On page 7 of the supplemental material s Figure S2. On the x-axis are the countries with forestry programs, whereas countries on the y-axis have deforestation caused by factors other than forestry.

Tree canopy density is an important concept in this study, because it determines whether an area of land is a "forest" or not a "forest."

To explain, Hansen and colleagues could analyze the satellite images of Earth at a resolution of 30 m by 30 m. For each of these 30 m by 30 m sections, they then calculated the proportion of that section that was covered in a tree canopy.

Using this map, forests can be defined as a user prefers by applying a threshold of tree cover density; for example, tree cover greater than 50% can be labeled as forest.

Landsat is a a joint program between the U.S. Geological Service (USGS) and the National Aeronautics and Space Administration (NASA).

In this program, satellites orbit around Earth and take photos of Earth's surface.

The photos taken from the satellites are not the type of photos you would take with a typical smartphone. Instead, these images can show the energy that is both reflected and emitted from Earth in many different wavelengths, including blue, green, red, near-infrared, midinfrared, and thermal-infrared light.

For a look at energy wavelengths click here.

To distinguish forests from other land types (e.g., grasslands, water, etc.), one can look at a combination of different wavelengths in the Landsat data. For instance, looking at a combination of the red, near-infrared, and shortwave infrared wavelengths helps identify forests. Our eyes are similar to a satellite sensor, except we only see in the visible wavelengths, namely red, green, and blue. Forests, to our eyes, appear dark green, meaning low blue and red reflectance and brighter green reflectance. By using remote sensing technology, we can improve our identification of forest extent and change by adding other wavelengths of reflected and emitted energy not visible to the naked eye.

Find out more about how the different wavelengths can help identify different features, here.

You can view some Landsat photos here. Be sure to check out the photos of deforestation in Bolivia, which is particularly relevant to this study!

Also check out this Landsat image video.

Landsat images are online and available to the public. You can find data here.

Before Hansen and colleagues could analyze the Landsat images, they had to preprocess them. This preprocessing included making corrections for clouds and shadows, assessing the quality of the images, and normalizing the images so that they can all be directly compared.

The total number of samples taken from a sample population.

Standard error of the mean = standard deviation/number of samples (Reference)

Figure 5 in Supplementary Materials shows differences in the cost of treatment in two cases: Average HRT and T=20C, Long HRT and T=25C (As mentioned before HRT describes the time necessary for particles to travel the system from the entrance till the outlet.)

Figure S5 shows the cost of treatment per m3 of water treated in the y-axis. The x-axis presents the two different scenarios: baseline (average HRT and T=20C) and long HRT and T=25C.

They looked at the effect of these two scenarios in two samples:

Source water sulfate with 15 mgS/L and Source water with no sulfate. In both scenarios, source water with sulfate had higher expenses compared with the condition with no sulfate in source water.

The long HRT condition is investigated to account for the conditions that could favor sulfide formation and corrosion in the sewer, in other words it is a representation of the worst-case scenario.

Author's Hypothesis: 4

The estimated duration of immune suppression in hypothesis 3 must be biologically relevant. We have years of data from other scientists who have measured the amount of mortality following measles infections. Thus, to strengthen the reliability of this paper's findings, then the duration of immune-amnesia that this paper determines should agree with the time frame during which previous studies have found children to be at increased risk of mortality following measles.

Additionally, a basic hypothesis underlying this paper is that children recover from immune-amnesia by rebuilding their immune response through re-exposure to pathogens. This process is similar to how children first build up their immune response after birth - through exposure to pathogens. Thus, if the hypothesis put forth in this paper is correct, then the time it takes to recover from measles induced immune-amnesia (i.e. the duration of immune-amnesia) should be similar to the amount of time it takes children to build an immune response in the first place.

This is a control experiment preformed by the authors.

To test that their analysis doesn't result in falsely positive results another childhood disease, Pertussis, which is preventable by vaccination but does not cause immunomodulation was also analyzed. It was found that data did not demonstrate immunomodulation like measles disease.

The authors also crossed the yellow F1 males to wildtype females to generate F2 offspring. A diagram of this cross is shown in Figure 2A.

After they had determined which of the F1 progeny expressed the mutagenic chain reaction allele (yMCR), they crossed the yMCR F1 females back to wildtype males to obtain the F2 progeny.

The authors injected their construct into fly embryos so that the germline cells in the embryo would incorporate the construct into their nuclei. Once these flies (called the F0 generation) were adults, they crossed them back to wildtype flies to obtain the F1 progeny.

This paper uses a new approach to look at an old problem--the problem of youth violence. The new approach involves testing whether summer jobs programs result in reduced youth violence.

Intravital microscopy is a technique used to image live animals. It is a live video of processes occurring in the animal while it is still alive. It gives information on different cellular interactions and activities in real time.

In this experiment, the authors inject tumor necrosis factor-α, an inflammatory cytokine within the scrotum of mice, and, via IVM, study local inflammatory response in the cremaster (that covers the testis and speramtic cord) muscles.

They next determined the receptor on the cell surface that allows these cells to interact with each other during these collisions.

There are also reasons why summer jobs might not have any effect or have the opposite effect by actually increasing violent activity. This is why this study is important to do.

In addition to the PCR genotyping, the authors performed DNA sequencing using DNA from F1 flies that were yellow (y-). DNA sequencing is a tool that allows you to determine the exact nucleotide sequence of a region of DNA. The goal of the sequencing was to confirm that the expected MCR construct had been inserted into the y locus.

This is information from Table 1.

In other words, measured or calculated sunlight intensities.

These are the sites marked on the map in figure S1 (see Figure 1 annotations).

As briefly discussed earlier in the paper, the authors used their calculated daily areal rated of dissolved organic carbon (DOC) processing to calculate the total amount of each type of DOC processing that occurs in their entire study area.

They calculated separate rates for three different types of water bodies.

The authors were able to use their dissolved organic carbon (DOC) degradation rates for the different types of water bodies to calculate the relative importance of sunlight- and microbial-driven DOC degradation in the whole study area (row labeled "sum" in Table 2).

The authors determined how important sunlight is for breaking down organic carbon by comparing how much microbes can degrade in the dark and how much all the sunlight-driven processes can degrade.

Measurement methods are summarized here and provided in detail in Reference 11.

Photostimulated bacterial respiration was measured by exposing some sterile water samples to sunlight and keeping some in the dark, then adding bacteria and measuring the difference in how much carbon dioxide was produced in the bacteria in the sunlight-exposed samples versus the bacteria in samples that were kept in the dark.

Hansen and colleagues looked at satellite images of Earth (see "Landsat data") for every year from 2000 to 2012 and determined how much of Earth is covered in forest, and whether forests increased or decreased in size from year to year.

This method involves a lot of computer processing, because the raw satellite images need to be screened and assessed before they can be used.

Hansen and colleagues performed the computational processing in Google's Earth Engine.

This sentence is referring to how Hansen and colleagues used Landsat data (e.g., the satellite images of Earth), which is all collected in exactly the same way each time. Thus, there are no inconsistencies between one sampling event (e.g., photo) and another sampling event.

By looking at the forest loss with or without subsequent forest gain, Hansen and colleagues can determine whether a country may have forestry programs or some other type of deforestation.

To explain, forestry programs treat forests as a crop in that the trees are harvested and subsequently replanted/regrown until the next harvest, and so on. Thus, countries that experience forest loss and subsequent gain likely have forestry programs.

Countries that have forest loss without much forest gain probably do not have forestry programs, and thus the deforestation is caused by some other factor. What could be some other causes of deforestation?

Hansen and colleagues are illustrating how the work they conducted in this study can be applied and used by governments around the globe to monitor changes in land cover over time.

Also, to clarify, "time-series data sets" refers to how their data (forest cover measurements) were collected, i.e., in this case in a series of collections through time (one collection of satellite images of Earth for each year from 2000 to 2012).

The researchers examined whether or not an individual's usage of positive/negative words and emoticons in tweets could be statistically predicted based on that individual's assumed political party affiliation (either Democrat or Republican).

This study is essentially the same as the one that examined photographs of members of Congress (Study 2), but this one uses photographs from a business setting, rather than a political one.

This is the main hypothesis for Study 1. The authors predict that the reason why conservatives report higher levels of well-being is that, compared with liberals, conservatives are more likely to self-enhance.

This procedure is necessary in order to ensure that any effect the authors find is specific to sleep (as opposed to hearing the sound consciously while awake).

The purpose of this task is to make the association between the sound and the training stronger.

On each trial participants were presented with a female face, a Black face, a science word and a good word.

If they they heard the gender-associated sound they had to match the female face with the science word. If they heard the race-associated sound they had to match the Black face with the good word.

The sounds were played immediately after a correct response. One sound was played for counter-gender bias responses, the other for counter-race bias responses.

For some participants Sound A was played with the gender items and Sound B with the race items, and for other participants Sound B was played with the gender items and Sound A with the race items.

Click to hear Sound A

Click to hear Sound B

Participants were asked to press the spacebar as quickly as possible after seeing a face-word pair that countered the typical bias (e.g. a female face with the word 'science').

Half the pairs countered the typical bias and half were filler trials that participants were not supposed to respond to (female + art, male + science, male + art).

This is another area for potential future research

This is another area for potential future research.

This is a problem that will definitely need to be resolved before these technologies can be deployed in human beings

This is another area for possible future research.

This could be an area of future research

Puromycin is an antibiotic that can be used to select cells which have developed resistance to it by killing off all the cells which have not. It is used here to purify a cell strain by eliminating all the cells which did not develop resistance. http://agscientific.com/blog/index.php/2012/10/10/puromycin-faqs/

That is, the AAVS1 locus in the PPP1R12C gene of chromosome 19 as mentioned above.

The authors checked the DNA sequence of daughter cells after they did the editing

This supports the authors' interpretation of what is happening.

By increasing the proportion of homologous recombination the researchers have better control over the process. Nonhomologous end joining is a less exact process and leads to more spontaneous errors.

The results of the editing process appeared sooner in the case of the authors' engineered guide RNAs as compared with the earlier method using TALENs

In other words, 3-8% of the cells returned to being fluorescent.

The authors constructed two different guide RNAs

This is the 68-bp fragment mentioned toward the end of the last paragraph. When it is expressed, it makes the protein non-fluorescent.

This method uses a laser to identify which cells are of interest and thus sort them out. http://www.bio.davidson.edu/courses/genomics/method/facs.html

By introducing the green fluorescent protein sequence and then disrupting it the authors were able to measure how well their genetic editing worked. They could measure this by determining how many of the daughter cells were fluorescent.

In the natural CRISPR system guide RNAs take fragments of the viral or plasmid DNA and guide them to specific locations in the CRISPR locus. The idea here is that these artificial guide RNAs can similarly guide a short strand of nucleic acids into a specific place in the target genome.

The authors combined two proteins which are needed for correct functioning of the CRISPR type II system.

Genes code for proteins, but characteristics of the cells that the genes are in may either help or hinder the genes from actually producing the desired protein.

For example, there are differences between insect protein and the protein of mammals. Cells can be engineered to produce the desired type of protein. For more about expression systems, see this link: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3848218/

Nuclear localization signals are amino acid sequences that mark a protein to be transported to a specific place in the nucleus.

A codon is a sequence of DNA "letters" that corresponds to a specific amino acid. By using a sequence of codons, specific proteins can be constructed.

To design their study, the authors combined counterbias training (discussed in the previous paragraph) with memory reactivation during sleep (discussed in this paragraph) in order to reduce racial and gender biases.

While participants were asleep, the experimenters played one of two sounds - either the sound associated with the gender counterbias training or the sound associated with the racial counterbias training. The sounds were played softly so that the participants did not wake up.

The IAT is a test that measures your implicit (unconscious) biases. You initially practice classifying items based on one set of two categories (e.g. good words respond with the left hand and bad words respond with your right hand). After a number of trials you then classify another set of two categories (e.g. White faces with the left hand and Black faces with the right hand). Then the categories are paired together (e.g. if you see a good word or a White face respond with the left hand and if you see a bad word or a Black face respond with your right hand). Finally the pairings are switched (e.g. if you see a good word or a Black face respond with the left hand and if you see a bad word or a White face respond with your right hand).

Your score is calculated based on your reaction times for responding to White faces when the same key is used to classify good words than your reaction time for responding to Black faces when the same key is used to classify good words.

Try the IAT for yourself here!

AuthorsExperiments

AuthorsExperiments test

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