Minimum Time Lags Research Articles

15N study of the reactivity of atmospheric nitrogen in four mountain forest catchments (Czech Republic, central Europe)

Reactivity of atmospherically deposited nitrate (NO3−) and ammonium (NH4+) was investigated in three mountain forest catchments and one ombrotrophic peat bog located in the northern Czech Republic. The study sites are characterized by moderate to high N pollution rates that are currently decreasing. Monitoring of hydrodynamic data and catchment hydrochemistry (precipitation, soil solutions and runoff) was complemented by δ15N analyses of dissolved inorganic N (NO3−, NH4+). Measured δ15N data were used to calculate the extent of biogeochemical reactions and to construct N mass balances. Two-component models of runoff generation were developed using hydrological and δ18O–H2O data on local precipitation, runoff, and soil waters collected by lysimeters. Catchment discharge was formed by groundwater (60–80%) and storm precipitation (40–20%), with minimal time lags. Groundwater had a diluting effect on reactions proceeding in the soil zone, including nitrification and denitrification. The rates of nitrification were estimated by comparing the δ15N values of atmospheric input and soil water, while the rates of denitrification were derived from the differences in the δ15N values of soil water and stream discharge. The Ν isotope effect of mineralisation of organic N was assessed by comparing δ15N values of soil and soil extracts. Nitrogen release from the catchments was controlled by temperature-dependent seasonality of soil reactions. Atmospheric N entered the runoff directly only during a short late winter - early spring period, accounting for approximately 10% of the total N input. Important inputs of mineralised organically cycled soil N were observed at the beginning and the end of the growing season, with measurable denitrification occurring during the same time periods. The measured apparent N isotope fractionations were significantly lower than previously published values (−3 to −14‰ vs. −30‰ for nitrification, and −3 vs. −20‰ for denitrification). Lower 15N fractionations originated both from the dilution effect of groundwater on stream discharge and from the depletion of available ammonium during nitrification reactions. Denitrification proceeding during recharge of the groundwater body was estimated from the difference in the δ15N values of NO3− in precipitation and groundwater.

Sea surface network optimization for tsunami forecasting in the near field: application to the 2015 Illapel earthquake

SUMMARYWe propose a method for defining the optimal locations of a network of tsunameters in view of near real-time tsunami forecasting using sea surface data assimilation in the near and middle fields, just outside of the source region. The method requires first the application of the empirical orthogonal function analysis to identify the potential initial locations, followed by an optimization heuristic that minimizes a cost-benefit function to narrow down the number of stations. We apply the method to a synthetic case of the 2015 Mw8.4 Illapel Chile earthquake and show that it is possible to obtain an accurate tsunami forecast for wave heights at near coastal points, not too close to the source, from assimilating data from three tsunameters during 14 min, but with a minimum average time lag of nearly 5 min between simulated and forecasted waveforms. Additional tests show that the time lag is reduced for tsunami sources that are located just outside of the area covered by the tsunameter network. The latter suggests that sea surface data assimilation from a sparse network of stations could be a strong complement for the fastest tsunami early warning systems based on pre-modelled seismic scenarios.

MILP models and valid inequalities for the two-machine permutation flowshop scheduling problem with minimal time lags

In this paper, we consider the problem of scheduling on two-machine permutation flowshop with minimal time lags between consecutive operations of each job. The aim is to find a feasible schedule that minimizes the total tardiness. This problem is known to be NP-hard in the strong sense. We propose two mixed-integer linear programming (MILP) models and two types of valid inequalities which aim to tighten the models’ representations. One of them is based on dominance rules from the literature. Then, we provide the results of extensive computational experiments used to measure the performance of the proposed MILP models. They are shown to be able to solve optimally instances until the size 40-job and even several larger problem classes, with up to 60 jobs. Furthermore, we can distinguish the effect of the minimal time lags and the inclusion of the valid inequalities in the basic MILP model on the results.

Convolutional Recurrent Neural Networks for Glucose Prediction.

