Challenging Recurrence and Management of Squamous Cell Carcinoma in the Calcaneal Region: A Case Report.

Squamous cell carcinoma (SCC) is the second most common type of skin cancer. As ultraviolet exposure represents an important risk factor, SCC commonly occurs on the face, lips, scalp, hands, and heels. The foot is an unusual location to manifest SCC.

A Theoretical Analysis of DeepWalk and Node2vec for Exact Recovery of Community Structures in Stochastic Blockmodels.

Random-walk-based network embedding algorithms like DeepWalk and node2vec are widely used to obtain euclidean representation of the nodes in a network prior to performing downstream inference tasks. However, despite their impressive empirical performance, there is a lack of theoretical results explaining their large-sample behavior. In this paper, we study node2vec and DeepWalk through the perspective of matrix factorization.

Degradation at the NaSbS/Anode Interface in an Operating All-Solid-State Sodium Battery.

All-solid-state sodium batteries utilize earth-abundant elements and are sustainable systems for large-scale energy storage and electric transportation. Replacing flammable carbonate-based electrolytes with solid-state ionic conductors promotes battery safety. Using solid-state electrolytes (SEs) also eliminates the need for packing when fabricating tandem cells, potentially enabling further enhanced energy density.

Supervised dimensionality reduction for big data.

To solve key biomedical problems, experimentalists now routinely measure millions or billions of features (dimensions) per sample, with the hope that data science techniques will be able to build accurate data-driven inferences. Because sample sizes are typically orders of magnitude smaller than the dimensionality of these data, valid inferences require finding a low-dimensional representation that preserves the discriminating information (e.g.

On a two-truths phenomenon in spectral graph clustering.

Clustering is concerned with coherently grouping observations without any explicit concept of true groupings. Spectral graph clustering-clustering the vertices of a graph based on their spectral embedding-is commonly approached via -means (or, more generally, Gaussian mixture model) clustering composed with either Laplacian spectral embedding (LSE) or adjacency spectral embedding (ASE). Recent theoretical results provide deeper understanding of the problem and solutions and lead us to a "two-truths" LSE vs.

Rumen fluid, feces, milk, water, feed, airborne dust, and bedding microbiota in dairy farms managed by automatic milking systems.

Microbiota of the gut, milk, and cowshed environment were examined at two dairy farms managed by automatic milking systems (AMS). Feed, rumen fluid, feces, milk, bedding, water, and airborne dust were collected and the microbiota on each was assessed by Illumina MiSeq sequencing. The most abundant taxa in feed, rumen fluid, feces, bedding, and water were Lactobacillaceae, Prevotellaceae, Ruminococcaceae, Ruminococcaceae, and Lactobacillaceae, respectively, at both farms.

Identification of lactic acid bacteria in the feces of dairy cows fed whole crop maize silage to assess the survival of silage bacteria in the gut.

In order to assess the survival of lactic acid bacteria (LAB) in whole crop maize silage in the gut of dairy cows, one representative silage sample and three different feces samples were collected from dairy cows on three dairy farms in Hua Bei, China and three dairy farms in Kyushu, Japan. The composition of the bacterial community was examined by denaturing gradient gel electrophoresis and quantitative polymerase chain reaction. Lactobacillus acetotolerans was detected in all bunker-made maize silage samples, regardless of the dairy farm or sampling region from which they were sourced.

Variability, stability, and resilience of fecal microbiota in dairy cows fed whole crop corn silage.

The microbiota of whole crop corn silage and feces of silage-fed dairy cows were examined. A total of 18 dairy cow feces were collected from six farms in Japan and China, and high-throughput Illumina sequencing of the V4 hypervariable region of 16S rRNA genes was performed. Lactobacillaceae were dominant in all silages, followed by Acetobacteraceae, Bacillaceae, and Enterobacteriaceae.

Diversity of lactic acid bacteria in vegetable-based and meat-based fermented foods produced in the central region of Vietnam.

The diversity of lactic acid bacteria (LAB) in naturally fermented foods produced in Hue, a city in the central region of Vietnam, was examined. From local markets, a total of 25 samples of three vegetable-based fermented products, specifically (bean sprouts), (cabbage), and (bamboo shoots), and two meat-based fermented products, specifically (uncooked pork) and (cooked pork) were obtained. The LAB diversity was assessed by quantitative real-time polymerase chain reaction (PCR) and qualitative denaturing gradient gel electrophoresis.

Comparative microbiota assessment of wilted Italian ryegrass, whole crop corn, and wilted alfalfa silage using denaturing gradient gel electrophoresis and next-generation sequencing.

The microbiota of pre-ensiled crop and silage were examined using denaturing gradient gel electrophoresis (DGGE) and next-generation sequencing (NGS). Wilted Italian ryegrass (IR), whole crop corn (WC), and wilted alfalfa (AL) silages stored for 2 months were examined. All silages contained lactic acid as a predominant fermentation product.

Coxiella burnetii Infection in a Community Operating a Large-Scale Cow and Goat Dairy, Missouri, 2013.

Coxiella burnetii is a zoonotic pathogen that causes Q fever in humans and is transmitted primarily from infected goats, sheep, or cows. Q fever typically presents as an acute febrile illness; however, individuals with certain predisposing conditions, including cardiac valvulopathy, are at risk for chronic Q fever, a serious manifestation that may present as endocarditis. In response to a cluster of Q fever cases detected by public health surveillance, we evaluated C.

Consistent latent position estimation and vertex classification for random dot product graphs.

In this work, we show that using the eigen-decomposition of the adjacency matrix, we can consistently estimate latent positions for random dot product graphs provided the latent positions are i.i.d.