Absolute pitch (AP), the ability to identify a musical pitch without a reference, has been examined behaviorally in numerous studies for more than a century, yet only a few studies have examined the neuroanatomical correlates of AP. Here, we used MRI and diffusion tensor imaging to investigate structural differences in brains of musicians with and without AP, by means of whole-brain vertex-wise cortical thickness (CT) analysis and tract-based spatial statistics (TBSS) analysis. APs displayed increased CT in a number of areas including the bilateral superior temporal gyrus (STG), the left inferior frontal gyrus, and the right supramarginal gyrus. Furthermore, we found higher fractional anisotropy in APs within the path of the inferior fronto-occipital fasciculus, the uncinate fasciculus, and the inferior longitudinal fasciculus. The findings in gray matter support previous studies indicating an increased left lateralized posterior STG in APs, yet they differ from previous findings of thinner cortex for a number of areas in APs. Finally, we found a relation between the white-matter results and the CT in the right parahippocampal gyrus. In this study, we present novel findings in AP research that may have implications for the understanding of the neuroanatomical underpinnings of AP ability.

We present a novel generic programming implementation of a column-generation algorithm for the generalized staff rostering problem. The problem is represented as a generalized set partitioning model, which is able to capture commonly occurring problem characteristics given in the literature. Columns of the set partitioning problem are generated dynamically by solving a pricing subproblem, and constraint branching in a branch-and-bound framework is used to enforce integrality. The pricing problem is formulated as a novel three-stage nested shortest path problem with resource constraints that exploits the inherent problem structure. A very efficient implementation of this pricing problem is achieved by using generic programming principles in which careful use of the C++ pre-processor allows the generator to be customized for the target problem at compile-time. As well as decreasing run times, this new approach creates a more flexible modeling framework that is well suited to handling the variety of problems found in staff rostering. Comparison with a more-standard run-time customization approach shows that speedups of around a factor of 20 are achieved using our new approach. The adaption to a new problem is simple and the implementation is automatically adjusted internally according to the new definition. We present results for three practical rostering problems. The approach captures all features of each problem and is able to provide high-quality solutions in less than 15 minutes. In two of the three instances, the optimal solution is found within this time frame. (C) 2013 Elsevier B.V. All rights reserved.

Perfect pitch, also known as absolute pitch (AP), refers to the rare ability to identify or produce a musical tone correctly without the benefit of an external reference. AP is often considered to reflect musical giftedness, but it has also been associated with certain disabilities due to increased prevalence of AP in individuals with sensory and developmental disorders. Here, we determine whether individual autistic traits are present in people with AP. We quantified subclinical levels of autism traits using the Autism-Spectrum Quotient (AQ) in three matched groups of subjects: 16 musicians with AP (APs), 18 musicians without AP (non-APs), and 16 non-musicians. In addition, we measured AP ability by a pitch identification test with sine wave tones and piano tones. We found a significantly higher degree of autism traits in APs than in non-APs and non-musicians, and autism scores were significantly correlated with pitch identification scores (r = .46, p = .003). However, our results showed that APs did not differ from non-APs on diagnostically crucial social and communicative domain scores and their total AQ scores were well below clinical thresholds for autism. Group differences emerged on the imagination and attention switching subscales of the AQ. Thus, whilst these findings do link AP with autism, they also show that AP ability is most strongly associated with personality traits that vary widely within the normal population.

Absolute pitch (AP) is the ability to identify or produce pitches of musical tones without an external reference. Active AP (i.e., pitch production or pitch adjustment) and passive AP (i.e., pitch identification) are considered to not necessarily coincide, although no study has properly compared these abilities. Using a novel computerized pitch adjustment test, we investigated active AP ability in musicians with and without AP (ages 18-43). We found a significant correlation between active and passive AP indicating that AP possessors (APs) identify and produce pitch equally well. Furthermore, we found that APs generally undershoot when adjusting musical pitch, a tendency that decreases when musical activity increases. Finally, APs are less accurate when adjusting the pitch to black key targets than to white key targets. Hence, AP ability may be partly practice-dependent and we speculate that APs may benefit from frequent contact with fixed standard chroma to keep in tune.

In the Home Care Crew Scheduling Problem a staff of home carers has to be assigned a number of visits to patients' homes, such that the overall service level is maximised. The problem is a generalisation of the vehicle routing problem with time windows. Required travel time between visits and time windows of the visits must be respected. The challenge when assigning visits to home carers lies in the existence of soft preference constraints and in temporal dependencies between the start times of visits.We model the problem as a set partitioning problem with side constraints and develop an exact branch-and-price solution algorithm, as this method has previously given solid results for classical vehicle routing problems. Temporal dependencies are modelled as generalised precedence constraints and enforced through the branching. We introduce a novel visit clustering approach based on the soft preference constraints. The algorithm is tested both on real-life problem instances and on generated test instances inspired by realistic settings. The use of the specialised branching scheme on real-life problems is novel. The visit clustering decreases run times significantly, and only gives a loss of quality for few instances. Furthermore, the visit clustering allows us to find solutions to larger problem instances, which cannot be solved to optimality. (C) 2011 Elsevier B.V. All rights reserved.

