Miracle-dz/UniFAR-FTUs huggingface dataset:
Development approach to the attack modeling for the needs of cyber security education

Critical infrastructure faces changed landscape of threats which requires progress in the understanding of highly sophisticated attacks. A reflection of this awareness is the upcoming technical documentation of umbrella organizations in critical infrastructure. The attack modeling is an important approach in the design stage of the system. The attack tree is a structural technique for attack modeling. In terms of graphic presentation, attack trees are not complex and can be designed manually, also, they are an important tool in recognizing threats and evaluating risks. The absence of the presentation of comprehensive and systematic approaches to the attack modeling is often reflected in rather generalized and inconsistent presentations of the attack modeling as well as in difficult transfer of attack modeling techniques into practice. The current absence of the agreement and lack of consistency in the development approach of structural attack models limits the transfer of concepts in the field of cyber-attacks to educational environments. The purpose of the paper is to present, in clear practical example, a proposal for the development approach to the attack modeling. Thus, we want to contribute to the implementation of attack modeling into practice, especially in the field of cyber security education.
Identification of Novel Malarial Cysteine Protease Inhibitors Using Structure-Based Virtual Screening of a Focused Cysteine Protease Inhibitor Library

Malaria, in particular that caused by Plasmodium falciparum , is prevalent across the tropics, and its medicinal control is limited by widespread drug resistance. Cysteine proteases of P. falciparum , falcipain-2 (FP-2) and falcipain-3 (FP-3), are major hemoglobinases, validated as potential antimalarial drug targets. Structure-based virtual screening of a focused cysteine protease inhibitor library built with soft rather than hard electrophiles was performed against an X-ray crystal structure of FP-2 using the Glide docking program. An enrichment study was performed to select a suitable scoring function and to retrieve potential candidates against FP-2 from a large chemical database. Biological evaluation of 50 selected compounds identified 21 diverse nonpeptidic inhibitors of FP-2 with a hit rate of 42%. Atomic Fukui indices were used to predict the most electrophilic center and its electrophilicity in the identified hits. Comparison of predicted electrophilicity of electrophiles in identified hits with those in known irreversible inhibitors suggested the soft-nature of electrophiles in the selected target compounds. The present study highlights the importance of focused libraries and enrichment studies in structure-based virtual screening. In addition, few compounds were screened against homologous human cysteine proteases for selectivity analysis. Further evaluation of structure-activity relationships around these nonpeptidic scaffolds could help in the development of selective leads for antimalarial chemotherapy.
A new empirical method to estimate the molecular gas mass in galaxies

We find a tight correlation between the dust extinction, traced by the Balmer Decrement (BD$=$H$\alpha$/H$\beta$), the CO(1-0) line luminosity (L$_{CO}$) and total molecular gas mass (M$_{H2}$) in a sample of $222$ local star-forming galaxies drawn from the xCOLD GASS survey. As expected, the galaxy disk inclination affects the correlation by inducing a saturation of the Balmer decrement on highly inclined galaxies. Once this effect is taken into account, L$_{CO}$ and M$_{H2}$ can be expressed as a function of BD with a scatter of $\sim 0.3$ dex. We do not find any dependence on galaxy size, mass, morphology, star formation activity, and gas metallicity. The correlation disappears if the atomic gas phase is considered. This is likely due to the fact that the region traced by the BD, the stellar disk, is much smaller than the HI disk.
Interactive Video Retrieval with Dialog

In the contemporary world, recording videos can be done quickly and easily. The quantity and availability of videos have continued to increase, therefore, an effective video retrieval method has also become important. To retrieve a target video from a large collection of videos, a video retrieval system needs to obtain appropriate queries from a user. Given a sentence query, there are many similar videos related to the query. The video retrieval system requires more information in addition to the sentence to distinguish the target video from others. If the system actively collects more information on the target video, we can perform video retrieval effectively. Thus, we propose a system to retrieve videos by asking questions about the content of the videos, and leveraging the user’s responses to the questions and the dialog history. Additionally, we confirmed the usefulness of the proposed system through experiments using the dataset called AVSD which includes videos and dialogs about the videos.
Observational constraints on two-field warm inflation

We study the two-field warm inflation models with a double quadratic potential and a linear temperature-dependent dissipative coefficient. We derive the evolution equation of all kinds of perturbations without assuming slow-roll approximation and obtained the curvature power spectrum at the end of inflation with a fully numerical method. Then, we compute the scalar spectral index ${n}_{s}$ and tensor-to-scalar ratio $r$ for several representative potentials and compare our results with observational data. At last, we use Planck data to constrain the parameters in our models. This work is a natural extension of single-field warm inflation, and the aim of this work is to present some features of multifield warm inflation using a simple two-field model.
Understanding extreme quasar optical variability with CRTS – II. Changing-state quasars

