Have a deep view into what people are curious about.

One red paperclip is a website created by Canadian blogger Kyle MacDonald, who bartered his way from a single red paperclip to a house in a series of fourteen online trades over the course of a year. MacDonald was inspired by the childhood game Bigger, Better. His site received a considerable amount of notice for tracking the transactions. "A lot of people have been asking how I've stirred up so much publicity around the project, and my simple answer is: 'I have no idea'", he told the BBC.

Neutral monism is an umbrella term for a class of metaphysical theories in the philosophy of mind, concerning the relation of mind to matter. These theories take the fundamental nature of reality to be neither mental nor physical; in other words it is "neutral".

Neutral monism has gained prominence as a potential solution to theoretical issues within the philosophy of mind, specifically the mind–body problem and the hard problem of consciousness. The mind–body problem is the problem of explaining how mind relates to matter. The hard problem is a related philosophical problem targeted at physicalist theories of mind specifically: the problem arises because it is not obvious how a purely physical universe could give rise to conscious experience. This is because physical explanations are mechanistic: that is, they explain phenomena by appealing to underlying functions and structures. And, though explanations of this sort seem to work well for a wide variety of phenomena, conscious experience seems uniquely resistant to functional explanations. As the philosopher David Chalmers has put it: "even when we have explained the performance of all the cognitive and behavioral functions in the vicinity of experience - perceptual discrimination, categorization, internal access, verbal report - there may still remain a further unanswered question: Why is the performance of these functions accompanied by experience?" The hard problem has motivated Chalmers and other philosophers to abandon the project of explaining consciousness in terms physical or chemical mechanisms (only 56.5% of philosophers are physicalists, according to the most recent PhilPapers survey).

With this, there has been growing demand for alternative ontologies (such as neutral monism) that may provide explanatory frameworks more suitable for explaining the existence of consciousness. It has been accepted by several prominent English-speaking philosophers, such as William James and Bertrand Russell.

This is a list of present-day cities by the time period over which they have been continuously inhabited as a city. The age claims listed are generally disputed. Differences in opinion can result from different definitions of "city" as well as "continuous habitation" and historical evidence is often disputed. Caveats (and sources) to the validity of each claim are discussed in the "Notes" column.

In computing, a zooming user interface or zoomable user interface (ZUI, pronounced zoo-ee) is a type of graphical user interface (GUI) where users can change the scale of the viewed area in order to see more detail or less, and browse through different documents. Information elements appear directly on an infinite virtual desktop (usually created using vector graphics), instead of in windows. Users can pan across the virtual surface in two dimensions and zoom into objects of interest. For example, as you zoom into a text object it may be represented as a small dot, then a thumbnail of a page of text, then a full-sized page and finally a magnified view of the page.

ZUIs use zooming as the main metaphor for browsing through hyperlinked or multivariate information. Objects present inside a zoomed page can in turn be zoomed themselves to reveal further detail, allowing for recursive nesting and an arbitrary level of zoom.

When the level of detail present in the resized object is changed to fit the relevant information into the current size, instead of being a proportional view of the whole object, it's called semantic zooming.

Some consider the ZUI paradigm as a flexible and realistic successor to the traditional windowing GUI, being a Post-WIMP interface.

The Mississippi River Basin Model Waterways Experiment Station, located near Clinton, Mississippi, was a large-scale hydraulic model of the entire Mississippi River basin, covering an area of 200 acres. The model was built from 1943 to 1966 and in operation from 1949 until 1973. By comparison, the better known San Francisco Bay Model covers 1.5 acres and the Chesapeake Bay Model covers 8 acres. The model is now derelict, but open to the public within Buddy Butts Park, Jackson.

The Brussels effect is the process of unilateral regulatory globalisation caused by the European Union de facto (but not necessarily de jure) externalising its laws outside its borders through market mechanisms.

Ys (pronounced EESS), also spelled Is or Kêr-Is in Breton, and Ville d'Ys in French, is a mythical city on the coast of Brittany that was swallowed up by the ocean. Most versions of the legend place the city in the Baie de Douarnenez.

Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced . They are two strongly related non-parametric regression methods that combine multiple regression models in a k-nearest-neighbor-based meta-model. In some fields, LOESS is known and commonly referred to as Savitzky–Golay filter (proposed 15 years before LOESS).

LOESS and LOWESS thus build on "classical" methods, such as linear and nonlinear least squares regression. They address situations in which the classical procedures do not perform well or cannot be effectively applied without undue labor. LOESS combines much of the simplicity of linear least squares regression with the flexibility of nonlinear regression. It does this by fitting simple models to localized subsets of the data to build up a function that describes the deterministic part of the variation in the data, point by point. In fact, one of the chief attractions of this method is that the data analyst is not required to specify a global function of any form to fit a model to the data, only to fit segments of the data.

The trade-off for these features is increased computation. Because it is so computationally intensive, LOESS would have been practically impossible to use in the era when least squares regression was being developed. Most other modern methods for process modeling are similar to LOESS in this respect. These methods have been consciously designed to use our current computational ability to the fullest possible advantage to achieve goals not easily achieved by traditional approaches.

A smooth curve through a set of data points obtained with this statistical technique is called a loess curve, particularly when each smoothed value is given by a weighted quadratic least squares regression over the span of values of the y-axis scattergram criterion variable. When each smoothed value is given by a weighted linear least squares regression over the span, this is known as a lowess curve; however, some authorities treat lowess and loess as synonyms.

Benford's law, also called the Newcomb–Benford law, the law of anomalous numbers, or the first-digit law, is an observation about the frequency distribution of leading digits in many real-life sets of numerical data. The law states that in many naturally occurring collections of numbers, the leading significant digit is likely to be small. For example, in sets that obey the law, the number 1 appears as the leading significant digit about 30% of the time, while 9 appears as the leading significant digit less than 5% of the time. If the digits were distributed uniformly, they would each occur about 11.1% of the time. Benford's law also makes predictions about the distribution of second digits, third digits, digit combinations, and so on.

The graph to the right shows Benford's law for base 10. There is a generalization of the law to numbers expressed in other bases (for example, base 16), and also a generalization from leading 1 digit to leading n digits.

It has been shown that this result applies to a wide variety of data sets, including electricity bills, street addresses, stock prices, house prices, population numbers, death rates, lengths of rivers, physical and mathematical constants. Like other general principles about natural data—for example the fact that many data sets are well approximated by a normal distribution—there are illustrative examples and explanations that cover many of the cases where Benford's law applies, though there are many other cases where Benford's law applies that resist a simple explanation. It tends to be most accurate when values are distributed across multiple orders of magnitude, especially if the process generating the numbers is described by a power law (which are common in nature).

It is named after physicist Frank Benford, who stated it in 1938 in a paper titled "The Law of Anomalous Numbers", although it had been previously stated by Simon Newcomb in 1881.