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Inclusion of unmanned aircraft systems (UAS) into the weather surveillance network has the potential to improve short-term (

Digital health promises to improve healthcare, health, and wellness through the use of digital technologies. The purpose of this commentary is to review and discuss the field of digital health for Parkinson’s disease (PD) focusing on the needs, expectations, and wishes of people with PD (PwP). Our analysis shows that PwP want to use digital technologies to actively manage the full complexity of living with PD on an individual level, including the unpredictability and variability of the condition. Current digital health projects focusing on PD, however, does not live up to the expectations of PwP. We conclude that for digital health to reach its full potential, the right of PwP to access their own data needs to be recognised, PwP should routinely receive personalised feedback based on their data, and active involvement of PwP as an equal partner in digital health development needs to be the norm.

Student's two-sample t-test is often used in medical research like randomized controlled trials. To control type I errors, normality of the observed data needs to be assessed. In practice, a two-st...

Issue addressed Physical activity tracking devices have potential to improve public health, but their data needs to be reliable. No study has compared movement data between the Fitbit Zip, Apple iPhone Health app and physical activity records in a community setting over 10 days. Methods University students aged 18+ years wore both a Fitbit Zip and an iPhone at/near their right waist and completed a modified Bouchard Activity Record (BAR) for 10 days in a free-living setting. Comparisons were made between the Fitbit Zip and iPhone for the number of steps and the distance travelled and between the Fitbit Zip and BAR for the minutes of activity in three different intensities. Results Eighteen students provided sufficient data for inclusion. There were strong correlations between steps per day (r = .87) and distance travelled (r = .88) between the Fitbit Zips and iPhones. However, the Fitbit Zip measured significantly more steps per day (mean 8437 vs 7303; P ≤ .001) and greater distances (mean 5.9 vs 4.9; P ≤ .001) than the iPhone. Correlations between the Fitbit Zips and the BARs were moderate for minutes of total (r = .51) and light (r = .40) activity and weak for moderate/fairly active (r = .20) and vigorous/very active (r = .25). Conclusions There were strong correlations between the physical activity data measured by Fitbit Zips and iPhones, but the iPhone Health app significantly underestimated the number of steps per day taken and the distance travelled when compared to the Fitbit Zip. SO WHAT?: Understanding the comparability of accelerometer devices provides useful information for future pragmatic physical activity measurement.

After an initial delay, Sub-Saharan Africa (SSA) is being hit by the pandemic Demand for exports is falling and caseloads are rising Governments have approached this crisis with a range of policy options Optimal policy balances reduced infection rates with lost economic output This paper discusses how an economic-epidemiological model used to analyze policy in high-income countries could be adapted to a context where poverty considerations are paramount Differences in country characteristics across the continent affect benefits and costs of alternative policy designs We conclude by highlighting data needs and model calibration challenges for COVID-19 policy research in SSA

The delayed delivery, poor fitting and discomfort of customised orthoses are reported in rehabilitation clinics as resulting in more invasive interventions. The current practice of orthosis customisation relies heavily upon the experience and fabrication processes of therapists. In order to better understand the current practice, and thus identify data that is required for better comfort moving towards a data-driven customisation, this article describes a study generating working models of therapists. Customisations of hand and wrist orthoses for 18 patients were observed. Verbal protocol analysis was employed to extend the current understanding of fabrication processes. Working models of four therapists were established with quantitative evaluation on major phases, interactive activities and iterations of performing tasks during fabrication, revealing different working models between in- and out-patient departments (e.g. fabrication for in-patients was more complex and focussed on ergonomic fitting whereas fabrication for out-patients paid attention to durability) which were qualitatively explained. Practitioner summary: Fit and comfort are imperative for orthosis design and fabrication, however the current practice of customisation of an orthosis relies upon the experience of individual hand therapist. The article presents working models of hand therapists, and relevant data that would enable customisation of orthosis for better fit. Abbreviations: VPA: verbal protocol analysis; hw LTT: low temperature thermoplastic; ANOVA: analysis of variance.

