Miracle-dz/UniFAR-FTUs huggingface dataset:
Anticancer Nanotherapeutics in Clinical Trials: The Work behind Clinical Translation of Nanomedicine

The ultimate goal of nanomedicine has always been the generation of translational technologies that can ameliorate current therapies. Cancer disease represented the primary target of nanotechnology applied to medicine, since its clinical management is characterized by very toxic therapeutics. In this effort, nanomedicine showed the potential to improve the targeting of different drugs by improving their pharmacokinetics properties and to provide the means to generate new concept of treatments based on physical treatments and biologics. In this review, we considered different platforms that reached the clinical trial investigation, providing an objective analysis about their physical and chemical properties and the working mechanism at the basis of their tumoritr opic properties. With this review, we aim to help other scientists in the field in conceiving their delivering platforms for clinical translation by providing solid examples of technologies that eventually were tested and sometimes approved for human therapy.
Nonlinear H∞ Control Based on Successive Gaussian Process Regression

Nonlinear $H_{\infty }$ controllers can be designed based on the solution of the celebrated Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation (PDE) and generally hard to solve. In this brief, a concise but effective Gaussian process regression based method is proposed, and the solution of the HJI equation is obtained without explicitly discretizing the PDE. Based on the successive approximation technique, the nonlinear HJI PDE is transformed into a sequence of linear PDEs, and it is shown in this brief that solution to the linear PDE can be obtained by dealing with easily solvable initial value problems. Then a successive Gaussian process regression based method is designed, and the solution of the HJI equation is calculated by successively solving initial value problems and constructing regression models. Simulations are conducted and numerical results demonstrate its superior performance in accuracy and efficiency.
Biological Control of Oomycete Soilborne Diseases Caused by Phytophthora capsici, Phytophthora infestans, and Phytophthora nicotianae in Solanaceous Crops

Abstract Oomycete pathogens that belong to the genus Phytophthora cause devastating diseases in solanaceous crops such as pepper, potato, and tobacco, resulting in crop production losses worldwide. Although the application of fungicides efficiently controls these diseases, it has been shown to trigger negative side effects such as environmental pollution, phytotoxicity, and fungicide resistance in plant pathogens. Therefore, biological control of Phytophthora-induced diseases was proposed as an environmentally sound alternative to conventional chemical control. In this review, progress on biological control of the soilborne oomycete plant pathogens, Phytophthora capsici, Phytophthora infestans, and Phytophthora nicotianae, infecting pepper, potato, and tobacco is described. Bacterial (e.g., Acinetobacter, Bacillus, Chryseobacterium, Paenibacillus, Pseudomonas, and Streptomyces) and fungal (e.g., Trichoderma and arbuscular mycorrhizal fungi) agents, and yeasts (e.g., Aureobasidium, Curvibasidium, and Metschnikowia) have been reported as successful biocontrol agents of Phytophthora pathogens. These microorganisms antagonize Phytophthora spp. via antimicrobial compounds with inhibitory activities against mycelial growth, sporulation, and zoospore germination. They also trigger plant immunity-inducing systemic resistance via several pathways, resulting in enhanced defense responses in their hosts. Along with plant protection, some of the microorganisms promote plant growth, thereby enhancing their beneficial relations with host plants. Although the beneficial effects of the biocontrol microorganisms are acceptable, single applications of antagonistic microorganisms tend to lack consistent efficacy compared with chemical analogues. Therefore, strategies to improve the biocontrol performance of these prominent antagonists are also discussed in this review.
NONPLANAR INTEGRABILITY AND PARITY IN ABJ THEORY

In this paper, we study the action of the nonplanar two-loop dilatation operator in an SU(2)×SU(2) subsector of the ABJ Chern–Simons-matter theory. The gauge invariant operators we consider are the restricted Schur polynomials. As in ABJM theory, there is a limit in which the spectrum reduces to a set of decoupled harmonic oscillators, indicating integrability in the large M and N double limit of the theory. We then consider parity transformations on the gauge invariant operators. In this case the nonplanar anomalous dimensions break parity invariance. Our analysis shows that (M-N) is related to the holonomy in the string theory, confirming one of the main features of the theory and its string dual. Furthermore, in the limit where ABJ theory reduces to ABJM theory, parity invariance is restored.
Bacterial Community Succession, Transmigration, and Differential Gene Transcription in a Controlled Vertebrate Decomposition Model

Decomposing remains are a nutrient-rich ecosystem undergoing constant change due to cell breakdown and abiotic fluxes, such as pH level and oxygen availability. These environmental fluxes affect bacterial communities who respond in a predictive manner associated with the time since organismal death, or the postmortem interval (PMI). Profiles of microbial taxonomic turnover and transmigration are currently being studied in decomposition ecology, and in the field of forensic microbiology as indicators of the PMI. We monitored bacterial community structural and functional changes taking place during decomposition of the intestines, bone marrow, lungs, and heart in a highly controlled murine model. We found that organs presumed to be sterile during life are colonized by Clostridium during later decomposition as the fluids from internal organs begin to emulsify within the body cavity. During colonization of previously sterile sites, gene transcripts for multiple metabolism pathways were highly abundant, while transcripts associated with stress response and dormancy increased as decomposition progressed. We found our model strengthens known bacterial taxonomic succession data after host death. This study is one of the first to provide data of expressed bacterial community genes, alongside transmigration and structural changes of microbial species during laboratory controlled vertebrate decomposition. This is an important dataset for studying the effects of the environment on bacterial communities in an effort to determine which bacterial species and which bacterial functional pathways, such as amino acid metabolism, provide key changes during stages of decomposition that relate to the PMI. Finding unique PMI species or functions can be useful for determining time since death in forensic investigations.
Generalized probabilistic theories without the no-restriction hypothesis

The framework of generalized probabilistic theories (GPTs) is a popular approach for studying the physical foundations of quantum theory. The standard framework assumes the no-restriction hypothesis, in which the state space of a physical theory determines the set of measurements. However, this assumption is not physically motivated. We generalize the framework to account for systems that do not obey the no-restriction hypothesis. We then show how our framework can be used to describe new classes of probabilistic theories, for example those which include intrinsic noise. Relaxing the restriction hypothesis also allows us to introduce a 'self-dualization' procedure, which yields a new class of theories that share many features of quantum theory, such as obeying Tsirelson's bound for the maximally entangled state. We then characterize joint states, generalizing the maximal tensor product. We show how this new tensor product can be used to describe the convex closure of the Spekkens toy theory, and in doing so we obtain an analysis of why it is local in terms of the geometry of its state space. We show that the unrestricted version of the Spekkens toy theory is the theory known as 'boxworld' that allows maximal nonlocal correlations.
Controllability Criteria on Discrete-Time Impulsive Hybrid Systems With Input Delay

Due to the importance of the hybrid systems, the controllability for linear discrete-time impulsive hybrid systems with input delay (DIHSID) is investigated by resorting to the geometric and algebraic analytical methods in this article. First, the null reachability and controllability geometric conditions are studied. Specifically, the null reachable set and controllable set for every impulsive and switching sequence are obtained by the properties of the invariant subspace. Besides, a new subspace sequence is constructed to analyze the null reachability and controllability of DIHSID. Second, the complete controllability of DIHSID is investigated by algebraic methods. In the form of Gramian matrices, several sufficient complete controllability conditions for DIHSID are established without assuming the nonsingularity of all impulsive matrices. Furthermore, a less conservative complete controllability criterion that is necessary and sufficient is developed by introducing a row matrix of some Gramian matrices. Finally, two illustrating examples show the effectiveness of the developed controllability theory.
Josephson coupling in junctions made of monolayer graphene on SiC

Graphene on silicon carbide (SiC) has proved to be highly successful in Hall conductance quantization for its homogeneity at the centimetre scale. Robust Josephson coupling has been measured in co-planar diffusive Al/monololayer graphene/Al junctions. Graphene on SiC substrates is a concrete candidate to provide scalability of hybrid Josephson graphene/superconductor devices, giving also promise of ballistic propagation.
Accurate and Efficient Surrogate Model-Assisted Optimal Design of Flux Reversal Permanent Magnet Arc Motor

An accurate and efficient surrogate model plays a significant role in the optimal design of electrical motors. This article presents an accurate and efficient surrogate modeling method for a flux reversal permanent magnet arc motor (FR-PMAM) based on machine learning algorithm. Specifically, the motor topology and the optimized design of the FR-PMAM are firstly illustrated. Then, the PM magnetic motive force-permeance model is developed to select structural parameters of FR-PMAM. After that, a finite-element analysis (FEA) model of FR-PMAM is calculated to obtain sample data. A machine learning algorithm random forest is introduced into the field of motor optimal design for the first time to evaluate the contribution of each parameter to the design objectives. Based on the sample data, an efficient machine learning algorithm CatBoost is innovatively employed to establish the accurate and efficient surrogate model of the FR-PMAM that can capture the complex function relationship between output objectives and input parameters. Subsequently, an improved genetic algorithm with the elitist reservation strategy is adopted to obtain the optimal combination of the structural parameters of FR-PMAM. Finally, a prototype of the FR-PMAM is manufactured. The FEA and experimental results validate the effectiveness of the investigated surrogate modeling method.
Experimental signatures of a light singlet-like scalar in NMSSM

NMSSM with a light singlet-like scalar and strongly suppressed couplings to $b$ and $\tau$ is investigated. It is shown that in such a scenario the singlet-like scalar to diphoton signal can be larger than for the SM Higgs for a wide range of masses between 60 and 110 GeV, in agreement with all the LEP and LHC data. Enhancement of the singlet-like scalar to diphoton signal is correlated with positive correction to the SM-like Higgs mass from mixing between SM-like Higgs and the singlet. It is also shown that the couplings to $b$ and $\tau$ and, in consequence, branching ratios of the SM-like Higgs are anti-correlated with those of the singlet-like scalar. If the singlet-like scalar to diphoton signal is enhanced, the signal strengths of the 125 GeV Higgs in the diphoton and $WW^*/ZZ^*$ channels are predicted to be smaller than for the SM Higgs.
Quantum corrections to the dynamics of the expanding universe

The dynamics of the expanding universe is analyzed in terms of the quantum geometrodynamical model. It is shown that the equations of quantum theory in the form of the eigenvalues equation similar to the stationary Schr\"{o}dinger equation complemented by the equations of motion for the momentum operator and its time derivative in Heisenberg's form reduce to the Einstein equations with an additional source of the gravitational field of quantum nature. The spatially closed universe with cosmological constant, originally filled with a uniform scalar field and radiation, is considered as quantum cosmological system. The perfect fluid in the form of radiation defines the material reference frame. The properties of the averaged scalar field which acts like ordinary matter are investigated. After averaging over its quantum states, the free scalar field turns into the Weyssenhoff fluid characterized by the energy density, pressure, and spin of constituent particles. The cases when the contribution of the quantum effects into the gravitational interaction becomes significant on macroscopic scale are analyzed. It is demonstrated that, unless the whole, at least a part of such matter-energy constituents as dark matter and dark energy may have a quantum origin.
Asymptotic work statistics of periodically driven Ising chains

