13197 research outputs found
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Interdependency Attack-Aware Secure and Performant Virtual Machine Allocation Policies With Low Attack Efficiency and Coverage
No full textCloud computing has completely changed IT (information technology) by providing IT resources as services on the internet. However, certain types of attacks, such as interdependency attacks, impede its wide adoption. With the latter, an attacker who succeeds in compromising the VM of a user can traverse the hypervisor to launch an attack on the VM(s) of other users on the same hypervisor. Unfortunately, we note a lack of secure and performant allocation policies against this problem. Existing policies focus on security but ignore other factors, including workload balance and energy consumption, which are vital for commercial cloud platforms. In this context, we propose different allocation policies for choosing the datacenter server to which we allocate a new virtual machine. These policies aim to minimize the interdependence of different users’ VMs while keeping the system performant regarding workload balance and/or power consumption. By default, our allocation policies treat all legitimate users as attackers and host their virtual machines according to their efficiency and coverage. We first design a secure and balanced solution that increases workload balance to prevent the servers from being overused. Afterward, we propose an algorithm that addresses security, power consumption, and workload balance objectives simultaneously. Based on our simulation results, our solutions perform better than existing algorithms regarding security, workload balance, and power consumption. The balanced solution reduces the chance of an attacker to zero and increases workload balance linearly. In other words, the workload balance is between [5,35] , and it utilizes slightly more hosts than existing proposals, with gains between [2,8] . Although our final proposal is less secure than previous algorithms, it performs better, so it has a good workload balance ( [5,30] ) and consumes less energy.journal articl
Nigerian Software Engineer or American Data Scientist? GitHub Profile Recruitment Bias in Large Language Models
No full textLarge Language Models (LLMs) have taken the world by storm, demonstrating their ability not only to automate tedious tasks, but also to show some degree of proficiency in completing software engineering tasks. A key concern with LLMs is their “black-box” nature, which obscures their internal workings and could lead to societal biases in their outputs. In the software engineering context, in this early results paper, we empirically explore how well LLMs can automate recruitment tasks for a geographically diverse software team. We use OpenAI's ChatGPT to conduct an initial set of experiments using GitHub User Profiles from four regions to recruit a six-person software development team, analyzing a total of 3,657 profiles over a five-year period (2019$20132023). Results indicate that ChatGPT shows preference for some regions over others, even when swapping the location strings of two profiles (counterfactuals). Furthermore, ChatGPT was more likely to assign certain developer roles to users from a specific country, revealing an implicit bias. Overall, this study reveals insights into the inner workings of LLMs and has implications for mitigating such societal biases in these models.conference pape
Generating an organ-deficient animal model using a multi-targeted CRISPR-Cas9 system
No full textGene-knockout animal models with organ-deficient phenotypes used for blastocyst complementation are generally not viable. Animals need to be maintained as heterozygous mutants, and homozygous mutant embryos yield only one-fourth of all embryos. In this study, we generated organ-deficient embryos using the CRISPR-Cas9-sgRNAms system that induces cell death with a single-guide RNA (sgRNAms) targeting multiple sites in the genome. The Cas9-sgRNAms system interrupted cell proliferation and induced cell ablation in vitro. The mouse model had Cas9 driven by the Foxn1 promoter with a ubiquitous expression cassette of sgRNAms at the Rosa26 locus (Foxn1Cas9; Rosa26_ms). It showed an athymic phenotype similar to that of nude mice but was not hairless. Eventually, a rat cell-derived thymus in an interspecies chimera was generated by blastocyst complementation of Foxn1Cas9; Rosa26_ms mouse embryos with rat embryonic stem cells. Theoretically, a half of the total embryos has the Cas9-sgRNAms system because Rosa26_ms could be maintained as homozygous.journal articl
Arabidopsis SDG proteins mediate Polycomb removal and transcription-coupled H3K36 methylation for gene activation
