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ABSTRACTRenewable generation plays an important part in today's power system. With the inclusion of the inverter interfaced renewable energy sources (RESs) into a microgrid, the total system inertia decreases and it leads to increased frequency deviation in presence of a disturbance. This paper proposes a cascaded Integral Minus Tilt Integral Derivative with Filter (I–TDN)‐Proportional‐Integral (PI), [(I‐TDN)‐PI] controller for frequency stabilization of a hybrid microgrid in presence of electric vehicles (EV). The microgrid model includes reheated thermal power plant with high degree of non‐linear system such as inverter based RESs like photovoltaic and wind generation systems. A diesel engine generator is incorporated for load frequency control during perturbation in the system frequency. Virtual inertia controller (VIC) with inverter based energy storage system (ESS) is commonly used to improve system inertia and frequency stability of the microgrid. In addition to the ESS, this paper proposes inclusion of the EVs in this VIC. The optimal gains of the proposed cascaded I‐TDN‐PI controller are determined using Mountain Gazelle Optimizer (MGO), a modern metaheuristic optimization algorithm. Sensitivity of the proposed controller is investigated in presence of system nonlinearities, load perturbations, time delay, system parameter variation and RES power fluctuations. The simulation results justify the robustness of the proposed control structure for frequency stabilization of the microgrid. [ABSTRACT FROM AUTHOR]

There is something particularly depressing about the current moment—when the possibility of thriving as a geography academic in British academia seems incompatible with anything else, be that a life outside work, a family, activism, or even sleep. What connects these multiple intensifications of demands on academics, and many of the external crises we are living through (the climate emergency, wage deflation, cost of living, the COVID pandemic etc.) is how we value, use and understand time. The non‐linearity of time is a useful way to understand how we work in academia. In this paper, I explore how can we change how we use our time. I propose three responses, which each play with time as non‐linear, multiple rhythms, and as having a lack of balance or stability. First, the possibility of working with the delight of shifting pace in helping us to enjoy our working time more. Second, in acting in collaboration, solidarity, and being alongside each other in ways where shared time is more expansive than individual time. Finally, in how we can collectively and structurally re‐order our time together. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Methods Results Main Conclusions Population dynamics are usually assessed through linear trend analysis, quantifying their general direction. However, linear trends may hide substantial variations in population dynamics that could reconcile apparent discrepancies when quantifying the extent of the biodiversity crisis. We seek to determine whether the use of non‐linear methods and the quantification of temporal variability can offer a more complete representation of changes in global population dynamics than commonly‐used linear approaches.We analysed 6437 population time series from 1257 vertebrate species from the Living Planet Database over the period 1950–2020. We modelled populations through the use of second‐order polynomials and classified trajectories according to their direction and acceleration. We modelled and classified these same populations using a more classical linear trend analysis. We quantified temporal variability using the mean squared error of the fitted polynomials. We then used generalised linear mixed models to test potential sources of heterogeneity in non‐linear trajectories and temporal variability.In all, 44.8% of the analysed population time series were non‐linear. Across all populations, 30% were declining, 30% were increasing, and 40% were with no linear trend. Among the population showing no linear trend, half were concave or convex. Non‐linearity was expressed differently between taxonomic groups, with mammals showing higher prevalence of non‐linearity. Marine and freshwater populations were more variable than terrestrial populations, and fish were more variable than other vertebrates. Differences between geographical regions were detected in both non‐linearity and temporal variability, but no straightforward pattern emerged. There were no differences in both components between IUCN categories.Non‐linearity and temporal variability reveal usually overlooked dramatic declines or recovery signals in global population dynamics. Thus, moving beyond linearity can improve our understanding of complex population dynamics and better inform conservation decisions. In particular, populations usually classified as ‘stable’ can hide informative changes in non‐linear and variability patterns that need to be considered in global biodiversity assessments. [ABSTRACT FROM AUTHOR]

Scholars increasingly raise concerns about the alleged detrimental impact of affective polarization on citizens’ democratic attitudes. Yet, prior studies on the relationship between affective polarization and democratic support have yielded mixed results: Whereas some scholars report evidence that affective polarization erodes citizens’ support for democracy, others report null findings. In this research note, we posit that one relevant explanation for these mixed results is that the relationship between affective polarization and democratic support is not linear, but rather negatively curvilinear (i.e., an inverted U‐shape). Though extreme levels of affective polarization may harm citizens’ democratic commitments, a moderate amount of affective polarization can strengthen democratic support by heightening the political stakes and stimulating democratic involvement. Employing generalized additive modelling on data from the CNEP collected in Germany, the United Kingdom, and the United States, we show strong and robust support for this negatively curvilinear pattern. These findings have important implications for our understanding of the dynamics between affective polarization and democratic support, as well as for the recommended estimation strategies of future studies that aim to explore this relationship. [ABSTRACT FROM AUTHOR]

