Miracle-dz/UniFAR-FTUs huggingface dataset:
Photo-thermal study of a layer of randomly distributed gold nanoparticles: from nano-localization to macro-scale effects

We present an experimental characterization and a comprehensive theoretical modeling of macroscopic plasmonic heat production that takes place in a single layer of small gold nanoparticles (GNPs), randomly distributed on a glass substrate, covered with different host media and acted on by a resonant radiation. We have performed a detailed experimental study of the temperature variations of three different systems, obtained by varying the density of nanoparticles. Due to the macroscopic dimension of the spot size, the used laser irradiates a huge number of nanoparticles, inducing a broad thermo-plasmonic effect that modifies the thermal conductivity of the entire system; starting from the state of art, we have implemented a simple model that enables to evaluate the resulting new thermal conductivity. We have also extended our theoretical approach to the macroscale, including an analysis of the effects predicted for different NP densities and laser spot size values, as well as for different values of the laser intensity, which can be as low as 0.05 W cm−2. Theoretically predicted temperature variations are in excellent agreement with experimental results.
Search for a diffuse astrophysical neutrino flux with KM3NeT/ARCA using data of 2021-2022

KM3NeT is a research infrastructure hosting two neutrino detectors which are currently under construction in the Mediterranean Sea. The KM3NeT/ARCA detector focuses on the detection of high energy neutrinos (>TeV) from astrophysical sources. In this contribution, an analysis of the data obtained during 2021-2022, using machine learning techniques
Numerical study of thermal effects in low dimensional quantum spin systems

This thesis is composed by three projects in which we investigate thermal effects in low dimensional quantum spin systems. Thanks to recent developments in DMRG/MPS techniques, it is possible to simulate for such systems the dynamics at finite temperature. This allows us in the first two parts to study the temperature dependence of the NMR spin-lattice relaxation rate and of the INS spectra. Numerical calculations are performed for a wide range of temperatures. This represents a bridge between analytical results available for very low and very high temperatures. Interesting deviations from bosonization results valid at low energy, are seen at temperatures comparable to the energy scale of the system. In the third part we study the temperature and magnetic field dependence of the Gruneisen parameter, a valuable quantity for the detection and investigation of quantum phase transitions. Using an effective theory valid close to criticality, we show deviations from the critical behavior.
The Targets of Opportunity Source Catalog for the EUSO-SPB2 Mission

The Extreme Universe Space Observatory on a Super Pressure Balloon 2, EUSO SPB2, mission was designed to take optical measurements of extensive air showers, EASs, from suborbital space. The EUSO SPB2 payload includes an optical Cherenkov Telescope, CT, which searches above and below the Earth's limb. Above the limb, the CT measures Cherenkov light from PeV scale EASs induced by cosmic rays. Below the limb, the CT searches for upwards going Cherenkov emission from PeV scale EASs induced by tau neutrinos, to follow up on astrophysical Targets of Opportunity, ToO. Target candidates include gamma ray bursts, tidal disruption events, and, after the start of the O4 obervation run from Ligo, Virgo, Kagra, binary neutron star mergers. Reported here is the selection and prioritization of relevant ToOs from alert networks such as the General Coordinates Network, Transient Name Server, and Astronomer Telegrams, and the translation to a viewing schedule for EUSO SPB2. EUSO SPB2 launched on a NASA super pressure balloon in May of 2023 from Wanaka, NZ.
The laplacian operator on a Riemann surface, III

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An SCN1A gene missense variant in a Chinese Tujia ethnic family with genetic epilepsy with febrile seizures plus

Genetic epilepsy with febrile seizures plus (GEFSP) is a familial epileptic syndrome that is genetically heterogeneous and inherited in an autosomal dominant form in most cases. To date, at least seven genes have been reported to associate with GEFSP. This study aimed to identify the disease-causing variant in a Chinese Tujia ethnic family with GEFSP by using whole exome sequencing, Sanger sequencing, and in silico prediction. A heterozygous missense variant c.5725A>G (p.T1909A) was identified in the sodium voltage-gated channel alpha subunit 1 gene (SCN1A) coding region. The variant co-segregated with the GEFSP phenotype in this family, and it was predicted as disease-causing by multiple in silico programs, which was proposed as the genetic cause of GEFSP, further genetically diagnosed as GEFSP2. These findings expand the genetic and phenotypic spectrum of GEFSP and should contribute to genetic diagnoses, personalized therapies, and prognoses.
Lignins as Promising Renewable Biopolymers and Bioactive Compounds for High-Performance Materials

The recycling of biomass into high-value-added materials requires important developments in research and technology to create a sustainable circular economy. Lignin, as a component of biomass, is a multipurpose aromatic polymer with a significant potential to be used as a renewable bioresource in many fields in which it acts both as promising biopolymer and bioactive compound. This comprehensive review gives brief insights into the recent research and technological trends on the potential of lignin development and utilization. It is divided into ten main sections, starting with an outlook on its diversity; main properties and possibilities to be used as a raw material for fuels, aromatic chemicals, plastics, or thermoset substitutes; and new developments in the use of lignin as a bioactive compound and in nanoparticles, hydrogels, 3D-printing-based lignin biomaterials, new sustainable biomaterials, and energy production and storage. In each section are presented recent developments in the preparation of lignin-based biomaterials, especially the green approaches to obtaining nanoparticles, hydrogels, and multifunctional materials as blends and bio(nano)composites; most suitable lignin type for each category of the envisaged products; main properties of the obtained lignin-based materials, etc. Different application categories of lignin within various sectors, which could provide completely sustainable energy conversion, such as in agriculture and environment protection, food packaging, biomedicine, and cosmetics, are also described. The medical and therapeutic potential of lignin-derived materials is evidenced in applications such as antimicrobial, antiviral, and antitumor agents; carriers for drug delivery systems with controlled/targeting drug release; tissue engineering and wound healing; and coatings, natural sunscreen, and surfactants. Lignin is mainly used for fuel, and, recently, studies highlighted more sustainable bioenergy production technologies, such as the supercapacitor electrode, photocatalysts, and photovoltaics.
Identification of the linear factor model

Abstract This paper provides several new results on identification of the linear factor model. The model allows for correlated latent factors and dependence among the idiosyncratic errors. I also illustrate identification under a dedicated measurement structure and other reduced rank restrictions. I use these results to study identification in a model with both observed covariates and latent factors. The analysis emphasizes the different roles played by restrictions on the error covariance matrix, restrictions on the factor loadings and the factor covariance matrix, and restrictions on the coefficients on covariates. The identification results are simple, intuitive, and directly applicable to many settings.
Microagressões raciais nas ciências exatas

Neste artigo apresentamos resultados de uma pesquisa em que buscamos identificar as experiências de estudantes da área de Ciências Exatas com microagressões raciais. O público-alvo da pesquisa foi composto por estudantes beneficiários de ações afirmativas matriculados em cursos da área de Ciências Exatas da Universidade Federal de Alfenas (n=390) que responderam um instrumento denominado Escala de Experiências Acadêmicas, Sociais e de Sobrevivência no âmbito das Exatas (EASS-Exatas). Para a análise, utilizamos correlações e Spearman, teste de significância qui-quadrado e Análise de Componentes Principais (ACP). Os resultados indicam que estudantes com idade entre 20 e 30 anos identificam com maior clareza aspectos relacionados às microagressões raciais. Além disso, os estudantes autodeclarados pretos foram aqueles que vivenciaram de forma mais intensa as microagressões raciais, inclusive com scores acima dos estudantes autodeclarados pardos, que também compõem o grupo de estudantes negros no Brasil. Isso evidencia que a cor da pele está diretamente relacionada às experiências com racismo e com microagressões raciais vivenciadas pelos estudantes. Mesmo vencendo a barreira do acesso, estudantes cotistas negros e negras de cursos de exatas continuam enfrentando o desafio de sobreviver academicamente devido a violência estrutural que vivenciam durante sua trajetória no curso e na universidade.
Dual purpose passive screen for simultaneous display and imaging

Advanced imaging and display techniques are widely explored for realistic content capture and visualization but cannot fully follow the miniaturization and mobility trends in technology. Wide field-of-view displays require large surfaces and image capture requires separate installation of cameras having separate footprints and perspective views. Here we propose a novel, portable dual purpose passive screen that can simultaneously facilitate display and imaging with unprecedented features and performance. The optical design of the screen is presented. A prototype of the dual-purpose screen paired with a camera and a low power mobile projector is demonstrated. The developed screen has size of 28×21cm2 to facilitate capture of eye contacted perspective view and displays high-quality images with high-brightness (>100cd/m2 ) using only 15 lumen pico projector.
Young Ocean Waves Favor the Rapid Intensification of Tropical Cyclones—A Global Observational Analysis

Identifying the condition(s) of how tropical cyclones intensify, in particular rapid intensification, is challenging, because of the complexity of the problem involving internal dynamics, environments, and mutual interactions; yet the benefit to improved forecasts may be rewarding. To make the analysis more tractable, an attempt is made here focusing near the sea surface, by examining 23-yr global observations comprising over 16 000 cases of tropical cyclone intensity change, together with upper-ocean features, surface waves, and low-level atmospheric moisture convergence. Contrary to the popular misconception, we found no statistically significant evidence that thicker upper-ocean layers and/or warmer temperatures are conducive to rapid intensification. Instead, we found in storms undergoing rapid intensification significantly higher coincidence of low-level moisture convergence and a dimensionless air–sea exchange coefficient closely related to the youth of the surface waves under the storm. This finding is consistent with the previous modeling results, verified here using ensemble experiments, that higher coincidence of moisture and surface fluxes tends to correlate with intensification, through greater precipitation and heat release. The young waves grow to saturation in the right-front quadrant as a result of trapped-wave resonance for a group of Goldilocks cyclones that translate neither too slowly nor too quickly, which 70% of rapidly intensifying storms belong. Young waves in rapidly intensifying storms also produce relatively less (as percentage of the wind input) Stokes-induced mixing and cooling in the cyclone core. A reinforcing coupling between tropical cyclone wind and waves leading to rapid intensification is proposed.
Data Characteristics and Preliminary Results from the Atacama B-Mode Search (ABS)

The Atacama B-Mode Search (ABS) is a 145 GHz polarimeter located at a high altitude site on Cerro Toco, in the Andes of northern Chile. Having deployed in early 2012, it is currently in its second year of operation, observing the polarization of the Cosmic Microwave Background (CMB). It seeks to probe the as yet undetected odd-parity B-modes of the polarization, which would have been created by the primordial gravitational wave background (GWB) predicted by theories of inflation. The magnitude of the B-mode signal is characterized by the tensor-to-scalar ratio, r. ABS features 60 cm cryogenic reflectors in the crossed-Dragone configuration, and a warm, continuously rotating sapphire half-wave plate to modulate the polarization of incoming radiation. The focal plane consists of 480 antenna-coupled transition edge sensor bolometers, arranged in orthogonal pairs for polarization sensitivity, and coupled to feedhorns in a hexagonal array. In this thesis we describe the ABS instrument in the state in which it is now operating, outline the first season of observations, and characterize the data obtained. Focusing on observations of the primary CMB field during a one month reference period, we detail the algorithms currently used to select the data suitable for making maps. This is the first pass at data cuts and provides a conservative estimate for the sensitivity of ABS to the polarization modes in the sky. We project that with one year total observation time of the primary CMB field, ABS should be able to detect the B-mode signal at roughly the level of r = 0.03.
Convergence and stability of iteratively reweighted least squares for low-rank matrix recovery

In this paper, we study the theoretical properties of iteratively reweighted least squares algorithm for recovering a matrix (IRLS-M for short) from noisy linear measurements. The IRLS-M was proposed by Fornasier et al. (2011) [ 17 ] for solving nuclear norm minimization and by Mohan et al. (2012) [ 31 ] for solving Schatten- \begin{document}$p$\end{document} (quasi) norm minimization ( \begin{document}$0 ) in noiseless case, based on the iteratively reweighted least squares algorithm for sparse signal recovery (IRLS for short) (Daubechies et al., 2010) [ 15 ], and numerical experiments have been given to show its efficiency (Fornasier et al. and Mohan et al.) [ 17 ], [ 31 ]. In this paper, we focus on providing convergence and stability analysis of iteratively reweighted least squares algorithm for low-rank matrix recovery in the presence of noise. The convergence of IRLS-M is proved strictly for all \begin{document}$0 . Furthermore, when the measurement map \begin{document}$\mathcal{A}$\end{document} satisfies the matrix restricted isometry property (M-RIP for short), we show that the IRLS-M is stable for \begin{document}$0 . Specially, when \begin{document}$p=1$\end{document} , we prove that the M-RIP constant \begin{document}$δ_{2r} is sufficient for IRLS-M to recover an unknown (approximately) low rank matrix with an error that is proportional to the noise level. The simplicity of IRLS-M, along with the theoretical guarantees provided in this paper, make a compelling case for its adoption as a standard tool for low rank matrix recovery.
Determining the Elastic Constants of Isotropic Materials by Measuring the Phase Velocities of the A0 and S0 Modes of Lamb Waves

In this study, a new method for determining the elastic constants of isotropic plates using Lamb wave fundamental modes is presented. This method solves the inverse problem, where the elastic constants (Young’s modulus and Poisson’s ratio) of the plate were estimated by measuring the phase velocities of the Lamb wave using the Rayleigh–Lamb equations to find the solution and determining the phase velocities of the A0 and S0 modes using a new method. The suitability of the proposed method for determining the elastic constants was evaluated using simulated and experimental signals propagating on an aluminum plate. The theoretical modeling on the aluminum 7075-T6 plate shows that the proposed method allows the determination of the Poisson ratio with a relative error not exceeding 2% and Young’s modulus with a relative error not exceeding 0.5%. The experimental measurements of an aluminum plate of known thickness (2 mm) and density (2685 kg/m3) confirmed the suitability of the proposed method for the measurements of elastic constants. In the proposed method, the processing of ultrasonic signals can be performed in real-time, and the values of the elastic constants can be obtained immediately after scanning the required distance.
MTL-FaultNet: Seismic Data Reconstruction Assisted Multitask Deep Learning 3-D Fault Interpretation

