dataesr/scientific-paragraphs-categorization huggingface dataset:
The two sets of measurements are obtained randomly interleaved. In total, we collect 100, 000 EM measurements (containing both fixed and random sets) for each TVLA test. Notably, each EM measurement covers the first 2. 5 rounds of AES, which is actually a trade-off between the amount of data processing (shorter measurement implies less data) and the computational complexity of the executed encryption since two rounds of AES give full diffusion [BFG + 17]. While for side-channel attacks, acquired EM measurements cover the first two SubBytes transformations in the first AES round.
Acknowledgments This work was also supported in part by  National Key R&D Program of China  ( 2020AA A0107700 ), by  National Natural Science Foundation of China  ( 62072398 ), by  Open Fund of State Key Laboratory of Cryptology  ( MMKFKT202013 ), by  Alibaba-Zhejiang University Joint Institute of Frontier Technologies , by  Major Scientific Research Project of Zhejiang Lab  ( 2018FD0ZX01 ), by  Zhejiang Key R&D Plan  ( 2021C01116 ), by  Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang  ( 2018R01005 ), by  Research Institute of Cyberspace Governance in Zhejiang University , by  National Key Laboratory of Science and Technology on Information System Security , by  State Key Laboratory of Mathematical Engineering and Advanced Computing , and by  Key Laboratory of Cyberspace Situation Awareness of Henan Province.
We present the results of a search for outer Solar System objects in the full six years of data ("Y6") from the Dark Energy Survey (DES ). The DES covered a contiguous 5000 deg 2 of the southern sky with ≈ 80, 000 3 deg 2 exposures in the grizY optical/IR filters between 2013 and 2019. This search yielded 815 trans-Neptunian objects (TNOs), one Centaur and one Oort cloud comet, with 461 objects reported for the first time in this paper. We present the search methodology that builds upon our previous search carried out on the first four years of data ("Y4"). Here, all DES images were reprocessed with an improved detection pipeline that leads to an average completeness gain of 0. 47 mag per exposure, as well as an improved transient catalog production and optimized algorithms for linkage of such detections into Solar System orbits.
All objects reported herein were verified by visual inspection and by computing the "sub-threshold significance", namely the total signal-to-noise ratio in the stack of images in which the object's presence is indicated by the orbit fit, but no detection was reported. This yields a highly pure catalog of trans-Neptunian objects complete to r ≈ 23. 8 mag and distances 29 < d < 2500 au. The Y6 TNOs have minimum (median) of 7 (  12 ) distinct nights' detections and arcs of 1. 1 (4. 2) years, and will have grizY magnitudes available in a further publication. We present publicly available software for simulating our observational biases that enable comparisons of population models to our TNO detections. Initial inferences demonstrating the statistical power of the DES Y6 catalog are: the data are inconsistent with the CFEPS-L7 model for the classical Kuiper Belt; the 16 "extreme" TNOs (a > 150 au, q > 30 au) are consistent with the null hypothesis of azimuthal isotropy; and non-resonant TNOs with q > 38 au, a > 50 au show a highly significant tendency to be sunward of the major mean motion resonances, as expected in models of resonance sweeping, whereas this tendency is not present for q < 38 au.
(2020a, hereafter Paper I)  presented the results of a uniform TNO search in the first four years of DES wide-survey data ("Y4") that yielded 316 objects. The Y4 search required the development of several algorithms for moving object identification, orbit linking and recovery, object confirmation, and simulations of object discovery and observational biases (see also  Bernardinelli et al. 2020b). In this paper, we describe a search of the full six years of DES wide-survey data ("Y6") for TNOs. Methodological improvements over the Y4 search are described in Section 2. Section 3 characterizes the selection function for the Y6 DES TNO search, and describes tools that we make available for simulating DES discoveries given hypothetical TNO populations. These tools are required for statistical comparisons of theoretical TNO populations to the Y6 catalog of DES TNOs.
THE YEAR 6 SEARCH The search for TNOs in the DES data has 3 major stages: 1. The identification of single-night transients, that is, a source that appears in the sky in a given location for only a single night; 2. Orbit linking, where we "connect" all sets of transients that could potentially come from the same outer-Solar-System object; 3. Verification of the linkage through the "sub-threshold significance" (STS) statistic, whereby we stack all images containing the putative TNO that did not yield a detection, thus yielding an independent check of whether the TNO actually exists. 1 Bannister (2020) presents a comprehensive review of these surveys and summarizes their discoveries. These steps are summarized below, with more detailed description of any aspects that have changed since the Y4 search.
Data acquisition and image processing The search presented here uses the DES Y6A2 internal release. Of 83,706 exposures processed from the wide survey, 76,217 pass quality cuts and their detections are entered into the "single-epoch" (SE) catalog. "Coadd" images are created as the average (per band) of all exposures in a given region of sky, and the detections and measurements derived from these images comprise the coadd catalog. The DES image processing pipeline is described in detail in  Morganson et al. (2018) , and the coadd catalogs as well as images used in this work correspond to those in the DES Data Release 2 (The Dark Energy Survey Collaboration 2021). The nominal survey strategy  (Diehl et al. 2016 (Diehl et al. , 2018) )  was such that the 5000 deg 2 footprint was tiled with 10 × 90 s exposures in each of the griz bands (and 6×45+2×90 s exposures in the Y band).
Detection threshold optimization & characterization We have improved the image processing pipeline presented in  Morganson et al. (2018)  to allow fainter sources to be detected in each exposure. This is done by lowering the Source Extractor (Bertin & Arnouts 1996) detection threshold to DETECT THRESH = 0. 8 instead of the previous 1. 5 used in the DES First Cut  (Morganson et al. 2018)  processing, and using a detection kernel that better matches the typical point spread function (PSF), changing from a boxcar  (Morganson et al. 2018)  to a Gaussian kernel. To optimize the threshold, we compared the catalogs of sources detected in DES exposure to the significantly deeper Hyper Suprime-Cam Subaru Strategic Program (HSC; Aihara et al. 2018) XMM-LSS catalog from their first data release. By using HSC, we have not only an independent set of measurements (so single-night transients from any DES exposure are not present on the HSC images), but also guarantee completeness of the reference catalog to fainter magnitudes than any DES exposure.
Orbit linking The process of linking of detections into orbits is very similar to the one described in Paper I. Pairs of detections are found by searching in bins of inverse distance γ ≡ 1/d (Bernstein & Khushalani 2000), with 30 < d < 2500 au. The detections are mapped to a frame that subtracts Earth's parallax at that distance, and so the dominant motion becomes linear in time. The pairs are found by first finding all pairs of exposures within some time ∆t of each other that could contain a common bound TNO within the distance bin. Then kD trees of both exposures' detections are searched for pairs of detections with separation that is consistent with the motion of a bound orbit. While the pair-finding algorithm remains unchanged, we have changed its implementation to use vaex table software (Breddels & Veljanoski 2018).
The vaex out-of-core functionality works well for very large datasets, e. g. some of our distance bins generate billions of pairs. A pair of exposures strongly constrains four out of the six orbital degrees of freedom, essentially leaving distance and line-of-sight motion weakly constrained. The triplet stage proceeds by determining the two-dimensional region of a future exposure spanned for plausible variations of these two parameters, and locates all detections within this region. The algorithm of Paper I used a kD tree implementation for this stage, but for the Y6 search we devise a linear-algebra-based "parallelogram" search which is faster. The details are presented in Appendix A. We consider only triplets whose dates of observation t 1 , t 2 , and t 3 satisfy |t 2t 1 | < 60 days and |t 3t 2 | < 60 days.
Simulator methods In order to quantify our observational biases, we have developed software that allows observations of population models to be simulated, similar to  Jones et al. (2006)  and  Lawler et al. (2018). Each simulated object requires a set of orbital elements, magnitudes (either apparent or absolute) in griz and potential light curve, allowing for a wide range of parameters to be varied in these tests. As an example, the populations of fakes described in Paper I and Section 2. 3 as well as the the extreme TNO ensemble of  Bernardinelli et al. (2020b)  were realized within this framework. For each set of orbital elements, we find all potential observations of such a TNO, that is, we find every DES pointing in which such an object's position would lie inside a functional DECam CCD.
This survey simulation software, as well a tutorial for its use, will be released in https://github. com/bernardinelli/ DESTNOSIM. The software works with the user stipulating a set of orbital elements or phase space coordinates, an absolute or apparent magnitude and colors for each object. Routines to include the color ranges of Equation 2 and light curves are also included. The software then evaluates if this object would be detected or not, and returns this information.
We believe we have reached the limits of the DES data for detection of Solar System objects at d > 29 au. A search for closer objects is currently beyond our computational means, as the burden grows as a high inverse power of d and the search reported here required an estimated 15-20 million CPU hours. It could be made feasible by reducing the transient catalog density significantly, e. g. by imposing a minimum S/N. This release includes only the r band photometry-a future publication will describe our dedicated TNO photometric processing and report detailed photometry for all bands and exposures. Searching for TNOs in the DES images presents challenges since it was not optimized for this purpose, such as its temporally sparse data, multi-band survey coverage, and extensive coverage at high ecliptic latitudes with lower TNO densities.
Despite this, the DES sample is comparable in number of objects to the largest predecessor TNO-targeted surveys. Its well characterized observational biases and publicly available survey simulator lead to a sample suited for statistical tests of Solar System population models. Indeed the fact the DES footprint is not concentrated at the ecliptic will make the combination of the DES and OSSOS particularly powerful for constraining TNO population models. The DES catalog represents a significant increase in the number of known dynamically detached objects, including new extreme and high-q TNOs, as well as objects in distant resonances or high inclinations, which are relevant to more detailed hypothesis of the formation of the outer Solar System. The data set presented here also contains a number of new notable objects, in particular the Oort cloud comet C/2014 UN 271 (Bernardinelli-Bernstein), as well as the detached object DES0502 with i = 62.
8 • and the q = 54. 3 au object DES0680 4. Initial applications of the statistical power of the DES Y6 TNO data are presented in three results for distinct populations of the trans-Neptunian region: • We show that our population of classical TNOs is formally incompatible with the CFEPS-L7 model for the H g < 8. 5 limit even if we change the relative sizes of the hot, stirred and kernel components. Such results indicate suggesting further substructure and/or a wider inclination distribution for the classical population. • The sample of extreme TNOs measured by DES is consistent with an underlying uniform distribution in ω and , agreeing with previous results from OSSOS  (Shankman et al. 2017 ), DES, (Bernardinelli et al. 2020b ) and their combination with the Sheppard-Trujillo surveys  (Napier et al.
Supported by the project CONCORDIA that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement  No. 830927  The challenge of automating the protection of cloud services and their underlying resources have already been investigated in the literature through several security approaches. In particular, endogenous security mechanisms directly impact the resources, such as generating specific cloud images with a low attack surface  [1] , modifying the internal parameterization of resources  [2] , and exploiting certification techniques for guaranteeing the resource behaviours  [3]. However, these solutions are often not designed for addressing the properties of cloud environments (e. g. elasticity, heterogeneity), or do not focus on vulnerable configurations.
II. CLOUD MIGRATION SECURITY TOOL The proposed tool, called CMSec (Cloud Migration Security), aims at preventing known vulnerabilities that may affect cloud composite services during the migration of their resources, through the assessment of their configurations and the selection of adequate countermeasures when vulnerabilities are identified. It corresponds to the implementation of the strategy that we have formalized in  [6]. The CMSec architecture, detailed on Figure  1 , has been prototyped using the Python language version 3. 7, and relies on SMT solvers compatible with the SMT-LIB (Satisfiability Modulo Theories LIBrary) format  [7]  as back-end services. As shown on the figure, the three main building blocks (represented in green) of the CMSec tool include: (1) the migrated resource projector, (2) the resource configuration assessor, and (3) the security function selector, that intervene successively in the process of preventing configuration vulnerabilities during the migration of resources in cloud composite services.
The CMSec tool considers cloud composite services orchestrated using the TOSCA 2 orchestration language  [8]. This language is both open-source and characterized by a high expressivity for supporting flexible, interoperable and distributed applications regardless of the underlying cloud service providers. It provides an important knowledge source about cloud services to our tool, by describing the elementary resources of these services, as well as their relationships. In particular, it specifies a cloud service as a TOSCA topology which defines a set of TOSCA nodes (e. g. web micro-service nodes) that are interconnected by a set of TOSCA relationships (e. g. the interconnection to MySQL database nodes). In addition, our CMSec tool relies on a set of vulnerabil-2 Topology and Orchestration Specification for Cloud Applications ity descriptions coming from the official OVAL 3 repository to perform vulnerability prevention activities.
OVAL is an open standardized language supported by MITRE  [9]  for describing vulnerability descriptions and specifying how to assess and report upon a system state. A vulnerability is typically considered as a logical combination of conditions that if observed on a target system, the security problem described by such vulnerability is present on the system. The OVAL language follows the same concept by considering a vulnerability description as an OVAL definition. An OVAL definition specifies a criterion that logically combines a set of OVAL tests. Each OVAL test in turn represents the process by which a specific condition or property is assessed on the target system. Each OVAL test examines an OVAL object (e. g. an Apache web server) looking for a specific OVAL state (e. g. a specific version for this server).
III. THE DEMONSTRATION In this demonstration we will show the operation of the CMSec vulnerability prevention tool for supporting migrations in cloud composite services orchestrated with the TOSCA language, by considering two main scenarios (shown on Figure  2 ) illustrating respectively the assessment of a migrated resource and the selection of countermeasures. In that context, we consider an e-commerce cloud composite service involving a set of micro-services together with back-end databases. The micro-services are implemented in the form of a web application built with the Struts open-source framework, that extends the Java Servlet API, and are running over Apache web servers deployed on virtualized infrastructures. Let us consider that one of these micro-services undergoes migrations across several cloud service providers that support different operating systems, namely Linux CentOS, Linux RedHat Enterprise, and Microsoft Windows Server, under different versions.
B. Remediation Scenario The second main scenario, depicted in orange color on the figure, illustrates the migration of another instance of the micro-service based on the Struts framework version 2. 5. 8. It appears that this version is characterized by a critical vulnerability, described in CVE-2017-5638  [14] , allowing an attacker to execute arbitrary code remotely on a given web application. While the source cloud environment implements a firewall rule preventing this vulnerability to be exploited, the destination cloud environment does not implement any countermeasures, at the time when the migration is requested. First, the CMSec vulnerability prevention tool establishes the projection of the migrated resource over the destination cloud environment. After having collected related vulnerability descriptions, it starts the resource configuration assessor, which detects the previously mentioned vulnerability.
C. Performance Evaluation In addition to these two main scenarios, the demonstration will also present some performance evaluation results, in particular regarding the vulnerability assessment process with different vulnerability description dataset from the official OVAL repository. The experiments are performed over a regular laptop equipped with a 2Ghz Intel Core i5 processor and 8GB of RAM memory. The experimental results are synthesized on Table  I , considering a projected configuration corresponding to an average of 12 properties. We can observe that the vulnerability assessment time takes less than 2 seconds with all the considered OVAL datasets. The highest assessment  This demonstration showcases the architecture of the CM-Sec vulnerability prevention tool, as well as the benefits and limits of this solution through concrete usage scenarios.
Implementation We wrote a proof of concept implementation of our scheme in C++ using the NTL-library  [43]. The implementation was benchmarked on an Intel Core i5 running at 2. 3 GHz with 16 GB RAM. We ran the protocol with λ = 40, τ = 1000, µ = 68. The timings are given in Table  1. The implementation is very simple, and consists of a total of 400 lines of code. Our source code is available online ⋆⋆. We note that our implementation does not use the number theoretic transform for fast multiplication of elements in the ring to reduce complexity. A rough comparison to NFLlib  [2] , where they show clear improvements compared to NTL, indicates that an optimized implementation should provide a speedup by at least an order of magnitude. We sketch an extension of the passively secure distributed decryption protocol Π DistDec given by Bendlin and Damgård  [11] , which is used in SPDZ  [20, 22].
g. Khatri and Parrilo (1998). But although attractive from a theoretical perspective, this approach was far from being applicable at that time. The first dedicated software was developed more than 20 years later by  Balas et al. (2012). It was a major improvement, although still not sufficient to address challenging industrial applications, as highlighted in  Marcos et al. (2015). The last round began a few years ago, when  Falcoz et al. (2017)  developed a new Matlab software based on the SMART Library of the SMAC Toolbox  (Roos (2013) ), that implements state-of-the-art µ-analysis based algorithms to compute robustness margins and performance levels. Shortly afterwards, the first version of the STOchastic Worst-case Analysis Toolbox (STOWAT) was released by  Thai et al. (2019)  and  Biannic et al.
Rodri ́guez et al. attributed this compound to a distorted MOF-5 phase caused by a default in one of the binding modes of carboxylate groups to Zn 2+. 45 Thirumurugan and Rao observed this phase as an intermediate in their hydrothermal reactions when using a Zn/BDC 1/1 molar ratio but were not able to propose an exact formula for it. 46 Hirai et al. were unable to isolate a pure phase of this material but were able to detect it in a microwave synthesis when using a Zn/BDC ratio of 2/1 and working at specific pH (between 5. 7 and 4. 9). 38 In 2016, a crystal structure was reported in the Cambridge crystallography database (CCDC ECATIO), which matches the pXRD pattern of this same phase and corresponds to the Zn 2 (OH) 2 (BDC) chemical formula (with a Zn/BDC ratio of 2/1). Unfortunately, no information on its synthesis could be found.
Diffraction techniques remain, at the moment, the most common analytical tool to obtain structural information on Zn-BDC MOFs. However, preparing good-quality crystals can be very challenging. Moreover, providing exact positions for hydrogen atoms from pXRD data remains an issue, and only two out of the four reported structures in Table  1  fully report hydrogen positions (aromatics and hydroxyls/water). In complement to XRD, chemical and structural information on these phases can also be obtained through FTIR spectroscopy. For example, the O-H stretching modes of hydroxyls and water molecules are easily observed above 3000 cm -1 and can inform on the H-bond networks in presence. Moreover, the C-O stretching modes of the carboxylate groups are identified by the presence of antisymmetric and symmetric vibrations (noted ν as (COO -) and ν s (COO -)) between 1650-1540 and 1450-1360 cm -1 , respectively, and information on the binding mode of the carboxylate ligands to zinc metal centers can a priori be proposed on the basis of the difference in wavenumbers between these two frequencies (Δ = ν as (COO -) -ν s (COO -)).
GIPAW-DFT Calculations. The unit cell parameters were set to the X-ray diffraction parameters and kept fixed during geometry optimizations to ensure consistency between experimental and optimized structures. Missing protons (in CCDC PUCYAO and PEKGAO structures) were initially positioned to be consistent with the expected structure of the system, and successively, only protons and then all atomic positions were relaxed with the VASP (Vienna ab initio simulation package) code  73  based on the Kohn-Sham density functional theory (DFT) and using a plane-wave pseudopotential approach. For the two structures mentioned above, several initial OH proton positions were tested. The NMR parameters were then calculated within the Kohn-Sham DFT using the QUANTUM-ESPRESSO code,  74, 75  keeping the atomic positions equal to the values previously calculated with VASP.