The global movement for ecosystem restoration has gained momentum in response to the Bonn Challenge (2010) and the UN Decade on Ecosystem Restoration (UNDER, 2021–2030). While several science‐based guidelines exist to aid in achieving successful restoration outcomes, significant variation remains in the outcomes of restoration projects. Some of this disparity can be attributed to unexpected responses of ecosystem components to planned interventions.Given the complex nature of ecosystems, we propose that concepts from Complex Systems Science (CSS) that are linked to non‐linearity, such as regime shifts, ecological resilience and ecological feedbacks, should be employed to help explain this variation in restoration outcomes from an ecological perspective.Our framework, Explore Before You Restore, illustrates how these concepts impact restoration outcomes by influencing degradation and recovery trajectories. Additionally, we propose incorporating CSS concepts into the typical restoration project cycle through a CSS assessment phase and suggest that the need for such assessment is explicitly included in the guidelines to improve restoration outcomes.To facilitate this inclusion and make it workable by practitioners, we describe indicators and methods available for restoration teams to answer key questions that should make up such CSS assessment. In doing so, we identify key outstanding science and policy tasks that are needed to further operationalize CSS assessment in restoration.Synthesis and applications. By illustrating how key Complex Systems Science (CSS) concepts linked to non‐linear threshold behaviour can impact restoration outcomes through influencing recovery trajectories, our framework Explore Before You Restore demonstrates the need to incorporate Complex Systems thinking in ecosystem restoration. We argue that inclusion of CSS assessment into restoration project cycles, and more broadly, into international restoration guidelines, may significantly improve restoration outcomes. [ABSTRACT FROM AUTHOR]

Multivariate Adaptive Regression Spline (MARS) is a simple and powerful non‐parametric machine learning algorithm that automatizes the selection of non‐linear terms in regression models. In this study, we propose using MARS in a spatial regression framework to account for potential non‐linearities and spatial effects in spatial regression models. Using a relatively large data set of 17,000 dwellings in St. Petersburg (Russia), we examine how this algorithm works. The empirical evidence shows that most explanatory variables in the spatial regression model—including the spatial lag of the dependent variable—have a non‐linear impact on the asking prices of dwellings. [ABSTRACT FROM AUTHOR]

This paper analyses the dynamics of financial deepening and the volatility of business cycle in the United Arab of Emirates (UAE). We use cointegration tests of regime‐shift with one and two endogenous structural breaks, respectively, using Gregory and Hansen, Oxford Bulletin of Economics and Statistics, 1996, 58, 555–560 and Hatemi‐J, Empirical Economics, 2008, 35, 497–505 approaches. The asymmetry in the underlying relationship of the concerned variables are examined following NARDL model over the period 1974–2016. The findings suggest the presence of regime shifts in the cointegrating relationship and asymmetry between growth volatility and financial deepening. Furthermore, the paper provides evidence of a significant difference in the response of business cycle to negative or positive changes in the financial deepening, which are more pronounced in the short run. Therefore, the obtained asymmetry suggests that business cycle responses are quick and adverse to changes in the financial system in the UAE. The empirical findings of this paper have potential policy implications in this emerging country that is aiming to establish an international reputation in its financial market and become a regional financial hub. [ABSTRACT FROM AUTHOR]

Aim: Despite the complexity of population dynamics, most studies concerning current changes in bird populations reduce the trajectory of population change to a linear trend. This may hide more complex patterns reflecting responses of bird populations to changing anthropogenic pressures. Here, we address this complexity by means of multivariate analysis and attribute different components of bird population dynamics to different potential drivers. Location: Czech Republic. Methods: We used data on population trajectories (1982–2019) of 111 common breeding bird species, decomposed them into independent components by means of the principal component analysis (PCA), and related these components to multiple potential drivers comprising climate, land use change and species' life histories. Results: The first two ordination axes explained substantial proportion of variability of population dynamics (42.0 and 12.5% of variation in PC1 and PC2 respectively). The first axis captured linear population trend. Species with increasing populations were characterized mostly by long lifespan and warmer climatic niches. The effect of habitat was less pronounced but still significant, with negative trends being typical for farmland birds, while positive trends characterized birds of deciduous forests. The second axis captured the contrast between hump‐shaped and U‐shaped population trajectories and was even more strongly associated with species traits. Species migrating longer distances and species with narrower temperature niches revealed hump‐shaped population trends, so that their populations mostly increased before 2000 and then declined. These patterns are supported by the trends of total abundances of respective ecological groups. Main Conclusion: Although habitat transformation apparently drives population trajectories in some species groups, climate change and associated species traits represent crucial drivers of complex population dynamics of central European birds. Decomposing population dynamics into separate components brings unique insights into non‐trivial patterns of population change and their drivers, and may potentially indicate changes in the regime of anthropogenic effects on biodiversity. [ABSTRACT FROM AUTHOR]

Shape optimisation of eccentrically loaded columns – theory and experimental verification. In shape optimisation, the external shape of the structural component is adapted to the predominant force flow. In this way, large load increases can be achieved with the same material use, or high material savings can be achieved with the same load‐bearing capacity. In this paper, a shape optimisation for eccentrically loaded columns is presented, where the bending stress results from a frame effect of the load‐bearing system. This is the case, for example, in edge columns of typical reinforced concrete skeleton structures, as they are usually used in residential and commercial buildings. The shape optimisation method presented in the article can be applied to columns with an arbitrary ratio of a moment‐normal force loading, provided that a material failure occurs. Results for shape optimisation in the case of a stability failure have already been published separately for centrically pressed columns. The optimisation itself is carried out iteratively on a column segmented over the height under the criterion of achieving a uniform stress state in the component. With the help of an experimental check on 3.3 m high columns, the selected calculation and optimisation method could be verified. In addition to the failure loads, the concrete strains and the deformation behaviour were also analysed and evaluated at selected points of the specimen. [ABSTRACT FROM AUTHOR]

Summary: Globally, the water‐level fluctuations in lakes are a dynamic and complex process. The fluctuation is characterized by higher non‐linearity and stochasticity, making it quite hard to forecast for future planning. However, the advent of machine learning algorithms in recent decades provides significant improvement in forecasting such fluctuations. This work provides a systematic review of the machine learning algorithms (ML) used for characterizing lake‐water level dynamics. Among those ML algorithms, the paper reviews seven distinct as well as popular algorithms namely, neural network model, support vector machines, extreme learning machine, artificial neuro‐fuzzy inference systems, evolutionary and hybrid algorithms, and deep learning models. The sample inputs, splitting of data, performance metrics, and its comparison are discussed with future scope. Moreover, the strength and limitations of those algorithms are also examined. Finally, the review in this paper gives a newer vision for water resource planners and hydrologists for sustainable lake management. [ABSTRACT FROM AUTHOR]

