Macro-micro feedback links of water management in South Africa : CGE analyses of selected policy regimes

The pressure on an already stressed water situation in South Africa is predicted to increase significantly under climate change, plans for large industrial expansion, observed rapid urbanization, and government programs to provide access to water to millions of previously excluded people. The present study employed a general equilibrium approach to examine the economy-wide impacts of selected macro and water related policy reforms on water use and allocation, rural livelihoods, and the economy at large. The analyses reveal that implicit crop-level water quotas reduce the amount of irrigated land allocated to higher-value horticultural crops and create higher shadow rents for production of lower-value, water-intensive field crops, such as sugarcane and fodder. Accordingly, liberalizing local water allocation in irrigation agriculture is found to work in favor of higher-value crops, and expand agricultural production and exports and farm employment. Allowing for water trade between irrigation and non-agricultural uses fueled by higher competition for water from industrial expansion and urbanization leads to greater water shadow prices for irrigation water with reduced income and employment benefits to rural households and higher gains for non-agricultural households. The analyses show difficult tradeoffs between general economic gains and higher water prices, making irrigation subsidies difficult to justify.Water Supply and Sanitation Governance and Institutions,Town Water Supply and Sanitation,Water Supply and Systems,Water and Industry,Water Conservation

Predicting Rising Follower Counts on Twitter Using Profile Information

When evaluating the cause of one's popularity on Twitter, one thing is considered to be the main driver: Many tweets. There is debate about the kind of tweet one should publish, but little beyond tweets. Of particular interest is the information provided by each Twitter user's profile page. One of the features are the given names on those profiles. Studies on psychology and economics identified correlations of the first name to, e.g., one's school marks or chances of getting a job interview in the US. Therefore, we are interested in the influence of those profile information on the follower count. We addressed this question by analyzing the profiles of about 6 Million Twitter users. All profiles are separated into three groups: Users that have a first name, English words, or neither of both in their name field. The assumption is that names and words influence the discoverability of a user and subsequently his/her follower count. We propose a classifier that labels users who will increase their follower count within a month by applying different models based on the user's group. The classifiers are evaluated with the area under the receiver operator curve score and achieves a score above 0.800.Comment: 10 pages, 3 figures, 8 tables, WebSci '17, June 25--28, 2017, Troy, NY, US

Detecting Sarcasm in Multimodal Social Platforms

Sarcasm is a peculiar form of sentiment expression, where the surface sentiment differs from the implied sentiment. The detection of sarcasm in social media platforms has been applied in the past mainly to textual utterances where lexical indicators (such as interjections and intensifiers), linguistic markers, and contextual information (such as user profiles, or past conversations) were used to detect the sarcastic tone. However, modern social media platforms allow to create multimodal messages where audiovisual content is integrated with the text, making the analysis of a mode in isolation partial. In our work, we first study the relationship between the textual and visual aspects in multimodal posts from three major social media platforms, i.e., Instagram, Tumblr and Twitter, and we run a crowdsourcing task to quantify the extent to which images are perceived as necessary by human annotators. Moreover, we propose two different computational frameworks to detect sarcasm that integrate the textual and visual modalities. The first approach exploits visual semantics trained on an external dataset, and concatenates the semantics features with state-of-the-art textual features. The second method adapts a visual neural network initialized with parameters trained on ImageNet to multimodal sarcastic posts. Results show the positive effect of combining modalities for the detection of sarcasm across platforms and methods.Comment: 10 pages, 3 figures, final version published in the Proceedings of ACM Multimedia 201

SUMOylation controls stem cell proliferation and regional cell death through Hedgehog signaling in planarians.

Mechanisms underlying anteroposterior body axis differences during adult tissue maintenance and regeneration are poorly understood. Here, we identify that post-translational modifications through the SUMO (Small Ubiquitin-like Modifier) machinery are evolutionarily conserved in the Lophotrocozoan Schmidtea mediterranea. Disruption of SUMOylation in adult animals by RNA-interference of the only SUMO E2 conjugating enzyme Ubc9 leads to a systemic increase in DNA damage and a remarkable regional defect characterized by increased cell death and loss of the posterior half of the body. We identified that Ubc9 is mainly expressed in planarian stem cells (neoblasts) but it is also transcribed in differentiated cells including neurons. Regeneration in Ubc9(RNAi) animals is impaired and associated with low neoblast proliferation. We present evidence indicating that Ubc9-induced regional cell death is preceded by alterations in transcription and spatial expression of repressors and activators of the Hedgehog signaling pathway. Our results demonstrate that SUMOylation acts as a regional-specific cue to regulate cell fate during tissue renewal and regeneration

Competition and Selection Among Conventions

In many domains, a latent competition among different conventions determines which one will come to dominate. One sees such effects in the success of community jargon, of competing frames in political rhetoric, or of terminology in technical contexts. These effects have become widespread in the online domain, where the data offers the potential to study competition among conventions at a fine-grained level. In analyzing the dynamics of conventions over time, however, even with detailed on-line data, one encounters two significant challenges. First, as conventions evolve, the underlying substance of their meaning tends to change as well; and such substantive changes confound investigations of social effects. Second, the selection of a convention takes place through the complex interactions of individuals within a community, and contention between the users of competing conventions plays a key role in the convention's evolution. Any analysis must take place in the presence of these two issues. In this work we study a setting in which we can cleanly track the competition among conventions. Our analysis is based on the spread of low-level authoring conventions in the eprint arXiv over 24 years: by tracking the spread of macros and other author-defined conventions, we are able to study conventions that vary even as the underlying meaning remains constant. We find that the interaction among co-authors over time plays a crucial role in the selection of them; the distinction between more and less experienced members of the community, and the distinction between conventions with visible versus invisible effects, are both central to the underlying processes. Through our analysis we make predictions at the population level about the ultimate success of different synonymous conventions over time--and at the individual level about the outcome of "fights" between people over convention choices.Comment: To appear in Proceedings of WWW 2017, data at https://github.com/CornellNLP/Macro

Comparison of Spectra in Unsequenced Species

International audienceWe introduce a new algorithm for the mass spectromet- ric identication of proteins. Experimental spectra obtained by tandem MS/MS are directly compared to theoretical spectra generated from pro- teins of evolutionarily closely related organisms. This work is motivated by the need of a method that allows the identication of proteins of unsequenced species against a database containing proteins of related organisms. The idea is that matching spectra of unknown peptides to very similar MS/MS spectra generated from this database of annotated proteins can lead to annotate unknown proteins. This process is similar to ortholog annotation in protein sequence databases. The difficulty with such an approach is that two similar peptides, even with just one mod- ication (i.e. insertion, deletion or substitution of one or several amino acid(s)) between them, usually generate very dissimilar spectra. In this paper, we present a new dynamic programming based algorithm: Packet- SpectralAlignment. Our algorithm is tolerant to modications and fully exploits two important properties that are usually not considered: the notion of inner symmetry, a relation linking pairs of spectrum peaks, and the notion of packet inside each spectrum to keep related peaks together. Our algorithm, PacketSpectralAlignment is then compared to SpectralAlignment [1] on a dataset of simulated spectra. Our tests show that PacketSpectralAlignment behaves better, in terms of results and execution tim

On the Origins of Memes by Means of Fringe Web Communities

Internet memes are increasingly used to sway and manipulate public opinion. This prompts the need to study their propagation, evolution, and influence across the Web. In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2.6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab, over the course of 13 months. We group the images posted on fringe Web communities (/pol/, Gab, and The_Donald subreddit) into clusters, annotate them using meme metadata obtained from Know Your Meme, and also map images from mainstream communities (Twitter and Reddit) to the clusters. Our analysis provides an assessment of the popularity and diversity of memes in the context of each community, showing, e.g., that racist memes are extremely common in fringe Web communities. We also find a substantial number of politics-related memes on both mainstream and fringe Web communities, supporting media reports that memes might be used to enhance or harm politicians. Finally, we use Hawkes processes to model the interplay between Web communities and quantify their reciprocal influence, finding that /pol/ substantially influences the meme ecosystem with the number of memes it produces, while \td has a higher success rate in pushing them to other communities.Comment: A shorter version of this paper appears in the Proceedings of 18th ACM Internet Measurement Conference (IMC 2018). This is the full versio

Search for Yukawa Production of a Light Neutral Higgs Boson at LEP

Within a Two-Higgs-Doublet Model (2HDM) a search for a light Higgs boson in the mass range of 4-12 GeV has been performed in the Yukawa process e+e- -> b bbar A/h -> b bbar tau+tau-, using the data collected by the OPAL detector at LEP between 1992 and 1995 in e+e- collisions at about 91 GeV centre-of-mass energy. A likelihood selection is applied to separate background and signal. The number of observed events is in good agreement with the expected background. Within a CP-conserving 2HDM type II model the cross-section for Yukawa production depends on xiAd = |tan beta| and xihd = |sin alpha/cos beta| for the production of the CP-odd A and the CP-even h, respectively, where tan beta is the ratio of the vacuum expectation values of the Higgs doublets and alpha is the mixing angle between the neutral CP-even Higgs bosons. From our data 95% C.L. upper limits are derived for xiAd within the range of 8.5 to 13.6 and for xihd between 8.2 to 13.7, depending on the mass of the Higgs boson, assuming a branching fraction into tau+tau- of 100%. An interpretation of the limits within a 2HDM type II model with Standard Model particle content is given. These results impose constraints on several models that have been proposed to explain the recent BNL measurement of the muon anomalous magnetic moment.Comment: 24 pages, 9 figures, Submitted to Euro. Phys. J.

Tests of model of color reconnection and a search for glueballs using gluon jets with a rapidity gap

Gluon jets with a mean energy of 22 GeV and purity of 95% are selected from hadronic Z0 decay events produced in e+e- annihilations. A subsample of these jets is identified which exhibits a large gap in the rapidity distribution of particles within the jet. After imposing the requirement of a rapidity gap, the gluon jet purity is 86%. These jets are observed to demonstrate a high degree of sensitivity to the presence of color reconnection, i.e. higher order QCD processes affecting the underlying color structure. We use our data to test three QCD models which include a simulation of color reconnection: one in the Ariadne Monte Carlo, one in the Herwig Monte Carlo, and the other by Rathsman in the Pythia Monte Carlo. We find the Rathsman and Ariadne color reconnection models can describe our gluon jet measurements only if very large values are used for the cutoff parameters which serve to terminate the parton showers, and that the description of inclusive Z0 data is significantly degraded in this case. We conclude that color reconnection as implemented by these two models is disfavored. The signal from the Herwig color reconnection model is less clear and we do not obtain a definite conclusion concerning this model. In a separate study, we follow recent theoretical suggestions and search for glueball-like objects in the leading part of the gluon jets. No clear evidence is observed for these objects.Comment: 42 pages, 18 figure