Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent advancements and perspective of ciprofloxacin-based antimicrobial polymers

Abstract In recent years, microbial pathogens, which are major sources of infections, have become a widespread concern across the world. The number of deaths caused by infectious diseases is continually rising, according to World Health Organization records. Antimicrobial resistance, particularly resistance to several drugs, is steadily growing in percentages of organisms. Ciprofloxacin is a second-generation fluoroquinolone with significant antimicrobial activity and pharmacokinetic characteristics. According to studies, many bacteria are resistant to the antibiotic ciprofloxacin. In this article, we look into polymers as ciprofloxacin macromolecular carriers with a wide range of antibacterial activity. We also discuss the latter form of coupling, in which ciprofloxacin and polymers are covalently bonded. This article also discusses the use of antimicrobial polymers in combination with ciprofloxacin in a various sectors. The current review article provides an overview of publications in the last five years on polymer loaded or modified with ciprofloxacin having applications in numerous sectors.
FrzS acts as a polar beacon to recruit SgmX, a central activator of type IV pili during Myxococcus xanthus motility

In rod‐shaped bacteria, type IV pili (Tfp) promote twitching motility by assembling and retracting at the cell pole. In Myxococcus xanthus, a bacterium that moves in highly coordinated cell groups, Tfp are activated by a polar activator protein, SgmX. However, while it is known that the Ras‐like protein MglA is required for unipolar targeting, how SgmX accesses the cell pole to activate Tfp is unknown. Here, we demonstrate that a polar beacon protein, FrzS, recruits SgmX at the cell pole. We identified two main functional domains, including a Tfp‐activating domain and a polar‐binding domain. Within the latter, we show that the direct binding of MglA‐GTP unveils a hidden motif that binds directly to the FrzS N‐terminal response regulator (CheY). Structural analyses reveal that this binding occurs through a novel binding interface for response regulator domains. In conclusion, the findings unveil the protein interaction network leading to the spatial activation of Tfp at the cell pole. This tripartite system is at the root of complex collective behaviours in this predatory bacterium.
NMN alleviates radiation-induced intestinal fibrosis by modulating gut microbiota

Abstract Aim Radiation-induced intestinal fibrosis, a common complication of long-term survivors after receiving abdominal and pelvic radiotherapy, has no effective clinical drugs at present. Nicotinamide mononucleotide (NMN) has been reported to alleviate a variety of age-related diseases and has potential of regulating gut microbiota. The current study focuses on the role of gut microbiota in chronic radiation induced intestinal fibrosis, and investigates whether NMN plays a protective role in radiation-induced intestinal fibrosis as well as the impact of NMN on radiation-induced dysbiosis of gut microbiota. Materials and methods C57BL/6J mice received 15 Gy abdominal irradiation and NMN (300 mg/kg/day) supplement in drinking water. Feces were collected at 4- and 8-months post-irradiation and performed 16S rRNA sequencing to detect the gut microbiota. Colon tissues were isolated at 12 months after irradiation with or without NMN supplementation for histological analysis. Results We found that irradiation caused intestinal fibrosis, and altered the β diversity and composition of gut microbiota, while the gut microbiota was observed to be affected by time post-irradiation and age of mice. Long-term NMN supplementation alleviated intestinal fibrosis, and reshaped the composition and function of gut microbiota dysregulated by ionizing radiation (IR). In addition, Akkermansia muciniphila, a promising probiotic, and metabolism-related pathways, such as Biosynthesis of other secondary metabolites and Amino acid metabolism, were more abundant after NMN treatment in irradiated mice. Conclusion IR has a long-term effect on the gut microbiota and NMN supplementation can alleviate radiation induced intestinal fibrosis by reshaping the composition of gut microbiota and regulating the metabolic function of the microorganism.
The potential of a universal influenza virus-like particle vaccine expressing a chimeric cytokine

Herein, a virus-like particle vaccine with chimeric cytokine shows the protective efficacy against different strains of influenza virus, laying the foundation for designing a universal influenza vaccine. The efficacy of the current influenza vaccines is frequently reduced because of antigenic drift, a trade-off of developing improved vaccines with broad cross-protective activity against influenza A viruses. In this study, we have successfully constructed a chimeric cytokine (CC) comprising the M2 protein, influenza A neuraminidase stalk, and interleukin-12. We produced virus-like particles (VLPs) containing CC and influenza hemagglutinin (HA) proteins using a baculovirus system in Eri silkworm pupae. The protective efficacy of the CCHA-VLP vaccine was evaluated in mice. The CCFkH5HA-VLP vaccine increased the survival rates of BALB/c mice, infected with a lethal dose of PRH1 and HKH5 viruses, to 80% and 100%, respectively. The results suggested that CCHA-VLP successfully induced potent cross-reactive protective immunity against infection with homologous and heterologous subtypes of the influenza A virus. This is the first study to design a CC-containing HA-VLP vaccine and validate its protective efficacy.
Is there supercurvature mode of massive vector field in open inflation?

We investigate the Euclidean vacuum mode functions of a massive vector field in a spatially open chart of de Sitter spacetime. In the one-bubble open inflationary scenario that naturally predicts a negative spatial curvature after a quantum tunneling, it is known that a light scalar field has the so-called supercurvature mode, i.e. an additional discrete mode which describes fluctuations over scales larger than the spatial curvature scale. If such supercurvature modes exist for a vector field with a sufficiently light mass, then they would decay slower and easily survive the inflationary era. However, the existence of supercurvature mode strongly depends on details of the system. To clarify whether a massive vector field has supercurvature modes, we consider a U(1) gauge field with gauge and conformal invariances spontaneously broken through the Higgs mechanism, and present explicit expressions for the Euclidean vacuum mode functions. We find that, for any values of the vector field mass, there is no supercurvature mode. In the massless limit, the absence of supercurvature modes in the scalar sector stems from the gauge symmetry.
Towards Measuring The Fungibility and Anonymity of Cryptocurrencies

Cryptocurrencies aim to replicate physical cash in the digital realm while removing centralized middlemen. Decentralization is achieved by the blockchain, a permanent public ledger that contains a record of every transaction. The public ledger ensures transparency, which enables public verifiability but harms fungibility and anonymity. Even though cryptocurrencies attracted millions of users in the last decade with their total market cap reaching approximately one trillion USD, their anonymity guarantees are poorly understood. Indeed, previous notions of privacy, anonymity, and fungibility for cryptocurrencies are either non-quantitative or inapplicable, e.g., computationally hard to measure. In this work, we put forward a formal framework to measure the fungibility and anonymity of cryptocurrencies, allowing us to quantitatively reason about the mixing characteristics of cryptocurrencies and the privacy-enhancing technologies built on top of them. Our methods apply absorbing Markov chains combined with Shannon entropy. To the best of our knowledge, our work is the first to assess the fungibility of cryptocurrencies. Among other results, we find that in the studied one-week interval, the Bitcoin network, on average, provided comparable but quantifiably more fungibility than the Ethereum network.
An Efficient Global Optimization Algorithm with Adaptive Estimates of the Local Lipschitz Constants

In this work, we present a new deterministic partition-based Global Optimization (GO) algorithm that uses estimates of the local Lipschitz constants associated with different sub-regions of the domain of the objective function. The estimates of the local Lipschitz constants associated with each partition are the result of adaptively balancing the global and local information obtained so far from the algorithm, given in terms of absolute slopes. We motivate a coupling strategy with local optimization algorithms to accelerate the convergence speed of the proposed approach. In the end, we compare our approach HALO (Hybrid Adaptive Lipschitzian Optimization) with respect to popular GO algorithms using hundreds of test functions. From the numerical results, the performance of HALO is very promising and can extend our arsenal of efficient procedures for attacking challenging real-world GO problems. The Python code of HALO is publicly available on GitHub. \url{https://github.com/dannyzx/HALO}
Herschel spectral mapping of the Helix nebula (NGC 7293) - Extended CO photodissociation and OH+ emission

