Smaller Exchanges, Larger Regimes: How Trading in Small, Interdependent Units Affects Treaty Stability

This Comment explores how exchanging in smaller, interdependent units of entitlement during treaty negotiation helps build consensus for large treaty regimes and creates incentives for maintaining stable, cooperative relationships in the long run. The existing literature related to this topic takes three approaches. Prior literature on the concept of equity has focused mostly on the division problem: how to allocate indivisible goods and how to create a proportionality or prioritization system that appeals to parties\u27 intuitive understandings of fairness. Prior economics and game theory literature has largely focused on explaining how cooperation and coalitions affect the feasibility of discrete transactions, such as spot contracts. Prior literature on international law tends to limit itself to political analysis on how issue linkages have facilitated consensus during treaty negotiations. This Comment tries to link these three approaches together to explain the economic incentives behind a general international phenomenon: the tendency to negotiate in more narrowly defined entitlements (smaller units) to build consensus for ambitious, comprehensive treaties that stretch over several regulatory regimes (greater interdependence). This approach differs from earlier approaches in equity literature because it proposes that parties want more than fair division from a discrete transaction. It differs from previous approaches in contract theory because the parties in focus here are states, who all have incentives to create agreements for the long-term5 and institutionalize norms that incentivize cooperation. It differs in focus from prior literature in international law in that it tries to generalize a larger economic principle behind why linkages help treaties succeed

L2 CONFIDENCE DEVELOPMENT OF ELF INTERNATIONAL STUDENTS IN TAIWAN

Second Language (L2) confidence is considered an affective variable for L2 users to claim ownership of English. However, the findings of previous studies could not be generalized to international students in a non-English-speaking context like Taiwan since English mainly functions as a lingua franca among individuals with diverse first languages. This study investigated three international students' development of L2 confidence while they were studying in Taiwanese universities. Qualitative semi-structured interviews were conducted on personal background, experiences, critical events, and personal evaluation of their L2 confidence. The interviews were transcribed, coded, and then analyzed in thematic narratives. Specific situations that affected this dynamic L2 confidence development were identified and probed deeper. The findings showed that the three participants seemed more confident in an English as Lingua Franca (ELF) community where local students were absent. Native Speaker (NS)-norms still dominated their English journey, and their confidence level greatly hinged on their NS-based proficiency. The ideology of following the NS English model threatened L2 confidence in ELF interactions. Furthermore, the participants’ perception of their nonnative speaker (NNS) identity might make them less confident. The findings contribute to the pedagogical implications for L2 learners, users and teachers

The crystal structure of the DNase domain of colicin E7 in complex with its inhibitor Im7 protein

AbstractBackground: Colicin E7 (ColE7) is one of the bacterial toxins classified as a DNase-type E-group colicin. The cytotoxic activity of a colicin in a colicin-producing cell can be counteracted by binding of the colicin to a highly specific immunity protein. This biological event is a good model system for the investigation of protein recognition.Results: The crystal structure of a one-to-one complex between the DNase domain of colicin E7 and its cognate immunity protein Im7 has been determined at 2.3 Å resolution. Im7 in the complex is a varied four-helix bundle that is identical to the structure previously determined for uncomplexed Im7. The structure of the DNase domain of ColE7 displays a novel α/β fold and contains a Zn2+ ion bound to three histidine residues and one water molecule in a distorted tetrahedron geometry. Im7 has a V-shaped structure, extending two arms to clamp the DNase domain of ColE7. One arm (α1∗–loop12–α2∗; where ∗ represents helices in Im7) is located in the region that displays the greatest sequence variation among members of the immunity proteins in the same subfamily. This arm mainly uses acidic sidechains to interact with the basic sidechains in the DNase domain of ColE7. The other arm (loop 23–α3∗–loop 34) is more conserved and it interacts not only with the sidechain but also with the mainchain atoms of the DNase domain of ColE7.Conclusions: The protein interfaces between the DNase domain of ColE7 and Im7 are charge-complementary and charge interactions contribute significantly to the tight and specific binding between the two proteins. The more variable arm in Im7 dominates the binding specificity of the immunity protein to its cognate colicin. Biological and structural data suggest that the DNase active site for ColE7 is probably near the metal-binding site

DRAINCLoG: Detecting Rogue Accounts with Illegally-obtained NFTs using Classifiers Learned on Graphs