A variety of data needs challenge the successful restoration and management of alosine populations, including information on the migration, mortality, behavior, demographic rates, and distribution of fish, both in riverine and marine environments. Radiotelemetry with gastric‐implanted transmitters has typically been used to answer some of these questions; however, observing alosines over extended periods and in the marine environment has remained beyond the limitations of this technology and implantation technique. To address these issues, we conducted an acoustic telemetry study on American Shad Alosa sapidissima by using surgical implantation methods. We tagged fish during 2015 (n = 46) and 2016 (n = 52) in the Charles River, Massachusetts, an urbanized watershed where American Shad were believed to be extirpated prior to restoration efforts beginning in 2006. Surgical implantation produced rates of in‐river mortality (40% overall) and posttagging fallback (39% overall) that were comparable to those from traditionally used gastric implantation methods. Data from American Shad that were retained for statistical analyses (n = 59) demonstrated that Watertown Dam (at river kilometer 14.3) impeded upstream migration and that New Boston Dam and Locks (at the mouth of the river) delayed postspawn emigration from the river. In total, 49 American Shad were detected outside of the Charles River. The distribution and low number of total detections, despite a large number of nearshore arrays, suggest that American Shad occupy waters farther offshore during their marine phase. American Shad were detected as overwintering on the Scotian Shelf (n = 5) and the Mid‐Atlantic Bight (n = 1). In 2017, 10 of the individuals that were tagged in 2016 returned to spawn, providing the first reported data on total migration timing and migratory behavior free of handling effects. Surgical implantation of acoustic telemetry tags is an effective method that can provide necessary and previously unattainable data on a species of conservation need.

Synchrotron beamlines acquiring data for tomographic imaging routinely produce a few TB of data per day, and significantly more in the case of time-resolved studies. This work investigates the impact of lossy compression of raw acquisitions onto tomographic reconstructions, aiming for production use. It is shown that a compression factor of at least three to four times does generally not affect the reconstruction quality and that higher factors (six to eight times) can be achieved for tomographic volumes with a high signal-to-noise ratio as it is the case for phase-retrieved datasets., Modern detectors used at synchrotron tomographic microscopy beamlines typically have sensors with more than 4–5 mega-pixels and are capable of acquiring 100–1000 frames per second at full frame. As a consequence, a data rate of a few TB per day can easily be exceeded, reaching peaks of a few tens of TB per day for time-resolved tomographic experiments. This data needs to be post-processed, analysed, stored and possibly transferred, imposing a significant burden onto the IT infrastructure. Compression of tomographic data, as routinely done for diffraction experiments, is therefore highly desirable. This study considers a set of representative datasets and investigates the effect of lossy compression of the original X-ray projections onto the final tomographic reconstructions. It demonstrates that a compression factor of at least three to four times does not generally impact the reconstruction quality. Potentially, compression with this factor could therefore be used in a transparent way to the user community, for instance, prior to data archiving. Higher factors (six to eight times) can be achieved for tomographic volumes with a high signal-to-noise ratio as it is the case for phase-retrieved datasets. Although a relationship between the dataset signal-to-noise ratio and a safe compression factor exists, this is not simple and, even considering additional dataset characteristics such as image entropy and high-frequency content variation, the automatic optimization of the compression factor for each single dataset, beyond the conservative factor of three to four, is not straightforward.

This paper presents a dataset produced from the largest known survey examining how researchers and support professionals discover, make sense of and reuse secondary research data. 1677 respondents in 105 countries representing a variety of disciplinary domains, professional roles and stages in their academic careers completed the survey. The results represent the data needs, sources and strategies used to locate data, and the criteria employed in data evaluation of these respondents. The data detailed in this paper have the potential to be reused to inform the development of data discovery systems, data repositories, training activities and policies for a variety of general and specific user communities., Measurement(s) data discovery behaviours • data reuse behaviours • data management Technology Type(s) Survey • Self-Report Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12445034

Policy document mention is considered to indicate the significance and societal impact of scientific product. However, the accuracy of policy document altmetrics data needs to be evaluated to fully understand its strength and limitation. An in-depth coding analysis was conducted on sample policy documents records of Altmetric.com database. The sample consists of 2079 records from all 79 distinct policy document source platforms tracked by the database. Errors about mentioned publications in the policy documents (type A error) are found in 8% of the records, while errors about either the recorded policy documents or the mentioned publications in the altmetrics database (type B error) are found in 70% of the records. In type B error, policy document link error (5% of the records) could be attributable to the policy document website, transcription error (52% of the records) could be attributable to the third-party bibliographic data provider. These two categories of error are relatively minor and may have limited influence on altmetrics research and practices. False positive policy document mention (13% of the records), however, could be attributable to the Altmetric database and may diminish the validity of research based on the policy document altmetrics data. The underlying reasons remain to be further investigated. Considering the high complexity of extracting mentions of publications from various sources and formats of policy documents as well as its short history, Altmetric database has achieved excellent performance.

