bluuebunny/crossref_metadata_2025_split huggingface dataset:
The cooperative capital constraint revisited
Authors: Li Ziran , Jacobs Keri L , Artz Georgeanne M 
Published: June 2015

Purpose
– There is little reason a priori to expect that a cooperative firm’s capital needs are different from a non-cooperative firm’s needs if the two firms are otherwise similar in function and size and operate within similar market economies. However, the notion that cooperatives face capital constraints that investor-owned firms (IOFs) do not is a persistent theme in the literature. The paper aims to discuss these issues.

Design/methodology/approach
– The authors revisit this hypothesis with an empirical examination of capital constraints in a panel data set of US agricultural supply and grain cooperatives and IOFs.

Findings
– The findings are mixed. While the authors find little to suggest that cooperatives face financial constraints on borrowing in the short run, relative to IOFs, the authors do find some evidence that for long-term investments, a capital constraint may exist.

Originality/value
– These short and long run differences have implications for the survival and growth of agricultural cooperatives. While in the short run, access to debt financing allows these firms to operative profitably, ultimately long-term large investments in technology and fixed assets will be required to maintain competitiveness in this industry.
Real estate risk: heavy tail modelling using Excel
Authors: Brown Roger , Klingenberg Beate 
Published: June 2015

Purpose– The purpose of this paper is to present a practice briefing in the form of a user’s manual for Excel-based simulation of real estate risk. Based on a generic discounted cash flow model, the simulation incorporates the often ignored heavy tail behaviour of real estate investments, and consolidates Jensen’s inequality. The briefing attempts to explain a model that permits the user to decide whether to include extreme events in real estate risk modelling and how extreme these events may be. Practitioners can generate a variety of modelling outcomes and then choose risk comfort zones in which to contemplate a range of returns.Design/methodology/approach– The paper provides an overview of the underlying mathematical concepts and challenges, as well as on the perspectives on their application from the current academic literature. It offers a step-by-step walk-through of the Excel model (the model being downloadable at:www.mathestate.com).Findings– Existing models for real estate risk modelling fall short with respect to realistic simulation of the probability of extreme events due to challenges in the implementation of stable laws. These former barriers to the implementation of stable laws have been overcome by providing a unique combination of Excel-resident functionalities with a stable pseudo random number generator.Research limitations/implications– Investment advisers no longer need expensive add-ins to estimate risk. The presented Excel model is more robust than common approaches as it considers distribution shapes that are not otherwise easily available. The only apparent limitation is that users need to be familiar with the most basic functionality of Excel.Practical implications– Practitioners are provided with an easy-to-use Excel model that does not require further software add-ins. The model simulates real estate investment returns, based on a more realistic inclusion of risk behaviour. It allows specifying how much extreme value behaviour characterizes the volatility in future projections modelled to guide investment decisions.Social implications– Risk is a cost to society. Many recent news events demonstrate the importance of including extreme values in modelling. The paper attempts to contribute to more realistic risk estimation in real estate investment.Originality/value– This briefing introduces a real estate risk simulation model that includes using stable laws, using Excel, a familiar and widely used platform. Such a model has not previously been reported in the academic or practitioners’ literature.
Property market modelling and forecasting: simple vs complex models
Authors: Jadevicius Arvydas , Huston Simon 
Published: June 2015