Control of blood glucose is essential for diabetes management. Current digital therapeutic approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and insulin bolus calculators leverage machine learning techniques for predicting subcutaneous glucose for improved control. Deep learning has recently been applied in healthcare and medical research to achieve state-of-the-art results in a range of tasks including disease diagnosis, and patient state prediction among others. In this paper, we present a deep learning model that is capable of forecasting glucose levels with leading accuracy for simulated patient cases (root-mean-square error (RMSE) = 9.38 ± 0.71 [mg/dL] over a 30-min horizon, RMSE = 18.87 ± 2.25 [mg/dL] over a 60-min horizon) and real patient cases (RMSE = 21.07 ± 2.35 [mg/dL] for 30 min, RMSE = 33.27 ± 4.79% for 60 min). In addition, the model provides competitive performance in providing effective prediction horizon ([Formula: see text]) with minimal time lag both in a simulated patient dataset ([Formula: see text] = 29.0 ± 0.7 for 30 min and [Formula: see text] = 49.8 ± 2.9 for 60 min) and in a real patient dataset ([Formula: see text] = 19.3 ± 3.1 for 30 min and [Formula: see text] = 29.3 ± 9.4 for 60 min). This approach is evaluated on a dataset of ten simulated cases generated from the UVA/Padova simulator and a clinical dataset of ten real cases each containing glucose readings, insulin bolus, and meal (carbohydrate) data. Performance of the recurrent convolutional neural network is benchmarked against four algorithms. The proposed algorithm is implemented on an Android mobile phone, with an execution time of 6ms on a phone compared to an execution time of 780ms on a laptop.

Heuristic approaches to solve a two-stage lot sizing and scheduling problem

This paper addresses the two-stage lot sizing and scheduling problem considering the production environment with parallel machines. The aim of this problem is to ensure the synchrony between the stages through of the integrated lot sizing and scheduling decisions. In addition, we consider the presence of a buffer between the production stages with minimum and maximum time lags of the items. Reprocessing, discarding and acceleration costs are considered when the permanence times of the items in the buffer are not respected. Two mathematical models and several heuristics strategies based on decomposition of the problem are presented to solve real data adapted instances. The results showed that our heuristic strategies can achieve competitive solutions in short computational time, outperforming the solutions provided by the optimization solver.

Using smartphone-delivered stereoscopic vision in microsurgery: a feasibility study.

Many surgical specialties are increasingly looking towards robot-assisted surgeries to improve patient outcome. Surgeons conducting robot-assisted operations require real-time surgical view. Ophthalmic robots can lead to novel vitreoretinal treatments, such as cannulating retinal vessels or even gene delivery to targeted retinal cells. This study investigates the feasibility of smartphone-delivered stereoscopic vision for microsurgical use. A stereo-camera, connected to a laptop, was used to capture the 3D view from a binocular surgical microscope. Wi-Fi connection was used to live-stream the laptop display onto the smartphone screen wirelessly. Finally, a Virtual Reality (VR) headset, which acts as a stereoscope, was used to house the smartphone. The headset wearer then fused these images to achieve stereoscopic perception. Using smartphone-delivered 3D vision, the author performed a simulated cataract extraction operation successfully, despite a time lag of 0.354 s ± 0.038. To the author's knowledge, this is the first simulated ophthalmic operation performed via smartphone-delivered stereoscopic vision. Microscopic output in 3D with minimal time lag can be readily achievable with smartphones and VR headsets. Uncoupling the surgeon from the operating microscope is required to achieve tele-presence, an essential step in tele-robotics. Where operating theatre space is a concern, head-mounted displays may be more convenient than 3D televisions. This 3D live-casting technique can be used in teaching and mentoring settings, where microsurgeries can be live-streamed stereoscopically onto smartphones via local Wi-Fi network. When connected to the internet, microsurgeries can be broadcasted live and viewers worldwide can see the surgeon's view wearing their VR headsets.

Resource Leveling in Projects with Stochastic Minimum Time Lags

AbstractIn project management, resources and time are two critical aspects influencing the success of a project. On the one hand, resource leveling, an effective resource optimization technique, is...

Impact of reduced frequency on the time lag in pressure distribution over a supercritical airfoil in a pitch-pause-return motion

Effects of reduced frequency, stop angle, and pause duration have been studied on a thin supercritical airfoil undergoing a pitch-pause-return motion, which is one of the classic maneuvers introduced by the AIAA Fluid Dynamics Technical Committee. Experiments were conducted in a low-speed wind tunnel at both a constant mean angle of attack and an oscillation amplitude with a reduced frequency ranging from 0.01 to 0.12. The desired stop angles of the airfoil were set to occur during the upstroke motion. The unsteady pressure distribution on the airfoil was measured for below, near, and beyond static stall conditions. Results showed that the reduced frequency and stop angle were the dominant contributors to the time lag in the flowfield. For stop angles in both below- and post-stall regions, the time for the flowfield to reach its steady state conditions, known as the time lag, decreased as the reduced frequency was increased. However, in the static-stall region and for a certain value of reduced frequency, a resonance phenomenon was observed, and a minimum time lag was achieved. The pressure distribution in this condition was shown to be highly influenced by this phenomenon.

Non-permutation flowshop scheduling problem with minimal and maximal time lags: theoretical study and heuristic

In this paper, we address the non-permutation flowshop scheduling problem with minimal and maximal time lags between successive operations of each job. For this problem, the set of permutation schedules is not a dominant set but not all non-permutation schedules are feasible because they are not always able to satisfy all time lag constraints. We present a theoretical study, limited to the two-machine case, and related to the change on one machine of the order of two successive jobs of a permutation schedule. This study gives first the necessary conditions to make such move with regard to the feasibility of the schedule; secondly the necessary conditions to make such move interesting with regard to either the makespan or the number of tardy jobs. Through this analysis, we obtain new properties of dominance of permutation schedules. The results of the study are incorporated into a heuristic algorithm which starts the search with optimal permutation schedules and tries to improve them so as to obtain better non-permutation schedules. We also propose a mixed integer linear programming model. The objective function is to minimize lexicographically the number of tardy jobs as primary criterion and the makespan as secondary one. Computational experiments are performed to compare permutation with non-permutation schedules.

Multi-mode resource leveling in projects with mode-dependent generalized precedence relations

In real-life project management, resource leveling is an important technique to ensure the effective use of resources, in which activities (a) can often be executed in alternative modes and (b) are constrained by precedence relations with minimum and maximum time lags that can be modeled using generalized precedence relations (GPRs). In addition, the values of the time lags tend to depend on activity modes. The resource leveling problem with multiple modes and mode-dependent GPRs (MRLP-GPR) is a generalization of the classic NP-hard resource leveling problem. To our knowledge, no literature exists regarding the MRLP-GPR.We propose several heuristics for the MRLP-GPR built upon two solution approaches: (a) a steepest descent algorithm and a fast descent algorithm that are based on a decomposition approach and (b) a hybrid estimation of distribution algorithm (EDA), which is based on an integration approach. Extensive computational experiments on a large number of benchmark instances are conducted to evaluate the proposed heuristics. A comparison of the results shows that our EDA outperforms or is competitive with three baseline heuristics (a random search algorithm and two variants of a genetic algorithm that is the best-performing metaheuristic for the single-mode resource leveling problem with GPRs). Our results can serve as a benchmark for future research. Our model and solution algorithms provide an automatic tool for the project manager's multi-mode resource leveling decision-making.

Mixed-integer linear programming and constraint programming formulations for solving resource availability cost problems

We consider the resource availability cost problem and two extensions through general temporal constraints and calendar constraints. With general temporal constraints minimum and maximum time lags between the activities can be ensured. Calendar constraints are used to model breaks in the availability of a resource, e.g., weekends or public holidays of resource types that equal staff. Especially if long-term and capital-intensive projects are under consideration, resource availability cost problems should be applied because in such projects it is more important to minimize the cost than, e.g., the project duration. We present mixed-integer linear programming (MILP) formulations as well as constraint programming (CP) models for the three problems. In a performance study we compare the results of the MILP formulations solved by cplex and the CP models solved by the lazy clause generation solver chuffed on benchmark instances from literature and also introduce new benchmarks. Our CP models close all open instances for resource availability cost problems from the literature.

Efficient heuristic for solving non-permutation flow-shop scheduling problems with maximal and minimal time lags

Flow-shop scheduling problem is an attractive subject in the scheduling field, which has attracted the attention of many researchers in the past five decades. However, few studies focused on non-permutation flow-shop problems with time lag consideration. In the present work, the non-permutation flow-shop scheduling problem with time lags has been studied to minimize the makespan as a performance measure. First, we obtain a near-optimal permutation solution using the permutation flow-shopproblem (PFSP) heuristic. Then, an effective iterated greedy heuristic, which can identify high-quality non-permutation solutions, is presented. Using the neighbourhood non-PFSP searching heuristic, we searched for non-PFSP schedules using the proposed heuristic algorithms in the second stage. Finally, the computational results were used to evaluate the performance and effectiveness of the proposed heuristic. The proposed heuristics were able to find near optimal non-PFSP solutions with very short computational time. Thus, the proposed algorithms is efficient and can be used in industrial applications. Moreover, the proposed heuristic algorithms are very simple to implement, which is attractive for industrial applications.

FLOATING-BIOADHESIVE MATRIX TABLETS OF HYDRALAZINE HCL MADE OF CASHEW GUM AND HPMC K4M

Objective: The objective of this paper was to prepare and evaluate floating-bioadhesive cashew gum-hydroxypropyl methylcellulose (HPMC K4M) matrix tablets for the gastro-retentive release of hydralazine HCl.Methods: The cashew gum-HPMC K4M matrix tablets of hydralazine HCl were prepared by direct compression method with the incorporation of sodium bicarbonate and citric acid as effervescent agents. Drug contents, weight variations, hardness, friability, in vitro swelling, in vitro floatation, ex vivo mucoadhesion and in vitro drug release of these matrix tablets were evaluated.Results: Drug contents, weight variations, hardness and friability of these matrix tablets were within the compendia limits. These tablets were floated well in vitro over 12 h in simulated gastric fluid (SGF, pH 1.2) with minimum lag time. The ex vivo adhesion of these matrix tablets with goat intestinal mucosa exhibited good bioadhesion in a wash off test. All these cashew gum-HPMC K4M floating-bioadhesive matrix tablets of hydralazine HCl showed in vitro sustained releases of hydralazine HCl over 12 h in SGF, pH 1.2. The in vitro hydralazine HCl followed Korsmeyer-Peppas kinetic model and anomalous (non-Fickian) diffusion mechanism. The drug-polymer compatibility analysis by FTIR spectroscopy indicated the absence of any drug-polymer interaction within this cashew gum-HPMC K4M floating-bioadhesive matrix tablets of hydralazine HCl.Conclusion: The results clearly indicate a promising potential of the use of cashew gum as matrix forming a material with HPMC K4M to prepare matrix tablets for gastro retentive delivery of hydralazine HCl through the combined approach of floatation and bioadhesion to reduce the dosing rate with better patient compliances.

Effective Iterated Greedy Algorithm for Flow-Shop Scheduling Problems with Time lags

Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem(PFSP with time lags) is concentrated but non-permutation problem(non-PFSP with time lags) seems to be neglected. With the aim to minimize the makespan and satisfy time lag constraints, efficient algorithms corresponding to PFSP and non-PFSP problems are proposed, which consist of iterated greedy algorithm for permutation(IGTLP) and iterated greedy algorithm for non-permutation (IGTLNP). The proposed algorithms are verified using well-known simple and complex instances of permutation and non-permutation problems with various time lag ranges. The permutation results indicate that the proposed IGTLP can reach near optimal solution within nearly 11% computational time of traditional GA approach. The non-permutation results indicate that the proposed IG can reach nearly same solution within less than 1% computational time compared with traditional GA approach. The proposed research combines PFSP and non-PFSP together with minimal and maximal time lag consideration, which provides an interesting viewpoint for industrial implementation.

