Miracle-dz/UniFAR-FTUs huggingface dataset:
How to Validate a Verification?

This paper introduces signature validation , a primitive allowing any third party T (Théodore) to verify that a verifier V (Vadim) computationally verified a signature s on a message m issued by a signer S (Sarah). A naive solution consists in sending by Sarah x = { m, σ s } where σ s is Sarah’s signature on m and have Vadim confirm reception by a signature σ v on x . Unfortunately, this only attests proper reception by Vadim, i.e. that Vadim could have checked x and not that Vadim actually verified x . By “actually verifying” we mean providing a proof or a convincing argument that a program running on Vadim’s machine checked the correctness of x . This paper proposes several solutions for doing so, thereby providing a useful building-block in numerous commercial and legal interactions for proving informed consent.
Understanding User-Perceived Security Risks and Mitigation Strategies in the Web3 Ecosystem

The advent of Web3 technologies promises unprecedented levels of user control and autonomy. However, this decentralization shifts the burden of security onto the users, making it crucial to understand their security behaviors and perceptions. To address this, our study introduces a comprehensive framework that identifies four core components of user interaction within the Web3 ecosystem: blockchain infrastructures, Web3-based Decentralized Applications (DApps), online communities, and off-chain cryptocurrency platforms. We delve into the security concerns perceived by users in each of these components and analyze the mitigation strategies they employ, ranging from risk assessment and aversion to diversification and acceptance. We further discuss the landscape of both technical and human-induced security risks in the Web3 ecosystem, identify the unique security differences between Web2 and Web3, and highlight key challenges that render users vulnerable, to provide implications for security design in Web3.
RMNAS: A Multimodal Neural Architecture Search Framework For Robust Multimodal Sentiment Analysis

Multimodal sentiment analysis (MSA) finds extensive applications, but the presence of missing modalities in real-world environments requires researchers to enhance the robustness of models, often demanding significant efforts. Multimodal neural architecture search (MNAS) is a more efficient approach. However, current MNAS methods, while effective in integrating multi-level information, are incapable of simultaneously searching for optimal operations to extract modality-specific information. This weakens the robustness of the model in addressing diverse scenarios. Moreover, these methods also fall short in enhancing the capture of emotional cues. In this paper, we propose robust-sentiment multimodal neural architecture search (RMNAS) framework. Specifically, we utilize the Transformer as a unified architecture for various modalities and incorporate a search for token mixers to enhance the encoding capacity of individual modalities and improve robustness across diverse scenarios. Subse-quently, we leverage BM-NAS to integrate multi-level information. Furthermore, we incorporate local sentiment variation trends to guide the token mixers computation, enhancing the model’s ability to capture sentiment context. Experimental results demonstrate that our approach outperforms or competitively matches existing state-of-the-art approaches in incomplete multimodal learning, both in sentence-level and dialogue-level MSA tasks, without the need for knowledge of incomplete learning.
Clinical Anesthesia and Analgesia in Fish

Fish have become a popular experimental model and companion animal, and are also farmed and caught for food. Thus, surgical and invasive procedures in this animal group are common, and this review will focus on the anesthesia and analgesia of fish. A variety of anesthetic agents are commonly applied to fish via immersion. Correct dosing can result in effective anesthesia for acute procedures as well as loss of consciousness for surgical interventions. Dose and anesthetic agent vary between species of fish and are further confounded by a variety of physiological parameters (e.g., body weight, physiological stress) as well as environmental conditions (e.g., water temperature). Combination anesthesia, where 2 anesthetic agents are used, has been effective for fish but is not routinely used because of a lack of experimental validation. Analgesia is a relatively underexplored issue in regards to fish medicine. However, recent studies have investigated opioid agents, nonsteroidal antiinflammatory drugs, and local anesthetics to determine their efficacy in minimizing pain and discomfort. The opioid morphine and the local anesthetic lidocaine do have significant effectiveness in reducing pain-related responses in rainbow trout (Oncorhynchus mykiss). Studies aimed at developing reliable analgesic protocols should explore a wide range of analgesic drug classes in several fish species. Copyright 2012 Elsevier Inc. All rights reserved.
Fast and scalable packet classification using perfect hash functions