As Non-Fungible Tokens (NFTs) continue to grow in popularity, NFT users have become targets of phishing attacks by cybercriminals, called \textit{NFT drainers}. Over the last year, \$100 million worth of NFTs were stolen by drainers, and their presence remains a serious threat to the NFT trading space. However, no work has yet comprehensively investigated the behaviors of drainers in the NFT ecosystem. In this paper, we present the first study on the trading behavior of NFT drainers and introduce the first dedicated NFT drainer detection system. We collect 127M NFT transaction data from the Ethereum blockchain and 1,135 drainer accounts from five sources for the year 2022. We find that drainers exhibit significantly different transactional and social contexts from those of regular users. With these insights, we design \textit{DRAINCLoG}, an automatic drainer detection system utilizing Graph Neural Networks. This system effectively captures the multifaceted web of interactions within the NFT space through two distinct graphs: the NFT-User graph for transaction contexts and the User graph for social contexts. Evaluations using real-world NFT transaction data underscore the robustness and precision of our model. Additionally, we analyze the security of \textit{DRAINCLoG} under a wide variety of evasion attacks.Comment: To appear in NDSS 202

Progress on the Low-Latency Inspiral Gravitational Wave Detection algorithm known as SPIIR

Low-latency event triggers to signify the presence of gravitational waves from coalescing binaries will be required to make prompt electromagnetic follow-up observations of electromagnetic counterparts. We present the recent progress made on implementing the time-domain low-latency detection algorithm known as summed parallel infinite impulse response (SPIIR) filtering into a real gravitational wave search pipeline

Histopathological analysis of vascular malformations

OBJECTIVE: To propose and develop a histopathological criteria to help diagnose vascular malformations. METHODS: All patients who underwent surgical resection and had a confirmed histopathological diagnosis of vascular malformations from 01 March 2018-26 February 2020 were included. A criteria based on 10 parameters was developed to help diagnose vascular malformations. Discrepancies between clinical and histopathological diagnosis were evaluated. RESULTS: A total of 18 cases were identified. There was a discrepancy between the clinical diagnosis and the initially reported histopathological diagnosis in 16 cases (88.9%). This was reduced to 7 (38.9%) and 6 cases (33.3%) with first and second time revised histopathological analysis using proposed criteria. CONCLUSIONS: The discrepancy between clinical and histopathological diagnoses of vascular malformations has highlighted the requirement of an agreed criteria for histopathologists to help formulate their diagnosis. The proposed criteria may be used as a guide in addressing this and guide treatment and improve clinical practice

A structural and physical study of sol–gel methacrylate–silica hybrids: intermolecular spacing dictates the mechanical properties

Sol–gel hybrids are inorganic/organic co-networks with nanoscale interactions between the components leading to unique synergistic mechanical properties, which can be tailored, via a selection of the organic moiety. Methacrylate based polymers present several benefits for class II hybrids (which exhibit formal covalent bonding between the networks) as they introduce great versatility and can be designed with a variety of chemical side-groups, structures and morphologies. In this study, the effect of high cross-linking density polymers on the structure–property relationships of hybrids generated using poly(3-trimethoxysilylpropyl methacrylate) (pTMSPMA) and tetraethyl orthosilicate (TEOS) was investigated. The complexity and fine scale of the co-network interactions requires the development of new analytical methods to understand how network evolution dictates the wide-ranging mechanical properties. Within this work we developed data manipulation techniques of acoustic-AFM and solid state NMR output that provide new approaches to understand the influence of the network structure on the macroscopic elasticity. The concentration of pTMSPMA in the silica sol affected the gelation time, ranging from 2 h for a hybrid made with 75 wt% inorganic with pTMSPMA at 2.5 kDa, to 1 minute for pTMSPMA with molecular weight of 30 kDa without any TEOS. A new mechanism of gelation was proposed based on the different morphologies derived by AC-AFM observations. We established that the volumetric density of bridging oxygen bonds is an important parameter in structure/property relationships in SiO2 hybrids and developed a method for determining it from solid state NMR data. The variation in the elasticity of pTMSPMA/SiO2 hybrids originated from pTMSPMA acting as a molecular spacer, thus decreasing the volumetric density of bridging oxygen bonds as the inorganic to organic ratio decreased

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction