Using markers for digital engagement and social change: Tracking meaningful narrative exchange in transmedia edutainment with text analytics techniques

While social media offer an unprecedented opportunity for orchestrating large-scale communication campaigns, it is often difficult to track audience responses on various digital platforms over time and to ascertain if their engagement is aligned with the original intention. In this article, we share a promising solution—the purposive embedding and tracking of unique content elements as “markers” using text analytics techniques. Four markers were introduced in an Indian melodramatic television serial, Main Kuch Bhi Kar Sakti Hoon (I, A Woman, Can Achieve Anything), which was part of a larger transmedia edutainment initiative in India to promote sanitation, family planning, and gender equality. These markers served as anchors for audience engagement with the originally intended messaging embedded in the narratives as well as for program monitoring and evaluation. We applied various web-based tools to systematically track marker-related engagement on Facebook, Twitter, and YouTube across eight months. We also conducted semantic network analysis to better understand how marker-related social media comments evolved over time. Our investigation of using markers for digital engagement and narrative exchange in MKBKSH makes an important and timely methodological contribution to the scholarship and praxis of social and behavior change communication.Using markers for digital engagement and social change: Tracking meaningful narrative exchange in transmedia edutainment with text analytics techniquespublishedVersio

Transgender and anxiety: a comparative study between transgender people and the general population

Background: Anxiety disorders pose serious public health problems. The data available on anxiety disorders in the transgender population is limited by the small numbers, the lack of a matched controlled population and the selection of a nonhomogenous group of transgender people. Aims: The aims of the study were (1) to determine anxiety symptomatology (based on the HADS) in a nontreated transgender population and to compare it to a general population sample matched by age and gender; (2) to investigate the predictive role of specific variables, including experienced gender, self-esteem, victimization, social support, interpersonal functioning, and cross-sex hormone use regarding levels of anxiety symptomatology; and (3) to investigate differences in anxiety symptomatology between transgender people on cross-sex hormone treatment and not on hormone treatment. Methods: A total of 913 individuals who self-identified as transgender attending a transgender health service during a 3-year period agreed to participate. For the first aim of the study, 592 transgender people not on treatment were matched by age and gender, with 3,816 people from the general population. For the second and third aim, the whole transgender population was included. Measurements: Sociodemographic variables and measures of depression and anxiety (HADS), self-esteem (RSE), victimization (ETS), social support (MSPSS), and interpersonal functioning (IIP-32). Results: Compared with the general population transgender people had a nearly threefold increased risk of probable anxiety disorder (all p < .05). Low self-esteem and interpersonal functioning were found to be significant predictors of anxiety symptoms. Trans women on treatment with cross-sex hormones were found to have lower levels of anxiety disorder symptomatology. Conclusions: Transgender people (particularly trans males) have higher levels of anxiety symptoms suggestive of possible anxiety disorders compared to the general population. The findings that self-esteem, interpersonal functioning, and hormone treatment are associated with lower levels of anxiety symptoms indicate the need for clinical interventions targeting self-esteem and interpersonal difficulties and highlight the importance of quick access to transgender health services

Ecophysiological basis of spatiotemporal patterns in picophytoplankton pigments in the global ocean

