Miracle-dz/UniFAR-FTUs huggingface dataset:
YeastIT: Reducing mutational bias for in vivo directed evolution using a novel yeast mutator strain based on dual adenine-/cytosine-targeting and error-prone DNA repair

Engineering proteins with new functions and properties often requires navigating large sequence spaces through rounds of iterative improvement. However, a disparity exists between the gradual pace of natural long-term evolution and a typical laboratory evolution workflow that relies on enriching functional variants from highly diverse in vitro generated libraries through very few screening rounds. Laboratory experiments often eschew presumed natural strategies such as neutral/non-adaptive and multi-phase evolution trajectories, and therefore mutagenesis technologies suitable for long ‘nature-like’ timescales are needed. Here, we introduce YeastIT, a novel in vivo mutagenesis tool for protein engineering that leverages an S. cerevisiae strain engineered to exhibit mutagenic activity directed to the gene of interest, allowing its continuous diversification. Mutagenesis is achieved by generating DNA damage through nucleoside deamination, followed by introduction of mutations by harnessing the process of error-prone DNA translesion synthesis. By eliminating the transformation step, YeastIT allows multiple rounds of screening or selection without interruptions for library diversification, thereby enabling long-term and continuous evolution campaigns. Our characterization of the mutational spectrum and frequency of the YeastIT-generated libraries, and its comparison to other methods (error-prone PCR, PACE, MutaT7, eMutaT7, OrthoRep, TRIDENT, EvolVR) demonstrates comparable mutation rates combined with a significant reduction in mutagenic bias relative to most of the alternatives. To validate YeastIT, we carried out directed evolution of a DARPin binding protein to achieve a 15-fold improved affinity. YeastIT thus provides a tool for exploring different evolutionary trajectories which overcomes previous limitations of variant availability (due to bias and low mutation rates) and emulates the way proteins emerge in Nature.
BLUFFS: Bluetooth Forward and Future Secrecy Attacks and Defenses

Bluetooth is a pervasive technology for wireless communication. Billions of devices use it in sensitive applications and to exchange private data. The security of Bluetooth depends on the Bluetooth standard and its two security mechanisms: pairing and session establishment. No prior work, including the standard itself, analyzed the future and forward secrecy guarantees of these mechanisms, e.g., if Bluetooth pairing and session establishment defend past and future sessions when the adversary compromises the current. To address this gap, we present six novel attacks, defined as the BLUFFS attacks, breaking Bluetooth sessions' forward and future secrecy. Our attacks enable device impersonation and machine-in-the-middle across sessions by only compromising one session key. The attacks exploit two novel vulnerabilities that we uncover in the Bluetooth standard related to unilateral and repeatable session key derivation. As the attacks affect Bluetooth at the architectural level, they are effective regardless of the victim's hardware and software details (e.g., chip, stack, version, and security mode). We also release BLUFFS, a low-cost toolkit to perform and automatically check the effectiveness of our attacks. The toolkit employs seven original patches to manipulate and monitor Bluetooth session key derivation by dynamically patching a closed-source Bluetooth firmware that we reverse-engineered. We show that our attacks have a critical and large-scale impact on the Bluetooth ecosystem, by evaluating them on seventeen diverse Bluetooth chips (eighteen devices) from popular hardware and software vendors and supporting the most popular Bluetooth versions. Motivated by our empirical findings, we develop and successfully test an enhanced key derivation function for Bluetooth that stops by-design our six attacks and their four root causes. We show how to effectively integrate our fix into the Bluetooth standard and discuss alternative implementation-level mitigations. We responsibly disclosed our contributions to the Bluetooth SIG.
Security games for vehicular networks

