Statistical methods for river runoff prediction

Methods used to analyze one type of nonstationary stochastic processes?the periodically correlated process?are considered. Two methods of one-step-forward prediction of periodically correlated time series are examined. One-step-forward predictions made in accordance with an autoregression model and a model of an artificial neural network with one latent neuron layer and with an adaptation mechanism of network parameters in a moving time window were compared in terms of efficiency. The comparison showed that, in the case of prediction for one time step for time series of mean monthly water discharge, the simpler autoregression model is more efficient.

Methods for assessment of pre-harvest sprouting in wheat cultivars

The objective of this work was to test methods for pre-harvest sprouting assessment in wheat cultivars. Fourteen wheat cultivars were grown in Londrina and Ponta Grossa municipalities, Paraná state, Brazil. They were sampled at 10 and 17 days after physiological maturity and evaluated using the methods of germination by rainfall simulation (in a greenhouse), in-ear grain sprouting, and grains removed from the ears. The in-ear grain sprouting method allowed the differentiation of cultivars, but showed different resistance levels from the available description of cultivars. The sprouting of grain removed from the ears did not allow a reliable distinction of data on germination in any harvest date or location. The method of rainfall simulation is the most suitable for the assessment of cultivars as to pre-harvest sprouting, regardless of the sampling date and evaluated location.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Subclinical coronary and aortic atherosclerosis detected by magnetic resonance imaging in type 1 diabetes with and without diabetic nephropathy.

BACKGROUND: Patients with type 1 diabetes and nephropathy maintain an excess cardiovascular mortality compared with diabetic patients with normoalbuminuria. We sought to evaluate coronary and aortic atherosclerosis in a cohort of asymptomatic type 1 diabetic patients with and without diabetic nephropathy using cardiovascular magnetic resonance imaging. METHODS AND RESULTS: In a cross-sectional study, 136 subjects with long-standing type 1 diabetes without symptoms or history of cardiovascular disease, including 63 patients (46%) with nephropathy and 73 patients with normoalbuminuria, underwent cardiovascular magnetic resonance imaging. All subjects underwent cardiac exercise testing and noninvasive tests for peripheral artery disease and autonomic neuropathy. Coronary artery stenoses were identified in 10% of subjects with nephropathy (versus 0% with normoalbuminuria; P=0.007). Coronary plaque burden, expressed as right coronary artery mean wall thickness (1.7+/-0.3 versus 1.3+/-0.2 mm; P<0.001) and maximum right coronary artery wall thickness (2.2+/-0.5 versus 1.6+/-0.3 mm; P<0.001), was greater in subjects with nephropathy. The prevalence of thoracic (3% versus 0%; P=0.28) and abdominal aortic plaque (22% versus 16%; P=0.7) was similar in both groups. Subjects with and without abdominal aortic plaques had similar coronary plaque burden. CONCLUSIONS: In asymptomatic type 1 diabetes, cardiovascular magnetic resonance imaging reveals greater coronary plaque burden in subjects with nephropathy compared with those with normoalbuminuria.

Vessel centerline tracking and boundary sgementation in coronary MRA with minimal manual interaction.

Magnetic resonance angiography (MRA) provides a noninvasive means to detect the presence, location and severity of atherosclerosis throughout the vascular system. In such studies, and especially those in the coronary arteries, the vessel luminal area is typically measured at multiple cross-sectional locations along the course of the artery. The advent of fast volumetric imaging techniques covering proximal to mid segments of coronary arteries necessitates automatic analysis tools requiring minimal manual interactions to robustly measure cross-sectional area along the three-dimensional track of the arteries in under-sampled and non-isotropic datasets. In this work, we present a modular approach based on level set methods to track the vessel centerline, segment the vessel boundaries, and measure transversal area using two user-selected endpoints in each coronary of interest. Arterial area and vessel length are measured using our method and compared to the standard Soap-Bubble reformatting and analysis tool in in-vivo non-contrast enhanced coronary MRA images.

Detecting, quantifying and adjusting for publication bias in meta-analyses: protocol of a systematic review on methods.

BACKGROUND: Health professionals and policymakers aspire to make healthcare decisions based on the entire relevant research evidence. This, however, can rarely be achieved because a considerable amount of research findings are not published, especially in case of 'negative' results - a phenomenon widely recognized as publication bias. Different methods of detecting, quantifying and adjusting for publication bias in meta-analyses have been described in the literature, such as graphical approaches and formal statistical tests to detect publication bias, and statistical approaches to modify effect sizes to adjust a pooled estimate when the presence of publication bias is suspected. An up-to-date systematic review of the existing methods is lacking. METHODS/DESIGN: The objectives of this systematic review are as follows:âeuro¢ To systematically review methodological articles which focus on non-publication of studies and to describe methods of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses.âeuro¢ To appraise strengths and weaknesses of methods, the resources they require, and the conditions under which the method could be used, based on findings of included studies.We will systematically search Web of Science, Medline, and the Cochrane Library for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses. A dedicated data extraction form is developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article. As this will be a qualitative systematic review, data reporting will involve a descriptive summary. DISCUSSION: Results are expected to be publicly available in mid 2013. This systematic review together with the results of other systematic reviews of the OPEN project (To Overcome Failure to Publish Negative Findings) will serve as a basis for the development of future policies and guidelines regarding the assessment and handling of publication bias in meta-analyses.

Steganalytic Methods for the Detection of Histogram Shifting Data Hiding Schemes

Peer-reviewed

In conspectu prope totius urbis: an application of different visual methods at the ager Tarraconensis landscape

We present in this paper the results of the application of several visual methods on a group of locations, dated between VI and I centuries BC, of the ager Tarraconensis (Tarragona, Spain) a Hinterland of the roman colony of Tarraco. The difficulty in interpreting the diverse results in a combined way has been resolved by means of the use of statistical methods, such as Principal Components Analysis (PCA) and K-means clustering analysis. These methods have allowed us to carry out site classifications in function of the landscape's visual structure that contains them and of the visual relationships that could be given among them.

Combining hypoxic methods for peak performance.

New methods and devices for pursuing performance enhancement through altitude training were developed in Scandinavia and the USA in the early 1990s. At present, several forms of hypoxic training and/or altitude exposure exist: traditional 'live high-train high' (LHTH), contemporary 'live high-train low' (LHTL), intermittent hypoxic exposure during rest (IHE) and intermittent hypoxic exposure during continuous session (IHT). Although substantial differences exist between these methods of hypoxic training and/or exposure, all have the same goal: to induce an improvement in athletic performance at sea level. They are also used for preparation for competition at altitude and/or for the acclimatization of mountaineers. The underlying mechanisms behind the effects of hypoxic training are widely debated. Although the popular view is that altitude training may lead to an increase in haematological capacity, this may not be the main, or the only, factor involved in the improvement of performance. Other central (such as ventilatory, haemodynamic or neural adaptation) or peripheral (such as muscle buffering capacity or economy) factors play an important role. LHTL was shown to be an efficient method. The optimal altitude for living high has been defined as being 2200-2500 m to provide an optimal erythropoietic effect and up to 3100 m for non-haematological parameters. The optimal duration at altitude appears to be 4 weeks for inducing accelerated erythropoiesis whereas &lt;3 weeks (i.e. 18 days) are long enough for beneficial changes in economy, muscle buffering capacity, the hypoxic ventilatory response or Na(+)/K(+)-ATPase activity. One critical point is the daily dose of altitude. A natural altitude of 2500 m for 20-22 h/day (in fact, travelling down to the valley only for training) appears sufficient to increase erythropoiesis and improve sea-level performance. 'Longer is better' as regards haematological changes since additional benefits have been shown as hypoxic exposure increases beyond 16 h/day. The minimum daily dose for stimulating erythropoiesis seems to be 12 h/day. For non-haematological changes, the implementation of a much shorter duration of exposure seems possible. Athletes could take advantage of IHT, which seems more beneficial than IHE in performance enhancement. The intensity of hypoxic exercise might play a role on adaptations at the molecular level in skeletal muscle tissue. There is clear evidence that intense exercise at high altitude stimulates to a greater extent muscle adaptations for both aerobic and anaerobic exercises and limits the decrease in power. So although IHT induces no increase in VO(2max) due to the low 'altitude dose', improvement in athletic performance is likely to happen with high-intensity exercise (i.e. above the ventilatory threshold) due to an increase in mitochondrial efficiency and pH/lactate regulation. We propose a new combination of hypoxic method (which we suggest naming Living High-Training Low and High, interspersed; LHTLHi) combining LHTL (five nights at 3000 m and two nights at sea level) with training at sea level except for a few (2.3 per week) IHT sessions of supra-threshold training. This review also provides a rationale on how to combine the different hypoxic methods and suggests advances in both their implementation and their periodization during the yearly training programme of athletes competing in endurance, glycolytic or intermittent sports.

