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Part 1 The crowd: the fear of being touched the open and closed crowd the discharge destructiveness the eruption persecution domestication of crowds in the world religions panic the crowd as a ring the attributes of the crowd rhythm stagnation slowness, or the remoteness of the goal invisible crowds classification of crowds according to their prevailing emotion baiting crowds flight crowds prohibition crowds reversal crowds feast crowds the double crowd - men and women, the living and the dead the double crowd - war crowd crystals crowd symbols - fire, the sea, rain, rivers, forest, corn, wind, sand, the heap, stone heaps, treasure. Part 2 The pack: the pack - kinds of pack hunting pack the war pack the lamenting pack the increase pack the communion inward and tranquil packs the pack's determination, the historical premanence of packs packs in the ancestor legends of the Aranda temporary formation among the Aranda. Part 3 The pack and religion: the transmutation of packs hunting and the forest among the Lele of Kasai the war booty and the Jivaros the rain dances of the Pueblo Indians on the dynamics of war, the first death, the triumph Islam as a religion of war the religions of lament the Muharram festival of the Shiites Catholicism and the crowd the Holy Fire in Jerusalem. Part 4 The crowd in history: national crowd symbols - the English, the Dutch, the Germans, the French, the Swiss, the Spaniards, the Italians, the Jews Germany and Versailles inflation and the crowd the nature of the parliamentary system distribution and increase, socialism and production the self-destruction of the Xosas. Part 5 The entrails of power: seizing and incorporation the hand - the patience of the hand, the finger exercises of monkeys, the hands and the birth of objects, destructiveness in monkeys and men, the killers are always the powerful on the psychology of eating. Part 6 The survivor: the survivor survival and invulnerability survival as a passion the rules as survivor the escape of Josephus the despot's hostility to survivors, rulers and their successors forms of survival the survivor in primitive belief the resentment of the dead epidemics cemetries immortality. Part 7 Elements of power. Part content.

