An iterative heuristic for passenger-centric train timetabling with integrated adaption times

In this paper we present a method to construct a periodic timetable from a tactical planning perspective. We aim at constructing a timetable that is feasible with respect to infrastructure constraints and minimizes average perceived passenger travel time. In addition to in-train and transfer times, our notion of perceived passenger time includes the adaption time (waiting time at the origin station). Adaption time minimization allows us to avoid strict frequency regularity constraints and, at the same time, to ensure regular connections between passengers’ origins and destinations. The combination of adaption time minimization and infrastructure constraints satisfaction makes the problem very challenging. The described periodic timetabling problem can be modelled as an extension of a Peri- odic Event Scheduling Problem (PESP) formulation, but requires huge computing times if it is directly solved by a general-purpose solver for instances of realistic size. In this paper, we propose a heuristic approach consisting of two phases that are executed iteratively. First, we solve a mixed-integer linear program to determine an ideal timetable that mini- mizes the average perceived passenger travel time but neglects infrastructure constraints. Then, a Lagrangian-based heuristic makes the timetable feasible with respect to infras- tructure constraints by modifying train departure and arrival times as little as possible. The obtained feasible timetable is then evaluated to compute the resulting average per- ceived passenger travel time, and a feedback is sent to the Lagrangian-based heuristic so as to possibly improve the obtained timetable from the passenger perspective, while still respecting infrastructure constraints. We illustrate the proposed iterative heuristic approach on real-life instances of Netherlands Railways and compare it to a benchmark approach, showing that it finds a feasible timetable very close to the ideal one

School functioning in 8- to 18-year-old children born after in vitro fertilization

The aim of this study was to examine the school functioning of 8- to 18-year-old children born after in vitro fertilization (IVF). We compared 233 children born after IVF to 233 matched control children born spontaneously from parents with fertility problems on measures of education level, general cognitive ability, school performance (need for extra help, repeating a grade, special education), and rates of learning and developmental disorders. No differences were found between IVF and control children on these measures of school functioning. More than 60% of adolescents at secondary school attended high academic levels (with access to high school or university). We conclude that children and adolescents born after IVF show good academic achievement and general cognitive ability. They do not experience any more educational limitations than the naturally conceived children and adolescents of the control group. The tendency of reassuring school functioning already found in younger IVF children has been shown to continue at secondary school age

Impaired sleep affects quality of life in children during maintenance treatment for acute lymphoblastic leukemia: an exploratory study

Contains fulltext : 97021.pdf (publisher's version ) (Open Access)BACKGROUND: With the increase of pediatric cancer survival rates, late effects and quality of life (QoL) have received more attention. Disturbed sleep in pediatric cancer is a common clinical observation, but research on this subject is sparse. In general, sleep problems can lead to significant morbidity and are associated with impaired QoL. Information on sleep is essential to develop interventions to improve QoL. METHODS: Children (2-18 years) with acute lymphoblastic leukemia (ALL) were eligible for this multi-center study. The Children's Sleep Habits Questionnaire (CSHQ), Child Health Questionnaire (CHQ) and Pediatric Quality of Life Inventory 3.0 Acute Cancer Version (PedsQL) were used to assess sleep and QoL halfway through maintenance therapy. Sleep and QoL were measured during and after dexamethasone treatment (on-dex and off-dex). RESULTS: Seventeen children participated (age 6.7 +/- 3.3 years, 44% boys). Children with ALL had more sleep problems and a lower QoL compared to the norm. There were no differences on-dex and off-dex. Pain (r = -0.6; p = 0.029) and worry (r = -0.5; p = 0.034) showed a moderate negative association with sleep. Reduced overall QoL was moderately associated with impaired overall sleep (r = -0.6; p = 0.014) and more problems with sleep anxiety (r = -0.8; p = 0.003), sleep onset delay (r = -0.5; p = 0.037), daytime sleepiness (r = -0.5; p = 0.044) and night wakenings (r = -0.6; p = 0.017). CONCLUSION: QoL is impaired in children during cancer treatment. The results of this study suggest that impaired sleep may be a contributing determinant. Consequently, enhanced counseling and treatment of sleep problems might improve QoL. It is important to conduct more extensive studies to confirm these findings and provide more detailed information on the relationship between sleep and QoL, and on factors affecting sleep in pediatric ALL and in children with cancer in general

Timetabling for strategic passenger railway planning

In research and practice, public transportation planning is executed in a series of steps, which are often divided into the strategic, the tactical, and the operational planning phase. Timetables are normally designed in the tactical phase, taking into account a given line plan, safety restrictions arising from infrastructural constraints, as well as regularity requirements and bounds on transfer times. In this paper, however, we propose a timetabling approach that is aimed at decision making in the strategic phase of public transportation planning and to determine an outline of a timetable that is good from the passengers’ perspective. Instead of including explicit synchronization constraints between train runs (as most timetabling models do), we include the adaption time (waiting time at the origin station) in the objective function to ensure regular connections between passengers’ origins and destinations. We model the problem as a mixed integer quadratic program and linearize it. Furthermore we propose a heuristic to generate starting solutions. We illustrate the trade-offs between dwell times and regularity of trains in two case studies based on the Dutch railway network

