Firewood extraction affects carbon pools and nutrients in remnant fragments of temperate forests at the Mexican Transvolcanic Belt

Globally, remnant fragments of forests represent the main carbon reservoir of terrestrial ecosystems, but they suffer strong degradation due to uncontrolled wood extraction mainly by tree cut for household fuel use and charcoal production. The present study evaluates the degradation caused by wood extraction on carbon pools and soil nutrient dynamics in temperate forests distributed in remnant fragments located in central Mexico. Four sites with different intensity of wood extraction were chosen for measuring carbon pools and nutrient fluxes during two years. Both, aboveground carbon biomass and soil organic carbon values decreased with the intensity of forest degradation. The degraded forest (DF) showed total carbon content 55 % lower than that shown by the seminatural forest (SF). Additionally, litterfall production was reduced in DF as compared to SF; the decomposition rate of standing litter was higher in the latter site. As a consequence, DF had lower organic matter inputs to the soil than that presented by SF. Soil extractable ammonium and microbial biomass-carbon and -nitrogen were lower in DF than in SF. It was concluded that the uncontrolled wood extraction in these remnants of temperate forest in Mexico significantly reduced the carbon pools, carbon and nutrient fluxes through litterfall and consequently, the soil nutrient dynamics were disrupted

Molecular Aspects and Structure Activity Relationship of Oxytocin Agonists and Antagonist’s Role in Health

Oxytocin (OT) and Oxytocin receptor signaling mechanism had emerged as a pathway for treatment of metabolic disorders like obesity, and diabetes. Both agonists and antagonists activity of the oxytocin receptor has beneficial aspects. This chapter will outline the receptor agonists and antagonist’s activity as a function of the features: hydrophobic regions, activity shapes, and positive and negative electrostatics. Also, their phenotype characteristics in various diseases like diabetes, obesity, cardiovascular and immune related diseases will be outlined. Finally, therapeutic development strategies for using various nanomaterials, and other biomaterials, as well as those in present use will be discussed

Detection of Cyanuric Acid and Melamine in Infant Formula Powders by Mid-FTIR Spectroscopy and Multivariate Analysis

Chemometric methods using mid-FTIR spectroscopy were developed in order to reduce the time of study of melamine and cyanuric acid in infant formulas. Chemometric models were constructed using the algorithms Partial Least Squares (PLS1, PLS2) and Principal Component Regression (PCR) in order to correlate the IR signal with the levels of melamine or cyanuric acid in the infant formula samples. Results showed that the best correlations were obtained using PLS1 (R2: 0.9998, SEC: 0.0793, and SEP: 0.5545 for melamine and R2: 0.9997, SEC: 0.1074, and SEP: 0.5021 for cyanuric acid). Also, the SIMCA model was studied to distinguish between adulterated formulas and nonadulterated samples, giving optimum discrimination and good interclass distances between samples. Results showed that chemometric models demonstrated a good predictive ability of melamine and cyanuric acid concentrations in infant formulas, showing that this is a rapid and accurate technique to be used in the identification and quantification of these adulterants in infant formulas

Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems.

Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional end-to-end system, such as object detection, tracking, path planning, sentiment or intent detection, amongst others. Nevertheless, few efforts have been made to systematically compile all of these systems into a single proposal that also considers the real challenges these systems will have on the road, such as real-time computation, hardware capabilities, etc. This paper reviews the latest techniques towards creating our own end-to-end autonomous vehicle system, considering the state-of-the-art methods on object detection, and the possible incorporation of distributed systems and parallelization to deploy these methods. Our findings show that while techniques such as convolutional neural networks, recurrent neural networks, and long short-term memory can effectively handle the initial detection and path planning tasks, more efforts are required to implement cloud computing to reduce the computational time that these methods demand. Additionally, we have mapped different strategies to handle the parallelization task, both within and between the networks

Global ecological predictors of the soil priming effect

Identifying the global drivers of soil priming is essential to understanding C cycling in terrestrial ecosystems. We conducted a survey of soils across 86 globally-distributed locations, spanning a wide range of climates, biotic communities, and soil conditions, and evaluated the apparent soil priming effect using 13C-glucose labeling. Here we show that the magnitude of the positive apparent priming effect (increase in CO2 release through accelerated microbial biomass turnover) was negatively associated with SOC content and microbial respiration rates. Our statistical modeling suggests that apparent priming effects tend to be negative in more mesic sites associated with higher SOC contents. In contrast, a single-input of labile C causes positive apparent priming effects in more arid locations with low SOC contents. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios

Toro Times: Raising Our Voices!

During the Spring 2019 semester, Dr. Noah Asher Golden\u27s Teaching of Writing K-12 students partnered with the Journalism class at Yorba Academy for the Arts. Through collaboration over a four-month period, Chapman\u27s future teachers and Yorba\u27s junior high journalists engaged a deep writing process to write a series of features, editorials, and news articles related to a number of global issues. Thank you to Principal Preciado-Martin, former principal Tracy Knibb, Mrs. Andrea Lopez, Mrs. Kori Shelton, and the Lloyd E. and Elisabeth H. Klein Family Foundation for supporting this project.https://digitalcommons.chapman.edu/yorba-chapman/1004/thumbnail.jp