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VisualCommunity is a platform designed to support community or neighborhood scale research. The platform integrates mobile, AI, visualization techniques, along with tools to help domain researchers, practitioners, and students collecting and working with spatialized video and geo-narratives. These data, which provide granular spatialized imagery and associated context gained through expert commentary have previously provided value in understanding various community-scale challenges. This paper further enhances this work AI-based image processing and speech transcription tools available in VisualCommunity, allowing for the easy exploration of the acquired semantic and visual information about the area under investigation. In this paper we describe the specific advances through use case examples including COVID-19 related scenarios.

Our objective was to assess within-herd seroprevalence of Anaplasma marginaleantibodies across 12 Florida beef cattle herds and compare with statewide seroprevalence.

Flexibility can be built into an irrevocable insurance trust by drafting provisions granting a limited power of appointment to beneficiaries, allowing the trustee to terminate the trust and distribute the policy to beneficiaries or the grantor's spouse, and by granting the trustee broad distribution and loan powers and the ability to modify nondispositive provisions in response to tax law changes. Proper drafting will also allow for changes in the grantor's marital situation. An inflexible trust can be transferred to a new trust, without triggering transfer-for-value or three-year includibility rules, by purchasing the policy from the existing trust and selling it to the new trust.

The complex interrelationship between the built environment and social problems is often described but frequently lacks the data and analytical framework to explore the potential of such a relationship in different applications. We address this gap using a machine learning (ML) approach to study whether street-level built environment visuals can be used to classify locations with high-crime and lower-crime activities. For training the ML model, spatialized expert narratives are used to label different locations. Semantic categories (e.g., road, sky, greenery, etc.) are extracted from Google Street View (GSV) images of those locations through a deep learning image segmentation algorithm. From these, local visual representatives are generated and used to train the classification model. The model is applied to two cities in the U.S. to predict the locations as being linked to high crime. Results show our model can predict high- and lower-crime areas with high accuracies (above 98% and 95% in first and second test cities, accordingly).

Real estate owners can realize savings in terms of income taxes, estate taxes and gift taxes. Taxpayers can incorporate their residences and investment realty into their estate planning strategies. A sale/leaseback arrangement allows the seller to retain control of the property, and the income tax on the gain from a sale can be deferred by reporting the gain under the installment method.

Observed petrophysical properties reflect the characteristics of a reservoir rock at a microscopic scale, thus close inspection of this microstructure is an indispensable part of core analysis. While conventional geological [...]

Bovine anaplasmosis, caused by the hemobacteria Anaplasma marginale(Am) is the most prevalent tick-transmitted disease of cattle worldwide and is associated with significant production losses in cattle. The objective of this survey was to investigate the within-herd seroprevalence of antibodies to Amand the relationship between disease status and milk production after anaplasmosis outbreak in a northern Iowa dairy herd.

Geoscientists use observed data to estimate properties of the Earth's interior. This often requires non‐linear inverse problems to be solved and uncertainties to be estimated. Bayesian inference solves inverse problems under a probabilistic framework, in which uncertainty is represented by a so‐called posterior probability distribution. Recently, variational inference has emerged as an efficient method to estimate Bayesian solutions. By seeking the closest approximation to the posterior distribution within any chosen family of distributions, variational inference yields a fully probabilistic solution. It is important to define expressive variational families so that the posterior distribution can be represented accurately. We introduce boosting variational inference(BVI) as a computationally efficient means to construct a flexible approximating family comprising all possible finite mixtures of simpler component distributions. We use Gaussian mixture components due to their fully parametric nature and the ease with which they can be optimized. We apply BVI to seismic travel time tomography and full waveform inversion, comparing its performance with other methods of solution. The results demonstrate that BVI achieves reasonable efficiency and accuracy while enabling the construction of a fully analytic expression for the posterior distribution. Samples that represent major components of uncertainty in the solution can be obtained analytically from each mixture component. We demonstrate that these samples can be used to solve an interrogation problem: to assess the size of a subsurface target structure. To the best of our knowledge, this is the first method in geophysics that provides both analytic and reasonably accurate probabilistic solutions to fully non‐linear, high‐dimensional Bayesian full waveform inversion problems. This paper introduces an efficient method to find possible images of the Earth's interior structures and estimate the uncertainties of these images using seismic data observed at the near surface. The method represents the imaging results with a flexible expression. We demonstrate the method by imaging the subsurface using two different types of seismic data, and by comparing the imaging results with other methods that have been introduced previously. We further show that the obtained imaging results can be used to estimate the size of a subsurface structure of interest with minimum bias. We apply boosting variational inference to Bayesian inversion, which uses a mixture of Gaussians to approximate the posterior distributionThe method is shown to be efficient and accurate, and constructs a fully analytic expression for a high‐dimensional posterior distributionThe analytic solution allows extremely efficient methods to be used to answer scientific questions with minimum bias We apply boosting variational inference to Bayesian inversion, which uses a mixture of Gaussians to approximate the posterior distribution The method is shown to be efficient and accurate, and constructs a fully analytic expression for a high‐dimensional posterior distribution The analytic solution allows extremely efficient methods to be used to answer scientific questions with minimum bias

Between 1975 and 1979, upwards of two million men, women, and children perished from starvation, disease, exhaustion, inadequate medical care, torture, murder, and execution during the Cambodian genocide. Within this context, the forced evacuation of Phnom Penh has figured prominently in the literature, especially with regard to the violence encountered on the route. To date, however, there has been no empirical reconstruction of the evacuation. Here we address this deficiency, while simultaneously presenting a novel geospatial approach that can be utilized to collect, map and analyze interviews in a more appropriate manner than by more traditional geographic information systems (GIS) use. We utilize a spatial video geonarrative to provide a geographically-supported reconstruction of the forced evacuation of Phnom Penh through the collection of first-hand accounts taken while retracing the route. We add previously unavailable, contextualized, spatial insights to this forced evacuation, including findings on why the bridges acted as choke points, leading to increased violence. Moreover, in some instances the direction of the march turned back towards the city because of the road configuration which again led to a choke point as two columns merged. In presenting these types of contextualized, spatial details we contribute to both the specifics of the Cambodian genocide, and to how thick mapping and inductive visualization can enrich similar research in the humanities

