Housing Search in the Age of Big Data: Smarter Cities or the Same Old Blind Spots?

Housing scholars stress the importance of the information environment in shaping housing search behavior and outcomes. Rental listings have increasingly moved online over the past two decades and, in turn, online platforms like Craigslist are now central to the search process. Do these technology platforms serve as information equalizers or do they reflect traditional information inequalities that correlate with neighborhood sociodemographics? We synthesize and extend analyses of millions of US Craigslist rental listings and find they supply significantly different volumes, quality, and types of information in different communities. Technology platforms have the potential to broaden, diversify, and equalize housing search information, but they rely on landlord behavior and, in turn, likely will not reach this potential without a significant redesign or policy intervention. Smart cities advocates hoping to build better cities through technology must critically interrogate technology platforms and big data for systematic biases

On the dynamical nature of the active center in a single-site photocatalyst visualized by 4D ultrafast electron microscopy

Understanding the dynamical nature of the catalytic active site embedded in complex systems at the atomic level is critical to developing efficient photocatalytic materials. Here, we report, using 4D ultrafast electron microscopy, the spatiotemporal behaviors of titanium and oxygen in a titanosilicate catalytic material. The observed changes in Bragg diffraction intensity with time at the specific lattice planes, and with a tilted geometry, provide the relaxation pathway: the Ti^(4+)=O^(2−) double bond transformation to a Ti^(3+)−O^(1−) single bond via the individual atomic displacements of the titanium and the apical oxygen. The dilation of the double bond is up to 0.8 Å and occurs on the femtosecond time scale. These findings suggest the direct catalytic involvement of the Ti^(3+)−O^(1−) local structure, the significance of nonthermal processes at the reactive site, and the efficient photo-induced electron transfer that plays a pivotal role in many photocatalytic reactions

Exploring the relation between remotely sensed vertical canopy structure and tree species diversity in Gabon

Mapping tree species diversity is increasingly important in the face of environmental change and biodiversity conservation. We explore a potential way of mapping this diversity by relating forest structure to tree species diversity in Gabon. First, we test the relation between canopy height, as a proxy for niche volume, and tree species diversity. Then, we test the relation between vertical canopy structure, as a proxy for vertical niche occupation, and tree species diversity. We use large footprint full-waveform airborne lidar data collected across four study sites in Gabon (Lopé, Mabounié, Mondah, and Rabi) in combination with in situ estimates of species richness (S) and Shannon diversity (H′). Linear models using canopy height explained 44% and 43% of the variation in S and H′ at the 0.25 ha resolution. Linear models using canopy height and the plant area volume density profile explained 71% of this variation. We demonstrate applications of these models by mapping S and H′ in Mondah using a simulated GEDI-TanDEM-X fusion height product, across the four sites using wall-to-wall airborne lidar data products, and across and between the study sites using ICESat lidar waveforms. The modeling results are encouraging in the context of developing pan-tropical structure diversity models applicable to data from current and upcoming spaceborne remote sensing missions

Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data

Interferometric Synthetic Aperture Radar (InSAR) and lidar are increasingly used active remote sensing techniques for forest structure observation. The TanDEM-X (TDX) InSAR mission of German Aerospace Center (DLR) and the upcoming Global Ecosystem Dynamics Investigation (GEDI) of National Aeronautics and Space Administration (NASA) together may provide more accurate estimates of global forest structure and biomass via their synergic use. In this paper, we explored the efficacy of simulated GEDI data in improving height estimates from TDX InSAR data. Our study sites span three major forest types: a temperate forest, a mountainous conifer forest, and a tropical rainforest. The GEDI lidar coverage was simulated for the full nominal two-year mission duration, under both cloud-free and 50%-cloud conditions. We then used these GEDI data to parameterize the Random Volume over Ground (RVoG) model driven by TDX imagery. In particular, we explored the following three strategies for forest structure estimation: 1) TDX data alone; 2) TDX + GEDI-derived digital terrain model (DTM); and 3) TDX + GEDI DTM + GEDI canopy height. We then validated the retrieved forest heights against wall-to-wall airborne lidar measurements. We found relatively large biases at 90 [m] spatial resolution, from 4.2–11.9 [m], and root mean square errors (RMSEs), from 7.9–12.7 [m] when using TDX data alone under constrained RVoG assumptions of a fixed extinction coefficient (σ) and a zero ground-to-volume amplitude ratio (μ = 0). Results improved significantly with the aid of a DTM derived from GEDI data which enabled estimation of spatially-varying σ values (vs. fixed extinction) under a μ = 0 assumption, with biases reduced to 1.7–4.2 [m] and RMSEs to 4.9–8.6 [m] across cloudy and cloud-free cases. The best agreement was achieved in the third strategy by also incorporating information of GEDI-derived canopy height to further enhance the RVoG parameters. The improved model, when still assuming μ = 0, reduced biases to less than or close to 1 m and further reduced RMSEs to 4.0–6.7 [m]. Finally, we used GEDI data to estimate spatially-varying μ in the RVoG model. We found biases of between −0.7–0.9 [m] and RMSEs in the range from 2.6–7.1 [m] over the three sites. Our results suggest that use of GEDI data improves height inversion from TDX, providing heights at more accuracy than can be achieved by TDX alone, and enabling wall-to-wall height estimation at much finer spatial resolution than can be achieved by GEDI alone

Societal Learning in Epidemics: Intervention Effectiveness during the 2003 SARS Outbreak in Singapore

BACKGROUND: Rapid response to outbreaks of emerging infectious diseases is impeded by uncertain diagnoses and delayed communication. Understanding the effect of inefficient response is a potentially important contribution of epidemic theory. To develop this understanding we studied societal learning during emerging outbreaks wherein patient removal accelerates as information is gathered and disseminated. METHODS AND FINDINGS: We developed an extension of a standard outbreak model, the simple stochastic epidemic, which accounts for societal learning. We obtained expressions for the expected outbreak size and the distribution of epidemic duration. We found that rapid learning noticeably affects the final outbreak size even when learning exhibits diminishing returns (relaxation). As an example, we estimated the learning rate for the 2003 outbreak of severe acute respiratory syndrome (SARS) in Singapore. Evidence for relaxation during the first eight weeks of the outbreak was inconclusive. We estimated that if societal learning had occurred at half the actual rate, the expected final size of the outbreak would have reached nearly 800 cases, more than three times the observed number of infections. By contrast, the expected outbreak size for societal learning twice as effective was 116 cases. CONCLUSION: These results show that the rate of societal learning can greatly affect the final size of disease outbreaks, justifying investment in early warning systems and attentiveness to disease outbreak by both government authorities and the public. We submit that the burden of emerging infections, including the risk of a global pandemic, could be efficiently reduced by improving procedures for rapid detection of outbreaks, alerting public health officials, and aggressively educating the public at the start of an outbreak

Growth Hormone Research Society perspective on the development of long-acting growth hormone preparations

Objective The Growth Hormone (GH) Research Society (GRS) convened a workshop to address important issues regarding trial design, efficacy, and safety of long-acting growth hormone preparations (LAGH). Participants A closed meeting of 55 international scientists with expertise in GH, including pediatric and adult endocrinologists, basic scientists, regulatory scientists, and participants from the pharmaceutical industry. Evidence Current literature was reviewed for gaps in knowledge. Expert opinion was used to suggest studies required to address potential safety and efficacy issues. Consensus process Following plenary presentations summarizing the literature, breakout groups discussed questions framed by the planning committee. Attendees reconvened after each breakout session to share group reports. A writing team compiled the breakout session reports into a draft document that was discussed and revised in an open forum on the concluding day. This was edited further and then circulated to attendees from academic institutions for review after the meeting. Participants from pharmaceutical companies did not participate in the planning, writing, or in the discussions and text revision on the final day of the workshop. Scientists from industry and regulatory agencies reviewed the manuscript to identify any factual errors. Conclusions LAGH compounds may represent an advance over daily GH injections because of increased convenience and differing phamacodynamic properties, providing the potential for improved adherence and outcomes. Better methods to assess adherence must be developed and validated. Long-term surveillance registries that include assessment of efficacy, cost-benefit, disease burden, quality of life, and safety are essential for understanding the impact of sustained exposure to LAGH preparations

Biochemical Properties of a Novel Cysteine Protease of Plasmodium vivax, Vivapain-4

Plasmodium vivax affects hundreds of millions each year and results in severe morbidity and mortality. Plasmodial cysteine proteases (CPs) play crucial roles during the progression of malaria since inhibition of these molecules impairs parasite growth. These CPs might be targeted for new antimalarial drugs. We characterized a novel P. vivax CP, vivapain-4 (VX-4), which appeared to evolve differentially among primate Plasmodium species. VX-4 showed highly unique substrate preference depending on surrounding micro-environmental pH. It effectively hydrolyzed benzyloxycarbonyl-Leu-Arg-4-methyl-coumaryl-7-amide (Z-Leu-Arg-MCA) and Z-Phe-Arg-MCA at acidic pH and Z-Arg-Arg-MCA at neutral pH. Three amino acids (Ala90, Gly157 and Glu180) that delineate the S2 pocket were found to be substituted in VX-4. Alteration of Glu180 abolished hydrolytic activity against Z-Arg-Arg-MCA at neutral pH, indicating Glu180 is intimately involved in the pH-dependent substrate preference. VX-4 hydrolyzed actin at neutral pH and hemoglobin at acidic pH, and participated in plasmepsin 4 activation at neutral/acidic pH. VX-4 was localized in the food vacuoles and cytoplasm of the erythrocytic stage of P. vivax. The differential substrate preferences depending on pH suggested a highly efficient mechanism to enlarge biological implications of VX-4, including hemoglobin degradation, maturation of plasmepsin, and remodeling of the parasite architecture during growth and development of P. vivax

Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth

A recent suite of new global-scale satellite sensors and regional-scale airborne campaigns are providing a wealth of remote sensing data capable of dramatically advancing our current understanding of the spatial distribution of forest structure and carbon stocks. However, a baseline for forest stature and biomass estimates has yet to be established for the wide array of available remote sensing products. At present, it remains unclear how the estimates from these sensors compare to one another in terrestrial forests, with a clear dearth of studies in high carbon density mangrove ecosystems. In the tallest mangrove forest on Earth (Pongara National Park, Gabon), we leverage the data collected during the AfriSAR campaign to evaluate 17 state-of-the-art sensor data products across the full range of height and biomass known to exist globally in mangrove forest ecosystems, providing a much-needed baseline for sensor performance. Our major findings are: (Houghton, Hall, Goetz) height estimates are not consistent across products, with opposing trends in relative and absolute errors, highlighting the need for an adaptive approach to constraining height estimates (Panet al., 2011); radar height estimates had the lowest calibration error and bias, with further improvements using LiDAR fusion (Bonan, 2008); biomass variability and uncertainty strongly depends on forest stature, with variation across products increasing with canopy height, while relative biomass variation was highest in low-stature stands (Le Quereet al., 2017); a remote sensing product's sensitivity to variations in canopy structure is more important than the absolute accuracy of height estimates (Mitchardet al., 2014); locally-calibrated area-wide totals are more representative than generalized global biomass models for high-precision biomass estimates. The findings presented here provide critical baseline expectations for height and biomass predictions across the full range of mangrove forest stature, which can be directly applied to current (TanDEM-X, GEDI, ICESat-2) and future (NISAR, BIOMASS) global-scale forest monitoring missions