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Topic
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Needa Brown receives Women’s Health Innovation Grant
As part of Governor Maura Healey’s support of the Massachusetts Life Science Center’s Women’s Health Initiative, Needa Brown, assistant teaching professor of physics at Northeastern University, has received funding for her project “InCITE: A Biomaterial Platform to Overcome Barriers to Drug Delivery.”
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Whitford receives NIH grant to ‘enable translation’ across ribosomes
“This award will use theoretical models and high-performance computing to study the ribosome, a massive molecular assembly composed of hundreds of thousands of atoms. The ribosome is responsible for translating our genes into proteins, making its function central to all life. In this study, we will identify the molecular factors that control protein synthesis in bacteria and higher-level organisms. Insights into bacteria will aim to identify novel antibiotics, while the study of human ribosomes can shed light on a range of diseases, including metabolic diseases and forms of cancer.”
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Weng receives funding to identify small molecules involved in diseases like Alzheimer’s, Parkinson’s
“The proposed research aims to develop a plant-based drug screening platform to identify small molecules that can disrupt protein and RNA aggregation associated with neurodegenerative diseases such as Huntington’s, Alzheimer’s and Parkinson’s. The project will utilize the unique lyciumin peptide biosynthesis pathway in plants to generate a diverse library of cyclic peptides. These peptides will be screened in engineered tobacco BY-2 cells … to identify compounds that alleviate cellular toxicity and alter aggregation kinetics. … The established screening platform and identified compounds will be made available to the research community, potentially offering new tools and therapeutic strategies.”
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‘Genome-Wide Association Identifies a BAHD Acyltransferase Activity that Assembles an Ester of Glucuronosylglycerol and Phenylacetic Acid’
“Genome-wide association studies (GWAS) are an effective approach to identify new specialized metabolites and the genes involved in their biosynthesis and regulation. In this study, GWAS of Arabidopsis thaliana soluble leaf and stem metabolites identified alleles of an uncharacterized BAHD-family acyltransferase (AT5G57840) associated with natural variation in three structurally related metabolites. … Together, this work extends our understanding of the catalytic diversity of BAHD acyltransferases and uncovers a pathway that involves contributions from both phenylalanine and lipid metabolism.” Find the paper and full list of authors at the National Library of Medicine.
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‘The Evolutionary Origin of Naturally Occurring Intermolecular Diels-Alderases From Morus alba’
“Biosynthetic enzymes evolutionarily gain novel functions, thereby expanding the structural diversity of natural products to the benefit of host organisms. Diels-Alderases (DAs), functionally unique enzymes catalysing [4 + 2] cycloaddition reactions, have received considerable research interest. However, their evolutionary mechanisms remain obscure. Here, we investigate the evolutionary origins of the intermolecular DAs in the biosynthesis of Moraceae plant-derived Diels-Alder-type secondary metabolites. Our findings suggest that these DAs have evolved from an ancestor functioning as a flavin adenine dinucleotide-dependent oxidocyclase, which catalyses the oxidative cyclisation reactions of isoprenoid-substituted phenolic compounds.” Find the paper and authors list at the National Library of…
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‘Developing and Sustaining Northeastern’s Ed.D. Program During and Post Pandemic’
“Northeastern University’s Ed.D. faculty faced unique challenges during the pandemic and racial reckoning following George Floyd’s murder. During this period, however, we found opportunities to adapt and improve our program. We prioritized compassion and connection. We made significant strides in curriculum development through design and implementation of three new concentrations. We focused all program elements on how social justice works in a variety of educational settings. We altered our approach to data collection and doctoral supervision. In so doing, we were able to maintain consistency for our students and develop a closer bond with our faculty colleagues.”