Vehicular ad-hoc networks (VANETs) enabling vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications is an emerging research field aiming to improve transportation security, reliability, and management. To better understand networking and security aspects of VANETs, we have been investigating network connectivity issues and mappings of car networks to the underlying road topology. Using this mapping and various metrics, we locate hot-spots in vehicular networks to determine the most vulnerable points for jamming. We also use these to optimize the placement of roadside units. To this end, we first develop quantitative measures for assessment of the importance of road segments in the context of security and traffic flow. We then use game theoretic analysis to investigate the effects of possible malicious users on the system for increased reliability and better management of resources. For example, we study the optimal deployment of traffic control and security infrastructure both in the static (roadside units) and dynamic case (law enforcement units). We use realistic simulation data, obtained from traffic scientists, as input to our models as well as to evaluate the effectiveness of countermeasures.
Capacity of a Class of Diamond Channels

We study a special class of diamond channels which was introduced by Schein in 2001. In this special class, each diamond channel consists of a transmitter, a noisy relay, a noiseless relay and a receiver. We prove the capacity of this class of diamond channels by providing an achievability scheme and a converse. The capacity we show is strictly smaller than the cut-set bound. We note that there exists a duality between this diamond channel coding problem and the Kaspi-Berger source coding problem.
Profile-guided System Optimizations for Accelerated Greybox Fuzzing

Greybox fuzzing is a highly popular option for security testing, incentivizing tremendous efforts to improve its performance. Prior research has brought many algorithmic advancements, leading to substantial performance growth. However, less attention has been paid to the system-level designs of greybox fuzzing tools, despite the high impacts of such designs on fuzzing throughput. In this paper, we explore system-level optimizations for greybox fuzzing. Throughout an empirical study, we unveil two system-level optimization opportunities. First, the common fuzzing mode with a fork server visibly slows down the target execution, which can be optimized by coupling persistent mode with efficient state recovery. Second, greybox fuzzing tools rely on the native Operating System (OS) to support interactions issued by the target program, involving complex but fuzzing-irrelevant operations. Simplification of OS interactions represents another optimization opportunity. We develop two techniques, informed by a short profiling phase of the fuzzing tool, to achieve the optimizations above. The first technique enables reliable and efficient persistent mode by learning critical execution states from the profiling and patching the target program to reset them. The second technique introduces user-space abstractions to simulate OS functionality, reducing expensive OS interactions. Evaluated with 20 programs and the MAGMA benchmark, we demonstrate that our optimizations can accelerate AFL and AFL++ for higher code coverage and faster bug finding.
Compositional verification of real-time systems using Ecdar

Abstra t We present a spe i(cid:28) ation theory for timed systems implemented in the E dar tool. We illustrate the operations of the spe i(cid:28) ation theory on a running example, showing the models and veri(cid:28) ation he ks. In order to demonstrate the power of the ompositional veri(cid:28) ation we perform an in depth ase study of a leader ele tion proto ol; Modeling it in E dar as Timed
Galápagos: Developing Verified Low Level Cryptography on Heterogeneous Hardwares

The proliferation of new hardware designs makes it difficult to produce high-performance cryptographic implementations tailored at the assembly level to each platform, let alone to prove such implementations correct. Hence we introduce Galápagos, an extensible framework designed to reduce the effort of verifying cryptographic implementations across different ISAs. In Galápagos, a developer proves their high-level implementation strategy correct once and then bundles both strategy and proof into an abstract module. The module can then be instantiated and connected to each platform-specific implementation. Galápagos facilitates this connection by generically raising the abstraction of the targeted platforms, and via a collection of new verified libraries and tool improvements to help automate the proof process. We validate Galápagos via multiple verified cryptographic implementations across three starkly different platforms: a 256-bit special-purpose accelerator, a 16-bit minimal ISA (the MSP430), and a standard 32-bit RISC-V CPU. Our case studies are derived from a real-world use case, the OpenTitan security chip, which is deploying our verified cryptographic code at scale.
FetchBench: Systematic Identification and Characterization of Proprietary Prefetchers

