It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Saturday, November 25, 2023
Chinese-Russian cooperation has strengthened significantly in the past 30 years, analysis shows
Chinese and Russian cooperation has grown significantly in the past three decades thanks to joint work on energy trade, politics and official visits, analysis shows.
There was a ‘limited’ Sino–Russian cooperation intensity in 1992–1995, which grew from then until 2007 and then rose. The bilateral relationship grew progressively, with no exponential growth or peaks, according to the study.
There were no or dramatic changes following Russia’s 2014 annexation of Crimea.
The study, by Maria Papageorgiou, from the University of Exeter, and Alena Vysotskaya Guedes Vieira, from the University of Minho, is published in the journal Europe-Asia Studies. They developed a “Bilateral Cooperation Intensity” index, to measure military, economic and political cooperation between 1992 and 2019.
The index shows after 2008 energy trade assumed a new importance in Sino–Russian cooperation.
Only political cooperation reached a ‘comprehensive’ level in 2000–2003) and remained at this level. Military cooperation was limited in the early 1990s, becoming slightly stronger after 1995, decreasing between 2008 and 2015 and then increasing.
Economic cooperation was limited in the early 1990s, falling lower at the second half of the decade and the early noughties, rising between 2004 and 2015, before finally reaching ‘enhanced’ intensity in 2016–2019.
Dr Papageorgiou said: “Bilateral cooperation has gradually strengthened since the early 1990s, without abrupt changes. Political cooperation structures the Sino–Russian relationship and is its driving force. Military cooperation has seen the most varied pattern of evolution, rather than a gradual strengthening.”
The BCI Index aggregates the results of three individually measured cooperation areas: military (arms transfers, military exercises), economic (overall trade, energy) and political (United Nations General Assembly voting similarity, state visits by officials). The overall score of the BCI Index reveals how a bilateral relationship has progressed (strengthened, weakened or remained constant).
At the beginning of the period analysed there were no bilateral joint military exercises, cooperation rose to ‘limited’ in 1996–1999, remaining there until the early to mid-2000s. A slight increase was seen in 2004–2007. In 2008–2011, cooperation intensity progressed to the ‘moderate’ level. Cooperation was most “enhanced” in both 2012–2015, when the first naval exercise took place and in 2016–2019.
Energy trade cooperation was low in the 1990s, growing until it reached ‘comprehensive’, in 2016–2019.
Voting similarity in the UN General Assembly, was ‘moderate’ during 1992–1995 and 1996–1999 and enhanced from 2000–2003 onwards.
The frequency of official visits between the two countries increased significantly, limited in the early 1990s, more moderate in the middle of the decade and ‘comprehensive’ in 2000–2003 and then ‘enhanced’ in 2004–2007. Since 2008, they have remained at a consistent ‘comprehensive’ level, a regular schedule of official visits.
Dr Vysotskaya Guedes Vieira said: “Sino–Russian relations have strengthened significantly. This confirms the existence of growing, dynamic and multifaceted cooperation, from a rapprochement in the early 1990s to a strategic partnership in the mid-1990s, to a further upgrade marked by the 2001 Treaty of Friendship and a comprehensive strategic partnership in the 2010s.”
Cornus wilsoniana (2n=22) is a common shrub in the northern temperate zone of China. It blooms white flowers in spring and produces purple-black berries in autumn. This tree has a unique mottled bark texture that makes it particularly eye-catching in winter, earning it the common name "ghost dogwood". Due to its peeling bark in winter, it is commonly known as "Guangpi tree" in China. The fruit of C. wilsoniana is rich in oil and can be used to extract edible oil. The oil content of the fruit can reach up to 55% and contains abundant unsaturated fatty acids. Compared to other edible oils, it has hypolipidemic effects. Therefore, the fruit oil of C. wilsoniana can not only serve as a well-balanced dietary oil, but also helps control blood lipids. Meanwhile, owing to its strong stress resistance, it can play a huge role in afforestation, sand-fixation and soil conservation.