Detailed knowledge of the rates, equilibria, and mechanism of biochemical reactions has traditionally been acquired through experiments conducted on solutions containing low concentrations (less than about 1 mg/ml) of total protein, nucleic acid, and/or polysaccharide together with buffer salts, low molecular weight substrates, and cofactors as required. In contrast, biochemical reactions in living systems take place in media containing substantially greater total concentrations (50–400 mg/ml) of macromolecules that may be present in solution and/or in indefinitely large arrays (e.g. cytoskeletal fibers) (1Fulton A.B. Cell. 1982; 30: 345-347Abstract Full Text PDF PubMed Scopus (618) Google Scholar, 2Zimmerman S.B. Trach S.O. J. Mol. Biol. 1991; 222: 599-620Crossref PubMed Scopus (899) Google Scholar). Because no single macromolecular species may be present at high concentration, but all species taken together occupy a significant fraction of the volume of the medium, such media are referred to as "crowded" (3Minton A.P. Wilf J. Biochemistry. 1981; 20: 4821-4826Crossref PubMed Scopus (241) Google Scholar) and/or "confining" (4Minton A.P. Biophys. J. 1992; 63: 1090-1100Abstract Full Text PDF PubMed Scopus (158) Google Scholar) rather than "concentrated," depending upon whether the macrosolutes are soluble and/or structured. Fig.1 provides a schematic illustration of crowding and confinement in eukaryotic cytoplasm. In such media, nonspecific interactions between macrosolutes contribute significantly to the total free energy of the medium. High concentrations of "background" macromolecules that do not participate directly in a particular test reaction have been observed to induce order-of-magnitude or greater changes in the rates and equilibria of numerous test reactions (see below). To properly assess the physiological role of a particular reaction or set of reactions characterized in vitro, it is important to consider the possible influence of crowding and/or confinement upon the reaction in its physiological milieu. A nonspecific interaction between a pair of macromolecules does not depend strongly upon details of the primary, secondary, or tertiary structure(s) of the interacting macromolecules but rather upon global properties such as net charge, dipole or multipole moment, the polarity of surface residues, and macromolecular "shape." Nonspecific interactions may be either repulsive (steric, electrostatic) or attractive (electrostatic, hydrophobic) and are generally substantially weaker on a pairwise basis than specific interactions between reaction partners. The concept of "nonspecific interaction" is widely misunderstood. Many if not most biomedical researchers still regard such interaction as an artifact of a particular experimental system that interferes with the acquisition of meaningful data. Strategies such as extrapolation of results to zero macromolecular concentration are devised for the reduction or elimination of the influence of nonspecific interaction on a test reaction. Although such procedures may be appropriate in certain specific experimental situations, they do not necessarily provide results that are more meaningful in a biological context. On the contrary, significant nonspecific interaction is an unavoidable consequence of crowding and confinement in most or all physiological fluid media. To understand molecular processes in such media one must therefore take account of nonspecific interactions rather than attempt to eliminate them. The contribution of a particular solute species X to the total free energy of the system is a function of an effective concentration, called the thermodynamic activity of X, denoted byax. Thermodynamics teaches that equilibrium constants are generally expressed in terms of equilibrium activities rather than actual concentrations. As a simple example, consider a protein molecule that may reversibly self-associate to form a dimer. The equilibrium association constant for this reaction is K120=(a2/a12), where subscripts 1 and 2 refer to monomer and dimer, respectively. Biochemists are accustomed to seeing equilibrium constants written as ratios of equilibrium concentrations. However, the so-called equilibrium constant written in terms of concentrations,K12, is actually an apparent constant related to the true equilibrium constant, K120 , by K12≡(c2/c2)=K120()(γ12/γ2) γ2), where γi denotes the ratio of effective to actual concentrations of species i, termed the activity coefficient. The activity coefficient has a precise definition in terms of nonspecific solute-solute interaction, lnγi = <gi>/kT, where <gi> denotes the (composition-dependent) equilibrium average free energy of nonspecific interaction between a molecule of species i and all of the other macrosolutes present in the medium, k is the Boltzmann constant, and T is the absolute temperature. Steric repulsion is the most fundamental of all interactions between macromolecules in solution and is always present at finite concentration, independent of the magnitude of additional electrostatic or hydrophobic interactions. Because solute molecules are mutually impenetrable, the presence of a significant volume fraction of macromolecules in the medium places constraints on the placement of an additional molecule of test macrosolute that depend upon the relative sizes, shapes, and concentrations of all macrosolutes in the medium. Fig. 2 depicts a region, demarcated by a square outline, in a solution containing spherical "background" macrosolutes of radius rb, colored black, that occupy ∼30% of the total volume (vtot) of the specified region. The available volume (va,T) is defined to be that part of the volume of the region which may be occupied by the center of massof a molecule of a spherical test species T of radius rt added to the solution. If the test species is very small relative to the background species (Fig. 2 A), then the available volume, indicated inblue, is approximately equal to that part of the total volume not occupied by the background species, i.e. ∼0.7vtot. However, if the size of the test species is comparable with (or larger than) the background species (Fig.2 B), the available volume is substantially smaller, as the center of a molecule of the test species can approach the center of any background molecule to no less than the distance, denoted byrC, at which the surfaces of the two molecules contact each other. 1For markedly non-spherical molecules,rC is a function of the mutual orientations of test and background molecules. For approximately spherical molecules,rC may be treated as a constant equal to the sum of the average radii of test and background molecules. One may visualize this restriction by drawing a circular shell with radiusrC about each background molecule. Then the volume available to the test species, indicated by the blue-colored regions in Fig. 2 B, is that part of the total volume which is not occupied by any background molecule or by any shell. It is evident upon inspection of Fig. 2, A andB, that the available volume is a sensitive function of the relative sizes (and shapes) of test and background molecules and the number density of background molecules. 2Although Fig. 2, A and B,reflects a static distribution of background molecules, these conclusions hold also for a dynamic distribution, assuming equivalence of spatial and time averages. Volume may be excluded to a test particle by the surfaces of immobile structures as well as by individual background macrosolutes (4Minton A.P. Biophys. J. 1992; 63: 1090-1100Abstract Full Text PDF PubMed Scopus (158) Google Scholar, 5Giddings J.C. Kucera E. Russell C.P. Myers M.N. J. Phys. Chem. 1968; 72: 4397-4408Crossref Scopus (439) Google Scholar), as illustrated in Fig. 3, which depicts a pore with square cross-section. 3This pore is one possible idealized representation of a small element of volume bounded by large macromolecular assemblies, such as interstices within a lattice of rodlike fibers or lamellar space between adjacent membrane surfaces. The center of a spherical test molecule whose diameter is comparable with the largest dimension of the pore (Fig. 3 B) is excluded from thepink-colored region, which in this instance represents a significant fraction of the total volume of the solution enclosed in the pore. In a solution of macromolecules interacting exclusively via steric repulsion there exists an extremely simple relationship between the effective and actual concentration of each solute species (6Lebowitz J.L. Helfand E. Praestgaard E. J. Chem. Phys. 1965; 43: 774-779Crossref Scopus (496) Google Scholar), γi ≡ (ai/ci) = (νtot/νa,i), where νtot and νa,i denote the total volume and volume available to speciesi, respectively. The thermodynamic activities of macromolecules in fluid media may be measured by several physical-chemical methods. In Fig. 4, the experimentally measured ratio of the effective to actual concentration of hemoglobin, under experimental conditions comparable with those encountered in a red blood cell, is plotted as a function of the actual concentration. The first remarkable feature of this dependence is its highly non-linear nature; the effective concentration of hemoglobin exceeds the actual concentration by a factor of >10 at 200 g/liter and a factor approaching 100 at 300 g/liter. (For reference, the concentration of hemoglobin within a normal red blood cell typically exceeds 300 g/liter.) The second remarkable feature is that the experimentally measured dependence may be accounted for quantitatively over the entire concentration range by a simple geometrical model for available volume, in which each hemoglobin molecule is represented by a rigid spherical particle of radius ∼29.5 Å, i.e. a particle closely resembling a "shrink-wrapped" hemoglobin molecule (7Ross P.D. Minton A.P. J. Mol. Biol. 1977; 112: 437-452Crossref PubMed Scopus (211) Google Scholar, 8Guttman H.J. Anderson C.F. Record Jr., T.M. Biophys. J. 1995; 68: 835-846Abstract Full Text PDF PubMed Scopus (25) Google Scholar). The ratio of effective to actual concentration (i.e.activity coefficient) of a protein within a polymer gel may be calculated from the extent to which the protein partitions between the gel and bulk solution (4Minton A.P. Biophys. J. 1992; 63: 1090-1100Abstract Full Text PDF PubMed Scopus (158) Google Scholar, 5Giddings J.C. Kucera E. Russell C.P. Myers M.N. J. Phys. Chem. 1968; 72: 4397-4408Crossref Scopus (439) Google Scholar). In Fig. 5, this ratio, measured experimentally in a dextran gel occupying about 3% of total solution volume, is plotted for a variety of globular proteins as a function of molar mass. We note that the dependence of activity coefficient upon molar mass is reasonably independent of the identity of the protein, indicating that it is a property primarily of protein size and is insensitive to small changes in shape or composition. The solid curve was calculated using a simple geometrical model for available volume (9Ogston A.G. J. Phys. Chem. 1970; 74: 668-669Crossref Scopus (56) Google Scholar), in which each protein is modeled as a hard spherical particle with a radius proportional to the cube root of mass, and polymer is modeled as a random matrix of hard cylindrical rods. We present a simple example of how the difference between activity and concentration in a crowded medium may qualitatively influence association equilibria. 4A more complete treatment is presented in Ref.10Minton A.P. Biopolymers. 1981; 20: 2093-2120Crossref Scopus (468) Google Scholar. Consider the dimerization reaction introduced above, with real and apparent equilibrium constants defined in the first two equations. For the sake of illustration, we set the molar mass of A equal to 100,000 and assume that both A andA2 have roughly spherical shape. 5Although the dimer is unlikely to be spherical, its deviation from sphericity will not be so large that treatment as an approximate sphere will introduce a qualitative error into the present estimate (10Minton A.P. Biopolymers. 1981; 20: 2093-2120Crossref Scopus (468) Google Scholar). Using the same geometrical model for excluded volume and the same size and shape parameters used to fit the data in Fig. 5 (9Ogston A.G. J. Phys. Chem. 1970; 74: 668-669Crossref Scopus (56) Google Scholar), the values of γ1 and γ2 may be estimated to be about 3 × 102 and 1 × 104, respectively, for a fractional volume occupancy φ of 0.2, and about 1 × 104 and 1 × 106, respectively, for φ = 0.3. It follows from the second equation that the experimentally observed equilibrium constant,K12, would be expected to exceed K12o (the value ofK12 in the limit of high dilution) by a factor of ∼10 in a medium of φ = 0.2 and ∼100 in a medium of φ = 0.3. Although this estimate is only qualitative, the large magnitude of the predicted effect of excluded volume transcends the crudeness of the theoretical model. Indeed, similar but somewhat more refined predictions have been confirmed, in some cases quantitatively, by experimental observation (see references in Ref. 11Zimmerman S.B. Minton A.P. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 27-65Crossref PubMed Scopus (1244) Google Scholar and in TableI).Table ISome recent reports of experimentally observed crowding and confinement effects on macromolecular reactionsObservation 1-aPEG, polyethylene glycol.MagnitudeEnhancement of spectrin self-association by PEG, dextran (35Cole N. Ralston G.B. Int. J. Biochem. 1994; 26: 799-804Crossref PubMed Scopus (20) Google Scholar,36Lindner R. Ralston G. Biophys. Chem. 1995; 57: 15-25Crossref PubMed Scopus (43) Google Scholar) 1-bNumbers in parentheses are references.10-fold increase of K12 in 20% dextranEnhancement of actin polymerization by dextran and PEG (37Lindner R. Ralston G. Biophys. Chem. 1997; 66: 57-66Crossref PubMed Scopus (57) Google Scholar)3-fold decrease in solubility in 15% dextranEnhancement of binding of HU protein toE. coli DNA by PEG and non-DNA binding proteins (38Murphy L.D. Zimmerman S.B. Biochim. Biophys. Acta. 1994; 1219: 277-284Crossref PubMed Scopus (74) Google Scholar,39Murphy L.D. Zimmerman S.B. Biophys. Chem. 1995; 57: 71-92Crossref PubMed Scopus (77) Google Scholar)12% PEG increases affinity of DNA for HU by >10-foldStabilization of supercoiled conformations of DNA by PEG (40Naimushin A.N. Quach N. Fujimoto B.S. Schurr J.M. Biopolymers. 2001; 58: 204-217Crossref PubMed Scopus (13) Google Scholar)Sequestration of protein molecules in hydrated sol-gel glass stabilizes them with respect to thermal denaturation (41Eggers D. Valentine J. Protein Sci. 2001; 10: 250-261Crossref PubMed Scopus (358) Google Scholar)T50 for α-lactalbumin increased by >25 °CSelf-association of fibrinogen induced by bovine serum albumin (42Rivas G. Fernández J.A. Minton A.P. Biochemistry. 1999; 38: 9379-9388Crossref PubMed Scopus (145) Google Scholar)Doubling of weight-average molar mass in >5% bovine serum albuminEnhancement by dextran of limited self-association of tubulin under conditions not permitting microtubule assembly>2-fold increase in weight-average molar mass in 10% dextranEnhancement of self-association of FtsZ by bovine serum albumin, hemoglobin (43Rivas G. Fernández J.A. Minton A.P. Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 3150-3155Crossref PubMed Scopus (150) Google Scholar)2-fold increase in weight-average molar mass in 30% albumin or hemoglobinEnhancement of unimolecular condensation of large linear DNA by PEG (44Kidoaki S. Yoshikawa K. Biophys. Chem. 1999; 76: 133-143Crossref PubMed Scopus (27) Google Scholar)>10-fold increase in 2-state equilibrium constant at 18% PEGEnhancement of productive refolding and assembly of GroEL by Ficoll 70 (45Galan A. Sot B. Llorca O. Carrascosa J.L. Valpuesta J.M. Muga A. J. Biol. Chem. 2001; 276: 957-964Abstract Full Text Full Text PDF PubMed Scopus (40) Google Scholar)>3-fold increase in recovery of ATPase activity in presence of >10% FicollReduction in solubility of deoxy sickle cell hemoglobin by dextran (46Bookchin R.M. Balasz T. Wang Z. Josephs R. Lew V.L. J. Biol. Chem. 1999; 274: 6689-6697Abstract Full Text Full Text PDF PubMed Scopus (27) Google Scholar)∼15-fold decrease in 21% dextranEarlier observations are tabulated in Zimmerman and Minton (11Zimmerman S.B. Minton A.P. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 27-65Crossref PubMed Scopus (1244) Google Scholar).1-a PEG, polyethylene glycol.1-b Numbers in parentheses are references. Open table in a new tab Earlier observations are tabulated in Zimmerman and Minton (11Zimmerman S.B. Minton A.P. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 27-65Crossref PubMed Scopus (1244) Google Scholar). There are two opposing effects of excluded volume on reaction rates (12Minton A.P. Methods Enzymol. 1998; 295: 127-149Crossref PubMed Scopus (276) Google Scholar). If the overall rate of the reaction is limited by the rate with which a transition state complex decays to products, then crowding would be expected to enhance the relative abundance of the transition state complex and hence the forward reaction rate. Under these conditions, the forward rate constant may be increased by up to the equilibrium enhancement factor, depending upon details of the particular reaction. However, if the overall rate of the reaction is limited by the rate with which reactant molecules encounter each other through diffusional motion, then crowding, which retards diffusional motion (13Ogston A.G. Preston B.N. Wells J.D. Proc. R. Soc. Lond. A. 1973; 353: 297-316Google Scholar, 14Muramatsu N. Minton A.P. Proc. Natl. Acad. Sci. U. S. A. 1988; 85: 2984-2988Crossref PubMed Scopus (137) Google Scholar), would be expected to lower the forward reaction rate. In the limit of high fractional volume occupancy, all association reactions are expected to be diffusion limited and hence slowed by crowding (11Zimmerman S.B. Minton A.P. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 27-65Crossref PubMed Scopus (1244) Google Scholar). Hence, depending upon the nature of a particular reaction, one of two types of behavior may be observed as the fractional volume occupancy of background molecules increases: the forward rate for a macromolecular association may decrease monotonically or may initially increase, pass through a maximum, and then decrease. A bimodal dependence of reaction rate on crowder concentration has been observed experimentally (15Harrison B. Zimmerman S.B. Nucleic Acids Res. 1986; 14: 1863-1870Crossref PubMed Scopus (24) Google Scholar). Macromolecular crowding and/or confinement by background molecules or structures can in principle affect the equilibrium and kinetics of any macromolecular reaction in which there exists a significant difference between the volume excluded to reactants and the volume excluded to products. Such reactions include self- or heteroassociation, condensation (crystallization, nucleation-controlled fiber formation), binding of macromolecules to specific surface sites, nonspecific surface adsorption, and protein isomerization, including folding/unfolding (4Minton A.P. Biophys. J. 1992; 63: 1090-1100Abstract Full Text PDF PubMed Scopus (158) Google Scholar, 10Minton A.P. Biopolymers. 1981; 20: 2093-2120Crossref Scopus (468) Google Scholar, 11Zimmerman S.B. Minton A.P. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 27-65Crossref PubMed Scopus (1244) Google Scholar, 16Ralston G.B. J. Chem. Educ. 1990; 67: 857-860Crossref Scopus (82) Google Scholar, 17Minton A.P. Biophys. J. 1995; 68: 1311-1322Abstract Full Text PDF PubMed Scopus (69) Google Scholar, 18Minton A.P. Biophys. J. 2000; 78: 101-109Abstract Full Text Full Text PDF PubMed Scopus (186) Google Scholar). Crowding may also affect enzyme-catalyzed reactions of small molecules if the mechanism of catalysis involves significant conformational change of the enzyme (3Minton A.P. Wilf J. Biochemistry. 1981; 20: 4821-4826Crossref PubMed Scopus (241) Google Scholar,10Minton A.P. Biopolymers. 1981; 20: 2093-2120Crossref Scopus (468) Google Scholar). Many such effects have indeed been observed experimentally. Most of the older observations are cited in Ref. 11Zimmerman S.B. Minton A.P. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 27-65Crossref PubMed Scopus (1244) Google Scholar, and some more recent observations are listed in Table I. In recent years increased attention has been paid to the functioning of ever larger macromolecular assemblies and systems of interacting components, sometimes referred to as molecular machines (19Alberts B. Cell. 1998; 92: 291-294Abstract Full Text Full Text PDF PubMed Scopus (981) Google Scholar). As larger and more complex systems have come under closer scrutiny, a growing number of biomedical researchers have emphasized the extremely broad ramifications of macromolecular crowding and confinement for biochemistry in the intact cell (see for example Refs.20Garner M.M. Burg M.B. Am. J. Physiol. 1994; 266: C877-C892Crossref PubMed Google Scholar, 21Zimmerman S.B. Murphy L.D. FEBS Lett. 1996; 390: 245-248Crossref PubMed Scopus (114) Google Scholar, 22Martin J. Hartl F.-U. Proc. Natl. Acad. Sci. U. S. A. 1997; 94: 1107-1112Crossref PubMed Scopus (100) Google Scholar, 23Kornberg A. J. Bacteriol. 2000; 182: 3613-3618Crossref PubMed Scopus (77) Google Scholar, 24van den Berg B. Wain R. Dobson C.M. Ellis R.J. EMBO J. 2000; 19: 3870-3875Crossref PubMed Scopus (225) Google Scholar, 25Ellis R.J. Curr. Opin. Struct. Biol. 2001; 11: 114-119Crossref PubMed Scopus (840) Google Scholar). It is becoming more widely appreciated that under physiological conditions of crowding or confinement, the size- and shape-dependent reduction of volume available to every species of macromolecule results in major shifts in the rates and equilibria of a broad range of macromolecular reactions relative to those measured in dilute solution. We now recognize that nonspecific interactions, including (but not limited to) steric repulsion, provide a substantial contribution to the free energy balance of a physiological system such as an intact cell or tissue. It seems likely that the constituent elements of these systems have evolved to function optimally under normal physiological (i.e. crowded and/or confined) conditions and that the proper functioning of the system depends upon maintenance of the free energy balance established under those crowded and/or confined conditions. Excluded volume theory predicts that at the high level of macromolecular fractional volume occupancy characteristic of all living cells (i.e. >0.20–0.30), the reactivity of almost every soluble macromolecular species, dilute as well as concentrated, will depend sensitively upon its available volume, which, in turn, depends sensitively upon the total volume fraction of macromolecules. It follows that relatively small changes in the fractional volume occupancy of the cellular interior are expected to have major effects on the equilibria and kinetics of a broad variety of intracellular reactions (26Minton A.P. Strange K. Cellular and Molecular Physiology of Cell Volume Regulation. Scholar, A.P. Curr. Opin. Struct. Biol. 2000; 10: PubMed Scopus Google Scholar). to understand two very properties of living changes of cellular volume in cells (i.e. concentration of intracellular are with changes in the rates of a broad of intracellular processes that are large to be accounted for on the basis of simple mass S. E. D. Physiol. Rev. 1998; 78: PubMed Scopus Google Scholar). of cell so from to is with one or more widely types of for the maintenance or of cellular volume, and/or in to changes in of the fluid G. and and Scholar). The presented are only a of the that macromolecular crowding and confinement important and in cell and (11Zimmerman S.B. Minton A.P. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 27-65Crossref PubMed Scopus (1244) Google Scholar, 24van den Berg B. Wain R. Dobson C.M. Ellis R.J. EMBO J. 2000; 19: 3870-3875Crossref PubMed Scopus (225) Google S.B. Biochim. Biophys. Acta. 1993; PubMed Scopus Google Scholar, S. H.J. Record J. Mol. Biol. 1991; 222: PubMed Scopus Google Scholar, A.P. 1997; PubMed Scopus Google Scholar, R.J. Curr. Biol. 1997; Full Text Full Text PDF PubMed Google Scholar, S. H.J. Biochem. Sci. 1998; Full Text Full Text PDF PubMed Scopus Google Scholar). of excluded volume in physiological media are of magnitude to a role in for any macromolecular reaction the for of this and Zimmerman for

The amount of knowledge and talent dispersed among the human race has always outstripped our capacity to harness it. Crowdsourcing corrects thatbut in doing so, it also unleashes the forces of creative destruction. From CrowdsourcingFirst identified by journalist Jeff Howe in a June 2006 Wired article, crowdsourcing describes the process by which the power of the many can be leveraged to accomplish feats that were once the province of the specialized few. Howe reveals that the crowd is more than wiseits talented, creative, and stunningly productive. Crowdsourcing activates the transformative power of todays technology, liberating the latent potential within us all. Its a perfect meritocracy, where age, gender, race, education, and job history no longer matter; the quality of work is all that counts; and every field is open to people of every imaginable background. If you can perform the service, design the product, or solve the problem, youve got the job.But crowdsourcing has also triggered a dramatic shift in the way work is organized, talent is employed, research is conducted, and products are made and marketed. As the crowd comes to supplant traditional forms of labor, pain and disruption are inevitable. Jeff Howe delves into both the positive and negative consequences of this intriguing phenomenon. Through extensive reporting from the front lines of this revolution, he employs a brilliant array of stories to look at the economic, cultural, business, and political implications of crowdsourcing. How were a bunch of part-time dabblers in finance able to help an investment company consistently beat the market? Why does Procter & Gamble repeatedly call on enthusiastic amateurs to solve scientific and technical challenges? How can companies as diverse as iStockphoto and Threadless employ just a handful of people, yet generate millions of dollars in revenue every year? The answers lie within these pages. The blueprint for crowdsourcing originated from a handful of computer programmers who showed that a community of like-minded peers could create better products than a corporate behemoth like Microsoft. Jeff Howe tracks the amazing migration of this new model of production, showing the potential of the Internet to create human networks that can divvy up and make quick work of otherwise overwhelming tasks. One of the most intriguing ideas of Crowdsourcing is that the knowledge to solve intractable problemsa cure for cancer, for instancemay already exist within the warp and weave of this infinite and, as yet, largely untapped resource. But first, Howe proposes, we need to banish preconceived notions of how such problems are solved. The very concept of crowdsourcing stands at odds with centuries of practice. Yet, for the digital natives soon to enter the workforce, the technologies and principles behind crowdsourcing are perfectly intuitive. This generation collaborates, shares, remixes, and creates with a fluency and ease the rest of us can hardly understand. Crowdsourcing, just now starting to emerge, will in a short time simply be the way things are done.

We propose a novel crowd counting model that maps a given crowd scene to its density. Crowd analysis is compounded by myriad of factors like inter-occlusion between people due to extreme crowding, high similarity of appearance between people and background elements, and large variability of camera view-points. Current state-of-the art approaches tackle these factors by using multi-scale CNN architectures, recurrent networks and late fusion of features from multi-column CNN with different receptive fields. We propose switching convolutional neural network that leverages variation of crowd density within an image to improve the accuracy and localization of the predicted crowd count. Patches from a grid within a crowd scene are relayed to independent CNN regressors based on crowd count prediction quality of the CNN established during training. The independent CNN regressors are designed to have different receptive fields and a switch classifier is trained to relay the crowd scene patch to the best CNN regressor. We perform extensive experiments on all major crowd counting datasets and evidence better performance compared to current state-of-the-art methods. We provide interpretable representations of the multichotomy of space of crowd scene patches inferred from the switch. It is observed that the switch relays an image patch to a particular CNN column based on density of crowd.

The maturation of emergency medicine (EM) as a specialty has coincided with dramatic increases in emergency department (ED) visit rates, both in the United States and around the world. ED crowding has become a public health problem where periodic supply and demand mismatches in ED and hospital resources cause long waiting times and delays in critical treatments. ED crowding has been associated with several negative clinical outcomes, including higher complication rates and mortality. This article describes emergency care systems and the extent of crowding across 15 countries outside of the United States: Australia, Canada, Denmark, Finland, France, Germany, Hong Kong, India, Iran, Italy, The Netherlands, Saudi Arabia, Catalonia (Spain), Sweden, and the United Kingdom. The authors are local emergency care leaders with knowledge of emergency care in their particular countries. Where available, data are provided about visit patterns in each country; however, for many of these countries, no national data are available on ED visits rates or crowding. For most of the countries included, there is both objective evidence of increases in ED visit rates and ED crowding and also subjective assessments of trends toward higher crowding in the ED. ED crowding appears to be worsening in many countries despite the presence of universal health coverage. Scandinavian countries with robust systems to manage acute care outside the ED do not report crowding is a major problem. The main cause for crowding identified by many authors is the boarding of admitted patients, similar to the United States. Many hospitals in these countries have implemented operational interventions to mitigate crowding in the ED, and some countries have imposed strict limits on ED length of stay (LOS), while others have no clear plan to mitigate crowding. An understanding of the causes and potential solutions implemented in these countries can provide a lens into how to mitigate ED crowding in the United States through health policy interventions and hospital operational changes.

Crowdsourcing is an online, distributed problem-solving and production model already in use by businesses such as Threadless.com, iStockphoto.com, and InnoCentive.com. This model, which harnesses the collective intelligence of a crowd of Web users through an open-call format, has the potential for government and non-profit applications. Yet, in order to explore new applications for the crowdsourcing model, there must be a better understanding of why crowds participate in crowdsourcing processes. Based on 17 interviews conducted via instant messenger with members of the crowd at Threadless, the present study adds qualitatively rich data on a new crowdsourcing case to an existing body of quantitative data on motivations for participation in crowdsourcing. Four primary motivators for participation at Threadless emerge from these interview data: the opportunity to make money, the opportunity to develop one's creative skills, the potential to take up freelance work, and the love of community at Threadless. A fifth theme is also discussed that addresses the language of ‘addiction’ used by the interviewees to describe their activity on the site. Understanding this kind of ‘addiction’ in an online community is perhaps the most important finding for future public crowdsourcing ventures. This study develops a more complete – though ongoing – composite of what motivates the crowd to participate in crowdsourcing applications generally, information crucial to adapt the crowdsourcing model to new forms of problem-solving.

BACKGROUND: An Institute of Medicine (IOM) report defines six domains of quality of care: safety, patient-centeredness, timeliness, efficiency, effectiveness, and equity. The effect of emergency department (ED) crowding on these domains of quality has not been comprehensively evaluated. OBJECTIVES: The objective was to review the medical literature addressing the effects of ED crowding on clinically oriented outcomes (COOs). METHODS: We reviewed the English-language literature for the years 1989-2007 for case series, cohort studies, and clinical trials addressing crowding's effects on COOs. Keywords searched included "ED crowding,""ED overcrowding,""mortality,""time to treatment,""patient satisfaction,""quality of care," and others. RESULTS: A total of 369 articles were identified, of which 41 were kept for inclusion. Study quality was modest; most articles reflected observational work performed at a single institution. There were no randomized controlled trials. ED crowding is associated with an increased risk of in-hospital mortality, longer times to treatment for patients with pneumonia or acute pain, and a higher probability of leaving the ED against medical advice or without being seen. Crowding is not associated with delays in reperfusion for patients with ST-elevation myocardial infarction. Insufficient data were available to draw conclusions on crowding's effects on patient satisfaction and other quality endpoints. CONCLUSIONS: A growing body of data suggests that ED crowding is associated both with objective clinical endpoints, such as mortality, as well as clinically important processes of care, such as time to treatment for patients with time-sensitive conditions such as pneumonia. At least two domains of quality of care, safety and timeliness, are compromised by ED crowding.

Cross-scene crowd counting is a challenging task where no laborious data annotation is required for counting people in new target surveillance crowd scenes unseen in the training set. The performance of most existing crowd counting methods drops significantly when they are applied to an unseen scene. To address this problem, we propose a deep convolutional neural network (CNN) for crowd counting, and it is trained alternatively with two related learning objectives, crowd density and crowd count. This proposed switchable learning approach is able to obtain better local optimum for both objectives. To handle an unseen target crowd scene, we present a data-driven method to fine-tune the trained CNN model for the target scene. A new dataset including 108 crowd scenes with nearly 200,000 head annotations is introduced to better evaluate the accuracy of cross-scene crowd counting methods. Extensive experiments on the proposed and another two existing datasets demonstrate the effectiveness and reliability of our approach.

Purpose The purpose of this paper is to analyze the emerging crowd‐funding phenomenon, that is a collective effort by consumers who network and pool their money together, usually via the internet, in order to invest in and support efforts initiated by other people or organizations. Successful service businesses that organize crowd‐funding and act as intermediaries are emerging, attesting to the viability of this means of attracting investment. Design/methodology/approach The research employs a “grounded theory” approach, performing an in‐depth qualitative analysis of three cases involving crowd‐funding initiatives: SellaBand in the music business, Trampoline in financial services, and Kapipal in non‐profit services. These cases were selected to represent a diverse set of crowd‐funding operations that vary in terms of risk/return for the investor and the type of payoff associated to the investment. Findings The research addresses two research questions: how and why do consumers turn into crowd‐funding participants? and how and why do service providers set up a crowd‐funding initiative? Concerning the first research question, the authors' findings reveal purposes, characteristics, roles and tasks, and investment size of crowd‐funding activity from the consumer's point of view. Regarding the second research question, the authors' analysis reveals purposes, service roles, and network effects of crowd‐funding activity investigated from the point of view of the service organization that set up the initiative. Practical implications The findings also have implications for service managers interested in launching and/or managing crowd‐funding initiatives. Originality/value The paper addresses an emerging phenomenon and contributes to service theory in terms of extending the consumer's role from co‐production and co‐creation to investment.

Many NLP applications require manual text annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of complexity, the tasks may be conducted by crowd workers on platforms such as MTurk as well as trained annotators, such as research assistants. Using four samples of tweets and news articles ( n = 6,183), we show that ChatGPT outperforms crowd workers for several annotation tasks, including relevance, stance, topics, and frame detection. Across the four datasets, the zero-shot accuracy of ChatGPT exceeds that of crowd workers by about 25 percentage points on average, while ChatGPT’s intercoder agreement exceeds that of both crowd workers and trained annotators for all tasks. Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk. These results demonstrate the potential of large language models to drastically increase the efficiency of text classification.

BACKGROUND: Emergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions. AIM: The aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding. METHOD: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439). RESULTS: From 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions. CONCLUSIONS: The negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its "non-aerodynamic" shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.

Forecasting the flow of crowds is of great importance to traffic management and public safety, and very challenging as it is affected by many complex factors, such as inter-region traffic, events, and weather. We propose a deep-learning-based approach, called ST-ResNet, to collectively forecast the inflow and outflow of crowds in each and every region of a city. We design an end-to-end structure of ST-ResNet based on unique properties of spatio-temporal data. More specifically, we employ the residual neural network framework to model the temporal closeness, period, and trend properties of crowd traffic. For each property, we design a branch of residual convolutional units, each of which models the spatial properties of crowd traffic. ST-ResNet learns to dynamically aggregate the output of the three residual neural networks based on data, assigning different weights to different branches and regions. The aggregation is further combined with external factors, such as weather and day of the week, to predict the final traffic of crowds in each and every region. Experiments on two types of crowd flows in Beijing and New York City (NYC) demonstrate that the proposed ST-ResNet outperforms six well-known methods.

In this paper we introduce a system called Crowds for protecting users' anonymity on the world-wide-web. Crowds, named for the notion of “blending into a crowd,” operates by grouping users into a large and geographically diverse group (crowd) that collectively issues requests on behalf of its members. Web servers are unable to learn the true source of a request because it is equally likely to have originated from any member of the crowd, and even collaborating crowd members cannot distinguish the originator of a request from a member who is merely forwarding the request on behalf of another. We describe the design, implementation, security, performance, and scalability of our system. Our security analysis introduces degrees of anonymity as an important tool for describing and proving anonymity properties.

Social groups can be remarkably smart and knowledgeable when their averaged judgements are compared with the judgements of individuals. Already Galton [Galton F (1907) Nature 75:7] found evidence that the median estimate of a group can be more accurate than estimates of experts. This wisdom of crowd effect was recently supported by examples from stock markets, political elections, and quiz shows [Surowiecki J (2004) The Wisdom of Crowds]. In contrast, we demonstrate by experimental evidence (N = 144) that even mild social influence can undermine the wisdom of crowd effect in simple estimation tasks. In the experiment, subjects could reconsider their response to factual questions after having received average or full information of the responses of other subjects. We compare subjects' convergence of estimates and improvements in accuracy over five consecutive estimation periods with a control condition, in which no information about others' responses was provided. Although groups are initially "wise," knowledge about estimates of others narrows the diversity of opinions to such an extent that it undermines the wisdom of crowd effect in three different ways. The "social influence effect" diminishes the diversity of the crowd without improvements of its collective error. The "range reduction effect" moves the position of the truth to peripheral regions of the range of estimates so that the crowd becomes less reliable in providing expertise for external observers. The "confidence effect" boosts individuals' confidence after convergence of their estimates despite lack of improved accuracy. Examples of the revealed mechanism range from misled elites to the recent global financial crisis.

The Motivation Crowding Effect suggests that external intervention via monetary incentives or punishments may undermine, and under different identifiable conditions strengthen, intrinsic motivation. As of today, the theoretical possibility of motivation crowding has been the main subject of discussion among economists. This study demonstrates that the effect is also of empirical relevance . There exist a large number of studies, offering empirical evidence in support of the existence of crowding–out and crowding–in. The study is based on circumstantial evidence, laboratory studies by both psychologists and economists, as well as field research by econometric studies. The pieces of evidence presented refer to a wide variety of areas of the economy and society and have been collected for many different countries and periods of time. Crowding effects thus are an empirically relevant phenomenon, which can, in specific cases, even dominate the traditional relative price effect.

With the increasing size and frequency of mass events, the study of crowd disasters and the simulation of pedestrian flows have become important research areas. However, even successful modeling approaches such as those inspired by Newtonian force models are still not fully consistent with empirical observations and are sometimes hard to calibrate. Here, a cognitive science approach is proposed, which is based on behavioral heuristics. We suggest that, guided by visual information, namely the distance of obstructions in candidate lines of sight, pedestrians apply two simple cognitive procedures to adapt their walking speeds and directions. Although simpler than previous approaches, this model predicts individual trajectories and collective patterns of motion in good quantitative agreement with a large variety of empirical and experimental data. This model predicts the emergence of self-organization phenomena, such as the spontaneous formation of unidirectional lanes or stop-and-go waves. Moreover, the combination of pedestrian heuristics with body collisions generates crowd turbulence at extreme densities--a phenomenon that has been observed during recent crowd disasters. By proposing an integrated treatment of simultaneous interactions between multiple individuals, our approach overcomes limitations of current physics-inspired pair interaction models. Understanding crowd dynamics through cognitive heuristics is therefore not only crucial for a better preparation of safe mass events. It also clears the way for a more realistic modeling of collective social behaviors, in particular of human crowds and biological swarms. Furthermore, our behavioral heuristics may serve to improve the navigation of autonomous robots.

Many observations of the dynamics of pedestrian crowds, including various self-organization phenomena, have been successfully described by simple many-particle models. For ethical reasons, however, there is a serious lack of experimental data regarding crowd panic. Therefore, we have analyzed video recordings of the crowd disaster in Mina/Makkah during the Hajj in 1426H on 12 January 2006. They reveal two subsequent, sudden transitions from laminar to stop-and-go and "turbulent" flows, which question many previous simulation models. While the transition from laminar to stop-and-go flows supports a recent model of bottleneck flows [D. Helbing, Phys. Rev. Lett. 97, 168001 (2006)], the subsequent transition to turbulent flow is not yet well understood. It is responsible for sudden eruptions of pressure release comparable to earthquakes, which cause sudden displacements and the falling and trampling of people. The insights of this study into the reasons for critical crowd conditions are important for the organization of safer mass events. In particular, they allow one to understand where and when crowd accidents tend to occur. They have also led to organizational changes, which have ensured a safe Hajj in 1427H.

Abstract We present an example‐based crowd simulation technique. Most crowd simulation techniques assume that the behavior exhibited by each person in the crowd can be defined by a restricted set of rules. This assumption limits the behavioral complexity of the simulated agents. By learning from real‐world examples, our autonomous agents display complex natural behaviors that are often missing in crowd simulations. Examples are created from tracked video segments of real pedestrian crowds. During a simulation, autonomous agents search for examples that closely match the situation that they are facing. Trajectories taken by real people in similar situations, are copied to the simulated agents, resulting in seemingly natural behaviors.