Prefetchers speculatively fetch memory using predictions on future memory use by applications. Different CPUs may use different prefetcher types, and two implementations of the same prefetcher can differ in details of their characteristics, leading to distinct runtime behavior. For a few implementations, security researchers showed through manual analysis how to exploit specific prefetchers to leak data. Identifying such vulnerabilities required tedious reverse-engineering, as prefetcher implementations are proprietary and undocumented. So far, no systematic study of prefetchers in common CPUs is available, preventing further security assessment. In this work, we address the following question: How can we systematically identify and characterize under-specified prefetchers in proprietary processors? To answer this question, we systematically analyze approaches to prefetching, design cross-platform tests to identify and characterize prefetchers on a given CPU, and demonstrate that our implementation FetchBench can characterize prefetchers on 19 different ARM and x86-64 CPUs. For example, FetchBench uncovers and characterizes a previously unknown replay-based prefetcher on the ARM Cortex-A72 CPU. Based on these findings, we demonstrate two novel attacks that exploit this undocumented prefetcher as a side channel to leak secret information, even from the secure TrustZone into the normal world.
Poster: Using CodeQL to Detect Malware in npm

Malicious packages are a problem on npm, but like other malware, they are rarely completely novel and share large semantic similarities. We propose to leverage the existing static analysis framework CodeQL to find malware on npm; but instead of detecting variants of vulnerabilities, we use it to detect variants of malware. We present a methodology for writing queries from recently reported packages, as a way of defining semantic signature for specific malicious behavior, where a single one can then be used to match entire families of malware. An iteration of our approach resulted in the discovery of 125 malicious packages from the registry, without producing a single false alarm.
Detecting and Characterizing Political Incivility on Social Media

Researchers of political communication study the impact and perceptions of political incivil-ity on social media. Yet, so far, relatively few works attempted to automatically detect and characterize political incivility. In our work, we study political incivility in Twitter, presenting several research contributions. First, we present state-of-the-art incivility detection re-sults using a large dataset, which we collected and labeled via crowd sourcing. Importantly, we distinguish between uncivil political speech that is impolite and intolerant anti-democratic discourse. Applying political incivility detection at large-scale, we derive insights regarding the prevalence of this phenomenon across users, and explore the network characteristics of users who are susceptible to disseminating uncivil political content online. Finally, we propose an approach for modeling social context information about the tweet author alongside the tweet content, showing that this leads to significantly improved performance on the task of political incivility detection. This result holds promise for related tasks, such as hate speech and stance detection.
Cryptic coral-crinoid “hanging gardens” from the Middle Devonian of southern Morocco

An unusual and exceptionally well preserved cryptic community of cnidarians, crinoids, sponges, and microbes developed in a submarine cavity of Middle Devonian age in the Hamar Laghdad area (Morocco). The biota encrusted the cavity roof and grew predominantly in an upside-down position, forming spectacular “hanging gardens. ” The investigated assemblage differs strikingly from both its Paleozoic and modern analogues; it constitutes one of a very few known examples of fossil cryptic assemblages developed in relatively deep water settings, and is the first report of a cryptic paleoecosystem dominated by rugose corals. The results support the view that during the middle Paleozoic there was no distinct polarization between open-surface and cryptic faunas in deep-water environments, but keen competition for space already existed in Devonian cryptic assemblages. The regional species pool seems to have been the main determinant of the ecological succession and structure of this cryptic community.
An In-Module Disturbance Barrier for Mitigating Write Disturbance Errors in Phase-Change Memory

—With the growing demand for technology scaling and storage capacity in server systems to support high-performance computing, phase-change memory (PCM) has garnered attention as the next-generation non-volatile memory to satisfy these requirements. However, write disturbance error (WDE) appears as a serious reliability problem preventing PCM from general commercialization. WDE occurs on the neighboring cells of a written cell due to heat dissipation. Previous studies for the prevention of WDEs are based on the write cache or verify-n-correction while they often suffer from signiﬁcant area overhead and performance degradation, making it unsuitable for high-performance computing. Therefore, an on-demand correction is required to minimize the performance overhead. In this paper, an in-module disturbance barrier (IMDB) mitigating WDEs is proposed. IMDB includes two sets of SRAMs into two levels and evicts entries with a policy that leverages the characteristics of WDE. In this work, the comparator dedicated to the replacement policy requires signiﬁcant hardware resources and latency. Thus, an approximate comparator is designed to reduce the area and latency considerably. Furthermore, the exploration of architecture parameters is conducted to obtain cost-effective design. The proposed work signiﬁcantly reduces WDEs without a noticeable speed degradation and additional energy consumption compared to previous methods. 1
Functional adaptability in playing style: A key determinant of competitive football performance