Context. The Helix nebula (NGC 7293) is our closest planetary nebulae. Therefore, it is an ideal template for photochemical studies at small spatial scales in planetary nebulae. Aims. We aim to study the spatial distribution of the atomic and the molecular gas, and the structure of the photodissociation region along the western rims of the Helix nebula as seen in the submillimeter range with Herschel. Methods. We used five SPIRE FTS pointing observations to make atomic and molecular spectral maps. We analyzed the molecular gas by modeling the CO rotational lines using a non-local thermodynamic equilibrium (non-LTE) radiative transfer model. Results. For the first time, we have detected extended OH+ emission in a planetary nebula. The spectra towards the Helix nebula also show CO emission lines (from J = 4 to 8), [N ii] at 1461 GHz from ionized gas, and [C i] (3P2–3P1), which together with the OH+ lines trace extended CO photodissociation regions along the rims. The estimated OH+ column density is ~ 1012 − 1013 cm-2. The CH+ (1–0) line was not detected at the sensitivity of our observations. Non-LTE models of the CO excitation were used to constrain the average gas density (n(H2) ~ (1 − 5) × 105 cm-3) and the gas temperature (Tk ~ 20−40 K). Conclusions. The SPIRE spectral-maps suggest that CO arises from dense and shielded clumps in the western rims of the Helix nebula, whereas OH+ and [C i] lines trace the diffuse gas and the UV and X-ray illuminated clump surfaces where molecules reform after CO photodissociation. The [N ii] line traces a more diffuse ionized gas component in the interclump medium.
Integrated Sensing, Computation, and Communication: System Framework and Performance Optimization

Integrated sensing, computation, and communication (ISCC) has been recently considered as a promising technique for beyond 5G systems. In ISCC systems, the competition for communication and computation resources between sensing tasks for ambient intelligence and computation tasks from mobile devices becomes an increasingly challenging issue. To address it, we first propose an efficient sensing framework with a novel action detection module. In this module, a threshold is used for detecting whether the sensing target is static and thus the overhead can be reduced. Subsequently, we mathematically analyze the sensing performance of the proposed framework and theoretically prove its effectiveness with the help of the sampling theorem. Based on sensing performance models, we formulate a sensing performance maximization problem while guaranteeing the quality-of-service (QoS) requirements of tasks. To solve it, we propose an optimal resource allocation strategy, in which the minimum resource is allocated to computation tasks, and the rest is devoted to the sensing task. Besides, a threshold selection policy is derived and the results further demonstrate the necessity of the proposed sensing framework. Finally, a real-world test of action recognition tasks based on USRP B210 is conducted to verify the sensing performance analysis. Extensive experiments demonstrate the performance improvement of our proposal by comparing it with some benchmark schemes.
Geometric Constellation Shaping for Fiber-Optic Channels via End-to-End Learning

End-to-end learning has become a popular method to optimize a constellation shape of a communication system. When the channel model is differentiable, end-to-end learning can be applied with conventional backpropagation algorithm for optimization of the shape. A variety of optimization algorithms have also been developed for end-to-end learning over a non-differentiable channel model. In this paper, we compare a gradient-free optimization method based on the cubature Kalman filter, model-free optimization and backpropagation for end-to-end learning on a fiber-optic channel modeled by the split-step Fourier method. The results indicate that the gradient-free optimization algorithms provide a decent replacement to backpropagation in terms of performance at the expense of computational complexity. Furthermore, the quantization problem of finite bit resolution of the digital-to-analog and analog-to-digital converters is addressed and its impact on geometrically shaped constellations is analysed. Here, the results show that when optimizing a constellation with respect to mutual information, a minimum number of quantization levels is required to achieve shaping gain. For generalized mutual information, the gain is maintained throughout all of the considered quantization levels. Also, the results imply that the autoencoder can adapt the constellation size to the given channel conditions.
Variable Markov dynamics as a multi-focal lens to map multi-scale complex networks