A group of 38 experts specializing in hyperspectral remote-sensing methods for aquatic ecosystems attended an interactive Euromarine Foresight Workshop at the Flanders Marine Institute (VLIZ) in Ostend, Belgium, June 4–6, 2019. The objective of this workshop was to develop recommendations for comprehensive, efficient, and effective laboratory and field programs to supply data for development of algorithms and validation of hyperspectral satellite imagery for micro-, macro- and endosymbiotic algal characterization across the globe. The international group of researchers from Europe, Asia, Australia, and North and South America (see online Supplementary Materials) tackled how to develop global databases that merge hyperspectral optics and phytoplankton group composition to support the next generation of hyperspectral satellites for assessing biodiversity in the ocean and in food webs and for detecting water quality issues such as harmful algal blooms. Through stimulating discussions in breakout groups, the team formulated a host of diverse programmatic recommendations on topics such as how to better integrate optics into phytoplankton monitoring programs; approaches to validating phytoplankton composition with ocean color measurements and satellite imagery; new database specifications that match optical data with phytoplankton composition data; requirements for new instrumentation that can be implemented on floats, moorings, drones, and other platforms; and the development of international task forces. Because in situ observations of phytoplankton biogeography and abundance are scarce, and many vast oceanic regions are too remote to be routinely monitored, satellite observations are required to fully comprehend the diversity of micro-, macro-, and endosymbiotic algae and any variability due to climate change. Ocean color remote sensing that provides regular synoptic monitoring of aquatic ecosystems is an excellent tool for assessing biodiversity and abundance of phytoplankton and algae in aquatic ecosystems. However, neither the spatial, temporal, nor spectral resolution of the current ocean color missions are sufficient to characterize phytoplankton community composition adequately. The near-daily overpasses from ocean color satellites are useful for detecting the presence of blooms, but the spatial resolution is often too coarse to assess the patchy distribution of blooms, and the multiband spectral resolution is generally insufficient to identify different types of phytoplankton from each other, even if progress has undeniably been achieved during the last two decades (e.g., IOCGG, 2014). Moreover, the methods developed for multichannel sensor use are often highly tuned to a region but are inaccurate when applied broadly. New orbital imaging spectrometers are being developed that cover the full visible and near-infrared spectrum with a large number of narrow bands dubbed “hyperspectral” (e.g., TROPOMI, PRISMA, EnMAP, PACE, CHIME, SBG). Hyper-spectral methods have been explored for many years to assess phytoplankton groups and map seafloor habitats. However, the utility of hyperspectral imaging still needs to be demonstrated across diverse aquatic regimes. Aquatic applications of hyperspectral imagery have been limited by both the technology and the ability to validate products. Some of the past hyperspectral space-based sensors have suffered from calibration artifacts, low sensitivity in aquatic ecosystems (e.g., CHRIS, HICO), and very low spatial resolution (e.g., SCIAMACHY), but the next generation of sensors are planned to have high signal-to-noise ratio and improved performance over aquatic targets. Providing data to develop and validate hyperspectral approaches to characterize phytoplankton groups across the globe poses new challenges. Several recent studies have documented gaps that need to be filled in order to assess algal diversity across the globe (IOCCG, 2014; Mouw et al., 2015; Bracher et al., 2017), which promoted/inspired the formation of this workshop.

Macroseismic intensity data are an important source to learn from historical earthquakes. Nevertheless, this data needs to be converted into more suitable intensity measures to be used in risk analyses, as well as in design practice. To this purpose, in this paper, correlations between macroseismic scales and ground motion parameters have been derived. Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV) and Housner Intensity (IH) as instrumental measures, and European Macroseismic Scale (EMS-98) and Mercalli-Cancani-Sieberg (MCS) as macroseismic measures, have been considered. 179 ground-motion records belonging to 32 earthquake events occurred in Italy in the last 40 years have been selected, provided that for each record, macroseismic intensity in terms of either EMS-98 or MCS or both were also available. Statistical analyses have been carried out to derive both direct (i.e. macroseismic vs instrumental intensity) and inverse (instrumental vs macroseismic intensity) relationships. Results obtained from the proposed relationships have been analyzed and compared with some of the most prominent results available in the technical literature.