We present the results of a systematic search for quasars in the Catalina Real-time Transient Survey exhibiting both strong photometric variability and spectroscopic variability over a decadal baseline. We identify 111 sources with specific patterns of optical and mid-infrared photometric behaviour and a defined spectroscopic change. These ‘changing-state’ quasars (CSQs) form a higher luminosity sample to complement existing sets of ‘changing-look’ AGNs and quasars in the literature. The CSQs (by selection) exhibit larger photometric variability than the changing-look quasars (CLQs). The spectroscopic variability is marginally stronger in the CSQs than CLQs as defined by the change in H β/[$\rm {O \,\rm {\small {III}}}$] ratio. We find 48 sources with declining H β flux and 63 sources with increasing H β flux, and discover 8 sources with $z$ > 0.8, further extending the redshift arm. Our CSQ sample compares to the literature CLQ objects in similar distributions of H β flux ratios and differential Eddington ratios between high (bright) and low (dim) states. Taken as a whole, we find that this population of extreme varying quasars is associated with changes in the Eddington ratio and the time-scales imply cooling/heating fronts propagating through the disc.
Measurement of charged jet cross section in 
pp
 collisions at 
s=5.02  TeV

The cross section of jets reconstructed from charged particles is measured in the transverse momentum range of 5 < p T < 100 GeV / c in pp collisions at the center-of-mass energy of √ s = 5 . 02 TeV with the ALICE detector. The jets are reconstructed using the anti- k T algorithm with resolution parameters R = 0 . 2, 0 . 3, 0 . 4, and 0 . 6 in the pseudorapidity range | η | < 0 . 9 − R . The charged jet cross sections are compared with the leading order (LO) and to next-to-leading order (NLO) perturbative Quantum ChromoDynamics (pQCD) calculations. It was found that the NLO calculations agree better with the measurements. The cross section ratios for different resolution parameters were also measured. These ratios increase from low p T to high p T and saturate at high p T , indicating that jet collimation is larger at high p T than at low p T . These results provide a precision test of pQCD predictions and serve as a baseline for the measurement in Pb − Pb collisions at the same energy to quantify the effects of the hot and dense medium created in heavy-ion collisions at the LHC.
A Biohybrid Setup for Coupling Biological and Neuromorphic Neural Networks

Developing technologies for coupling neural activity and artificial neural components, is key for advancing neural interfaces and neuroprosthetics. We present a biohybrid experimental setting, where the activity of a biological neural network is coupled to a biomimetic hardware network. The implementation of the hardware network (denoted NeuroSoC) exhibits complex dynamics with a multiplicity of time-scales, emulating 2880 neurons and 12.7 M synapses, designed on a VLSI chip. This network is coupled to a neural network in vitro, where the activities of both the biological and the hardware networks can be recorded, processed, and integrated bidirectionally in real-time. This experimental setup enables an adjustable and well-monitored coupling, while providing access to key functional features of neural networks. We demonstrate the feasibility to functionally couple the two networks and to implement control circuits to modify the biohybrid activity. Overall, we provide an experimental model for neuromorphic-neural interfaces, hopefully to advance the capability to interface with neural activity, and with its irregularities in pathology.
The Astrochemical Impact of Cosmic Rays in Protoclusters. I. Molecular Cloud Chemistry

We present astrochemical photodissociation region models in which cosmic-ray (CR) attenuation has been fully coupled to the chemical evolution of the gas. We model the astrochemical impact of CRs, including those accelerated by protostellar accretion shocks, on molecular clouds hosting protoclusters. Our models with embedded protostars reproduce observed ionization rates. We study the imprint of CR attenuation on ions for models with different surface CR spectra and different star formation efficiencies. We find that abundances, particularly ions, are sensitive to the treatment of CRs. We show the column densities of ions are underpredicted by the “classic” treatment of CRs by an order of magnitude. We also test two common chemistry approximations used to infer ionization rates. We conclude that the approximation based on the abundance underpredicts the ionization rate, except in regions where the CRs dominate the chemistry. Our models suggest the chemistry in dense gas will be significantly impacted by the increased ionization rates, leading to a reduction in molecules such as NH3 and causing H2-rich gas to become [C ii] bright.
PRSim: Sublinear Time SimRank Computation on Large Power-Law Graphs