Ranitidine Loaded Biopolymer Floats: Designing, Characterization, and Evaluation

The float formulation is a strategy to improve the bioavailability of drugs by gastroretentive drug delivery system (GRDDS). A drug delivery model based on swellable and reswellable low density biopolymers has been designed to evaluate its drug release profile using ranitidine (RNT) as a model drug and formulations have been prepared utilizing 32factorial designs. The drug release (DR) data has been subjected to various kinetic models to investigate the DR mechanism. A reduction in rate has been observed by expanding the amounts of PSG and LSG parts, while an expansion has been noted by increasing the concentration of tragacanth (TG) and citric acid (CA) with an increment in floating time. The stearic acid (SA) has been used to decrease the lag time because a decrease in density of system was observed. The kinetic analysis showed that the optimized formulation (S4F3) followed zero-order kinetics and power law was found to be best fitted due to its minimum lag time and maximum floating ability. The resemblance of observed and predicted values indicated the validity of derived equations for evaluating the effect of independent variables while kinetic study demonstrated that the applied models are feasible for evaluating and developing float for RNT.

Isolation of polysaccharides from Plantago ovata and their evaluation as potential matrices for designing the controlled release floats of Piroxicam

The present study deals with isolation of different polysaccharides from Plantago Ovata husk and their use in designing the controlled release Gastro-Retentive (GR) floats of piroxicam (PRC). Gastroretentive floats are actually drug release (DR) moieties of low density used to retain the drug in stomach for maximum time to increase its bioavailability. The polysaccharides extracted from P. Ovata were selected due to its therapeutic impacts and ease in accessibility although synthetic polymers have already been utilized for designing such types of floats. The floats of that fraction were selected for designing further formulations having least lag time with maximum drug release retarding ability. For modifying the drug release (DR) rate; flax seed gel, gum tragacanth and Stearic acid were used as variables. The direct compression technique was used for compression and floats were characterized for uniformity in weight, drug content, friability and in vitro buoyancy. All fractions were characterized by FTIR, TGA, GPC and SEM study to find the nature of polysaccharide, predicting its stability and compatibility with human body. Some mathematical tools i.e. kinetic study and regression analysis (RA) were applied to find the effect of different variables on DR rate and closeness among the theoretical and experimental DR profile. The ethanol separated part (ENa) was seen to be most suitable in view of its better swelling ability and minimum lag time. The formulation S4F9 was seem to be best fitted due to its minimum lag time, best drug entrapping ability and best suitability to Higuchi's model (R2 = 0.957) and Power law (R2 = 0.963). The DR mechanism was found to be non-Fickian diffusion (n > 0.45). Keywords: Polysaccharide Gels; GR floats; GPC; FTIR; TGA; 32 Factorial design; Lag time http://dx.doi.org/10.19045/bspab.2016.50128

In vitro kinetic parameters of marandu palisadegrass associated with nonfiber carbohydrates

This study aimed to evaluate the effects of different levels (0, 10, 20 and 30%) of starch or glucose associated with marandu palisadegrass (Urochloa brizantha cv. Marandu) on its kinetic parameters and fiber digestion by the in vitro gas production technique. The experiment was arranged in a completely randomized design, with four treatments and six replications for each energy source. The marandu palisadegrass associated with nonfiber carbohydrate levels was incubated in 120 ml bottles, with McDougall buffer and rumen fluid from two rumen-cannulated sheep. Readings were taken of gas pressure within the bottle, and two vials were removed at 24, 48 and 96 hours (h) to assess residual neutral detergent fiber (NDF). The one-pool logistic model was used to estimate the kinetic parameters for pure forage and forage associated with starch, however it was necessary to use the two-pools model when glucose was added. Each 1% of added starch promoted a linear increase in total gas production of 0.2254 ml and a decrease in lag time of 0.2451 h, but did not affect the digestion rate. Glucose levels had a quadratic effect on digestion rate and lag time, with a minimum estimated value for digestion rate of 0.01689 h-1 at a glucose level of 10.07% and a minimum lag time of zero. Starch levels caused a linear reduction in NDF digestion of 0.296% only at 24 h, while glucose levels linearly reduced the NDF digestion in all evaluated times (0.3269, 0.4171 and 0.2340% at 24, 48 and 96 h, respectively). Glucose levels promoted different effects on the in vitro gas production kinetic parameters of marandu palisadegrass compared to starch supplementation, highlighting the prolonged negative effects on NDF digestion.