The past decade (2009-19) has seen orthodontics incorporate many new infusions into its fold. This scoping review analyzes published orthodontic literaure in five different domains:(1) Recent advancements in orthodontic 3D applications including 3D printing, diagnosis and management. (2) Recent advancements in orthodontic biomaterials, nanotechnology, biomimetics, battery-driven devices. (3) Recent advancements in orthodontic patient education, orthodontic training, and orthodontics practice management. (4) Recent advancements in orthodontic E-health protocols, tele-orthodontics, teleconsultations etc. and (5) Recent advancements in orthodontic marketing and social media influences. A total of 1245 records were searched,of which 65 potentially relevant articles were retrieved in full. 42 studies met the selection criteria following screening and were included in the scoping review. The review found studies pertaining to morphological features or surface characteristics with respect to 3D applications (3D printing, diagnosis and management)as the most represented outcome assessment (49%).Orthodontic Marketing & Influence of Social Media (27%) and Biomaterials,Nano-Technology,Biomimetics and battery Driven devices have also been considerably reported (20%) in the past decade. More scientific data needs to be gathered in the field of Patient education, E-health, tele-orthodontics, and protection of patient confidentiality. The authors present COS (Core Outcome Sets)that could be a road map for evaluating currently employed developments as well as testing new ones in future.

Recent years have witnessed an increasing frequency of disasters, both natural and human-induced. This applies pressure to critical infrastructures (CIs). Among all the CI sectors, the energy infrastructure plays a critical role, as almost all other CIs depend on it. In this paper, 30 energy infrastructure models dedicated for the modeling and simulation of power or natural gas networks are collected and reviewed using the emerging concept of resilience. Based on the review, typical modeling approaches for energy infrastructure resilience problems are summarized and compared. The authors, then, propose five indicators for evaluating a resilience model; namely, catering to different stakeholders, intervening in development phases, dedicating to certain stressor and failure, taking into account different interdependencies, and involving socio-economic characteristics. As a supplement, other modeling features such as data needs and time scale are further discussed. Finally, the paper offers observations of existing energy infrastructure models as well as future trends for energy infrastructure modeling.

Experts representative of Texas’ water sectors identified critical water data needs and described the design of a comprehensive open access data system that facilitates use of public water data in Texas at the April 2018 Connecting Texas Water Data Workshop as reported in the Texas Water Journal. Participants described potential use cases to initiate work on the most critical data hubs for connecting Texas water data. This update describes progress on a flood dashboard by the Texas Water Development Board and development of use cases by stakeholders with expertise in water data for drought and surface water – groundwater interactions., Texas Water Journal, Vol. 11 No. 1 (2020)

Animal heat production and transfer data needs updating as genetics evolve, and newer technology provides alternative settings for collecting heat flux measurements. The project objective was to use heat flux sensors to measure the postural (resting, standing) effects on heat flux from finishing pigs, and compare estimated tissue resistance and sensible heat production based on these measurements to literature values. We measured heat flux from 12 individually housed active barrows with average (±SD) weight ranges of 95.6±15.5 kg and 111±13.9 kg, for Trials 1 and 2, respectively. We affixed heat flux sensors to the shaved areas on the right and left sides and rumps of the pigs to collect heat flux measurements every minute over a 6-h period during each trial. An overhead video camera system recorded pig behavior and positioning within each pen throughout the trials. Heat flux measurements showed rapid heat loss between a pig and floor when the pig lies on a cooled surface, but the heat flux starts to decrease almost immediately to steady state levels. When standing, the average heat flux from the rear of the pigs (124±8 W m-2) was greater than the heat flux from the sides of the animal (117±8 W m-2) (p2=0.2735, n=24) with an intercept of 143 W m-2, suggests the heat flux decreases 0.25 W m-2 for each 1 kg increase in pig mass. Tissue resistance estimates from these heat flux measurements are approximately 60% of tissue resistance model estimates from the 1990’s. The heat flux data translate to sensible heat production estimates of 1.8 W kg-1, within the range of calorimeter-based estimates from recent literature. Keywords: Heat transfer model, Pigs, Pig housing, Tissue resistance.

This paper considers questions related to the adoption of stochastic methods in hydrogeology. It looks at factors affecting the adoption of stochastic methods including environmental regulations, financial incentives, higher education, and the collective feedback loop involving these factors. We begin by evaluating two previous paper series appearing in the stochastic hydrogeology literature, one in 2004 and one in 2016, and identifying the current thinking on the topic, including the perceived data needs of stochastic methods, the attitude in regulations and the court system regarding stochastic methods, education of the workforce and the availability of software tools needed for implementing stochastic methods in practice. Comparing the state of adoption in hydrogeology to petroleum reservoir engineering allowed us to identify quantitative metrics on which to base our analysis. For impediments to the adoption of stochastic hydrology, we identified external factors as well as self-inflicted wounds. What emerges is a picture much broader than current views. Financial incentives and regulations play a major role in stalling adoption. Stochastic Hydrology's blind spot is in confusing between risk and uncertainty and ignoring uncertainty. We show that stochastic hydrogeology comfortably focused on risk while ignoring uncertainty, to its own detriment and to the detriment of its potential clients. The imbalance between the treatment on risk on one hand and uncertainty on the other is shown to be common to multiple disciplines in hydrology that interface with risk and uncertainty.

This paper reviews the recent literature on rural-urban migration in developing countries, focusing on three key questions: What motivates or forces people to migrate? What costs do migrants face? What are the impacts of migration on migrants and the economy? The literature paints a complex picture whereby rural-urban migration is driven by many factors and the returns to migration as well as the costs are very high. The evidence supports the notion that migration barriers hinder labor market adjustment and are likely to be welfare reducing. The review concludes by identifying gaps in current research and data needs.

Contaminant exposure is among the many threats to Golden Eagle (Aquila chrysaetos) populations throughout North America, particularly lead poisoning and anticoagulant rodenticides (AR). These threats may act in concert with others (e.g., lead poisoning and trauma associated with striking objects) to exacerbate risk. Golden Eagles are skilled hunters but also exploit scavenging opportunities, making them particularly susceptible to contaminant exposure from ingesting tissues of poisoned or shot animals. Lead poisoning has long been recognized as an important source of mortality for Golden Eagles throughout North America. More recently, ARs have been associated with both sublethal and lethal effects in raptor species worldwide. In this review, we examine the current state of knowledge for lead and AR exposure in Golden Eagles, drawing from the broader raptor contaminant ecology literature. We examine lead and AR sources within Golden Eagle habitats, exposure routes and toxicity, effects on individuals and populations, synergistic effects, and data and information needs. Continued research addressing data needs and information gaps will help with Golden Eagle conservation planning.

PurposeThe purpose of this paper is to investigate the substitutability of corporate hedging and diversification in the real estate investment trusts (REITs) industry. The authors hypothesize that, relative to diversified firms, focused firms are more likely to be associated with hedging. The role of firm size is also analyzed.Design/methodology/approachThe logistic regression approach is utilized to analyze the probability of hedging and the panel regression approach is used to examine the amount of hedging.FindingsThe authors find that, relative to diversified firms, firms focused on a single property type are more likely to engage in hedging. However, this finding is significant only for smaller firms, which implies a non-linear relation between hedging and firm size. The evidence is not as strong when firm focus is measured by geographic concentration. In terms of hedging amount, smaller firms’ average hedge ratio is greater than that of larger firms. For either small or large firms group, hedging amounts increase with firm focus measured by either property or geographic concentration and increase with firm sizes.Research limitations/implicationsThe results imply that, relative to diversified REITs, REITs focused on a single property type are more likely to engage in hedging. However, this finding is significant only for smaller firms, which implies a non-linear relation between hedging and firm size. The evidence is not as strong when firm focus is measured by geographic concentration, suggesting that geographic concentration is perceived to be less risky than property type concentration. For either small or large firms group, hedging amounts increase with firm focus measured by either property or geographic concentration and increase with firm sizes, which implies that hedging amount does not depend on firm size. The sample period is limited to the years 2010 to 2013 because some data needs to be manually collected.Practical implicationsThe results imply that REITs consider both property diversification and hedging in managing their risk.Originality/valueThe research represents an early attempt to investigate the relation between corporate hedging and diversification. The investigation into the REIT industry has several advantages such as a lower likelihood of using derivatives for speculation.

This pilot study provides a conceptual framework for the application of the anthropological analysis of skeletal features and surgical interventions for the purpose of identification in cases of unknown deceased individuals with unavailable fingerprint, genetic or odontological antemortem data. The study sample includes 276 individuals with known demographic and clinical information from the Italian CAL Milano Cemetery Skeletal Collection. In the sample, 124 (45%) individuals showed one or more skeletal features that may be potentially individualizing. Of these, 79% showed two and more features, which occurred in a multitude of different combinations. Skeletal findings may provide useful postmortem information that can be compared with antemortem witness statements and clinical imaging. However, more research into the utility of dry bone findings and the availability of comparative material, including imaging, and epidemiological data needs to be undertaken before skeletal features can be implemented into identification protocols and databases.

The yellow-billed loon Gavia adamsii was designated as a candidate species for listing as threatened or endangered under the U.S. Endangered Species Act in 2009. Subsistence harvest was identified as a threat based on the 2007 harvest estimate for the Bering Strait region of Alaska. This estimate was unusually high and inconsistent with data on the species' abundance and distribution. We conducted this study in 2011–2012 on St. Lawrence Island, in the Bering Sea, to fulfill data needs related to this Endangered Species Act listing process. Our objectives were to clarify 1) loon species harvested, 2) numbers of loons harvested, and 3) loon harvest methods and uses by local subsistence communities. We conducted harvest surveys, ethnographic research, and shore-based bird counts. Loons were

Background: Despite therapeutics based on siRNA have an immense potential for the treatment of incurable diseases such as cancers. However, the in vivo utilization of siRNA and also the delivery of this agent to the target site is one of the most controversial challenges. The helpful assistance by nanoparticles can improve stable delivery and also enhance efficacy. More nanoparticle-based siRNA therapeutics is expected to become available in the near future. Methods: The search strategy followed the guidelines of the Centre of Reviews and Dissemination. The studies were identified from seven databases (Scopus, Web of Science, Academic Search Premiere, CINAHL, Medline Ovid, Eric and Cochrane Library). Studies was selected based on titles, abstracts and full texts. Results: One hundred twenty nine papers were included in the review. These papers defined hurdles in RNAi delivery and also strategies to overcome these hurdles. This review discussed the existing hurdles for systemic administration of siRNA as therapeutic agents and highlights the various strategies to overcome these hurdles, including lipid-based nanoparticles and polymeric nanoparticles, and we also briefly reviewed chemical modification. Conclusion: Delivery of siRNA to the target site is the biggest challenge for its application in the clinic. The findings of this review confirmed by encapsulation siRNA in the nanoparticles can overcome these challenges. The rapid progress in nanotechnology has enabled the development of effective nanoparticles as the carrier for siRNA delivery. However, our data about siRNA-based therapeutics and also nanomedicine are still limited. More clinical data needs to be completely understood in the benefits and drawbacks of siRNA-based therapeutics. Prospective studies must pay attention to the in vivo safety profiles of the different delivery systems, including uninvited immune system stimulation and cytotoxicity. In essence, the development of nontoxic, biocompatible, and biodegradable delivery systems for medical application of RNAi-based therapeutics is needed.

Introduction The significance of nuclear data in the choice and medical application of a radionuclide is considered: the decay data determine its suitability for organ imaging or internal therapy and the reaction cross section data allow optimisation of its production route. A brief discussion of reaction cross sections and yields is given. Standard radionuclides The standard SPECT, PET and therapeutic radionuclides are enumerated and their decay and production data are considered. The status of nuclear data is generally good. Some existing discrepancies are outlined. A few promising alternative production routes of 99mTc and 68Ga are discussed. Research-oriented radionuclides The increasing significance of non-standard positron emitters in organ imaging and of low-energy highly-ionizing radiation emitters in internal therapy is discussed, their nuclear data are considered and a brief review of their status is presented. Some other related nuclear data issues are also mentioned. Production of radionuclides using newer technologies The data needs arising from new directions in radionuclide applications (multimode imaging, theranostic approach, radionanoparticles, etc.) are considered. The future needs of data associated with possible utilization of newer irradiation technologies (intermediate energy cyclotron, high-intensity photon accelerator, spallation neutron source, etc.) are outlined. Conclusion Except for a few small discrepancies, the available nuclear data are sufficient for routine production and application of radionuclides. Considerable data needs exist for developing novel radionuclides for applications. The developing future technologies for radionuclide production will demand further data-related activities.

