Re: Hd Video Resolution 1080p Dpig
Siri Vonbank
Doug thrives on helping his clients through successful resolution of their personal injury claims. This is almost always a very difficult and stressful process, yet Doug consistently earns client accolades and appreciation for his thoughtful and expert approach.
This document describes the disposition of comments in relation to Last Call Working Draft of the Speech Synthesis Markup Language (SSML) Version 1.1( -speech-synthesis11-20080620/). Each issue is described by the name of the commenter, a description of the issue, and either the resolution or the reason that the issue was not resolved.
My reaction may not come to you as a surprise ... I would propose a similar resolution as for the PLS 1.0 schema. Both in PLS 1.0 and SSML 1.1 you already have one element for general, additional markup. In SSML 1.1 this is the metadata element which has both element and attribute extensibility. I understand that you do not want to introduce general element extensibility, but I would propose you to do the same as I proposed for PLS 1.0: add general attribute extensibility to the SML 1.1. schema. I think this is harmless and a huge benefit for "foreign vocabularies" like ITS.
"By approving this resolution, we would essentially be overstepping our authority by usurping the home rule authority of the residents and the township trustees," he said. It could be interpreted as government overreach, even if it complies with the terms set forth under SB 52. "This resolution might be legal, but that does not make it right.
In this paper, we use census data available at different administrative levels to analyze the evolution of the pig production system between 2007 and 2017 at the provincial scale. We describe the pig farming intensification in China with the pig population, number of intensive farms and productivity measures. Finally, with a downscaling methodology that harmonizes and standardizes the census data, we provide a recent and accurate distribution of pigs in China to map the recent changes at a local scale. The digital layer of the pig distribution at 1 km resolution for the year 2017 is available in the Supplementary Material.
Two different spatial databases were assembled. The first database aims to identify and integrate the highest resolution data available on pig populations in 2017. We collected the province data from the China Statistical Yearbook (National Bureau of Statistics of China or NBSC, 2008, 2018), and searched for more detailed city and county level data on the website of each province. Of the 31 provincial units in mainland, 11 have data at the county level, 13 have data at the city level and 7 only have data at the provincial level (table A1). The pig data were linked to a map of provincial administrative boundaries obtained from the Department of Resources and Environment Remote Sensing database of China (2016). These databases allowed us to construct a multi-level map with the most detailed data available on the pig population.
The downscaling and gap-filling procedures of the latest version of the Gridded Livestock of the World database are described in the paper (Gilbert et al 2018) and are only briefly recalled here. The pig distribution is available in two representations, termed dasymetric (DA) and areal-weighted (AW). The AW model distributes the animals in a census polygon uniformly, and the density of animals in each pixel is the average number of animals per pixel (i.e. the surface of a pixel is about 1 km2) of suitable land in the census unit. This representation allows to visualize the available census data, but does not provide information of the livestock distribution at local scale. However, AW representation is free of the influence of the spatial predictors. In contrast, in the DA representation, different animal densities are assigned to different pixels within a given census polygon according to the random forest (RF) models. The DA representation allows estimating the animal densities at higher resolution which is crucial for further studies such as transmission disease models or environmental impacts assessments. We detail below the modeling procedure of the DA model (figure A1).
The first step is to collect and harmonize data from different data censuses. We gathered data from the 1050 counties from 11 provinces in the 2017 published in the statistical yearbooks (table A1). The second step is to train a RF model (ranger package in R) using available pig population data and covariates, and then applying the model to make predictions at the pixel level (1 km resolution). Finally, after creating the initial prediction map out of the model, province-level totals were adjusted to match the pig stock totals at the province-level spatial database for the year 2017. This ensure that aggregated pig densities at the province level correspond to the numbers in the China Statistical Yearbook (NBSC, 2018).
Figure 3. (a) Pig density map in 2017 (AW) in number of animal per pixel (i.e. the area of a pixel is about 1 km2). Here, we used the most detailed available data for 2017, resulting in a mix of county level, city level, and province level data. The tiff format of this figure is available in the supplementary data. (b) Pig density map in 2017 at 1 km resolution pixel (DA) generated through RF modeling. The tiff format of this figure is available in the supplementary data. (c) Map of changes in pig distribution between 2010 and 2017. The increase in pig density is shown in blue, and the decrease in pig density is shown in red. The DA map produced for 2017 (figure 2(B)) were aggregated to a 10 km resolution by summing the 1 km pixel values. The differences by pixel between 2010 and 2017 are calculated as follows: \Delta D_i = D_i, 2010 - D_i, 2017 where D_i, 2010 is the pig density in 2010 of the pixel i and D_i, 2017 is the pig density in 2017 of the pixel i.
This study provides a better understanding of pig distribution and pork production in China between 2007 and 2017. Qiao et al (2016) and Zhang et al (2017) have shown a shift from extensive to intensive farms, but mapping the evolution of pig density in China (figures 3(b) and (c)) is a new aspect. In addition, we provide the most recent map of pig distribution in China at a higher resolution than previous studies (Gilbert et al 2018). These new aspects would allow several research studies to be conducted to assist in the development of environmental policies and in controlling the spread of epidemics.
Also, without appropriate technology to manage manure, the increase in large farms in the SW and NW regions, where grasslands are fragile, will threaten the local ecology due to soil degradation and air and water pollution. According to Wang et al (2006) one pig produces 5.3 kg of waste daily, which contains large amounts of heavy metals (copper, zinc, iron, other trace element additives) and pharmaceutical residues. Long-term application of livestock fecal waste to agricultural lands may lead to excessive accumulation of heavy metal elements in the soil degrading agricultural product quality and compromising food safety (Bai et al 2018, Pan et al 2019). Some recently built scale pig farms are short of facilities to manage manure which are often simply washed into watercourses (Bai et al 2019). Therefore, assessing environmental impacts and adopting beneficial management practices require livestock and environmental data at the local scale (Zhang et al 2019). While environmental impacts have been measured at the provincial scale in China (Sun and Wu 2013, Gan and Hu 2016), the recent higher spatial resolution pig map presented here would improve the reliability of these studies.
After practicing family law for over 40 years, I am now focusing my practice on mediation. My intent is to use my experience and resolution skills to assist attorneys and their clients in resolving family law disputes without lengthy and expensive litigation.
Successful mediation can hasten resolution, allow for more creative problem-solving, and provide clients the opportunity to own their solution. The goal is to resolve with less conflict and long-term damage to relationships.
Doug has been invaluable in my career development, providing me with the resources and guidance to achieve my goals as an Executive. He is an excellent active listener and thought provoker, providing insightful coaching on motivation, teamwork, leadership, conflict resolution and many other soft skills. I highly recommend Doug as an executive and career coach.
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