Effect of dexamethasone on quality of life in children with acute lymphoblastic leukaemia: a prospective observational study

<p>Abstract</p> <p>Background</p> <p>Glucocorticoids are important in the treatment of childhood acute lymphoblastic leukaemia (ALL). However, cyclic administration of high dose glucocorticoids may cause rapid and substantial changes in quality of life (QoL). The maintenance phase of the Dutch ALL-9 protocol consisted of alternating two weeks on and five weeks off dexamethasone (6 mg/m²/day). The present study was performed to assess the effect of dexamethasone on QoL during treatment for ALL according to this protocol.</p> <p>Methods</p> <p>In a multicentre prospective cohort study, QoL was assessed halfway (T1) and at the end of the two-year treatment (T2). A generic (Child Health Questionnaire) and disease specific (PedsQL™ cancer version) QoL questionnaire were used to assess QoL in two periods: on and off dexamethasone, respectively.</p> <p>Results</p> <p>41 children (56% males) were evaluated, mean age at diagnosis was 5.6 years. The CHQ physical and psychosocial summary scores were significantly lower than population norms. At T1 and T2, overall QoL showed no significant change. However, regarding specific domains (pain, cognitive functioning, emotion/behaviour and physical functioning) QoL decreased over time. QoL was significantly more impaired during periods on dexamethasone.</p> <p>Conclusion</p> <p>Dexamethasone was associated with decreased QoL. At the end of treatment, reported QoL during dexamethasone deteriorated even more on certain scales (pain, cognitive functioning, emotion/behaviour and physical functioning). Knowledge of the specific aspects of QoL is essential to improve counselling and coping in paediatric oncology. Adverse effects of specific drugs on QoL should be taken into account when designing treatment protocols.</p

A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics

OBJECTIVES: To determine the value of a deep learning masked (DLM) auto-fixed volume of interest (VOI) segmentation method as an alternative to manual segmentation for radiomics-based diagnosis of clinically significant (CS) prostate cancer (PCa) on biparametric magnetic resonance imaging (bpMRI). MATERIALS AND METHODS: This study included a retrospective multi-center dataset of 524 PCa lesions (of which 204 are CS PCa) on bpMRI. All lesions were both semi-automatically segmented with a DLM auto-fixed VOI method (averaging < 10 s per lesion) and manually segmented by an expert uroradiologist (averaging 5 min per lesion). The DLM auto-fixed VOI method uses a spherical VOI (with its center at the location of the lowest apparent diffusion coefficient of the prostate lesion as indicated with a single mouse click) from which non-prostate voxels are removed using a deep learning-based prostate segmentation algorithm. Thirteen different DLM auto-fixed VOI diameters (ranging from 6 to 30 mm) were explored. Extracted radiomics data were split into training and test sets (4:1 ratio). Performance was assessed with receiver operating characteristic (ROC) analysis. RESULTS: In the test set, the area under the ROC curve (AUCs) of the DLM auto-fixed VOI method with a VOI diameter of 18 mm (0.76 [95% CI: 0.66-0.85]) was significantly higher (p = 0.0198) than that of the manual segmentation method (0.62 [95% CI: 0.52-0.73]). CONCLUSIONS: A DLM auto-fixed VOI segmentation can provide a potentially more accurate radiomics diagnosis of CS PCa than expert manual segmentation while also reducing expert time investment by more than 97%. KEY POINTS: * Compared to traditional expert-based segmentation, a deep learning mask (DLM) auto-fixed VOI placement is more accurate at detecting CS PCa. * Compared to traditional expert-based segmentation, a DLM auto-fixed VOI placement is faster and can result in a 97% time reduction. * Applying deep learning to an auto-fixed VOI radiomics approach can be valuable

Allogeneic cord blood transfusions for extremely preterm neonates: an extremely promising proof of concept

Thrombosis and Hemostasi

Preparing children with a mock scanner training protocol results in high quality structural and functional MRI scans

We evaluated the use of a mock scanner training protocol as an alternative for sedation and for preparing young children for (functional) magnetic resonance imaging (MRI). Children with severe mental retardation or developmental disorders were excluded. A group of 90 children (median age 6.5 years, range 3.65–14.5 years) participated in this study. Children were referred to the actual MRI investigation only when they passed the training. We assessed the pass rate of the mock scanner training sessions. In addition, the quality of both structural and functional MRI (fMRI) scans was rated on a semi-quantitative scale. The overall pass rate of the mock scanner training sessions was 85/90. Structural scans of diagnostic quality were obtained in 81/90 children, and fMRI scans with sufficient quality for further analysis were obtained in 30/43 of the children. Even in children under 7 years of age, who are generally sedated, the success rate of structural scans with diagnostic quality was 53/60. FMRI scans with sufficient quality were obtained in 23/36 of the children in this younger age group. The association between age and proportion of children with fMRI scans of sufficient quality was not statistically significant. We conclude that a mock MRI scanner training protocol can be useful to prepare children for a diagnostic MRI scan. It may reduce the need for sedation in young children undergoing MRI. Our protocol is also effective in preparing young children to participate in fMRI investigations

[11C]Flumazenil brain uptake is influenced by the blood-brain barrier efflux transporter P-glycoprotein

Background: