Substantial Leakage Research Articles

Inferring the distribution of the ionising photon escape fraction

The escape fraction of ionising photons from galaxies ($f_ esc $) is a key parameter for understanding how intergalactic hydrogen became reionised, but it remains mostly unconstrained. Measurements have been limited to the average value in galaxy ensembles and to handfuls of individual detections. To help understand which mechanisms govern ionising photon escape, here we infer the distribution of $f_ esc We developed a hierarchical Bayesian inference technique to estimate the population distribution of $f_ esc $ from the ratio of Lyman continuum to non-ionising UV flux measured from broadband photometry. We applied it to a sample of 148 $z 3.5$ star-forming galaxies from the VANDELS spectroscopic survey. We explored four physically motivated distributions: constant, log-normal, exponential, and bimodal, and recovered $ f_ esc for most models. We find the observations are best described by an exponential $f_ esc $ distribution with scale factor $ $. This indicates most galaxies in our sample exhibit very low escape fractions, while predicting substantial ionising photon leakage for only a few galaxies, implying a range of optical depths in the interstellar medium and/or time variability in ionising photon escape. We rule out a bimodal distribution at high significance, indicating that a purely bimodal model of ionising photon escape (due to very strong sightline and/or time variability) is not favoured. We compare our recovered exponential distribution with the SPHINX simulations and find that, while the simulation also predicts an exponential distribution, it significantly underpredicts our inferred mean. The distribution of $f_ esc $ can be a vital test for simulations in understanding ionising photon leakage, and is important to consider to gain a complete picture of reionisation.

Study on instability mechanisms and control of coal pillar spalling and coal crumbs leakage during working face crossing faults

The stability of coal pillars in fault areas is crucial for ensuring the safe passage of working faces. Based on field observations, frequent coal pillar spalling and substantial tectonic coal crumbs leakage, as well as tilting of hydraulic supports, are observed when working faces transition from primary coal to tectonic coal. To analyze the instability mechanisms behind these phenomena, this paper establishes a mechanical model of coal pillars in fault areas and analyzes the distribution of tectonic stresses and factors affecting the stability of coal pillars. The results indicate that horizontal tectonic stress adheres to an exponential function dependent on the angle factor, where (k0) is a parameter associated with the friction angle of the coal body, the dip angle of the fault, and the friction angle of the fault plane. The stability of coal pillars is influenced by factors such as roof and floor pressures, coal pillar integrity, mining height, and shield support force, with coal pillar integrity being the most critical. To ensure the smooth passage of working faces through faults, this study proposes a combined control technique of “inclined mining” and “grouting,” including reducing mining heights, adjusting the slope of working face advancement, and pre-grouting of coal pillars. Industrial experiments conducted on-site have shown improved integrity of tectonic coal, enabling the working face to pass through faults smoothly and significantly increasing production efficiency.

Optimal unilateral climate policy with carbon leakage at the extensive and the intensive margins

AbstractWe derive the optimal unilateral climate policy for an open economy with a domestic emissions target and aversion to carbon leakage, distinguishing between leakage at the extensive margin, where domestic firms relocate to foreign countries, and leakage at the intensive margin, where domestic firms lose world market shares. Implementing the optimal allocation requires several instruments including a lump‐sum location subsidy to counter leakage at the extensive margin. Simulations indicate substantial leakage at the extensive margin and a social welfare gain of around 0.3 percent of national income from our optimal leakage‐adjusted tax‐subsidy scheme compared to uniform carbon taxation.

Environmentally friendly production of petroleum systems with high CO2 content

Natural gas hydrates represents a huge source of energy. At the same time substantial leakages of natural gas from hydrates contributes significantly to climate changes. One of the most important reasons for these natural gas fluxes is leakage of seawater in to the hydrates from seafloor, through fracture systems. Hydrate dissociates if surrounding seawater is less than hydrate stability limit. Another interesting aspect of natural gas hydrates is the potential for safe CO2 storage. These different aspects of hydrates in natural sediments put demands on thermodynamic models. In addition to accurate description of pressure temperature hydrate stability there also a need to describe hydrate dissociation in concentration gradients towards surrounding water or surrounding gas as two examples. In this work we present new experimental data and an extensive thermodynamic model for hydrate. In contrast to conventional thermodynamic models for hydrate the model is consistent since all thermodynamic properties are derived from the Gibbs free energy. In this work we examine mixtures of CH4, C2H6, N2, CO2 from the China Sea and some synthetic mixtures, using this model. Maximum CO2 content in these mixtures are 60 mol% and the rest is dominated by CH4. Agreement between experimental data and model calculations are generally good and average deviations are below 5.5% for all the systems and conditions examined. Another aspect of the model is the ability for incorporation of effects of mineral surfaces. Specifically it is illustrated that adsorption of water on rust dominates liquid water drop out from gas as compared to water dew-point. Production of natural gas with such high CO2 content requires a strategy for CO2 separation and storage. It is proposed that the CH4 is separated from the C2H6, CO2 and N2 and cracked to H2 and CO2 using steam. Thermodynamic analysis indicates a significant potential for safe CO2 storage in natural gas hydrate and H2 as the only export product.

Orally Deliverable Microalgal-Based Carrier with Selenium Nanozymes for Alleviation of Inflammatory Bowel Disease.

Excessive reactive oxygen species (ROS) is a hallmark of both the onset and progression of inflammatory bowel disease (IBD), where a continuous cycle of ROS and inflammation drives the progression of diseases. The design of oral antioxidant nanoenzymes for scavenging ROS has emerged as a promising strategy to intervene in IBD. However, the practical application of these nanoenzymes is limited due to their single catalytical property and significantly impacted by substantial leakage in the upper gastrointestinal tract. This study introduces a novel oral delivery system, SP@CS-SeNPs, combining natural microalgae Spirulina platensis (SP), which possesses superoxide dismutase (SOD)-like activity, with chitosan-functionalized selenium nanoparticles (CS-SeNPs) that exhibit catalase-like activity. The SP@CS-SeNPs system leverages the dual catalytic capabilities of these components to initiate a cascade reaction that first converts superoxide anion radicals (O2•-) into hydrogen peroxide (H2O2), and then catalyzes the decomposition of H2O2 into water and oxygen. This system not only utilizes the resistance of the microalgae carrier to gastric acid and its efficient capture by intestinal villi, thereby enhancing intestinal distribution and retention but also demonstrates significant anti-inflammatory effects and effective repair of the damaged intestinal barrier in a colitis mice model. These results demonstrate that this oral delivery system successfully combines the features of microalgae and nanozymes, exhibits excellent biocompatibility, and offers a novel approach for antioxidant nanozyme intervention in IBD.

Quantitative insights into the mechanism of proton conduction and selectivity for the human voltage-gated proton channel Hv1

Human voltage-gated proton (hHv1) channels are crucial for regulating essential biological processes such as immune cell respiratory burst, sperm capacitation, and cancer cell migration. Despite the significant concentration difference between protons and other ions in physiological conditions, hHv1 demonstrates remarkable proton selectivity. Our calculations of single-proton, cation, and anion permeation free energy profiles quantitatively demonstrate that the proton selectivity of the wild-type channel originates from its strong proton affinity via the titration of the key residues D112 and D174, although the channel imposes similar kinetic blocking effects for protons compared to other ions. A two-proton knock-on model is proposed to mathematically explain the electrophysiological measurements of the pH-dependent proton conductance in the conductive state. Moreover, it is shown that the anion selectivity of the D112N mutant channel is tied to impaired proton transport and substantial anion leakage.