We study the work statistics of a periodically-driven integrable closed quantum system, addressing in particular the role played by the presence of a quantum critical point. Taking the example of a one-dimensional transverse Ising model in the presence of a spatially homogeneous but periodically time-varying transverse field of frequency ω0 ? >, we arrive at the characteristic cumulant generating function G(u), which is then used to calculate the work distribution function P(W). By applying the Floquet theory we show that, in the infinite time limit, P(W) converges, starting from the initial ground state, towards an asymptotic steady state value whose small-W behaviour depends only on the properties of the small-wave-vector modes and on a few important ingredients: the time-averaged value of the transverse field, h0, the initial transverse field, hi ? >, and the equilibrium quantum critical point hc ? >, which we find to generate a sequence of non-equilibrium critical points h*l=hc+lω0/2 ? >, with l integer. When hi≠hc ? >, we find a ‘universal’ edge singularity in P(W) at a threshold value of Wth=2|hi−hc| ? > which is entirely determined by hi ? >. The form of that singularity—Dirac delta derivative or square root—depends on h0 being or not at a non-equilibrium critical point h*l. On the contrary, when hi=hc ? >, G(u) decays as a power-law for large u, leading to different types of edge singularity at Wth=0 ? >. Generalizing our calculations to the case in which we initialize the system in a finite temperature density matrix, the irreversible entropy generated by the periodic driving is also shown to reach a steady state value in the infinite time limit.
Cohomologically Cofinite Complexes

Let A be a commutative noetherian ring, and 𝔞 an ideal in it. In this paper we continue the study, begun in [11], of the derived 𝔞-adic completion and the derived 𝔞-torsion functors. Here are our results: (1) a structural characterization of bounded above cohomologically complete complexes; (2) the Cohomologically Complete Nakayama Theorem; and (3) a characterization of cohomologically cofinite complexes.
Rms–flux relation and fast optical variability simulations of the nova-like system MV Lyr

The stochastic variability (flickering) of the nova-like system (subclass of cataclysmic variable) MV Lyr yields a complicated power density spectrum with four break frequencies. Scaringi et al. (2012) analysed high-cadence Kepler data of MV Lyr, taken almost continuously over 600 days, giving the unique opportunity to study multicomponent Power Density Spectra (PDS) over a wide frequency range. We modelled this variability with our statistical model based on disc angular momentum transport via discrete turbulent bodies with an exponential distribution of the dimension scale. Two different models were used, a full disc (developed from the white dwarf to the outer radius of ~10^10 cm) and a radially thin disc (a ring at a distance of ~10^10 cm from the white dwarf) that imitates an outer disc rim. We succeed in explaining the two lowest observed break frequencies assuming typical values for a disc radius of 0.5 and 0.9 times the primary Roche lobe and an alpha parameter of 0.1-0.4. The highest observed break frequency was also modelled, but with a rather small accretion disc with radius of 0.3 times the primary Roche lobe and a high alpha value of 0.9 consistent with previous findings by Scaringi (2014). Furthermore, the simulated light curves exhibit the typical linear rms-flux proportionality linear relation and the typical log-normal flux distribution. As the turbulent process is generating fluctuations in mass accretion that propagate through the disc, this confirms the general knowledge that the typical rms-flux relation is mainly generated by these fluctuations. In general a higher rms is generated by a larger amount of superposed flares which is compatible with a higher mass accretion rate expressed by a larger flux.
Model-independent constraints on the cosmological anisotropic stress

= / is a key variable in the characterisation of the physical origin of the dark energy, as it allows to test for a non-minimal coupling of the dark sector to gravity in the Jordan frame. It is however important to use a fully modelindependent approach when measuring to avoid introducing a theoretical bias into the results. In this paper we forecast the precision with which future large surveys can determine in a way that only relies on directly observable quantities. In particular, we do not assume anything concerning the initial spectrum of perturbations, nor on its evolution outside the observed redshift range, nor on the galaxy bias. We first leave free to vary in space and time and then we model it as suggested in Horndeski models of dark energy. Among our results, we find that a future large scale lensing and clustering survey can constrain to within 10% if k-independent, and to within 60% or better at k = 0.1h/Mpc if it is restricted to follow the Horndeski model.
The number of \bar{2}413\bar{5}-avoiding permutations

We answer a question of R. J. Mathar and confirm that the counting sequence for $\bar{2}413\bar{5}$-avoiding permutations is the Invert transform of the Bell numbers. The proof relies on a simple decomposition of these permutations and the known fact that $\bar{2}413$-avoiding permutations are counted by the Bell numbers.
Enhanced absorption of monolayer MoS2 with resonant back reflector

