Brigham Young University

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

SUMMARY: The program MODELTEST uses log likelihood scores to establish the model of DNA evolution that best fits the data. AVAILABILITY: The MODELTEST package, including the source code and some documentation is available at http://bioag.byu. edu/zoology/crandall_lab/modeltest.html.

Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

BACKGROUND: Somatoform disorders are characterised by chronic, medically unexplained physical symptoms (MUPS). Although different medications are part of treatment routines for people with somatoform disorders in clinics and private practices, there exists no systematic review or meta-analysis on the efficacy and tolerability of these medications. We aimed to synthesise to improve optimal treatment decisions. OBJECTIVES: To assess the effects of pharmacological interventions for somatoform disorders (specifically somatisation disorder, undifferentiated somatoform disorder, somatoform autonomic dysfunction, and pain disorder) in adults. SEARCH METHODS: We searched the Cochrane Depression, Anxiety and Neurosis Review Group's Specialised Register (CCDANCTR) (to 17 January 2014). This register includes relevant randomised controlled trials (RCTs) from The Cochrane Library (all years), MEDLINE (1950 to date), EMBASE (1974 to date), and PsycINFO (1967 to date). To identify ongoing trials, we searched ClinicalTrials.gov, Current Controlled Trials metaRegister, the World Health Organization International Clinical Trials Registry Platform, and the Chinese Clinical Trials Registry. For grey literature, we searched ProQuest Dissertation & Theses Database, OpenGrey, and BIOSIS Previews. We handsearched conference proceedings and reference lists of potentially relevant papers and systematic reviews and contacted experts in the field. SELECTION CRITERIA: We selected RCTs or cluster RCTs of pharmacological interventions versus placebo, treatment as usual, another medication, or a combination of different medications for somatoform disorders in adults. We included people fulfilling standardised diagnostic criteria for somatisation disorder, undifferentiated somatoform disorder, somatoform autonomic dysfunction, or somatoform pain disorder. DATA COLLECTION AND ANALYSIS: One review author and one research assistant independently extracted data and assessed risk of bias. Primary outcomes included the severity of MUPS on a continuous measure, and acceptability of treatment. MAIN RESULTS: We included 26 RCTs (33 reports), with 2159 participants, in the review. They examined the efficacy of different types of antidepressants, the combination of an antidepressant and an antipsychotic, antipsychotics alone, or natural products (NPs). The duration of the studies ranged between two and 12 weeks.One meta-analysis of placebo-controlled studies showed no clear evidence of a significant difference between tricyclic antidepressants (TCAs) and placebo for the outcome severity of MUPS (SMD -0.13; 95% CI -0.39 to 0.13; 2 studies, 239 participants; I(2) = 2%; low-quality evidence). For new-generation antidepressants (NGAs), there was very low-quality evidence showing they were effective in reducing the severity of MUPS (SMD -0.91; 95% CI -1.36 to -0.46; 3 studies, 243 participants; I(2) = 63%). For NPs there was low-quality evidence that they were effective in reducing the severity of MUPS (SMD -0.74; 95% CI -0.97 to -0.51; 2 studies, 322 participants; I(2) = 0%).One meta-analysis showed no clear evidence of a difference between TCAs and NGAs for severity of MUPS (SMD -0.16; 95% CI -0.55 to 0.23; 3 studies, 177 participants; I(2) = 42%; low-quality evidence). There was also no difference between NGAs and other NGAs for severity of MUPS (SMD -0.16; 95% CI -0.45 to 0.14; 4 studies, 182 participants; I(2) = 0%).Finally, one meta-analysis comparing selective serotonin reuptake inhibitors (SSRIs) with a combination of SSRIs and antipsychotics showed low-quality evidence in favour of combined treatment for severity of MUPS (SMD 0.77; 95% CI 0.32 to 1.22; 2 studies, 107 participants; I(2) = 23%).Differences regarding the acceptability of the treatment (rate of all-cause drop-outs) were neither found between NGAs and placebo (RR 1.01, 95% CI 0.64 to 1.61; 2 studies, 163 participants; I(2) = 0%; low-quality evidence) or NPs and placebo (RR 0.85, 95% CI 0.40 to 1.78; 3 studies, 506 participants; I(2) = 0%; low-quality evidence); nor between TCAs and other medication (RR 1.48, 95% CI 0.59 to 3.72; 8 studies, 556 participants; I(2) =14%; low-quality evidence); nor between antidepressants and the combination of an antidepressant and an antipsychotic (RR 0.80, 95% CI 0.25 to 2.52; 2 studies, 118 participants; I(2) = 0%; low-quality evidence). Percental attrition rates due to adverse effects were high in all antidepressant treatments (0% to 32%), but low for NPs (0% to 1.7%).The risk of bias was high in many domains across studies. Seventeen trials (65.4%) gave no information about random sequence generation and only two (7.7%) provided information about allocation concealment. Eighteen studies (69.2%) revealed a high or unclear risk in blinding participants and study personnel; 23 studies had high risk of bias relating to blinding assessors. For the comparison NGA versus placebo, there was relatively high imprecision and heterogeneity due to one outlier study. Although we identified 26 studies, each comparison only contained a few studies and small numbers of participants so the results were imprecise. AUTHORS' CONCLUSIONS: The current review found very low-quality evidence for NGAs and low-quality evidence for NPs being effective in treating somatoform symptoms in adults when compared with placebo. There was some evidence that different classes of antidepressants did not differ in efficacy; however, this was limited and of low to very low quality. These results had serious shortcomings such as the high risk of bias, strong heterogeneity in the data, and small sample sizes. Furthermore, the significant effects of antidepressant treatment have to be balanced against the relatively high rates of adverse effects. Adverse effects produced by medication can have amplifying effects on symptom perceptions, particularly in people focusing on somatic symptoms without medical causes. We can only draw conclusions about short-term efficacy of the pharmacological interventions because no trial included follow-up assessments. For each of the comparisons where there were available data on acceptability rates (NGAs versus placebo, NPs versus placebo, TCAs versus other medication, and antidepressants versus a combination of an antidepressant and an antipsychotic), no clear differences between the intervention and comparator were found.Future high-quality research should be carried out to determine the effectiveness of medications other than antidepressants, to compare antidepressants more thoroughly, and to follow-up participants over longer periods (the longest follow up was just 12 weeks). Another idea for future research would be to include other outcomes such as functional impairment or dysfunctional behaviours and cognitions as well as the classical outcomes such as symptom severity, depression, or anxiety.

Phylogenies are extremely useful tools, not only for establishing genealogical relationships among a group of organisms or their parts (e.g. genes), but also for a variety of research once the phylogenies are estimated. In a recent review, Pagel (1999) eloquently outline a number of uses for phylogenetic information from discovery of drug resistance to reconstructing the common ancestor to all of life. Phylogenies have been used to predict future trends in infectious disease ( Bush et al. 1999 ) and have even been offered as evidence in a court of law ( Vogel 1997). Yet phylogenies are only as useful as they are accurate. Estimating genealogical relationships among genes at the population level presents a number of difficulties to traditional methods of phylogeny reconstruction. These traditional methods such as parsimony, neighbour-joining, and maximum-likelihood make assumptions that are invalid at the population level. For example, these methods assume ancestral haplotypes are no longer in the population, yet coalescent theory predicts that ancestral haplotypes will be the most frequent sequences sampled in a population level study ( Watterson & Guess 1977; Donnelly & Tavaré 1986; Crandall & Templeton 1993). Traditional methods require reasonably large numbers of variable characters to accurately reconstruct relationships ( Huelsenbeck & Hillis 1993) and population level studies typically lack such variation. Also, recombination is a real possibility among sequences at the population level and traditional methods assume recombination does not occur. The failure to incorporate the possibility of recombination in phylogeny reconstruction can lead to grave errors in the resulting estimated phylogeny. The combination of these effects can lead parsimony methods to infer a cumbersome amount of most parsimonious trees at the population level with no resolution among the set (e.g. over one billion trees for a set of human mitochondrial DNA (mtDNA), Excoffier & Smouse 1994). These effects can also lead neighbour-joining and traditional maximum-likelihood methods to be over confident in the resulting relationships ( Bandelt et al. 1995 ). Therefore, an alternative approach is needed to provide accurate estimates of gene genealogies at the population level that take into account these population level phenomena not addressed by traditional methods. Multiple groups have looked to network representations for population level genealogical information ( Bandelt & Dress 1992; Templeton et al. 1992 ; Excoffier & Smouse 1994; Fitch 1997). Networks allow one to naturally incorporate the often-times nonbifurcating genealogical information associated with population level divergences. The method of Templeton et al. (1992) (TCS) has been used extensively with restriction site and nucleotide sequence data to infer population level genealogies when divergences are low ( Georgiadis et al. 1994 ; Routman et al. 1994 ; Gerber & Templeton 1996; Hedin 1997; Schaal et al. 1998 ; Viláet al. 1999 , Gómez-Zurita et al. 2000). TCS has been used with traditional methods to estimate relationships among organisms that span a wide range of divergence ( Crandall & Fitzpatrick 1996; Benabib et al. 1997 ). The approach has also been used extensively with a nested analysis procedure to partition population structure from population history ( Templeton et al. 1995 ; Templeton 1998) and explore the phylogeographic history of a diversity of organisms (e.g. Johnson & Jordon 2000; Turner et al. 2000 ). In this note, we announce the availability of a new software package, TCS, to estimate genealogical relationships among sequences using the method of Templeton et al. (1992) . The TCS software opens nucleotide sequence files in either nexus ( Maddison et al. 1997 ) or phylip ( Felsenstein 1991) sequential format. Sequences should not be collapsed into haplotypes as frequency data can be incorporated into the output. The program collapses sequences into haplotypes and calculates the frequencies of the haplotypes in the sample. These frequencies are used to estimate haplotype outgroup probabilities, which correlate with haplotype age ( Donnelly & Tavaré 1986; Castelloe & Templeton 1994). An absolute distance matrix is then calculated for all pairwise comparisons of haplotypes. The probability of parsimony [as defined in Templeton et al. (1992) , equations 6, 7, and 8] is calculated for pairwise differences until the probability exceeds 0.95. The number of mutational differences associated with the probability just before this 95% cut-off is then the maximum number of mutational connections between pairs of sequences justified by the ‘parsimony’ criterion. These justified connections are then made resulting in a 95% set of plausible solutions. The program outputs the sequences, the pairwise absolute distance matrix, probabilities of parsimony for mutational steps just beyond the 95% cut-off, a test listing of connections made and missing intermediates generated, and a graph output file containing the resulting network ( Fig. 1). This graph output file can be opened in the freeware VGJ 1.0.3 ( http://www.eng.auburn.edu/department/cse/research/graphdrawing/graphdrawing.html; distributed under the terms of the GNU General Public License, Version 2), which is packaged with the TCS algorithm. The program can handle a reasonable number of sequences. For example, an HTLV data set with 69 haplotypes of length 725 bp took over one hour to run in a Macintosh G3. Memory requirements are low, and the program will run with less than 1 MB RAM. The TCS software package, including executables for Mac and PC, documentation, and Java source code, is distributed freely and is available at our website, along with a host of other programs for population genetic and phylogenetic analyses: http://bioag.byu.edu/zoology/crandalllab/programs.htm. TCS Java interface. The maximum number of steps connecting parsimoniously two haplotypes is indicated. Gaps can be treated as a 5th state or as missing data. The graph can be edited and arranged using different algorithms. By double-clicking over a haplotype, some information is displayed, such as sequences included in the haplotype and outgroup weights. The haplotype with the highest outgroup probability is displayed as a square, while other haplotypes are displayed as ovals. The size of the square or oval corresponds to the haplotype frequency. This work was supported by the Alfred P. Sloan Foundation, a Shannon Award from the National Institutes of Health, and NIH R01-HD34350.