Packet classification is an important operation for applications such as routers, firewalls or intrusion detection systems. Many algorithms and hardware architectures for packet classification have been created, but none of them can compete with the speed of TCAMs in the worst case. We propose new hardware-based algorithm for packet classification. The solution is based on problem decomposition and is aimed at the highest network speeds. A unique property of the algorithm is the constant time complexity in terms of external memory accesses. The algorithm performs exactly two external memory accesses to classify a packet. Using FPGA and one commodity SRAM chip, a throughput of 150 million packets per second can be achieved. This makes throughput of 100 Gbps for the shortest packets. Further performance scaling is possible with more or faster SRAM chips.
The ExoMars Spectral Tool (ExoSpec): an image analysis tool for ExoMars 2020 PanCam imagery

The upcoming launch of the European Space Agency (ESA) ExoMars 2020 rover signals a need for an analysis tool to be created which can exploit the multi- and hyperspectral data that will be returned by its Panoramic Camera (PanCam), Infrared Spectrometer for Mars (ISEM), and Close-UP Imager (CLUPI) instruments. Data processed by this analysis tool will be invaluable in (i) characterising the geology local to the ExoMars rover, (ii) relating ground-based observations to orbital Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data, (iii) detecting evidence of past habitability on Mars, and (iv) identifying drilling locations. PanCam, ISEM, and CLUPI offer spectral analysis capabilities in both spatial (140-1310 microns/pixel at 2 m working distance) and spectral (440-3300 nm) dimensions. We have developed the ExoMars Spectral Tool (ExoSpec) which functions as a GUI-based extension to ENVI + IDL and performs steps from image import and compilation into ENVI . dat format, flat-fielding, radiometric correction, radiance-toreflectance (R*) corrections using the in-scene Gretag MacBeth ColorCheckerTM, and calculation of spectral parameters. We demonstrate the functionality of ExoSpec at its current stage of development and illustrate its utility with results from field expeditions to Mars analogue terrains in: (i) geothermally altered basalts in N´amafjall, Iceland, and (ii) layered alluvial plains deposits in Hanksville, USA, using ExoMars PanCam, ISEM, and CLUPI emulator instruments.
Diversity of Diatom epilithons and quality of water from the subbasin of Oued Mina (district of Tiaret, Algeria)

After two years of work, we have explored most of water systems of the western region of Tiaret areas; represented mainly by the Oued Mina and Oued Louhou. The study started with a sampling, executed successively during Autumn and Spring, with the aim to identify the diatomic flora on the first part; and to analyze the ecology of these diatoms on the other part, regarding the Environmental factors through canonical correspondence analysis in order to estimate the organic pollution index. Our results highlighted 104 inventoried species, distributed on 20 different families, with 13 new taxa as a new record in Algeria: Brachysira microcephala, Eunotia cataractarum, Hippodonta capitata, Luticola kotschyi, Luticola nivalis Neidium binodeforme, Neidium ampliatum, Neidium dubium, Nitzschia bita, Nitzschia sinuata var. Tabellaria. Pinnularia obscura, Stauroneis gracilis and Surirella crumena. Otherwise, the calculation of the Organic Pollution Index OPI along the describing stations shows a degraded condition of the quality of water in Oued Mina, due to the discharge of domestic and industrial waste water from agglomerations. Four functional groups of the diatoms were revealed. A functional group A is presented by 21 species. The high trophy preference is a most important ecological property of the functional group A. Species which constitute this functional group are mainly eutraphentic. A functional group B is presented by 10 species. Species which constitute this functional group are mainly acidophilous. A functional group C is presented by 20 species. The preference of the low nitrogen level is a most important ecological property of the functional group C. A functional group D is presented by 8 species. Species which constitute this functional group are mainly facultatively nitrogen-heterotrophic taxa needing periodically elevated concentration of organically bound nitrogen.
Hungaria Asteroid Region Telescopic Spectral Survey (HARTSS): Establishing Asteroid-Meteorite Connections Between Hungaria Asteroids and Meteorites of the Acapulcoite-Lodranite Clan

The Hungaria asteroids remain as survivors of late giant planet migration that destabilized a now extinct inner portion of the primordial asteroid belt and left in its wake the current resonance structure of the Main Belt. In this scenario, the Hungaria region represents a “purgatory” for the closest, preserved samples of the asteroidal material from which the terrestrial planets accreted. Deciphering the surface composition of these unique samples may provide constraints on the nature of the primordial building blocks of the terrestrial planets. We have undertaken an observational campaign entitled the Hungaria Asteroid Region Telescopic Spectral Survey (HARTSS) to record near-infrared (NIR) reflectance spectra in order to characterize their taxonomy, surface mineralogy, and potential meteorite analogs. The overall objective of HARTSS is to evaluate the compositional diversity of asteroids located throughout the Hungaria region. This region harbors a collisional family of Xe-type asteroids, which are situated among a background (i.e., non-family) of predominantly S-complex asteroids. In order to assess the compositional diversity of the Hungaria region, we have targeted background objects during Phase I of HARTSS. Collisional family members likely reflect the composition of one original homogeneous parent body, so we have largely avoided them in this phase. We have employed NIR instruments at two ground-based telescope facilities: the NASA Infrared Telescope Facility (IRTF), and the Telescopio Nazionale Galileo (TNG). Our data set includes the NIR spectra of 42 Hungaria asteroids (36 background; 6 family). We find that stony Scomplex asteroids dominate the Hungaria background population (29/36 objects; ~80%). Ccomplex asteroids are uncommon (2/42; ~5%) within the Hungaria region. Background Scomplex objects exhibit considerable spectral diversity as band parameter measurements of diagnostic absorption features near 1and 2-μm indicate that several different S-subtypes are represented therein, which translates to a variety of surface compositions. We identify the Gaffey S-subtype (Gaffey et al. [1993]. Icarus 106, 573–602) and potential meteorite analogs for 24 of these S-complex background asteroids. Additionally, we estimate the olivine and orthopyroxene mineralogy for 18 of these objects using spectral band parameter analysis established from laboratory-based studies of ordinary chondrite meteorites. Nine of the asteroids have band parameters that are not consistent with ordinary chondrites. We compared these to the band parameters measured from laboratory VIS+NIR spectra of six primitive achondrite (acapulcoitelodranite) meteorites. These comparisons suggest that two main meteorite groups are represented
Modulated oscillations in many dimensions

Modulated oscillations are described via their time-varying amplitude and frequency. For multivariate signals, there is structure in the signal beyond this local amplitude and frequency defined for each signal component, in turn describing the commonality of the components. The multivariate structure encodes how the common oscillation is present in each component signal. This structure will also be evolving. I review the special case of the representation of both bivariate and trivariate oscillations. Additionally, existing results on the general multivariate oscillation are covered. I discuss the difference between a model of a multivariate oscillation compared with other common signal models of phenomena observed in several channels, and how their properties are different. I show how for the multivariate signal the global dimensionality of the signal is built up from local one-dimensional contributions, and introduce the purely unidirectional signal, to quantify how any given signal is different from the closest such signal. I illustrate the properties of the derived representation of the multivariate signal with synthetic examples, and discuss the representation of data from observations in physical oceanography.
Accurate Reconstruction of the Temporal Order of Mutations in Neoplastic Progression