SimRank is a classic measure of the similarities of nodes in a graph. Given a node u in graph $G =(V, E)$, a \em single-source SimRank query returns the SimRank similarities $s(u, v)$ between node u and each node $v \in V$. This type of queries has numerous applications in web search and social networks analysis, such as link prediction, web mining, and spam detection. Existing methods for single-source SimRank queries, however, incur query cost at least linear to the number of nodes n, which renders them inapplicable for real-time and interactive analysis. This paper proposes \prsim, an algorithm that exploits the structure of graphs to efficiently answer single-source SimRank queries. \prsim uses an index of size $O(m)$, where m is the number of edges in the graph, and guarantees a query time that depends on the \em reverse PageRank distribution of the input graph. In particular, we prove that \prsim runs in sub-linear time if the degree distribution of the input graph follows the power-law distribution, a property possessed by many real-world graphs. Based on the theoretical analysis, we show that the empirical query time of all existing SimRank algorithms also depends on the reverse PageRank distribution of the graph. Finally, we present the first experimental study that evaluates the absolute errors of various SimRank algorithms on large graphs, and we show that \prsim outperforms the state of the art in terms of query time, accuracy, index size, and scalability.
Dietary patterns are associated with hyperhomocysteinemia in an urban Pakistani population.

Little attention has been given to the association of dietary patterns with plasma homocysteine. Our objective in this study was to identify major dietary patterns and investigate their association with plasma homocysteine. In a cross-sectional survey, 872 healthy adults (355 males, 517 females; aged 18-60 y) were enrolled from an urban population in Karachi. Dietary intake was assessed by a FFQ. We used factor analysis to define major dietary patterns. Fasting concentrations of plasma or serum homocysteine, folate, pyridoxal-phosphate (PLP; coenzyme form of vitamin B-6), and vitamin B-12 were measured. Three major dietary patterns were identified and labeled as "prudent diet," "high animal-protein diet," and "high plant-protein diet. " We observed a protective effect of the prudent dietary pattern for the highest quartile of intake compared with the lowest quartile of hyperhomocysteinemia when the model was adjusted for age, gender, household income, BMI, tobacco chewing, and smoking [OR = 0.52 (95% CI = 0.30-0.90); P = 0.01]. The high plant-protein diet pattern was inversely related to hyperhomocysteinemia, with a higher intake being protective. Compared with the 1st quartile, the adjusted OR was 0.42 (95% CI = 0.25-0.69; P = 0.001) for the 4th quartile. The high animal-protein diet was positively associated with hyperhomocysteinemia, with participants in the highest quartile of intake having the greatest increase in risk [OR = 2.10 (95% CI = 1.22-3.60); P = 0.007]. Plasma homocysteine concentrations appeared to be correlated more with circulating folate (r = -0.25; P < 0.001) than with PLP (r = -0.02; P = 0.663) or vitamin B-12 (r = -0.16; P < 0.001). A diet rich in fruits and uncooked vegetables decreased the risk of hyperhomocysteinemia, whereas diets rich in red meat, chicken, and tea with milk were positively associated with hyperhomocysteinemia.
Generating Realistic Unrestricted Adversarial Inputs using Dual-Objective GAN Training

The correctness of deep neural networks is well-known to be vulnerable to small, 'adversarial' perturbations of their inputs. Although studying these attacks is valuable, they do not necessarily conform to any real-world threat model. This has led to interest in the generation of (and robustness to) unrestricted adversarial inputs, which are not constructed as small perturbations of correctly-classified ground-truth inputs. We introduce a novel algorithm to generate realistic unrestricted adversarial inputs, in the sense that they cannot reliably be distinguished from the training dataset by a human. This is achieved by modifying generative adversarial networks: a generator neural network is trained to construct examples that deceive a fixed target network (so they are adversarial) while also deceiving the usual co-training discriminator network (so they are realistic). Our approach is demonstrated by the generation of unrestricted adversarial inputs for a trained image classifier that is robust to perturbation-based attacks. We find that human judges are unable to identify which image out of ten was generated by our method about 50 percent of the time, providing evidence that they are moderately realistic.
Implementing TLS with Verified Cryptographic Security

TLS is possibly the most used protocol for secure communications, with a 18-year history of flaws and fixes, ranging from its protocol logic to its cryptographic design, and from the Internet standard to its diverse implementations. We develop a verified reference implementation of TLS 1.2. Our code fully supports its wire formats, ciphersuites, sessions and connections, re-handshakes and resumptions, alerts and errors, and data fragmentation, as prescribed in the RFCs; it interoperates with mainstream web browsers and servers. At the same time, our code is carefully structured to enable its modular, automated verification, from its main API down to computational assumptions on its cryptographic algorithms. Our implementation is written in F# and specified in F7. We present security specifications for its main components, such as authenticated stream encryption for the record layer and key establishment for the handshake. We describe their verification using the F7 typechecker. To this end, we equip each cryptographic primitive and construction of TLS with a new typed interface that captures its security properties, and we gradually replace concrete implementations with ideal functionalities. We finally typecheck the protocol state machine, and obtain precise security theorems for TLS, as it is implemented and deployed. We also revisit classic attacks and report a few new ones.
Onset of synchronization of Kuramoto oscillators in scale-free networks.