Ultrasound and x-ray imageable poloxamer-based hydrogel for loco-regional therapy delivery in the liver

Intratumoral injections have the potential for enhanced cancer treatment efficacy while reducing costs and systemic exposure. However, intratumoral drug injections can result in substantial off-target leakage and are invisible under standard imaging modalities like ultrasound (US) and x-ray. A thermosensitive poloxamer-based gel for drug delivery was developed that is visible using x-ray imaging (computed tomography (CT), cone beam CT, fluoroscopy), as well as using US by means of integrating perfluorobutane-filled microbubbles (MBs). MBs content was optimized using tissue mimicking phantoms and ex vivo bovine livers. Gel formulations less than 1% MBs provided gel depositions that were clearly identifiable on US and distinguishable from tissue background and with minimal acoustic artifacts. The cross-sectional areas of gel depositions obtained with US and CT imaging were similar in studies using ex vivo bovine liver and postmortem in situ swine liver. The gel formulation enhanced multimodal image-guided navigation, enabling fusion of ultrasound and x-ray/CT imaging, which may enhance targeting, definition of spatial delivery, and overlap of tumor and gel. Although speculative, such a paradigm for intratumoral drug delivery might streamline clinical workflows, reduce radiation exposure by reliance on US, and boost the precision and accuracy of drug delivery targeting during procedures. Imageable gels may also provide enhanced temporal and spatial control of intratumoral conformal drug delivery.

Ultrasound and x-ray imageable poloxamer-based hydrogel for loco-regional therapy delivery in the liver.

Intratumoral injections have the potential for enhanced cancer treatment efficacy while reducing costs and systemic exposure. However, intratumoral drug injections can result in substantial off-target leakage and are invisible under standard imaging modalities like ultrasound (US) and x-ray. A thermosensitive poloxamer-based gel for drug delivery was developed that is visible using x-ray imaging (computed tomography (CT), cone beam CT, fluoroscopy), as well as using US by means of integrating perfluorobutane-filled microbubbles (MBs). MBs content was optimized using tissue mimicking phantoms and ex vivo bovine livers. Gel formulations less than 1% MBs provided gel depositions that were clearly identifiable on US and distinguishable from tissue background and with minimal acoustic artifacts. The cross-sectional areas of gel depositions obtained with US and CT imaging were similar in studies using ex vivo bovine liver and postmortem in situ swine liver. The gel formulation enhanced multimodal image-guided navigation, enabling fusion of ultrasound and x-ray/CT imaging, which may enhance targeting, definition of spatial delivery, and overlap of tumor and gel. Although speculative, such a paradigm for intratumoral drug delivery might streamline clinical workflows, reduce radiation exposure by reliance on US, and boost the precision and accuracy of drug delivery targeting during procedures. Imageable gels may also provide enhanced temporal and spatial control of intratumoral conformal drug delivery.

High-performance Ga2O3 solar-blind UV photodetectors via film growth regulation and surface state engineering

Gallium oxide (Ga2O3) with a wide bandgap is emerging as one of the most promising candidates for solar-blind photodetectors (SBPDs). However, the practical application of Ga2O3-based SBPDs is impeded by substantial defects-related leakage currents, sluggish response speed, and high-cost, making their practical applications face great challenges. Here, we proposed strategic films growth regulation and surface state engineering to grow high-quality yet economical β-Ga2O3 films, thereby achieving high-performance SBPDs. High-resolution transmission electron microscopy revealed the presence of high-quality films with an extremely regular arrangement of β-Ga2O3 (2‾01) planes. The full width at half maximum and root mean square roughness values are 0.07° and 0.716 nm, respectively. The β-Ga2O3 films demonstrated a significant reduction in VO concentrations after O2/N2 plasma treatment. This process can effectively minimize thermal damage to the sample surface while retaining highly reactive free radicals. The photocurrents of devices can be further enhanced, leading to a larger PDCRs of 8.6 × 107, through N2 plasma treatment. Moreover, the films effectually suppress the persistent photoconductivity effect with τr and τd values of 5.31/0.97 s and 0.49/0.87 s before and after N2 plasma treatment, respectively. We have demonstrated the influence mechanism of O2/N2 plasma treatment on photoelectronic performance. This study provides a practical approach to growing high-quality β-Ga2O3 films and preparing high-performance but low-cost Ga2O3-based SBPDs.