From traffic flows on road networks to electrical signals in brain networks, many real-world networks contain modular structures of different sizes and densities. In the networks where modular structures emerge due to coupling between nodes with similar dynamical functions, we can identify them using flow-based community detection methods. However, these methods implicitly assume that communities are dense or clique-like which can shatter sparse communities due to a field-of-view limit inherent in one-step dynamics. Taking multiple steps with shorter or longer Markov time enables us to effectively zoom in or out to capture small or long-range communities. However, zooming out to avoid the field-of-view limit comes at the expense of introducing or increasing a lower resolution limit. Here we relax the constant Markov time constraint and introduce variable Markov dynamics as a multi-focal lens to capture functional communities in networks with a higher range of scales. With variable Markov time, a random walker can keep one-step dynamics in dense areas to avoid the resolution limit and move faster in sparse areas to detect long-range modular structures and prevent the field-of-view limit. We analyze the performance of variable Markov time using the flow-based community detection method called the map equation. We have implemented the map equation with variable Markov time in the search algorithm Infomap without any complexity overhead and tested its performance on synthetic and real-world networks from different domains. Results show that it outperforms the standard map equation in networks with constrained structures and locally sparse regions. In addition, the method estimates the optimal Markov time and avoids parameter tuning.
Fast GPU-based Two-way Continuous Collision Handling

Step-and-project is a popular method to simulate non-penetrating deformable bodies in physically based animation. The strategy is to first integrate the system in time without considering contacts and then resolve potential intersections, striking a good balance between plausibility and efficiency. However, existing methods can be defective and unsafe when using large time steps, taking risks of failure or demanding repetitive collision testing and resolving that severely degrade performance. In this article, we propose a novel two-way method for fast and reliable continuous collision handling. Our method launches an optimization from both ends of the intermediate time-integrated state and the previous intersection-free state. It progressively generates a piecewise linear path and eventually obtains a feasible solution for the next time step. The algorithm efficiently alternates between a forward step and a backward step until the result is conditionally converged. Thanks to a set of unified volume-based contact constraints, our method offers flexible and reliable handling of various codimensional deformable bodies, including volumetric bodies, cloth, hair, and sand. Experimental results demonstrate the safety, robustness, physical fidelity, and numerical efficiency of our method, making it particularly suitable for scenarios involving large deformations or large time steps.
MAGNETIC FIELDS AND COSMIC-RAY ANISOTROPIES AT TeV ENERGIES

Several cosmic-ray (CR) observatories have provided high-accuracy maps of the sky at TeV–PeV energies. The data reveal an O(0.1%) deficit from north galactic directions that peaks at 10 TeV and then evolves with the energy, together with other anisotropies at smaller angular scales. Using the Boltzmann equation, we derive expressions for the CR flux that fit these features. The anisotropies depend on the local interstellar magnetic field , on the average galactic field in our vicinity, and on correlations between fluctuating quantities. We show that the initial dipole anisotropy along can be modulated by changes in the global CR flow, and that a variation in the dipole direction would imply a given radius of coherence for the local . We also show that small- and medium-scale anisotropies may appear when the full-sky anisotropy finds a field configuration acting as a magnetic lens.
Some remarks on the attractor behaviour in ELKO cosmology

Recent results on the dynamical stability of a system involving the interaction of the ELKO spinor field with standard matter in the universe have been reanalysed, and the conclusion is that such system does not exhibit isolated stable points that could alleviate the cosmic coincidence problem. When a constant parameter δ related to the potential of the ELKO field is introduced in the system however, stable fixed points are found for some specific types of interaction between the ELKO field and matter. Although the parameter δ is related to an unknown potential, in order to satisfy the stability conditions and also that the fixed points are real, the range of the constant parameter δ can be constrained for the present time and the coincidence problem can be alleviated for some specific interactions. Such restriction on the ELKO potential opens possibility to apply the ELKO field as a candidate to dark energy in the universe, and so explain the present phase of acceleration of the universe through the decay of the ELKO field into matter.
Almost symmetric numerical semigroups with given Frobenius number and type

We give two algorithmic procedures to compute the whole set of almost symmetric numerical semigroups with fixed Frobenius number and type, and the whole set of almost symmetric numerical semigroups with fixed Frobenius number. Our algorithms allow to compute the whole set of almost symmetric numerical semigroups with fixed Frobenius number with similar or even higher efficiency that the known ones. They have been implemented in the GAP [The GAP Group, GAP — Groups, Algorithms and Programming, Version 4.8. 6; 2016, https://www.gap-system.org ] package NumericalSgps [M. Delgado and P. A. García-Sánchez and J. Morais, “numericalsgps”: A GAP package on numerical semigroups, https://github.com/gap-packages/numericalsgps ].
Motif-guided Time Series Counterfactual Explanations

With the rising need of interpretable machine learning methods, there is a necessity for a rise in human effort to provide diverse explanations of the influencing factors of the model decisions. To improve the trust and transparency of AI-based systems, the EXplainable Artificial Intelligence (XAI) field has emerged. The XAI paradigm is bifurcated into two main categories: feature attribution and counterfactual explanation methods. While feature attribution methods are based on explaining the reason behind a model decision, counterfactual explanation methods discover the smallest input changes that will result in a different decision. In this paper, we aim at building trust and transparency in time series models by using motifs to generate counterfactual explanations. We propose Motif-Guided Counterfactual Explanation (MG-CF), a novel model that generates intuitive post-hoc counterfactual explanations that make full use of important motifs to provide interpretive information in decision-making processes. To the best of our knowledge, this is the first effort that leverages motifs to guide the counterfactual explanation generation. We validated our model using five real-world time-series datasets from the UCR repository. Our experimental results show the superiority of MG-CF in balancing all the desirable counterfactual explanations properties in comparison with other competing state-of-the-art baselines.
COV19IR : COVID-19 Domain Literature Information Retrieval

Increasing number of COVID-19 research literatures cause new challenges in effective literature screening and COVID-19 domain knowledge aware Information Retrieval. To tackle the challenges, we demonstrate two tasks along withsolutions, COVID-19 literature retrieval, and question answering. COVID-19 literature retrieval task screens matching COVID-19 literature documents for textual user query, and COVID-19 question answering task predicts proper text fragments from text corpus as the answer of specific COVID-19 related questions. Based on transformer neural network, we provided solutions to implement the tasks on CORD-19 dataset, we display some examples to show the effectiveness of our proposed solutions.
Hydraulic Fracture

We consider a variation of Grifﬁth’s analysis of rupture, one which simulates the process of hydrofracturing, where ﬂuid forced into a crack raises the ﬂuid pressure until the crack begins to grow. Unlike that of Grifﬁth, in this analysis ﬂuid pressure drops as a hydrofracture grows. We ﬁnd that growth of the fracture depends on the ratio of the compliances of the ﬂuid and the fracture, a non-dimensional parameter called α 0 here. The pressure needed to initiate a hydrofracture is found to be the same as that derived by Grifﬁth. Once a fracture initiates, for relatively low values of the model parameter α 0 ( α 0 ≤ 0 . 2) the fracture advances spontaneously to a new radius which depends on the value of α 0 . For α 0 ≤ 0 . 2 further ﬂuid injection is required to increase the fracture radius after spontaneous growth stops. For the case where α 0 > 0 . 2 each increment of fracture growth requires injection of more ﬂuid. For the extreme case where α 0 = 0 our results are the same as Grifﬁth’s, i.e., a fracture once initiated grows without limit.