No full textPolycomb Repressive Complex 2 (PRC2) recognizes Polycomb response elements (PREs) and catalyzes trimethylation of histone H3 on lysine 27 (H3K27me3) for gene silencing. This silencing is counteracted by H3K36 methylation for epigenetic activation of gene expression. Here, we show that the Arabidopsis thaliana H3K36 methyltransferases SET DOMAIN-CONTAINING PROTEIN 7 (SDG7) and SDG8 antagonize PRC2-mediated silencing and establish H3K36 methylation patterns with the general transcription machinery. The sdg7 sdg8 double mutant shows developmental defects and lower H3K36me2 and H3K36me3 levels. SDG7 preferentially binds near PREs, but SDG8 is recruited to H3K36 methylation peaks. The sdg7 sdg8 phenotypes are partially rescued by loss of Polycomb function. SDG7 overlaps with PRC2 and its recruiters on chromatin and evicts them from shared target genes when conditionally induced. SDG8 and RNA Polymerase II associate at SDG- and RNA POLYMERASE II ASSOCIATED FACTOR 1 complex-regulated targets for H3K36 methylation and transcription. These results suggest that SDG proteins evict PRC2 from PREs to prevent H3K27me3 deposition and activate target genes via transcription-coupled H3K36 methylation. Post-translational modifications of histone proteins play critical roles in regulating the physical properties of chromatin and defining the transcriptional state1. Among various histone modifications, histone methylation primarily occurs on lysine or arginine residues and can affect both chromatin condensation and transcriptional states. Trimethylation of lysine 27 on histone H3 (H3K27me3) is associated with downregulation of nearby genes, leading to the formation of heterochromatic regions that are responsive to certain conditions2. Methylation of lysine 4 and 36 on histone H3 (H3K4 and H3K36) is present on nucleosomes of transcriptionally active chromatin2. Histone modifications are complex and reflect the topological constraints caused by nearby modifications. Indeed, the presence of particular histone modifications can promote the addition of the same type of modification or the removal of different types: for example, higher H3K36 levels hinder H3K27me3 deposition3. Such interconnected epigenetic systems, characterized by bistable states, determine the transcriptional activity of each gene. Methylation marks can be added to histones by specific enzymes called methyltransferases. In all eukaryotic organisms, the activity of H3K27 methyltransferase is controlled by Polycomb Repressive Complex 2 (PRC2)42014CURLY LEAF (CLF), SWINGER (SWN) and MEDEA (MEA)$2014that catalyze H3K27me37. Because these methyltransferases act redundantly, higher-order mutants exhibit more severe developmental defects than any single mutant8. Arabidopsis FERTILIZATION INDEPENDENT ENDOSPERM (FIE) is a WD40 homolog of D. melanogaster Esc. PRC2 interacts with multiple transcription factors through its subunits and is recruited to cis-regulatory regions of several hundred base pairs in length called Polycomb Response Elements (PREs). Proper PRC2 placement by trans-acting factors, such as BASIC PENTACYSTEINE (BPC), APETALA2 (AP2)-like or C2H2 zinc-finger (ZnF) family members, triggers the initial deposition of H3K27me39,10. The opposing H3K36 trimethylation is regulated by SET DOMAIN GROUP8 (SDG8)11. SDG8 interacts with the transcription machinery, namely RNA polymerase II (RNA Pol II) and the polymerase-associated factor 1 (Paf1) complex (PAF1C)12. PAF1C components include VERNALIZATION INDEPENDENCE2 (VIP2, also named EARLY FLOWERING 7 [ELF7]), VIP3, VIP4, VIP5 and VIP6 (also named ELF8)13. Despite the critical importance of H3K36me3 and the general transcription machinery, sdg8 single mutants show relatively weak developmental defects14, suggesting that the full function of SDG8 may be masked by partial redundancy with closely related protein(s). However, the identity of such factor(s) and their roles in the epigenetic systems have not been established. In this study, we focus on one SDG8 homolog, SDG7, to consolidate the existing knowledge of the epigenetic interaction network along with the general transcription machinery. We show that the sdg7 sdg8 double mutant exhibits developmental abnormalities and a notable decrease in both H3K36me2 and H3K36me3 levels, supporting the partial redundancy of SDG7 and SDG8. We also examine the genomic regions to which SDG7 and SDG8 are recruited and explore the connection between the sdg7 sdg8 mutant phenotypes, the PRC2 complex, and RNA Pol II. We propose that SDGs displace PRC2 from PREs, preventing the deposition of H3K27me3 and activating the expression of target genes through transcription-coupled H3K36 methylation.journal articl
mCSQA: Multilingual Commonsense Reasoning Dataset with Unified Creation Strategy by Language Models and Humans
No full textIt is very challenging to curate a dataset for language-specific knowledge and common sense in order to evaluate natural language understanding capabilities of language models. Due to the limitation in the availability of annotators, most current multilingual datasets are created through translation, which cannot evaluate such language-specific aspects. Therefore, we propose Multilingual CommonsenseQA (mCSQA) based on the construction process of CSQA but leveraging language models for a more efficient construction, e.g., by asking LM to generate questions/answers, refine answers and verify QAs followed by reduced human efforts for verification. Constructed dataset is a benchmark for cross-lingual language-transfer capabilities of multilingual LMs, and experimental results showed high language-transfer capabilities for questions that LMs could easily solve, but lower transfer capabilities for questions requiring deep knowledge or commonsense. This highlights the necessity of language-specific datasets for evaluation and training. Finally, our method demonstrated that multilingual LMs could create QA including language-specific knowledge, significantly reducing the dataset creation cost compared to manual creation. The datasets are available at https://huggingface.co/datasets/yusuke1997/mCSQA.conference pape
STLNet: Symmetric Transformer Learning Network for Remote Sensing Image Change Detection
No full textChange detection (CD) signifies a pivotal domain within remote sensing image processing. The transformer has been introduced in the field of CD for its global perception capabilities. However, existing transformer-based methodologies serve primarily as mere direct feature extractors, rendering the attention mechanism within the decoder underutilized. To address this, we propose a symmetric transformer learning network (STLNet) specifically tailored for remote sensing image CD tasks, constructed entirely using transformers. The STLNet is designed to leverage the intrinsic capability of transformers to model extensive long-range dependencies effectively. This approach significantly bolsters the extraction of distinctive global-level features, thereby facilitating the accurate delineation of CD regions. Initially, we utilize an adaptive multigrain encoder to extract feature information from bitemporal images, thereby honing the focus on changing targets and providing deeper and more comprehensive information. Subsequently, we adopt an effective decoder architecture comprised of transformer structures, namely, local gather decoder (LGD). The LGD employs a multilevel semantic feature integration from the encoder to augment feature representation and interdependencies, crucial for detailing small changed areas effectively via a hierarchical attentional fusion block. Ultimately, the detection of changes is based on the rich semantic information provided by the LGD, enabling us to achieve enhanced precision in our remote sensing CD efforts. Results show that the proposed STLNet achieved F1 scores of 92.32% on the LEVIR-CD dataset, 90.01% on the WHU-CD dataset, and 82.15% on the SYSU-CD dataset, surpassing mainstream CD methods.journal articl
アニメ チョウ バーチャル キャラクタ ノ ウゴキ ト ブキミサ ノ カンケイ ノ チョウサ
Get PDFメタバース空間のキャラクタやVTuberは，モーションキャプチャにより人の実際の動きをアニメ調のキャラクタに表現することができる．しかし本来のアニメ調のキャラクタは，リミテッドアニメーションや誇張された動きなどのアニメ特有の動きをしていることから，キャラクタの外見と動きの滑らかさの不一致によって不気味さが発生する可能性がある．本研究では，リアル調とアニメ調の外見と動作の組み合わせによる不気味さの関係性を調査する．conference pape
Cognitive modeling of human-robot interactions in traffic
No full textvideo/mp4Robots and autonomous vehicles increasingly rely on models of human behavior. However, models commonly used in robotics often lack in accuracy, transparency, and generalization. In this lecture, I will demonstrate how established models from cognitive science can help address these issues. I will illustrate how these models can be translated to human-robot interaction in traffic, which challenges need to be addressed in doing so, and how such modeling can contribute to development and assessment of autonomous vehicles.講演日: 2024年6月11日講演場所: エーアイ大講義室, AI Inc. Seminar Hall （L1）vide
Enforcement and Enlargement of the Saccharomyces cerevisiae Endoplasmic Reticulum through Artificial Evocation of the Unfolded Protein Response
No full textUpon dysfunction of the Endoplasmic Reticulum (ER), eukaryotic cells provoke a gene expression program, namely, the Unfolded Protein Response (UPR), leading to an increase in the size and function of the ER. In the yeast Saccharomyces cerevisiae, the UPR is modulated by the Hac1i protein, which is a transcription factor produced by ER stress. When the UPR is artifi cially triggered under non-stress conditions by artifi cial expression of the Hac1i protein, S. cerevisiae cells carry an enforced and enlarged ER, which allows us to obtain commercially valuable materials such as secretory proteins and functional lipids abundantly.journal articl
Dual-Responsive Poly(N-Isopropylacrylamide) Hydrogel Loaded with Poly-l-Lactic Acid Microparticles Encapsulating Boesenbergia Rotunda Extract for Enhanced Topical Delivery
Get PDFIn response to the pH and temperature alterations characteristic of atopic dermatitis (AD), we developed a dual pH- and thermoresponsive hydrogel as a drug delivery system model. The thermoresponsive polymeric-based hydrogel incorporated pH-responsive microparticles encapsulating betamethasone dipropionate (BD) and hexane extract derived from Boesenbergia rotunda. PLLA-V6-OEG3 microparticles were prepared using an emulsification-solvent evaporation method, and their physicochemical properties were subsequently determined. Monodisperse spherical and negatively charged microparticles were obtained in the range of 1$20134 μm (polydispersity index, PDI 600%) and swelling transition (>250%). The hydrogels were further investigated for ex vivo skin retention and permeation in AD-like mouse skin. The findings revealed that the formulated PNIPAM-BIS3 hydrogel loaded with MP HE BD microparticles facilitated the topical delivery of BD, resulting in a deposition of 31.01 ± 1.78 μg/cm2 on the mice’s skin. Remarkably, the addition of B. rotunda hexane extract, which mainly incorporated pinostrobin, was found to contribute to the topical release of BD. The PNIPAM-BIS3 hydrogel loaded with PLLA-V6-OEG3 microparticles supplemented with B. rotunda hexane extract holds promise as a smart dual-responsive drug carrier for managing AD skin conditions.journal articl