In view of the rapidly growing number of synthesized nanoparticles as well as public concerns about their potential negative impacts on human health and the environment, there is an urgent need to address current risk assessment data gaps. Thus, the development of comprehensive computational methods (e.g., read-across methods) for filling data gaps that meet realistic data needs is crucial. The present study proposes a new quantitative read-across approach based on linear algebra (i.e., one/two-point-slope formula) and one of the most widely used unsupervised pattern recognition methods (i.e., principal component analysis). The applicability and usefulness of the newly developed read-across algorithm for pre-screening hazard assessment of nanomaterials are confirmed by using three literature nanotoxicity datasets. The findings from this study clearly indicate that the proposed read-across approach provides reasonably accurate and statistically significant results of estimations of nanotoxicity data. Therefore, the method can be used for prioritizing current and future nanoparticles for the purpose of further testing and risk assessment.

Earth observation imagery collected by the series of Landsat satellites constitutes the longest and most consistent collection of moderate spatial resolution remotely sensed data. Feedback from the Landsat user community has played an important role in assessing its utility and making improvements to future Landsat missions. The United States Geological Survey (USGS) and the National Aeronautical and Space Administration (NASA) continue to input from user communities. This paper describes the outcome of soliciting input from experts associated with AmericaView (AV), a non-profit organization aimed at promoting remote sensing applications in the US. The AV community identified the importance of rigorously calibrated Landsat data for LULC applications at the state level and made several recommendations for future Landsat missions. Recommendations suggested by the community of AV experts provide extremely valuable insights to USGS and NASA to further their discussions about the design and operation of future Landsat missions.

The US Environmental Protection Agency Endocrine Disruptor Screening Program (EDSP) is a tiered screening approach to determine the potential for a chemical to interact with estrogen, androgen, or thyroid hormone systems and/or perturb steroidogenesis. Use of high-throughput screening (HTS) to predict hazard and exposure is shifting the EDSP approach to (1) prioritization of chemicals for further screening; and (2) targeted use of EDSP Tier 1 assays to inform specific data needs. In this work, toxicology data for three triazole fungicides (triadimefon, propiconazole, and myclobutanil) were evaluated, including HTS results, EDSP Tier 1 screening (and other scientifically relevant information), and EPA guideline mammalian toxicology study data. The endocrine-related bioactivity predictions from HTS and information that satisfied the EDSP Tier 1 requirements were qualitatively concordant. Current limitations in the available HTS battery for thyroid and steroidogenesis pathways were mitigated by inclusion of guideline toxicology studies in this analysis. Similar margins (3–5 orders of magnitude) were observed between HTS-predicted human bioactivity and exposure values and between in vivo mammalian bioactivity and EPA chronic human exposure estimates for these products’ registered uses. Combined HTS hazard and human exposure predictions suggest low priority for higher-tiered endocrine testing of these triazoles. Comparison with the mammalian toxicology database indicated that this HTS-based prioritization would have been protective for any potential in vivo effects that form the basis of current risk assessment for these chemicals. This example demonstrates an effective, human health protective roadmap for EDSP evaluation of pesticide active ingredients via prioritization using HTS and guideline toxicology information.

Agent modeling has rightfully garnered much attention in the design and study of autonomous agents that interact with other agents. However, despite substantial progress to date, existing agent-modeling methods too often (a) have unrealistic computational requirements and data needs; (b) fail to properly generalize across environments, tasks, and associates; and (c) guide behavior toward inefficient (myopic) solutions. Can these challenges be overcome? Or are they just inherent to a very complex problem? In this reflection, I argue that some of these challenges may be reduced by, first, modeling alternative processes than what is often modeled by existing algorithms and, second, considering more deeply the role of non-binding communication signals. Additionally, I believe that progress in developing autonomous agents that effectively interact with other agents will be enhanced as we develop and utilize a more comprehensive set of measurement tools and benchmarks. I believe that further development of these areas is critical to creating autonomous agents that effectively model and interact with other agents.