251 research outputs found
SMS texts on corruption help Ugandan voters hold elected councillors accountable at the polls
Many politicians manipulate information to prevent voters from holding them accountable; however, mobile text messages may make it easier for nongovernmental organizations to credibly share information on official corruption that is difficult for politicians to counter directly. We test the potential for texts on budget management to improve democratic accountability by conducting a large (n = 16,083) randomized controlled trial during the 2016 Ugandan district elections. In cooperation with a local partner, we compiled, simplified, and text-messaged official information on irregularities in local government budgets. Verified recipients of messages that described more irregularities than expected reported voting for incumbent councillors 6% less often; verified recipients of messages conveying fewer irregularities than expected reported voting for incumbent councillors 5% more often. The messages had no observable effect on votes for incumbent council chairs, potentially due to voters\u27 greater reliance on other sources of information for higher profile elections. These mixed results suggest that text messages on budget corruption help voters hold some politicians accountable in settings where elections are not free and fair
Individualized text messages about public services fail to sway voters: evidence from a field experiment on Ugandan elections
Mobile communication technologies can provide citizens access to information that is tailored to their specific circumstances. Such technologies may therefore increase citizens' ability to vote in line with their interests and hold politicians accountable. In a large-scale randomized controlled trial in Uganda (n = 16,083), we investigated whether citizens who receive private, timely, and individualized text messages by mobile phone about public services in their community punished or rewarded incumbents in local elections in line with the information. Respondents claimed to find the messages valuable and there is evidence that they briefly updated their beliefs based on the messages; however, the treatment did not cause increased votes for incumbents where public services were better than expected nor decreased votes where public services were worse than anticipated. The considerable knowledge gaps among citizens identified in this study indicate potential for communication technologies to effectively share civic information. Yet the findings imply that when the attribution of public service outcomes is difficult, even individualized information is unlikely to affect voting behavior
Information about service provision in Uganda is insufficient to affect voting behaviour
The quality of service provision in Uganda varies greatly across regions and between villages, and yet evidence suggests citizens’ are unable to assess these differences. A research experiment used SMS messages about public services to help Ugandans make informed voting decisions, but it found no effect on voting outcomes. Here is why information alone is sometimes insufficient to affect political behaviour
Emissions pathways, climate change, and impacts on California
The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine subalpine forests are reduced by 50–75%; and Sierra snowpack is reduced 30–70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine subalpine forests are reduced by 75–90%; and snowpack declines 73–90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California’s water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades
Gene prediction in metagenomic fragments: A large scale machine learning approach
<p>Abstract</p> <p>Background</p> <p>Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions.</p> <p>Results</p> <p>We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability.</p> <p>Conclusion</p> <p>Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments. In particular, the combination of linear discriminants and neural networks is promising and should be considered for integration into metagenomic analysis pipelines. The data sets can be downloaded from the URL provided (see Availability and requirements section).</p
New directions for patient-centred care in scleroderma : the Scleroderma Patient-centred Intervention Network (SPIN)
Systemic sclerosis (SSc), or scleroderma,
is a chronic multisystem autoimmune
disorder characterised by
thickening and fibrosis of the skin and
by the involvement of internal organs
such as the lungs, kidneys, gastrointestinal
tract, and heart. Because there is
no cure, feasibly-implemented and easily
accessible evidence-based interventions
to improve health-related quality
of life (HRQoL) are needed. Due to a
lack of evidence, however, specific recommendations
have not been made
regarding non-pharmacological interventions
(e.g. behavioural/psychological,
educational, physical/occupational
therapy) to improve HRQoL in SSc. The
Scleroderma Patient-centred Intervention
Network (SPIN) was recently organised
to address this gap. SPIN is
comprised of patient representatives,
clinicians, and researchers from Canada,
the USA, and Europe. The goal
of SPIN, as described in this article, is
to develop, test, and disseminate a set
of accessible interventions designed to
complement standard care in order to
improve HRQoL outcomes in SSc.The initial organisational meeting for SPIN was funded by a Canadian Institutes of Health Research (CIHR) Meetings, Planning, and Dissemination grant to B.D. Thombs (KPE-109130), Sclerodermie Quebec, and the Lady Davis Institute for Medical Research of the Jewish General Hospital, Montreal, Quebec. SPIN receives finding support from the Sclemderma Society of Ontario, the Scleroderma Society of Canada, and Sclerodermie Quebec. B.D. Thombs and M. Hudson are supported by New Investigator awards from the CIHR, and Etablissement de Jeunes Chercheurs awards from the Fonds de la Recherche en Sante Quebec (FRSQ). M. Baron is the director of the Canadian Scleroderma Research Group, which receives grant folding from the CIHR, the Scleroderma Society of Canada and its provincial chapters, Scleroderma Society of Ontario, Sclerodermie Quebec, and the Ontario Arthritis Society, and educational grants from Actelion Pharmaceuticals and Pfizer. M.D. Mayes and S. Assassi are supported by the NIH/NIAMS Scleroderma Center of Research Translation grant no. P50-AR054144. S.J. Motivala is supported by an NIH career development grant (K23 AG027860) and the UCLA Cousins Center for Psychoneuroimmunology. D. Khanna is supported by a NIH/NIAMS K23 AR053858-04) and NIH/NIAMS U01 AR057936A, the National Institutes of Health through the NIH Roadmap for Medical Research Grant (AR052177), and has served as a consultant or on speakers bureau for Actelion, BMS, Gilead, Pfizer, and United Therapeutics
The Mount Perkins block, northwestern Arizona: An exposed cross section of an evolving, preextensional to synextensional magmatic system
This is the published version. Reuse is subject to Society of Exploration Geophysicists terms of use and conditions.The steeply tilted Mount Perkins block, northwestern Arizona, exposes a cross section of a magmatic system that evolved through the onset of regional extension. New 40Ar/39Ar ages of variably tilted (0–90°) volcanic strata bracket extension between 15.7 and 11.3 Ma. Preextensional intrusive activity included emplacement of a composite Miocene laccolith and stock, trachydacite dome complex, and east striking rhyolite dikes. Related volcanic activity produced an ∼18–16 Ma stratovolcano, cored by trachydacite domes and flanked by trachydacite-trachyandesite flows, and ∼16 Ma rhyolite flows. Similar compositions indicate a genetic link between the stratovolcano and granodioritic phase of the laccolith. Magmatic activity synchronous with early regional extension (15.7–14.5 Ma) generated a thick, felsic volcanic sequence, a swarm of northerly striking subvertical rhyolite dikes, and rhyolite domes. Field relations and compositions indicate that the dike swarm and felsic volcanic sequence are cogenetic. Modes of magma emplacement changed during the onset of extension from subhorizontal sheets, east striking dikes, and stocks to northerly striking, subvertical dike swarms, as the regional stress field shifted from nearly isotropic to decidedly anisotropic with an east-west trending, horizontal least principal stress. Preextensional trachydacitic and preextensional to synextensional rhyolitic magmas were part of an evolving system, which involved the ponding of mantle-derived basaltic magmas and ensuing crustal melting and assimilation at progressively shallower levels. Major extension halted this system by generating abundant pathways to the surface (fractures), which flushed out preexisting crustal melts and hybrid magmas. Remaining silicic melts were quenched by rapid, upper crustal cooling induced by tectonic denudation. These processes facilitated eruption of mafic magmas. Accordingly, silicic magmatism at Mount Perkins ended abruptly during peak extension ∼14.5 Ma and gave way to mafic magmatism, which continued until extension ceased
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