Trauma and resilience: McGill study explores the enduring effects of sexual violence during the Rwandan genocide against the Tutsi

Mothers often struggled with feelings of ambivalence and guilt, while many of their children displayed compassion toward them, researchers found

McGill University

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

A study led by McGill University researchers offers insights into intergenerational memory and the experiences of children born of conflict-related sexual violence and their mothers in post-genocide Rwanda.

“These children are frequently referred to as ‘children of hate,’ and are often seen as living reminders of the brutality of genocide,” said lead researcher Myriam Denov, a professor at McGill’s School of Social Work and the Canada Research Chair in Children, Families and Armed Conflict. “Yet, what we found was a profound story of empathy, love and resilience.” Denov’s study, published in the Journal of Gender Studies, offers insights into the ways in which these Rwandan mothers and children have sought justice and built relationships with one another despite facing stigma, economic and social discrimination, and violence from their families and communities.

The researchers found that many mothers struggled with feelings of guilt and ambivalence toward their child due to the circumstances of their conception. The mothers also described finding it difficult and painful to talk to their offspring about their experiences of sexual violence. Yet, growing up, their children wanted to know the truth about their birth origins and why they didn’t have a father. When mothers managed to disclose their histories of sexual violence, some found that their bond with their child was stronger as a result. Many of the children showed a deep empathy and compassion toward their mothers.

It is estimated that 250,000 to 500,000 women and girls in Rwanda experienced some form of sexual violence during the Rwandan genocide against the Tutsi in 1994. Many were the victims of gang rape. The number of children born as a result of sexual violence is estimated at 10,000 to 25,000.

The findings are based on interviews with 44 Rwandan women who bore children after having been raped and interviews and group discussions involving 60 youth born of the conflict-related sexual violence. Several youth were hired as co-researchers and involved at every step of the research process and continue to be active in the research. When the interviews took place in 2016, the youth were 19 to 21 years old and their mothers were ages 33 to 52.

Most of the children lived with their mothers and didn’t know the identity of their fathers. This often impeded the children’s access to education (some Rwandan school registration forms require a father’s signature), social acceptance and upward mobility.

Children born of rape often reported being ostracized, rejected, beaten and victimized by their families, neighbours and the broader community, the researchers said. Many learned the truth about their biological origins from family or neighbours, including through insults (such as being called “little killers”).

Many youths found comfort, belonging and acceptance with one another, forming peer support networks with other youth born of sexual violence who often became like family, the researchers noted.

“In Rwanda, more than 30 years after the genocide, these intergenerational memories continue to linger – both piercingly and silently – in daily life,” said Denov. “Although many of the youth we spoke with would like to be recognized formally as victims of the genocide against the Tutsi, they have been largely invisible in post-genocide reparation initiatives. It is my hope that this research can amplify their voices to incite understanding, recognition and change.”

Note

Out of concern about the potential impacts of the study, the youth participants were offered free monthly group counselling sessions led by a Rwandan psychologist for eight months following data collection. Mothers and youth could contact the psychologist for additional support.

About the study:

“Remembering to Forget: Intergenerational Memory for Rwandan Women Survivors of Genocidal Rape and Children Born of Conflict-Related Sexual Violence” by Myriam Denov and Shu-Hua Kang was published in the Journal of Gender Studies

DOI: https://doi.org/10.1080/09589236.2025.2527699

Funding

This research was funded by the Social Science and Humanities Research Council of Canada, the Canada Council for the Arts (Killam Program), the Canada Research Chair Program and the Pierre Elliott Trudeau Foundation.

 

---

Journal

Journal of Gender Studies

DOI

10.1080/09589236.2025.2527699 

Article Title

“Remembering to Forget: Intergenerational Memory for Rwandan Women Survivors of Genocidal Rape and Children Born of Conflict-Related Sexual Violence”

 

AI for ecology and conservation: New tools track ecosystem health

Rice University

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

César A. Uribe is the the Louis Owen Assistant Professor of Electrical and Computer Engineering and a member of the Ken Kennedy Institute at Rice University.

view more 

Credit: Rice University

HOUSTON – (Sept. 17, 2025) – Artificial intelligence (AI) is opening new ground in ecology. At Rice University, César A. Uribe is developing computational tools to help scientists better understand ecosystems with recent studies using AI to glean new insights from different kinds of ecological data — from African mammal food webs to tropical forest soundscapes.

“AI allows us to analyze ecological data in ways that were not possible before,” said Uribe, the Louis Owen Assistant Professor of Electrical and Computer Engineering and a member of the Ken Kennedy Institute at Rice. “These recent projects look at two different questions using different types of data from two different continents. We can span a large set of regions and types of data with these tools.”

One project introduces a new way to compare biological networks — the webs of interaction among species that underpin every ecosystem. The goal is to identify structural similarities between ecosystems in different regions, even when they are made up of completely different species. Such comparisons can inform large-scale monitoring of ecosystem health and guide conservation priorities. Traditional methods, however, often struggle with data this complex.

Uribe, together with Lydia Beaudrot at Michigan State University and other colleagues, applied a new class of mathematical tools known as optimal transport distances to analyze over a hundred African mammal food webs across six different regions on the continent.

Optimal transport describes the minimum amount of work needed to transform one object into another: If each object is represented by a mound of dirt, then optimal transport, or “earth mover’s” distance, represents the most efficient way to move dirt around so that the two mounds become analogous. In ecology, each network of species interactions can be thought of as one of those “mounds.” Optimal transport distances let researchers align the overall structure of two networks, showing how their patterns of connection compare even when the networks consist of different species.

Using these tools, the researchers analyzed data from multiple sources and were able to identify functionally equivalent species, i.e. different species that play the same ecological role in their respective ecosystems.

“This allows us to determine, for example, if the lion in this food web plays the same role as the jaguar in this other one or the leopard in this other one,” Uribe said.

The effort to quantify the ecological data was led by former Rice undergraduates Kai Hung, now a doctoral student at the Massachusetts Institute of Technology, and Alex Zalles, now pursuing a doctorate at the University of California, Berkeley.

“They did so well here at Rice that they were recruited into the top programs in the nation,” Uribe said. “It really speaks to the caliber of training and undergraduate research experience we provide.”

An earlier project focused on the tropical forests of Colombia and used sound to map biodiversity. Led by Maria Guerrero, a doctoral student in Colombia who is joining Rice this fall as a visiting scholar on a Fulbright Scholarship, the study placed 17 microphones across a range of habitats within a Colombian oil palm plantation. Over 10 days, the team recorded hundreds of hours of sound, capturing the calls of frogs, birds and insects.

Through AI analysis, the researchers created what Uribe called a “tropical forest connectome,” borrowing a term from neuroscience to describe how different areas of the forest are linked through sound.

“Instead of connections inside the brain, we were looking at the connections in the tropical forest ⎯ how information and energy flows,” Uribe said. “We were using bioacoustics data as a proxy to understand the health status of an ecosystem. The novelty here is being able to automatically identify and segment the sounds.”

The results showed that habitat matters more than distance: Two patches of intact forest can sound alike even when far apart, while a forest and a nearby region planted with oil palms may be completely different. The study confirmed the fact that converting native forests to monoculture plantations drastically reduces biodiversity, highlighting how bioacoustics can serve as a low-cost tool for large-scale monitoring.

For Uribe, who is from Colombia, the project carried special weight.

“It is personally meaningful because I am doing research that has global impact, using techniques that I am developing here in the United States with many local, regional and international collaborators,” Uribe said. “In terms of impact, both papers are meaningful because the research entails applying AI for something other than maximizing profit or gaining a competitive edge: This is AI for ecology and conservation.”

Both papers are published in Methods in Ecology and Evolution, the leading journal in the field.

For the African mammals’ food webs study, the research was supported by the National Science Foundation (2211815, 2213568, 2443064) and Google. For the bioacoustics study, the research was supported by Universidad de Antioquia, the Alexander von Humboldt Institute for Research on Biological Resources, the National Science Foundation (2213568, 2443064) and Rice, with data from Puerto Wilches funded by Universidad de Antioquia, SGI and Ecopetrol under contract FOGR09. The content in this press release is solely the responsibility of the authors and does not necessarily represent the official views of funding organizations and institutions.

-30-

This news release can be found online at news.rice.edu.

Follow Rice News and Media Relations via Twitter @RiceUNews.

Peer-reviewed papers:

Quantifying functionally equivalent species and ecological network dissimilarity with optimal transport distances | Methods in Ecology and Evolution | DOI: 10.1111/2041-210x.70130

Authors: Kai Hung, Lydia Beaudrot, Ann Finneran, Alex Zalles and César A. Uribe

https://doi.org/10.1111/2041-210x.70130

Graphical representation of landscape heterogeneity identification through unsupervised acoustic analysis | Methods in Ecology and Evolution | DOI: 10.1111/2041-210X.70041

Authors: Maria Guerrero, Camilo Sánchez-Giraldo, César A. Uribe, Víctor M. Martínez-Arias and Claudia Isaza

https://doi.org/10.1111/2041-210X.70041

About Rice:

Located on a 300-acre forested campus in Houston, Texas, Rice University is consistently ranked among the nation’s top 20 universities by U.S. News & World Report. Rice has highly respected schools of architecture, business, continuing studies, engineering and computing, humanities, music, natural sciences and social sciences and is home to the Baker Institute for Public Policy. Internationally, the university maintains the Rice Global Paris Center, a hub for innovative collaboration, research and inspired teaching located in the heart of Paris. With 4,776 undergraduates and 4,104 graduate students, Rice’s undergraduate student-to-faculty ratio is just under 6-to-1. Its residential college system builds close-knit communities and lifelong friendships, just one reason why Rice is ranked No. 1 for lots of race/class interaction and No. 7 for best-run colleges by the Princeton Review. Rice is also rated as a best value among private universities by the Wall Street Journal and is included on Forbes’ exclusive list of “New Ivies.”

---

Journal

Methods in Ecology and Evolution

DOI

10.1111/2041-210x.70130 

Article Title

Quantifying functionally equivalent species and ecological network dissimilarity with optimal transport distances

 

Algorithm optimizes robot teamwork for efficient manufacturing assembly

Stanford University

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

An image from the X-Wing construction simulation, showing nine robots collaboratively transporting the main assembly to the final construction area, while additional robot teams carry support equipment. | Stanford Intelligent Systems Laboratory

view more 

Credit: Stanford Intelligent Systems Laboratory

Developments in autonomous robotics have the potential to revolutionize manufacturing processes, making them more flexible, customizable, and efficient. But coordinating fleets of autonomous, mobile robots in a shared space – and helping them work with each other and with human partners – is an extremely complicated task.

Researchers at Stanford have created an algorithm that can take a design plan for a particular product and figure out the most efficient way to manufacture it with a team of robots. Their work, published recently in the journal Robotics and Autonomous Systems, includes planning how to construct subassemblies that are built separately and then combined, such as constructing a car door and then attaching it to the body; directing the robots to work both alone and in teams; and laying out the assembly floor in an efficient manner that prevents collisions.

“What’s really unusual about what we’re doing here is the scope of the problems we’re solving,” said Mac Schwager, an associate professor of aeronautics and astronautics at Stanford and co-author of the paper. “There has been research into some of these individual pieces, but I think we’re the first to really think about how it all fits together into a large-scale system.”

Modular manufacturing

The ability to generate assembly plans quickly and efficiently could help provide a new level of flexibility in manufacturing. Currently, automated assembly lines are very rigid – they can build one thing quickly and well. Using general purpose robots and distributed stations that are able to accomplish basic manufacturing tasks, such as welding or sanding, factories could be able to pivot more quickly or create customized products without having to retool the entire manufacturing floor.

“Right now, if you want to change your construction pipeline to something different, it requires a lot of planning and work to tear it down and set it back up,” said Dylan Asmar, a PhD student in the Stanford Intelligent Systems Laboratory and co-author on the paper. “With a more modular approach like this, changing your pipeline would be a lot easier and more streamlined.”

To make this modular construction process a reality, manufacturers need to be able to rapidly plan, coordinate, and reconfigure the movements of robots around the factory floor. Asmar, Schwager, and their colleagues designed an algorithm that can do just that. The researchers tell the algorithm how many robots it has to work with and the basic specifications of those robots, such as how much each one can carry, and provide a schematic of what they want to build and the manufacturing tasks that need to occur. The algorithm determines how the robots will split up to construct subassemblies that can be built separately from each other and how the robots will bring these pieces together quickly and efficiently.

“Our objective is to go from raw material to the finished product as quickly as possible, and the way you do that is through parallelization,” said Mykel Kochenderfer, an associate professor of aeronautics and astronautics at Stanford and senior author on the paper. “It’s not a linear sequence – we try to do operations in parallel as frequently as possible.”

The algorithm lays out assembly stations and assigns specific robots to collect and deliver parts to the correct stations at the correct times. It directs the robots to work in teams when parts are too large for an individual robot to carry and maps out how the robots will move to avoid interfering with others. And it does this all remarkably quickly – it took less than three minutes for the researchers to generate plans to assemble a toy construction block model of a Saturn V launch vehicle, which has 1,845 parts and can be broken into 306 subassemblies, with a team of 250 robots.

A platform for experimentation

“There are still plenty of problems to be solved before our work could be used in a real-world manufacturing context,” said Kyle Brown, who began this work as part of his doctoral thesis and is the lead author on the paper. Brown and his colleagues have built a simulator to help other researchers test their own construction algorithms and bring the next revolution in manufacturing closer to fruition.

The open-source platform allows researchers to try out new algorithms or adjust existing ones to see how optimizing certain aspects or working within specific constraints affects the process as a whole. It evaluates those algorithms with toy construction block models. Brown has also used the simulator as an educational tool for elementary school students, letting them race against the robots to construct a model of an airplane.

“I adjusted the speed of the simulation so that the robots went slow enough for the kids to just barely win,” Brown said. “The kids were elated at their narrow victory, and I got to teach them a little bit about robots. They may not all grow up to be roboticists, but this was definitely a positive exposure to the field.”

---

Journal

Robotics and Autonomous Systems

DOI

10.1016/j.robot.2025.105179 

Article Title

Large-scale multi-robot assembly planning for autonomous manufacturing

Article Publication Date

10-Sep-2025

XAOS

Engineers uncover why tiny particles form clusters in turbulent air

Finding could improve predictions for wildfire smoke, extreme rainfall, pharmaceutical development and more

University at Buffalo

Facebook

XLinkedInWeChaBlueskyMessage

BUFFALO, N.Y. — Tiny solid particles – like pollutants, cloud droplets and medicine powders – form highly concentrated clusters in turbulent environments like smokestacks, clouds and pharmaceutical mixers.

What causes these extreme clusters – which make it more difficult to predict everything from the spread of wildfire smoke to finding the right combination of ingredients for more effective drugs – has puzzled scientists.

A new University at Buffalo study, published Sept. 19 in Proceedings of the National Academy of Sciences, suggests the answer lies within the electric forces between particles.

“Small, uneven electric charges between particles in turbulent airflows play a much more important role than we previously thought,” says corresponding author Hui Meng, PhD, UB Distinguished Professor in the Department of Mechanical and Aerospace Engineering. “Uncovering this hidden mechanism could lead to better predictions and controls in climate research, medicine, engineering and science.”

The team began its work with the idea that particles exchange small portions of electric charge when they collide in turbulent air. But instead of spreading out evenly, the charges form irregular patches across the surface of each particle – what the team refers to as a “mosaic charge.”

These patchy charges create electrical dipoles that attract one another, which leads to more collisions and more charges.

“Ultimately, this action strengthens the attraction between the particles, creating a positive feedback loop that we named IMPACT, which is short for Inhomogeneous Mosaic Potential Amplified Collisions in Turbulence,” says first author Danielle R. Johnson, who recently earned her PhD from UB.

To test this hypothesis, the team placed hollow glass spheres – a stand-in for solid particles – into a chamber where they controlled turbulent airflows. Researchers then used a high-resolution, high-speed, 3D particle tracking system, as well as atomic force microscopic tools, to measure nanoscale charge patterns on the particles.

They found that the glass spheres acted as hypothesized, with movements matching those of the dipoles. While performed in controlled setting, the team says the results can be applied to a bevy of real-world scenarios where particle interactions are key. For example:

• Drug development – In pharmaceutical manufacturing, powders mix and behave in a variety of ways. If they’re forming extreme clusters, it could prompt drugmakers to change how the drugs are made, and ultimately make them more effective in fighting disease.
• Extreme rainfall – Cloud droplets and ice crystals collide to create rainstorms. Clustering may change these interactions, leading to less predictable or stronger storms. Better understanding such behavior could improve predictions, and help save lives and property.
• Air pollution – Smog particles may clump differently than models predict, changing the smog’s intensity and how long it stays in the air.
• Fuel combustion – Tiny particle interactions in engines and other sources of combustion have great impacts. Better understanding clustering could lead to more efficient energy use.

“What’s really exciting about this finding is that it sheds light on a previously overlooked phenomenon in particulate turbulence, and it has broad environmental, industrial and societal implications,” says co-author James Chen, PhD, associate professor in the Department of Mechanical and Aerospace Engineering.

Additional co-authors include Adam Bocanski, a UB PhD candidate in the Department of Mechanical and Aerospace Engineering, and Emily M. Diorio, a UB senior majoring in electrical engineering.

The research was supported by the National Science Foundation and the University at Buffalo Experiential Learning Network Funding.

---

Journal

Proceedings of the National Academy of Sciences

Article Title

Amplification of particle collision through contact electrification in isotropic turbulence

Article Publication Date

19-Sep-2025

A third of licensed GPs in England not working in NHS general practice

Number of patients per GP in NHS general practice has risen by 15% in last 10 years By end of 2024, there were twice as many NHS patients for each full time equivalent NHS GP than for each NHS consultant

BMJ Group

Facebook

XLinkedInWeChatBluesky
Email

Despite rising patient demand and commitments to strengthen primary care, one in three GPs with a licence to practise in England are not working in NHS general practice, finds a study published by The BMJ today.

The results also suggest that many newly qualified GPs are not entering the NHS general practice workforce or are leaving within the first 10 years. 

Overall, the number of patients for each full time equivalent GP in NHS general practice in England has risen by 15% since 2015. And by the end of 2024, there were twice as many NHS patients for each full time equivalent NHS general practice GP than for each full time equivalent NHS consultant.

The researchers say the findings highlight a widening imbalance between primary and secondary medical workforce capacity and a critical need to address the underlying reasons for workforce attrition in NHS general practice to achieve the government’s stated goals of strengthening community-based care.

Problems with recruitment and retention of GPs in England are longstanding with many GPs citing unsustainable workloads, increasing demands from patients, and insufficient time to do justice to the job as reasons to leave or reduce their hours.

To better understand this shortfall, researchers set out to compare the numbers and characteristics of GPs across three national sources of workforce data, and to examine trends in GP numbers relative to population growth and the specialist medical workforce in England.

They found that, on average, for every five additional GPs licensed by the General Medical Council (GMC), NHS general practice lost one full time equivalent GP each year for the period 2015-24.

As a result, the proportion of licensed GPs not working in NHS general practice increased from 27% (13,492) in 2015 to 34% (19,922) in 2024 by headcount and from 41% (20,210) to 52% (30,351) by full time equivalent GPs.

The differences were greatest among female GPs, younger GPs, UK qualified GPs in absolute terms but GPs who qualified outside the UK in relative terms, and for GPs in London and the South East.

In contrast, between 2015 and 2024, for every five additional GMC licensed specialist doctors, the NHS gained 4.3 full time equivalent consultants. 

Taking population growth into account, the number of NHS patients for each full time equivalent GP in NHS general practice increased by 15%, whereas the number of patients for each full time equivalent NHS consultant fell by 18%. By the end of 2024, there were twice as many NHS patients for each full time equivalent GP in NHS general practice (2,260) than for each full time equivalent NHS consultant (1,092).

These are observational findings, so no firm conclusions can be drawn about cause and effect, and the authors acknowledge that discrepancies between data sources and poor recording methods likely underestimate GPs’ true working hours in NHS general practice.

However, they conclude: “Addressing the underlying reasons for workforce attrition in NHS general practice is critical to achieving the government’s stated goals of strengthening community based care and shifting the focus of care from treatment to prevention.”

These trends threaten government plans to create a neighbourhood health service, bringing care out of hospitals and into communities, underpinned by a revitalised general practice, say researchers in an associated editorial.

The editorial points out that after years of decline, the number of full time equivalent fully qualified GPs has been rising since January 2025, offering hope that the tide may be turning, but highlights that ensuring jobs exist for newly trained GPs is only part of the solution.

“The complex mix of factors driving one in three qualified GPs out of NHS general practice must be addressed in the round,” the editorial argues. “The UK government has promised a long term workforce plan in the autumn, and this research article describes a problem that plan must solve.”

---

Journal

The BMJ

DOI

10.1136/bmj-2024-083978 

Method of Research

Observational study

Subject of Research

People

Article Title

Trends in the shortfall of English NHS general practice doctors: repeat cross sectional study

Article Publication Date

17-Sep-2025