Separation of river network–scale nitrogen removal among the main channel and two transient storage compartments

Transient storage (TS) zones are important areas of dissolved inorganic nitrogen (DIN) processing in rivers. We assessed sensitivities regarding the relative impact that the main channel (MC), surface TS (STS), and hyporheic TS (HTS) have on network denitrification using a model applied to the Ipswich River in Massachusetts, United States. STS and HTS connectivity and size were parameterized using the results of in situ solute tracer studies in first‐ through fifth‐order reaches. DIN removal was simulated in all compartments for every river grid cell using reactivity derived from Lotic Intersite Nitrogen Experiment (LINX2) studies, hydraulic characteristics, and simulated discharge. Model results suggest that although MC‐to‐STS connectivity is greater than MC‐to‐HTS connectivity at the reach scale, at basin scales, there is a high probability of water entering the HTS at some point along its flow path through the river network. Assuming our best empirical estimates of hydraulic parameters and reactivity, the MC, HTS, and STS removed approximately 38%, 21%, and 14% of total DIN inputs during a typical base flow period, respectively. There is considerable uncertainty in many of the parameters, particularly the estimates of reaction rates in the different compartments. Using sensitivity analyses, we found that the size of TS is more important for DIN removal processes than its connectivity with the MC when reactivity is low to moderate, whereas TS connectivity is more important when reaction rates are rapid. Our work suggests a network perspective is needed to understand how connectivity, residence times, and reactivity interact to influence DIN processing in hierarchical river systems

Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili

We consider hate speech detection through keyword spotting on radio broadcasts. One approach is to build an automatic speech recognition (ASR) system for the target low-resource language. We compare this to using acoustic word embedding (AWE) models that map speech segments to a space where matching words have similar vectors. We specifically use a multilingual AWE model trained on labelled data from well-resourced languages to spot keywords in data in the unseen target language. In contrast to ASR, the AWE approach only requires a few keyword exemplars. In controlled experiments on Wolof and Swahili where training and test data are from the same domain, an ASR model trained on just five minutes of data outperforms the AWE approach. But in an in-the-wild test on Swahili radio broadcasts with actual hate speech keywords, the AWE model (using one minute of template data) is more robust, giving similar performance to an ASR system trained on 30 hours of labelled data.Comment: Accepted to Interspeech 202

Resurrecting immortal‐time bias in the study of readmissions

ObjectiveTo compare readmission rates as measured by the Centers for Medicare and Medicaid Services and the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) methods.Data Sources20 percent sample of national Medicare data for patients undergoing cystectomy, colectomy, abdominal aortic aneurysm (AAA) repair, and total knee arthroplasty (TKA) between 2010 and 2014.Study DesignRetrospective cohort study comparing 30‐day readmission rates.Data Collection/Extraction MethodsPatients undergoing cystectomy, colectomy, abdominal aortic aneurysm repair, and total knee arthroplasty between 2010 and 2014 were identified.Principal FindingsCystectomy had the highest and total knee arthroplasty had the lowest readmission rate. The NSQIP measure reported significantly lower rates for all procedures compared to the CMS measure, which reflects an immortal‐time bias.ConclusionsWe found significantly different readmission rates across all surgical procedures when comparing CMS and NSQIP measures. Longer length of stay exacerbated these differences. Uniform outcome measures are needed to eliminate ambiguity and synergize research and policy efforts.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154628/1/hesr13252-sup-0001-Authormatrix.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154628/2/hesr13252.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154628/3/hesr13252_am.pd

Submesoscale dispersion in the vicinity of the Deepwater Horizon spill

Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity field at the submesoscales (100 meters to tens of kilometers, hours to days) remain unresolved due to a lack of synoptic measurements at these scales. \textcolor{black} {Using high-frequency position data provided by the near-simultaneous release of hundreds of accurately tracked surface drifters, we study the structure of submesoscale surface velocity fluctuations in the Northern Gulf Mexico. Observed two-point statistics confirm the accuracy of classic turbulence scaling laws at 200m$-$50km scales and clearly indicate that dispersion at the submesoscales is \textit{local}, driven predominantly by energetic submesoscale fluctuations.} The results demonstrate the feasibility and utility of deploying large clusters of drifting instruments to provide synoptic observations of spatial variability of the ocean surface velocity field. Our findings allow quantification of the submesoscale-driven dispersion missing in current operational circulation models and satellite altimeter-derived velocity fields.Comment: 9 pages, 6 figure

Lattice models and Landau theory for type II incommensurate crystals

Ground state properties and phonon dispersion curves of a classical linear chain model describing a crystal with an incommensurate phase are studied. This model is the DIFFOUR (discrete frustrated phi4) model with an extra fourth-order term added to it. The incommensurability in these models may arise if there is frustration between nearest-neighbor and next-nearest-neighbor interactions. We discuss the effect of the additional term on the phonon branches and phase diagram of the DIFFOUR model. We find some features not present in the DIFFOUR model such as the renormalization of the nearest-neighbor coupling. Furthermore the ratio between the slopes of the soft phonon mode in the ferroelectric and paraelectric phase can take on values different from -2. Temperature dependences of the parameters in the model are different above and below the paraelectric transition, in contrast with the assumptions made in Landau theory. In the continuum limit this model reduces to the Landau free energy expansion for type II incommensurate crystals and it can be seen as the lowest-order generalization of the simplest Lifshitz-point model. Part of the numerical calculations have been done by an adaption of the Effective Potential Method, orginally used for models with nearest-neighbor interaction, to models with also next-nearest-neighbor interactions.Comment: 33 pages, 7 figures, RevTex, submitted to Phys. Rev.

The crime drop and the security hypothesis

Major crime drops were experienced in the United States and most other industrialised countries for a decade from the early to mid-1990s. Yet there is little agreement over explanation or lessons for policy. Here it is proposed that change in the quantity and quality of security was a key driver of the crime drop. From evidence relating to vehicle theft in two countries it is concluded that electronic immobilisers and central locking were particularly effective. It is suggested that reduced car theft may have induced drops in other crime including violence. From this platform a broader security hypothesis, linked to routine activity and opportunity theory, is outlined

The Prevalence and Clinical Implications of Comorbid Back Pain in Shoulder Instability: A Multicenter Orthopaedic Outcomes Network (MOON) Shoulder Instability Cohort Study.

Background:Understanding predictors of pain is critical, as recent literature shows that comorbid back pain is an independent risk factor for worse functional and patient-reported outcomes (PROs) as well as increased opioid dependence after total joint arthroplasty. Purpose/Hypothesis:The purpose of this study was to evaluate whether comorbid back pain would be predictive of pain or self-reported instability symptoms at the time of stabilization surgery. We hypothesized that comorbid back pain will correlate with increased pain at the time of surgery as well as with worse scores on shoulder-related PRO measures. Study Design:Cross-sectional study; Level of evidence, 3. Methods:As part of the Multicenter Orthopaedic Outcomes Network (MOON) Shoulder Instability cohort, patients consented to participate in pre- and intraoperative data collection. Demographic characteristics, injury history, preoperative PRO scores, and radiologic and intraoperative findings were recorded for patients undergoing surgical shoulder stabilization. Patients were also asked, whether they had any back pain. Results:The study cohort consisted of 1001 patients (81% male; mean age, 24.1 years). Patients with comorbid back pain (158 patients; 15.8%) were significantly older (28.1 vs 23.4 years; P < .001) and were more likely to be female (25.3% vs 17.4%; P = .02) but did not differ in terms of either preoperative imaging or intraoperative findings. Patients with self-reported back pain had significantly worse preoperative pain and shoulder-related PRO scores (American Shoulder and Elbow Surgeons score, Western Ontario Shoulder Instability Index) (P < .001), more frequent depression (22.2% vs 8.3%; P < .001), poorer mental health status (worse scores for the RAND 36-Item Health Survey Mental Component Score, Iowa Quick Screen, and Personality Assessment Screener) (P < .01), and worse preoperative expectations (P < .01). Conclusion:Despite having similar physical findings, patients with comorbid back pain had more severe preoperative pain and self-reported symptoms of instability as well as more frequent depression and lower mental health scores. The combination of disproportionate shoulder pain, comorbid back pain and mental health conditions, and inferior preoperative expectations may affect not only the patient's preoperative state but also postoperative pain control and/or postoperative outcomes

Treatment effect of switching from intravenous to subcutaneous C1-inhibitor for prevention of hereditary angioedema attacks: COMPACT subgroup findings

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Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation