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Real-time bus travel time prediction has been an interesting problem since past decade, especially in India. Popular methods for travel time prediction include time series analysis, regression methods, Kalman filter method and Artificial Neural Network (ANN) method. Reported studies using these methods did not consider the high variance situations arising from the varying traffic and weather conditions, which is very common under heterogeneous and lane-less traffic conditions such as the one in India. The aim of the present study is to analyse the variance in bus travel time and predict the travel time accurately under such conditions. Literature shows that Support Vector Machines (SVM) technique is capable of performing well under such conditions and hence is used in this study. In the present study, nu-Support Vector Regression (SVR) using linear kernel function was selected. Two models were developed, namely spatial SVM and temporal SVM, to predict bus travel time. It was observed that in high mean and variance sections, temporal models are performing better than spatial. An algorithm to dynamically choose between the spatial and temporal SVM models, based on the current travel time, was also developed. The unique features of the present study are the traffic system under consideration having high variability and the variables used as input for prediction being obtained from Global Positioning System (GPS) units alone. The adopted scheme was implemented using data collected from GPS fitted public transport buses in Chennai (India). The performance of the proposed method was compared with available methods that were reported under similar traffic conditions and the results showed a clear improvement. [ABSTRACT FROM AUTHOR]

Clopidogrel is an antiplatelet drug with high intraindividual variability in systemic exposure and efficacy. It has been used for treating atherosclerosis and acute coronary syndrome and in preventing stent restenosis and thrombotic complications after stent implantation in clinical practice for nearly 20 years. In this study we aimed to evaluate the bioequivalence of 2 clopidogrel hydrogen sulfate formulations (75‐mg tablets) under fed (n = 66) and fasted (n = 66) conditions by using the reference‐scaled average bioequivalence method. An open‐label, randomized, 3‐sequence and 3‐period crossover (3×3), semireplicated study was designed and conducted. Clopidogrel concentration of plasma samples was measured by high‐precision liquid chromatography and tandem mass spectrometry. The pharmacokinetic parameters were derived by a noncompartmental model. In the fed condition the geometric least‐squares mean ratios of peak concentration (Cmax) and area under the concentration‐time curve (AUC0‐t) were, respectively, 103.38% and 98.97%, and the corresponding 90%CIs were 95.68% to 111.70% and 94.67% to 103.47%. In the fasted condition the geometric least squares mean ratios of Cmax and AUC0‐t were, respectively, 106.53% and 105.77%, and the corresponding 90%CIs were 97.62% to 116.25% and 96.96% to 115.38%. According to the criteria for bioequivalence (80.00% to 125.00%), the test formulations of clopidogrel and Plavix were determined to be bioequivalent. [ABSTRACT FROM AUTHOR]

For grape bunches, a loose architecture is one of the most important physical barriers to avoid fungal infections, making the phenotyping of grape bunches, i.e., the derivation of the morphological attributes, a major goal for breeders. The stem skeleton plays an important role in determining the architecture, but is for grape bunches with berries ready for harvest usually completely occluded by the berries, making it invisible in the data. We introduce geometrical and topological constraints to encode knowledge about geometry and topology of the plant organs to foster efficient sampling of infinitely large hypotheses spaces for target objects with a high amount of self-occlusion and high within-class-scatter. To further support the reconstruction process, we introduce a new variant of the Reversible-Jump-Markov-Chain-Monte-Carlo algorithm with locally optimised jumps, meaning that after using a jump to select a model, a parameter optimisation is performed on the changed parts. We show the usability of our method by deriving established phenotypes, like berry diameters and average pedicle length, from scans created in a lab environment, yielding promising Pearson correlation coefficients between 0.7 and 0.9 on 52 grape bunches spread over four grapevine cultivars. Our approach reduces the active working time required for grape phenotyping by the factor of 12 compared to the manual method currently used at the Institute for Grapevine Breeding Geilweilerhof in Siebeldingen. This speed-up can be increased even more by taking scans in the field. On this application, we achieve first results that are for symmetrical grape bunches comparable to lab scans. • 3D reconstruction of grape bunches including the stem skeleton. • Constraint-based optimization to deal with high within-class-scatter. • Two-phased approach for model selection with local optimisation. • Robust results on 52 grape bunches spread over 4 cultivars. • Promising first results for field scans on 23 grape bunches spread over 3 cultivars. [ABSTRACT FROM AUTHOR]

The highly ambiguous nature of boundaries and similar objects is difficult to address in some ultrasound image segmentation tasks, such as neck muscle segmentation, leading to unsatisfactory performance. Thus, this paper proposes a two-stage network called SCCNet (self-correction context network) using a self-correction boundary preservation module and class-context filter to alleviate these problems. The proposed self-correction boundary preservation module uses a dynamic key boundary point (KBP) map to increase the capability of iteratively discriminating ambiguous boundary points segments, and the predicted segmentation map from one stage is used to obtain a dynamic class prior filter to improve the segmentation performance at Stage 2. Finally, three datasets, Neck Muscle, CAMUS and Thyroid, are used to demonstrate that our proposed SCCNet outperforms other state-of-the art methods, such as BPBnet, DSNnet, and RAGCnet. Our proposed network shows at least a 1.2–3.7% improvement on the three datasets, Neck Muscle, Thyroid, and CAMUS. The source code is available at https://github.com/lijixing0425/SCCNet. • First, we proposed a new Self-Correction boundary preservation module, named DBPB, which is an iterative training strategy proved to have effect on decreasing ambiguous boundary problem for Ultrasound image segmentation with high-variability. • Second, we propose a new Dynamic Class Prior Filter(DCPF) module that it incorporates a class-level context prior to construct the dynamic multiscale filter. The proposed DCPF outperforms DCM (Dynamic Convolutional Module), and other popular context modules for ultrasound image segmentation with high-variability,proved by our ablation experiments. • Third, we demonstrate that the proposed SCCNet, considering boundary and context modules outperforms the-state-of-the-art networks such as BPBnet, RAGCnet which only considering one of context and boundary modules. Meanwhile, SCCNet outperforms LFB-Neton CAMUS dataset, further demonstrating that our method consistently outperforms the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Myroxylon balsamum is in great demand in Central America as its botanical and wood properties are useful in the pharmaceutical, timber and cosmetics industries. In Colombia, it is classified as near threatened (NT) due to over-exploitation for resin or wood, or habitat destruction in the department of Sucre. A guide was necessary to establish propagation practices for population restoration in natural areas. Here we quantify and analyze the germination behavior of M. balsamum. During the germination process, testa rupture occurred 15 days after sowing; obtaining a germination percentage of 77, 2% and germination rate of 23.3 days. The coefficient of variation for variable seedling height (AP), root length (LR), number of leaves (NH) and number of nodes per seedling (NN) generally showed a wide dispersion, but it was greater in the variables LR y NN. This high behavioural diversity maybe due to the provenance of the seed by different mother plants, their maturity or differences in genetic and physiological characteristics. [ABSTRACT FROM AUTHOR]

Abstract: Efficient system management requires continuous knowledge about the state of system and application resources that are typically represented through time series obtained by monitors. Capacity planning studies, forecasting, state aggregation, anomaly and event detection would be facilitated by evidence of data correlations. Unfortunately, the high variability characterizing most monitored time series affects the accuracy and robustness of existing correlation solutions. This paper proposes an innovative approach that is especially tailored to detect linear and non-linear correlation between time series characterized by high variability. We compare the proposed solution and existing algorithms in terms of accuracy and robustness for several synthetic and real settings characterized by low and high variability, linear and non-linear correlation. The results show that our proposal guarantees analogous performance for low variable time series, and improves state of the art in finding correlations in highly variable domains that are of interest for the application context. [Copyright &y& Elsevier]

A bioequivalence study of two verapamil formulations (generic verapamil tablets and Isoptin® tablets) was performed by comparing pharmacokinetic parameters of the parent drug and its major metabolite, norverapamil following a single dose administration of 80 mg verapamil hydrochloride in 22 healthy volunteers according to a randomized, two-period, crossover-design study. Moreover, the feasibility of proving bioequivalence of verapamil oral dosing form by means of norverapamil pharmacokinetic parameters was evaluated. Concentrations of verapamil and norverapamil were quantified in plasma using a validated high-performance liquid chromatography (HPLC) with fluorescence detection. The 90% CIs for the log-transformed ratios of verapamil Cmax (maximum plasma concentration) and AUC0-∞(area under the plasma concentration-versus-time curve from time zero to the infinity) were 73 to 101 and 80 to 103, respectively. Similarly, the corresponding ranges for norverapamil were 80-100 and 84-103, respectively. According to the parent drug data, the 90% confidence intervals around the geometric mean ratio of AUC happened to fit within preset bioequivalence limits of 80-125%, whereas those for Cmax did not. The 90% confidence intervals for both Cmax and AUC of norverapamil met preset bioequivalence limits. The AUC and Cmax of metabolite, when compared to parent drug, showed a much lower degree of variability and the 90% confidence intervals of the metabolite were therefore narrower than those of the parent drug. These observations indicate that bioequivalence studies using metabolite, norverapamil, could be a more suitable and preferable approach to assess bioequivalence of verapamil formulations due to its much lower variability and therefore lower number of volunteers that are required to conduct the study. [ABSTRACT FROM AUTHOR]

Background Baclofen is a GABA-B receptor agonist used in the treatment of spasticity. Recently, baclofen is used out of its label to decrease craving of alcoholic patients. Its optimal use in these patients requires further pharmacokinetic information. The objective of this study was to characterize the pharmacokinetics of baclofen in alcohol-dependent patients. Randomized clinical trials are ongoing to evaluate the efficacy for this new indication. Methods Thirty-seven outpatients (weight: 74.0 kg [42.0 to 104.0]; age: 49 years [31 to 68]) followed in the addictology unit were studied. Total mean dose of 77.9 mg (30 to 240) per day was administered by oral route. Therapeutic drug monitoring allowed the measurement of 139 plasma concentrations. The following covariates were evaluated: demographic data (age, body weight, height, sex), biological data (creatinine, urea, AST, ALT, albumin, PR, VGM, PAL, CDT, GGT), and tobacco consumption (number of cigarettes and Fagerstrom test). Pharmacokinetic analysis was performed by using a nonlinear mixed-effect population model ( NONMEM 7.2 software). Results Data were modeled with a 1-compartment pharmacokinetic model. The population typical mean (95% confidence interval [95% CI]) values for clearance ( CL), apparent volume of distribution (V), and rate constant of absorption (Ka) were 9.9 l/h (9.0 to 11.1), 80.7 l (63.6 to 96.9), and 4.6/h (1.5 to 19.9), respectively. The interindividual variability of CL (95% CI) and V (95% CI), and residual variability (95% CI) were 56.0% (47.9 to 60.7), 68.3% (48.7 to 80.1), and 0.096 mg/l (0.079 to 0.107), respectively. Conclusions Baclofen exhibited a linear pharmacokinetics with a proportional relationship from 30 to 240 mg per day, the dose range currently used in alcoholic patients. A wide interpatient variability was observed which could not be explained by the covariates. This high variation of baclofen exposure may explain the lack of response observed for some patients. [ABSTRACT FROM AUTHOR]