Reducing Inequalities in Water Supply, Sanitation, and Hygiene in the Era of the Sustainable Development Goals

The Sustainable Development Goals (SDGs) and the World Bank's corporate goals of ending extreme poverty and boosting shared prosperity call for specific attention to the poor and vulnerable. The overarching objective of the SDGs is to end poverty in all its forms, but their key difference from the earlier Millennium Development Goals (MDGs) is the integration of social, economic, and environmental goals (UN 2015). This has significant implications for reforms aimed at improving service delivery. With this understanding as its guiding compass, the Water Supply, Sanitation, and Hygiene (WASH) Poverty Diagnostic Initiative focuses on what it would take to reduce existing inequalities in WASH services worldwide. This report, a synthesis of that global initiative, offers new insights on how data can be used to inform allocation decisions to reduce inequalities and prioritize investment in WASH to boost human capital. It also offers a fresh perspective on service delivery that considers how institutional arrangements affect the incentives of a range of actors

Regulation of plants’ phosphate uptake in common mycorrhizal networks: Role of intraradical fungal phosphate transporters

We have recently identified two genes coding for inorganic phosphate transporters (Pht) in sorghum (Sorghum bicolor) and flax (Linum usitatissimum) that were induced in roots colonized by arbuscular mycorrhizal (AM) fungi. Mycorrhizal acquisition of inorganic phosphorus (Pi) was strongly affected by the combination of plant and AM fungal species, but the expression level of these genes coding for AM-inducible Pi transporters did not explain differences in plant phosphorus acquisition where flax and sorghum are sharing a common mycorrhizal network. In the present study, we investigated the possible role of fungal Pi transporters in the regulation of mycorrhizal Pi acquisition by measuring their expression in roots of flax and sorghum. One Pi transporter of Rhizophagus irregularis (RiPT5) showed a positive correlation with mycorrhizal Pi acquisition of sorghum. This indicates that a possible involvement in the regulation of mycorrhizal Pi acquisition. In general, expression of AMF Pi transporters was more related to mycorrhizal Pi acquisition of sorghum than of flax, indicating plant species-specific differences in the regulation of mycorrhizal Pi acquisition

Histopathological Analyses of Respiratory Viral Co-infections in Mice.

Patients suffering from viral respiratory disease are often infected with several unrelated viruses, known as co-infection; however, it is unclear how viral co-infections influence disease pathogenesis. Our lab previously established a respiratory viral co-infection mouse model to answer this question. Mice were inoculated with a mild respiratory virus (rhinovirus, RV1B) two days before a virus that causes severe disease (influenza A virus, PR8; or pneumonia virus of mice, PVM). Co-infection with RV1B reduced severity of both PR8 and PVM infections, determined by mortality, weight loss, and clinical signs of disease. Bronchoalveolar lavage (BAL) samples were collected from lungs of mice infected with PR8 or PVM alone or those that were co-infected with RV1B. BAL samples were used to quantify leukocyte subtypes present in the airways of infected mice. Lung tissues were paraffin-embedded for staining and further analysis. Histology slides were stained with Masson’s trichrome stain and a hematoxylin and eosin (H&E) stain to evaluate inflammation and tissue damage, and immunohistochemistry was used to show localization of virus and immune cells. These analyses will inform how respiratory viral co-infection alters lung pathology compared to single infections, including mechanisms responsible for RV1B-mediated protection

Comments on "A closed-form solution to Tensor voting: theory and applications"

We comment on a paper that describes a closed-form formulation to Tensor Voting, a technique to perceptually group clouds of points, usually applied to infer features in images. The authors proved an analytic solution to the technique, a highly relevant contribution considering that the original formulation required numerical integration, a time-consuming task. Their work constitutes the first closed-form expression for the Tensor Voting framework. In this work we first observe that the proposed formulation leads to unexpected results which do not satisfy the constraints for a Tensor Voting output, hence they cannot be interpreted. Given that the closed-form expression is said to be an analytic equivalent solution, unexpected outputs should not be encountered unless there are flaws in the proof. We analyzed the underlying math to find which were the causes of these unexpected results. In this commentary we show that their proposal does not in fact provide a proper analytic solution to Tensor Voting and we indicate the flaws in the proof.Fil: Maggiori, Emmanuel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados; ArgentinaFil: Lotito, Pablo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados; ArgentinaFil: Manterola, Hugo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados; ArgentinaFil: del Fresno, Mariana. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentin

Visualization and thermodynamic encoding of single-molecule partition functions

Ensemble averaging of molecular states is fundamental for the experimental determination of thermodynamic quantities. A special case occurs for single-molecule investigations under equilibrium conditions, for which free energy, entropy and enthalpy at finite-temperatures are challenging to determine with ensemble-averaging alone. Here, we provide a method to access single-molecule thermodynamics, by confining an individual molecule to a nanoscopic pore of a two-dimensional metal-organic nanomesh, where we directly record finite-temperature time-averaged statistical weights using temperature-controlled scanning tunneling microscopy. The obtained patterns represent a real space equilibrium probability distribution. We associate this distribution with a partition function projection to assess spatially resolved thermodynamic quantities, by means of computational modeling. The presented molecular dynamics based Boltzmann weighting model is able to reproduce experimentally observed molecular states with high accuracy. By an in-silico customized energy landscape we demonstrate that distinct probability distributions can be encrypted at different temperatures. Such modulation provides means to encode and decode information into position-temperature space or to realize nanoscopic thermal probes.Comment: 20 Pages Main text, 5 Figures. 10 Pages Annexed tex