Purpose– The commercial property market is complex, but the literature suggests that simple models can forecast it. To confirm the claim, the purpose of this paper is to assess a set of models to forecast UK commercial property market.Design/methodology/approach– The employs five modelling techniques, including Autoregressive Integrated Moving Average (ARIMA), ARIMA with a vector of an explanatory variable(s) (ARIMAX), Simple Regression (SR), Multiple Regression, and Vector Autoregression (VAR) to model IPD UK All Property Rents Index. The Bank Rate, Construction Orders, Employment, Expenditure, FTSE AS Index, Gross Domestic Product (GDP), and Inflation are all explanatory variables selected for the research.Findings– The modelling results confirm that increased model complexity does not necessarily yield greater forecasting accuracy. The analysis shows that although the more complex VAR specification is amongst the best fitting models, its accuracy in producing out-of-sample forecasts is poorer than of some less complex specifications. The average Theil’sU-value for VAR model is around 0.65, which is higher than that of less complex SR with Expenditure (0.176) or ARIMAX (3,0,3) with GDP (0.31) as an explanatory variable models.Practical implications– The paper calls analysts to make forecasts more user-friendly, which are easy to use or understand, and for researchers to pay greater attention to the development and improvement of simpler forecasting techniques or simplification of more complex structures.Originality/value– The paper addresses the issue of complexity in modelling commercial property market. It advocates for simplicity in modelling and forecasting.
To use or not to use: which type of property should you choose?
Authors: Appel-Meulenbroek Rianne , Kemperman Astrid , Kleijn Marleen , Hendriks Els 
Published: June 2015

Purpose
– Corporate real estate (CRE) is a costly and risky asset in need of more rigorous evaluation methods to support strategic decision making for portfolio and asset management. Especially the indirect added value on organizational revenues is hard to quantify, while it is gaining importance. The purpose of this paper is to describe a quantitative technique that predicts office use as input for CRE management (CREM) decisions.

Design/methodology/approach
– After a literature study to identify relevant aspects influencing office use in modern work environments, a Bayesian belief network (BN) is constructed from a large database of 80,907 observations of office use in three organizations in Belgium and the Netherlands. Next specific evidence from future scenarios of organizational change is entered to discuss the application of BN for CRE decision-making processes.

Findings
– This study showed that the use of activity-based offices might be influenced by a complex network of office design variables and user characteristics. The use of the predicting possibilities of a BN model can help CRE managers identify employee behaviour inside their offices. That information is valuable input for future workplace decisions and strategic CREM activities.

Practical implications
– This study provides CRE managers with a model to gain knowledge on office use to get a better grip on how to add value with activity-based office concepts. The results obtained through using such a model can help support decision making on their office layouts.

Originality/value
– Bayesian BNs have not been used in this area of research before. This paper provides both academics and practitioners with valuable insights in the possibilities of this methodology for the field.
Converging sustainability definitions: industry independent dimensions
Authors: John Lijo , Narayanamurthy Gopalakrishnan 
Published: June 2015

Purpose– Sustainability as a construct is still debated and is yet to attain a consensus among researchers and practitioners. Sustainable development has been seen differently by players from different industry sectors. There is need to understand the commonality prevailing on sustainability practices across different industry sectors to arrive at a consensual sustainability definition. The purpose of this paper is to propose four dimensions of sustainability and studies how it captures sustainability practices across key industrial sectors.Design/methodology/approach– Current study argues the case for sustainability using four constructs, namely, economical, environmental, ethical, and social. Subsequently a holistic definition with a model is proposed incorporating the four constructs for sustainability. Studies documenting sustainability practices across industries, namely, automobile, infrastructure, cement and concrete, electronics, mining, paper, pharmaceutical, and logistics were reviewed to validate the applicability of the proposed four construct model across different key industrial sectors.Findings– Current study validates the industry independence of the proposed four constructs of sustainability model through a literature review. Very few studies have documented industry-specific sustainability practices and much lesser have studied the ethical dimension of sustainability. Furthermore, the organizational strategic plan is developed for incorporating the environmental, economical, ethical, and social needs into the organizational business operations at the strategic, tactical, and the operational levels.Research limitations/implications– Proposed model needs to be applied in multiple case organizations from diverse sectors to evaluate its capacity to capture the aspects of sustainability across different sectors. Future study could attempt to understand the interrelationships between the identified constructs and how they impact each other within different industrial sectors.Practical implications– Model linked to organizational business operations at the strategic, tactical, and the operational levels helps in the alignment of the organizational activity towards the strategic intent of the organizational sustainability philosophy in the business ecology. It also helps in equipping the organization to achieve the operational excellence and the strategic business growth at the same time.Originality/value– Current study is unique in its attempt to understand the capability of proposed sustainability dimensions to capture the sustainability practices followed across different industrial sectors.
Adalimumab treatment optimization for psoriasis: Results of a long‐term phase 2/3 Japanese study
Authors: Asahina Akihiko , Ohtsuki Mamitaro , Etoh Takafumi , Gu Yihua , Okun Martin M. , Teixeira Henrique D. , Yamaguchi Yuji , Nakagawa Hidemi 
Published: June 2015