Investigation antibacterial application and mechanism of the cyclodextrin-metal-organic framework loaded with gold nanoparticle

ABSTRACT The severe threat of microbial contamination to human life and health safety necessitates urgent research and development of antimicrobial materials capable of inhibiting or eradicating pathogens. Cyclodextrin metal-organic framework (CD-MOF) was utilized as a carrier to encapsulate gold nanoparticles (AuNPs), resulting in a composite material (Au@CD-MOF) that exhibited remarkable antibacterial properties. The antibacterial study revealed that Au@CD-MOF completely eradicated Staphylococcus aureus (S. aureus) and Listeria monocytogenes (L. monocytogenes) at a concentration of approximately 1 × 105 CFU/mL after 48 h and 36 h, respectively. Moreover, Au@CD-MOF also demonstrated the complete elimination of Escherichia coli O157:H7 (E. coli O157:H7), Pseudomonas aeruginosa PAO1 (P. aeruginosa PAO1), and Salmonella typhimurium (S. typhimurium) at a concentration of approximately 1 × 105 CFU/mL after 48 h. Moreover, the antibacterial mechanism of Au@CD-MOF was investigated using E. coli O157:H7 and S. aureus as model organisms. The findings revealed that Au@CD-MOF disrupted the integrity of cell membranes and diminished their potential, consequently impeding the normal functions of the bacteria. Additionally, the heightened permeability of cell membranes induced by Au@CD-MOF resulted in substantial leakage of nucleic acids and proteins, ultimately leading to bacterial eradication.

Data-driven modal analysis of turbulent momentum exchange and heat transfer in composite porous fluid systems

This paper investigates the dynamics governing turbulent momentum exchange and heat transfer between pore flow within porous media and the turbulent flow passing over it. Employing high-fidelity pore-scale large eddy simulation, our investigation explores the fundamental mechanisms driving these phenomena. Modal analysis based on snapshot proper orthogonal decomposition (POD) is employed to quantify the modes of interaction between porous and non-porous regions, providing a comprehensive understanding of the underlying processes. Spatial and temporal modes reveal the existence of localized flow structures at the pore scale, contributing to time-varying patterns of information exchange. At the commencement of the porous block, the mean flow (Mode = 0) from the porous to non-porous region is the dominant mechanism in momentum exchange and heat transfer. This mode facilitates convective heat transfer from the porous to the non-porous region through upward and forward flow movements, showcasing positive flow leakage. In addition to the mean flow, the turbulent flux inherent in alternate POD modes (Mode ≠ 0) plays a substantial role in information propagation, influencing diverse directions. Spatial modes, complemented by statistical analysis, uncover a significant likelihood of observing negative vertical velocity values in the wake of the porous ligaments at the porous-fluid interface, indicative of negative flow leakage. This negative flow leakage precisely corresponds to the local penetration of fluid from the non-porous region into the porous region. Furthermore, our study reveals that information exchange via turbulence fluctuations manifests through complex outward and inward interactions in regions characterized by substantial positive flow leakage. Notably, these regions exhibit a distinct tendency for high-momentum streamwise-oriented flow to migrate outward from the porous region into the non-porous region (outward interactions). Conversely, inward interactions arise in these regions when the instantaneous magnitude of positive flow leakage is smaller than the mean value of positive flow leakage, emphasizing the pulsating nature of positive flow leakage. Finally, the distribution of the Nusselt number highlights that more than 60% of total heat transfer occurs within the initial one-third of the porous block length. Significantly, a notable portion of the porous ligaments experiences insufficient cooling due to positive flow leakage, underlining the critical implications of these findings for the understanding of turbulent momentum exchange and heat transfer in a composite porous-fluid system.

LactoSpanks: A Collection of IPTG Inducible Promoters for the Commensal Lactic Acid Bacteria Lactobacillus gasseri.

Lactic acid bacteria (LAB) are important for many biotechnological applications such as bioproduction and engineered probiotics for therapy. Inducible promoters are key gene expression control elements, yet those available in LAB are mainly based on bacteriocin systems and have many drawbacks, including large gene clusters, costly inducer peptides, and little portability to in vivo settings. Using Lactobacillus gasseri, a model commensal bacteria from the human gut, we report the engineering of synthetic LactoSpanks promoters (Pls), a collection of variable strength inducible promoters controlled by the LacI repressor from E.coli and induced by isopropyl β-d-1-thiogalactopyranoside (IPTG). We first show that the Phyper-spank promoter from Bacillus subtilis is functional in L.gasseri, albeit with substantial leakage. We then construct and screen a semirational library of Phyper-spank variants to select a set of four IPTG-inducible promoters that span a range of expression levels and exhibit reduced leakages and operational dynamic ranges (from ca. 9 to 28 fold-change). With their low genetic footprint and simplicity of use, LactoSpanks will support many applications in L.gasseri, and potentially other lactic acid and Gram-positive bacteria.

Engineering of surface-altered polydopamine nanocomposites for successive drug release and in vivo antitumor effects in cervical cancer therapy: Investigation of antiproliferative effects and apoptosis

Extreme side effects and drug resistance are common with single-drug chemotherapy, reducing its efficacy as a treatment. Photothermal therapy (PTT) is a promising technique for treating cancer since it is noninvasive, can be controlled from a distance, and is highly targeted. Nanomedicines having synergistic chemo-photothermal characteristics may be more effective at combating tumors. To deliver gemcitabine (GEM) for targeted cancer therapy, we fabricated polydopamine (PDA)-loaded with polyethylene glycol and folic acid (FA). The findings demonstrated this delivery vehicle's narrow size distribution and nanoscale particle size. During the stability test, no substantial drug leakage or particle aggregation occurred. This system's photothermal conversion performance in near-infrared laser (NIR) irradiation was remarkable because of the PDA layer. HeLa cells were severely reduced in their ability to recover, and apoptosis was triggered in cancer cells after FA modification increased intracellular absorption of nanoparticles. To prevent drug-related cardiotoxicity, the nanoparticle group decreased GEM levels in the heart compared to the free GEM group. HeLa cervical carcinoma was reduced in an in vivo investigation by injecting fabricated nanoformulations intravaginally into female mice. Histological data from the NPs-treated mouse model demonstrates tumour reduction by H&E. Rats with tumors would benefit significantly from the suggested nanoformulation loaded with GEM. Using chemo-photothermal treatment, it was demonstrated in vitro and in vivo that cervical cancers could be totally removed, and the lives of survivors may be significantly prolonged.

Study on the Influence of KOH Wet Treatment on Red μLEDs

InGaN-based red micro-light-emitting diodes (µLEDs) of different sizes were prepared in this work. The red GaN epilayers were grown on 4-inch sapphire substrates through metal-organic chemical vapor deposition (MOCVD). Etching, sidewall treatment, and p- and n-contact deposition were involved in the fabrication process. Initially, the etching process would cause undesirable damage to the GaN sidewalls, which leads to an increase in leakage current. Hence, we employed KOH wet treatment to rectify the defects on the sidewalls and conducted a comparative and systematic analysis of electrical as well as optical properties. We observed that the µLEDs with a size of 5 µm exhibited a substantial leakage current, which was effectively mitigated by the application of KOH wet treatment. In terms of optical performance, the arrays with KOH demonstrated improved light output power (LOP). Additionally, while photoelectric performance exhibited a decline with increased current density, the devices treated with KOH consistently outperformed their counterparts in terms of optoelectronic efficiency. It is noteworthy that the optimized devices displayed enhanced photoelectric characteristics without significantly altering their original peak wavelength and FWHM. Our findings point to the elimination of surface non-radiative recombination by KOH wet treatment, thereby enhancing the performance of small-sized red µLEDs, which has significant potential in realizing full-color micro-displays in near-eye projection applications.

Deep convolutional and conditional neural networks for large-scale genomic data generation.

