Preparedness and Promotion of Technology Leadership Toward Self-Efficacy and Instructional Performance

This study focused on the preparedness and promotion of technology leadership towards self- efficacy and instructional performance of public elementary school teachers. This utilized 442 public elementary school teachers from Candelaria, Quezon through a descriptive correlational design conducted during academic year 2021- 2022. A researcher- made survey questionnaire was utilized via Google form. The study revealed that self- efficacy was significantly predicted by systematic development when it comes to preparedness of technology leadership while promotion of technology leadership, self- efficacy was significantly predicted by technology infrastructure and support and vision, planning and management. Meanwhile, instructional performance was significantly predicted by systematic development and visionary leadership when it comes to preparedness of technology leadership while promotion of technology leadership, it was significantly predicted by vision, planning and management, technology and infrastructure support, and evaluation and research. This implies that working with peers and doing reflection may also help in enhancing self-evaluation towards teaching performance so teachers can assess points they are good at and they need to develop further

The importance of transport model uncertainties for the estimation of CO2 sources and sinks using satellite measurements

This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by s=0.5 ppm over the continents and s=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transpor

Toward accurate CO_2 and CH_4 observations from GOSAT

The column-average dry air mole fractions of atmospheric carbon dioxide and methane (X_(CO_2) and X_(CH_4)) are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground-based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of −0.05% and −0.30% for X_(CO_2) and X_(CH_4) with a station-to-station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root-mean square deviation of the bias-corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for X_(CO_2) and 0.015 ppm for X_(CH_4). Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of X_(CO_2) suggesting the use of the satellite retrievals for constraining surface fluxes

Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results

SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO_2 and XCH_4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00 ± 0.16 ppm yr^(−1) compared to 1.94 ± 0.03 ppm yr−1 on global average). The XCO_2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1–1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH_4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10–20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH_4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements

Drivers of column-average CO_2 variability at Southern Hemispheric Total Carbon Column Observing Network sites

We investigate factors that drive the variability in total column CO_2 at the Total Carbon Column Observing Network sites in the Southern Hemisphere using fluxes tagged by process and by source region from the CarbonTracker analysed product as well as the Simple Biosphere model. We show that the terrestrial biosphere is the largest driver of variability in the Southern Hemisphere column CO_2. However, it does not dominate in the same fashion as in the Northern Hemisphere. Local- and hemispheric-scale biomass burning can also play an important role, particularly at the tropical site, Darwin. The magnitude of seasonal variability in the column-average dry-air mole fraction of CO_2, X_CO_2, is also much smaller in the Southern Hemisphere and comparable in magnitude to the annual increase. Comparison of measurements to the model simulations highlights that there is some discrepancy between the two time series, especially in the early part of the Darwin data record. We show that this mismatch is most likely due to erroneously estimated local fluxes in the Australian tropical region, which are associated with enhanced photosynthesis caused by early rainfall during the tropical monsoon season

Technical Note: Latitude-time variations of atmospheric column-average dry air mole fractions of CO_2, CH_4 and N_2O

We present a comparison of an atmospheric general circulation model (AGCM)-based chemistry-transport model (ACTM) simulation with total column measurements of CO_2, CH_4 and N_2O from the Total Carbon Column Observing Network (TCCON). The model is able to capture observed trends, seasonal cycles and inter hemispheric gradients at most sampled locations for all three species. The model-observation agreements are best for CO_2, because the simulation uses fossil fuel inventories and an inverse model estimate of non-fossil fuel fluxes. The ACTM captures much of the observed seasonal variability in CO_2 and N_2O total columns (~81 % variance, R>0.9 between ACTM and TCCON for 19 out of 22 cases). These results suggest that the transport processes in troposphere and stratosphere are well represented in ACTM. Thus the poor correlation between simulated and observed CH4 total columns, particularly at tropical and extra-tropical sites, have been attributed to the uncertainties in surface emissions and loss by hydroxyl radicals. While the upward-looking total column measurements of CO_2 contains surface flux signals at various spatial and temporal scales, the N_2O measurements are strongly affected by the concentration variations in the upper troposphere and stratosphere

Toward accurate CO2 and CH4 observations from GOSAT

The column-average dry air mole fractions of atmospheric carbon dioxide and methane (XCO2 and XCH4) are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground-based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of-0.05% and-0.30% for XCO2 and XCH4 with a station-to-station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root-mean square deviation of the bias-corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for XCO2 and 0.015 ppm for X CH4. Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of XCO2 suggesting the use of the satellite retrievals for constraining surface fluxes. Copyright 2011 by the American Geophysical Union

Persistent HIV-infected cells in cerebrospinal fluid are associated with poorer neurocognitive performance

BACKGROUND. Persistence of HIV in sanctuary sites despite antiretroviral therapy (ART) presents a barrier to HIV remission and may affect neurocognitive function. We assessed HIV persistence in cerebrospinal fluid (CSF) and associations with inflammation and neurocognitive performance during long-term ART. METHODS. Participants enrolled in the AIDS Clinical Trials Group (ACTG) HIV Reservoirs Cohort Study (A5321) underwent concurrent lumbar puncture, phlebotomy, and neurocognitive assessment. Cell-associated HIV DNA and HIV RNA (CA-DNA, CA-RNA) were measured by quantitative PCR (qPCR). in peripheral blood mononuclear cells (PBMCs) and in cell pellets from CSF. In CSF supernatant and blood plasma, cell-free HIV RNA was quantified by qPCR with single copy sensitivity, and inflammatory biomarkers were measured by enzyme immunoassay. RESULTS. Sixty-nine participants (97% male, median age 50 years, CD4 696 cells/mm3, plasma HIV RNA <100 copies/mL) were assessed after a median 8.6 years of ART. In CSF, cell-free RNA was detected in 4%, CA-RNA in 9%, and CA-DNA in 48% of participants (median level 2.1 copies/103 cells). Detection of cell-free CSF HIV RNA was associated with higher plasma HIV RNA (P = 0.007). CSF inflammatory biomarkers did not correlate with HIV persistence measures. Detection of CSF CA-DNA HIV was associated with worse neurocognitive outcomes including global deficit score (P = 0.005), even after adjusting for age and nadir CD4 count. CONCLUSION. HIV-infected cells persist in CSF in almost half of individuals on long-term ART, and their detection is associated with poorer neurocognitive performance