AbstractThe tumor necrosis factor‐α inhibitor, adalimumab, is approved to treat moderate‐to‐severe plaque psoriasis (40 mg every‐other‐week or 80 mg every‐other‐week following inadequate response at 40 mg in Japan). This open‐label extension (OLE) trial evaluated the optimal adalimumab dose for long‐term efficacy and safety in Japanese patients with moderate‐to‐severe plaque psoriasis following a prior 24‐week, phase 2/3, randomized, double‐blind study. Of the 169 patients from the phase 2/3 trial, 147 entered the OLE on 40 mg (n = 89) or 80 mg (n = 58) adalimumab every‐other‐week. Patients on 40 mg with Psoriasis Area and Severity Index (PASI) of less than 50 could escalate to 80 mg. At week 52 (28 of OLE), patients entering the OLE on 80 mg were reduced to 40 mg, with the option to re‐escalate. For patients entering the OLE on 40 mg, final PASI 50/75/90 response rates were 85.1%/73.3%/60.4%, respectively, including effects of dose escalation. Among patients whose dose was escalated, final PASI 50/75/90 response rates were 70.0%/53.3%/36.7%, respectively. For patients entering the OLE on 80 mg, final PASI 50/75/90 response rates were 92.5%/84.9%/73.6%, respectively, including effects of dose re‐escalation. Overall incidence rates of adverse events (AE) and injection‐site reaction AE declined over time; rates for serious AE and infections were generally stable. Clinically meaningful efficacy of adalimumab was sustained to 4 years. Dose escalation to 80 mg every‐other‐week for patients with suboptimal response to 40 mg every‐other‐week, and dose reduction to 40 mg every‐other‐week for patients satisfactorily controlled on 80 mg every‐other‐week, are viable strategies for adalimumab optimization.
Genomic diagnosis by whole genome sequencing in a Korean family with atypical progeroid syndrome
Authors: Lee Seungbok , Park Sae Mi , Kim Hyun Ji , Kim Jin‐Wou , Yu Dong Soo , Lee Young Bok 
Published: June 2015

AbstractClinical genomic diagnosis is unfamiliar to many dermatologists. Limited knowledge of bioinformatics has limited the use of the next generation sequencing method in dermatological clinics. We evaluated the usefulness of whole genome sequencing as a diagnostic approach to inherited dermatological disease. Here, we present our experience with two female siblings with atypical familial generalized lipodystrophy with diabetes mellitus and dyslipidemia. Whole genome sequencing was performed to diagnose the inherited disease. We compared control genomic databases using the Exome Aggregation Consortium, and filtered false‐positive calls with the segmental duplication, non‐flagged single nucleotide variants and COSMIC mutation databases, and applied the prediction tools of SIFT and PolyPhen2. The two siblings who presented with generalized lipodystrophy were diagnosed with an atypical progeroid syndrome with a p.D136H mutation in the LMNA gene (NM_005572). We diagnosed a familial atypical progeroid syndrome using whole genome sequencing. In this paper, we present our experience with whole genome sequencing and demonstrate that it can provide useful information for clinical genomic diagnosis of inherited diseases with atypical clinical features, such as atypical progeroid syndrome.
Evolutionary potential of multiple measures of upper thermal tolerance in Drosophila melanogaster
Authors: Hangartner Sandra , Hoffmann Ary A. 
Published: June 2015

Summary

Thermal tolerance influences the distribution and abundance of many species, but the adaptive capacity of species to increase upper thermal tolerance is poorly understood. Given that patterns of heat tolerance can strongly depend on assay method, it is crucial to get a better understanding of genetic variances and correlations among different heat tolerance components.

This study tests for correlated responses in different heat tolerance assays in Drosophila melanogaster lines selected for increased heat tolerance following exposure to a static high temperature. Traits tested included heat tolerance measured under static (basal and hardened) and ramping assays (using different starting temperatures and ramping rates), with lines exposed to fluctuating conditions (3 days of a cycling temperature regime) and a variable food treatment.

Selected lines had higher heat tolerance than control lines in all static and ramping assays. The upper thermal tolerance was up to 0·5 °C higher in the selected compared to control lines after ten generations of strong selection.

Selection using a static assay therefore leads to correlated responses in other heat‐resistant components, suggesting that traits are genetically correlated and not influenced strongly by assay conditions.

While the D. melanogaster population we studied harboured additive genetic variation to evolve increased upper thermal tolerance, the level detected may be insufficient to keep up with temperature increases predicted under climate change.
Regularized sparse‐grid geometric sampling for uncertainty analysis in non‐linear inverse problems
Authors: Azevedo Leonardo , Tompkins Michael J. , Mukerji Tapan 
Published: June 2015

ABSTRACTThis paper introduces an efficiency improvement to the sparse‐grid geometric sampling methodology for assessing uncertainty in non‐linear geophysical inverse problems. Traditional sparse‐grid geometric sampling works by sampling in a reduced‐dimension parameter space bounded by a feasible polytope, e.g., a generalization of a polygon to dimension above two. The feasible polytope is approximated by a hypercube. When the polytope is very irregular, the hypercube can be a poor approximation leading to computational inefficiency in sampling. We show how the polytope can be regularized using a rotation and scaling based on principal component analysis. This simple regularization helps to increase the efficiency of the sampling and by extension the computational complexity of the uncertainty solution. We demonstrate this on two synthetic 1D examples related to controlled‐source electromagnetic and amplitude versus offset inversion. The results show an improvement of about 50% in the performance of the proposed methodology when compared with the traditional one. However, as the amplitude versus offset example shows, the differences in the efficiency of the proposed methodology are very likely to be dependent on the shape and complexity of the original polytope. However, it is necessary to pursue further investigations on the regularization of the original polytope in order to fully understand when a simple regularization step based on rotation and scaling is enough.
Population dynamics of an invasive forest insect and associated natural enemies in the aftermath of invasion: implications for biological control
Authors: Duan Jian J. , Bauer Leah S. , Abell Kristopher J. , Ulyshen Michael D. , Van Driesche Roy G. 
Published: June 2015

Summary

Understanding the population dynamics of exotic pests and associated natural enemies is important in developing sound management strategies in invaded forest ecosystems. The emerald ash borer (EAB) Agrilus planipennis Fairmaire is an invasive phloem‐feeding beetle that has killed tens of millions of ash Fraxinus trees in North America since first detected in 2002.

We evaluated populations of immature EAB life stages and associated natural enemies over a 7‐year period (2008–2014) in six stands of eastern deciduous forest in southern Michigan, where Tetrastichus planipennisi Yang and two other Asian‐origin EAB parasitoids were released for biological control between 2007 and 2010.

We observed ≈90% decline in densities of live EAB larvae in infested ash trees at both parasitoid‐release and control plots from 2009 to 2014 and found no significant differences in EAB density or mortality rates by parasitoids, avian predators or other undetermined factors between parasitoid‐release and control plots. The decline in EAB larval density in our study sites was correlated with significant increases in EAB larval parasitism, first by native parasitoids, then by T. planipennisi.

Life table analyses further indicated that parasitism by the introduced biocontrol agent and the North American native parasitoids contributed significantly to the reduction of net EAB population growth rates in our study sites from 2010 to 2014.