CONTEXT: Associations have been found between day-to-day particulate air pollution and increased risk of various adverse health outcomes, including cardiopulmonary mortality. However, studies of health effects of long-term particulate air pollution have been less conclusive. OBJECTIVE: To assess the relationship between long-term exposure to fine particulate air pollution and all-cause, lung cancer, and cardiopulmonary mortality. DESIGN, SETTING, AND PARTICIPANTS: Vital status and cause of death data were collected by the American Cancer Society as part of the Cancer Prevention II study, an ongoing prospective mortality study, which enrolled approximately 1.2 million adults in 1982. Participants completed a questionnaire detailing individual risk factor data (age, sex, race, weight, height, smoking history, education, marital status, diet, alcohol consumption, and occupational exposures). The risk factor data for approximately 500 000 adults were linked with air pollution data for metropolitan areas throughout the United States and combined with vital status and cause of death data through December 31, 1998. MAIN OUTCOME MEASURE: All-cause, lung cancer, and cardiopulmonary mortality. RESULTS: Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality. Each 10-microg/m(3) elevation in fine particulate air pollution was associated with approximately a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively. Measures of coarse particle fraction and total suspended particles were not consistently associated with mortality. CONCLUSION: Long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality.

BACKGROUND: Recent studies have reported associations between particulate air pollution and daily mortality rates. Population-based, cross-sectional studies of metropolitan areas in the United States have also found associations between particulate air pollution and annual mortality rates, but these studies have been criticized, in part because they did not directly control for cigarette smoking and other health risks. METHODS: In this prospective cohort study, we estimated the effects of air pollution on mortality, while controlling for individual risk factors. Survival analysis, including Cox proportional-hazards regression modeling, was conducted with data from a 14-to-16-year mortality follow-up of 8111 adults in six U.S. cities. RESULTS: Mortality rates were most strongly associated with cigarette smoking. After adjusting for smoking and other risk factors, we observed statistically significant and robust associations between air pollution and mortality. The adjusted mortality-rate ratio for the most polluted of the cities as compared with the least polluted was 1.26 (95 percent confidence interval, 1.08 to 1.47). Air pollution was positively associated with death from lung cancer and cardiopulmonary disease but not with death from other causes considered together. Mortality was most strongly associated with air pollution with fine particulates, including sulfates. CONCLUSIONS: Although the effects of other, unmeasured risk factors cannot be excluded with certainty, these results suggest that fine-particulate air pollution, or a more complex pollution mixture associated with fine particulate matter, contributes to excess mortality in certain U.S. cities.

BACKGROUND: The quality and quantity of individuals' social relationships has been linked not only to mental health but also to both morbidity and mortality. OBJECTIVES: This meta-analytic review was conducted to determine the extent to which social relationships influence risk for mortality, which aspects of social relationships are most highly predictive, and which factors may moderate the risk. DATA EXTRACTION: Data were extracted on several participant characteristics, including cause of mortality, initial health status, and pre-existing health conditions, as well as on study characteristics, including length of follow-up and type of assessment of social relationships. RESULTS: Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period. Significant differences were found across the type of social measurement evaluated (p<0.001); the association was strongest for complex measures of social integration (OR = 1.91; 95% CI 1.63 to 2.23) and lowest for binary indicators of residential status (living alone versus with others) (OR = 1.19; 95% CI 0.99 to 1.44). CONCLUSIONS: The influence of social relationships on risk for mortality is comparable with well-established risk factors for mortality. Please see later in the article for the Editors' Summary.

Efforts to understand and mitigate thehealth effects of particulate matter (PM) air pollutionhave a rich and interesting history. This review focuseson six substantial lines of research that have been pursued since 1997 that have helped elucidate our understanding about the effects of PM on human health. There hasbeen substantial progress in the evaluation of PM health effects at different time-scales of exposure and in the exploration of the shape of the concentration-response function. There has also been emerging evidence of PM-related cardiovascular health effects and growing knowledge regarding interconnected general pathophysiological pathways that link PM exposure with cardiopulmonary morbidiity and mortality. Despite important gaps in scientific knowledge and continued reasons for some skepticism, a comprehensive evaluation of the research findings provides persuasive evidence that exposure to fine particulate air pollution has adverse effects on cardiopulmonaryhealth. Although much of this research has been motivated by environmental public health policy, these results have important scientific, medical, and public health implications that are broader than debates over legally mandated air quality standards.

BackgroundExposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels.MethodsWe estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure–response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure–response functions spanning the global range of exposure.FindingsAmbient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000–422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015.InterpretationAmbient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction.FundingBill & Melinda Gates Foundation and Health Effects Institute.

This note considers the problem of information consensus among multiple agents in the presence of limited and unreliable information exchange with dynamically changing interaction topologies. Both discrete and continuous update schemes are proposed for information consensus. This note shows that information consensus under dynamically changing interaction topologies can be achieved asymptotically if the union of the directed interaction graphs have a spanning tree frequently enough as the system evolves.

Actual and perceived social isolation are both associated with increased risk for early mortality. In this meta-analytic review, our objective is to establish the overall and relative magnitude of social isolation and loneliness and to examine possible moderators. We conducted a literature search of studies (January 1980 to February 2014) using MEDLINE, CINAHL, PsycINFO, Social Work Abstracts, and Google Scholar. The included studies provided quantitative data on mortality as affected by loneliness, social isolation, or living alone. Across studies in which several possible confounds were statistically controlled for, the weighted average effect sizes were as follows: social isolation odds ratio (OR) = 1.29, loneliness OR = 1.26, and living alone OR = 1.32, corresponding to an average of 29%, 26%, and 32% increased likelihood of mortality, respectively. We found no differences between measures of objective and subjective social isolation. Results remain consistent across gender, length of follow-up, and world region, but initial health status has an influence on the findings. Results also differ across participant age, with social deficits being more predictive of death in samples with an average age younger than 65 years. Overall, the influence of both objective and subjective social isolation on risk for mortality is comparable with well-established risk factors for mortality.

Previous research suggests that knowledge diffusion occurs more quickly within Toyota’s production network than in competing automaker networks. In this paper we examine the ‘black box’ of knowledge sharing within Toyota’s network and demonstrate that Toyota’s ability to effectively create and manage network-level knowledge-sharing processes at least partially explains the relative productivity advantages enjoyed by Toyota and its suppliers. We provide evidence that suppliers do learn more quickly after participating in Toyota’s knowledge-sharing network. Toyota’s network has solved three fundamental dilemmas with regard to knowledge sharing by devising methods to (1) motivate members to participate and openly share valuable knowledge (while preventing undesirable spillovers to competitors), (2) prevent free riders, and (3) reduce the costs associated with finding and accessing different types of valuable knowledge. Toyota has done this by creating a strong network identity with rules for participation and entry into the network. Most importantly, production knowledge is viewed as the property of the network. Toyota’s highly interconnected, strong tie network has established a variety of institutionalized routines that facilitate multidirectional knowledge flows among suppliers. Our study suggests that the notion of a dynamic learning capability that creates competitive advantage needs to be extended beyond firm boundaries. Indeed, if the network can create a strong identity and coordinating rules, then it will be superior to a firm as an organizational form at creating and recombining knowledge due to the diversity of knowledge that resides within a network. Copyright © 2000 John Wiley & Sons, Ltd.

Python is an excellent "steering" language for scientific codes written in other languages. However, with additional basic tools, Python transforms into a high-level language suited for scientific and engineering code that's often fast enough to be immediately useful but also flexible enough to be sped up with additional extensions.

The use of space-division multiple access (SDMA) in the downlink of a multiuser multiple-input, multiple-output (MIMO) wireless communications network can provide a substantial gain in system throughput. The challenge in such multiuser systems is designing transmit vectors while considering the co-channel interference of other users. Typical optimization problems of interest include the capacity problem - maximizing the sum information rate subject to a power constraint-or the power control problem-minimizing transmitted power such that a certain quality-of-service metric for each user is met. Neither of these problems possess closed-form solutions for the general multiuser MIMO channel, but the imposition of certain constraints can lead to closed-form solutions. This paper presents two such constrained solutions. The first, referred to as "block-diagonalization," is a generalization of channel inversion when there are multiple antennas at each receiver. It is easily adapted to optimize for either maximum transmission rate or minimum power and approaches the optimal solution at high SNR. The second, known as "successive optimization," is an alternative method for solving the power minimization problem one user at a time, and it yields superior results in some (e.g., low SNR) situations. Both of these algorithms are limited to cases where the transmitter has more antennas than all receive antennas combined. In order to accommodate more general scenarios, we also propose a framework for coordinated transmitter-receiver processing that generalizes the two algorithms to cases involving more receive than transmit antennas. While the proposed algorithms are suboptimal, they lead to simpler transmitter and receiver structures and allow for a reasonable tradeoff between performance and complexity.

The purpose of this article is to provide a tutorial overview of information consensus in multivehicle cooperative control. Theoretical results regarding consensus-seeking under both time invariant and dynamically changing communication topologies are summarized. Several specific applications of consensus algorithms to multivehicle coordination are described

INSIGHTS about professional communication may come from odd and unexpected places. McCloud's Understanding Comics (hereafter UC) is a case in point. Despite the juvenile connotations evoked by any discussion of comic books, the theory of visual communication presented in UC arguably rivals the best of contemporary semiotics (that is, the study of how we make meaning out of gestures, words, paragraphs, pictures, and so on).

Abstract Do shareholders gain when managers disperse corporate resources through activities classified as corporate social responsibility (CSR)? Strategy scholars have recently developed a theoretical model that links such activities to shareholder value when a firm suffers a negative event; we test key portions of this theory of the ‘insurance‐like’ property of CSR activity. We posit that such activity leads to positive attributions from stakeholders, who then temper their negative judgments and sanctions toward firms because of this goodwill. We extend the risk management model by theorizing that some types of CSR activities will be more likely to create goodwill and offer insurance‐like protection than other types. We delineate several firm and event specific characteristics that we expect to influence the link between CSR activities and an insurance effect. We then test our model using an event study of 178 negative legal/regulatory actions against firms throughout the 11 years from 1993–2003. We find that participation in institutional CSR activities—those aimed at a firm's secondary stakeholders or society at large—provides an ‘insurance‐like’ benefit, while participation in technical CSRs—those activities targeting a firm's trading partners—yields no such benefits. We conclude by considering the implications of our findings for future theorizing and research into the economic value of CSR engagement. Copyright © 2008 John Wiley &amp; Sons, Ltd.

I present a complex theoretical explanation that draws on multiple bodies of literature to present an academically rigorous version of a simple argument: good deeds earn chits. I advance/defend three core assertions: (1) corporate philanthropy can generate positive moral capital among communities and stakeholders, (2) moral capital can provide shareholders with insurance-like protection for a firm's relationship-based intangible assets, and (3) this protection contributes to shareholder wealth. I highlight several managerial implications of these core assertions.

A technique is presented for deforming solid geometric models in a free-form manner. The technique can be used with any solid modeling system, such as CSG or B-rep. It can deform surface primitives of any type or degree: planes, quadrics, parametric surface patches, or implicitly defined surfaces, for example. The deformation can be applied either globally or locally. Local deformations can be imposed with any desired degree of derivative continuity. It is also possible to deform a solid model in such a way that its volume is preserved.The scheme is based on trivariate Bernstein polynomials, and provides the designer with an intuitive appreciation for its effects.