Despite the great attention devoted to the study of phase oscillators on complex networks in the last two decades, it remains unclear whether scale-free networks exhibit a nonzero critical coupling strength for the onset of synchronization in the thermodynamic limit. Here, we systematically compare predictions from the heterogeneous degree mean-field (HMF) and the quenched mean-field (QMF) approaches to extensive numerical simulations on large networks. We provide compelling evidence that the critical coupling vanishes as the number of oscillators increases for scale-free networks characterized by a power-law degree distribution with an exponent 23, we show that the critical coupling remains finite, in agreement with HMF calculations and highlight phenomenological differences between critical properties of phase oscillators and epidemic models on scale-free networks. Finally, we also discuss at length a key choice when studying synchronization phenomena in complex networks, namely, how to normalize the coupling between oscillators.
Attention-based Fusion for Multi-source Human Image Generation

We present a generalization of the person-image generation task, in which a human image is generated conditioned on a target pose and a set X of source appearance images. In this way, we can exploit multiple, possibly complementary images of the same person which are usually available at training and at testing time. The solution we propose is mainly based on a local attention mechanism which selects relevant information from different source image regions, avoiding the necessity to build specific generators for each specific cardinality of X. The empirical evaluation of our method shows the practical interest of addressing the person-image generation problem in a multi-source setting.
Sum-of-Squares Polynomial Flow

Triangular map is a recent construct in probability theory that allows one to transform any source probability density function to any target density function. Based on triangular maps, we propose a general framework for high-dimensional density estimation, by specifying one-dimensional transformations (equivalently conditional densities) and appropriate conditioner networks. This framework (a) reveals the commonalities and differences of existing autoregressive and flow based methods, (b) allows a unified understanding of the limitations and representation power of these recent approaches and, (c) motivates us to uncover a new Sum-of-Squares (SOS) flow that is interpretable, universal, and easy to train. We perform several synthetic experiments on various density geometries to demonstrate the benefits (and short-comings) of such transformations. SOS flows achieve competitive results in simulations and several real-world datasets.
Bee+: A 95-mg Four-Winged Insect-Scale Flying Robot Driven by Twinned Unimorph Actuators

We introduce Bee+, a 95-mg four-winged microrobot with improved controllability and open-loop-response characteristics with respect to those exhibited by state-of-the-art two-winged microrobots with the same size and similar weight (i.e., the 75-mg Harvard RoboBee). The key innovation that made possible the development of Bee+ is the introduction of an extremely light (28-mg) pair of twinned unimorph actuators, which enabled the design of a new microrobotic mechanism that flaps four wings independently. A first main advantage of the proposed design, compared to those of two-winged flyers, is that by increasing the number of actuators from two to four, the number of direct control inputs increases from three to four when simple sinusoidal excitations are employed. A second advantage of Bee+ is that its four-wing configuration and flapping mode naturally damp the rotational disturbances that commonly affect the yaw degree of freedom of two-winged microrobots. In addition, the proposed design greatly reduces the complexity of the associated fabrication process compared to those of other microrobots, as the unimorph actuators are fairly easy to build. Finally, we hypothesize that given the relatively low wing-loading affecting their flapping mechanisms, the life expectancy of Bee+s must be considerably higher than those of the two-winged counterparts. The functionality and basic capabilities of the robot are demonstrated through a set of simple control experiments.
ROCKs as immunomodulators of stroke

Introduction: Stroke is the third leading cause of death and a major cause of long-term disability in the adult population. Growing evidence suggests that inflammation may play an important role in the evolution of stroke. Because Rho-associated coiled-coil containing kinases (ROCKs) are important mediators of inflammation, they may contribute to stroke and stroke recovery. Areas covered: The pathophysiological role of ROCKs in mediating inflammation at different phases of stroke, and the therapeutic opportunities for stroke prevention and stroke treatment with ROCK inhibitors will be discussed. Expert opinion: Inflammation is a double-edged sword during the evolution of stroke. Immunomodulation might provide a novel therapeutic approach for stroke prevention and stroke treatment. ROCK plays an important role in mediating the inflammatory response following vascular injury as well as platelet activation and thrombus formation. ROCK inhibitors have been shown to be beneficial in stroke prevention, acute neuroprotection and chronic stroke recovery by affecting inflammatory-mediated platelet and endothelial function, smooth muscle contraction and neuronal regeneration. Thus, ROCK-mediated inflammation could be a potential therapeutic target for stroke prevention and stroke treatment. However, the mechanism by which ROCKs regulate the inflammatory response is unclear, and the role of the two ROCK isoforms in stroke and stroke recovery remains to be determined.