Novel genes and novel pathogenetic mechanisms in adult-onset primary dystonia

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Genetic issues in the diagnosis of dystonias

Dystonias are heterogeneous hyperkinetic movement disorders characterized by involuntary muscle contractions which result in twisting and repetitive movements and abnormal postures. Several causative genes have been identified, but their genetic bases still remain elusive. Primary Torsion Dystonias (PTDs), in which dystonia is the only clinical sign, can be inherited in a monogenic fashion, and many genes and loci have been identified for autosomal dominant (DYT1/TOR1A; DYT6/THAP1; DYT4/TUBB4a; DYT7; DYT13; DYT21; DYT23/CIZ1; DYT24/ANO3; DYT25/GNAL) and recessive (DYT2; DYT17) forms. However most sporadic cases, especially those with late-onset, are likely multifactorial, with genetic and environmental factors interplaying to reach a threshold of disease. At present, genetic counseling of dystonia patients remains a difficult task. Recently non-motor clinical findings in dystonias, new highlights in the pathophysiology of the disease, and the availability of high-throughput genome-wide techniques are proving useful tools to better understand the complexity of PTD genetics. We briefly review the genetic basis of the most common forms of hereditary PTDs, and discuss relevant issues related to molecular diagnosis and genetic counseling

Minority Games, Local Interactions, and Endogenous Networks

In this paper we study a local version of the Minority Game where agents are placed on the nodes of a directed graph. Agents care about beingin the minority of the group of agents they are currently linked to and employ myopic best-reply rules to choose their next-period state. We show that, in this benchmark case, the smaller the size of local networks, the larger long-run population-average payoffs. We then explore the collective behavior of the system when agents can: (i) assign weights to each link they hold and modify them over time in response to payoff signals; (ii) delete badly-performing links (i.e. opponents) and replace them with randomly chosen ones. Simulations suggest that, when agents are allowed to weight links but cannot delete/replace them, the system self-organizes into networked clusters which attain very high payoff values. These clustered configurations are not stable and can be easily disrupted, generating huge subsequent payoff drops. If however agents can (and are sufficiently willing to) discard badly performing connections, the system quickly converges to stable states where all agents get the highest payoff, independently of the size of the networks initially in placeMinority Games, Local Interactions, Non-Directed Graphs, Endogenous Networks, Adaptive Systems.

Beam search heuristics for the single machine scheduling problem with linear earliness and quadratic tardiness costs

In this paper, we consider the single machine scheduling problem with linear earliness and quadratic tardiness costs, and no machine idle time. We present heuristic algorithms based on the beam search technique. These algorithms include classic beam search procedures, as well as the filtered and recovering variants. Several dispatching rules are considered as evaluation functions, in order to analyse the effect of different rules on the effectiveness of the beam search algorithms. The computational results show that using better rules indeed improves the performance of the beam search heuristics. The detailed, filtered and recovering beam search procedures outperform the best existing heuristic. The best results are given by the recovering and detailed variants, which provide objective function values that are quite close to the optimum. For small to medium size instances, either of these procedures can be used. For larger instances, however, the detailed beam search algorithm requires excessive computation times, and the recovering beam search procedure then becomes the heuristic of choice.scheduling, single machine, linear earliness, quadratic tardiness, beam search, heuristics

Beam search heuristics for quadratic earliness and tardiness scheduling

In this paper, we present beam search heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. These heuristics include classic beam search procedures, as well as filtered and recovering algorithms. We consider three dispatching heuristics as evaluation functions, in order to analyse the effect of different rules on the performance of the beam search procedures. The computational results show that using better dispatching heuristics improves the effectiveness of the beam search algorithms. The performance of the several heuristics is similar for instances with low variability. For high variability instances, however, the detailed, filtered and recovering beam search procedures clearly outperform the best existing heuristic. The detailed beam search algorithm performs quite well, and is recommended for small to medium size instances. For larger instances, however, this procedure requires excessive computation times, and the recovering beam search algorithm then becomes the heuristic of choice.scheduling, heuristics, beam search, single machine, quadratic earliness, quadratic tardiness

An exact approach for single machine scheduling with quadratic earliness and tardiness penalties

In this paper, we consider the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. We propose two different lower bounds, as well as a lower bounding procedure that combines these two bounds. Optimal branch-and-bound algorithms are then presented. These algorithms incorporate the proposed lower bound, as well as an insertion-based dominance test. The lower bounding procedure and the branch-and-bound algorithms are tested on a wide set of randomly generated problems. The computational results show that the branch-and-bound algorithms are capable of optimally solving, within reasonable computation times, instances with up to 20 jobs.scheduling, single machine, quadratic earliness and tardiness, lower bounds, branch-and-bound

Using Instance Statistics to Determine the Lookahead Parameter Value in the ATC Dispatch Rule: Making a good heuristic better

The Apparent Tardiness Cost (ATC) heuristic is one of the best performing dispatch rules for the weighted tardiness scheduling problem. This heuristic uses a lookahead parameter whose value must be specified. In this paper we develop a function that maps some instance statistics into an appropriate value for the lookahead parameter. This function is compared with some fixed values that have been previously used. The computational results show that the ATC heuristic performs better when the lookahead parameter value is determined by the proposed function.scheduling, weighted tardiness, dispatch rule, instance statistics