Personal site of Tom Bishop, laboratory technician
Many of our lab users have been trying to use various Zeiss software packages to make measurements from photomicrographs. It is often easier and quicker to use ImageJ to make these measurements.
Here’s how:
If you are measuring circular or oval objects, you may have better results using the oval selection tool (second from the left). You may wish to experiment with different selection tools depending on your measurement.
You don’t have to select everything manually. The particles can be analysed automatically. Firstly, the colour image needs to be converted into binary. Then, individual particles need to be separated where they overlap, and finally, the automatic particle recognition can be run and summary statistics obtained.
There’s loads of useful tools in ImageJ, including many that can speed up and improve repetitive workflows, and assist in preparing images for publication. Just pop by the office for a chat if you are interested in a demonstration of some features.
I’ve just passed my intermediate amateur radio exams with the help of Stockport Radio Society G8SRS. I’ll be keeping my previous call-sign M6TKG for now, but I’ll also now be using 2E0TKG under certain circumstances. As a gift to myself for passing, I’ve started putting together a little portable rig for low-power (QRP) work based on a Yaesu FT-817ND. I’ve already started reading for my full licence test, and have just begun working towards my 12 words-per-minute Morse code test. I hope that soon I’ll be in a position to bring a rig away when I travel, and make some contacts from some of the unusual places I sometimes have the opportunity to visit.
I’m pleased to announce that a paper I was involved in (led by colleagues from Manchester Metropolitan University and Liverpool John Moores University) has now been published in Boreas. The paper presents a record of glacial activity in Greenland over centennial time-scales using lake sediment geochemical proxies. My contribution was in the multi-variate statistical treatment of the elemental data, alongside some modelling work on the chronology. The paper is available online here.
The Gatsby Charitable Foundation runs a campaign called Technicians Make it Happen, raising the profile of technicians in the U.K. It’s been supported by the Science Council, amongst others, and I’m glad to be a part of the campaign this week with my profile being published on their website.
A student recently came to us with a project that would make use of Dr Ian Walker’s bicycle overtaking sensor, so I agreed to make him one. Since Dr Walker published his original article, the code has had to change a bit, so I thought this would be a good opportunity to post the updated code and include a complete bill of materials.
You’ll need a USB cable to program the Arduino. I have made some modifications to Dr Walker’s original code. They address four points:
The revised code is available here. Remember that the first time you use the RTC, you need to program it – instructions can be found here.
It should be pretty obvious how this all goes together from the photographs, code and wiring diagrams, but a few hints:
I’ll update this section in due course when we have the results of the research conducted with this sensor!
Sometimes when coring, cores can become compressed in the chamber. For example, if you know you’ve started a drive at 1 m, and finished at 2 m, but only collected 0.95 m of sediment, you may have compression. This is often a problem for Livingstone-type corers, but not an issue with Russian-types. This can be caused by:
It’s difficult to know whether you’ve lost material or suffered compression, so good practice says the stratigraphy should be cross-correlated with an adjacent sequence. If there is compression, this can be corrected for, but in practice it can be a pain. Here’s a simple way of doing it in R. Here I’m correcting the depths for sub-samples taken at 10 mm intervals, in a core that should have been 1 m in length, from 1 m to 2 m depth, but was actually 0.95 m in length when extracted.
length <- 950 # the measured length of the core when extracted
truestart <- 1000 # the starting depth of the drive
trueend <- 2000 # the finishing depth of the drive
intervals <- 10 # the sampling interval
# create the sampling sequence - this may already be available in your data
z <- seq(from = trueend-length, to = trueend, by = intervals)
# correct those depths
zc <- seq(from = truestart, to = trueend, length.out = length(z))
# compare the data
df <- data.frame(original = z,
corrected = round(zc, digits = 0),
difference = round(z-zc, digits = 0)
)
head(df)
tail(df)
This code assumes that there’s more compression at the top, and less at the bottom of the sequence, which is not unreasonable given the possibles causes listed above. Sometimes cores can expand due to decompression of the sediment following coring. This is particularly common in gytjja from lakes, where the weight of the water column compresses the sediment in-situ, thus it expands ex-situ. Take an example where we have a core of length 1.05 m, but we know we only cored from 1 m to 2 m; we need to compress the core back to 1 m length. The following code deals with this problem:
length <- 1050 # the measured length of the core when extracted
truestart <- 1000 # the starting depth of the drive
trueend <- 2000 # the finishing depth of the drive
intervals <- 10 # the sampling interval
# create the sampling sequence - this may already be available in your data
z <- seq(from = truestart, to = truestart+length, by = intervals)
# shift the depths so they are centered
zs <- z-(max(z)-trueend)/2
# correct these depths
zc <- (trueend-truestart)/length * zs + mean(c(trueend, truestart)) - ((trueend-truestart)/length) * mean(zs)
# compare the data
df <- data.frame(original = z,
shifted = zs,
corrected = round(zc, digits = 0),
difference = round(zs-zc, digits = 0)
)
head(df)
tail(df)
It’s official! The I.C.S. have announced the subdivisions for the Holocene, so I’ve made a helpful graphic to summarise their announcement, which I’ve reproduced in full below.
Formal subdivision of the Holocene Series/Epoch
It has been announced that the proposals for the subdivision of the Holocene Series/Epoch (11 700 years ago to the present day) into three stages/ages and their corresponding subseries/subepochs by the International Subcommission on Quaternary Stratigraphy (ISQS) (a subcommission of the International Commission on Stratigraphy – ICS) have been ratified unanimously by the International Union of Geological Sciences (IUGS). The subdivisions now formally defined are:
1. Greenlandian Stage/Age = Lower/Early Holocene Subseries/Subepoch
Boundary Stratotype (GSSP): NorthGRIP2 ice core, Greenland (coincident with the Holocene Series/Epoch GSSP, ratified 2008). Age: 11,700 yr b2k (before AD 2000).2. Northgrippian Stage/Age = Middle/Mid-Holocene Subseries/Subepoch
Boundary Stratotype (GSSP): NorthGRIP1 ice core, Greenland. Global Auxiliary Stratotype: Gruta do Padre Cave speleothem, Brazil. Age: 8326 yr b2k.3. Meghalayan Stage/Age = Upper/Late Holocene Subseries/Subepoch
Boundary stratotype (GSSP): Mawmluh Cave speleothem, Meghalaya, India. Global Auxiliary Stratotype, Mount Logan ice core, Canada. Age: 4250 yr b2k.These divisions are now each defined by Global Stratotype Sections and Points (GSSPs), which means that they are fixed in time in sedimentary sequences. The terms Greenlandian Stage/Age, Northgrippian Stage/Age, Meghalayan Stage/Age, Lower/Early Holocene Subseries/Subepoch, Middle/Mid-Holocene Subseries/Subepoch and Late/Upper Holocene Subseries/Subepoch therefore have formal definitions and boundaries.
These definitions represent the first formal geological subdivision of the Holocene Series/Epoch, resulting from over a decade of labour by members of the joint ISQS (International Subcommission on Quaternary Stratigraphy) – INTIMATE Members Working Group (Integration of Ice-core, Marine and Terrestrial Records), led by Professor Mike Walker (University of Aberystwyth).
Phil Gibbard
Secretary General ICS
Cambridge 26.6.18
The Morgan silver dollar is a precious metal coin minted in the late 19th century into the early 20th century. They are collectable and thus occasionally counterfeited. I’ve recently analysed genuine and counterfeit silver dollars using x-ray fluorescence (XRF) – here I’ve used a Rigaku NEX-CG ED-XRF instrument using a “fundamental parameters” estimation mode. There’s some work to do to optimise the system for these samples – it’s not something we usually work on!
Anyhow, the counterfeit seems to be brass, plated with silver. The real thing has a specification of 90% Ag, 10% Cu.
| Element | Specification | Genuine | Counterfeit |
| Ag | 90 % | 92.3 % | 27.2 % |
| Cu | 10 % | 6.6 % | 43.1 % |
| Zn | 0 % | 0.0 % | 26.0 % |
I’ve also analysed some old “round-pound” £1 coins. These were demonetised in 2017, because nationally around 1 in 30 of the coins in circulation were counterfeit – I’ve heard that in some areas, the number could have been as high as 1 in 5. I’ve found that genuine and counterfeit coins have a pretty similar Nickel-Brass metal, but can be easily distinguished by their Pb content – around 1.5 % in counterfeits, and negligible in genuine coins. The Pb is added to improve malleability.
| Specification | Genuine (1 σ, n = 8) | Counterfeit (1 σ, n = 2) | |
| Ni | 5.5 % | 6.0 ± 0.5 % | 4.9 ± 0.1 % |
| Cu | 70.0 % | 69.9 ± 0.6 % | 67.3 ± 0.4 % |
| Zn | 24.5 % | 23.1 ± 0.9 % | 25.1 ± 0.1 % |
| Pb | 0.0 % | 0.0 ± 0.0 % | 1.4 ± 0.6 % |
I’m going to develop this into part of an outreach activity that uses our Niton Handheld XRF. I’m planning demonstrations of contaminated vs. uncontaminated soils, and some other geological samples.
I’m writing up some lecture material on transfer functions and environmental reconstruction, and needed to draw a diagram to illustrate the mutual climatic range method. This code could also be used to make simple MCR calculations and the like.