In this article, we formulate the vehicle routing problem with time windows and temporal dependencies. The problem is an extension of the well studied vehicle routing problem with time windows. In addition to the usual constraints, a scheduled time of one visit may restrain the scheduling options of other visits. Special cases of temporal dependencies are synchronization and precedence constraints. Two compact formulations of the problem are introduced and the Dantzig–Wolfe decompositions of these formulations are presented to allow for a column generation‐based solution approach. Temporal dependencies are modeled by generalized precedence constraints. Four different master problem formulations are proposed and it is shown that the formulations can be ranked according to the tightness with which they describe the solution space. A tailored time window branching is used to enforce feasibility on the relaxed master problems. Finally, a computational study is performed to quantitatively reveal strengths and weaknesses of the proposed formulations. It is concluded that, depending on the problem at hand, the best performance is achieved either by relaxing the generalized precedence constraints in the master problem, or by using a time‐indexed model, where generalized precedence constraints are added as cuts when they become severely violated. © 2011 Wiley Periodicals, Inc. NETWORKS, Vol. 58(4), 273–289 2011

Emotions are often understood in relation to conditioned responses. Narrative emotions, however, cannot be reduced to a simple associative relationship between emotion words and their experienced counterparts. Intensity in stories may arise without any overt emotion depicting words and vice versa. In this fMRI study we investigated BOLD responses to naturally fluctuating emotions evoked by listening to a story. The emotional intensity profile of the text was found through a rating study. The validity of this profile was supported by heart rate variability (HRV) data showing a significant correspondence across participants between intensity ratings and HRV measurements obtained during fMRI. With this ecologically valid stimulus we found that narrative intensity was accompanied by activation in temporal cortices, medial geniculate nuclei in the thalamus and amygdala, brain regions that are all part of the system for processing conditioned emotional responses to auditory stimuli. These findings suggest that this system also underpins narrative emotions in spite of their complex nature. Traditional language regions and premotor cortices were also activated during intense parts of the story whereas orbitofrontal cortex was found linked to emotion with positive valence, regardless of level of intensity.

A primary focus within neuroimaging research on language comprehension is on the distribution of semantic knowledge in the brain. Studies have shown that the left posterior middle temporal gyrus (LPMT), a region just anterior to area MT/V5, is important for the processing of complex action knowledge. It has also been found that motion verbs cause activation in LPMT. In this experiment we investigated whether this effect could be replicated in a setting resembling real life language comprehension, i.e. without any overt behavioral task during passive listening to a story. During fMRI participants listened to a recording of the story "The Ugly Duckling". We incorporated a nuisance elimination regression approach for factoring out known nuisance variables both in terms of physiological noise, sound intensity, linguistic variables and emotional content. Compared to the remaining text, clauses containing motion verbs were accompanied by a robust activation of LPMT with no other significant effects, consistent with the hypothesis that this brain region is important for processing motion knowledge, even during naturalistic language comprehension conditions.

This paper describes a new approach for easily creating customised staff rostering column generation programs. In previous work, we have built a large very flexible software system which is tailored at run time to meet the particular needs of a client. This system has proven to be very capable, but is difficult to maintain, and incurs the time penalties of run-time customisation. Our new approach is to customise the software at compile time, allowing compiler optimisations to be fully exploited to give faster code. The code has also proven to be easier to read and debug.

In this paper, we present the Slab Yard Planning and Crane Scheduling Problem. The problem has its origin in steel production facilities with a large throughput. A slab yard is used as a buffer for slabs that are needed in the upcoming production. Slabs are transported by cranes and the problem considered here is concerned with the generation of schedules for these cranes. The problem is decomposed and modeled in two parts, namely a planning problem and a scheduling problem. In the planning problem, a set of crane operations is created to take the yard from its current state to a desired goal state. In the scheduling problem, an exact schedule for the cranes is generated, where each operation is assigned to a crane and is given a specific time of initiation. For both models, a thorough description of the modeling details is given along with a specification of objective criteria. Preliminary tests are run on a generic setup with simulated data. The test results are very promising. The production delays are reduced significantly in the new solutions compared with the corresponding delays observed in a simulation of manual planning.

In this paper, we consider the manpower allocation problem with time windows, job-teaming constraints and a limited number of teams (m-MAPTWTC). Given a set of teams and a set of tasks, the problem is to assign to each team a sequential order of tasks to maximize the total number of assigned tasks. Both teams and tasks may be restricted by time windows outside which operation is not possible. Some tasks require cooperation between teams, and all teams cooperating must initiate execution simultaneously. We present an integer programming model for the problem, which is decomposed using Dantzig–Wolfe decomposition. The problem is solved by column generation in a branch-and-price framework. Simultaneous execution of tasks is enforced by the branching scheme. To test the efficiency of the proposed algorithm, 12 realistic test instances are introduced. The algorithm is able to find the optimal solution in 11 of the test instances. The main contribution of this article is the addition of synchronization between teams in an exact optimization context.

In the Home Care Crew Scheduling Problem (HCCSP) a staff of caretakers has to be assigned a number of tasks, such that the total number of assigned tasks is maximised. The tasks have different locations and positions in time, and travelling time and time windows must be respected. The challenge when assigning tasks to caretakers lies in the existence of several soft constraints and indeed also in timewise constraints connecting the tasks. Preferably all of these constraints are satisfied, however for different reasons, this is not always possible. We call a solution to the problem home care optimal, if it satisfies all soft constraints. The problem originates from the scheduling of tasks in the home care sector and has many similarities with the well-studied Vehicle Routing Problem with Time Windows (VRPTW) and the Crew Scheduling Problem with Time Windows (CSPTW). Former approaches to solving the HCCSP involve the use of heuristic methods. In this thesis, we will show that by using an exact algorithm as the basis and then modifying this intelligently, it is possible to generate home care optimal solutions which are in general better than the solutions found by the use of heuristics. The thesis constitutes a proof-of-concept and only focuses on the efficiency of the algorithm to some extent. The developed exact algorithm is based on a branch-and-price approach using column generation. The algorithm is tested on real-life problem instances supplied by the Danish company Zealand Care and we obtain solutions that are near to home care optimal in most cases. The problem is decomposed into a master and a subproblem. We model a very general precedence constraint that captures all timewise constraints from real-life, and we handle precedence constraints in the branching, which we have not seen elsewhere in the literature. We devise an exact label setting algorithm for solving the Elementary Shortest Path Problem with Resource Constraints (ESPPRC) subproblem. Solving the subproblem constitutes a substantial impact on the overall running time of the branch-and-price algorithm. To counteract this, intelligent reductions of the ESPPRC networks are introduced. When reducing the ESPPRC networks, the number of unassigned tasks may increase, hence the branch-and-price algorithm is extended to handle tasks that are unassigned as a consequence of the reductions of the ESPPRC networks. The reductions in the ESPPRC networks and the changes to the branchand-price algorithm result in improvements of both the quality of the solutions, many of which are close to being home care optimal, and the overall efficiency of the algorithm.

The Manpower Allocation Problem with Time Windows, Job-Teaming Constraints and a limited number of teams (m-MAPTWTC) is a crew scheduling problem faced in several different contexts in the industry. The number of teams is predetermined and hence the objective is to create a schedule that will maximize utilization by leaving as few tasks uncompleted as possible. The schedule must respect working hours of the teams, transportation time between locations, and skill requirements and time windows of the tasks. Furthermore, some tasks are completed by multiple cooperating teams. Cooperating teams must initiate work simultaneously and hence this must be maintained in the schedule. The problem is solved using column generation and Branch-and-Bound. Optimal solutions are found in 11 of 12 test instances originating from real-life problems. The paper illustrates a way to exploit the close relations between scheduling and vehicle routing problems. The formulation as a routing problem gives a methodological benefit, leading to optimal solutions. A constraint on synchronization is imposed and successfully dealt with in the branching scheme.

The p/q-ACTIVE uncapacitated facility location problem is the problem of locating p facilities on n possible sites each serving at least q of the m clients at the minimum cost. The problem is an extension of the uncapacitated facility location problem (UFL) where constraints on the number of facilities and their minimum activity have been added. A use of this formulation could be the opening of p new schools where each must have at least q pupils. p/q-ACTIVE is NP-hard like the UFL.In this paper we present a thorough investigation of the p/q-ACTIVE UFL and propose a heuristic solution method. Different geometric and random cost problem instances are considered. Experiments show that 60% of the problems can be solved to optimality just by solving the corresponding LP-relaxation. Using a simple local search heuristic, the remaining geometric problems are solved with an average gap of 0.1% to a lower bound found by LP-relaxation. An effort is put into isolating problem types that are hard to solve. Problems with low p, p - q close to m combined with clustered clients or a low variation in the facility opening cost are most likely to give results worse than average. Gaps up to 8% are observed in the worst cases. (c) 2006 Elsevier B.V. All rights reserved.