Floods claim a high toll in fatalities and economic impacts. Despite their societal relevance, there is much more to learn about the projected changes in discharge and flooding. Here we force an operational hydrologic model over the state of Iowa with high‐resolution convection‐permitting climate‐model precipitation to evaluate the response of 140 watersheds to climate change. At the end of the century, under the most aggressive scenario in terms of fossil fuel use, we show that the transition from snow to rainfall and approximately 30% increase in extreme precipitation rates lead to a doubling of maximum discharge during the spring and extending the flood season into the fall. Total discharge volumes are also expected to increase. Our results suggest that flood projections based on extreme precipitation increases alone substantially underestimate future risk due to the non‐linearity of the hydrologic response explained by long‐term soil moisture memory and its feedbacks with precipitation. This study is one of the first to show floods are increasing due to the prevalence of rain‐on‐snow events, and indeed that discharge might increase more than precipitation. [ABSTRACT FROM AUTHOR]

Accurate simulators are relied upon in the process industry for plant design and operation. Typical simulators, based on mechanistic models, require considerable resources: skilled engineers, computational time, and proprietary data. This article explores the complexities of developing a statistical modelling framework for chemical processes, focusing on inherent non‐linearity in phenomena and the difficulty of obtaining data. A Bayesian approach to modelling is forwarded in this article, utilising Bayesian sequential design to maximise information gain for each experiment. Gaussian process regression is used to provide a highly flexible model class to capture non‐linearities in the process data. A non‐linear process simulator, modelled in Aspen Plus is used as a surrogate for a real chemical process, to test the capabilities of the framework. [ABSTRACT FROM AUTHOR]

Understanding the role of soil moisture and other controls in runoff generation is important for predicting runoff across scales. This paper aims to identify the degree of non‐linearity of the relationship between event peak runoff and potential controls for different runoff generation mechanisms in a small agricultural catchment. The study is set in the 66 ha Hydrological Open Air Laboratory, Austria, where discharge was measured at the catchment outlet and for 11 sub‐catchments or hillslopes with different runoff generation mechanisms. Peak runoff of 73 events was related to three potential controls: event precipitation, soil moisture and groundwater levels. The results suggest that the hillslopes dominated by ephemeral overland flow exhibit the most non‐linear runoff generation behaviour for its controls; runoff is only generated above a threshold of 95% of the maximum soil moisture. Runoff generation through tile drains and in wetlands is more linear. The largest winter and spring events at the catchment outlet are caused by runoff from hillslopes with shallow flow paths (ephemeral overland flow and tile drainage mechanisms), while the largest summer events are caused by other hillslopes, those with deeper flow paths or with saturation areas throughout the year. Therefore, the response of the entire catchment is a mix of the various mechanisms, and the groundwater contribution makes the response more linear. The implications for hydrological modelling are discussed. [ABSTRACT FROM AUTHOR]

The development, uncertainty evaluation and certification of eleven newly developed zinc isotope ratio reference materials (GBW04465‐04475) are described. The reference materials were gravimetrically prepared with enriched isotopic materials. During the certification, calibrated MC‐ICP‐MS measrements were performed. The improved techniques for certification in this study are as follows: (a) the isotopic compositions of purified enriched isotopes used for preparation of synthetic isotopic mixtures were obtained by total evaporation‐TIMS instead of the traditional iteration method; and (b) the mass discrimination effect in MC‐ICP‐MS was investigated through a series of isotopic mixtures with a wide range of isotopic compositions, and a non‐linearity effect of K factors was observed, and a new correction proposal was employed. The reference materials were certified with a point‐to‐point proposal instead of the traditional mean and stable K method. Further, the uncertainties were evaluated in detail, and contributions from characterisation, homogeneity and long‐term stability were taken into consideration. Among them, contributions from characterisation were particularly detailed: any budgets, for example, weighing and impurity checking, were clearly addressed, and the combined uncertainties were derived by a mathematical differentiation method. In addition, the traceability chain was established, directly pointing to the SI unit, the mole, and a between‐laboratory comparison was carried out to validate the reference values. [ABSTRACT FROM AUTHOR]

A well documented stylized fact in commodity‐exporting countries is the robust relationship between commodity prices and real exchange rates. However, empirical evidences of factors that affect the strength of the commodity price‐real exchange rate connection remain inconclusive. In this paper, we investigate how structural and financial factors affect the relationship between world commodity prices and the Brazilian real exchange rate during the floating exchange rate regime. The key results show that the strength of the real exchange rate response to real commodity price fluctuations depends on the trade openness in the long run and on the country risk in the short run. Our findings provide important insights for the appropriated design of foreign exchange policy in Brazil. [ABSTRACT FROM AUTHOR]

Complex crises like the coronavirus pandemic are showing us that modern societies are becoming increasingly unable to live in equilibrium with nature. These crises are the result of multiple causes, which interact at different scales and across different domains. Therefore, investigating their proximate causes is not enough to fully understand them. It is also crucial to take into account the structural factors involved. As concerns the global pandemic, I suggest four levels of analysis: (i) the surface or "proximate" level of the crisis; (ii) the human–environment–animal interface, as pointed out by the One Health approach; (iii) the broader socioeconomic context; and (iv) the deeper or worldview level. Furthermore, I argue that there is the need for a mindset shift if we want to properly trace causality. Much more attention must be given to the study of multilevel connecting patterns and nonlinear mechanisms as the producers of emergent global effects. [ABSTRACT FROM AUTHOR]

To fulfill the 2030 Agenda, the complexity of sustainable development goal (SDG) interactions needs to be disentangled. However, this understanding is currently limited. We conduct a cross‐sectional correlational analysis for 2016 to understand SDG interactions under the entire development spectrum. We apply several correlation methods to classify the interaction as synergy or trade‐off and characterize them according to their monotony and linearity. Simultaneously, we analyze SDG interactions considering population, location, income, and regional groups. Our findings highlight that synergies always outweigh trade‐offs and linear outweigh non‐linear interactions. SDG 1, 5, and 6 are associated with linear synergies, SDG 3, and 7 with non‐linear synergies. SDG interactions vary according to a country's income and region along with the gender, age, and location of its population. In summary, to achieve the 2030 Agenda the detected interactions and inequalities across countries need be tracked and leveraged to "leave no one behind." [ABSTRACT FROM AUTHOR]

Short‐time work (STW) is a labor‐market policy that subsidizes working‐time reductions among firms in financial difficulty to prevent lay‐offs. Many OECD countries have used this policy in the Great Recession. In this paper, we show that the effects of STW are strongly time‐dependent and non‐linear over the business cycle. Discretionary STW policy might save up to 0.87 jobs per short‐time worker in deep economic crises. In expansions, the effects are smaller and might turn negative. We disentangle discretionary STW from automatic stabilization in German data using smooth‐transition vector autoregressions. [ABSTRACT FROM AUTHOR]

Disturbance plays a key role in ecological structure and function. Two important and often studied components of disturbance are frequency and magnitude. Despite the potential for non‐linear interactions between frequency and magnitude, their effects are often assumed to combine in a linear manner. Additionally, studies of disturbance have mainly examined effects on species diversity and competitive interactions within a single trophic level, with less focus on exploitative interactions across trophic levels. Furthermore, while the effects of disturbance are often viewed in terms of reducing population abundance, disturbances can also alter demographic processes, 'indirectly' changing abundances. We analyzed several classic dynamic models of species interactions to examine the effects of varying disturbance frequency and magnitude on population persistence in predator–prey and competition systems. Our analysis revealed the potential for non‐linear interactions between frequency and magnitude and their effect on population persistence. Effects differed depending on the form of population dynamics and whether disturbance affected abundance or demographic rates. It is critical to management efforts aiming to improve chances of population persistence to further understand the effects of varying disturbances on interacting populations. [ABSTRACT FROM AUTHOR]

Employees of a certain rank are motivated by the pay gap between them and the levels above (upward comparison), and the pay gap between them and the levels below (downward comparison). In some cases, employees face multiple upward comparisons such as immediate and subsequent upward comparisons. We hypothesise that upward comparison matters more than downward comparison, and in the case of multiple upward comparisons, the immediate one matters more than the subsequent ones. We also hypothesise that the pay gap effect resulting from the upward/downward comparison ought to be non‐linear in that performance increases with pay gap size at a decreasing rate. The results from two empirical studies, namely, a longitudinal field study and a laboratory experiment, largely support our hypotheses. [ABSTRACT FROM AUTHOR]

We use a flexible semi‐parametric estimation approach and a sample of 7,227 U.S., U.K., and Canadian banks for 2009–2015 to provide evidence that banking stability is non‐linearly determined by competition. We show that stability is not monotonic against competition, and may increase and decrease at high competition, has a mixed behaviour at medium competition, and increases at low competition. This non‐monotonic stability behaviour at different competition levels is attributed to the intervention quality, which is found to be an important determinant of the competition–stability relation. It is non‐linearly related to and being revised at different competition levels. As intervention is a policy variable, its level can be adjusted to reduce the competition effects on stability. We illustrate that for the U.S. banking sector, the intervention quality has to hedge these competition effects. Regulators should treat intervention quality as a "hedging instrument" against the destabilizing competition effects. [ABSTRACT FROM AUTHOR]

Decay of palsas can indicate permafrost status, particularly in regions where air temperatures have increased rapidly in recent decades. Using weather data, annual surveys of active-layer thickness, and analyses of high-resolution aerial imagery from the eastern Selwyn/western Mackenzie Mountains, NT, Canada, we show that permafrost temperatures have increased, active layers have deepened, and palsa areal extents have decreased considerably since the 1940s. High-altitude palsas thawed quickly from the 1940s to the 1980s, although some low-altitude palsas have recently decreased rapidly in areal extent due to peat-block calving. The linear rate of increasing active-layer thickness may not be congruent with the non-linear rate of areal loss of palsas. The rapid and episodic collapse of palsas at some sites highlights the necessity to consider hydrology, vegetation cover, landscape position, and morphology in palsa dynamics in addition to a warming climate. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper examines the importance of nominal rigidity for nonlinearity and asymmetry of exchange rate pass-through. For this purpose, we rely on company-level data of French importing firms. We find that the well established fact that 'prices rise faster than they fall,' which is characterized by the convex import price reaction function, lies primarily with the presence of nominal rigidity. Once price stickiness is controlled for, there is empirical evidence that the import price reaction function is rather concave if the linearity assumption can be rejected, indicating that firms aim primarily to protect their market share. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) reliability and durability have seen increased interest in recent years. Historically, and as a preliminarily reasonable approximation, linear degradation rates have been used to quantify long-term module and system performance. The underlying assumption of linearity can be violated at the beginning of the life, as has been well documented, especially for thin-film technology. Additionally, non-linearities in the wear-out phase can have significant economic impact and appear to be linked to different failure modes. In addition, associating specific degradation and failure modes with specific time series behavior will aid in duplicating these degradation modes in accelerated tests and, eventually, in service life prediction. In this paper, we discuss different degradation modes and how some of these may cause approximately linear degradation within the measurement uncertainty (e.g., modules that were mainly affected by encapsulant discoloration) while other degradation modes lead to distinctly non-linear degradation (e.g., hot spots caused by cracked cells or solder bond failures and corrosion). The various behaviors are summarized with the goal of aiding in predictions of what may be seen in other systems. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. [ABSTRACT FROM AUTHOR]