Purpose The present study examined the relationship between playing style adaptability and team match performance indicators throughout the season. Three playing style adaptability metrics were analysed, namely, (1) flexibility (i.e., exhibiting a wide range of playing styles), (2) reactivity (i.e., adapting playing style based on opposition) and (3) imposition (i.e., executing predetermined playing style regardless of opposition). Methods Team playing styles were derived through a clustering analysis of 21,708 matches played in the top five male European leagues from 2014/15 to 2019/20. Spearman’s correlation was utilized to assess the association between the three playing style adaptability metrics and four team match performance indicators (e.g., shots taken in opposition penalty box; shots conceded in own penalty box; goals scored; goals conceded; and total wins). Results Playing style flexibility was positively associated with both offensive and defensive match performance indicators and win frequency. Conversely, playing style reactivity and imposition were negatively associated with these team match performance indicators. Conclusions Our results suggest that the capacity to exhibit a wide range of playing styles throughout a season is associated with greater team performance. Furthermore, it is possible that high performing teams are capable of functionally switching between playing style reactivity and imposition, depending on match dynamics.
Poster: Towards Practical Brainwave-based User Authentication

Brainwave measuring devices have transitioned from specialized medical tools to user-friendly and economically accessible consumer products. This shift has opened new avenues for pervasive services, with applications spanning brain-computer interfaces (BCIs), disease detection, criminal trials, and, notably, authentication in computer security. Electroencephalography (EEG) signals, being difficult to steal and revocable, present an attractive biometric option. However, the practical deployment of these signals is hindered by security threats, usability issues, and privacy concerns. To this end, we expect to improve the overall performance of authentication systems using consumer-grade devices, gain a better understanding of user attitudes toward this type of authentication, and protect the user's privacy against unauthorized use of samples collected during enrollment and verification.
ELEKTRA: Efficient Lightweight multi-dEvice Key TRAnsparency

Key Transparency (KT) systems enable service providers of end-to-end encrypted communication (E2EE) platforms to maintain a Verifiable Key Directory (VKD) that maps each user's identifier, such as a username or email address, to their identity public key(s). Users periodically monitor the directory to ensure their own identifier maps to the correct keys, thus detecting any attempt to register a fake key on their behalf to Meddler-in-the-Middle (MitM) their communications. We introduce and formalize a new primitive called Multi-Device Verifiable Key Directory (MVKD), which strengthens both the security, privacy, and usability guarantees of VKD by leveraging the multi-device setting. We formalize three properties for a MVKD (completeness, extraction-based soundness, and privacy), striking a non-trivial balance between strong guarantees and the limitations imposed by a truly practical system. We then present a new MVKD system called ELEKTRA. This system combines the core of the Keybase KT system (running in production since 2014) with ideas from SEEMless (Chase et. al., 2019) and RZKS (Chen et. al., 2022). Our construction is the first to achieve the above multi-device guarantees while having formal security and privacy proofs. Finally, we implement ELEKTRA and present benchmarks demonstrating its practicality.
Phoenix: Detect and Locate Resilience Issues in Blockchain via Context-Sensitive Chaos

Resilience is vital to blockchain systems and helps them automatically adapt and continue providing their service when adverse situations occur, e.g., node crashing and data discarding. However, due to the vulnerabilities in their implementation, blockchain systems may fail to recover from the error situations, resulting in permanent service disruptions. Such vulnerabilities are called resilience issues. In this paper, we propose Phoenix, a system that helps detect and locate blockchain systems' resilience issues by context-sensitive chaos. First, we identify two typical types of resilience issues in blockchain systems: node unrecoverable and data unrecoverable. Then, we design three context-sensitive chaos strategies tailored to the blockchain feature. Additionally, we create a coordinator to effectively trigger resilience issues by scheduling these strategies. To better analyze them, we collect and sort all strategies into a pool and generate a reproducing sequence to locate and reproduce those issues. We evaluated Phoenix on 5 widely used commercial blockchain systems and detected 13 previous-unknown resilience issues. Besides, Phoenix successfully reproduces all of them, with 5.15 steps on average. The corresponding developers have fixed these issues. After that, the chaos resistance time of blockchains is improved by 143.9% on average. This indicates that Phoenix can significantly improve the resilience of these blockchains.
Análisis de la expresión en membrana de receptores ionotrópicos de glutamato y GABA en cerebelo. Alteraciones en modelos animales de encefalopatía hepática

Hepatic encephalopathy is a complex neuropsychiatric syndrome that can occur in patients with acute or chronic liver disease. It is characterized by a progressive alteration of cognitive, motor and sleep as a result of liver failure functions and can progress at different stages to coma and death. The mechanisms leading to neurological disorders in HE are not yet well established but begin to identify in animal models (Felipo V., Nature Reviews Neuroscience, 2013). The most widely accepted about the neurobiological basis of HE hypothesis point to a synergistic combination of two factors: the high concentration of ammonium or hyperammonemia due to poor elimination in the liver of this toxin and neuroinflammation. These two factors lead to abnormalities in glutamatergic and GABAergic neurotransmission are responsible for cognitive and motor impairment. One of the mechanisms that could contribute to impaired neurotransmission is a change in expression of membrane receptors for the neurotransmitters glutamate and GABA. This paper analyzes how HE affects the membrane expression, in cerebellum, of ionotropic receptors (NMDA, AMPA and GABA) involved in learning and memory as well as transporters responsible for removing the neurotransmitter glutamate of the synaptic cleft after his release. We will be used slices of cerebellum ex vivo in different animal models of HE to study the possible alteration of the membrane expression of these receptors and their involvement in cognitive and motor impairment.
The Routledge Handbook of Audio Description

, 2012; Reiss & Vermeer, 2014), to the modelling of two new AD variants: one variant used to label the emotions occurring in short narrative film extracts (EMO-AD) and a second variant used to both label the emotions and provide an explanation as to their cause and/or consequence (CXT-AD). Each of these AD variants was compared with and controlled by standard audio description of the variety typically used to assist viewers with visual impairments (BPS-AD). The second experiment tested the efficacy of and engagement with all three variants (EMO-AD; CXT-AD; BPS-AD) with a sample group of young people on the autism spectrum. All participants registered average or above IQs and fell into the age range nine to 14 years.
Helium-3 in the Guaymas Basin: Evidence for injection of mantle volatiles in the Gulf of California

Helium isotope measurements in six major basins in the Gulf of California show that the deep Guaymas Basin has 3He/4He 65–70% higher than atmospheric helium, clear evidence of mantle helium injection. Smaller 3He excesses observed in the Carmen and Farallon basins may be derived from this Guaymas Basin anomaly. The 3He concentrations in the Mazatlan Basin in the mouth of the Gulf of California are similar to average eastern Pacific values, indicating that the Gulf does not provide a significant flux of 3He into the general Pacific circulation. On the basis of temperature and salinity measurements an upper limit of 0.28°C can be placed on the amount of geothermal heating observed in any of the basins. The isotopic ratio of the injected Guaymas Basin helium is found to be 3He/4He = (1.10±0.06) × 10−5, almost identical to the helium signature observed at the Galapagos Rift but somewhat lower than the average ratio in oceanic basalt glasses.