Seismic fault interpretation is of extraordinary significant for hydrocarbon reservoir characterization and drilling hazard mitigation. In recent years, deep learning-based seismic fault detection methods have been conducted actively. Considering efficiency and fault prediction consistency, the most appealing way is to train a 3-D segmentation network using synthetic seismic data with ground-truth fault structure. However, the differences in signal-to-noise ratio, resolution, and fault strike distribution between synthetic and real data can lead to inconsistent and unreliable prediction results. In this article, we propose a multitask deep learning-based seismic fault detection method, which takes seismic fault detection as the main task and 3-D seismic data reconstruction as the auxiliary task, named MTL-FaultNet. The auxiliary branch can provide suggestive information to the main branch, thus improving its performance. We also design two levels of multiscale modules and embedded attention mechanisms in the network, so as to improve the network’s ability to focus on multiscale fault features and learn stable fault structures. Different weights are assigned to the loss for different tasks, with large and small weights on the main and auxiliary branches, respectively. We apply the proposed method to Netherlands offshore F3 seismic data and a land field seismic data collected from Tarim Basin with mainly strike-slip faults, and Poseidon 3-D seismic data. The proposed fault detection method is experimentally demonstrated on the improved network generalization and achieves reliable fault interpretation on field seismic data.
Polymeric-Micelle-Based Delivery Systems for Nucleic Acids

Nucleic acids can modulate gene expression specifically. They are increasingly being utilized and show huge potential for the prevention or treatment of various diseases. However, the clinical translation of nucleic acids faces many challenges due to their rapid clearance after administration, low stability in physiological fluids and limited cellular uptake, which is associated with an inability to reach the intracellular target site and poor efficacy. For many years, tremendous efforts have been made to design appropriate delivery systems that enable the safe and effective delivery of nucleic acids at the target site to achieve high therapeutic outcomes. Among the different delivery platforms investigated, polymeric micelles have emerged as suitable delivery vehicles due to the versatility of their structures and the possibility to tailor their composition for overcoming extracellular and intracellular barriers, thus enhancing therapeutic efficacy. Many strategies, such as the addition of stimuli-sensitive groups or specific ligands, can be used to facilitate the delivery of various nucleic acids and improve targeting and accumulation at the site of action while protecting nucleic acids from degradation and promoting their cellular uptake. Furthermore, polymeric micelles can be used to deliver both chemotherapeutic drugs and nucleic acid therapeutics simultaneously to achieve synergistic combination treatment. This review focuses on the design approaches and current developments in polymeric micelles for the delivery of nucleic acids. The different preparation methods and characteristic features of polymeric micelles are covered. The current state of the art of polymeric micelles as carriers for nucleic acids is discussed while highlighting the delivery challenges of nucleic acids and how to overcome them and how to improve the safety and efficacy of nucleic acids after local or systemic administration.
Algorithms on special classes of graphs and partially ordered sets

This thesis addresses a variety of problems on special classes of graphs and partially ordered sets. Special classes of graphs arise in many applications. On these classes of graphs, many problems are found to have faster algorithms. We first present a fast algorithm for split decomposition. Split decomposition has been used in solving other problems. Recently, it provides the basis for recognition algorithms on circle graphs. Substitution decomposition is a more restricted version of split decomposition. We introduce a linear time algorithm to perform substitution decomposition on chordal graphs. Some potential applications are also pointed out. Matrix multiplication is a commonly used tool in solving many combinatorial problems. For example, it provides the fastest algorithm to solve the transitive closure and the neighborhood containment problems. We show that by using a characterization of N-free posets, we can avoid matrix multiplication and find a faster algorithm for the transitive closure problem on N-free posets. The chain subgraph cover problem has been a useful vehicle in proving NP-completeness of many open problems. In this thesis, we further explore the relationship between chain graphs and posets. We also find many problems which can be easily transformed into the two chain subgraph cover problem. By presenting an O($n\sp2$) reduction from the two chain subgraph cover problem to the partial order dimension two problem, we develop O($n\sp2$) algorithms for bidimension two, Ferrers dimension two, interval dimension two, and trapezoid graph recognition problems. The dimension of posets is one of the most studied invariant of posets. A poset is called cycle-free if its comparability graph is chordal. Using the clique tree representations of chordal graphs, we prove that every cycle-free poset is at most 4 dimensional.