In generalized linear modelling of responses and response times, the observed response time variables are commonly transformed to make their distribution approximately normal. A normal distribution for the transformed response times is desirable as it justifies the linearity and homoscedasticity assumptions in the underlying linear model. Past research has, however, shown that the transformed response times are not always normal. Models have been developed to accommodate this violation. In the present study, we propose a modelling approach for responses and response times to test and model non-normality in the transformed response times. Most importantly, we distinguish between non-normality due to heteroscedastic residual variances, and non-normality due to a skewed speed factor. In a simulation study, we establish parameter recovery and the power to separate both effects. In addition, we apply the model to a real data set. [ABSTRACT FROM AUTHOR]

The relationship between the BOLD response and an applied force was quantified in the cerebellum using a power grip task. To investigate whether the cerebellum responds in an on/off way to motor demands or contributes to motor responses in a parametric fashion, similarly to the cortex, five grip force levels were investigated under visual feedback. Functional MRI data were acquired in 13 healthy volunteers and their responses were analyzed using a cerebellum-optimized pipeline. This allowed us to evaluate, within the cerebellum, voxelwise linear and non-linear associations between cerebellar activations and forces. We showed extensive non-linear activations (with a parametric design), covering the anterior and posterior lobes of the cerebellum with a BOLD-force relationship that is region-dependent. Linear responses were mainly located in the anterior lobe, similarly to the cortex, where linear responses are localized in M1. Complex responses were localized in the posterior lobe, reflecting its key role in attention and executive processing, required during visually guided movement. Given the highly organized responses in the cerebellar cortex, a key question is whether deep cerebellar nuclei show similar parametric effects. We found positive correlations with force in the ipsilateral dentate nucleus and negative correlations on the contralateral side, suggesting a somatotopic organization of the dentate nucleus in line with cerebellar and cortical areas. Our results confirm that there is cerebellar organization involving all grey matter structures that reflect functional segregation in the cortex, where cerebellar lobules and dentate nuclei contribute to complex motor tasks with different BOLD response profiles in relation to the forces. Hum Brain Mapp 38:2566-2579, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

In this paper, we have examined the inflation rates in the Group of Seven countries, investigating issues such as the existence of unit roots, structural breaks, fractional integration and potential non-linearities using a fractional dependence (FD) approach based on Chebyshev polynomials in time. This robust FD approach allows one to test for persistence as well as non-linearity of the series. We first tested for stationarity and structural breaks using classical approaches and observed inconclusive results with regard to the stationarity levels of the series. Using Bai-Perron tests, we actually confirmed significant structural breaks, even up to five, in each of the inflation series. However, noting that structural breaks are significantly related to fractional differentiation, this latter approach was also conducted. Here, we observed that the estimates of the differencing parameter were quite stable across time, and evidence of unit roots was found in the cases of the UK, Canada, France, Japan and the USA; for Germany, we found some evidence of mean reversion, while estimates of d above 1 were found in the case of Italy. On the other hand, non-linear deterministic trends were clearly rejected in all cases. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper considers how some well-documented deficiencies of mental models make it difficult to create effective policies, and suggests that systems modelling can begin to address this issue. To illustrate the argument, three short cases are presented. These relate to specific domains but demonstrate how systems modelling can illuminate different general phenomena: effects on labour costs (unintended consequences and feedback), fishery management (accumulation and non-linearity) and child protection (worldviews and sense-making). Six levers for increasing the use of systems modelling in the policy arena are then discussed. The paper closes by emphasising the opportunities for systems modellers in the Anthropocene Era. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Published data on photovoltaic (PV) degradation measurements were aggregated and re-examined. The subject has seen an increased interest in recent years resulting in more than 11 000 degradation rates in almost 200 studies from 40 different countries. As studies have grown in number and size, we found an impact from sampling bias attributable to size and accuracy. Because of the correlational nature of this study we examined the data in several ways to minimize this bias. We found median degradation for x-Si technologies in the 0.5-0.6%/year range with the mean in the 0.8-0.9%/year range. Hetero-interface technology (HIT) and microcrystalline silicon (µc-Si) technologies, although not as plentiful, exhibit degradation around 1%/year and resemble thin-film products more closely than x-Si. Several studies showing low degradation for copper indium gallium selenide (CIGS) have emerged. Higher degradation for cadmium telluride (CdTe) has been reported, but these findings could reflect a convolution of less accurate studies and longer stabilization periods for some products. Significant deviations for beginning-of-life measurements with respect to nameplate rating have been documented over the last 35 years. Therefore, degradation rates that use nameplate rating as reference may be significantly impacted. Studies that used nameplate rating as reference but used solar simulators showed less variation than similar studies using outdoor measurements, even when accounting for different climates. This could be associated with confounding effects of measurement uncertainty and soiling that take place outdoors. Hotter climates and mounting configurations that lead to sustained higher temperatures may lead to higher degradation in some, but not all, products. Wear-out non-linearities for the worst performing modules have been documented in a few select studies that took multiple measurements of an ensemble of modules during the lifetime of the system. However, the majority of these modules exhibit a fairly linear decline. Modeling these non-linearities, whether they occur at the beginning-of-life or end-of-life in the PV life cycle, has an important impact on the levelized cost of energy. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: Diabetes is a major public health problem and thought to be a risk factor for infectious diseases, but pertinent epidemiological evidence is limited. This study aimed to analyse the associations of diabetes, disease duration and glycated haemoglobin levels (HbA1c) with infectious diseases mortality in the general population, including the investigation of potential non-linear relationships.Methods: An observational, prospective study of 19 783 subjects included in the Third National Health and Nutrition Examination Survey, representing the adult non-institutionalized population of the United States of America, was conducted. The analysis was done by multiple Cox regression and restricted cubic spline modelling.Results: Self-reported diabetes and diabetes duration were not significantly associated with the outcomes. However, there was evidence for a non-linear association of HbA1c with mortality from influenza, pneumonia or other acute lower respiratory infections. Spline regression suggested a roughly doubled risk of mortality beyond an HbA1c of 6.5% (48 mmol/mol) in reference to 5.2% (33 mmol/mol).Conclusions: Future studies on diabetes and infections should adequately address potential non-linearity, which may be necessary to better understand and characterize more precisely the relationship of diabetes with infectious diseases. [ABSTRACT FROM AUTHOR]

Aim To cluster peri-implantitis patients and explore non-linear patterns in peri-implant bone levels. Materials and Methods Clinical and radiographic variables were retrieved from 94 implant-treated patients (340 implants, mean 7.1 ± 4.1 years in function). Kernel probability density estimations on patient mean peri-implant bone levels were used to identify patient clusters. Inter-relationships of all variables were evaluated by principal component analysis; a k-nearest neighbours method was performed for supervised prediction of implant bone levels at the patient level. Self-similar patterns of mean bone level per implant from different jaw bone sites were examined and their associated fractal dimensions were estimated. Results Two clusters of implant-treated patients were identified, one at patient mean bone levels of 1.7 mm and another at 4.0 mm. Five of thirteen available variables (number of teeth, age, gender, periodontitis severity, years of implant service), were predictive for peri-implant bone levels. A high jaw bone fractal dimension was associated with less severe peri-implantitis. Conclusions Non-linearity of peri-implantitis was evidenced by finding different peri-implant bone levels between two main clusters of implant-treated patients and among six different jaw bone sites. The patient mean peri-implant bone levels were predicted from five variables and confirmed complexity for peri-implantitis. [ABSTRACT FROM AUTHOR]

Complexity has long been recognized and is increasingly becoming mainstream in geomorphology. However, the relative novelty of various concepts and techniques associated to it means that ambiguity continues to surround complexity. In this commentary, we present and discuss a variety of recent contributions that have the potential to help clarify issues and advance the use of complexity in geomorphology. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT We generalize the classical theory of acoustoelasticity to the porous case (one fluid and a solid frame) and finite deformations. A unified treatment of non-linear acoustoelasticity of finite strains in fluid-saturated porous rocks is developed on the basis of Biot's theory. A strain-energy function, formed with eleven terms, combined with Biot's kinetic and dissipation energies, yields Lagrange's equations and consequently the wave equation of the medium. The velocities and dissipation factors of the P- and S-waves are obtained as a function of the 2nd- and 3rd-order elastic constants for hydrostatic and uniaxial loading. The theory yields the limit to the classical theory if the fluid is replaced with a solid with the same properties of the frame. We consider sandstone and obtain results for open-pore jacketed and closed-pore jacketed 'gedanken' experiments. Finally, we compare the theoretical results with experimental data. [ABSTRACT FROM AUTHOR]

SUMMARY The paper presents a mechanical model for non-isothermal behaviour of unsaturated soils. The model is based on an incrementally non-linear hypoplastic model for saturated clays and can therefore tackle the non-linear behaviour of overconsolidated soils. A hypoplastic model for non-isothermal behaviour of saturated soils was developed and combined with the existing hypoplastic model for unsaturated soils based on the effective stress principle. Features of the soil behaviour that are included into the model, and those that are not, are clearly distinguished. The number of model parameters is kept to a minimum, and they all have a clear physical interpretation, to facilitate the model usefulness for practical applications. The step-by-step procedure used for the parameter calibration is described. The model is finally evaluated using a comprehensive set of experimental data for the thermo-mechanical behaviour of an unsaturated compacted silt. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The temporal dynamics and geographical sources of streamflow were conceptualized in a lumped rainfall-runoff model (isoSAMdyn) using isotopic and geochemical tracers derived from a field study in a 3.6 km2 upland catchment in Scotland. High-resolution (daily) sampling of stable isotopes in precipitation and streamflow over a hydrological year, supplemented by fortnightly sampling of groundwater and riparian saturation zones, allowed hypotheses of runoff generation processes to be tested. These were conceptualized in a previously developed model (SAMdyn) based only on geochemically defined geographic source tracers, which showed that the nonlinear dynamic expansion and contraction of riparian saturation areas is the dominant mechanism for storm runoff generation in the catchment. While SAMdyn resulted in reasonable simulation of streamflows and alkalinity (as a source tracer), it was unable to reproduce the rainfall-runoff dynamics of deuterium ( δ2H). Using the model in a learning framework, incorporation of parameters for passive storage in catchment hillslopes and groundwater mixing in riparian saturation zones, along with associated isotopic fractionation, improved δ2H simulations in stream water and the major catchment water stores. The resulting model provided a conceptualization of rainfall-runoff processes that broadly reconciled hydrometric data and geochemical and isotopic signals. However, in this particular catchment, fractionation of water in surface saturation zones appears to be a complex process that prevents the simulation of short-term isotope dynamics in the stream during the summer period. [ABSTRACT FROM AUTHOR]

The article presents a study which compared various spatial interpolation techniques in mapping fog frequency in the Argón region, Spain. It assessed spatial interpolation methods such as generalized linear models (GLM), general additive models (GAM) and ordinary least squares regression (OLSR) on mist, moderate, and dense fog conditions. Result shows that GLM produces unreliable prediction of fog frequency compared to OLSR; however, its combination with GAM drives to an improved outcome.

We develop a simple theoretical model in which chartists and fundamentalists interact. The model predicts the existence of different regimes, and thus non-linearities in the link between the exchange rate and its fundamentals. We test the model empirically by adopting a Markov-switching vector error correction model. The results suggest the presence of non-linear mean reversion in the nominal exchange rate process. The implications are that different sets of macroeconomic fundamentals act as driving forces of the exchange rates during different time periods. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article discusses the linear and non-linear statistical downscaling methods for identifying the winter daily temperature at eight European stations. The linear methods include linear regression of gridpoint values, also known as pointwise regression, and of predictors' principal components, also known as PC regression. The non-linear methods are represented by artificial neural networks, and is achieved by a stratification of data through classification of circulation patterns. The said downscaling methods are evaluated according to four criteria: fit to observations quantified by the correlation coefficient, shape of the statistical distribution such as skewness and kurtosis, temporal autocorrelations with one day lag, and interstation correlations.

Background The effects of environmental factors and ambient concentrations of grass pollen on allergic asthma are yet to be established. Objective We sought to estimate the independent effects of grass pollen concentrations in the air over Melbourne on asthma hospital admissions for the 1992–1993 pollen season. Methods Daily grass pollen concentrations were monitored over a 24-h period at three stations in Melbourne. The outcome variable was defined as all-age asthma hospital admissions with ICD9-493 codes. The ambient air pollutants were average daily measures of ozone, nitrogen dioxide and sulphur dioxide, and the airborne particle index representing fine particulate pollution. Semi-parametric Poisson regression models were used to estimate these effects, adjusted for air temperature, humidity, wind speed, rainfall, day-of-the-week effects and seasonal variation. Results Grass pollen was a strong independent non-linear predictor of asthma hospital admissions in a multi-pollutant model ( P=0.01). Our data suggest that grass pollen had an increasing effect on asthma hospital admissions up to a threshold of 30 grains/m3, and that the effect remains stable thereafter. Conclusion Our findings suggest that grass pollen levels influence asthma hospital admissions. High grass pollen days, currently defined as more than 50 grains/m3, are days when most sensitive individuals will experience allergic symptoms. However, some asthmatic patients may be at a significant risk even when airborne grass pollen levels are below this level. Patients with pollen allergies and asthma would be advised to take additional preventive medication at lower ambient concentrations. [ABSTRACT FROM AUTHOR]

This article discusses the use of phase-space diagrams to construct a coherent classification of hydrologic systems. According to the authors there is a need to determine type of data and amounts of data necessary to simplify hydrologic models,. They suggest a classification based on low-, medium- or high-dimensionality and the region of attraction of trajectories. They use different river data from various climatic and geographic regions with many temporal scales. The results indicated the usefulness of simple reconstruction for studying hydrologic system classification and complexity.

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1 Boundaries between forest and tundra ecosystems, tree lines, are expected to advance in altitude and latitude in response to climate warming. However, varied responses to 20th century warming suggest that in addition to temperature, tree line dynamics are mediated by species-specific traits and environmental conditions at landscape and local scales. 2 We examined recent tree line dynamics at six topographically different, but climatically similar, sites in south-west Yukon, Canada. Dendroecological techniques were used to reconstruct changes in density of the dominant tree species, white spruce ( Picea glauca), and to construct static age distributions of willow ( Salix spp.), one of two dominant shrub genera. Data were analysed to identify periods and rates of establishment and mortality and to relate these to past climate. 3 Tree line elevation and stand density increased significantly during the early to mid 20th century. However, this change was not uniform across sites. Spruce advanced rapidly on south-facing slopes and tree line rose 65–85 m in elevation. Tree line did not advance on north-facing slopes, but stand density increased 40–65%. Differences observed between aspects were due primarily to the differential presence of permafrost. Additional variability among sites was related to slope and vegetation type. Results were less conclusive for willow, but evidence for an advance was found at two sites. 4 Increases in stand density were strongly correlated with summer temperatures. The period of rapid change coincided with a 30-year period of above average temperatures, beginning in 1920. The highest correlations were obtained using a forward average of 30–50 years, supporting the hypothesis that tree line dynamics are controlled more by conditions influencing recruitment than by establishment alone. 5 The changes observed at several sites are suggestive of a threshold response and challenge the notion that tree lines respond gradually to climate warming. Overall, the results provide further evidence to support the idea that the pattern and timing of change is contingent on local, landscape, and regional-scale factors, as well as species’ biology. [ABSTRACT FROM AUTHOR]

