Pre-specified Period Of Time Research Articles

Prevalence of Positivity for Diabetes-Associated Autoantibodies in Individuals with Type 2 Diabetes and Their Further Characterisation: Cross-sectional Study from Slovakia.

Individuals initially diagnosed with type 2 diabetes (T2D) might exhibit positivity for diabetes-associated autoantibodies (DAA +). We investigated the prevalence of DAA positivity in a group of individuals with T2D who were referred to a tertiary diabetes centre within a pre-specified period of time. We aimed to identify characteristics linked with DAA positivity by comparing DAA + individuals with their DAA-negative counterparts. This was a cross-sectional study into which all T2D patients referred to the NationalInstitute of Endocrinology and Diabetology, Ľubochňa, Slovakia, between 1 January and 30 June 2016 were included. Data on > 70 participants' characteristics, including antibodies against glutamic acid decarboxylase (anti-GAD65), insulinoma-associated antigen IA-2 (IA-2A) and insulin (IAA), were collected. Six hundred and ninety-two individuals (387, 55.6% female) with a median (range) age of 62 (24-83) years, HbA1c of 8.9 (5.0-15.7)% [74 (31-148mmol/mol)] and diabetes duration of 13.0 (0-42) years were analysed. One hundred and forty-five (145/692, 21.0%) tested positive for at least one DAA; 136/692 (19.7%) were positive for anti-GAD65, 21/692 (3.0%) were positive for IA-2A and 9/692 (1.3%) were positive for IAA. Only 84.9% of the DAA + individuals aged > 30years at the time of diabetes diagnosis met the current diagnostic criteria for latent autoimmune diabetes of adults (LADA). DAA + differed from DAA- individuals in multiple characteristics, including the incidence of hypoglycaemia. Several pathological processes linked with distinct types of diabetes can develop in parallel, including insulin resistance and autoimmune insulitis. In this single-centre cross-sectional study from Slovakia, we report a higher than previously published prevalence of DAA positivity in agroup ofindividualswith a formal diagnosis of T2D.

A linear programming based method for designing menus for controlled feeding trials

BackgroundControlled feeding trials are an important method to determine cause-effect relationships between dietary intake and metabolic parameters, risk factors, or health outcomes. Participants of a controlled feeding trial receive full-day menus during a prespecified period of time. The menus have to comply with the nutritional and operational standards of the trial. Levels of nutrients under investigation should differ sufficiently between intervention groups, and be as similar as possible for all energy levels within intervention groups. Levels of other key nutrients should be as similar as possible for all participants. All menus have to be varied and manageable. Designing these menus is both a nutritional and a computational challenge that relies largely on the expertise of the research dietician. The process is very time consuming, and last-minute disruptions are very hard to manage. ObjectiveThis paper demonstrates a mixed integer linear programming model to support the design of menus for controlled feeding trials. MethodsThe model is demonstrated for a trial that involved consumption of individualized, isoenergetic menus with either a low or a high protein content. ResultsAll menus generated by the model comply with all standards of the trial. The model allows for including tight ranges on nutrient composition, and complex design features. The model is very helpful in managing contrast and similarity of key nutrient intake levels between groups and energy levels, and in coping with many energy levels and nutrients. The model helps to propose several alternative menus and to manage last-minute disruptions. The model is flexible; it can easily be adapted to suit trials with other components or different nutritional requirements. ConclusionsThe model helps to design menus in a fast, objective, transparent, and reproducible way. It greatly facilitates the design procedure for menus in controlled feeding trials and lowers development costs.

"Nonroutine Events" as a Nonroutine Outcome for Perioperative Systems Research.

"Nonroutine Events" as a Nonroutine Outcome for Perioperative Systems Research.

Pricing 'partial-average' Asian options with the binomial method

An Asian option is path-dependent derivatives whose payoff depends on the average of the underlying asset price over a certain pre-specified period of time. There is no simple closed-form solution for arithmetic Asian option hence the development of efficient and accurate numerical methods has become critical. In this paper, a modified binomial method is presented for pricing a more common arithmetic Asian option, by averaging the asset between two time periods in the life span of the option. This option is called the 'partial-average' Asian option. Subsequently, the representative averages are used instead of the actual ones for pricing the option. The set of representative averages is constructed first by determining the maximum and the minimum averages, where other averages are calculated by dividing equally the distance between the maximum and the minimum averages. For Asian option with average strike, if the distance between two time periods is widened by shifting the second time period to the right then the price becomes lower. But if the distance is widened by shifting the first time period to the left then the price becomes higher. The algorithm is not only simple but also easy to implement.

Pricing Partial-Average Asian Options with the Binomial Method

An Asian option is path-dependent derivatives whose payoff depends on the average of the underlying asset price over a certain pre-specified period of time. There is no simple closed-form solution for arithmetic Asian option hence the development of efficient and accurate numerical methods has become critical. In this paper, a modified binomial method is presented for pricing a more common arithmetic Asian option, by averaging the asset between two time periods in the life span of the option. This option is called the 'partial-average' Asian option. Subsequently, the representative averages are used instead of the actual ones for pricing the option. The set of representative averages is constructed first by determining the maximum and the minimum averages, where other averages are calculated by dividing equally the distance between the maximum and the minimum averages. For Asian option with average strike, if the distance between two time periods is widened by shifting the second time period to the right then the price becomes lower. But if the distance is widened by shifting the first time period to the left then the price becomes higher. The algorithm is not only simple but also easy to implement.

Improved implementation of the risk-adjusted Bernoulli CUSUM chart to monitor surgical outcome quality.

The traditional implementation of the risk-adjusted Bernoulli cumulative sum (CUSUM) chart for monitoring surgical outcome quality requires waiting a pre-specified period of time after surgery before incorporating patient outcome information. We propose a simple but powerful implementation of the risk-adjusted Bernoulli CUSUM chart that incorporates outcome information as soon as it is available, rather than waiting a pre-specified period of time after surgery. A simulation study is presented that compares the performance of the traditional implementation of the risk-adjusted Bernoulli CUSUM chart to our improved implementation. We show that incorporating patient outcome information as soon as it is available leads to quicker detection of process deterioration. Deterioration of surgical performance could be detected much sooner using our proposed implementation, which could lead to the earlier identification of problems.

MOMENTUM TRADING IN NEW YORK STOCK EXCHANGE (NYSE) ENERGY STOCKS

This paper investigates whether the momentum effect exists in the NYSE energy sector. Momentum is defined as the strategy that buys (sells) these stocks that are best (worst) performers, over a pre-specified past period of time (the 'look-back' period), by constructing equally weighted portfolios. Different momentum strategies are obtained by changing the number of stocks included in these portfolios, as well as the look-back period. Next, their performance is compared against two benchmarks: the equally weighted portfolio consisting of most stocks in the NYSE energy index and the market portfolio, and the S&P500 index. The results indicate that the momentum effect is strongly present in the energy sector, and leads to highly profitable portfolios, improving the risk-reward measures and easily outperforming both benchmarks.

A naonoporous cell-therapy device with controllable biodegradation for long-term drug release

Herein we describe the development and implementation of a nanoporous cell-therapy device with controllable biodegradation. Dopamine-secreting PC12 cells were housed within newly formulated alginate-glutamine degradable polylysine (A-GD-PLL) microcapsules. The A-GD-PLL microcapsules provided a 3-D microenvironment for good spatial cell growth, viability and proliferation. The microcapsules were subsequently placed within a poly(ethylene glycol) (PEG)-coated poly(ε-caprolactone) (PCL) chamber covered with a PEG-grafted PCL nanoporous membrane formed by phase inversion. To enhance PC12 cell growth and to assist in controlled degradation of both the PC12 cells and the device construct, small PCL capsules containing neural growth factor (PCL-NGF) and a poly(lactic-co-glycolic acid) pellet containing glutamine (PLGA-GLN) were also placed within the PCL chamber. Release of NGF from the PCL-NGF capsules facilitated cell proliferation and viability, while the controlled release of GLN from the PLGA-GLN pellet resulted in A-GD-PLL microcapsule degradation and eventual PC12 cell death following a pre-specified period of time (4weeks in this study). In vivo, our device was found to be well tolerated and we successfully demonstrated the controlled release of dopamine over a period of four weeks. This integrated biodegradable device holds great promise for the future treatment of a variety of diseases.

Searching for novelty: Challenges with open access data

Searching for novelty: Challenges with open access data

A study of maintenance policies for second-hand products

This paper proposes two maintenance schemes for reused products. In order to reduce the purchasing cost or conform to the concept of environmental protection, reuse is considered as one of the most efficient strategies. However, the initial quality of reused product is often inferior to the new one and then product failures will occur frequently during usage period. Therefore, two periodical preventive maintenance (PM) policies in this paper are developed to decrease the high failure rate of the second-hand products. When a second-hand product with Weibull life time distribution of known age is intended to be used for a pre-specified period of time, the optimal number of PM actions and the corresponding maintenance degree are derived such that the expected total maintenance cost is minimized. The impact of providing preventive maintenance is illustrated through numerical examples.

Design of optimum multiple-stress accelerated life testing plans based on proportional odds model

Accelerated Life Testing (ALT) is used to obtain failure time data quickly under high stress levels in order to predict product life and performance under the design stress. Most of the previous work on designing ALT plans is focused on the application of a single stress. However, as components or products become more reliable due to technological advances, it becomes more difficult to obtain significant amount of failure data within a reasonable amount of time using single stress only. Multiple-stress ALTs have been employed as a means of overcoming such difficulties. In this paper, we design optimum multiple-stress ALT plans based on the Proportional Odds (PO) model. The optimum combinations of stress levels and the number of test units allocated to each combination are determined such that the variance of the reliability prediction of the product over a pre-specified period of time is minimised. The proposed ALT plan is illustrated by a numerical example.

