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Obviously, the complexity of mathematical database cost models increases with the evolution of the database technology brought by emerging hardware and the new deployment platforms (ex. Cloud). This finding raises questions about the reliability of past Cost Models (CMs). Indeed, redesigning a database CM to evaluate the quality of service (QoS) attributes (i.e. response time, energy, sizing, etc.) is becoming a challenging task. First, because developers directly implement the CM by hard coding inside a DBMS without a prior design. Second, due to a lack of a stepwise development process to support an incremental CM design and continuous testing to diagnose errors that occur at each design stage. Moreover, reusing CMs for other purposes is a major issue that necessitates investigations to allow designers reusing and adapting CMs according to their needs. To take up these challenges, we propose a model-based framework for incremental design and continuous testing of Database CMs Specifically, we are motivated by proposing an approach that aims at shifting CMs design from an adhoc design to a structured and shared design by using a set of design guidelines inspired from software engineering practices. Finally, we propose to use the DevOps reuse practices (Continuous Integration/Continuous Delivery: CI/CD) to store the CM under design in a repository after each upgrade to be reused, improved, calibrated, and refined for other purposes. We evaluate our approach against common CM features, and we carry out a comparison with some analytical models from the literature. Findings show that our framework provides a high CM prediction accuracy, and identify the right design components with a precision ranging from 85% to 100%.

This work analyses the effect of the fair value and historical cost models, optionally applicable under IAS 40 for investment properties on the market value of Spanish groups of real estate listed companies between 2005 and 2018. The results of the application of the Ohlson Model do not suggest any relationship of financial information with the market value in the pre-crisis and economic crisis periods. However, in the post-crisis period, financial information represented by book value gains relevance, showing a significant positive relationship with the market value of real estate companies, although suggesting a reduction in the asymmetry of financial information in companies using the fair value method. Este trabajo analiza el efecto de los modelos de valor razonable y coste histórico, aplicables opcionalmente según la NIC 40 para las inversiones inmobiliarias, sobre el valor de mercado de los grupos inmobiliarios cotizados españoles entre 2005 y 2018. Los resultados de la aplicación del Modelo de Ohlson no sugieren relación alguna de la información financiera con el valor de cotización en los períodos de pre-crisis y crisis económica. Sin embargo, en el período post-crisis, la información financiera representada por el valor en libros gana en relevancia, mostrando una relación positiva significativa con el valor de mercado de las empresas inmobiliarias, aunque sugiriendo una reducción en la asimetría de la información financiera en las empresas que utilizan el método del valor razonable.

1. Better tools are needed to predict population connectivity in complex landscapes. 'Least-cost modelling' is one commonly employed approach in which dispersal costs are assigned to distinct habitat types and the least-costly dispersal paths among habitat patches are calculated using a geographical information system (GIS). Because adequate data on dispersal are usually lacking, dispersal costs are often assigned solely from expert opinion. Spatially explicit, high-resolution genetic data may be used to infer variation in animal movements. We employ such an approach to estimate habitat-specific migration rates and to develop least-cost connectivity models for desert bighorn sheep Ovis canadensis nelsoni. 2. Bighorn sheep dispersal is thought to be affected by distance and topography. We incorporated both factors into least-cost GIS models with different parameter values and estimated effective geographical distances among 26 populations. We assessed which model was correlated most strongly with gene flow estimates among those populations, while controlling for the effect of anthropogenic barriers. We used the best-fitting model to (i) determine whether migration rates are higher over sloped terrain than flat terrain; (ii) predict probable movement corridors; (iii) predict which populations are connected by migration; and (iv) investigate how anthropogenic barriers and translocated populations have affected landscape connectivity. 3. Migration models were correlated most strongly with migration when areas of at least 10% slope had 1/10th the cost of areas of lower slope; thus, gene flow occurred over longer distances when 'escape terrain' was available. Optimal parameter values were consistent across two measures of gene flow and three methods for defining population polygons. 4. Anthropogenic barriers disrupted numerous corridors predicted to be high-use dispersal routes, indicating priority areas for mitigation. However, population translocations have restored high-use dispersal routes in several other areas. Known intermountain movements of bighorn sheep were largely consistent with predicted corridors. 5. Synthesis and applications. Population genetic data provided sufficient resolution to infer how landscape features influenced the behaviour of dispersing desert bighorn sheep. Anthropogenic barriers that block high-use dispersal corridors should be mitigated, but population translocations may help maintain connectivity. We conclude that developing least-cost models from similar empirical data could significantly improve the utility of these tools.