Information on the intracellular content and functional diversity of phytoplankton pigments can provide valuable insight on the ecophysiological state of primary producers and the flow of energy within aquatic ecosystems. Combined global datasets of analytical flow cytometry (AFC) cell counts and High-Performance Liquid Chromatography (HPLC) pigment concentrations were used to examine vertical and seasonal variability in the ratios of phytoplankton pigments in relation to indices of cellular photoacclimation. Across all open ocean datasets, the weight-to-weight ratio of photoprotective to photosynthetic pigments showed a strong depth dependence that tracked the vertical decline in the relative availability of light. The Bermuda Atlantic Time-series Study (BATS) dataset revealed a general increase in surface values of the relative concentrations of photoprotective carotenoids from the winter-spring phytoplankton communities dominated by low-light acclimated eukaryotic microalgae to the summer and early autumn communities dominated by high-light acclimated picocyanobacteria. In Prochlorococcus-dominated waters, the vertical decline in the relative contribution of photoprotective pigments to total pigment concentration could be attributed in large part to changes in the cellular content of photosynthetic pigments (PSP) rather than photoprotective pigments (PPP), as evidenced by a depth-dependent increase of the intracellular concentration of the divinyl chlorophyll-a (DVChl-a) whilst the intracellular concentration of the PPP zeaxanthin remained relatively uniform with depth. The ability of Prochlorococcus cells to adjust their DVChl-a cell-1 over a large gradient in light intensity was reflected in more highly variable estimates of carbon-to-Chl-a ratio compared to those reported for other phytoplankton groups. This cellular property is likely the combined result of photoacclimatory changes at the cellular level and a shift in dominant ecotypes. Developing a mechanistic understanding of sources of variability in pigmentation of picocyanobacteria is critical if the pigment markers and bio-optical properties of these cells are to be used to map their biogeography and serve as indicators of photoacclimatory state of subtropical phytoplankton communities more broadly. It would also allow better assessment of effects on, and adaptability of phytoplankton communities in the tropical/subtropical ocean due to climate chang

Helping feed the world with rice innovations: CGIAR research adoption and socioeconomic impact on farmers

Rice production has increased significantly with the efforts of international research centers and national governments in the past five decades. Nonetheless, productivity improvement still needs to accelerate in the coming years to feed the growing population that depends on rice for calories and nutrients. This challenge is compounded by the increasing scarcity of natural resources such as water and farmland. This article reviews 17 ex-post impact assessment studies published from 2016 to 2021 on rice varieties, agronomic practices, institutional arrangements, information and communication technologies, and post-harvest technologies used by rice farmers. From the review of these selected studies, we found that stress-tolerant varieties in Asia and Africa significantly increased rice yield and income. Additionally, institutional innovations, training, and natural resource management practices, such as direct-seeded rice, rodent control, and iron-toxicity removal, have had a considerable positive effect on smallholder rice farmers’ economic well-being (income and rice yield). Additional positive impacts are expected from the important uptake of stress-tolerant varieties documented in several Asian, Latin American, and African countries

Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

Evaluation of the third- and fourth-generation GOCE Earth gravity field models with Australian terrestrial gravity data in spherical harmonics

In March 2013 the fourth generation of ESA’s (European Space Agency) global gravity field models, DIR4 (Bruinsma et al, 2010b) and TIM4 (Pail et al, 2010), generated from the GOCE (Gravity field and steady-state Ocean Circulation Explorer) gravity observation satellite were released. We evaluate the models using an independent ground truth data set of gravity anomalies over Australia. Combined with GRACE (Gravity Recovery and Climate Experiment) satellite gravity, a new gravity model is obtained that is used to perform comparisons with GOCE models in spherical harmonics. Over Australia, the new gravity model proves to have significantly higher accuracy in the degrees below 120 as compared to EGM2008 and seems to be at least comparable to the accuracy of this model between degree 150 and degree 260. Comparisons in terms of residual quasi-geoid heights, gravity disturbances, and radial gravity gradients evaluated on the ellipsoid and at approximate GOCE mean satellite altitude (h=250 km) show both fourth generation models to improve significantly w.r.t. their predecessors.Relatively, we find a root-mean-square improvement of 39 % for the DIR4 and 23 % for TIM4 over the respective third release models at a spatial scale of 100 km (degree 200). In terms of absolute errors TIM4 is found to perform slightly better in the bands from degree 120 up to degree 160 and DIR4 is found to perform slightly better than TIM4 from degree 170 up to degree 250. Our analyses cannot confirm the DIR4 formal error of 1 cm geoid height (0.35 mGal in terms of gravity) at degree 200. The formal errors of TIM4, with 3.2 cm geoid height (0.9 mGal in terms of gravity) at degree 200, seem to be realistic. Due to combination with GRACE and SLR data, the DIR models, at satellite altitude, clearly show lower RMS values compared to TIM models in the long wavelength part of the spectrum (below degree and order 120). Our study shows different spectral sensitivity of different functionals at ground level and at GOCE satellite altitude and establishes the link among these findings and the Meissl scheme (Rummel and van Gelderen in Manuscripta Geodaetica 20:379–385, 1995)