31 research outputs found
Haplotype block structure from one replicate generated by the block method (ALS)
<p><b>Copyright information:</b></p><p>Taken from "Generating samples for association studies based on HapMap data"</p><p>http://www.biomedcentral.com/1471-2105/9/44</p><p>BMC Bioinformatics 2008;9():44-44.</p><p>Published online 24 Jan 2008</p><p>PMCID:PMC2375120.</p><p></p
Haplotype block structure from one replicate generated by the extension method (ALS)
<p><b>Copyright information:</b></p><p>Taken from "Generating samples for association studies based on HapMap data"</p><p>http://www.biomedcentral.com/1471-2105/9/44</p><p>BMC Bioinformatics 2008;9():44-44.</p><p>Published online 24 Jan 2008</p><p>PMCID:PMC2375120.</p><p></p
Global warming and life under the water
<p>With the development of society, people have already stepped into a fast-developing industrial age. The use of fossil fuels, coal and petroleum has become a main source of carbon dioxide emission, which is the key of global warming. Carbon dioxide, in recent years, is known as a greenhouse gas which has caused a rise in global temperature. There are many harmful effects global warming would bring to humans. Due to dramatic climate change, it is time to raise people’s awareness towards this ecological and social issue. The purpose of this research was to find whether global warming would have any impact on life under the water and how that can be used in future predictions. This research report looked at the water data for Ontario Lake, one of the freshwater lakes among the Great Lakes. The databases of daily water surface temperature, ice concentration, and concentration of chlorophyll absorbed in water have all proven that global warming did have great influence on lacustrine organisms. Also, according to the trend that was produced from the databases, a rough future trend was able to be produced. At the end, there are also some suggestions on what people can do to reduce environmental impact.</p
Carrier Mobility Modulation in Cu<sub>2</sub>Se Composites Using Coherent Cu<sub>4</sub>TiSe<sub>4</sub> Inclusions Leads to Enhanced Thermoelectric Performance
Carrier
transport engineering in bulk semiconductors
using inclusion
phases often results in the deterioration of carrier mobility (μ)
owing to enhanced carrier scattering at phase boundaries. Here, we
show by leveraging the temperature-induced structural transition between
the α-Cu2Se and β-Cu2Se polymorphs
that the incorporation of Cu4TiSe4 inclusions
within the Cu2Se matrix results in a gradual large drop
in the carrier mobility at temperatures below 400 K (α-Cu2Se), whereas the carrier mobility remains unchanged at higher
temperatures, where the β-Cu2Se polymorph dominates.
The sharp discrepancy in the electronic transport within the α-Cu2Se and β-Cu2Se matrices is associated with
the formation of incoherent α-Cu2Se/Cu4TiSe4 interfaces, owing to the difference in their atomic
structures and lattice parameters, which results in enhanced carrier
scattering. In contrast, the similarity of the Se sublattices between
β-Cu2Se and Cu4TiSe4 gives
rise to coherent phase boundaries and good band alignment, which promote
carrier transport across the interfaces. Interestingly, the different
cation arrangements in Cu4TiSe4 and β-Cu2Se contribute to enhanced phonon scattering at the interfaces,
which leads to a reduction in the lattice thermal conductivity. The
large reduction in the total thermal conductivity while preserving
the high power factor of β-Cu2Se in the (1–x)Cu2Se/(x)Cu4TiSe4 composites results in an improved ZT of
1.2 at 850 K, with an average ZT of 0.84 (500–850
K) for the composite with x = 0.01. This work highlights
the importance of structural similarity between the matrix and inclusions
when designing thermoelectric materials with improved energy conversion
efficiency
All identified GO categories of <i>C</i>. <i>elegans</i> for each biochar.
All identified GO categories of C. elegans for each biochar.</p
KEGG pathway classification for <i>C</i>. <i>elegans</i> exposed to different biochar treatments.
Dark/light colour of columns and numbers in the figure and right axis represent the differentially expressed genes and total genes.</p
Major gene ontology (GO) terms for <i>C</i>. <i>elegans</i> exposed to different biochar, respectively.
Rich factor was the ratio of significant to annotated DEGs. (TIF)</p
The lignocellulosic biomass of raw material for biochar.
The lignocellulosic biomass of raw material for biochar.</p
Correlation of <i>C. elegans</i> expressed genes between biochar treatments and the control.
Correlation of C. elegans expressed genes between biochar treatments and the control.</p
All identified KEGG categories of <i>C</i>. <i>elegans</i> for each biochar.
All identified KEGG categories of C. elegans for each biochar.</p