Interacting with Law Enforcement Audiences in Livestock Management

An Ohio voter initiative was passed to create the Ohio Livestock Care Standards Board. The board established livestock animal care regulations. Eight workshops were held for humane officers and others who deal with livestock animal care complaints. A total of 127 participants were trained on beef, dairy, swine, sheep/goat, equine and poultry husbandry; body condition scoring; farm animal behavior and handling; and biosecurity. The OPOTA has authority over training the County Humane Agents. OPOTA put together a team, including instructors from Animal Agriculture 101, to edit this section of their training on how to determine animal abuse related to livestock

Influence of a Maternal Dietary Yeast Supplement on Immunoglobulin Concentrations in Foals from Birth to Four Months of Age

Agriculture/Environmental Science: 2nd Place (The Ohio State University Denman Undergraduate Research Forum)Previous studies in multiple species have shown that maternal diet can affect immunoglobulin concentrations in their resulting offspring. To our knowledge, the effect of maternal dietary yeast supplementation on immunoglobulin levels in foals has not been studied. In this study eight Quarter Horse mares (14.5 ± 7.5 yr) were randomly assigned to one of two groups: Yeast or Control. All mares received a control diet of 0.5% BW of a 16% CP pelleted concentrate with water and mixed grass hay ad libitum. Mares in the yeast treatment group also received 1g/45.4 kg of BW/d of a live culture of Saccharomyces cerevisiae from 250 d of gestation to 90 d post-foaling. All mares were vaccinated at d 300 of gestation against Eastern and Western equine encephalomyelitis, equine rhinopneumonitis (EHV-1 and EHV-4), equine influenza (type A2), tetanus and West Nile virus. Blood samples were collected from the foals via jugular venipuncture immediately after parturition (d 0), at 12 and 24 hr and 30, 60, 90, and 120 d post-foaling. Sera samples were analyzed for total IgG including IgGa, IgGb, and IgG(T), as well as IgA, IgM, and IgE concentrations using commercial ELISA kits. Data were analyzed using PROC MIXED of SAS and a p-value of ≤ 0.05 was considered statistically significant. Supplementing the maternal diet with live yeast did not influence foal IgGa, IgGb, IgA, IgM, or IgE concentrations. However, IgG(T) concentrations were significantly higher (P = 0.0063) on d 60 post-foaling in foals born from mares fed the yeast supplement compared to controls. Overall, maternal dietary yeast supplementation during late gestation and early lactation did not influence immunoglobulin concentrations in their foals.Academic Major: Animal Science

Characterization of the Degradation and Conversion of Bone Cement and Borate Bioactive Glass Composites

Periprosthetic infections are a devastating complication of orthopedic procedures, costing time and money as well as the quality of life of affected patients. 13-93B3 is a boron-based bioactive glass that degrades and converts into hydroxyapatite when immersed in a physiological fluid. Its ability to break down and dissolve quickly would be useful for drug delivery when combined with bone cement because this glass can create passages in the cement that would increase the elution of incorporated antibiotics. The conversion of this bioactive glass into calcium phosphate products could also attract surrounding bone growth, further integrating implants with tissue and removing space on the cement surfaces where biofilms can form. While bioactive glasses have previously been added to bone cement, the incorporation of 13-93B3 into commercial bone cement has not yet been reported in literature. The focus of this study was to characterize composites of these materials by measuring its degradation rate and the identity of its resulting precipitate while monitoring for adverse reductions of mechanical strength. Particles of 13-93B3 with diameters of 5 μm, 33 μm, and 100 μm were mixed into a PMMA-based commercial bone cement, DePuy SmartSet MV, to create composites with 20%, 30%, and 40% glass loadings. The composites were formed into pellets and paired with bone cement control groups. These samples were soaked in phosphate-buffered saline (PBS). The compressive strength, Young’s modulus, water uptake, and weight loss of the pellets over time were recorded. The pH and boron concentrations of the solutions were measured at various soak durations. Results showed that smaller glass particles degraded faster in composites than larger particles, and that a higher amount of glass incorporation increased the amount of degradation that occurred. Composites with smaller glass diameters had higher compressive strengths than composites with larger glass particles, though the compressive strengths of all composites were found to be consistently above ASTM F451 and ISO 5833 standards. The conversion of 13-93B3 in the composites was studied using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), Fourier transform infrared spectroscopy – attenuated total reflection (FTIR-ATR), and micro-Raman spectroscopy. The solid precipitate that accumulated on the surfaces was determined to be hydroxyapatite incorporated with magnesium ions from the dissolved glass. The presence of this magnesium in the hydroxyapatite layer could improve the adhesion of the bone cement to living bone. Results from these tests suggest that composites made of 13-93B3 and bone cement may have a promising future in helping to prevent periprosthetic infections and would benefit from further investigation

When Does Contrastive Visual Representation Learning Work?

Recent self-supervised representation learning techniques have largely closed the gap between supervised and unsupervised learning on ImageNet classification. While the particulars of pretraining on ImageNet are now relatively well understood, the field still lacks widely accepted best practices for replicating this success on other datasets. As a first step in this direction, we study contrastive self-supervised learning on four diverse large-scale datasets. By looking through the lenses of data quantity, data domain, data quality, and task granularity, we provide new insights into the necessary conditions for successful self-supervised learning. Our key findings include observations such as: (i) the benefit of additional pretraining data beyond 500k images is modest, (ii) adding pretraining images from another domain does not lead to more general representations, (iii) corrupted pretraining images have a disparate impact on supervised and self-supervised pretraining, and (iv) contrastive learning lags far behind supervised learning on fine-grained visual classification tasks.Comment: CVPR 202

Effects of Par1a Deletion on Tubulointerstitial Fibrosis in Folic Acid Mouse Models of Renal Injury

Chronic Kidney Disease (CKD) affects 1 out of 7 adults in the United States and causes significant morbidity and mortality. Development of tubulointerstitial fibrosis, and the accompanying loss of functional tubular cells, leads to CKD progression. The Notch signaling pathway is required for renal development, however, sustained Notch activation in adult mice induces tubulointerstitial fibrosis. Dual deletion of Par1a and Par1b, serine threonine kinases, in developing mouse kidneys impaired Notch activation and resulted in the formation of abnormal glomeruli and proximal tubules. Deletion of either Par1a or 1b does not affect kidney development.We hypothesize that Par1a or 1b deletion in mice would protect against folic acid (FA) induced tubulointerstitial fibrosis. FA models of renal fibrosis were induced in Par1a WT and Par1a KO mice with intraperitoneal injections of 250 mg/kg FA dissolved in 300 nM NaHCO3. Mice were examined 7 days after injection—the time of earliest fibrosis and peak Notch expression. Sirius red collagen staining was used to quantify the severity of fibrosis. Immunohistochemical staining for Notch signaling components and Par1a were performed. It was observed that Par1a expression was increased after FA injection. Par1a colocalized in tubules with increased Jag1 expression. Sirius red staining demonstrated less fibrosis in Par1a KO vs. WT mice. Together, our results suggest Par1a deletion may be protective against renal fibrosis. Par1-Notch interactions may be mediated by effects on Jag1. Par1-Notch signaling could be a novel target for therapeutic intervention and potentially attenuate CKD progression