By definition, a remanufactured product must perform to the same (or higher) level as the original product, and must therefore be issued a warranty of the same (or longer) duration. However, many components of remanufactured products will have been subjected to regular stresses in their first cycle of use and may exhibit unseen signs of damage at a microstructural level. This may not affect the remanufactured product’s performance initially but could cause it to fail before its renewed warranty expires. To combat this, we propose that the integrity of individual components is assessed non-destructively before they are consigned to storage. However, lack of remanufacture specific tools and techniques for assessment, particularly non-destructive tools, are major hindrances to this strategy. Furthermore, ease of non-destructive testing (NDT) is not currently a consideration in the design of components; components with complex geometries may therefore be difficult to test. This preview paper presents, for the first time, a framework for including NDT suitability as a design criterion at the outset of the component’s lifecycle, where the geometry and surface accessibility of the component are optimised for future assessment. Ensuring that components can be easily inspected would not only allow increased confidence in the structural integrity of remanufactured products, but it would also extend the range of products suitable for remanufacturing. This paper serves as a proof of concept, examining simple inspection scenarios in order to demonstrate how the shape of components and data acquisition geometries can adversely affect the coverage of ultrasonic NDT.

Quality factor (Q) or equivalently attenuation α=1Qdescribes the amount of energy lost per cycle as a wave travels through a medium. This is important to correct seismic data amplitudes for near‐surface effects, to locate subsurface voids or porosity, to aid seismic interpretation, or for characterizing other rock and fluid properties. Seismic attenuation can be variable even when there are no discernible changes in seismic velocity or density (Yıldırım et al., 2017, https://doi.org/10.1016/j.jappgeo.2016.11.010) and so provides independent information about subsurface heterogeneity. This study uses ambient noise recordings made on the Ekofisk Life of Field Seismic array to estimate Qstructure in the near surface. We employ the method of X. Liu et al. (2015, https://doi.org/10.1093/gji/ggv357), which uses linear triplets of receivers to estimate Q—ours is the first known application of the method to estimate the Qstructure tomographically. Estimating Qrequires an estimate of phase velocity which we obtain using the method of Bloch and Hales (1968, https://pubs.geoscienceworld.org/ssa/bssa/article‐abstract/58/3/1021/116607/) followed by traveltime tomography. The Qstructure at Ekofisk has features which can be related to local geology, showing that surface ambient noise recordings may provide a new and robust method to image Q. Our results suggest that there is a nonlinear relationship between Qand compression. They also may explain why it has been found that in the period range of 1 to 2 s considered here, ambient noise cross correlations along paths that span the North Sea Basin are unreliable: Such Qvalues would attenuate almost all ambient seismic energy during such a traverse. Qstructure estimated from ambient seismic noise recordings shows some correlation with known geologyResults suggest that there is a nonlinear relationship between Qand compressionEstimated Qvalues may explain poor ambient noise interferometry results for signals crossing the North Sea

This study utilizes geospatial tools of remote sensing, geographical information systems (GIS), and global positioning system (GPS) to examine the land loss, land cover (LC) change, landuse of Kutubdia Island, Bangladesh. Multi-spectral Scanner (MSS), Thematic Mapper (TM), and Landsat8 OLI imageries were used for land cover change. For assessing the landuse patterns of 2012, spatial video data were collected by using contour GPS camera. Using remote sensing analysis three different land cover classes (water, trees and forest, and agriculture) were identified and land cover changes were detected from 1972 to 2013. The results show from 1972 to 2013, an estimated 9 km2 of land has been lost and significant changes have taken place from 1972 to 2013. Only an estimated .35 km2 area of accretion has taken place during the study period. Using GIS eight different landuse patterns were identified based on spatial video data.

After decades of low but continuing activity, applications of machine learning (ML) in solid Earth geoscience have exploded in popularity. This special collection provides a snapshot of those applications, which range from data processing to inversion and interpretation, for which ML appears particularly well suited. Inevitably, there are variations in the degree to which these methods have been developed. We hope that the progress seen in some areas will inspire efforts in others. Challenges remain, including the formidable task of how geoscience can keep pace with developments in ML while ensuring the scientific rigor that our field depends on, but with improvements in sensor technology and accelerating rates of data accumulation, the methods of ML seem poised to play an important role for the foreseeable future. Machine learning has been the topic that attracts massive academic attention in Solid‐Earth Geosciences in the past decade. Applications of machine learning (ML), including the more conventional signal processing‐based methods and the trending deep neural network‐based methods, have dominated many scientific conversations. We introduce the special collection of ML applications in Solid‐Earth geosciences that range from earthquake signal processing, automatic image interpretation, to joint understanding of multiple geoscience datasets. With the extraordinary efforts in ML studies, we now have a better outline of the areas where ML has contributed most significantly through efficiency and automation, and where ML has the potential to revolutionize the workflow and advance the integrated scientific understanding of the Solid‐Earth processes. Applications of machine learning (ML) in solid Earth geoscience have exploded in the past few yearsThis special collection provides a snapshot of ML applications from data processing to inversion and interpretationBetter integration of ML algorithms and scientific rigor is expected to further improve our understanding of the Earth Applications of machine learning (ML) in solid Earth geoscience have exploded in the past few years This special collection provides a snapshot of ML applications from data processing to inversion and interpretation Better integration of ML algorithms and scientific rigor is expected to further improve our understanding of the Earth

AbstractTo adapt to an interactive generation of learners, video resources can provide information necessary for lab preparation, describe clinical correlations, and maximize dissection time. In this study, dissection summary videos with embedded quizzes were to be viewed by K-State first-year veterinary students prior to their canine anatomy lab sessions. Videos were created using an iPhone, edited via Camtasia editing software, and uploaded to the course Canvas page. Following the conclusion of the Fall 2022 semester, final course grade, practical exam scores (exam), pre-lab video (video) time interaction, pre-lab quiz (quiz) scores, and student perception data were analyzed. Positive, statistically significant correlations were found between number of videos viewed and certain exam scores, with the strongest correlation being for the lower quartile specifically. Significant correlations were also found between average exam score and total number of videos viewed throughout the semester, and final course grade and total time spent viewing all videos. Positive, statistically significant correlations were found between average quiz score and exam score. A thematic analysis of student comments revealed videos appeared to have been a beneficial part of the course, providing students with a valuable resource for preparation, study, and increased understanding and confidence. These findings indicate that providing videos as a supplemental resource is beneficial to veterinary student learning and well perceived. This study also suggests that video views can predict lower quartile student exam score. The correlations in this study are weak, but the statistical significance depicts a positive impact on student practical exam scores.

Several letters to the editor are presented in response to articles in previous issues including "False Security," about the recovery of the sketch of Canterbury earthquake and the economic condition in the Christchurch after hit by an earthquake.

If energy emitted by a seismic source such as an earthquake is recorded on a suitable backbone array of seismometers, source‐receiver interferometry (SRI) is a method that allows those recordings to be projected to the location of another target seismometer, providing an estimate of the seismogram that would have been recorded at that location. Since the other seismometer may not have been deployed at the time at which the source occurred, this renders possible the concept of “retrospective seismology” whereby the installation of a sensor at one period of time allows the construction of virtual seismograms as though that sensor had been active before or after its period of installation. Here we construct such virtual seismograms on target sensors in both industrial seismic and earthquake seismology settings, using both active seismic sources and ambient seismic noise to construct SRI propagators, and on length scales ranging over 5 orders of magnitude from ∼40 m to ∼2500 km. In each case we compare seismograms constructed at target sensors by SRI to those actually recorded on the same sensors. We show that spatial integrations required by interferometric theory can be calculated over irregular receiver arrays by embedding these arrays within 2‐D spatial Voronoi cells, thus improving spatial interpolation and interferometric results. The results of SRI are significantly improved by restricting the backbone receiver array to include approximately those receivers that provide a stationary‐phase contribution to the interferometric integrals. Finally, we apply both correlation‐correlation and correlation‐convolution SRI and show that the latter constructs fewer nonphysical arrivals. Virtual seismograms are constructed by source‐receiver interferometry (SRI)Ambient noise interferometry constructs robust SRI propagators over 1500 kmCorrelation‐convolution SRI constructs seismograms even in attenuative media

Geoscientists often use spatially discretized cellular models of the Earth where data in each grid cell provide independent information about the model parameters of interest at that location. In Bayesian inference this information is given as a set of likelihoods describing the (unnormalized) probability of the parameters, given only the data in each cell. Preexisting information about the model parameters' values and their spatial correlations may be described by a prior probability distribution. The prior, likelihoods, and Bayes' rule together specify a posterior probability distribution that describes the resultant state of information over all model parameters. However, due to the high dimensionality of typical models, the posterior is usually only known up to a multiplicative constant and only at specific, numerically evaluated points in the model space (i.e., it is not known analytically). Markov chain Monte Carlo (MCMC) methods are typically used to produce an ensemble of correlated samples from the posterior. These ensembles are slow to converge in distribution to the posterior; indeed, they may not converge in finite time, and detecting their state of convergence is often impossible in practice. Thus, estimates of the posterior obtained in this way may be biased. We derive a recursive algorithm which samples the posterior exactly, so as to avoid these convergence issues. Its computational cost scales with the size of the parameters' sample space, the prior's spatial range of dependency, and the shortest edge dimension of the grid. We develop an approximation to the algorithm such that it may be used on large 2‐D (and potentially 3‐D) model grids. We apply it to synthetic seismic attribute data and obtain results which compare favorably to the results of MCMC (Gibbs) sampling—which exhibits convergence problems. MCMC sampling methods for estimating posteriors often yield biased resultsA recursive algorithm to sample exactly from the posterior avoids bias issuesAlgorithm outperforms Gibbs sampling for synthetic application to seismic data

Dehorning is performed on a high percentage of dairies in the United States. Concern for animal welfare has led to investigating pain mitigation during dehorning. The objective was to compare the effectiveness of bupivacaine liposome suspension, lidocaine, or lidocaine + meloxicam administered at dehorning. Fifty male Holstein calves, 10–14 weeks of age were enrolled and randomly assigned to 1 of 5 treatment groups: 1) bupivacaine liposome suspension block, oral placebo, cautery dehorn (BUP); 2) lidocaine block, oral placebo, cautery dehorn (LID); 3) lidocaine block, oral meloxicam, cautery dehorn (LID + MEL); 4) saline block, oral placebo, cautery dehorn (CON); and 5) saline block, oral placebo, sham dehorn (SHAM). Biomarkers were collected from 0 to 120 hours post-dehorning and included infrared thermography (IRT), mechanical nociceptive threshold (MNT), and pressure mat gait analysis. Biomarkers were statistically analyzed using repeat measures with the calf being the repeated measure. There were no significant treatment differences for IRT measures. A treatment effect was observed for the mean difference of the right horn bud minus a control point which were -1.21 kgF, -1.41 kgF, -1.56 kgF, -1.65 kgF, and -1.68 kgF for the SHAM, CON, BUP, LID + MEL, and LID groups, respectively (P = 0.004). The BUP group did not differ from CON (P = 0.78) or SHAM (P = 0.07). A treatment effect was observed for gait distance means which were 182.05 cm, 189.69 cm, 195.77 cm, 199.54 cm, and 200.59 cm for the SHAM, BUP, LID + MEL, LID and CON groups, respectively (P = 0.04). The CON group did not differ from BUP, LID, or LID + MEL (P > 0.05) but did differ from SHAM (P = 0.02). These data show that administration of bupivacaine liposome suspension at the time of dehorning was not different than lidocaine or lidocaine + meloxicam.

Administration of non-steroidal anti-inflammatory drugs, such as the widely available drug aspirin, or acetylsalicylic acid (ASA), may improve health and milk production in postpartum dairy cows. However, plasma pharmacokinetic (PK) data for salicylic acid (SA), the active metabolite of ASA, are unrepresentative of lactating dairy cows and current treatment regimens, and there are currently no published milk residue and minimal pharmacodynamic data available for ASA or SA in dairy cows. The objectives of this descriptive study were to (1) describe the pharmacokinetics of SA in the milk and plasma of postpartum dairy cows following oral ASA administration; (2) to estimate a milk withdrawal period for dairy cows treated with ASA; and (3) to determine the impact of ASA on plasma prostaglandin E2metabolite (PGEM) concentrations. Primiparous (n = 3) and multiparous (n = 7) postpartum Holstein dairy cows received 2 oral treatments with ASA at 200 mg/kg, 24 h apart. Plasma and milk SA concentrations from 0 h through 120 h after ASA administration were analyzed using ultra-performance liquid chromatography triple quadrupole mass spectrometry. Plasma PK analysis was performed using a non-compartmental approach using the free software, PKSolver, in Excel. An estimated milk withdrawal interval of 168 h was determined using the FDA Milk Discard App in R (RStudio, Boston, MA) using a 99thpercentile upper tolerance limit with 95% confidence. Plasma PGEM concentrations from 0 h to 24 h after ASA administration were determined in duplicate using ELISA and were reduced compared with baseline for up to 12 h after ASA administration. A mean reduction in PGEM of -49.3% was observed at 2 h. Results from this study suggest that the current milk withhold recommendation of 24 h for dairy cows administered ASA should be revised and that ASA administration may mitigate postpartum inflammation through reduction in prostaglandin production.

The ultimate goal of a scientific investigation is usually to find answers to specific, often low‐dimensional questions: what is the size of a subsurface body? Does a hypothesized subsurface feature exist? Existing information is reviewed, an experiment is designed and performed to acquire new data, and the most likely answer is estimated. Typically the answer is interpreted from geological and geophysical data or models, but is biased because only one particular forward function is considered, one inversion method is applied, and because human interpretation is a biased process. Interrogation theory provides a systematic way to answer specific questions by combining forward, design, inverse, and decision theories. The optimal answer is made more robust since it balances multiple possible forward models, inverse algorithms and model parametrizations, probabilistically. In a synthetic test, we evaluate the area of a low‐velocity anomaly by interrogating Bayesian tomographic results. By combining the effect of four inversion algorithms, the optimal answer is very close to the true answer, even on a coarsely gridded parametrization. In a field data test, we evaluate the volume of the East Irish Sea basins using probabilistic 3D shear wave speed depth inversion results. This example shows that interrogation theory provides a useful way to answer realistic questions about the Earth. A key revelation is that while the majority of computation may be spent solving inverse problems, much of the skill and effort involved in answering questions may be spent defining and calculating target function values in a clear and unbiased manner. This paper shows how to answer specific questions about the subsurface using probabilistic tomography. Usually tomographic methods are used to estimate images of the subsurface; the “best” images are then interpreted to answer questions of interest. This work shows that by setting up a formal target function that allows any image to be interpreted automatically, many samples of possible subsurface models can be translated into probabilistic answers to the questions, from which a least‐biased answer can be constructed. In the real‐data examples presented here the subsurface shape of a sedimentary basin is determined automatically, and a least‐biased estimate of its volume is constructed. This method is shown to give accurate answers about high resolution structures even given only low resolution tomographic images; this suggests that the probabilistic results compensate for the lack of resolution. We use interrogation theoryto answer specific questions about the subsurface using probabilistic tomography resultsIn a synthetic example, the method estimates the area of a low velocity anomaly accurately, even given coarsely gridded tomographic imagesWe apply the method to a real data set and evaluate the volume of the East Irish Sea sedimentary basins using 3D depth inversion results We use interrogation theoryto answer specific questions about the subsurface using probabilistic tomography results In a synthetic example, the method estimates the area of a low velocity anomaly accurately, even given coarsely gridded tomographic images We apply the method to a real data set and evaluate the volume of the East Irish Sea sedimentary basins using 3D depth inversion results

