. This review focuses on the development of the ‘Little Ice Age’ as a glaciological and climatic concept, and evaluates its current usefulness in the light of new data on the glacier and climatic variations of the last millennium and of the Holocene. ‘Little Ice Age’ glacierization occurred over about 650 years and can be defined most precisely in the European Alps (c. AD 1300–1950) when extended glaciers were larger than before or since. ‘Little Ice Age’ climate is defined as a shorter time interval of about 330 years (c. AD 1570–1900) when Northern Hemisphere summer temperatures (land areas north of 20°N) fell significantly below the AD 1961–1990 mean. This climatic definition overlaps the times when the Alpine glaciers attained their latest two highstands (AD 1650 and 1850). It is emphasized, however, that ‘Little Ice Age’ glacierization was highly dependent on winter precipitation and that ‘Little Ice Age’ climate was not simply a matter of summer temperatures. Both the glacier‐centred and the climate‐centred concepts necessarily encompass considerable spatial and temporal variability, which are investigated using maps of mean summer temperature variations over the Northern Hemisphere at 30‐year intervals from AD 1571 to 1900. ‘Little Ice Age’‐type events occurred earlier in the Holocene as exemplified by at least seven glacier expansion episodes that have been identified in southern Norway. Such events provide a broader context and renewed relevance for the ‘Little Ice Age’, which may be viewed as a ‘modern analogue’ for the earlier events; and the likelihood that similar events will occur in the future has implications for climatic change in the twenty‐first century. It is concluded that the concept of a ‘Little Ice Age’ will remain useful only by (1) continuing to incorporate the temporal and spatial complexities of glacier and climatic variations as they become better known, and (2) by reflecting improved understanding of the Earth‐atmosphere‐ocean system and its forcing factors through the interaction of palaeoclimatic reconstruction with climate modelling.
We study the low-energy phenomenology of the little Higgs model. We first discuss the linearized effective theory of the ``littlest Higgs model'' and study the low-energy constraints on the model parameters. We identify sources of the corrections to low-energy observables, discuss model-dependent arbitrariness, and outline some possible directions of extensions of the model in order to evade the precision electroweak constraints. We then explore the characteristic signatures to test the model in the current and future collider experiments. We find that the CERN LHC has great potential to discover the new $\mathrm{SU}(2)$ gauge bosons and the possible new $U(1)$ gauge boson to the multi-TeV mass scale. Other states such as the colored vectorlike quark T and doubly charged Higgs boson ${\ensuremath{\Phi}}^{++}$ may also provide interesting signals. At a linear collider, precision measurements on the triple gauge boson couplings could be sensitive to the new physics scale of a few TeV. We provide a comprehensive list of the linearized interactions and vertices for the littlest Higgs model in the appendices.
Most investigations of creativity tend to take one of two directions: everyday creativity (also called “little-c”), which can be found in nearly all people, and eminent creativity (also called “Big-C”), which is reserved for the great. In this paper, the authors propose a Four C model of creativity that expands this dichotomy. Specifically, the authors add the idea of “mini-c,” creativity inherent in the learning process, and Pro-c, the developmental and effortful progression beyond little-c that represents professional-level expertise in any creative area. The authors include different transitions and gradations of these four dimensions of creativity, and then discuss advantages and examples of the Four C Model.
A detailed and relatively evenly resolved food web of Little Rock Lake, Wisconsin, was constructed to evaluate the sensitivity of food—web patterns to the level of detail (degree of resolution) in food—web data. This study presents definitions (e.g., ecosystem food webs) and methods for constructing and reducing the resolution of food webs to provide relatively pragmatic and rigorous touchstones for consistency in future food—web studies. This analysis suggests that food—web patterns such as the scale—invariant links—per—species ratio, short chain lengths, and limited number of trophic levels are constrained by the resolution of food—web data rather than by ecological factors. Patterns less sensitive to changes in resolution such as directed connectance (the proportion of observed directed links to all possible directed links) may be robust food—web attributes. The food web of Little Rock Lake appears to be the first highly and evenly resolved food web of a large natural ecosystem originally documented for the purpose of examining quantitative food—web patterns. This ecosystem food web contains roughly twice as many species as the largest web to date. It also may provide the most credible portrait available of the detailed trophic structure of a whole ecosystem. The 93—trophic—species web of Little Rock Lake differs from previously published trophic—species webs by having more links per species (L/S = 11), longer chain lengths (average: ≥10, maximum: ≥16), species at higher trophic levels (maximum: = 12), higher fractions of intermediate species, and smaller fractions of top species and links to top species. The sensitivity of quantitative food—web patterns to changes in resolution was examined in several series of tropically aggregated Little Rock Lake webs. Each of the series starts with a highly and relatively evenly resolved web with 182 consumer, producer, and decomposer taxa and ends with low—resolution webs with 9 aggregates of taxa. Taxa were aggregated based on the proportion of predators and prey shared by the taxa. Different series of webs were generated using different criteria for linking aggregates to evaluate the sensitivity of food—web patterns to linkage criteria. The sensitivity analysis revealed that several, but not all, quantitative food—web patterns are very sensitive to systematic aggregation of the web. Sensitive patterns include number of links per species, linkage complexity, the distributions of chain lengths and species among trophic levels, and the proportions of top species and links to top species. Less—sensitive patterns include connectance, the ratio of predators to prey, the proportions of intermediate and basal species, and the proportions of links that are between intermediate and basal species. Directed connectance is the only pattern examined that is both very robust to trophic aggregation and generally comparable to other community webs. Quantitative food—web patterns in published community webs are generally similar to highly aggregated Little Rock Lake webs (versions with 9—40 aggregates). These findings suggest that previously described community food webs are severely aggregated versions of more elaborate webs similar to that of Little Rock Lake.
The evidence for the Little Ice Age, the most important fluctuation in global climate in historical times, is most dramatically represented by the advance of mountain glaciers in the sixteenth and seventeenth centuries and their retreat since about 1850. The effects on the landscape and the daily life of people have been particularly apparent in Norway and the Alps. This major book places an extensive body of material relating to Europe, in the form of documentary evidence of the history of the glaciers, their portrayal in paintings and maps, and measurements made by scientists and others, within a global perspective. It shows that the glacial history of mountain regions all over the world displays a similar pattern of climatic events. Furthermore, fluctuations on a comparable scale have occurred at intervals of a millennium or two throughout the last ten thousand years since the ice caps of North America and northwest Europe melted away. This is the first scholarly work devoted to the Little Ice Age, by an author whose research experience of the subject has been extensive. This book includes large numbers of maps, diagrams and photographs, many not published elsewhere, and very full bibliographies. It is a definitive work on the subject, and an excellent focus for the work of economic and social historians as well as glaciologists, climatologists, geographers, and specialists in mountain environment.
The term Little Ice Age was originally coined by F Matthesin 1939 to describe the most recent 4000 year climaticinterval (the Late Holocene) associated with a particularlydramatic series of mountain glacier advances and retreats,analogous to, though considerably more moderate than, thePleistocene glacial fluctuations. This relatively prolongedperiod has now become known as the Neoglacial period.The term Little Ice Age is, instead, reserved for the mostextensive recent period of mountain glacier expansion and isconventionally defined as the 16th–mid 19th century periodduring which European climate was most strongly impacted.This period begins with a trend towards enhanced glacialconditions in Europe following the warmer conditions ofthe so-called medieval warm period or medieval climaticoptimum of Europe (
Global temperatures are known to have varied over the past 1500 years, but the spatial patterns have remained poorly defined. We used a global climate proxy network to reconstruct surface temperature patterns over this interval. The Medieval period is found to display warmth that matches or exceeds that of the past decade in some regions, but which falls well below recent levels globally. This period is marked by a tendency for La Niña-like conditions in the tropical Pacific. The coldest temperatures of the Little Ice Age are observed over the interval 1400 to 1700 C.E., with greatest cooling over the extratropical Northern Hemisphere continents. The patterns of temperature change imply dynamical responses of climate to natural radiative forcing changes involving El Niño and the North Atlantic Oscillation-Arctic Oscillation.
We present LITTLE THINGS (Local Irregulars That Trace Luminosity Extremes, The H I Nearby Galaxy Survey), which is aimed at determining what drives star formation in dwarf galaxies. This is a multi-wavelength survey of 37 dwarf irregular and 4 blue compact dwarf galaxies that is centered around H I-line data obtained with the National Radio Astronomy Observatory (NRAO) Very Large Array (VLA). The H I-line data are characterized by high sensitivity (≤1.1 mJy beam–1 per channel), high spectral resolution (≤2.6 km s–1), and high angular resolution (~6''). The LITTLE THINGS sample contains dwarf galaxies that are relatively nearby (≤10.3 Mpc; 6'' is ≤300 pc), that were known to contain atomic hydrogen, the fuel for star formation, and that cover a large range in dwarf galactic properties. We describe our VLA data acquisition, calibration, and mapping procedures, as well as H I map characteristics, and show channel maps, moment maps, velocity-flux profiles, and surface gas density profiles. In addition to the H I data we have GALEX UV and ground-based UBV and Hα images for most of the galaxies, and JHK images for some. Spitzer mid-IR images are available for many of the galaxies as well. These data sets are available online
Why can we never seem to keep on top of our workload, social diary or chores? Why does poverty persist around the world? Why do successful people do things at the last minute in a sudden rush of energy? Here, economist Sendhil Mullainathan and psychologist Eldar Shafir reveal that the hidden side of all these problems is that they're all about scarcity. We've all struggled with packing a suitcase with too many items and not enough time to do it. In Scarcity, two intellectual adventurers show us that this simple idea explains the most fundamental problems in all walks of life. Using the new science of scarcity, they explain why obesity is rampant; why people find it difficult to sleep when most sleep deprived; and why the lonely find it so hard to make friends. Scarcity will change the way you think about both the little everyday tasks and the big issues of global urgency. Sendhil Mullainathan is a Professor of Economics at Harvard, and a recipient of a MacArthur Foundation genius grant. He conducts research on development economics, behavioral economics, and corporate finance. He is Executive Director of Ideas 42, Institute of Quantitative Social Science, Harvard University. Eldar Shafir is William Stewart Tod Professor of Psychology and Public Affairs at Princeton University. Most of his work focuses on descriptive analyses of inference, judgment, and decision making, and on issues related to behavioral economics. 'Stars in their respective disciplines, and the combination is greater than the sum of its parts. Their project has a unique feel to it: it is the finest combination of heart and head that I have seen in our field', Daniel Kahneman, author of Thinking, Fast and Slow 'Scarcity is a captivating book, overflowing with new ideas, fantastic stories, and simple suggestions that just might change the way you live' Steven D. Levitt, coauthor of Freakonomics 'Here is a winning recipe. Take a behavioral economist and a cognitive psychologist, each a prominent leader in his field, and let their creative minds commingle. What you get is a highly original and easily readable book that is full of intriguing insights. What does a single mom trying to make partner at a major law firm have in common with a peasant who spends half her income on interest payments? The answer is scarcity. Read this book to learn the surprising ways in which scarcity affects us all', Richard Thaler, co-author of Nudge.
We examine models in which the dark energy density increases with time (so that the equation-of-state parameter $w$ satisfies $w<\ensuremath{-}1$), but $w\ensuremath{\rightarrow}\ensuremath{-}1$ asymptotically, such that there is no future singularity. We refine previous calculations to determine the conditions necessary to produce this evolution. Such models can display arbitrarily rapid expansion in the near future, leading to the destruction of all bound structures (a ``little rip''). We determine observational constraints on these models and calculate the point at which the disintegration of bound structures occurs. For the same present-day value of $w$, a big rip with constant $w$ disintegrates bound structures earlier than a little rip.
INTRODUCTION: Frequent assessments of rheumatoid arthritis (RA) disease activity allow timely adaptation of therapy, which is essential in preventing disease progression. However, values of acute phase reactants (APRs) are needed to calculate current composite activity indices, such as the Disease Activity Score (DAS)28, the DAS28-CRP (i.e. the DAS28 using C-reactive protein instead of erythrocyte sedimentation rate) and the Simplified Disease Activity Index (SDAI). We hypothesized that APRs make limited contribution to the SDAI, and that an SDAI-modification eliminating APRs - termed the Clinical Disease Activity Index (CDAI; i.e. the sum of tender and swollen joint counts [28 joints] and patient and physician global assessments [in cm]) - would have comparable validity in clinical cohorts. METHOD: Data sources comprised an observational cohort of 767 RA patients (average disease duration 8.1 +/- 10.6 years), and an independent inception cohort of 106 patients (disease duration 11.5 +/- 12.5 weeks) who were followed prospectively. RESULTS: Our clinically based hypothesis was statistically supported: APRs accounted only for 15% of the DAS28, and for 5% of the SDAI and the DAS28-CRP. In both cohorts the CDAI correlated strongly with DAS28 (R = 0.89-0.90) and comparably to the correlation of SDAI with DAS28 (R = 0.90-0.91). In additional analyses, the CDAI when compared to the SDAI and the DAS28 agreed with a weighted kappa of 0.70 and 0.79, respectively, and comparably to the agreement between DAS28 and DAS28-CRP. All three scores correlated similarly with Health Assessment Questionnaire (HAQ) scores (R = 0.45-0.47). The average changes in all scores were greater in patients with better American College of Rheumatology response (P < 0.0001, analysis of variance; discriminant validity). All scores exhibited similar correlations with radiological progression (construct validity) over 3 years (R = 0.54-0.58; P < 0.0001). CONCLUSION: APRs add little information on top (and independent) of the combination of clinical variables included in the SDAI. A purely clinical score is a valid measure of disease activity and will have its greatest merits in clinical practice rather than research, where APRs are usually always available. The CDAI may facilitate immediate and consistent treatment decisions and help to improve patient outcomes in the longer term.
Northern Hemisphere summer temperatures over the past 8000 years have been paced by the slow decrease in summer insolation resulting from the precession of the equinoxes. However, the causes of superposed century‐scale cold summer anomalies, of which the Little Ice Age (LIA) is the most extreme, remain debated, largely because the natural forcings are either weak or, in the case of volcanism, short lived. Here we present precisely dated records of ice‐cap growth from Arctic Canada and Iceland showing that LIA summer cold and ice growth began abruptly between 1275 and 1300 AD, followed by a substantial intensification 1430–1455 AD. Intervals of sudden ice growth coincide with two of the most volcanically perturbed half centuries of the past millennium. A transient climate model simulation shows that explosive volcanism produces abrupt summer cooling at these times, and that cold summers can be maintained by sea‐ice/ocean feedbacks long after volcanic aerosols are removed. Our results suggest that the onset of the LIA can be linked to an unusual 50‐year‐long episode with four large sulfur‐rich explosive eruptions, each with global sulfate loading >60 Tg. The persistence of cold summers is best explained by consequent sea‐ice/ocean feedbacks during a hemispheric summer insolation minimum; large changes in solar irradiance are not required.
Although research has established that receiving expressions of gratitude increases prosocial behavior, little is known about the psychological mechanisms that mediate this effect. We propose that gratitude expressions can enhance prosocial behavior through both agentic and communal mechanisms, such that when helpers are thanked for their efforts, they experience stronger feelings of self-efficacy and social worth, which motivate them to engage in prosocial behavior. In Experiments 1 and 2, receiving a brief written expression of gratitude motivated helpers to assist both the beneficiary who expressed gratitude and a different beneficiary. These effects of gratitude expressions were mediated by perceptions of social worth and not by self-efficacy or affect. In Experiment 3, we constructively replicated these effects in a field experiment: A manager's gratitude expression increased the number of calls made by university fundraisers, which was mediated by social worth but not self-efficacy. In Experiment 4, a different measure of social worth mediated the effects of an interpersonal gratitude expression. Our results support the communal perspective rather than the agentic perspective: Gratitude expressions increase prosocial behavior by enabling individuals to feel socially valued.
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Low-income countries typically collect taxes of between 10 to 20 percent of GDP while the average for high-income countries is more like 40 percent. In order to understand taxation, economic development, and the relationships between them, we need to think about the forces that drive the development process. Poor countries are poor for certain reasons, and these reasons can also help to explain their weakness in raising tax revenue. We begin by laying out some basic relationships regarding how tax revenue as a share of GDP varies with per capita income and with the breadth of a country's tax base. We sketch a baseline model of what determines a country's tax revenue as a share of GDP. We then turn to our primary focus: why do developing countries tax so little? We begin with factors related to the economic structure of these economies. But we argue that there is also an important role for political factors, such as weak institutions, fragmented polities, and a lack of transparency due to weak news media. Moreover, sociological and cultural factors—such as a weak sense of national identity and a poor norm for compliance—may stifle the collection of tax revenue. In each case, we suggest the need for a dynamic approach that encompasses the two-way interactions between these political, social, and cultural factors and the economy.
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An examination of the uses of data within a changing knowledge infrastructure, offering analysis and case studies from the sciences, social sciences, and humanities. “Big Data” is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data—because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure—an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation—six “provocations” meant to inspire discussion about the uses of data in scholarship—Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.
1. Planners Versus Searchers WHY PLANNERS CANNOT BRING PROSPERITY 2. The Legend of the Big Push 3. You Can't Plan a Market 4. Planners and Gangsters ACTING OUT THE BURDEN 5. The Rich Have Markets, the Poor Have Bureaucrats 6. Bailing Out the Poor 7. The Healers: Triumph and Tragedy THE WHITE MAN'S ARMY 8. From Colonialism to Postmodern Imperialism 9. Invading the Poor THE FUTURE 10. Homegrown Development 11. The Future of Western Assistance