Now may be heard a discouraging word : the impact of climate fluctuation on Texas ranching in the 1880s

This thesis deals with the negative interrelationship between climate fluctuation and cattle ranching during the 1880s. The focus is on three large ranches that were used as case studies on the Texas Panhandle. These ranches were selected because of their size, longevity, and the number of primary documents that were available at the Panhandle Plains Museum and Archive in Canyon, Texas. The temporal focus is from 1880 to 1890. The primary documents that have been examined are letters from ranchers to the Capitol Syndicates that owned the ranch and the financial documents of each ranch. Scientific journals that examined grassland ecology, animal ecology, and climate were used in conjunction with the primary documents. The combination of these sources led to a nuanced reinterpretation of a cattle disaster from the 1880s. The disaster was a massive loss of stock through a series of extremely cold winters and a drought that lasted several years. In the wake of this disaster, through the use of technology, these ranches were able to recover and increase their stock numbers beyond what they were prior to the years dominated by stock losses and low cattle prices

Dose Effect of Whey Protein on Gut Hormone Responses in Pre-Diabetics and Type 2 Diabetics

GLP-1 and GIP have been shown to increase following a 50 g dose of whey protein prior to a high glycemic load in type 2 diabetics. However, this increase is reduced in diabetics compared to healthy individuals. Pancreatic polypeptide (PP) and peptide tyrosine tyrosine (PYY) also increase, while ghrelin decreases after the consumption of whey protein; however, it is not known if a similar hormone response occurs with a lower dose of whey protein prior to a glycemic load or if there is a dose effect. Our hypothesis was that 20 g and 30 g of whey protein would increase GLP-1, GIP, PP, and PYY and decrease ghrelin in a dose dependent manner. PURPOSE: The purpose of this study was to examine the effect of two different doses of whey protein ingested 30 min prior to a 50 g OGTT on gut hormone and incretin response. METHODS: Nine diabetic and pre-diabetic participants (n=9, mean ± SD; age: 64.3 + 8.1 yrs.; BMI: 29.4 + 6.0 kg/m2; HbA1c: 6.4 + 0.6%) completed three trials. The randomly assigned trials consisted of: ingestion of 250ml of water (CON); 250 ml of water + 20 g whey (20g); 250ml of water + 30 g whey (30g), prior to completing a 50 g OGTT. Blood was collected at -30, 0, 15, 30, 60, 90, 120, and 150 min for the measurement of GIP, GLP-1, ghrelin, PP, and PYY. The whey protein was administered immediately following the -30 min and the 50 g OGTT began immediately after the 0 min blood draw. Metabolites were measured using multiplex fluorescent detection. One-way repeated measure ANOVA was used for statistical analysis for each dependent variable (P \u3c 0.05). RESULTS: 20g and 30g of whey protein significantly increased incremental area under the curve (AUC) of GIP 32% and 38% compared to CON. 30g significantly decreased ghrelin AUC -13.9% and -20% compared to 20g and CON. 30g significantly increased PP AUC 28% compared to CON only. There were no differences in ghrelin and PP AUC between 20g and CON. There were no significant differences for GLP-1 and PYY between all trials. CONCLUSION: 30 g of whey protein prior to a glucose challenge increased secretion of GIP and PP and decreased ghrelin in type 2 and pre-diabetics. There seems to be a dose effect relationship between whey, ghrelin, and PP. 30 g of whey preload may induce insulinotropic and satiety effects from GIP, PP, and ghrelin responses in type 2 and pre-diabetics

The Dose Effect of Whey Protein on Insulin Responses in Pre-Diabetics and Type 2 Diabetics

People with pre-diabetes and type 2 diabetes have shown an increase in insulin secretion after ingesting 55 g of whey protein coupled with a glycemic challenge. However, the effect of lower amounts of whey protein on insulin responses remains unclear. Our hypothesis was that both 20 g and 30 g of whey consumption prior to an oral glucose tolerance test (OGTT) would produce an increase in insulin secretion, with 30 g producing the greatest increase compared to a control. PURPOSE: The purpose of this study was to examine the effect of two different doses of whey protein ingested 30 min prior to a 50 g OGTT on glucose, insulin, C-peptide, and glucagon responses. METHODS: Diabetic or pre-diabetic participants (n=9, mean ± SD; age: 64.3 + 8.1 yrs; BMI: 29.4 + 6.0 kg/m2; body fat percentage: 42.5 + 7.8 %; fasting plasma glucose: 6.9 + 1.2 mmol/l; HbA1c: 6.4 + 0.6 %) completed three trials. The randomly assigned trials consisted of: 250 ml of water (CON), 250 ml of water + 20 g whey (20g), and 250 ml of water + 30 g whey (30g), followed by an OGTT. Blood was collected at -30, 0, 15, 30, 60, 90, 120, and 150 min for the measurement of glucose, insulin, C-peptide, and glucagon. The whey protein mixture was administered immediately following the -30 min blood draw, and the 50 g OGTT began immediately following the 0 min blood draw. Glucose was analyzed using a YSI 2900D glucose analyzer and insulin, C-peptide, and glucagon were measured via multiplex fluorescent detection (MagPix). A one-way repeated measures ANOVA (pRESULTS: Incremental area under the curve (AUC) for glucose presented no difference between the 3 trials. Insulin AUC was significantly increased from CON to 20g (p=0.004, 36.3%), CON to 30g (p=0.002, 61.7%), and 20g to 30g (p=0.030, 18.6%). C-peptide and glucagon AUC significantly increased from CON to 20g (p=0.018, 20.6%; p=0.046, 33.1%) and CON to 30g (p=0.001, 30.1%; p=0.017, 33.7%). CONCLUSION: Whey protein elicited a dose response on plasma insulin, increasing concentrations from CON to 20g, and 20g to 30g, however plasma glucose was unaffected. 20g and 30g displayed similar responses for glucagon. Neither 20 g nor 30 g of whey protein may be adequate to provide glycemic improvement in the disease management of type 2 or pre-diabetes

Complaint-driven Training Data Debugging for Query 2.0

As the need for machine learning (ML) increases rapidly across all industry sectors, there is a significant interest among commercial database providers to support "Query 2.0", which integrates model inference into SQL queries. Debugging Query 2.0 is very challenging since an unexpected query result may be caused by the bugs in training data (e.g., wrong labels, corrupted features). In response, we propose Rain, a complaint-driven training data debugging system. Rain allows users to specify complaints over the query's intermediate or final output, and aims to return a minimum set of training examples so that if they were removed, the complaints would be resolved. To the best of our knowledge, we are the first to study this problem. A naive solution requires retraining an exponential number of ML models. We propose two novel heuristic approaches based on influence functions which both require linear retraining steps. We provide an in-depth analytical and empirical analysis of the two approaches and conduct extensive experiments to evaluate their effectiveness using four real-world datasets. Results show that Rain achieves the highest recall@k among all the baselines while still returns results interactively.Comment: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Dat

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure