Miracle-dz/UniFAR-FTUs huggingface dataset:
Pulmonary Fissure Detection in CT Images Using a Derivative of Stick Filter

Pulmonary fissures are important landmarks for recognition of lung anatomy. In CT images, automatic detection of fissures is complicated by factors like intensity variability, pathological deformation and imaging noise. To circumvent this problem, we propose a derivative of stick (DoS) filter for fissure enhancement and a post-processing pipeline for subsequent segmentation. Considering a typical thin curvilinear shape of fissure profiles inside 2D cross-sections, the DoS filter is presented by first defining nonlinear derivatives along a triple stick kernel in varying directions. Then, to accommodate pathological abnormality and orientational deviation, a max-min cascading and multiple plane integration scheme is adopted to form a shape-tuned likelihood for 3D surface patches discrimination. During the post-processing stage, our main contribution is to isolate the fissure patches from adhering clutters by introducing a branch-point removal algorithm, and a multi-threshold merging framework is employed to compensate for local intensity inhomogeneity. The performance of our method was validated in experiments with two clinical CT data sets including 55 publicly available LOLA11 scans as well as separate left and right lung images from 23 GLUCOLD scans of COPD patients. Compared with manually delineating interlobar boundary references, our method obtained a high segmentation accuracy with median F1-scores of 0.833, 0.885, and 0.856 for the LOLA11, left and right lung images respectively, whereas the corresponding indices for a conventional Wiemker filtering method were 0.687, 0.853, and 0.841. The good performance of our proposed method was also verified by visual inspection and demonstration on abnormal and pathological cases, where typical deformations were robustly detected together with normal fissures.
Peripheral F2‐isoprostanes and F4‐neuroprostanes are not increased in Alzheimer's disease

Quantitative biomarkers of oxidative damage, such as the F2‐isoprostanes (IsoPs) and F4‐neuroprostanes (F4‐NeuroPs), may be useful in assessing progression and response to therapeutics in patients with Alzheimer's disease. F2‐IsoPs and F4‐NeuroPs are reproducibly increased in brain and cerebrospinal fluid of Alzheimer's disease patients; however, results in blood and urine have been conflicting. We tested the hypothesis that F2‐IsoPs and F4‐NeuroPs in plasma or urine quantitatively reflect oxidative damage to the central nervous system. Our results showed that urine levels of F2‐IsoPs or their major metabolite were not significantly different between 56 Alzheimer's disease patients and 34 controls. In addition, urine and cerebrospinal fluid F2‐IsoP levels in 32 Alzheimer's disease patients did not correlate. Supporting these conclusions, elevated rat cerebral F2‐IsoPs and F4‐NeuroPs after systemic exposure to kainic acid were not associated with a significant change in their plasma or urine levels. These results show that plasma and urine F2‐IsoPs and F4‐NeuroPs do not accurately reflect central nervous system levels of these biomarkers and are not reproducibly elevated in body fluids outside of central nervous system in Alzheimer's disease patients. These results should guide the organization of clinical trials now being planned for patients with Alzheimer's disease.
Titan's ionosphere: Model comparisons with Cassini Ta data

On October 26, 2004, during its first encounter with Titan (Ta), the Cassini Orbiter moved from the dayside to the nightside with a closest approach altitude of 1174 km. In situ measurements of the main part of Titan's ionosphere were made by the Langmuir probe on the Cassini Radio and Plasma Wave Experiment (RPWS), while the Ion and Neutral Mass Spectrometer (INMS) measured the main constituents of the neutral atmosphere. The results of model calculations of Titan's ionosphere for Ta encounter conditions (e.g., near the terminator) are presented in this paper. The paper includes comparisons of calculated and measured electron densities along the spacecraft track. Ionization both by solar radiation and by incoming energetic electrons from Saturn's magnetosphere are needed to obtain good agreement between the measured and calculated electron densities.
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes

We derive the optimal approximate posterior over the top-layer weights in a Bayesian neural network for regression, and show that it exhibits strong dependencies on the lower-layer weights. We adapt this result to develop a correlated approximate posterior over the weights at all layers in a Bayesian neural network. We extend this approach to deep Gaussian processes, unifying inference in the two model classes. Our approximate posterior uses learned "global" inducing points, which are defined only at the input layer and propagated through the network to obtain inducing inputs at subsequent layers. By contrast, standard, "local", inducing point methods from the deep Gaussian process literature optimize a separate set of inducing inputs at every layer, and thus do not model correlations across layers. Our method gives state-of-the-art performance for a variational Bayesian method, without data augmentation or tempering, on CIFAR-10 of $86.7\%$.
Influence of Carbon Source on Nitrate Removal by Nitrate-TolerantKlebsiella oxytoca CECT 4460 in Batch and Chemostat Cultures

ABSTRACT The nitrate-tolerant organism Klebsiella oxytoca CECT 4460 tolerates nitrate at concentrations up to 1 M and is used to treat wastewater with high nitrate loads in industrial wastewater treatment plants. We studied the influence of the C source (glycerol or sucrose or both) on the growth rate and the efficiency of nitrate removal under laboratory conditions. With sucrose as the sole C source the maximum specific growth rate was 0.3 h−1, whereas with glycerol it was 0.45 h−1. In batch cultures K. oxytocacells grown on sucrose or glycerol were able to immediately use sucrose as a sole C source, suggesting that sucrose uptake and metabolism were constitutive. In contrast, glycerol uptake occurred preferentially in glycerol-grown cells. Independent of the preculture conditions, when sucrose and glycerol were added simultaneously to batch cultures, the sucrose was used first, and once the supply of sucrose was exhausted, the glycerol was consumed. Utilization of nitrate as an N source occurred without nitrite or ammonium accumulation when glycerol was used, but nitrite accumulated when sucrose was used. In chemostat cultures K. oxytoca CECT 4460 efficiently removed nitrate without accumulation of nitrate or ammonium when sucrose, glycerol, or mixtures of these two C sources were used. The growth yields and the efficiencies of C and N utilization were determined at different growth rates in chemostat cultures. Regardless of the C source, yield carbon (YC) ranged between 1.3 and 1.0 g (dry weight) per g of sucrose C or glycerol C consumed. Regardless of the specific growth rate and the C source, yield nitrogen (YN) ranged from 17.2 to 12.5 g (dry weight) per g of nitrate N consumed. In contrast to batch cultures, in continuous cultures glycerol and sucrose were utilized simultaneously, although the specific rate of sucrose consumption was higher than the specific rate of glycerol consumption. In continuous cultures double-nutrient-limited growth appeared with respect to the C/N ratio of the feed medium and the dilution rate, so that for a C/N ratio between 10 and 30 and a growth rate of 0.1 h−1 the process led to simultaneous and efficient removal of the C and N sources used. At a growth rate of 0.2 h−1the zone of double limitation was between 8 and 11. This suggests that the regimen of double limitation is influenced by the C/N ratio and the growth rate. The results of these experiments were validated by pulse assays.
A Simple Theory of Defensive Patenting

This paper examines innovating firms’ incentives to engage in defensive patenting. It first establishes a “truce equilibrium” in patent enforcement: when litigation is costly, the equal strength of two symmetric parties’ patent portfolios deters any patent disputes along the equilibrium path. This equilibrium behavior generates two benefits of defensive patenting, namely, to prevent licensing outlays and to protect downstream investments. In addition, firms can use patents to coordinate non-contractible investment decisions. Depending on the joint interests, they can either reach a license in order to guarantee high investment incentives, or agree not to grant a license so that investments are deterred by the litigation threat. On the other hand, the strategic patenting concern may generate a bandwagon of patent accumulation, where firms rush to the patent office to get a patent, but the subsequent investment performance is the same as when there is no patent at all. The paper also argues that defensive patenting may weaken the effectiveness of patents as an appropriation scheme. This offers an explanation that the “pro-patent” policy shift in the United States since the 1980s may actually have undermined the incentive power of the patent system.
Statistical Inference in Factor Analysis

In this paper we discuss some methods of factor analysis. The entire discussion is centered around one general probability model. We consider some mathematical problems of the model, such as whether certain kinds of observed data determine the model uniquely. We treat the statistical problems of estimation and tests of certain hypotheses. For these purposes the asymptotic distribution theory of some statistics is treated. The primary aim of this paper is to give a unified exposition of this part of factor analysis from the viewpoint of the mathematical statistician. The literature on factor analysis is scattered; moreover, the many papers and books have been written from many different points of view. By confining ourselves to one model and by emphasizing statistical inferences for this model we hope to present a clear picture to the statistician. The development given here is expected to point up features of model-building and statistical inference that occur in other areas where statistical theories are being developed. For example, nearly all of the problems met in factor analysis are met in latent structure analysis. There are also some new results given in this paper. The proofs of these are mainly given in a technical Part II of the paper. In confining.ourselves to the mathematical and statistical aspects of one model, we are leaving out of consideration many important and interesting topics. We shall not consider how useful this model may be nor in what substantive areas one may expect to find data (and problems) that fit the model. We also do not consider methods based on other models. In doing this, we do not mean to imply that the model considered here is the most useful or important. It seems that this model has some usefulness and importance, it has been studied considerably, and one can give a fairly unified exposition of it. Extensive discussion of the purposes and applications (as well as other developments) of factor analysis is given in books by psychologists (for example, Holzinger and Harmon [10], Thomson [23], Thurstone [24]). Some general discussion of statistical inference has been given in papers by Bartlett [9] and Kendall [12].
Validity and Reliability of the Spanish Version of the Revised Self-Monitoring Scale

Abstract Self-Monitoring (SM) is a concept that refers to individual differences in this orientation toward regulation of social behavior. The goal of the present research was to provide a Spanish adaptation of Snyder and Gangestad’s (1986) Revised SM Scale. After conducting an initial pilot study, results showed that the Spanish version of the scale had good internal reliability and adequate factor structure. In Study 1, analyses support a unidimensional structure of the scale (χ2/df = 2.64; GFI = .97; IFI = .97; TLI = .96; RMSEA = .06). In Study 2, the scale showed discriminant validity from other individual differences measures, such as Need for Cognition (r = 0.12 p = 0.14), Social Desirability (r = 0.06, p > .45) and Extraversion (r = 0.28 p = .001). In Study 3, the scale showed adequate test-retest reliability (r = 0.71, p < .001). Finally, using a paradigm of attitude-behavior consistenty, Study 4 showed that the validated scale also had good predictive validity (B = –0.819, p = .035).
Handbook of spatial point-pattern analysis in ecology

Find loads of the handbook of spatial point pattern analysis in ecology chapman and hall or crc applied environmental statistics book catalogues in this site as the choice of you visiting this page. You can also join to the website book library that will show you numerous books from any types. Literature, science, politics, and many more catalogues are presented to offer you the best book to find. The book that really makes you feels satisfied. Or that's the book that will save you from your job deadline.
A Neural Network Model of Cortical Activity during Reaching

A neural network model that produces many of the directional and spatial response properties that have been observed for cortical neurons in monkeys moving toward targets in space is described. These include motor cortex units with broad tuning in a single preferred direction, approximately linear variation in activity for different hold positions, and approximate invariance in preferred direction for different starting points in space. Association cortex units in the model are sometimes irregular and reminiscent of neurons observed in visually responsive brain areas such as the posterior parietal cortex. The model is also compatible with population analyses performed on motor cortical neurons. Across network units, the distribution of preferred directions is uniformly distributed in directional space, and the degree of tuning and response magnitude vary from unit to unit. A population code used to predict accurately the direction of arm movements from a large population of coarsely tuned individual neurons allows predictions using a simulated population of unit responses obtained from the neural network model. This code works for different starting locations in space using the same parameters.
Appetitive Pavlovian-Instrumental Interactions: Effects of Inter-Stimulus Interval and Baseline Reinforcement Conditions

Experiment I manipulated two variables which appear to influence whether a signal for food enhances or suppresses food-rewarded instrumental performance: interstimulus interval (ISI) during classical conditioning and instrumental reinforcement schedule during testing. In two groups a 10-s conditioned stimulus (CS) and food were paired (10-s and 20- to 100-s ISI), while in a third group they were unpaired. During signalled reinforcement of lever-pressing (S+), the CS suppressed responding in both paired groups. During signalled extinction (S−), responding in the 10-s ISI group was suppressed during the CS and enhanced for 60 s after CS offset; responding in the 20- to 100-s ISI group was enhanced both during the CS and for 120 s after CS offset. Experiment II examined whether the long ISI enhancement effect would occur when the baseline response rate was lowered by satiation rather than extinction. A 20- to 100-s CS and food were paired in one group and unpaired in another. After near-satiation on a CRF schedule, CS presentations caused a reduction in responding in both groups, with no significant difference between the two groups. The results of the two experiments were interpreted in terms of an interaction between the expectancy of food generated by stimuli conditioned at short and long ISIs and the expectancy of food availability controlled by the instrumental schedule.
Towards Microbenchmarking XQuery

A substantial part of the database research field focusses on optimizing XQuery evaluation. However, there is a lack of tools that allows one to easily compare different implementations of isolated language features. This implies that there is no overview of which engines perform best at certain XQuery aspects, which in turn makes it hard to pick a reference platform for an objective comparison. This paper is the first to give an overview of a large subset of the open source XQuery implementations in terms of performance. Several specific XQuery features are tested for each engine on the same hardware to give an impression of the strengths and weaknesses of that implementation. This paper aims at guiding implementors in benchmarking and improving their products.
A design of current-mode analog circuits for fuzzy inference hardware systems

Current-mode analog circuits, i.e., a maximum (MAX) circuit, a minimum (MIN) circuit, and a defuzzified circuit, for fuzzy inference hardware systems, are proposed. The design of the proposed MAX and MIN circuits is based on simple bounded-difference equations. The defuzzifier circuit is synthesized using multipliers/dividers based on the translinear principle. The design considerations and the simulation results of a 2 /spl times/ 2 fuzzy controller using the proposed circuits are described. <<ETX>>
Outwitting the blood-brain barrier for therapeutic purposes: osmotic opening and other means.

OBJECTIVE This article reviews historical aspects of the blood-brain barrier (BBB) and recent advances in mechanisms to deliver therapeutic agents across the BBB for the treatment of intracerebral tumors and other neurological diseases. METHODS The development of the osmotic BBB disruption procedure as a clinically useful technique is described. Osmotic BBB disruption is contrasted with alternative methods for opening or bypassing the BBB, including pharmacological modification of the BBB with bradykinin and direct intracerebral infusion. RESULTS Laboratory studies have played a fundamental role in advancing our understanding of the BBB and delivery of agents to brain. Preclinical animal studies will continue to serve an integral function in our efforts to improve the diagnosis and treatment of a number of neurological disorders. Techniques involving the modification of the BBB and/or blood-tumor barrier to increase delivery of therapeutic agents have been advanced to clinical trials in patients with brain tumors with very favorable results. CONCLUSION Improving delivery of agents to the brain will play a major role in the therapeutic outcome of brain neoplasms. As techniques for gene therapy are advanced, manipulation of the BBB also may be important in the treatment of central nervous system genetic disorders.
By-passing of P-glycoprotein Using Immunoliposomes