Synthesis and applications. Our findings indicate that successful biocontrol of emerald ash borer (EAB) may involve suppression of EAB abundance both by local, generalist natural enemies (such as Atanycolus spp.) and by introduced specialist parasitoids (such as T. planipennisi). Biological control programmes against EAB in the aftermath of invasion should focus on establishing stable populations of T. planipennisi and other introduced specialist parasitoids for sustained suppression of low‐density EAB populations. Moreover, we recommend releasing the introduced specialist biocontrol agents as soon as possible to prevent the outbreak of EAB populations in both newly infested and aftermath forests when EAB densities are still low.
Disentangling the heritable and plastic components of the competitive and facilitative effects of an alpine foundation species
Authors: Al Hayek Patrick , Maalouf Jean‐Paul , Touzard Blaise , Michalet Richard 
Published: June 2015

Summary

Differences in effects between phenotypes of foundation species on subordinate species have been reported, but no study has separated their heritable and plastic components. In a subalpine community of the French Pyrenees, we observed two phenotypes of Festuca gautieri: tight cushions in dry convex outcrops with few subordinate species and loose cushions in wet concave slopes with many subordinate species, suggesting differences in effects of the two phenotypes on subordinates.

Using two reciprocal transplantation gardens, we studied the responses of the two phenotypes to changes in environmental conditions, thus assessing the contribution of heritability and plasticity to the phenotypic variation. Using a target cross‐transplantation experiment, we assessed the plasticity and heritability bases of their contrasting effects. We also quantified the recolonization of resident plants within the reciprocally transplanted cushions.

We found that morphological differences between cushions had both heritability and plasticity bases. The two competition experiments showed heritable increase in competitive effects from loose to tight cushions. This was counteracted by plasticity effects, which decreased competition from the benign to the stressful garden.

Synthesis. We conclude that heritable effects overcome plasticity effects resulting in higher diversity in the loose phenotype from the benign habitats.
Impacts of drought and nitrogen addition onCallunaheathlands differ with plant life‐history stage
Authors: Meyer‐Grünefeldt Maren , Calvo Leonor , Marcos Elena , von Oheimb Goddert , Härdtle Werner 
Published: June 2015

SummaryClimate change and atmospheric deposition of nitrogen (N) affect the biodiversity patterns and functions of ecosystems world‐wide. While many single‐factor studies have quantified ecosystem responses to single global change drivers, less is known about the interaction effects of these drivers on ecosystem functions.Here, we present the results of a three‐year field and a two‐year glasshouse experiment, in which we assessed responses ofCalluna vulgarisheathlands to the single and combined effects of drought events (D) and N fertilization (D: 25% precipitation reduction in the field experiment and 20–50% soil water content reduction in the glasshouse experiment; N fertilization: 35 kg N ha−1 year−1).We examined the effects of D and N treatments on growth responses of the dominant dwarf shrubCalluna vulgaris(in terms of biomass production and allocation, tissue δ13C signatures and C:N ratios) in relation to two plant life‐history stages and different ‘ecotypes’ (sub‐Atlantic vs. subcontinental heathlands).Plant responses varied strongly with life‐history stage, and the interaction of N and D showed lower effects than would be expected based on additive responses to single factors. While D treatments had no effects onCallunain the building phase (ca. ten‐year‐old plants), seedlings (particularly one‐year‐old plants) were highly susceptible to drought. Differences in response patterns were attributable to the high shoot–root ratios typical of youngCallunaplants. These ratios decreased with progressing life history as a result of increasing below‐ground biomass investments. Below‐ground biomass production and shoot–root ratios differed between plants from the different heathland sites.Tissue δ13C signatures decreased and C:N ratios increased with plant age as a result of decreasing evaporative demands (per unit root biomass). N fertilization increases the shoot–root ratios and thereby the drought susceptibility ofCallunaplants.Synthesis. Our findings suggest that plant responses to global change are difficult to anticipate by means of single‐factor studies or by focusing on a single life‐history stage. This highlights the need for global change research to include multiple factors and life‐history stages when assessing an ecosystem's susceptibility to shifts in environmental conditions.