Strategic Manipulation on Emissions Trading Banking Program with Fixed Horizon

This paper considers a permit market with both spatial and intertemporal trading. The intertemporal market allows firms to freely borrow or bank permits over a pre-specified period of time. When this period is over, the permit bank has to be balanced, so firms cannot avoid compliance just by borrowing from the future. Market power is introduced by assuming a large dominant agent in a Stackelberg position and a large number of small firms who are nonstrategic but forward looking. The equilibrium is characterized by for the monopoly case and for intermediate cases.

Optimum multiple-stress-type accelerated life testing plans based on proportional odds model with simple step-stress loading

Accelerated-life testing (ALT) is used to induce early failures under high stress levels in order to predict product reliability performance at the design stress. Most of the previous work on designing ALT plans is focused on the application of a single stress type. However, the mission time of today's products is extended so much that it becomes more difficult to obtain significant amount of failure data within reasonable amount of time using single stress type only. Multiple-stress-type ALTs have been employed as means of overcoming such difficulties. In this paper, we design optimum multiple-stress-type ALT plans based on the proportional odds model with simple step-stress loading and cumulative exposure model. Low stress levels of each stress type and the stress level changing time are optimally determined such that the variance of the reliability prediction of the product at the design stress levels over a pre-specified period of time is minimized. The proposed ALT plans are illustrated by a numerical example.

Formation of HCN and NH 3 during coal macerals pyrolysis and gasification with CO 2

Three coal macerals with high purities were separated from Pingshuo gas coal. The formation rules of HCN and NH 3 during macerals pyrolysis and gasification were investigated. Experiments were carried out in a tubular quartz reactor at atmospheric pressure. The reactor allowed coal particles to be heated up rapidly and held for a prespecified period of time at a peak temperature. The amount of HCN and NH 3 were quantified by ion chromatography. The influence of temperature and macerals type on the formation rules of HCN and NH 3 was discussed. Results showed that the formation of HCN was mainly due to the thermal cracking of volatile, and NH 3 formed both from the thermal cracking of volatile and the cracking of nascent char. The HCN yield increased with an increase in pyrolysis temperature. For three coal macerals (liptinite, vitrinite and inertinite), the yield of HCN depended not only on their volatile contents but also nitrogen-containing functional groups, in which more pyrrole-type nitrogens would form more amount of HCN at lower temperature. The yield of NH 3 depended on the ability of forming ‘H’ radical. Under the experiment condition in this study, inertinite could convert more nitrogen into NH 3 than vitrinite and liptinite. The yield of HCN during gasification was almost the same as that during pyrolysis, the yield of NH 3 during gasification was little higher than that during pyrolysis.

Studies of the release rule of NO x precursors during gasification of coal and its char

This investigation involved the formation and release of precursors of NO x , which were HCN and NH 3, during gasification of coal and its char. Gasification was carried out in a fixed bed reactor at atmospheric pressure. The reactor allowed coal particles to be heated up rapidly and held for a pre-specified period of time at peak temperature. The influence of coal rank and coal particle size on the release of N-containing compounds during coal gasification with CO 2 is discussed. Gasification agents and coal gasification temperature were two key factors on the amount of nitrogenous compounds released. Results showed that with an increase of reaction temperature a great amount of NH 3 was formed during gasification with steam: The yield of NH 3 was highest at 800 °C during gasification with CO 2. The volatiles in coal played the key role in the formation of HCN and NH 3 during coal gasification under steam atmosphere. Volatiles were the main source of the formation of HCN and NH 3, mainly from the nascent char thermal cracking, whose procedure could be promoted by H 2O(g): The yield of HCN during coal gasification had no strong relation with gasification agents and increased with an increase in gasification temperature. A reasonable mechanism for the formation of nitrogenous compounds during coal gasification was suggested in this study, which could explain some results in the literature on pyrolysis and gasification of coal.

