Territorializing spatial data: Controlling land through One Map projects in Indonesia and Myanmar

Once confined to paper, national cartographic projects increasingly play out through spatial data infrastructures such as software programs and smartphones. Across the Global South, foreign donor-funded digital platforms emphasize transparency, accountability and data sharing while echoing colonial projects that consolidated statebased territorial knowledge. This article brings political geography scholarship on state and counter-mapping together with new work on the political ecology of data to highlight a contemporary dimension of territorialization, one in which state actors seek to consolidate and authorize national geospatial information onto digital platforms. We call attention to the role of data infrastructures in contemporary resource control, arguing that territorializing data both extends state territorialization onto digital platforms and, paradoxically, provides new avenues for non-state actors to claim land. Drawing on interviews, document review, and long-term fieldwork, we compare the origins, institutionalization and realization of Indonesia and Myanmar’s ‘One Map’ projects. Both projects aimed to create a government-managed online spatial data platform, building on national mapping and management traditions while responding to new international incentives, such as climate change mitigation in Indonesia and good democratic governance in Myanmar. While both projects encountered technical difficulties and evolved during implementation, different national histories and political trajectories resulted in the embrace and expansion of the program in Indonesia but reluctant participation and eventual crisis in Myanmar. Together, these cases show how spatial data infrastructures can both extend state control over space and offer opportunities for contesting or reimagining land and nation, even as such infrastructures remain embedded in local power relations

Separation and Quantification of N-acetylcysteine-amide (NACA) by HPLC with Fluorescence Detection

N-acetyl-l-cysteine (NAC) is a well-known antioxidant that is capable of facilitating glutathione (GSH) biosynthesis and replenishing intracellular GSH under oxidatively challenging circumstances. N-acetyl-cysteine-amide (NACA), the amide form of NAC, is a newly designed and synthesized thiol-containing compound which is believed to be more lipophilic and permeable through cell membranes than NAC. The metabolic and antioxidant effects of these compounds in vitro and in vivo are under investigation. However, an analytical method that can separate and quantify both compounds simultaneously is not yet available, to the best of our knowledge. Because of their structural similarities, the two compounds are difficult to separate using earlier HPLC methods which were designed for NAC quantification. Therefore, the goal of this work was to develop an HPLC method with fluorescence detection for simultaneous quantification of NAC and NACA in biological blood and tissue samples. A gradient HPLC program with fluorescence detection (λex = 330 nm, λem = 376 nm) using N-(1-pyrenyl)maleimide (NPM) as the derivatizing agent was developed. The calibration curves were linear over a concentration range of 25-5000 nm (r2 \u3e 0.997). The coefficients of variation for within-run precision and between-run precision ranged from 0.67 to 5.23% and for accuracy ranged from 0.98 to 10.54%; the percentage relative recovery ranged from 94.5 to 102.8%. This new method provides satisfactory separation of NAC and NACA, along with other biological thiols, in 20 min with a 5 nm limit of detection (LOD) per 5 µL injection volume

Pre-Hawking Radiation from a Collapsing Shell

We investigate the effect of induced massive radiation given off during the time of collapse of a massive spherically symmetric domain wall in the context of the functional Schr\"odinger formalism. Here we find that the introduction of mass suppresses the occupation number in the infrared regime of the induced radiation during the collapse. The suppression factor is found to be given by $e^{-\beta m}$, which is in agreement with the expected Planckian distribution of induced radiation. Thus a massive collapsing domain wall will radiate mostly (if not exclusively) massless scalar fields, making it difficult for the domain wall to shed any global quantum numbers and evaporate before the horizon is formed.Comment: 10 pages, 3 figures. We updated the acknowledgments as well as added a statement clarifying that we are following the methods first laid out in Phys. Rev. D 76, 024005 (2007

Implications of mining practices in an open-pit gold mine for monitoring of a comprehensive test-ban treaty

This report summarizes the results of an experiment at the Gold Quarry pit, operated by the Newmont Gold Company at Carlin, NV The purpose of the experiment was to obtain local and regional seismic data, together with ``ground truth``, from conventional surface blasting activity and to use these data to help determine the effectiveness with which conventional mining blasts can be discriminated from underground nuclear explosions

Regional Brain Morphometry Predicts Memory Rehabilitation Outcome after Traumatic Brain Injury

Cognitive deficits following traumatic brain injury (TBI) commonly include difficulties with memory, attention, and executive dysfunction. These deficits are amenable to cognitive rehabilitation, but optimally selecting rehabilitation programs for individual patients remains a challenge. Recent methods for quantifying regional brain morphometry allow for automated quantification of tissue volumes in numerous distinct brain structures. We hypothesized that such quantitative structural information could help identify individuals more or less likely to benefit from memory rehabilitation. Fifty individuals with TBI of all severities who reported having memory difficulties first underwent structural MRI scanning. They then participated in a 12 session memory rehabilitation program emphasizing internal memory strategies (I-MEMS). Primary outcome measures (HVLT, RBMT) were collected at the time of the MRI scan, immediately following therapy, and again at 1-month post-therapy. Regional brain volumes were used to predict outcome, adjusting for standard predictors (e.g., injury severity, age, education, pretest scores). We identified several brain regions that provided significant predictions of rehabilitation outcome, including the volume of the hippocampus, the lateral prefrontal cortex, the thalamus, and several subregions of the cingulate cortex. The prediction range of regional brain volumes were in some cases nearly equal in magnitude to prediction ranges provided by pretest scores on the outcome variable. We conclude that specific cerebral networks including these regions may contribute to learning during I-MEMS rehabilitation, and suggest that morphometric measures may provide substantial predictive value for rehabilitation outcome in other cognitive interventions as well

Trends in Anemia Care in Older Patients Approaching End-Stage Renal Disease in the United States (1995-2010)

Anemia is common in patients with advanced chronic kidney disease. While the treatment of anemia in patients with end-stage renal disease (ESRD) has attracted considerable attention, relatively little is known about patterns and trends in the anemia care received by patients before initiating maintenance dialysis or pre-emptive kidney transplantation

Regional seismic discrimination research at LLNL

The ability to verify a Comprehensive Test Ban Treaty (CTBT) depends in part on the ability to seismically detect and discriminate between potential clandestine underground nuclear tests and other seismic sources, including earthquakes and mining activities. Regional techniques are necessary to push detection and discrimination levels down to small magnitudes, but existing methods of event discrimination are mainly empirical and show much variability from region to region. The goals of Lawrence Livermore National Laboratory`s (LLNL`s) regional discriminant research are to evaluate the most promising discriminants, improve the understanding of their physical basis and use this information to develop new and more effective discriminants that can be transported to new regions of high monitoring interest. In this report the authors discuss preliminary efforts to geophysically characterize the Middle East and North Africa. They show that the remarkable stability of coda allows one to develop physically based, stable single station magnitude scales in new regions. They then discuss progress to date on evaluating and improving physical understanding and ability to model regional discriminants, focusing on the comprehensive NTS dataset. The authors apply this modeling ability to develop improved discriminants including slopes of P to S ratios. They find combining disparate discriminant techniques is particularly effective in identifying consistent outliers such as shallow earthquakes and mine seismicity. Finally they discuss development and use of new coda and waveform modeling tools to investigate special events

A dynamic risk score for early prediction of cardiogenic shock using machine learning

Myocardial infarction and heart failure are major cardiovascular diseases that affect millions of people in the US. The morbidity and mortality are highest among patients who develop cardiogenic shock. Early recognition of cardiogenic shock is critical. Prompt implementation of treatment measures can prevent the deleterious spiral of ischemia, low blood pressure, and reduced cardiac output due to cardiogenic shock. However, early identification of cardiogenic shock has been challenging due to human providers' inability to process the enormous amount of data in the cardiac intensive care unit (ICU) and lack of an effective risk stratification tool. We developed a deep learning-based risk stratification tool, called CShock, for patients admitted into the cardiac ICU with acute decompensated heart failure and/or myocardial infarction to predict onset of cardiogenic shock. To develop and validate CShock, we annotated cardiac ICU datasets with physician adjudicated outcomes. CShock achieved an area under the receiver operator characteristic curve (AUROC) of 0.820, which substantially outperformed CardShock (AUROC 0.519), a well-established risk score for cardiogenic shock prognosis. CShock was externally validated in an independent patient cohort and achieved an AUROC of 0.800, demonstrating its generalizability in other cardiac ICUs

Longer-term Outcomes of Darbepoetin Alfa Versus Epoetin Alfa in Patients With ESRD Initiating Hemodialysis: A Quasi-experimental Cohort Study

Adequately-powered studies directly comparing hard clinical outcomes of darbepoetin alfa (DPO) versus epoetin alfa (EPO) in patients undergoing dialysis are lacking