Hot-iron branding uses thermal injury to permanently identify cattle causing painful tissue damage. The primary objective was to examine the physiological and behavioral effects of oral meloxicam (MEL), compared to a control, administered at the time of hot-iron branding in Angus and Hereford steers and heifers. The secondary objectives were to investigate breed and sex effects on pain biomarkers. A total of 70 yearlings, consisting of 35 heifers and 35 steers (Angus, Hereford, or Angus × Hereford), were enrolled in the study. Animals were blocked by sex, randomized across weight, and assigned to receive MEL (1 mg/kg) or a placebo (CON). Biomarkers were assessed for 48 h after branding and included infrared thermography (IRT), mechanical nociceptive threshold (MNT), accelerometry and a visual analog scale (VAS), and serum cortisol and prostaglandin E2metabolites (PGEM). Wound healing was assessed for 12 wk. Hair samples to quantify cortisol levels were taken prior to and 30 d post-branding. Responses were analyzed using repeated measures with calf nested in treatment as a random effect, and treatment, time, treatment by time interaction, breed, and sex as fixed effects. There was a treatment by time interaction for PGEM (P< 0.01) with MEL having lower values than CON at 6, 24, and 48 h (MEL: 18.34 ± 3.52, 19.61 ± 3.48, and 22.24 ± 3.48 pg/mL, respectively; CON: 32.57 ± 3.58, 37.00 ± 3.52, and 33.07 ± 3.48 pg/mL; P< 0.01). MEL showed less of a difference in maximum IRT values between the branded (2.27 ± 0.29 °C) and control site (3.15 ± 0.29 °C; P< 0.01). MEL took fewer lying bouts at 0–12 h (4.91 bouts ± 0.56) compared with CON (6.87 bouts ± 0.55; P< 0.01). Compared with Hereford calves, Angus calves exhibited greater serum but lower hair cortisol, greater PGEM, more lying bouts, and less healed wound scores at 3, 4, and 5 wk. Compared with heifers, steers exhibited lower PGEM, lower branding site and ocular IRT, higher MNT, and lower plasma meloxicam levels. Steers spent more time lying, took more lying bouts and had greater VAS pain, and more healed wound scores at 5 wk than heifers. Meloxicam administration at branding reduced branding and control site temperature differences and reduced lying bouts for the first 12 h. Breed and sex effects were observed across many biomarkers. Changes from baseline values for IRT, MNT, lying time, step count, VAS pain, and wound scoring all support that branding cattle is painful.Hot-iron branding uses thermal injury to permanently identify cattle causing painful tissue damage. The primary objective was to examine the effects of oral meloxicam (MEL), compared with a control, administered at the time of hot-iron branding in Angus and Hereford steers and heifers. The secondary objectives were to investigate breed and sex effects on pain biomarkers. A total of 70 yearlings, consisting of 35 heifers and 35 steers (Angus, Hereford, or Angus × Hereford), were enrolled. Animals were assigned to receive MEL or a placebo. Changes from baseline values for infrared thermography (IRT), mechanical nociceptive threshold, lying time, step count, visual analog scale score, and wound scoring all support that hot-iron branding cattle is painful and investigation into analgesic strategies is needed. MEL administration reduced IRT differences from the branding and control site and reduced lying bouts. Breed and sex effects were observed across a wide range of biomarkers and should be considered in future pain studies. The practicality of administering a nonsteroidal anti-inflammatory drug once at the time of branding is attractive. However, a multimodal approach using a combination of analgesics or longer acting analgesic option warrants further investigation to alleviate pain and discomfort caused by hot-iron branding.Our results supported that hot-iron branding cattle is painful and oral meloxicam administration reduced infrared thermography differences from the branding and control site and reduced lying bouts. Breed and sex effects were observed across a wide range of biomarkers and should be considered in future pain studies.

Large-scale Internet applications, such as content distribution networks, are deployed across multiple datacenters and consume massive amounts of electricity. To provide uniformly low access latencies, these datacenters are geographically distributed and the deployment size at each location reflects the regional demand for the application. Consequently, an application's environmental impact can vary significantly depending on the geographical distribution of end-users, as electricity cost and carbon footprint per watt is location specific. In this paper, we describe FORTE: Flow Optimization based framework for request-Routing and Traffic Engineering. FORTE dynamically controls the fraction of user traffic directed to each datacenter in response to changes in both request workload and carbon footprint. It allows an operator to navigate the three-way tradeoff between access latency, carbon footprint, and electricity costs and to determine an optimal datacenter upgrade plan in response to increases in traffic load. We use FORTE to show that carbon taxes or credits are impractical in incentivizing carbon output reduction by providers of large-scale Internet applications. However, they can reduce carbon emissions by 10% without increasing the mean latency nor the electricity bill.

ABSTRACTGeographic information systems (GIS) and geospatial technology (GT) can help hospitals improve plans for postdisaster surge by assessing numbers of potential patients in a catchment area and providing estimates of special needs populations, such as pediatrics. In this study, census-derived variables are computed for blockgroups within a 3-mile radius from Children's Hospital Los Angeles (CHLA) and from Los Angeles County–University of Southern California (LAC–USC) Medical Center. Landslide and liquefaction zones are overlaid on US Census Bureau blockgroups. Units that intersect with the hazard zones are selected for computation of pediatric surge potential in case of an earthquake. In addition, cartographic visualization and cluster analysis are performed on the entire 3-mile study area to identify hot spots of socially vulnerable populations. The results suggest the need for locally specified vulnerability models for pediatric populations. GIS and GT have untapped potential to contribute local specificity to planning for surge potential after a disaster. Although this case focuses on an earthquake hazard, the methodology is appropriate for an all-hazards approach. With the advent of Google Earth, GIS output can now be easily shared with medical personnel for broader application and improvement in planning.(Disaster Med Public Health Preparedness. 2012;6:163–169)

OpenFlow is a great concept, but its original design imposes excessive overheads. It can simplify network and traffic management in enterprise and data center environments, because it enables flow-level control over Ethernet switching and provides global visibility of the flows in the network. However, such fine-grained control and visibility comes with costs: the switch-implementation costs of involving the switch's control-plane too often and the distributed-system costs of involving the OpenFlow controller too frequently, both on flow setups and especially for statistics-gathering. In this paper, we analyze these overheads, and show that OpenFlow's current design cannot meet the needs of high-performance networks. We design and evaluate DevoFlow, a modification of the OpenFlow model which gently breaks the coupling between control and global visibility, in a way that maintains a useful amount of visibility without imposing unnecessary costs. We evaluate DevoFlow through simulations, and find that it can load-balance data center traffic as well as fine-grained solutions, without as much overhead: DevoFlow uses 10--53 times fewer flow table entries at an average switch, and uses 10--42 times fewer control messages.

This paper considers the interrelationship between residential occupancy status, blight, and crime. An analytical frame is provided for a fine-scale analysis that is sufficiently flexible to capture both spatial and temporal dynamism in field-collected data. Unlike other works linking crime to evidence of disorder within neighborhoods, this paper considers this relationship in terms of neighborhoods affected by an external event (natural disaster), which results in more dynamic spatial and temporal patterns as the neighborhood is in a state of flux. As a result, new means of data collection and analysis are required, as any fine-scale relationship is longitudinal as well as cross sectional. The focus here is on the interrelationship of post-disaster residential occupancy, building conditions, and crime incidence for the Holy Cross neighborhood of New Orleans as it recovers from Hurricane Katrina. Results suggest that crime is inversely related to the amount of activity on a recovering street.

The devastation caused by Hurricane Katrina is still being felt by many neighborhoods of New Orleans and along the Gulf Coast. As these communities struggle to recover, academia has been forced to acknowledge that there is little known or theorized about the spatial processes of recovery, especially at the fine scale. As a result this paper will investigate how post-disaster landscape characteristics can be extracted from spatial video data for neighborhoods of New Orleans. These will be turned into a statistical surface using analytical approaches more commonly applied in spatial epidemiology. Spatial patterns of abandonment and recovery will be identified that can be used as a basis for a next round of causative investigation. The paper finds that by using the spatial overlap of four different analyses involving two different data input locations and two filter sizes, the Holy Cross neighborhood of New Orleans does indeed reveal areas with higher rates of recovery, and continuing abandonment. However, even within these areas, spatial heterogeneity can be found. This paper uses Google Street View to mirror spatial video data collected in participatory collaborations with New Orleans community groups so that readers can replicate the methods presented here for other neighborhoods of New Orleans.

Ground‐penetrating radar (GPR) is widely used on polythermal glaciers to image bed topography and detect internal scatter due to water inclusions in temperate ice. The glaciological importance of this is twofold: bed topography is a primary component for modeling the long‐term evolution of glaciers and ice sheets, and the presence of temperate ice and associated englacial water significantly reduces overall ice viscosity. Englacial water has a direct influence on radar velocity, which can result in incorrect observations of bed topography due to errors in depth conversion. Assessment of radar velocities often requires multi‐offset surveys, yet these are logistically challenging and time consuming to acquire, hence techniques to extract velocity from common‐offset data are required. We calculate englacial radar velocity from common offset GPR data collected on Von Postbreen, a polythermal glacier in Svalbard. We first separate and enhance the diffracted wavefield by systematically assessing data coherence. We then use the focusing metric of negative entropy to deduce a migration velocity field and produce a velocity model which varies spatially across the glacier. We show that this velocity field successfully differentiates between areas of cold and temperate ice and can detect lateral variations in radar velocity close to the glacier bed. This velocity field results in consistently lower ice depths relative to those derived from a commonly assumed constant velocity, with an average difference of 4.9 ± 2.5% of local ice depth. This indicates that diffraction focusing and velocity estimation are crucial in retrieving correct bed topography in the presence of temperate ice. The internal structure and thickness of glaciers can often be mapped using a technique called ground‐penetrating radar (GPR). To do this, we emit pulses of radio waves into the ice from the surface, and record the returning energy reflected back to the surface. Reflections are a result of contrasts in the material properties within the ice or at the ice‐bed interface. Sometimes, glacier ice can have quantities of water stored within pores between the ice crystals; this complicates the mapping process as it scatters the radio signal, and distorts the image of the bed below by changing the speed at which radio waves travel through ice. In this paper, we apply a new technique to use this scatter to estimate the changes in radio wave velocity. We use this newly estimated radio wave velocity to improve our understanding of the shape of the bed, and to improve our understanding of water distribution within the glacier. We use diffractions in ground‐penetrating radar data to retrieve the radar velocity field of a polythermal glacierThe retrieved radar velocity field successfully differentiates between cold and temperate iceWe use the retrieved velocity field to improve bed topography relative to a constant velocity field We use diffractions in ground‐penetrating radar data to retrieve the radar velocity field of a polythermal glacier The retrieved radar velocity field successfully differentiates between cold and temperate ice We use the retrieved velocity field to improve bed topography relative to a constant velocity field

