenFlow in wireless sensor networks

A novel idea presented in this paper is to exploit the OpenFlow technology to address reliability, which is one of the most important factors in sensor networks. The proposed approach unified with flow-sensor and communication with controller. Hardware to programmable hardware, operating system to network operating system, vendor to owner specific, previous hardware defined networking (device monitoring, traffic controlling, and topology definition) turns to be software defined and where everything leads to a programmable and customized networking system. OpenFlow bears the characteristics to control the flow-sensor and monitor sensor traffic flow that also addresses another two important problems robust routing and load balancing. Flow-sensor displayed much better performances in comparison to typical sensors through generating less number of packets with lower simulation time in ideal scenario and even better results are possible for larger networks.