A Practical and Robust Execution Time-Frame Procedure for the Multi-Mode Resource-Constrained Project Scheduling Problem with Minimal and Maximal Time Lags

Modeling and optimizing organizational processes, such as the one represented by the Resource-Constrained Project Scheduling Problem (RCPSP), improve outcomes. Based on assumptions and simplification, this model tackles the allocation of resources so that organizations can continue to generate profits and reinvest in future growth. Nonetheless, despite all of the research dedicated to solving the RCPSP and its multi-mode variations, there is no standardized procedure that can guide project management practitioners in their scheduling tasks. This is mainly because many of the proposed approaches are either based on unrealistic/oversimplified scenarios or they propose solution procedures not easily applicable or even feasible in real-life situations. In this study, we solve a more true-to-life and complex model, Multimode RCPSP with minimal and maximal time lags (MRCPSP/max). The complexity of the model solved is presented, and the practicality of the proposed approach is justified depending on only information that is available for every project regardless of its industrial context. The results confirm that it is possible to determine a robust makespan and to calculate an execution time-frame with gaps lower than 11% between their lower and upper bounds. In addition, in many instances, the solved lower bound obtained was equal to the best-known optimum.

Serial image analysis of Mycobacterium tuberculosis colony growth reveals a persistent subpopulation in sputum during treatment of pulmonary TB

SummaryFaster elimination of drug tolerant ‘persister’ bacteria may shorten treatment of tuberculosis (TB) but no method exists to quantify persisters in clinical samples. We used automated image analysis to assess whether studying growth characteristics of individual Mycobacterium tuberculosis colonies from sputum on solid media during early TB treatment facilitates ‘persister’ phenotyping. As Time to Detection (TTD) in liquid culture inversely correlates with total bacterial load we also evaluated the relationship between individual colony growth parameters and TTD. Sputum from TB patients in Malawi was prepared for solid and liquid culture after 0, 2 and 4 weeks of treatment. Serial photography of agar plates was used to measure time to appearance (lag time) and radial growth rate for each colony. Mixed-effects modelling was used to analyse changing growth characteristics from serial samples. 20 patients had colony measurements recorded at ≥1 time-point. Overall lag time increased by 6.5 days between baseline and two weeks (p = 0.0001). Total colony count/ml showed typical biphasic elimination, but long lag time colonies (>20days) had slower, monophasic decline. TTD was associated with minimum lag time (time to appearance of first colony1). Slower elimination of long lag time colonies suggests that these may represent a persister subpopulation of bacilli.

An approach using SAT solvers for the RCPSP with logical constraints

This paper presents a new solution approach to solve the resource-constrained project scheduling problem in the presence of three types of logical constraints. Apart from the traditional AND constraints with minimal time-lags, these precedences are extended to OR constraints and bidirectional (BI) relations. These logical constraints extend the set of relations between pairs of activities and make the RCPSP definition somewhat different from the traditional RCPSP research topics in literature. It is known that the RCPSP with AND constraints, and hence its extension to OR and BI constraints, is NP-hard.The new algorithm consists of a set of network transformation rules that removes the OR and BI logical constraints to transform them into AND constraints and hereby extends the set of activities to maintain the original logic. A satisfiability (SAT) solver is used to guarantee the original precedence logic and is embedded in a metaheuristic search to resource feasible schedules that respect both the limited renewable resource availability as well as the precedence logic.Computational results on two well-known datasets from literature show that the algorithm can compete with the multi-mode algorithms from literature when no logical constraints are taken into account. When the logical constraints are taken into account, the algorithm can report major reductions in the project makespan for most of the instances within a reasonable time.