This study obtained the chromosome-level genome sequence of C. wilsoniana using PacBio HiFi and Hi-C sequencing technologies. The genome size is about 843.51 Mb, with a contig N50 of 4.49 Mb and scaffold N50 of 78.00 Mb. A total of 30,474 protein-coding genes were annotated. Comparative genomics analysis identified that the genome of C. wilsoniana has experienced one whole genome triplication event (WGT-γ, 115.86 Mya) and one whole genome duplication event (WGD, 44.90 Mya). The researchers also explored the origin of C. wilsoniana chromosomes and reconstructed its karyotype evolution history. Collinearity analysis revealed that C. wilsoniana shares similar genome structures with C. controversa (2n=20), and they both belong to the genus Cornus in the Cornaceae family, completing divergence about 12.46 Mya. Transcriptomic analysis found that FAD2 gene family members play a key role in regulating the oleic to linoleic acid ratio in C. wilsoniana oil. Additionally, 33 MADS transcription factor genes highly correlated with the flowering process of C. wilsoniana were identified by transcriptomic and metabolomic techniques. The above research provides valuable resources for germplasm innovation and genetic improvement of C. wilsoniana.
Spurred by the current climate crisis, there has been a heightened attention within the scientific community in recent years to how past climate variation contributed to historic human migration and other behaviors.
Now, an international group of scientists — including archaeologists, historians, climate scientists, paleo-scientists, a volcanologist and others — are calling for a strengthened commitment to transdisciplinary collaboration to study past and present human-environmental interactions, which they say will advance our understanding of these complex, entangled histories. Their recommendations were published Nov. 22 in Science Advances.
In doing so, the group has introduced a new tool, the “dahliagram,” to enable researchers to analyze and visualize a wide array of quantitative and qualitative knowledge from diverse disciplinary sources and epistemological backgrounds.
“Backed by higher-resolution data concerning past climates, environmental change is increasingly seen as a crucial factor in debates concerning social, political and economic change — and human behavior generally — through time and space,” said Michael Frachetti, a professor of archaeology in Arts & Sciences at Washington University in St. Louis, and a lead author of the paper.
“Yet interdisciplinary attempts to cross data from history, climate science, archaeology and ecology to model past social-environmental interactions are challenged by mismatched units of measure and degrees of uncertainty,”
The dahliagram attempts to overcome those challenges by creating auniversal and visual language to enable cross-disciplinary collaboration. Moreover, it allows researchers to compress vast amounts of data into a single, easy-to-interpret model.
Named for the dahlia flower whose petals bloom in concentric arrays , the dahliagram’s “petals” illustrate the relative impact of different pull and push factors contributing to human behavior over time. For example, the petals could represent the climate and environment, conflicts, politics and power, technology and resource availability. These are just examples, though. One of the benefits of the tool is that it is fully customizable to meet each study’s needs.
According to Frachetti, the tool is meant to stimulate conceptual thinking and promote critical engagement, dialogue and debate. It welcomes data from domains of research like history or archaeology that are not easily quantified as factors in understanding behaviors like migration. And it requires the user to think beyond simply causality and consider the unique intersection of social, economic, political and environmental conditions for each case.
“The tool not only allows for a more nuanced understanding of complex data, but also can be a ‘gut check’ — a way of testing your hypotheses and assumptions,” Frachetti said.
Testing the dahliagram
To test the capabilities of the proposed dahliagram tool, the group created three models that assess the impacts of a range of factors on local- to large-scale mobility in three pivotal regions of world history: eastern Africa, inner Eurasia and the North Atlantic. These selected case studies range in chronological scale from decades to centuries to millennia.
Although the dahliagram is a universal device for human-environmental research, for the purpose of this study, the researchers focused on human mobility as a behavioral response.
In each model, “movement” is placed at the center of the dahliagram while different factors are represented in a surrounding array of petals. The team synthesized volumes of research and data on each factor and then ranked it according to its influence from low to high over three concentric rings of increasing intensity.
“One of the challenges to studying past phases of migration is that there’s very rarely a single driver. It’s usually a multitude of things that are impacting the people. Changes in the climate or access to resources could be one factor, but it’s usually accompanied by something like war, new innovations, economic or political pressures, etc. The people in the Sahara, for example, have adapted to desertification for more than 5,000 years, making a simple driver for their patterned mobility, or a discrete migratory event, rather unlikely,” Frachetti said.
An interesting thing happened when the team compared the dahliagram models for each of the three case studies. Although they are separated historically by hundreds of years and thousands of kilometers, unexpected parallels between the cases became obvious to the team.
“Population movement within emergent empires in both Asia and East Africa appears to be rooted in similar forces of political and social identity, as well as ambitious interests to acquire regional resources and stimulate trade and connectivity,” the authors write. “Environmental factors were an omnipresent concern but appear to be outweighed by factors such as conflict and sovereignty.
“The historical implications of mobility within these formative empires in their respective era and region are unique, but only when visualized in the dahliagram do we see the shared correlations across an array of factors that may produce fruitful onward investigation into their behavioral similarities at the human-environmental nexus.”
Overall, the group found the dahliagram to be effective in assessing population movements that occurred within richly documented historical time scales, as well as over long periods of time.
“We now hope that our new dahligram approach will be applied by many scholars from different fields across the natural and social sciences and the humanities to enhance interdisciplinary investigations into the entanglements between nature and humans,” said Ulf Büntgen, a professor of environmental systems analysis in the Department of Geography at University of Cambridge, U.K., and a lead author of the paper.
Inspired by and built for transdisciplinary research
In recent years, the academic community has embraced the concept of transdisciplinary research. Like interdisciplinary or multidisciplinary research, transdisciplinary research connects scholarship from various disciplines to more fully grasp the complexity of problems and enable creative problem solving and discovery. What makes transdisciplinary research unique is that it incorporates the perspectives of non-academic stakeholders, including members of tribes and ethnic groups, historians, artists and other subject-matter experts.
Translating and effectively communicating complicated findings and uncertainties across disciplines, and with non-academic stakeholders, is not without its challenges, though. In fact, the idea for the dahliagram was inspired by the group’s ongoing transdisciplinary work in the “Volcanoes, Climate and History” project, which was convened by Ulf Büntgen and Clive Oppenheimer from the University of Cambridge and supported by The Center for Interdisciplinary Research (ZiF: Zentrum für interdisziplinäre Forschung) at Bielefeld University in Germany.
The dahliagram not only enables researchers to synthesize data from various sources with different metrics, it also helps ensure equity among the various contributors, Frachetti said. Moreover, the visual nature of the dahliagram is especially helpful when communicating with various stakeholders.
“This tool allows us to gather communities of specialists and fairly and collectively express our knowledge in a way that that is on equal footing, rather than allowing one discipline to lead the way. I think that that kind of equity is a significant component of what the dahliagram provides,” he said.
Ultimately, the team hopes the dahliagram will be adopted within the scientific community to stimulate further explorations of complex human behaviors by leveraging multidisciplinary team building and consensus.
According to Nicola Di Cosmo, a historian and Luce Foundation professor in East Asian Studies at the Institute for Advanced Study in Princeton, NJ and co-author of the study, the addition of the dahliagram will expand the analytical tools available for historical research.
“Historians may be encouraged to use the dahliagram to translate into a visual representation a wealth of data from multiple sources and different disciplines and thus avoid monocausal explanations derived from limited datasets,” he said.
As for scientists, Frachetti said that some might initially have hesitations about the tool because it does not provide hard facts, but he hopes the community will come to appreciate the tool for what it does provide: a visualization of the facts.
“The dahliagram is a contextual tool that’s meant to help you question your assumptions and consider other explanations. And that’s really important because even our best ‘hard facts’ — things like tree rings and our measurements to monitor the planet’s health — are conditioned by assumptions and uncertainty.”
In addition to Frachetti and Büntgen, the following experts contributed to this paper: Nicola Di Cosmo, Institute for Advanced Study; Jan Esper, Johannes Gutenberg University; Lamya Khalidi, Université Côte d’Azur CNRS, CEPAM; Franz Mauelshagen, University of Bielefeld; Clive Oppenheimer, University of Cambridge; and Eleonora Rohland, University of Bielefeld.
Dahliagram time-series modeling human movement in east Africa/southern Arabia over the past ~10,000 years.
Dahliagram time-series modeling human movement in Inner Eurasia over the past ~5,000 years.
Dahliagram time-series modeling human movement in the North Atlantic region over the past ~1500 years.
To build mountains from dolomite, a common mineral, it must periodically dissolve. This counter-intuitive lesson could help make new defect-free semiconductors and more.
ANN ARBOR—For 200 years, scientists have failed to grow a common mineral in the laboratory under the conditions believed to have formed it naturally. Now, a team of researchers from the University of Michigan and Hokkaido University in Sapporo, Japan have finally pulled it off, thanks to a new theory developed from atomic simulations.
Their success resolves a long-standing geology mystery called the "Dolomite Problem." Dolomite—a key mineral in the Dolomite mountains in Italy, Niagara Falls, the White Cliffs of Dover and Utah's Hoodoos—is very abundant in rocks older than 100 million years, but nearly absent in younger formations.
"If we understand how dolomite grows in nature, we might learn new strategies to promote the crystal growth of modern technological materials," said Wenhao Sun, the Dow Early Career Professor of Materials Science and Engineering at U-M and the corresponding author of the paper published today in Science.
The secret to finally growing dolomite in the lab was removing defects in the mineral structure as it grows. When minerals form in water, atoms usually deposit neatly onto an edge of the growing crystal surface. However, the growth edge of dolomite consists of alternating rows of calcium and magnesium. In water, calcium and magnesium will randomly attach to the growing dolomite crystal, often lodging into the wrong spot and creating defects that prevent additional layers of dolomite from forming. This disorder slows dolomite growth to a crawl, meaning it would take 10 million years to make just one layer of ordered dolomite.
Luckily, these defects aren't locked in place. Because the disordered atoms are less stable than atoms in the correct position, they are the first to dissolve when the mineral is washed with water. Repeatedly rinsing away these defects—for example, with rain or tidal cycles—allows a dolomite layer to form in only a matter of years. Over geologic time, mountains of dolomite can accumulate.
To simulate dolomite growth accurately, the researchers needed to calculate how strongly or loosely atoms will attach to an existing dolomite surface. The most accurate simulations require the energy of every single interaction between electrons and atoms in the growing crystal. Such exhaustive calculations usually require huge amounts of computing power, but software developed at U-M's Predictive Structure Materials Science (PRISMS) Center offered a shortcut.
"Our software calculates the energy for some atomic arrangements, then extrapolates to predict the energies for other arrangements based on the symmetry of the crystal structure," said Brian Puchala, one of the software's lead developers and an associate research scientist in U-M's Department of Materials Science and Engineering.
That shortcut made it feasible to simulate dolomite growth over geologic timescales.
"Each atomic step would normally take over 5,000 CPU hours on a supercomputer. Now, we can do the same calculation in 2 milliseconds on a desktop," said Joonsoo Kim, a doctoral student of materials science and engineering and the study's first author.
The few areas where dolomite forms today intermittently flood and later dry out, which aligns well with Sun and Kim's theory. But such evidence alone wasn't enough to be fully convincing. Enter Yuki Kimura, a professor of materials science from Hokkaido University, and Tomoya Yamazaki, a postdoctoral researcher in Kimura's lab. They tested the new theory with a quirk of transmission electron microscopes.
"Electron microscopes usually use electron beams just to image samples," Kimura said. "However, the beam can also split water, which makes acid that can cause crystals to dissolve. Usually this is bad for imaging, but in this case, dissolution is exactly what we wanted."
After placing a tiny dolomite crystal in a solution of calcium and magnesium, Kimura and Yamazaki gently pulsed the electron beam 4,000 times over two hours, dissolving away the defects. After the pulses, dolomite was seen to grow approximately 100 nanometers—around 250,000 times smaller than an inch. Although this was only 300 layers of dolomite, never had more than five layers of dolomite been grown in the lab before.
The lessons learned from the Dolomite Problem can help engineers manufacture higher-quality materials for semiconductors, solar panels, batteries and other tech.
"In the past, crystal growers who wanted to make materials without defects would try to grow them really slowly," Sun said. "Our theory shows that you can grow defect-free materials quickly, if you periodically dissolve the defects away during growth."
The research was funded by the American Chemical Society PRF New Doctoral Investigator grant, the U.S. Department of Energy and the Japanese Society for the Promotion of Science. Study: Dissolution enables dolomite crystal growth near ambient conditions (DOI: 10.1126/science.adi3690)
AMERICAN ASSOCIATION FOR THE ADVANCEMENT OF SCIENCE (AAAS)
Addressing the long-standing “dolomite problem,” an oddity that has vexed scientists for nearly 200 years, researchers report that dolomite crystals require cycling of saturation conditions to grow. The findings provide new insights into how dolomite is formed and why modern dolomite is primarily found in natural environments with pH or salinity fluctuations. Dolomite – a calcium magnesium carbonate – is one of the major minerals in carbonate rocks, accounting for nearly 30% of the sedimentary carbonate minerality in Earth’s crust. However, despite its geological abundance, dolomite does not readily grow under laboratory conditions, hindering the study of the mineral. For two centuries, scientific efforts have failed to precipitate dolomite in the laboratory near ambient conditions. The apparent contradiction between the massive deposits of dolomite in nature and its inability to grow even in supersaturated solutions under ambient conditions has resulted in the so-called dolomite problem. Here, using atomistic simulations of dolomite, Joonsoo Kim and colleagues make a discovery that informs this issue. Kim et al. used density function theory and kinetic Monte Carlo crystal growth simulations to show that cycles of saturation conditions are needed to promote dolomite crystal growth in the laboratory. According to the simulation’s predictions, frequent cycling of a solution between supersaturation and undersaturation can speed up dolomite growth by up to 10 million times – a process that may be paramount for producing the large amounts of dolomite on Earth’s surface. The authors validated their predictions using a transmission electron microscope to observe bulk dolomite crystal growth in situ under fluctuating saturation conditions. “The findings of Kim et al. raise many questions about how geochemical fluctuations occur in the natural world over geological timescales and what factors influence the process,” writes Juan Manuel García-Ruiz in a related Perspective.
SCIENTISTS FROM THE UNIVERSITY OF CAMBRIDGE STUDIED HUNDREDS OF TREE TRUNKS, DUG UP BY FENLAND FARMERS WHILE PLOUGHING THEIR FIELDS. THE TEAM FOUND THAT MOST OF THE ANCIENT WOOD CAME FROM YEW TREES THAT POPULATED THE AREA BETWEEN FOUR AND FIVE THOUSAND YEARS AGO.
The Fens of eastern England, a low-lying, extremely flat landscape dominated by agricultural fields, was once a vast woodland filled with huge yew trees, according to new research.
Scientists from the University of Cambridge studied hundreds of tree trunks, dug up by Fenland farmers while ploughing their fields. The team found that most of the ancient wood came from yew trees that populated the area between four and five thousand years ago.
These trees, which are a nuisance when they jam farming equipment during ploughing, contain a treasure trove of perfectly preserved information about what the Fens looked like thousands of years ago.
The Fen yew woodlands suddenly died about 4,200 years ago, when the trees fell into peat and were preserved until today. The researchers hypothesise that a rapid sea level rise in the North Sea flooded the area with salt water, causing the vast woodlands to disappear.
The climate and environmental information these trees contain could be a valuable clue in determining whether this climate event could be related to other events that happened elsewhere in the world at the same time, including a megadrought in the Middle East that may have been a factor in the collapse of ancient Egypt’s Old Kingdom. Their results are reported in the journal Quaternary Science Reviews.
Yew (Taxus baccata) trees are one of the longest-lived species in Europe, and can reach up to 20 metres in height. While these trees are fairly common in Cambridge College gardens and churchyards across southern England, they are absent in the Fens, the low-lying marshy region of eastern England. Much of the Fens was a wetland until it was drained between the 17th and 19th centuries using artificial drainage and flood protection. Today, the area is some of the most productive farmland in the UK, thanks to its rich peat soil.
While the area is great for farming and does have its own charms, few people would describe the Fens as spectacular: for the most part, the area is extremely flat and dominated by fields of potatoes, sugar beet, wheat and other crops. But five thousand years ago, the area was a huge forest.
“A common annoyance for Fenland farmers is getting their equipment caught on big pieces of wood buried in the soil, which can often happen when planting potatoes, since they are planted a little deeper than other crops,” said lead author Tatiana Bebchuk, a PhD student from Cambridge’s Department of Geography. “This wood is often pulled up and piled at the edge of fields: it’s a pretty common sight to see these huge piles of logs when driving through the area.”
For farmers, these logs are a nuisance. But for Bebchuk and her colleagues, they are buried treasure. The Cambridge team approached several Fenland farmers and took samples of hundreds of logs that had been dug up and discarded, to find out what secrets they might hold.
“I remember when I first saw this enormous pile of abandoned trees, it was incredible just how many there were,” said Bebchuk. “But when we got them back to lab, we were even more surprised: these trees were so well-preserved, it looked as if they were cut down just yesterday.”
To put current anthropogenic climate change in a long-term context of natural variability, scientists need accurate evidence from the past, and trees are some of the best recorders of past conditions: their annual growth rings contain information about temperature and hydroclimate for every growing season they witnessed. “But the further back in time we go, the less reliable evidence we have, since very old trees and well-preserved wood materials are extremely rare,” said Professor Ulf Büntgen, the senior author of the study.
However, analysis by the Cambridge Tree-Ring Unit (TRU) showed that the yew trees dug up from Fenland fields were very old indeed: some of these ancient trees were 400 years old when they died. The new find provides unique climate information for over a millennium from around 5,200 years ago until about 4,200 years ago, when much of the Fens was a woodland of yew and oak: completely different than it looks today.
“Finding these very old trees in the Fens is completely unexpected – it would be like turning a corner in rural Cambridgeshire and seeing an Egyptian pyramid – you just wouldn’t expect it,” said Bebchuk. “It’s the same with nature – wood rots and decomposes easily, so you just don’t expect a tree that died five or four thousand years ago to last so long.”
Given that most of the Fens are barely above sea level, about 4,200 years ago, a sudden rise in sea level most likely killed the Fen woodlands. The period that the Fen woodlands died coincided with major climatic changes elsewhere in the world: at roughly the same time, a megadrought in China and the Middle East was a possible trigger of the collapse of several civilisations, including Egypt’s Old Kingdom and the Akkadian Empire in Mesopotamia.
“We want to know if there is any link between these climatic events,” said Bebchuk. “Are the megadroughts in Asia and the Middle East possibly related to the rapid sea level rise in northern Europe? Was this a global climate event, or was it a series of unrelated regional changes? We don’t yet know what could have caused these climate events, but these trees could be an important part of solving this detective story.”
“This is such a unique climate and environmental archive that will provide lots of opportunities for future studies, and it’s right from Cambridge’s own backyard,” said Büntgen. “We often travel all over the world to collect ice cores or ancient trees, but it’s really special to find such a unique archive so close to the office.”
The Fens of eastern England, a low-lying, extremely flat landscape dominated by agricultural fields, was once a vast woodland filled with huge yew trees, according to new research. Scientists from the University of Cambridge studied hundreds of tree trunks, dug up by Fenland farmers while ploughing their fields. The team found that most of the ancient wood came from yew trees that populated the area between four and five thousand years ago.
Inner part of the pile of subfossil yew trunks. Note fresh chain-saw cuts after sampling cross-sectional discs.
Cross-section of a subfossil yew trunk after surface preparation. The disc contains 380 tree-rings, i.e the tree was at least 380 years old when it died.