Applications of generative models for genomic data have gained significant momentum in the past few years, with scopes ranging from data characterization to generation of genomic segments and functional sequences. In our previous study, we demonstrated that generative adversarial networks (GANs) and restricted Boltzmann machines (RBMs) can be used to create novel high-quality artificial genomes (AGs) which can preserve the complex characteristics of real genomes such as population structure, linkage disequilibrium and selection signals. However, a major drawback of these models is scalability, since the large feature space of genome-wide data increases computational complexity vastly. To address this issue, we implemented a novel convolutional Wasserstein GAN (WGAN) model along with a novel conditional RBM (CRBM) framework for generating AGs with high SNP number. These networks implicitly learn the varying landscape of haplotypic structure in order to capture complex correlation patterns along the genome and generate a wide diversity of plausible haplotypes. We performed comparative analyses to assess both the quality of these generated haplotypes and the amount of possible privacy leakage from the training data. As the importance of genetic privacy becomes more prevalent, the need for effective privacy protection measures for genomic data increases. We used generative neural networks to create large artificial genome segments which possess many characteristics of real genomes without substantial privacy leakage from the training dataset. In the near future, with further improvements in haplotype quality and privacy preservation, large-scale artificial genome databases can be assembled to provide easily accessible surrogates of real databases, allowing researchers to conduct studies with diverse genomic data within a safe ethical framework in terms of donor privacy.

Leveraging opportunity of low carbon transition by super-emitter cities in China

Chinese cities are core in the national carbon mitigation and largely affect global decarbonisation initiatives, yet disparities between cities challenge country-wide progress. Low-carbon transition should preferably lead to a convergence of both equity and mitigation targets among cities. Inter-city supply chains that link the production and consumption of cities are a factor in shaping inequality and mitigation but less considered aggregately. Here, we modelled supply chains of 309 Chinese cities for 2012 to quantify carbon footprint inequality, as well as explored a leverage opportunity to achieve an inclusive low-carbon transition. We revealed significant carbon inequalities: the 10 richest cities in China have per capita carbon footprints comparable to the US level, while half of the Chinese cities sit below the global average. Inter-city supply chains in China, which are associated with 80% of carbon emissions, imply substantial carbon leakage risks and also contribute to socioeconomic disparities. However, the significant carbon inequality implies a leveraging opportunity that substantial mitigation can be achieved by 32 super-emitting cities. If the super-emitting cities adopt their differentiated mitigation pathway based on affluence, industrial structure, and role of supply chains, up to 1.4 Gt carbon quota can be created, raising 30% of the projected carbon quota to carbon peak. The additional carbon quota allows the average living standard of the other 60% of Chinese people to reach an upper-middle-income level, highlighting collaborative mechanism at the city level has a great potential to lead to a convergence of both equity and mitigation targets.

Low-leakage epitaxial graphene field-effect transistors on cubic silicon carbide on silicon

Epitaxial graphene (EG) on cubic silicon carbide (3C-SiC) on silicon holds the promise of tunable nanoelectronic and nanophotonic devices, some uniquely unlocked by the graphene/cubic silicon carbide combination, directly integrated with the current well-established silicon technologies. Yet, the development of graphene field-effect devices based on the 3C-SiC/Si substrate system has been historically hindered by poor graphene quality and coverage, as well as substantial leakage issues of the heteroepitaxial system. We address these issues by growing EG on 3C-SiC on highly resistive silicon substrates using an alloy-mediated approach. In this work, we demonstrate a field-effect transistor based on EG/3C-SiC/Si with gate leakage current 6 orders of magnitude lower than the drain current at room temperature, which is a vast improvement on the current literature, opening the possibility for dynamically tunable nanoelectronic and nanophotonic devices on silicon at the wafer level.

Abstract LB101: Cell-generated IL12 combined with PD-1 inhibition produces local and abscopal immune activation to eradicate metastatic melanoma and pancreatic cancer

