Impact of fatty acid on markers of exocrine pancreatic stimulation

Chronic pancreatitis in dogs is typically managed with a low-fat diet. Human research suggests consuming medium-chain triglycerides (MCT) may lower pancreatic enzyme release compared to consuming long chain fatty acids (LCFA). Twelve healthy adult colony dogs were fed a meal of cod and rice with either 3% metabolizable energy (ME) fat (control), high MCT (25% ME MCT oil, 25% ME butter), high saturated LCFA (50% ME butter), or high unsaturated LCFA (50% ME canola oil) in a 4-period by 4-treatment crossover design. Serum concentrations of canine pancreatic lipase immunoreactivity, gastrin, amylase, cholecystokinin (CCK), cholesterol, triglycerides and serum activities of DGGR lipase were measured at times 0 (fasted), 30, 120 and 180 minutes post-prandial. Following a 3-or 4-day wash-out period, each dog was assigned a new diet and the process was repeated for all treatments. Data was analyzed as a repeated-measures mixed model ANOVA. Post-hoc pairwise comparisons were run using Tukey-Kramer adjusted p-values. Shapiro-Wilk tests were used to evaluate residual normality. All statistical assumptions were sufficiently met. Statistical significance was defined as

Complexity of Leading Digit Sequences

Let $S_{a,b}$ denote the sequence of leading digits of $a^n$ in base $b$. It is well known that if $a$ is not a rational power of $b$, then the sequence $S_{a,b}$ satisfies Benford's Law; that is, digit $d$ occurs in $S_{a,b}$ with frequency $\log_{b}(1+1/d)$, for $d=1,2,\dots,b-1$. In this paper, we investigate the \emph{complexity} of such sequences. We focus mainly on the \emph{block complexity}, $p_{a,b}(n)$, defined as the number of distinct blocks of length $n$ appearing in $S_{a,b}$. In our main result we determine $p_{a,b}(n)$ for all squarefree bases $b\ge 5$ and all rational numbers $a>0$ that are not integral powers of $b$. In particular, we show that, for all such pairs $(a,b)$, the complexity function $p_{a,b}(n)$ is \emph{affine}, i.e., satisfies $p_{a,b}(n)=c_{a,b} n + d_{a,b}$ for all $n\ge1$, with coefficients $c_{a,b}\ge1$ and $d_{a,b}\ge0$, given explicitly in terms of $a$ and $b$. We also show that the requirement that $b$ be squarefree cannot be dropped: If $b$ is not squarefree, then there exist integers $a$ with $1<a<b$ for which $p_{a,b}(n)$ is not of the above form. We use this result to obtain sharp upper and lower bounds for $p_{a,b}(n)$, and to determine the asymptotic behavior of this function as $b\to\infty$ through squarefree values. We also consider the question which linear functions $p(n)=cn+d$ arise as the complexity function $p_{a,b}(n)$ of some leading digit sequence $S_{a,b}$. We conclude with a discussion of other complexity measures for the sequences $S_{a,b}$ and some open problems

Influences of Stone–Wales defects on the structure, stability and electronic properties of antimonene: A first principle study

AbstractDefects are inevitably present in materials, and their existence strongly affects the fundamental physical properties of 2D materials. Here, we performed first-principles calculations to study the structural and electronic properties of antimonene with Stone–Wales defects, highlighting the differences in the structure and electronic properties. Our calculations show that the presence of a SW defect in antimonene changes the geometrical symmetry. And the band gap decreases in electronic band structure with the decrease of the SW defect concentration. The formation energy and cohesive energy of a SW defect in antimonene are studied, showing the possibility of its existence and its good stability, respectively. The difference charge density near the SW defect is explored, by which the structural deformations of antimonene are explained. At last, we calculated the STM images for the SW defective antimonene to provide more information and characters for possible experimental observation. These results may provide meaningful references to the development and design of novel nanodevices based on new 2D materials

Improving garment thermal insulation property by combining two non-contact measuring tools

To investigate the effect of air gaps on the heat transfer performance of clothing, the method using the combination of two non-contact measuring tools (infrared thermal camera and 3D body scanner) has been developed considering the quantification of the air gap thickness and clothing surface temperature of different body parts without contacting clothing surface directly. The results show that the air gaps over middle and lower back of upper body have the largest thickness in all body parts, while the front and back shoulders have the smallest air gap thickness. The one-way analysis of variance shows that air gap thickness under shoulder segments has no significant difference in terms of size. Furthermore, clothing surface temperatures of shoulder and chest decrease gradually along with air gap thickness; clothing surface temperatures of front abdomen, front waist, pelvis and hip segments decrease initially but begin to increase when the air gap is above 1.5cm; clothing surface temperatures of middle back and back waist continually increase with the air gap thickness. Based on the comprehensive analyzation of the distributed features of air gap thickness and clothing surface temperature of different body parts, a revised clothing pattern with lower regional temperature and higher thermal insulation is put forward

Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding

Mining a set of meaningful topics organized into a hierarchy is intuitively appealing since topic correlations are ubiquitous in massive text corpora. To account for potential hierarchical topic structures, hierarchical topic models generalize flat topic models by incorporating latent topic hierarchies into their generative modeling process. However, due to their purely unsupervised nature, the learned topic hierarchy often deviates from users' particular needs or interests. To guide the hierarchical topic discovery process with minimal user supervision, we propose a new task, Hierarchical Topic Mining, which takes a category tree described by category names only, and aims to mine a set of representative terms for each category from a text corpus to help a user comprehend his/her interested topics. We develop a novel joint tree and text embedding method along with a principled optimization procedure that allows simultaneous modeling of the category tree structure and the corpus generative process in the spherical space for effective category-representative term discovery. Our comprehensive experiments show that our model, named JoSH, mines a high-quality set of hierarchical topics with high efficiency and benefits weakly-supervised hierarchical text classification tasks.Comment: KDD 2020 Research Track. (Code: https://github.com/yumeng5/JoSH