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‘Design for Emergency: How Digital Technologies Enabled an Open Design Platform to Respond to COVID-19’
“In the COVID-19 pandemic, digital technologies (DT) supported the design and implementation of solutions addressing new needs and living conditions. We describe Design for Emergency, a digital open design platform developed to ideate solutions for people’s fast-changing needs in the pandemic, to analyze how DT can affect human-centered design processes during emergencies. We illustrate how DT: i) helped quickly collect and analyse people’s needs…; ii) facilitated the creation of a virtual network of stakeholders and an open-innovation digital platform; iii) inspired the ideation of solutions.” Find the paper and full list of authors at Interacting With Computers.
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‘Monodromy of the Casimir Connection of a Symmetrisable Kac–Moody Algebra’
“Let g be a symmetrisable Kac–Moody algebra and V an integrable g–module in category O. We show that the monodromy of the (normally ordered) rational Casimir connection on V can be made equivariant with respect to the Weyl group W of g, and therefore defines an action of the braid group Bw on V. … This action is canonically equivalent to the quantum Weyl group action of Bw on a quantum deformation of V, that is an integrable, category O module V over the quantum group Uhg such that V/hV is isomorphic to V.” Find authors at Inventiones Mathematicae.
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Engineering professor wants to revolutionize wireless communication by manipulating ‘acoustic waves in solids’
Assistant professor of electrical and computer engineering Siddhartha Ghosh has received two prestigious early career awards for his work on radio frequency front-end devices, developing materials that convert radio signals into acoustic waves at the microchip level.
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‘Black-Box Access is Insufficient for Rigorous AI Audits’
“External audits of AI systems are increasingly recognized as a key mechanism for AI governance. The effectiveness of an audit, however, depends on the degree of system access granted to auditors. Recent audits of state-of-the-art AI systems have primarily relied on black-box access, in which auditors can only query the system and observe its outputs. However, white-box access to the system’s inner workings … allows an auditor to perform stronger attacks. … In this paper, we examine the limitations of black-box audits and the advantages of white- and outside-the-box audits.” Find the paper and full list of authors at ArXiv.
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‘Deploying and Evaluating LLMs to Program Service Mobile Robots’
“Recent advancements in large language models (LLMs) have spurred interest in using them for generating robot programs from natural language, with promising initial results. We investigate the use of LLMs to generate programs for service mobile robots leveraging mobility, perception and human interaction skills, and where accurate sequencing and ordering of actions is crucial for success. We contribute CodeBotler, an open-source robot-agnostic tool to program service mobile robots from natural language, and RoboEval , a benchmark for evaluating LLMs’ capabilities of generating programs to complete service robot tasks.” Find the paper and list of authors at IEEE Robotics and Automation…
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‘How Beginning Programmers and Code LLMs (Mis)read Each Other’
“Generative AI models, specifically large language models (LLMs), have made strides towards the long-standing goal of text-to-code generation. This progress has invited numerous studies of user interaction. However, less is known about the struggles and strategies of non-experts, for whom each step of the text-to-code problem presents challenges: describing their intent in natural language, evaluating the correctness of generated code, and editing prompts when the generated code is incorrect. This paper presents a large-scale controlled study of how 120 beginning coders across three academic institutions approach writing and editing prompts.” Find the paper and full list of authors at ArXiv.
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Ocean Genome Legacy Center receives grant in support of student research
The Ocean Genome Legacy Center (OGL) has a received a grant from Cell Signaling Technology “providing funds for [student] experiments to improve the quality of DNA extracted from frozen biological materials.” Capitalizing on previous hypotheses made by OGL students, they are now “testing what happens if frozen tissue is thawed overnight in chilled liquid preservatives instead of extracting DNA directly from frozen tissue” in order to prevent DNA degradation.
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Wanunu receives patent for hybrid nanopores
Professor of physics and bioengineering Meni Wanunu has received a patent for “Hybrid nanopores, comprising a protein pore supported within a solid-state membrane,” according to the patent’s abstract. “In an embodiment,” the abstract continues, “a lipid-free hybrid nanopore comprises a water soluble and stable, modified portal protein of the Thermus thermophilus bacteriophage G20c, electrokinetically inserted into a larger nanopore in a solid-state membrane. The hybrid pore is stable and easy to fabricate, and exhibits low peripheral leakage, allowing sensing and discrimination among different types of biomolecules.”
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‘Early life adversity accelerates hypothalamic drive of pubertal timing in female rats with associated enhanced acoustic startle’
“Early life adversity in the form of childhood maltreatment in humans or as modeled by maternal separation (MS) in rodents is often associated with an earlier emergence of puberty in females. Earlier pubertal initiation is an example of accelerated biological aging and predicts later risk for anxiety in women, especially in populations exposed to early life trauma. … These findings indicate precocial maturation of central pubertal timing mechanisms after MS, as well as a potential role of CRH-R1 in these effects and an association with a translational measure of anxiety.” Find the paper and list of authors at Hormones and…
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‘Solid-State Sensors’ invites ‘advanced students’ into the field
Ravinder Dahiya, professor of electrical and computer engineering, with co-authors Ambarish Paul and Mitradip Bhattacharjee, has published “Solid-State Sensors,” an “up-to-date introduction to solid-state sensors, materials, fabrication processes and applications,” according to the publisher’s webpage. Oriented toward “advanced students and professionals in disciplines such as electrical and electronics engineering, physics, chemistry and biomedical engineering,” the textbook includes “the fundamentals and classification of all major types of solid-state sensors, including piezoresistive, capacitive, thermometric, optical bio-chemical, magnetic and acoustic-based sensors.”
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Large language models can lie to you — this professor wants you to know when they do
Assistant professor of computer science Malihe Alikhani has received a DARPA AI Exploration grant to introduce “healthy frictions” into human-AI interactions. These frictions would help human users understand the varying levels of certainty large language models have regarding their own statements and decrease the likelihood of users falling for AI “hallucinations.”
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‘Top-Down Control Over Dissolved Organic Carbon in the Bottom Water of the Weddell Sea and its Implication for the Continental Shelf Pump’
“Dense water out of the Antarctic shelves is expected to drive the transport of carbon into the deep Southern Ocean via the formation of Antarctic Bottom Water. However, bottom water formation’s capacity to sequester carbon into the deep ocean is poorly constrained. Here, dissolved organic carbon (DOC), dissolved black carbon and particulate organic carbon were examined to reveal the influence of the Weddell Sea Deep Water on DOC transport. … This study highlights the key role of the Antarctic continental shelf pump in carbon sequestration.” Find the paper and authors list at Progress in Oceanography.
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‘Local and Regional Geographic Variation in Inducible Defenses’
“Invasive predators can cause substantial evolutionary change in native prey populations. … Our ability to understand how local variation shapes patterns of inducible defense expression has thus far been limited by insufficient replication of populations within regions. Here, we examined local and regional variation in the inducible defenses of 12 native marine snail (Littorina obtusata) populations within two geographic regions in the Gulf of Maine that are characterized by vastly different contact histories with the invasive predatory green crab (Carcinus maenas).” Find the paper and full list of authors in Ecology.
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‘ICML 2023 Topological Deep Learning Challenge: Design and Results’
“This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topological neural networks from the literature by contributing to the python packages TopoNetX (data processing) and TopoModelX (deep learning). The challenge attracted twenty-eight qualifying submissions in its two month duration. This paper describes the design of the challenge and summarizes its main findings.” Find the paper and full list of authors at Proceedings of Machine Learning Research.
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‘Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture’
“Real-world domain experts (e.g., doctors) rarely annotate only a decision label in their day-to-day workflow without providing explanations. Yet, existing low-resource learning techniques, such as Active Learning (AL), that aim to support human annotators mostly focus on the label while neglecting the natural language explanation of a data point. This work proposes a novel AL architecture to support experts’ real-world need for label and explanation annotations in low-resource scenarios.” Find the paper and full list of authors in the Findings of the Association for Computational Linguistics.
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‘Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation Tasks’
“Large Language Models (LLMs) have demonstrated considerable advances, and several claims have been made about their exceeding human performance. However, in real-world tasks, domain knowledge is often required. … In this work, we conduct an empirical experiment on four datasets from three different domains comparing SOTA LLMs with small models trained on expert annotations with [Active Learning]. We found that small models can outperform GPT-3.5 with a few hundreds of labeled data, and they achieve higher or similar performance with GPT-4 despite that they are hundreds time smaller.” Find the paper and full list of authors at ArXiv.
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‘”The Wallpaper is Ugly”: Indoor Localization Using Vision and Language’
“We study the task of locating a user in a mapped indoor environment using natural language queries and images from the environment. Building on recent pretrained vision-language models, we learn a similarity score between text descriptions and images of locations in the environment. … Our approach is capable of localizing on environments, text, and images that were not seen during training. One model, finetuned CLIP, outperformed humans in our evaluation.” Find the paper and full list of authors in the 32nd IEEE International Conference on Robot and Human Interactive Communication proceedings.
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‘Is a Seat at the Table Enough? Engaging Teachers and Students in Dataset Specification for ML in Education’
“Despite the promises of ML in education, its adoption in the classroom has surfaced numerous issues. … A root cause of these issues is the lack of understanding of the complex dynamics of education, including teacher-student interactions, collaborative learning and classroom environment. To overcome these challenges … software practitioners need to work closely with educators and students to fully understand the context of the data (the backbone of ML applications) and collaboratively define the ML data specifications. … We conduct ten co-design sessions with ML software practitioners, educators and students.” Find the paper and full list of authors at ArXiv.
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‘Multi-Instance Randomness Extraction and Security Against Bounded-Storage Mass Surveillance’
“Consider a state-level adversary who observes and stores large amounts of encrypted data from all users on the Internet, but does not have the capacity to store it all. Later, it may target certain ‘persons of interest.’ … We would like to guarantee that, if the adversary’s storage capacity is only (say) 1% of the total encrypted data size, then even if it can later obtain the decryption keys of arbitrary users, it can only learn something about the contents of (roughly) 1% of the ciphertexts.” Find the paper and authors list at Theory of Cryptography.
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‘More Samples or More Prompt Inputs? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering’
“While most existing works on LLM prompting techniques focus only on how to select a better set of data samples inside one single prompt input (In-Context Learning or ICL), why can not we design and leverage multiple prompts together to further improve the LLM’s performance? In this work, we propose In-Context Sampling (ICS), a low-resource LLM prompting technique to produce confident predictions by optimizing the construction of multiple ICL prompt inputs.” Find the paper and full list of authors at ArXiv.
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‘Bergeron: Combating Adversarial Attacks Through a Conscience-Based Alignment Framework’
“Research into AI alignment has grown considerably since the recent introduction of increasingly capable Large Language Models (LLMs). Unfortunately, modern methods of alignment still fail to fully prevent harmful responses when models are deliberately attacked. These attacks can trick seemingly aligned models into giving manufacturing instructions for dangerous materials, inciting violence, or recommending other immoral acts. To help mitigate this issue, we introduce Bergeron: a framework designed to improve the robustness of LLMs against attacks without any additional parameter fine-tuning.” Find the paper and full list of authors at ArXiv.
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‘Hierarchical RL-Guided Large-Scale Navigation of a Snake Robot’
“Classical snake robot control leverages mimicking snake-like gaits tuned for specific environments. However, to operate adaptively in unstructured environments, gait generation must be dynamically scheduled. In this work, we present a four-layer hierarchical control scheme to enable the snake robot to navigate freely in large-scale environments. The proposed model decomposes navigation into global planning, local planning, gait generation and gait tracking. Using reinforcement learning (RL) and a central pattern generator (CPG), our method learns to navigate in complex mazes within hours.” Find the paper and full list of authors at ArXiv.