Oops! Another medication error : a literature review of contributing factors and methods to prevent medication errors

The purpose of this bachelor's thesis was to chart scientific research articles to present contributing factors to medication errors done by nurses in a hospital setting, and introduce methods to prevent medication errors. Additionally, international and Finnish research was combined and findings were reflected in relation to the Finnish health care system. Literature review was conducted out of 23 scientific articles. Data was searched systematically from CINAHL, MEDIC and MEDLINE databases, and also manually. Literature was analysed and the findings combined using inductive content analysis. Findings revealed that both organisational and individual factors contributed to medication errors. High workload, communication breakdowns, unsuitable working environment, distractions and interruptions, and similar medication products were identified as organisational factors. Individual factors included nurses' inability to follow protocol, inadequate knowledge of medications and personal qualities of the nurse. Developing and improving the physical environment, error reporting, and medication management protocols were emphasised as methods to prevent medication errors. Investing to the staff's competence and well-being was also identified as a prevention method. The number of Finnish articles was small, and therefore the applicability of the findings to Finland is difficult to assess. However, the findings seem to fit to the Finnish health care system relatively well. Further research is needed to identify those factors that contribute to medication errors in Finland. This is a necessity for the development of methods to prevent medication errors that fit in to the Finnish health care system.

Protective effect and economic impact of insecticide application methods on barley

The objective of this work was to evaluate the protective effect of different forms of insecticide application on the transmission of yellow dwarf disease in barley cultivars, as well as to determine the production costs and the net profit of these managements. The experiments were carried out during 2011 and 2012 growing seasons, using the following managements at main plots: T1, seed treatment with insecticide (ST) + insecticide on shoots at 15-day interval; T2, just ST; T3, insecticide applied on shoots, when aphid control level (CL) was reached; T4, without insecticide; and T5, ST + insecticide on shoots when CL was reached. Different barley cultivars - BRS Cauê, BRS Brau and MN 6021 - were arranged in the subplots. Insecticides lambda cyhalothrin (pyrethroid) and thiamethoxam (neonicotinoid) were used. There were differences on yellow dwarf disease index in both seasons for the different treatments, while damage to grain yield was influenced by year and aphid population. Production costs and net profit were different among treatments. Seed treatment with insecticide is sufficient to reduce the transmission of yellow dwarf disease in years with low aphid population pressure, while in years with larger populations, the application of insecticide on shoots is also required.

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study.

To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

Fluid flow and dispersion predictions in porous media by utilizing advanced numerical methods

Diplomityön tavoitteena oli tarkastella numeerisen virtauslaskennan avulla virtaukseen liittyviä ilmiöitä ja kaasun dispersiota. Diplomityön sisältö on jaettu viiteen osaan; johdantoon, teoriaan, katsaukseen virtauksen mallinnukseen huokoisessa materiaalissa liittyviin tutkimusselvityksiin, numeeriseen mallinnukseen sekä tulosten esittämiseen ja johtopäätöksiin. Diplomityön alussa kiinnitettiin huomiota erilaisiin kokeellisiin, numeerisiin ja teoreettisiin mallinnusmenetelmiin, joilla voidaan mallintaa virtausta huokoisessa materiaalissa. Kirjallisuusosassa tehtiin katsaus aikaisemmin julkaistuihin puoliempiirisiin ja empiirisiin tutkimusselvityksiin, jotka liittyvät huokoisen materiaalin aiheuttamaan painehäviöön. Numeerisessa virtauslaskenta osassa rakennettiin ja esitettiin huokoista materiaalia kuvaavat numeeriset mallit käyttäen kaupallista FLUENT -ohjelmistoa. Työn lopussa arvioitiin teorian, numeerisen virtauslaskennan ja kokeellisten tutkimusselvitysten tuloksia. Kolmiulotteisen huokoisen materiaalinnumeerisessa mallinnuksesta saadut tulokset vaikuttivat lupaavilta. Näiden tulosten perusteella tehtiin suosituksia ajatellen tulevaa virtauksen mallinnusta huokoisessa materiaalissa. Osa tässä diplomityössä esitetyistä tuloksista tullaan esittämään 55. Kanadan Kemiantekniikan konferenssissa Torontossa 1619 Lokakuussa 2005. ASME :n kansainvälisessä tekniikan alan julkaisussa. Työ on hyväksytty esitettäväksi esitettäväksi laskennallisen virtausmekaniikan (CFD) aihealueessa 'Peruskäsitteet'. Lisäksi työn yksityiskohtaiset tulokset tullaan lähettämään myös CES:n julkaisuun.

Methods for the analysis of two dimensional measurement data of paper web

This work is devoted to the problem of reconstructing the basis weight structure at paper web with black{box techniques. The data that is analyzed comes from a real paper machine and is collected by an o®-line scanner. The principal mathematical tool used in this work is Autoregressive Moving Average (ARMA) modelling. When coupled with the Discrete Fourier Transform (DFT), it gives a very flexible and interesting tool for analyzing properties of the paper web. Both ARMA and DFT are independently used to represent the given signal in a simplified version of our algorithm, but the final goal is to combine the two together. Ljung-Box Q-statistic lack-of-fit test combined with the Root Mean Squared Error coefficient gives a tool to separate significant signals from noise.