The canonical route from normal tissue to cancer occurs through sequential acquisition of somatic mutations. Many studies have constructed a linear genetic model for tumorigenesis using the genetic alterations associated with samples at different stages of neoplastic progression from cross-sectional data. The common interpretation of these models is that they reflect the temporal order within any given tumor. Linear genetic methods implicitly neglect genetic heterogeneity within a neoplasm; each neoplasm is assumed to consist of one dominant clone. We modeled neoplastic progression of colorectal cancer using an agent-based model of a colon crypt and found clonal heterogeneity within our simulated neoplasms, as observed in vivo. Just 7.3% of cells within neoplasms acquired mutations in the same order as the linear model. In 41% of the simulated neoplasms, no cells acquired mutations in the same order as the linear model. We obtained similarly poor results when comparing the temporal order with oncogenetic tree models inferred from cross-sectional data. However, when we reconstructed the cell lineage of mutations within a neoplasm using several biopsies, we found that 99.7% cells within neoplasms acquired their mutations in an order consistent with the cell lineage mutational order. Thus, we find that using cross-sectional data to infer mutational order is misleading, whereas phylogenetic methods based on sampling intratumor heterogeneity accurately reconstructs the evolutionary history of tumors. In addition, we find evidence that disruption of differentiation is likely the first lesion in progression for most cancers and should be one of the few regularities of neoplastic progression across cancers. Cancer Prev Res; 4(7); 1135–44. ©2011 AACR.
FrameSLAM: From Bundle Adjustment to Real-Time Visual Mapping

Many successful indoor mapping techniques employ frame-to-frame matching of laser scans to produce detailed local maps as well as the closing of large loops. In this paper, we propose a framework for applying the same techniques to visual imagery. We match visual frames with large numbers of point features, using classic bundle adjustment techniques from computational vision, but we keep only relative frame pose information (a skeleton). The skeleton is a reduced nonlinear system that is a faithful approximation of the larger system and can be used to solve large loop closures quickly, as well as forming a backbone for data association and local registration. We illustrate the workings of the system with large outdoor datasets (10 km), showing large-scale loop closure and precise localization in real time.
Examining the Risk of Cardiovascular Disease in Patients with Psoriasis: A Critical Review

Background: Increased prevalence of cardiovascular disease (CVD) in psoriasis patients could be due to a greater prevalence of traditional cardiovascular (CV) risk factors or increased inflammatory disease burden. Objective: To critically evaluate evidence on the etiology and magnitude of CV risk in psoriasis patients. Methods: A total of 497 articles were identified for review through a PubMed search using the terms “CVD and psoriasis”; 43 were selected. Data measuring the risk of comorbidities and CV risk factors in psoriasis were retrieved. Results: Psoriasis patients have an increased prevalence of CV risk factors. Evidence suggests an increased risk of CV morbidity and mortality associated with psoriasis itself. Risk estimates vary across studies (OR range 1.13–6.48), possibly due to heterogeneous study design and incomplete data. Conclusion: Although additional data are required, increased awareness of the association of psoriasis with CV risk factors could lead to early diagnosis and treatment of comorbidities, with resultant improvement in morbidity and mortality.
Intrusion Detection System Intended for Multigigabit Networks

Network intrusion detection systems (IDS) are becoming an important tool for securing critical information and infrastructure. Current software-based IDS often fails to keep up with high-speed network links so a hardware based IDS is requested. This paper deals with design and implementation of complete hardware accelerated IDS solution based on field-programmable gate array (FPGA). Core generator for automatic mapping of IDS rules to FPGA logic was designed to assure fast packet classification and high speed pattern matching. Proposed architecture has been evaluated on a COMB06X card with FPGA Virtex-II Pro. Using COMB06X card theoretical throughput 6.4 Gbps was achieved for all Snort rules. The designed system can be configured by rules described in Snort format using web interface.
Cache-aware user association in backhaul-constrained small cell networks

Anticipating multimedia file requests via caching at the small cell base stations (SBSs) of a cellular network has emerged as a promising technique for optimizing the quality of service (QoS) of wireless user equipments (UEs). However, developing efficient caching strategies must properly account for specific small cell constraints, such as backhaul congestion and limited storage capacity. In this paper, we address the problem of devising a user-cell association, in which the SBSs exploit caching capabilities to overcome the backhaul capacity limitations and enhance the users' QoS. In the proposed approach, the SBSs individually decide on which UEs to service based on both content availability and on the data rates they can deliver, given the interference and backhaul capacity limitations. We formulate the problem as a one-to-many matching game between SBSs and UEs. To solve this game, we propose a distributed algorithm, based on the deferred acceptance scheme, that enables the players (i.e., UEs and SBSs) to self-organize into a stable matching, in a reasonable number of algorithm iterations. Simulation results show that the proposed cell association scheme yields significant gains, reaching up to 21% improvement compared to a traditional cell association techniques with no caching considerations.
Partial Purification and Characterization of Arf-sensitive Phospholipase D from Porcine Brain (*)

Phospholipase D (PLD) activity from membranes of cultured cells can be activated by guanosine 5′-O-(3-thiotriphosphate) and the small GTP-dependent protein, Arf. While this activity was readily apparent in membranes from HL60 cells, it was much lower or not observable in membranes from various mammalian tissues. However, extraction of porcine brain membranes with detergent and subsequent chromatography with SP-Sepharose revealed a large peak of Arf-sensitive PLD activity. This activity has been enriched through several steps of chromatography and characterized with respect to size, nucleotide specificity, and sensitivity to different Arf and Arf-like proteins. Hydrodynamic analysis indicated that the enriched PLD had an s of 5.1 and a Stokes radius of 4.3 nm. These parameters indicate that the enzyme has an apparent molecular mass of 95,000 Da. Effective stimulation of the enriched enzyme was achieved with GTP as well as nonhydrolyzable analogs. All of the Arf subtypes tested were effective activators of PLD activity. Arf derived from yeast could activate mammalian PLD but with lower potency. The Arf-related Arl proteins were ineffective. PLD that has been highly enriched retained a requirement for phosphatidylinositol 4,5-bisphosphate for efficient expression of activity. Additionally, the ability of recombinant or purified porcine brain Arf to stimulate PLD activity was reduced relative to impure fractions of Arf activity. Thus, porcine PLD that has been purified about 5,000-10,000-fold is synergistically activated by Arf in combination with other cytosolic components that are described in the accompanying paper (Singer, W. D., Brown, H. A., Bokoch, G. M., and Sternweis, P. C.(1995) J. Biol. Chem. 270, 14944-14950). Taken together, these data suggest that physiological regulation of Arf-sensitive PLD may involve the coordinate assembly of several interacting regulatory subunits.
Population structure and genetic diversity of the Critically Endangered bowmouth guitarfish (Rhina ancylostomus) in the Northwest Indian Ocean

The bowmouth guitarfish (Rhina ancylostomus) is a unique and relatively understudied species of wedgefish with a distribution spanning the Indo-Pacific Oceans. Due to targeted and bycatch fisheries, this species is experiencing serious declines across its range. It is now considered among the most threatened species of elasmobranch. Despite this, species-specific management is limited, particularly around primary fishing hotspots. This is in part due to knowing very little about fundamental population processes. Here, we combine mitochondrial and single nucleotide polymorphism (SNP) data to carry out the first genetic assessment of R. ancylostomus across the Northwest Indian Ocean. We find evidence for population structure across the species’ northwest range that is best explained by dispersal constraints and therefore emphasises the importance of habitat connectivity. We also uncover a cline in genetic variation from east to west of the sampling distribution and identify regions in potential need of heightened protection. In doing so, our study provides baseline information to support conservation management of R. ancylostomus and highlights the value of genomic data in elasmobranch conservation.