Wind Effects on Near- and Midfield Mixing in Tidally Pulsed River Plumes

River plumes transport and mix land-based tracers into the ocean. In tidally pulsed river plumes, wind effects have long been considered negligible in modulating interfacial mixing in the energetic nearfield region. This research tests the influence of variable, realistic winds on mixing in the interior plume. A numerical model of the Merrimack River plume-shelf system is utilized, with an application of the salinity variance approach employed to identify spatial and temporal variation in advection, straining, and dissipation (mixing) of vertical salinity variance (stratification). Results indicate that moderate wind stresses (∼0.5 Pa) with a northward component countering the downcoast rotation of the plume are most effective at decreasing stratification in the domain relative to other wind conditions. Northward winds advect plume and ambient shelf stratification offshore, allowing shelf water salinity to increase in the nearshore, which strengthens the density gradient at the plume base. Straining in the plume increases with winds enhancing offshore-directed surface velocities, leading to increased shear at the plume base. Increased straining and larger density gradients at the plume base enhance variance dissipation in the near- and midfield plume, and dissipation remains enhanced if the shelf is clear of residual stratification. The smaller spatial and temporal scales of the Merrimack plume allow the mechanisms to occur at tidal time scales in direct response to instantaneous winds. This is the first study to show tidal time scale wind-induced straining and advection as controlling factors on near- and midfield mixing rates in river plumes under realistic winds

Freshwater Composition and Connectivity of the Connecticut River Plume During Ambient Flood Tides

The Connecticut River plume interacts with the strong tidal currents of the ambient receiving waters in eastern Long Island Sound. The plume formed during ambient flood tides is studied as an example of tidal river plumes entering into energetic ambient tidal environments in estuaries or continental shelves. Conservative passive freshwater tracers within a high-resolution nested hydrodynamic model are applied to determine how source waters from different parts of the tidal cycle contribute to plume composition and interact with bounding plume fronts. The connection to source waters can be cut off only under low-discharge conditions, when tides reverse surface flow through the mouth after max ambient flood. Upstream plume extent is limited because ambient tidal currents arrest the opposing plume propagation, as the tidal internal Froude number exceeds one. The downstream extent of the tidal plume always is within 20 km from the mouth, which is less than twice the ambient tidal excursion. Freshwaters in the river during the preceding ambient ebb are the oldest found in the new flood plume. Connectivity with source waters and plume fronts exhibits a strong upstream-to- downstream asymmetry. The arrested upstream front has high connectivity, as all freshwaters exiting the mouth immediately interact with this boundary. The downstream plume front has the lowest overall connectivity, as interaction is limited to the oldest waters since younger interior waters do not overtake this front. The offshore front and inshore boundary exhibit a downstream progression from younger to older waters and decreasing overall connectivity with source waters. Plume-averaged freshwater tracer concentrations and variances both exhibit an initial growth period followed by a longer decay period for the remainder of the tidal period. The plume-averaged tracer variance is increased by mouth inputs, decreased by entrainment, and destroyed by internal mixing. Peak entrainment velocities for younger waters are higher than values for older waters, indicating stronger entrainment closer to the mouth. Entrainment and mixing time scales (1–4 h at max ambient flood) are both shorter than half a tidal period, indicating entrainment and mixing are vigorous enough to rapidly diminish tracer variance within the plume

Benchmarking Representation Learning for Natural World Image Collections

Recent progress in self-supervised learning has resulted in models that are capable of extracting rich representations from image collections without requiring any explicit label supervision. However, to date the vast majority of these approaches have restricted themselves to training on standard benchmark datasets such as ImageNet. We argue that fine-grained visual categorization problems, such as plant and animal species classification, provide an informative testbed for self-supervised learning. In order to facilitate progress in this area we present two new natural world visual classification datasets, iNat2021 and NeWT. The former consists of 2.7M images from 10k different species uploaded by users of the citizen science application iNaturalist. We designed the latter, NeWT, in collaboration with domain experts with the aim of benchmarking the performance of representation learning algorithms on a suite of challenging natural world binary classification tasks that go beyond standard species classification. These two new datasets allow us to explore questions related to large-scale representation and transfer learning in the context of fine-grained categories. We provide a comprehensive analysis of feature extractors trained with and without supervision on ImageNet and iNat2021, shedding light on the strengths and weaknesses of different learned features across a diverse set of tasks. We find that features produced by standard supervised methods still outperform those produced by self-supervised approaches such as SimCLR. However, improved self-supervised learning methods are constantly being released and the iNat2021 and NeWT datasets are a valuable resource for tracking their progress.Comment: CVPR 202