Fixed Period Of Time Research Articles

THE MORNING BLOOD PRESSURE SURGE IN PATIENTS WITH HYPERTENSION

Objective: The aim of study was to definite validity and reliability of the new morning blood pressure surge (MBPS) assessment method in patients with arterial hypertension (AH).Design and method: We assessed 150 ambulatory blood pressure monitoring (ABPM) data of AH patients. ABPM monitor (Spacelabs 90207) was applied after the washout period. The new method determined the MBPS value as the difference between the mean BP during the period from 6 to 8 hours (for this period we determined the maximum rate of BP rise) and the minimum night BP (MBPS6_8/BPnigh_min). Test-re-test reliability (reproducibility) of the new method was determined as the correlation between the measurements of the first and second ABPM sessions carried out during the week (only for MBPS6_8/BPnigh_min indices). Construct validity of the new method was defined as the correlation between the MBPS6_8/BPnigh_min coefficient and left ventricular mass index (LVMI) (only for 98 patients). LVMI was measured using echocardiography (L. Teichholtz et all.). Results: The mean daytime BP was (M ± SD): systolic (SBP) – 141,1 ± 13,9; diastolic (DBP) – 90,1 ± 10,3 mm Hg. We found that the new method of MBPS assessment had a high degree of reliability: coefficient correlation (r) between parameters of the two ABPM sessions were (for MBPS6_8/BPnigh_min): for DBP r = 0,70, for SBP r = 0,83 (table 1). The validity of the new method was high: the MBPS value obtained using new method (MBPS6_8/BPnigh_min) correlated with LVMI (an objective factor of validation) (table 2). Conclusions: We found that the new method of the morning blood pressure surge assessment had a high level of validity and reproducibility (test-re-test reliability). The high reliability of the new method is probably due to the exclusion of subjective factors (patient's diary) in the evaluation of the MBPS value. The reference mean morning BP was determined for a fixed time period, and not by the patient's diary.

Maximum likelihood estimation of dynamic panel threshold models

Threshold estimation methods are developed for dynamic panels with individual specific fixed effects covering short time periods. Maximum likelihood estimation of the threshold and slope parameters is proposed using first difference transformations. Threshold estimate is shown to be consistent and its asymptotic distribution is nonstandard when the number of individuals grows to infinity for a fixed time period; the slope estimates are consistent and asymptotically normally distributed. The method is applied to a sample of 74 countries and 11 periods of 5-year averages to determine the effect of inflation rate on long-run economic growth.

Analysis of an inventory system with discrete scheduling period, time-dependent demand and backlogged shortages

A deterministic inventory model for goods with a power demand pattern, allowing backlogged shortages, is analyzed. The inventory cycle must be an integer multiple of a fixed time period (called basic period). Demand follows a power demand pattern during this basic time period. Demand not satisfied along the inventory cycle is fully backlogged and the stock-out period must be an integer multiple of the basic period. The goal of the inventory management is to minimize the inventory cost per unit time, considering that this inventory cost is the sum of the costs of holding, backlogging and ordering. Thus, the objective function of the inventory problem depends on two integer decision variables: the number of basic periods contained in an inventory cycle and the number of basic periods that constitute the stock-in period. The optimal inventory policy is found through a two-dimensional search method. This procedure is based on the properties of the inventory cost function. An algorithmic approach to calculate the economic order quantity and the optimal inventory cycle that minimize the total cost per unit time is proposed. The theoretical results are discussed and illustrated with some numerical examples. Finally, a sensitivity analysis of the optimal policy with respect to some parameters of the inventory model is developed.

Development of a Quick Knockdown Test for Diagnosing Resistance to Phosphine in Sitophilus oryzae (Coleoptera: Curculionidae), a Major Pest of Stored Products.

A key component in the management of resistance to fumigant phosphine in stored products pests is their early detection and implementation of control strategies. Currently, resistance testing involves exposing adults to a specific discriminating concentration over a fixed time period (20-48 h). Although it is widely adopted, this test takes significant time for assay preparation (up to 4 wk) as well as diagnosis (1-2 wk). To address these lacunae, we have established a 'quick knockdown test' using a key grain insect pest, rice weevil, Sitophilus oryzae (L.). Susceptible, weakly and strongly phosphine-resistant reference strains were exposed to a threshold concentration of phosphine over short exposure periods (min to h). The time to knockdown (KT) responses to phosphine were characterized at 2 (1,440 ppm) and 5 mg/liter (3,600 ppm). The time to 99.9% KT (KT99.9) at 2 mg/liter was 12.52 min for the susceptible adults, compared with 167.9 and 1,510 min in the case of weakly and strongly resistant phenotypes, respectively. As anticipated, increasing the concentration of phosphine to 5 mg/liter halved the KT99.9 (81.57 min) to separate weakly and strongly resistant populations than it was required at 2 mg/liter. We validated the KT99.9 value for the 5 mg/liter against field-derived populations of S. oryzae. The results were aligned with the existing Food and Agriculture Organization approach, confirming that the proposed 'quick test' is a reliable tool to rapidly diagnose resistance in this species.

The Magnitude of Offset Analgesia as a Measure of Endogenous Pain Modulation in Healthy Participants and Patients With Chronic Pain: A Systematic Review and Meta-Analysis.

Offset analgesia (OA) is a test paradigm increasingly used to estimate endogenous pain modulation characterized by a disproportionally profound analgesia after a small decrease of a heat stimulus. This systematic review and meta-analysis examined the magnitude and difference of OA in healthy participants and chronic pain patients. Controlled trials, case-control studies, cross-sectional studies, case-series or other observational studies evaluating the effect of a ±1°C offset trial in healthy controls and patients with chronic pain were searched in PubMed, Web of Science, CINAHL, PEDro, PsycINFO, and Cochrane CENTRAL. An additional hand search was conducted. Studies fulfilling the eligibility criteria were independently assessed for methodological quality with the Downs and Black scale by 2 reviewers. Twenty-six studies (healthy participants n=758; chronic pain patients n=134) were included in the qualitative synthesis and 12 in meta-analyses (healthy participants n=366; chronic pain patients n=73). A significant difference between offset and constant temperature trials was found for continuous pain intensity rating immediately after a 1°C decrease in temperature (-0.46 [visual analogue scale, 0 to 10]; 95% confidence interval, -0.75 to -0.17; P=0.002), but not after a fixed time period of 5 seconds. Furthermore, a significant difference of the magnitude of OA between chronic pain patients and healthy controls was calculated (-29.9%; 95% confidence interval, -40.3 to -19.5; P<0.00001). Results indicate that pain-free participants show a larger OA response when rating pain continuously compared with individuals with chronic pain.

Restricted Quadratic Optimal Control of a Spacecraft Turning in a Fixed Time Period

Restricted Quadratic Optimal Control of a Spacecraft Turning in a Fixed Time Period

Interim analysis of binary outcome data in clinical trials: a comparison of five estimators

ABSTRACT In clinical trials, where the outcome of interest is the occurrence of an event over a fixed time period, estimation of the event proportion at interim analysis can form a basis for decision-making such as early trial termination, sample size re-estimation, and/or dropping inferior treatment arms. In addition to derivation of mean squared error under an exponential time-to-event distribution, we performed a simulation study to examine the performance of five estimators of the event proportion when time to the event is assessable. The simulation results showed advantages of the Kaplan–Meier estimator over others in terms of robustness, and the bias and variability of the event proportion estimate. An example was given to illustrate how the estimators affect dropping treatment arms in a multi-arm multi-stage adaptive trial. We recommended the use of the Kaplan–Meier estimator and discourage the use of other estimators that discard the inherent time-to-event information.

Precursory Pattern Based Feature Extraction Techniques for Earthquake Prediction

Earthquake prediction is an important and complex task in the real world. Although many data mining-based methods have been proposed to solve this problem, the prediction accuracy is still far from satisfactory due to the deficiency of feature extraction techniques. To this end, in this paper, we propose a precursory pattern-based feature extraction method to enhance the performance of earthquake prediction. Especially, the raw seismic data is firstly divided into fixed day time periods, and the magnitude of the largest earthquake in each fixed time period is labeled as the main shock. The precursory pattern is a part of the seismic sequence before the main shock, on which the existing mathematical statistic features can be directly generated as seismic indicators. Based on these precursory pattern-based features, a simple yet effective classification and regression tree algorithm is adopted to predict the label of the main shock in a pre-defined future time period. The experimental results on two historical earthquake records of the Changding-Garze and Wudu-Mabian seismic zones of China demonstrate the effectiveness of the proposed precursory pattern-based features with the selected CART algorithm for earthquake prediction.

Water status and productivity of 'Hass' avocado trees in response to supplemental irrigation during winter

Abstract: The objective of this work was to evaluate the effects of supplemental irrigation, during winter dry season, on the water status and productivity of 'Hass' avocado (Persea Americana) trees. The experiment was carried out on a clayey Oxisol from 2014 to 2016, when extreme climatic events were recorded in the state of São Paulo, Brazil. The rainfed regime was compared with two irrigation regimes, applied during the whole and half of the irrigation run time defined by the grower, corresponding to 5,091 and 2,545 m3 ha-1 water, respectively. The following variables were evaluated: soil water tension; leaf water potential, color, and chlorophyll content; leaf and fruit abscission rates; tree size; and fruit size and yield. Supplemental irrigation applied during half of the run time increased fruit yield by 18.2%. However, irrigation applied during a fixed-time period and the occurrence of unusual rainfall spells caused soil water logging, negatively affecting tree growth and water status.

Concentric Ring Probe for Bioimpedance Spectroscopic Measurements: Design and Ex Vivo Feasibility Testing on Pork Oral Tissues.

Many oral diseases, such as oral leukoplakia and erythroplakia, which have a high potential for malignant transformations, cause abnormal structural changes in the oral mucosa. These changes are clinically assessed by visual inspection and palpation despite their poor accuracy and subjective nature. We hypothesized that non-invasive bioimpedance spectroscopy (BIS) might be a viable option to improve the diagnostics of potentially malignant lesions. In this study, we aimed to design and optimize the measurement setup and to conduct feasibility testing on pork oral tissues. The contact pressure between a custom-made concentric ring probe and tissue was experimentally optimized. The effects of loading time and inter-electrode spacing on BIS spectra were also clarified. Tissue differentiation testing was performed for ex vivo pork oral tissues including palatinum, buccal mucosa, fat, and muscle tissue samples. We observed that the most reproducible results were obtained by using a loading weight of 200 g and a fixed time period under press, which was necessary to allow meaningful quantitative comparison. All studied tissues showed their own unique spectra, accompanied by significant differences in both impedance magnitude and phase (p ≤ 0.014, Kruskal-Wallis test). BIS shows promise, and further studies are warranted to clarify its potential to detect specific pathological tissue alterations.

Urban Traffic Optimization with Real Time Intelligence Intersection Traffic Light System

Traffic system is a complex system where a lot of smart components which include signals, vehicles, sensor and pedestrian have communication skills with together on local level and act in a particular manner on high level. Insufficient traffic light control system on intersections brings about unnecessary delays and waste of time, extremely oil firing of engine which run idle mode on lights and increasing greenhouse gas emission. Various systems have been developed in order to overcome these traffic problems. In this paper we proposed an Intelligence Traffic Light System. In this system, the traffic flow at intersections is optimized using instant traffic information. These are the primary developed methods for the traffic optimization systems: fixed time period systems of lighting where time is pre-determined, green wave lighting system and real time optimization system of traffic light. Real data of traffic has been gathered on Karabuk-Safranbolu route to test above systems for different data density. The results of these tests on data show that real time traffic light optimization systems get better results than fixed time period and green wave lighting systems.

Pravastatin for Primary Prevention in Older Adults: Restricted Mean Survival Time Analysis.

To use restricted mean survival time, which summarizes treatment effects in terms of event-free time over a fixed time period, to evaluate the benefit of pravastatin therapy for primary prevention of cardiovascular disease in older adults. Secondary analysis of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial-Lipid-Lowering Trial (ALLHAT-LLT). Ambulatory setting. Individuals aged 65 and older (mean aged 71, 49% female) free of cardiovascular disease (N=2,867). Pravastatin 40 mg/d (n=1,467) versus usual care (n=1,400). We estimated the difference in RMST for total and coronary heart disease (CHD)-free survival between the pravastatin and usual care groups over the 6-year trial period and used parametric survival models to estimate RMST differences projected over 10 years. Over 6 years, individuals treated with pravastatin lived (RMST 2,008.1 days), on average, 33.7 fewer days than those receiving usual care (RMST 2,041.8 days) (difference -33.7 days, 95% confidence interval (CI)=-67.0 to -0.5 days, p=.047). Pravastatin-treated individuals lived RMST 2,088.1 days), on average, 18.7 more days free of CHD over 6 years than those receiving usual care (RMST 2,069.4 days), but this difference was not statistically significant (difference 18.7 days, 95% CI=-10.4-47.8 days, p=.21). The 10-year projection showed that pravastatin-treated individuals would live 108.1 fewer days (95% CI=-204.5 to -14.1, p=.03) than those receiving usual care, although treated individuals would gain 77.9 days (95% CI=3.8-159.6, p=.046) of CHD-free survival. RMST provides an intuitive and explicit way to express the effect of pravastatin therapy on CHD-free and overall survival in older adults free of cardiovascular disease. This measure allows a more personalized interpretation than hazard ratios of the benefits and risks of a medical intervention for decision-making.

Носії довготермінового зберігання даних

The results of the analysis of media development technologies for long-term data storage are presented. It is shown that the use of hard disk drive and solid-state non-volatile media only partially solve the problem of long-term information storage. Particular attention is paid to modern technologies for storing data on optical media. It is shown that the latest developments of optical media are aimed at a significant increase of optical media capacity by means of the nanostructured recording materials use. It was shown that maintaining of the big data security and integrity includes request stability of the readout signal contrast and data errors rates for long and fixed period of time. Therefore capacity of single disk for long data memory should be high enough to store the whole data to avoid the variation of the baseline over many disks. It was proposed to develop optical storage based on a nanoplasmonic hybrid glass matrix. The nanoplasmonic hybrid glass composite has to be formed by a sol-gel process to incorporate gold nanorods into hybrid glass composite. Incorporation of the inorganic phase increases the local Young’s modulus of the host matrix around nanorods which helps to improve the lifespan of the shape of nanorods by removing the unwanted shape degradation susceptible to the environmental thermal perturbation and increase lifespan of the data storage. Proposed method could be compared with the spin coating method, paving a way to the low-cost large-scale mass production of the optical disks.

Constructing dynamic treatment regimes over indefinite time horizons

Existing methods for estimating optimal dynamic treatment regimes are limited to cases where a utility function is optimized over a fixed time period. We develop an estimation procedure for the optimal dynamic treatment regime over an indefinite time period and derive associated large-sample results. The proposed method can be used to estimate the optimal dynamic treatment regime in chronic disease settings. We illustrate this by simulating a dataset corresponding to a cohort of patients with diabetes that mimics the third wave of the National Health and Nutrition Examination Survey, and examining the performance of the proposed method in controlling the level of haemoglobin A1c.

Motion estimation: A biologically inspired model

When humans (or robots) move through a scene, the scene can be represented as an optic flow (optical flow) field that contains vectors representing all of the movement within the scene projected onto a two-dimensional sensor. A simultaneous sample of these resulting vectors contain a good deal of information. A general model of motion estimation of local vectors would therefore be valuable. This paper addresses the estimation of motion vectors with uniform motion over a fixed time period. Previous reported attempts at computing motion estimation have been dominated by the machine vision community; however, these attempts are not specifically concerned with biological plausibility. Here, the author presents a model of motion estimation that computes motion based on filtering the moving image into sinusoidal responses varying in spatial frequency and orientation similar to the early visual responses found in human vision. Unlike similar spatio-temporal energy models “motion energy” is not computed. The model is mathematically explicit and simulated in MATLAB. It has been tested using over 7000 synthetic moving images with known veridical velocity (ground truth). These images range from sparse translating patterns containing 1 to 10,000 random pixels, to dense narrow band sinusoidal patterns. Simulation results show that the model correctly estimates motion trajectories between 84% and 100% angular direction error (within ±2°), and displacement error (within ±1 pixel). The results remain robust at different contrasts. In addition, a number of psychophysical and physiological results are examined in the context of the model.

A unified EOQ model with financial constraints and market tolerance

• Deterministic lot sizing within the general EOQ with partial backorders framework is studied. • Financial constraints and tolerance to shortages are considered. • The unified profit is generally non convex and incorporates two separate branches. • Properties that lead to a closed form global optimal solution are provided. We consider the general EOQ (with partial backorders) paradigm to study factors related to the recent financial crisis. Upstream, there are financial constraints, which first limit the available capital per replenishment and second impose the prepayment (in full or partial) of the quantity ordered. Downstream, the concept of market tolerance is operationalized, permitting here backorders to occur at no-cost for a fixed time period (directly analogous to upstream payment credit). For the resulting system, we present an exact unified model of the total average profit/cost. Optimal profit/cost and respective decision variables (i.e. order cycle and shortage period) are subsequently obtained in closed form. Interestingly, by appropriately relaxing the solution of the unified system, the solution of several (some previously studied) EOQ-type models prevails. Finally, analytical and computational results reveal the impact that each factor (individually and jointly) has on system optimal solution and on the behavior of the respective optimizers.

Effect of Low-Level Laser Irradiation on the Function of Glycated Catalase.

Introduction: The aim of this work is to evaluate the effect of low-level laser irradiation (LLLI), by lasers with different wavelengths, on glycated catalase enzyme in vitro experimentally. Methods: This is done by measuring the activity and structure properties of glycated catalase enzyme. The structure properties were evaluated with circular dichroism (CD) and fluoroscopy methods. Three continuous wave (CW) lasers in the visible spectrum (λ =450, 530, 638 nm) and a 100-ns pulsed laser in the infrared spectrum (λ =905 nm) were chosen for comparison. For the infrared laser, same effects have been investigated for different energy doses. The effect of photon energy (hυ) at different wavelengths was measured on activity, CD, and fluoroscopy properties of catalase, and compared with the control group (samples without irradiation). The energy intensity of laser should not exceed 0.1 J/cm2 . Experiments were performed on glycated catalase between 2 to 16 weeks after glycation of catalase. The LLLI effect was also investigated on the samples, by comparing the catalase activity, CD and fluoroscopy for different wavelengths. Results: Our results indicated, the decrease in catalase activity as a function of glycation time (weeks) for all samples, and a slight increase on its activity by different laser wavelengths irradiation for any fixed period of glycation time. Finally, the catalase activity has been increased as the laser's photon energy (hυ) intensified. More specifically, the blue laser (λ =450 nm) had the most and the red laser (λ =638 nm) had the least effect, and the green laser (λ =530 nm) had the medium effect on catalase activity as well. Furthermore, pulsed laser had an additional effect by increasing energy dosage. Conclusion: As we expected in all experiments, an increase in the catalase activity was coincident with a decrease in the catalase fluoroscopy and CD parameters.

The Gamma/Weibull Customer Lifetime Model

This paper proposes a new customer lifetime model: the Gamma/Weibull distribution (G/W). Similar to the Pareto/NBD model, we propose a G/W/NBD model by combining the G/W distribution with a negative binomial distribution (NBD) and study its properties such as (i) the probability that a customer to be alive at a time point; (ii) the expectation and variance of the number of transactions for a customer during a fixed time period; (iii) the conditional expectation and conditional variance of the number of future transactions for a customer during a fixed time period. Several simulation studies are conducted to investigate the forecasting accuracy and flexibility of the proposed model. A CDNOW data set is analyzed by the proposed model.

Estimating functions for SDE driven by stable Lévy processes

This paper is concerned with parametric inference for a stochastic differential equation driven by a pure-jump Levy process, based on high frequency observations on a fixed time period. Assuming that the Levy measure of the driving process behaves like that of an α-stable process around zero, we propose an estimating functions based method which leads to asymptotically efficient estimators for any value of α ∈ (0, 2) and does not require any integrability assumptions on the process. The main limit theorems are derived thanks to a control in total variation distance between the law of the normalized process, in small time, and the α-stable distribution. This method is an alternative to the non Gaussian quasi-likelihood estimation method proposed by Masuda [20] where the Blumenthal-Getoor index α is restricted to belong to the interval [1, 2).

Time since maximum of Brownian motion and asymmetric Lévy processes

Motivated by recent studies of record statistics in relation to strongly correlated time series, we consider explicitly the drawdown time of a Lévy process, which is defined as the time since it last achieved its running maximum when observed over a fixed time period . We show that the density function of this drawdown time, in the case of a completely asymmetric jump process, may be factored as a function of t multiplied by a function of T − t. This extends a known result for the case of pure Brownian motion. We state the factors explicitly for the cases of exponential down-jumps with drift, and for the downward inverse Gaussian Lévy process with drift.