Mortality derivatives and the option to annuitise

Most US-based insurance companies offer holders of their tax-sheltered savings plans (VAs), the long-term option to annuitise their policy at a pre-determined rate over a pre-specified period of time. Currently, there is approximately one trillion dollars invested in such policies, with guaranteed annuitisation rates, in addition to any guaranteed minimum death benefit. The insurance company has essentially granted the policyholder an option on two underlying stochastic variables; future interest rates and future mortality rates. Although the (put) option on interest rates is obvious, the (put) option on mortality rates is not. Motivated by this product, this paper attempts to value (options on) mortality-contingent claims, by stochastically modelling the future hazard-plus-interest rate. Heuristically, we treat the underlying life annuity as a defaultable coupon-bearing bond, where the default occurs at the exogenous time of death. From an actuarial perspective, rather than considering the force of mortality (hazard rate) at time t for a person now age x, as a number μx(t), we view it as a random variable forward rate μ˜x(t), whose expectation is the force of mortality in the classical sense ( μx(t)=E[μ˜x(t)]). Our main qualitative observation is that both mortality and interest rate risk can be hedged, and the option to annuitise can be priced by locating a replicating portfolio involving insurance, annuities and default-free bonds. We provide both a discrete and continuous-time pricing framework.

Mortality Derivatives and the Option to Annuitize

Most U.S.-based insurance companies offer holders of their tax-sheltered savings plans (VAs), the long-term option to annuitize their policy at a pre-determined rate over a pre-specified period of time. Currently, there is approximately one trillion dollars invested in such policies, with guaranteed annuitization rates, in addition to any guaranteed minimum death benefit. The insurance company has essentially granted the policyholder an option on two underlying stochastic variables; future interest rates and future mortality rates. Although the (put) option on interest rates is obvious, the (put) option on mortality rates is not. Motivated by this product, this paper attempts to value (options on) mortality-contingent claims, by stochastically modelling the future hazard-plus-interest rate. Heuristically, we treat the underlying life annuity as a defaultable coupon-bearing bond, where the default occurs at the exogenous time of death. From an actuarial perspective, rather than considering the force of mortality (hazard rate) at time-t for a person now age-x, as a number, we view it as a random variable forward rate,whose expectation is the force of mortality in the classical sense. Our main qualitative observation is that both mortality and interest rate risk can be hedged, and the option to annuitize can be priced by locating a replicating portfolio involving insurance, annuities and default-free bonds. We provide both a discrete and continuous-time pricing framework.

Formation of NO x and SO x precursors during the pyrolysis of coal and biomass. Part I. Effects of reactor configuration on the determined yields of HCN and NH 3 during pyrolysis

The formation of HCN and NH 3 during the pyrolysis of a biomass (bagasse) and a set of rank-ordered coal samples has been studied in a novel reactor. The reactor has some features of both a drop-tube reactor and a fixed-bed reactor: the reactor allows the coal/biomass particles to be heated up rapidly as well as to be held for a pre-specified period of time at peak temperature. The experimental results obtained suggest that a considerable amount of the nitrogen in the nascent char could be converted into HCN and NH 3 if the char is held at high temperatures for long time. The formation of NH 3 from the thermal cracking of char was seen to last for more than an hour even at temperatures as high as 700–900°C. The formation of HCN went to completion much more rapidly than that of NH 3. Compared with the results in the literature from the pyrolysis of coals in a fluidised-bed reactor, the reactor configuration used in this study allows the effects of fuel rank to be studied on an unbiased basis towards the type of fuel. The yields of HCN and NH 3 from the present study decrease with increasing rank. The experimental results suggest that the differences in reactor configurations used by various researchers would account at least partially for some of the discrepancies in the literature regarding the formation of HCN and NH 3 during the pyrolysis of coals.

Hopfield neural network for the multichannel segmentation of magnetic resonance cerebral images

In this paper, we present an approach for the segmentation of magnetic resonance images of the brain, based on Hopfield neural network. We formulate the segmentation problem as a minimization of an energy function constructed with two terms, the cost-term, that is a sum of errors' squares, and the second term is a temporary noise added to the cost-term as an excitation to the network to escape from certain local minima and be closer to the global minimum. Also, to ensure the convergence of the network and its utility in the clinic with useful results, the minimization is achieved in a way that after a prespecified period of time the energy function can reach a local minimum close to the global minimum and remain there ever after. We present here, segmentation results of two patients data diagnosed with a metastatic tumor and multiples sclerosis in the brain.

A comparison of Hopfield neural network and Boltzmann machine in segmenting MR images of the brain

Presents contributions to improve a previously published approach for the segmentation of magnetic resonance images of the human brain, based on an unsupervised Hopfield neural network. The authors formulate the segmentation problem as the minimization of an energy function constructed with two terms: the cost-term as a sum of squared errors and the second term temporary noise added to the cost-term as an excitation to the network to escape certain local minima, with the result of being closer to the global minimum. Also, to ensure the convergence of the network and its utilization in the clinic with useful results, the minimization is achieved with a step function that permits the network to reach stability corresponding to a local minimum close to the global minimum in a prespecified period of time. The authors present segmentation results of their approach for data of patient diagnosed with a metastatic tumor in the brain, and they compare them to those obtained from previous work using Hopfield neural networks, the Boltzmann machine, and the conventional ISODATA clustering technique.