Pleuritic chest pain from bacterial pneumonia is often reported in human medicine. However, studies investigating pain associated with bovine respiratory disease (BRD) are lacking. The objectives of this study were to assess if bacterial pneumonia elicits a pain response in calves with experimentally induced BRD and to determine the analgesic effects of transdermally administered flunixin. A total of 26 calves, 6–7 mo of age, with no history of BRD were enrolled into one of three treatment groups: 1) experimentally induced BRD + transdermal flunixin at 3.3 mg/kg twice, 24 h apart (BRD + FTD); 2) experimentally induced BRD + placebo (BRD + PLBO); and 3) sham induction + placebo (CNTL + PLBO). Calves induced with BRD were inoculated with Mannheimia haemolyticavia bronchoalveolar lavage. Outcomes were collected from −48 to 192 h post-treatment and included serum cortisol, infrared thermography, mechanical nociceptive threshold, substance P, kinematic gait analysis, visual analog scale (VAS), clinical illness score, computerized lung score, average activity and rumination level, prostaglandin E2metabolite, plasma serum amyloid A, and rectal temperature. Outcomes were evaluated using either a generalized logistic mixed model for categorical variables or a generalized linear mixed model for continuous variables. Right front force differed by treatment (P= 0.01). The BRD + PLBO had lower mean force applied to the right front limb (85.5 kg) compared with BRD + FTD (96.5 kg; P< 0.01). Average VAS differed by a treatment by time interaction (P= 0.01). The VAS scores differed for BRD + PLBO at −48 (3.49 mm) compared with 168 and 192 h (13.49 and 13.64 mm, respectively) (P< 0.01). Activity for BRD + PLBO was higher at −48 h (27 min/h) compared with 48, 72, 120, and 168 h (≤ 22.24 min/h; P< 0.01). Activity differed by a treatment by time interaction (P= 0.01). Activity for BRD + FTD was higher at −48 and 0 h (28.2 and 28.2 min/h, respectively) compared to 48, 72, 96, and 168 h (≤23.7 min/h; P< 0.01). Results show a combination of reduced activity levels, decreased force on the right front limb, and increased VAS pain scores all support that bacterial pneumonia in cattle is painful. Differences in right front force indicate that flunixin transdermal may attenuate certain pain biomarkers in cattle with BRD. These findings suggest that BRD is painful and analgesic drugs may improve the humane aspects of care for cattle with BRD.

Castration is a routine procedure performed on beef and dairy operations in the United States. All methods of castration cause behavioral, physiologic, and neuroendocrine changes associated with pain. The American Veterinary Medical Association and the American Association of Bovine Practitioners recommend that anesthesia and analgesia be administered during castration. The objective of this study was to evaluate the effectiveness of bupivacaine liposome suspension, a novel, long-acting, local anesthetic formulation administered as a nerve block at castration. The authors chose to investigate this novel formulation as an alternative to the current industry standards using lidocaine nerve blocks alone or in combination with meloxicam. Thirty male Holstein calves, 16 to 20 wk of age, were enrolled and randomly assigned to one of the four treatment groups prior to surgical castration: 1) bupivacaine liposome suspension block + oral placebo (BUP), 2) lidocaine block + oral placebo (LID), 3) lidocaine block + oral meloxicam (1 mg/kg) (LID + MEL), and 4) saline block + oral placebo (CON). Biomarkers were collected at −24 h and from 0 to 120 h post-castration and included infrared thermography, pressure mat gait analysis, chute defense and behavior scoring (pain and activity), and blood sampling for serum cortisol and prostaglandin E2metabolites (PGEMs). Responses were analyzed using repeated measures, with calf nested in treatment as a random effect, and treatment, time, and their interaction designated as fixed effects. The results from pressure mat gait analysis show that the CON had a shorter front limb stance time from baseline (−8.73%; 95% confidence interval [CI]: −24.84% to 7.37%) compared with BUP and LID + MEL (>5.70%; 95% CI: −22.91% to 23.79%) (P< 0.03). The CON tended to have an increase in front limb force from baseline (6.31%; 95% CI: −1.79% to 14.41%) compared with BUP, LID, and LID + MEL (<−5.06%; 95% CI: −14.22% to 0.95%) (P< 0.04). The CON displayed higher counts of hunched standing (2.00; 95% CI: 1.68 to 2.32) compared with LID + MEL (1.43; 95% CI: 1.13 to 1.72) (P= 0.05). The CON had higher cortisol concentrations at 24 h (7.70 ng/mL; 95% CI: 1.52 to 13.87 ng/mL) relative to BUP (3.11 ng/mL; 95% CI: −2.56 to 8.79 ng/mL) (P= 0.002). At 4 and 24 h, LID + MEL had lower PGEM concentrations from baseline (−32.42% and −47.84%; 95% CI: −78.45% to −1.80%) compared with CON (27.86% and 47.63%; 95% CI: 7.49% to 82.98%) (P< 0.02). The administration of bupivacaine liposome suspension as a local anesthetic block at the time of castration was as effective at controlling pain as a multimodal approach of lidocaine and meloxicam.Castration is a routine procedure performed on beef and dairy operations in the United States. All methods of castration cause pain. The American Veterinary Medical Association and the American Association of Bovine Practitioners recommend that anesthesia and analgesia be administered during castration. The objective of this study was to evaluate the effectiveness of bupivacaine liposome suspension, a novel, long-acting, local anesthetic formulation administered as a nerve block at castration, as an alternative to current industry standards using lidocaine nerve blocks alone or in combination with meloxicam. Evidence provided in the current study demonstrates that pain from surgical castration can last up to 120 h post-castration, indicated by changes in ocular temperature, gait analysis, and prostaglandin metabolite concentrations. These data show that the administration of bupivacaine liposome suspension as a local anesthetic block at the time of castration was as effective at controlling pain as a multimodal approach of lidocaine and meloxicam. A single injection that alleviates both perioperative and postoperative pain would be an attractive option for livestock producers to alleviate pain at the time of castration. Further research is needed to discover effective ways of managing pain for extended durations following painful husbandry procedures.These data show that the administration of bupivacaine liposome suspension as a local anesthetic block at the time of castration was as effective at controlling pain as a multimodal approach of lidocaine and meloxicam. A single injection that alleviates both perioperative and postoperative pain would be an attractive option for livestock producers to alleviate pain at the time of castration.

The article examines the effectiveness of the under-tree travelling irrigator. It describes the tests conducted by the investigators to gauge the performance of this type of orchard irrigation system. According to the authors, this irrigation system is not so effective, thus, they suggest ways to improve the weaknesses of this type of irrigation.

This article evaluates the degree to which reverse address-matching (i.e., geospatial techniques that include scanning, geo-rectifying, and digitizing) would allow to recover personal data attached to the location of somebody’s residence from a map. Preliminary research results demonstrate that only after a few hours of instruction, novices to geospatial technology possess sufficient knowledge to perform successful reverse address-matching. A second finding is that the probability of somebody’s confidentiality being revealed through reverse address-matching varies across space and changes from neighborhood to neighborhood.

During Hurricane Katrina a group of faculty, staff, and students at Louisiana State University voluntarily helped create, manage, and staff Geographic Information System (GIS) efforts in the Louisiana Emergency Operations Center (EOC). GIS is an integral component to decision support in all phases of emergency operations (Curtis et al 2006; Eichenbaum 2002; Gunes and Kovel 2000; Johnson and Uba 1997; Kaiser et al 2003; Kehrlein and Shreve 1995; Maniruzzaman et al 2001; Morrow 1999; Newsom and Matrani 1993; Pine 1997; Thomas et al 2002). However, for the Katrina response, no Louisiana state employees were assigned to the GIS desk at the EOC. This failure to have an established support system for all other agencies providing response could have been a devastating fault without the volunteer support provided by LSU. Most agencies looked for us in the EOC and then relied upon us throughout the operation. This paper documents the way our group utilized our academic backgrounds to expand and improve the geospatial decision support in the EOC.

Constraining geophysical models with observed data usually involves solving nonlinear and nonunique inverse problems. Neural mixture density networks (MDNs) provide an efficient way to estimate Bayesian posterior marginal probability density functions (pdf's) that represent the nonunique solution. However, it is difficult to infer correlations between parameters using MDNs, and in turn to draw samples from the posterior pdf. We introduce an alternative to resolve these issues: invertible neural networks (INNs). These are simultaneously trained to represent uncertain forward functions and to solve Bayesian inverse problems. In its usual form, the method does not account for uncertainty caused by data noise and becomes less effective in high dimensionality. To overcome these issues, in this study, we include data uncertainties as additional model parameters, and train the network by maximizing the likelihood of the data used for training. We apply the method to two types of imaging problems: One‐dimensional surface wave dispersion inversion and two‐dimensional travel time tomography, and we compare the results to those obtained using Monte Carlo and MDNs. Results show that INNs provide comparable posterior pdfs to those obtained using Monte Carlo, including correlations between parameters, and provide more accurate marginal distributions than MDNs. After training, INNs estimate posterior pdfs in seconds on a typical desktop computer. Hence they can be used to provide efficient solutions for repeated inverse problems using different data sets. Also even accounting for training time, our results show that INNs can be more efficient than Monte Carlo methods for solving inverse problems only once. We introduce invertible neural networks that solve Bayesian geophysical inverse problems probabilisticallyWe use the networks to solve two types of problems: surface wave dispersion inversion and travel time tomographyFor repeated (or even individual) inverse problems the method provides efficient and accurate approximations to results from Monte Carlo sampling We introduce invertible neural networks that solve Bayesian geophysical inverse problems probabilistically We use the networks to solve two types of problems: surface wave dispersion inversion and travel time tomography For repeated (or even individual) inverse problems the method provides efficient and accurate approximations to results from Monte Carlo sampling

Four families, each with two individuals affectecd by Rett Syndrome (RS), were analysed using restriction fragment lenght polymorphisms and microsatellite markers from the X chromosome. In two of the families, X-linked dominant inheritance of the RS defect from a germinally mosaic mother could be assumed. Therefore, maternal X chromosome markers showing discordant inheritance were used to exclude regions of the X chromosome as locations of the RS gene. Much of the short arm could be excluded, including regions containing three candidate genes, OTC, synapsin 1 and synaptophysin. Although most of the long arm was inherited in common it was possible to exclude a centromeric region. Inheritance of X chromosome markers is also presented for two families with affected aunt-niece pairs, one of which has not been previously studied at the DNA level.

Holt-Oram syndrome is a developmental disorder affecting the heart and upper limb, the gene for which was mapped to chromosome 12 two years ago. We have now identified a gene for this disorder (HOS1). The gene (TBX5) is a member of the Brachyury (T) family corresponding to the mouse TbxS gene. We have identified six mutations, three in HOS families and three in sporadic HOS cases. Each of the mutations introduces a premature stop codon in the TBXS gene product. Tissue in situ hybridization studies on human embryos from days 26 to 52 of gestation reveal expression of TBXS in heart and limb, consistent with a role in human embryonic development.

During cardiopulmonary bypass (CPB) an adequate reservoir volume is maintained by the addition of crystalloid, colloid or packed cells to the reservoir. This volume contributes to the overall perioperative positive fluid balance. We studied the effect of the preoperative addition of either 75 g albumin, or 50 g mannitol followed by 50 g at commencement of rewarming or both of the above to a bypass circuit prime of lactated Ringer's solution (LR) on intraoperative fluid balance, postoperative indices of oxygenation and time to extubation. The study was a prospective, randomized, single-blinded controlled trial of 103 patients undergoing cardiac surgery requiring CPB. There was a large and highly significant reduction in volume of fluid added to the reservoir during CPB (2137 ± 1499 ml versus 144 ± 230 ml), the fluid balance during bypass, including prime volume (3236 ± 650 ml versus 5876 ± 1465 ml), and perioperative fluid balance (4470 ± 936 ml versus 7023 ± 1760 ml) in the group receiving both mannitol and albumin in the pump prime compared with the group receiving only lactated Ringer's solution. There were no differences between the groups with respect to both measured indices of oxygenation measured on return to ICU (alveolar-arterial oxygen tension difference (DA-aO2) or arterial oxygen tension to inspired oxygen fraction ratio (PaO2/FiO2), or time from ICU admission to extubation.