The optical absorption of monolayer MoS2 on top of one-dimensional photonic crystal (1DPC) or metal films with spacer layers is theoretically investigated by extracting the permittivity of monolayer MoS2 from existing experimental results [K. F. Mak et al., Phys. Rev. Lett. 105, 136805 (2010)]. The absorption of graphene with 1DPC across a broad spectral range is substantially enhanced because of the photonic localization at the optical micro-cavity on top of the 1DPC or metal films. The absorption of monolayer MoS2 can be tuned by varying either the distance between the monolayer MoS2 and the back reflector or the thickness of the cover layers.
Dynamics of helical vortices and helical-vortex rings

The letter considers dynamics of helical vortices and helical-vortex rings either solving directly the equations of motions of a vortex line or using canonical relations following from the Hamiltonian equations of motion. An analytical solution in elliptical integrals was found for helical-vortex rings in the local-induction approximation. The analysis based on the canonical Hamilton relation provides a clear physical explanation for anomalous velocities of helical-vortex rings, i.e., for suppression of the velocity and even inversion of its direction at sufficiently large amplitude of the helical distortion. The extended local-induction approximation is suggested, which provides an exact solution for the equations of motion of helical vortices and helical-vortex rings in the limit when the small-pitch helical vortex reduces to a cylindric sheet of uniform vorticity.
TESTING THE DARK ENERGY WITH GRAVITATIONAL LENSING STATISTICS

We study the redshift distribution of two samples of early-type gravitational lenses, extracted from a larger collection of 122 systems, to constrain the cosmological constant in the ΛCDM model and the parameters of a set of alternative dark energy models (XCDM, Dvali-Gabadadze-Porrati, and Ricci dark energy models), in a spatially flat universe. The likelihood is maximized for ΩΛ = 0.70 ± 0.09 when considering the sample excluding the Sloan Lens ACS systems (known to be biased toward large image-separation lenses) and no-evolution, and ΩΛ = 0.81 ± 0.05 when limiting to gravitational lenses with image separation Δθ > 2″ and no-evolution. In both cases, results accounting for galaxy evolution are consistent within 1σ. The present test supports the accelerated expansion, by excluding the null hypothesis (i.e., ΩΛ = 0) at more than 4σ, regardless of the chosen sample and assumptions on the galaxy evolution. A comparison between competitive world models is performed by means of the Bayesian information criterion. This shows that the simplest cosmological constant model—that has only one free parameter—is still preferred by the available data on the redshift distribution of gravitational lenses. We perform an analysis of the possible systematic effects, finding that the systematic errors due to sample incompleteness, galaxy evolution, and model uncertainties approximately equal the statistical errors, with present-day data. We find that the largest sources of systemic errors are the dynamical normalization and the high-velocity cutoff factor, followed by the faint-end slope of the velocity dispersion function.
Generative pulsar timing analysis

A new Bayesian method for the analysis of folded pulsar timing data is presented that allows for the simultaneous evaluation of evolution in the pulse profile in either frequency or time, along with the timing model and additional stochastic processes such as red spin noise, or dispersion measure variations. We model the pulse profiles using `shapelets' - a complete ortho-normal set of basis functions that allow us to recreate any physical profile shape. Any evolution in the profiles can then be described as either an arbitrary number of independent profiles, or using some functional form. We perform simulations to compare this approach with established methods for pulsar timing analysis, and to demonstrate model selection between different evolutionary scenarios using the Bayesian evidence. %s The simplicity of our method allows for many possible extensions, such as including models for correlated noise in the pulse profile, or broadening of the pulse profiles due to scattering. As such, while it is a marked departure from standard pulsar timing analysis methods, it has clear applications for both new and current datasets, such as those from the European Pulsar Timing Array (EPTA) and International Pulsar Timing Array (IPTA).