The over-expression of MDR1 P-glycoprotein has been associated with the development of multidrug-resistance in cancer cells. Methods used to overcome multidrug-resistance often involve the co-administration of inhibitors of P-glycoprotein. Here, we test the hypothesis that an immunoliposome-based drug delivery system may be used as an alternative approach to overcome multidrug-resistance since immunoliposomes penetrate target cells by receptor-mediated endocytosis which allows to by-pass membrane-associated P-glycoprotein. Targeting of immunoliposomes was achieved by the use of an anti-transferrin receptor monoclonal antibody (OX26 mAb). Incorporation of radiolabelled digoxin within OX26-immunoliposomes enhanced cellular uptake of digoxin by a factor of 25 in immortalised RBE4 rat brain capillary endothelial cells. Uptake of liposomal digoxin was insensitive to ritonavir, a P-glycoprotein inhibitor, and was reduced in presence of increasing free concentrations of OX26 mAb or nocodazole, a reversible inhibitor of endocytosis. In contrast, uptake of free digoxin was enhanced by a factor of 1.8 in presence of ritonavir and was insensitive to OX26 mAb or nocodazole. Cellular uptake and intracellular accumulation of liposomal digoxin (55% internalisation within 30 min) was demonstrated by acid wash of the cells and was confirmed by confocal microscopy studies. Endosomal release to the cytosol of propidium iodide loaded immunoliposomes was shown. These in vitro studies suggest that immunoliposome-based drug delivery systems can be used to by-pass P-glycoprotein and thus deliver drugs to the cytosol of a target cell.
Mammographic densities and risk of breast cancer

To determine the relation of mammographic densities to subsequent breast cancer risk, a case—control study was undertaken using prediagnostic mammograms of screening program participants. Mammograms of cases (n = 266) and controls (n = 301) were blindly assessed for mammographic densities, which were measured by planimetry. The odds of breast cancer increased steadily with increasing breast density (test for trend, P < 0.0001). Breast cancer odds was 1.7 for densities between 5% and 24.9%, 2.5 for 25% through 44.9%, 3.8 for 45% through 64%, and 4.3 for densities of 65% and greater (referent = <5% densities). Odds ratios also increased with increasing densities among women with the P2 and DY mammographic patterns. These findings suggest that the percentage of mammographic densities in the breast can predict breast cancer risk more accurately than a qualitative assessment of mammographic patterns.
IAP guidelines 2006 on hospital based management of severely malnourished children (adapted from the WHO Guidelines).

Malnutrition in children is widely prevalent in India. It is estimated that 57 million children are underweight (moderate and severe). More than 50% of deaths in 0-4 years are associated with malnutrition. The median case fatality rate is approximately 23.5% in severe malnutrition reaching 50% in edematous malnutrition. There is a need for standardized protocol-based management to improve the outcome of severely malnourished children. In 2006 Indian Academy of Pediatrics undertook the task of developing guidelines for the management of severely malnourished children based on adaptation from the WHO guidelines. We summarize below the revised consensus recommendations (and wherever relevant the rationale) of the group. (excerpt)
Influence of crash pulse duration on injury risk in frontal impacts based on real life crashes

To study the influence of crash pulse duration on injury risk, data of 272 real life frontal collisions with recorded crash pulses was used. 371 restrained occupants were included. It was found that compared with acceleration, the duration has a limited influence on injury risk. The study shows that the average pulse duration in cases with AIS2+ injuries was 7 % longer than in cases with AIS1 injuries. The corresponding difference for mean acceleration was 89%. It was found that the injury reduction effect of airbags was not negatively affected in crashes with a long duration. The results show that in the design of a crash-worthy road transport system the design criteria should be based on acceleration, not on change in velocity, because long pulse duration was not found to have a big influence on injury risk. Key words: acceleration, crash recorder, injury risk, injury severity, impact severity
Utilization of terrestrial organic matter by the bivalve Corbicula japonica estimated from stable isotope analysis

Carbon and nitrogen isotopic ratios in tissue of the bivalve corbicula (Corbicula japonica) and particulate organic matter (POM) were measured along a salinity gradient in the Kushida Estuary, Japan. The bivalve exhibited a gradual isotopic enrichment from the uppermost estuarine site (σ13C=−24.8‰ and σ15N=8.6‰) to the marine site (σ13C=−16.1‰ and σ15N=11.8‰). Using the concentration-weighted mixing model, the bivalves’ food source is estimated from the isotope values for the bivalves and POM from terrestrial plants, marine phytoplankton and benthic microalgae. The results indicated that the contributions of benthic micro algae and phytoplankton were small, while terrestrial particulate matter is significantly important for the corbicula diet, although the contribution varies among sampling sites.