Fishery enhancement methods are being explored globally to sustain commercial and recreational fisheries through improving the productivity and management of marine populations impacted by anthropogenic stressors. It is expected that access to important Atlantic surfclam fishing grounds will be limited or lost due to growing overlap with offshore wind energy development. This study explores the economic viability of large‐scale hatchery production to improve fishery access and potentially offset additional costs, reduced revenues and potential job losses associated with the displacement of the fishing fleet. Reports and primary literature were used to understand the growth and survival of Atlantic surfclams in hatchery and nursery settings to calculate the scale of hatchery efforts needed to support one million (1M) bushels of fishery‐sized clams (>120 mm). Data on labour, energy, construction and material inputs and costs for hatchery and nursery production were gathered by analysing available literature and information provided by hatchery managers, researchers and others knowledgeable about shellfish hatchery production. A techno‐economic cost model and Monte Carlo analyses were employed to explore average costs and their variability. This study suggests that 374M–2.1B Atlantic surfclams are needed at the end of the hatchery stage to produce 1M bushels of market‐sized product. Total production costs range from$3.7 to $ 15.1M, including$2.9–$ 13.3M in hatchery costs and$800K–$ 1.9M in nursery costs. Under current market conditions, where Atlantic surfclams regularly sell for$14–$ 17/bushel, this analysis suggests that hatchery production could be considered a viable fishery enhancement method that supports human access to the fishery, though several additional questions remain. This study explores the economic viability of large‐scale hatchery production to improve fishery access and potentially offset additional costs, reduced revenues, and potential job losses associated with the displacement of the Atlantic surfclam fishing fleet due to anthropogenic stressors. Total production costs range from$3.7M to $ 15.1M, including$2.9M ‐ $ 13.3M in hatchery costs and$800K‐$ 1.9M in nursery costs. Under current market conditions, where Atlantic surfclams regularly sell for$14‐$ 17/bushel, this analysis suggests that hatchery production could be considered a viable fishery enhancement method that supports human access to the fishery, though several additional questions remain.

Information is power in supply chain operations, negotiations, continuous improvement programs, process improvement, and indeed in all aspects of managing an operation. Accurate and timely information can result in better decisions that translate into the improvement of bottomline results. The development and effective use of cost modeling as a method to understand the cost of products, services, and processes can help drive improvements in the quality and timeliness of decision making. In the supply chain community, an understanding of the actual cost structures of processes, products and services, whether with new or nonpartner suppliers, can facilitate fact-based discussions that are more likely to result in agreements that are competitively priced and with fair margins. Further, accurate cost models that are cooperatively developed between supply chain partners can form the basis for joint efforts to reduce non-value-added costs and provide additional focus toward operational improvement.

\"In this second edition, Vic and Chris have done an excellent job of citing the importance of accurate problem identi cation and the need for validated data input for the decision making process--a must read book for those managers responsible for making operational decisions.\" - Richard Bozeman, Jr., Author and Inventor, Retired Chief.

Epistasis between mutations in two genes is thought to reflect an interdependence of their functions. While sometimes epistasis is predictable using mechanistic models, its roots seem, in general, hidden in the complex architecture of biological networks. Here, we ask how epistasis can be quantified based on the mathematical dependence of a system-level trait (e.g. fitness) on lower-level traits (e.g. molecular or cellular properties). We first focus on a model in which fitness is the difference between a benefit and a cost trait, both pleiotropically affected by mutations. We show that despite its simplicity, this model can be used to analytically predict certain properties of the ensuing distribution of epistasis, such as a global negative bias, resulting in antagonism between beneficial mutations, and synergism between deleterious ones. We next extend these ideas to derive a general expression for epistasis given an arbitrary functional dependence of fitness on other traits. This expression demonstrates how epistasis relative to fitness can emerge despite the absence of epistasis relative to lower level traits, leading to a formalization of the concept of independence between biological processes. Our results suggest that epistasis may be largely shaped by the pervasiveness of pleiotropic effects and modular organization in biological networks.

Supply chain network design is to determine factories and distribution centers to produce and distribute products, in order to satisfy the demand of customers to some extent. Supply chain network design plays an important strategic role in supply chain management and faces kinds of uncertainties, such as uncertain demand and cost. In order to deal with the impact of uncertain factors, this paper considers the supply chain network design under hybrid uncertainties, namely, the objective randomness of retailers’ demand and the subjective uncertainties of operating costs. We construct three models to handle managers’ different needs. They are the expected cost minimization model that minimizes the expected total cost, the β -cost minimization model that minimizes the β -cost which means that the chance measure of the actual cost not exceeding the cost is not less than the confidence level β , and the chance measure maximization model that maximizes the chance measure of the actual cost not exceeding the given cost. This paper then transforms them into deterministic classes by uncertainty theory, and several numerical examples are presented to verify the validity of the models and algorithm.

The giant panda (Ailuropoda melanoleuca), is one of the world's most endangered species. Habitat loss and fragmentation have reduced its numbers, shrunk its distribution, and separated the population into isolated subpopulations. Such isolated, small populations are in danger of extinction due to random demographic factors and inbreeding. We used least-cost modeling as a systematic approach to incorporate satellite imagery and data on ecological and behavioral parameters of the giant panda collected during more than 10 years of field research to design a conservation landscape for giant pandas in the Minshan Mountains. We identified 8 core habitats and 4 potential linkages that would link core habitats CH3, CH4, and CH5 with core habitats CH6, CH7, and CH8. Establishing and integrating the identified habitats with existing reserves would create an efficient reserve network for giant panda conservation. The core habitats had an average density of 4.9 pandas/100 km² and contained approximately 76.6% of the giant panda population. About 45% of the core habitat (3245.4 km²) existed outside the current nature reserves network. Total estimated core habitat decreased between 30.4 and 44.5% with the addition of residential areas and road networks factored into the model. A conservation area for giant panda in the Minshan Mountains should aim to ensure habitat retention and connectivity, improve dispersal potential of corridors, and maintain the evolutionary potential of giant pandas in the face of future environmental changes.

The aim of this article is to show the impact of adjustments in construction projects. The methodology and impact of costs in construction are analyzed by applying the formula for calculating the cost of price adjustments based on inflation. The cost of a project is defined by its direct and indirect costs, but in projects carried out by the state, there are adjustments to the cost. The adjustment cost is intended to take over a price increase due to changes that are not related to the project and are related to the market economy of the construction industry.