School Resources and Educational Outcomes in Developing Countries: A Review of the Literature from 1990 to 2010

Developing countries spend hundreds of billions of dollars each year on schools, educational materials and teachers, but relatively little is known about how effective these expenditures are at increasing students’ years of completed schooling and, more importantly, the skills that they learn while in school. This paper examines studies published between 1990 and 2010, in both the education literature and the economics literature, to investigate which specific school and teacher characteristics, if any, appear to have strong positive impacts on learning and time in school. Starting with over 9,000 studies, 79 are selected as being of sufficient quality. Then an even higher bar is set in terms of econometric methods used, leaving 43 “high quality” studies. Finally, results are also shown separately for 13 randomized trials. The estimated impacts on time in school and learning of most school and teacher characteristics are statistically insignificant, especially when the evidence is limited to the “high quality” studies. The few variables that do have significant effects – e.g. availability of desks, teacher knowledge of the subjects they teach, and teacher absence – are not particularly surprising and thus provide little guidance for future policies and programs.

Potential carcinogenic hazards of non-regulated disinfection by-products: Haloquinones, halo-cyclopentene and cyclohexene derivatives, N-halamines, halonitriles, and heterocyclic amines

Drinking water disinfectants react with natural organic material (NOM) present in source waters usedfor drinking water to produce a wide variety of by-products. Several hundred disinfections by-products(DBPs) have been identified, but none have been identified with sufficient carcinogenic potency to account for the cancer risks projected from epidemiological studies. In a search for DBPs that might fill this risk gap, the present study projected reactions of chlorine and chloramine that could occur with substructures present in NOM to produce novel by-products. A review of toxicological data on related compounds, supplemented by use of a quantitative structure toxicity relationship (QSTR) program TOPKAT identified chemicals with a high probability of being chronically toxic and/or carcinogenic among 489 established and novel DBPs. Classes of DBPs that were specifically examined were haloquinones (HQs), related halocyclopentene and cyclohexene (HCP&H) derivatives, halonitriles (HNs), organic N-chloramines (NCls), haloacetamides (HAMs), and nitrosamines (NAs). A review of toxicological data available for quinones suggested that HQs and HCP&H derivatives appeared likely to be of health concern and were predicted to have chronic lowest observed adverse effect levels (LOAELs) in the low g/kg day range. Several HQs were predicted to be carcinogenic. Some have now been identified in drinking water. The broader class of HNs was explored by considering current toxicological data on haloacetonitriles and extending this to halopropionitriles. 2,2-dichloropropionitrile has been identified in drinking water at low concentrations, as well as the more widely recognized haloacetonitriles. The occurrence of HAMs has been previously documented. The very limited toxicological data on HAMs suggests that this class would have toxicological potencies similar to the dihaloacetic acids. Organic N-halamines are also known to be produced in drinking water treatment and have biological properties of concern, but no member has ever been characterized toxicologically beyond bacterial or in vitro studies of genotoxicity. The documented formation of several nitrosamines from secondary amines from both natural and industrial sources prompted exploration of the formation of additional nitrosamines. N-diphenylnitrosamine was identified in drinking waters. Of more interest, however, was the formation of phenazine (and subsequently N-chorophenazine) in a competing reaction. These are the first heterocyclic amines that have been identified as chlorination by-products. Consideration of the amounts detected of members of these by-product classes and their probable toxicological potency suggest a prioritization for obtaining more detailed toxicological data of HQs > HCP&H derivatives > NCls > HNs. Based upon a ubiquitous occurrence and virtual lack of in vivo toxicological data, NCls are the most difficult group to assign a priority as potential carcinogenic risks. This analysis indicates that research on the general problem of DBPs requires a more systematic approach than has been pursued in the past. Utilization of predictive chemical tools to guide further research can help bring resolution to the DBP issue by identifying likely DBPs with high toxicological potency

G band atmospheric radars: new frontiers in cloud physics

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow

G band atmospheric radars: New frontiers in cloud physics

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow. © 2014 Author(s)

CH4 emission estimates from an active landfill site inferred from a combined approach of CFD modelling and in situ FTIR measurements

Globally, the waste sector contributes to nearly a fifth of anthropogenic methane emitted to the atmosphere and is the second largest source of methane in the UK. In recent years great improvements to reduce those emissions have been achieved by installation of methane recovery systems at landfill sites and subsequently methane emissions reported in national emission inventories have been reduced. Nevertheless, methane emissions of landfills remain uncertain and quantification of emission fluxes is essential to verify reported emission inventories and to monitor changes in emissions. Here we present a new approach for methane emission quantification from a complex source like a landfill site by applying a Computational Fluid Dynamics (CFD) model to calibrated in situ measurements of methane as part of a field campaign at a landfill site near Ipswich, UK, in August 2014. The methane distribution for different meteorological scenarios is calculated with the CFD model and compared to methane mole fractions measured by an in situ Fourier Transform Infrared (FTIR) spectrometer downwind of the prevailing wind direction. Assuming emissions only from the active site, a mean daytime flux of 0.83 mg m−2 s−1, corresponding to 53.26 kg h−1, was estimated. The addition of a secondary source area adjacent to the active site, where some methane hotspots were observed, improved the agreement between the simulated and measured methane distribution. As a result, the flux from the active site was reduced slightly to 0.71 mg m−2 s−1 (45.56 kg h−1), at the same time an additional flux of 0.32 mg m−2 s−1 (30.41 kg h−1) was found from the secondary source area. This highlights the capability of our method to distinguish between different emission areas of the landfill site, which can provide more detailed information about emission source apportionment compared to other methods deriving bulk emissions

Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations

Wetlands are the largest natural source of methane. The ability to model the emissions of methane from natural wetlands accurately is critical to our understanding of the global methane budget and how it may change under future climate scenarios. The simulation of wetland methane emissions involves a complicated system of meteorological drivers coupled to hydrological and biogeochemical processes. The Joint UK Land Environment Simulator (JULES) is a process-based land surface model that underpins the UK Earth System Model (UKESM) and is capable of generating estimates of wetland methane emissions. In this study, we use GOSAT satellite observations of atmospheric methane along with the TOMCAT global 3-D chemistry transport model to evaluate the performance of JULES in reproducing the seasonal cycle of methane over a wide range of tropical wetlands. By using an ensemble of JULES simulations with differing input data and process configurations, we investigate the relative importance of the meteorological driving data, the vegetation, the temperature dependency of wetland methane production and the wetland extent. We find that JULES typically performs well in replicating the observed methane seasonal cycle. We calculate correlation coefficients to the observed seasonal cycle of between 0.58 and 0.88 for most regions; however, the seasonal cycle amplitude is typically underestimated (by between 1.8 and 19.5 ppb). This level of performance is comparable to that typically provided by state-of-the-art data-driven wetland CH4 emission inventories. The meteorological driving data are found to be the most significant factor in determining the ensemble performance, with temperature dependency and vegetation having moderate effects. We find that neither wetland extent configuration outperforms the other, but this does lead to poor performance in some regions. We focus in detail on three African wetland regions (Sudd, Southern Africa and Congo) where we find the performance of JULES to be poor and explore the reasons for this in detail. We find that neither wetland extent configuration used is sufficient in representing the wetland distribution in these regions (underestimating the wetland seasonal cycle amplitude by 11.1, 19.5 and 10.1 ppb respectively, with correlation coefficients of 0.23, 0.01 and 0.31). We employ the Catchment-based Macro-scale Floodplain (CaMa-Flood) model to explicitly represent river and floodplain water dynamics and find that these JULES-CaMa-Flood simulations are capable of providing a wetland extent that is more consistent with observations in this regions, highlighting this as an important area for future model development.</p

TransitFit: an exoplanet transit fitting package for multi-telescope datasets and its application to WASP-127~b, WASP-91~b, and WASP-126~b

We present TransitFit, an open-source Python~3 package designed to fit exoplanetary transit light-curves for transmission spectroscopy studies (Available at https://github.com/joshjchayes/TransitFit and https://github.com/spearnet/TransitFit, with documentation at https://transitfit.readthedocs.io/). TransitFit employs nested sampling to offer efficient and robust multi-epoch, multi-wavelength fitting of transit data obtained from one or more telescopes. TransitFit allows per-telescope detrending to be performed simultaneously with parameter fitting, including the use of user-supplied detrending alogorithms. Host limb darkening can be fitted either independently ("uncoupled") for each filter or combined ("coupled") using prior conditioning from the PHOENIX stellar atmosphere models. For this TransitFit uses the Limb Darkening Toolkit (LDTk) together with filter profiles, including user-supplied filter profiles. We demonstrate the application of TransitFit in three different contexts. First, we model SPEARNET broadband optical data of the low-density hot-Neptune WASP-127~b. The data were obtained from a globally-distributed network of 0.5m--2.4m telescopes. We find clear improvement in our broadband results using the coupled mode over uncoupled mode, when compared against the higher spectral resolution GTC/OSIRIS transmission spectrum obtained by Chen et al. (2018). Using TransitFit, we fit 26 transit observations by TESS to recover improved ephemerides of the hot-Jupiter WASP-91~b and a transit depth determined to a precision of 170~ppm. Finally, we use TransitFit to conduct an investigation into the contested presence of TTV signatures in WASP-126~b using 126 transits observed by TESS, concluding that there is no statistically significant evidence for such signatures from observations spanning 31 TESS sectors.Comment: 14 pages, 5 figures, 5 tables, submitted to MNRAS. Temporary data address at https://cdsarc.u-strasbg.fr/ftp/vizier.submit/wasp-127b/ (Final address to be included in accepted paper

Kinematical analysis of the nutation speed reducer

This paper discusses the development of a Nutating Speed Reducer (NSR) which is characterized by high reduction ratio, high tooth contact ratio, very high torque to weight/volume ratio, quiet and smooth operation under load and very high efficiency. All of these advantages are due to the presence of conjugate face-gear pairs, which incorporate each other, which called nutating/rotating gear mechanism. Details of the NSR, its kinematics, gear tooth load capacity, and mesh efficiency are explained. The NSR component speeds and speed reduction ratios of the NSR are calculated. Effect of the varying nutation angles on the geometry of the NSR is discussed and compared

Intramolecular Modulation of Serine Protease Inhibitor Activity in a Marine Cyanobacterium with Antifeedant Properties

Extracts of the Floridian marine cyanobacterium Lyngbya cf. confervoides were found to deter feeding by reef fish and sea urchins (Diadema antillarum). This antifeedant activity may be a reflection of the secondary metabolite content, known to be comprised of many serine protease inhibitors. Further chemical and NMR spectroscopic investigation led us to isolate and structurally characterize a new serine protease inhibitor 1 that is formally derived from an intramolecular condensation of largamide D (2). The cyclization resulted in diminished activity, but to different extents against two serine proteases tested. This finding suggests that cyanobacteria can endogenously modulate the activity of their protease inhibitors