Non-linear variability in financial markets can emerge from several mechanisms, including simultaneity and time-varying coefficients. In simultaneous equation systems, the reduced-form coefficients that determine the behaviour of jointly dependent variables are products and ratios of the original structural coefficients. If the coefficients are stochastic, the resulting multiplicative interactions will result in high degrees of non-linearity. Processes generated in this way will scale as fractals: they will exhibit intermittent outliers and scaling symmetries, i.e. proportionality relationships between fluctuations at different separation distances. A model is specified in which both the exchange rate itself and the exchange rate residual exhibit simultaneity. The exchange rate depends on other exchange rates, while the residual depends on the other residuals. The model is then simulated using embedding noise from a t-distribution. The simulations replicate the observed properties of exchange rates, heavy-tailed distributions and long memory in the variance. A forecasting algorithm is specified in two stages. The first stage is a model for the actual process. In the second stage the residuals are modelled as a function of the predicted rate of change. The first and second stage models are then combined. This algorithm exploits the scaling symmetry: the residual is proportional to the predicted rate of change at separation distances corresponding to the forecast horizon. The procedure is tested empirically on three exchange rates. At a daily frequency and a 1-day forecast horizon, two-stage models reduce the forecast error by one fourth. At a 5-day horizon, the improvement is 10–15 percent. At a weekly frequency, the improvement at the 1-week horizon is on the order of 30–40 percent. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We compare linear autoregressive (AR) models and self-exciting threshold autoregressive (SETAR) models in terms of their point forecast performance, and their ability to characterize the uncertainty surrounding those forecasts, i.e. interval or density forecasts. A two-regime SETAR process is used as the data- generating process in an extensive set of Monte Carlo simulations, and we consider the discriminatory power of recently developed methods of forecast evaluation for different degrees of non-linearity. We find that the interval and density evaluation methods are unlikely to show the linear model to be deficient on samples of the size typical for macroeconomic data. [ABSTRACT FROM AUTHOR]

Following recent non-linear extensions of the present-value model, this paper examines the out-of-sample forecast performance of two parametric and two non-parametric nonlinear models of stock returns. The parametric models include the standard regime switching and the Markov regime switching, whereas the non-parametric are the nearest-neighbour and the artificial neural network models. We focused on the US stock market using annual observations spanning the period 1872-1999. Evaluation of forecasts was based on two criteria, namely forecast accuracy and forecast encompassing. In terms of accuracy, the Markov and the artificial neural network models produce at least as accurate forecasts as the other models. In terms of encompassing, the Markov model outperforms all the others. Overall, both criteria suggest that the Markov regime switching model is the most preferable non-linear empirical extension of the present-value model for out-of-sample stock return forecasting. [ABSTRACT FROM AUTHOR]

Recent empirical and theoretical work on river meanders suggests that instability is inherent. Within this context, an occurrence of multiple cut-offs could be interpreted as a clustering associated with self-organized criticality. Types of meander behaviour ranging from stable to chaotic are examined as trajectories or attractors within the phase space of rate of meander movement and bend curvature and change to the system is explored as shift from one attractor to another. It is suggested that this new approach provides insights into meander dynamics and provides a basis to identify the conditions, limits and constraints under which different behaviour occurs. Basic controls of energy and resistance underlie planform behaviour, but need to be refined in relation to the morphology and stability of channel courses. [ABSTRACT FROM AUTHOR]

Abstract. This paper presents the use of likelihood-based methods for controlled calibration. Recent results on higher-order asymptotics are exploited to obtain confidence regions for the output of the calibration process. A general likelihood-based approach is presented, and several types of calibration problems are tackled within this framework. The methods provide simple and accurate solutions which may have some potential usefulness for applications. The results are illustrated with reference to widely used models. [ABSTRACT FROM AUTHOR]

Abstract The whole spectrum of medicine consists of complex non-linear systems that are balanced and interact with each other. How non-linearity confers stability on a system and explains variation and uncertainty in clinical medicine is discussed. A major theme is that a small alteration in initial conditions may have a major effect on the end result. In the context of non-linearity, it is argued that ‘evidence-based medicine’ (EBM) as it exists today can only ever be relevant to a small fraction of the domain of medicine, that the ‘art of medicine’ consists of an intuitive ‘tuning in’ to these complex systems and as such is not so much an art as an expression of non-linear science. The main cause of iatrogenic disease is interpreted as a failure to understand the complexity of the systems being treated. Case study examples are given and analysed in non-linear terms. It is concluded that good medicine concerns individualized treatment of an individual patient whose body functions are governed by non-linear processes. EBM as it exists today paints with a broad and limited brush, but it does promise a fresh new direction. In this context, we need to expand the spectrum of scientific medicine to include non-linearity, and to look upon the ‘art of medicine’ as a historical (but unstated) legacy in this domain. [ABSTRACT FROM AUTHOR]

This paper analyses the net barter terms of trade measured by the primary commodity price index relative to the indexes of unit values of export of manufactures from industrial countries. The starting point is that the series is stationary but possibly non-linear. Statistical tests indicate that the logarithmed series is non-linear and we estimate a Smooth Transition Autoregressive model to describe the process. The dynamics of the model are illustrated by use of parametrically estimated local spectra and generalized impulse response functions. Our model encompasses models from several previous studies, and our conclusion is that the starting point very much decides the outcome. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The nature of the data we usually encounter in market-based accounting research is such that the results of the regressions of market capitalization on financial statement variables (referred to ‘price-levels’ regressions) are driven by a relatively small subset of the very largest firms in the sample. We refer to this overwhelming influence of the largest firms as the ‘scale effect’. This effect is more than heteroscedasticity. It arises due to the non-linearity in the relation between market capitalization and the financial statement variables. We present the case that scale is market capitalization rather than a correlated omitted variable. Since scale is market capitalization, we advocate its use as a deflator in a regression estimated using weighted least squares. This regression overcomes the scale effect and the resultant regression residuals are more economically meaningful. Christie's (1987) depiction of scale is the same as ours but he advocates the use of the returns regression specification in order to avoid scale effects. We agree that returns regressions should be used unless the research question calls for a price-levels regression. [ABSTRACT FROM AUTHOR]