Good practices for a literature survey are not followed by authors while preparing scientific manuscripts

The number of citations received by authors in scientific journals has become a major parameter to assess individual researchers and the journals themselves through the impact factor. A fair assessment therefore requires that the criteria for selecting references in a given manuscript should be unbiased with respect to the authors or the journals cited. In this paper, we advocate that authors should follow two mandatory principles to select papers (later reflected in the list of references) while studying the literature for a given research: i) consider similarity of content with the topics investigated, lest very related work should be reproduced or ignored; ii) perform a systematic search over the network of citations including seminal or very related papers. We use formalisms of complex networks for two datasets of papers from the arXiv repository to show that neither of these two criteria is fulfilled in practice

Soft systems methodology: a context within a 50-year retrospective of OR/MS

Soft systems methodology (SSM) has been used in the practice of operations research and management science OR/MS) since the early 1970s. In the 1990s, it emerged as a viable academic discipline. Unfortunately, its proponents consider SSM and traditional systems thinking to be mutually exclusive. Despite the differences claimed by SSM proponents between the two, they have been complementary. An extensive sampling of the OR/MS literature over its entire lifetime demonstrates the richness with which the non-SSM literature has been addressing the very same issues as does SSM

Optimal management of an insurer's exposure in a competitive general insurance market

The qualitative behavior of the optimal premium strategy is determined for an insurer in a finite and an infinite market using a deterministic general insurance model. The optimization problem leads to a system of forward-backward differential equations obtained from Pontryagin’s Maximum Principle. The focus of the modelling is on how this optimization problem can be simplified by the choice of demand function and the insurer’s objective. Phase diagrams are used to characterize the optimal control. When the demand is linear in the relative premium, the structure of the phase diagram can be determined analytically. Two types of premium strategy are identified for an insurer in an infinite market, and which is optimal depends on the existence of equilibrium points in the phase diagram. In a finite market there are four more types of premium strategy, and optimality depends on the initial exposure of the insurer and the position of a saddle point in the phase diagram. The effect of a nonlinear demand function is examined by perturbing the linear price function. An analytical optimal premium strategy is also found using inverse methods when the price function is nonlinear

Protein Design Using Continuous Rotamers

Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE. Availability: Software is available under the Lesser GNU Public License v3. Contact the authors for source code

Exploring the constraint profile of winter sports resort tourist segments

Many studies have confirmed the importance of market segmentation both theoretically and empirically. Surprisingly though, no study has so far addressed the issue from the perspective of leisure constraints. Since different consumers face different barriers, we look at participation in leisure activities as an outcome of the negotiation process that winter sports resort tourists go through, to balance between related motives and constraints. This empirical study reports the findings on the applicability of constraining factors in segmenting the tourists who visit winter sports resorts. Utilizing data from 1,391 tourists of winter sports resorts in Greece, five segments were formed based on their constraint, demographic and behavioral profile. Our findings indicate that such segmentation sheds light on factors that could potentially limit the full utilization of the market. To maximize utilization, we suggest customizing marketing to the profile of each distinct winter sports resort tourist segment that emerge

Volatility in the Housing Market: Evidence on Risk and Return in the London Sub-market

The impact of volatility in housing market analysis is reconsidered via examination of the risk-return relationship in the London housing market is examined. In addition to providing the first empirical results for the relationship between risk (as measured by volatility) and returns for this submarket, the analysis offers a more general message to empiricists via a detailed and explicit evaluation of the impact of empirical design decisions upon inferences. In particular, the negative risk-return relationship discussed frequently in the housing market literature is examined and shown to depend upon typically overlooked decisions concerning components of the empirical framework from which statistical inferences are drawn

Using clustering of rankings to explain brand preferences with personality and socio-demographic variables

The primary aim of market segmentation is to identify relevant groups of consumers that can be addressed efficiently by marketing or advertising campaigns. This paper addresses the issue whether consumer groups can be identified from background variables that are not brand-related, and how much personality vs. socio-demographic variables contribute to the identification of consumer clusters. This is done by clustering aggregated preferences for 25 brands across 5 different product categories, and by relating socio-demographic and personality variables to the clusters using logistic regression and random forests over a range of different numbers of clusters. Results indicate that some personality variables contribute significantly to the identification of consumer groups in one sample. However, these results were not replicated on a second sample that was more heterogeneous in terms of socio-demographic characteristics and not representative of the brands target audience