Plan estratégico de posicionamiento de la marca “En forma de U”, medio de comunicación digital dedicado al club universitario de deportes

El informe que se presenta tiene como objetivo establecer el proceso de posicionamiento del proyecto En Forma de U, medio digital partidario dedicado al club Universitario de Deportes. Se consideró la identificación de un nicho de mercado y un público determinado para el desarrollo de propuestas periodísticas, además se definió el contenido del proyecto en la plataforma digital. En el Perú se han desarrollado cambios en las formas de consumir contenido periodístico sobre diferentes temas, entre ellos el deportivo. Estos cambios se generaron a partir de la masificación de plataformas digitales y el acceso a Internet. En Forma de U es un proyecto digital que enfrentó la pandemia de COVID-19 en 2020 y se adaptó a las necesidades de su audiencia ejecutando nuevas estrategias de comunicación que favorecieron a su crecimiento. Se consultaron a expertos para analizar sus puntos de vista, los cuales se contrastaron con estudios estadísticos sobre el uso de internet y consuma, con el objetivo de otorgar una visión más amplia y realista del informe.The purpose of this report is to establish the process of positioning of the sport’s digital media and soccer supporter, En forma de U, devoted to Club Universitario de Deportes. The process mentioned included the identification of a market niche and a specific target audience for the development of journalistic proposals. These tasks define the content of the project and are used in the digital platform. The ways of consuming journalistic content on different topics, including sports, have changed progressively a few years ago in our country. These changes were generated from the widespread growth of Internet platforms. During its development, our digital platform En forma de U had to face the covid-19 pandemic in 2020. Initially, this situation represented a barrier for the platform, however, it was able to adapt to the needs of the public using new communication strategies and for more than a year we were able to see a constant growth in our metrics. To provide a broader and more realistic vision throughout this report we will consult with experts and analyze their points of view to compare them with statistical studies on the use of the Internet and its consumption

Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon

While the fighting in the Syrian civil war has mostly stopped, an estimated 5.6 million Syrians remain living in neighboring countries1. Of these, an estimated 1.5 million are sheltering in Lebanon. Ongoing efforts by organizations such as UNHCR to support the refugee population are often ineffective in reaching those most in need. According to UNHCR's 2019 Vulnerability Assessment of Syrian Refugees Report (VASyR), only 44% of the Syrian refugee families eligible for multipurpose cash assistance were provided with help, as the others were not captured in the data. In this project, we are investigating the use of non-traditional data, derived from Facebook advertising data, for population level vulnerability assessment. In a nutshell, Facebook provides advertisers with an estimate of how many of its users match certain targeting criteria, e.g., how many Facebook users currently living in Beirut are “living abroad,” aged 18–34, speak Arabic, and primarily use an iOS device. We evaluate the use of such audience estimates to describe the spatial variation in the socioeconomic situation of Syrian refugees across Lebanon. Using data from VASyR as ground truth, we find that iOS device usage explains 90% of the out-of-sample variance in poverty across the Lebanese governorates. However, evaluating predictions at a smaller spatial resolution also indicate limits related to sparsity, as Facebook, for privacy reasons, does not provide audience estimates for fewer than 1,000 users. Furthermore, comparing the population distribution by age and gender of Facebook users with that of the Syrian refugees from VASyR suggests an under-representation of Syrian women on the social media platform. This work adds to growing body of literature demonstrating the value of anonymous and aggregate Facebook advertising data for analysing large-scale humanitarian crises and migration events

Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon

While the fighting in the Syrian civil war has mostly stopped, an estimated 5.6 million Syrians remain living in neighboring countries1. Of these, an estimated 1.5 million are sheltering in Lebanon. Ongoing efforts by organizations such as UNHCR to support the refugee population are often ineffective in reaching those most in need. According to UNHCR's 2019 Vulnerability Assessment of Syrian Refugees Report (VASyR), only 44% of the Syrian refugee families eligible for multipurpose cash assistance were provided with help, as the others were not captured in the data. In this project, we are investigating the use of non-traditional data, derived from Facebook advertising data, for population level vulnerability assessment. In a nutshell, Facebook provides advertisers with an estimate of how many of its users match certain targeting criteria, e.g., how many Facebook users currently living in Beirut are “living abroad,” aged 18–34, speak Arabic, and primarily use an iOS device. We evaluate the use of such audience estimates to describe the spatial variation in the socioeconomic situation of Syrian refugees across Lebanon. Using data from VASyR as ground truth, we find that iOS device usage explains 90% of the out-of-sample variance in poverty across the Lebanese governorates. However, evaluating predictions at a smaller spatial resolution also indicate limits related to sparsity, as Facebook, for privacy reasons, does not provide audience estimates for fewer than 1,000 users. Furthermore, comparing the population distribution by age and gender of Facebook users with that of the Syrian refugees from VASyR suggests an under-representation of Syrian women on the social media platform. This work adds to growing body of literature demonstrating the value of anonymous and aggregate Facebook advertising data for analysing large-scale humanitarian crises and migration events