Abstract Background: Cytokines have been FDA approved for cancer immunotherapy for treatment of metastatic melanoma and renal carcinoma for over 30 years (1, 2). To overcome stability and toxicity limitations seen with high dose cytokine immunotherapy, we developed a delivery platform, called cytokine factories, composed of genetically engineered epithelial cells encapsulated in biocompatible polymers. These clinically translatable cytokine factories are able to safely deliver high local doses of pro-inflammatory cytokines, such as interleukin-12 (IL12), and allow for controlled and predictable dosing in vivo. Results: Tumor-adjacent administration of IL12-based cytokine factories in vivo created a high local cytokine concentration (IP space) without substantial leakage into the systemic circulation. In addition, administration of cytokine factories in combination with anti-PD1 checkpoint inhibitors caused reduction of tumor burden by over 60% when delivered as a monotherapeutic to mice with metastatic melanoma (3). Further, when administered in combination with local anti-PD1 checkpoint inhibitors, these cytokine factories led to reduction of intraperitoneal tumor burden by over 80% after only 10 days of treatment. Finally, we evaluated the ability of this therapy to treat pancreatic tumors which are notoriously known to be resistant to immunotherapy. We found that the median survival for control animals was 45 days. However, 8/8 of animals treated with IL12 cytokine factories survived throughout the duration of the study (110 days), demonstrating a significant extension of overall survival time. Conclusions: Our findings demonstrate efficacy of cytokine factories as single agent and combination therapeutics in preclinical animal models and provide rationale for future clinical testing for the treatment of metastatic peritoneal cancers in humans.

Alternative carbon border adjustment mechanisms in the European Union and international responses: Aggregate and within-coalition results

The European Union (EU) recently declared its intention to implement a carbon border adjustment mechanism (CBAM) to address carbon leakage and competitiveness concerns associated with elevated climate ambitions in its Green Deal. Current literature points to uncertainties regarding the CBAM’s effectiveness and compatibility with international trade rules. This study numerically evaluates how alternative EU CBAM designs under various international reactions affect global and regional GHG emissions, outputs and trade flows.Our modeling results confirm substantial carbon leakages and output reductions in the EU’s emissions-intensive trade-exposed (EITE) sectors when implementing the Green Deal. We find that the design of the CBAM matters: while a “non-discriminatory” CBAM based on the EU’s own scope 1 emission intensities fails to effectively reduce leakages, an ‘aggressive’ CBAM based on exporters’ scope 1 & 2 emission intensities can achieve such goal (albeit with potentially high implementation cost). International retaliations by non-EU countries can only partially offset the EU’s gains from the ‘aggressive’ CBAM, while their cooperation can result in smaller losses to the EU EITE sectors and lower leakages. Finally, the CBAM cannot change within-EU imbalances in the EITE sectors, as several EU members lose EITE outputs consistently in all scenarios with and without retaliations.

Titan: Security Analysis of Large-Scale Hardware Obfuscation Using Graph Neural Networks

Hardware obfuscation is a prominent design-for-trust solution that thwarts intellectual property (IP) piracy and reverse-engineering of integrated circuits (ICs). Researchers have proposed several large-scale obfuscation techniques that achieve high output corruption—thus offering resilience against seminal attacks along with acceptable power, performance, and area overheads. However, the research community has primarily evaluated hardware obfuscation on relatively small scales of obfuscation (i.e., a fixed number of obfuscated components). Moreover, prior art caters toward specific schemes based either on gate obfuscation or interconnect obfuscation, i.e., two prominent types of hardware obfuscation. The former shortcoming suggests focusing on large-scale obfuscation schemes, and the latter suggests the need for a holistic assessment framework. In this work, we propose Titan, a holistic framework considering large-scale gate and interconnect obfuscation schemes. More specifically, we propose a graph neural network (GNN)-based attack framework that is trained to exploit structural and functional properties of any secured circuit to recover its obfuscated components. We evaluate Titan on various obfuscation schemes, considering selected ITC-99 benchmarks with up to 50% obfuscation scale, i.e., up to 21,326 obfuscated components. We observe a substantial information leakage through structural and functional properties of secured designs even for large-scale obfuscation. We quantify the information leakage in two ways: first, an average reduction of Hamming distance (HD, a well-established metric for attack evaluation) by 23.27 and 16.19 percentage points over the baseline of random guessing for gate and interconnect obfuscation, respectively; second, an average recovery of 63.40% and 77.94% of obfuscated components for gate and interconnect obfuscation, respectively. Importantly, these results are superior to six state-of-the-art attacks. We will open-source our framework and associated artifacts to enable reproducibility and foster future work.