Miracle-dz/UniFAR-FTUs huggingface dataset:
Characteristics of Tropical Convective Gravity Waves Resolved by ERA5 Reanalysis

ERA5 reanalysis with hourly time steps and ~30 km horizontal resolution resolves a substantially larger fraction of the gravity wave spectrum than its predecessors. Based on a representation of the two-sided zonal wavenumber-frequency spectrum, we show evidence of gravity wave signatures in a suite of atmospheric fields. Cross-spectrum analysis reveals (i) a substantial upward flux of geopotential for both eastward and westward propagating waves, (ii) an upward flux of westerly momentum in eastward propagating waves and easterly momentum in westward propagating waves, and (iii) anticyclonic rotation of the wind vector with time— all characteristics of vertically propagating gravity and inertio-gravity waves. Two-sided meridional wavenumber-frequency spectra, which are computed along individual meridians and then zonally averaged, exhibit characteristics similar to the spectra computed on latitude circles, indicating that these waves propagate in all directions. The three-dimensional structure of these waves is also documented in composites of the temperature field relative to grid-resolved, wave-induced downwelling events at individual reference grid points along the equator. It is shown that the waves radiate outward and upward relative to the respective reference grid points, and their amplitude decreases rapidly with time. Within the broad continuum of gravity wave phase speeds there are preferred values around ±49 m s−1 and ±23 m s−1, the former associated with the first baroclinic mode in which the vertical velocity perturbations are of the same sign throughout the depth of the troposphere, and the latter with the second mode in which they are of opposing polarity in the lower and upper troposphere.
Exploring Deep Learning for Metalloporphyrins: Databases, Molecular Representations, and Model Architectures

Metalloporphyrins have been studied as biomimetic catalysts for more than 120 years and have accumulated a large amount of data, which provides a solid foundation for deep learning to discover chemical trends and structure–function relationships. In this study, key components of deep learning of metalloporphyrins, including databases, molecular representations, and model architectures, were systematically investigated. A protocol to construct canonical SMILES for metalloporphyrins was proposed, which was then used to represent the two-dimensional structures of over 10,000 metalloporphyrins in an existing computational database. Subsequently, several state-of-the-art chemical deep learning models, including graph neural network-based models and natural language processing-based models, were employed to predict the energy gaps of metalloporphyrins. Two models showed satisfactory predictive performance (R2 0.94) with canonical SMILES as the only source of structural information. In addition, an unsupervised visualization algorithm was used to interpret the molecular features learned by the deep learning models.
On the generic local Langlands correspondence for GSpin groups

In the case of split $GSpin$ groups, we prove an equality of $L$-functions between automorphic local $L$-functions defined by the Langlands-Shahidi method and local Artin $L$-functions. Our method of proof is based on previous results of the first author which allow to reduce the problem to supercuspidal representations of Levi subgroups of $GSpin$, by constructing Langlands parameters for general generic irreducible admissible representations of $GSpin $ from the one for generic irreducible supercuspidal representations of its Levi subgroups.
Underwater pressure measurement using fibre optic extrinsic Fabry-Perot interferometric (EFPI) sensors

A fibre optic extrinsic Fabry Perot Interferometer (EFPI) sensor is developed for monitoring pressure in the underwater and sub-seabed under simulated conditions. The sensor is robust in design and is fabricated entirely from Silica glass. The EFPI is formed at the tip of the fibre, where the single mode is spliced to a 200μm capillary, sealed by a 200μm Multimode, which forms the diaphragm. The diaphragm thickness is reduced by polishing and etching with hydrofluoric (HF) acid to about 2-3μm for a high sensitivity. The thickness of the diaphragm is monitored online during polishing and HF etching. The spectrum of the fibre optic sensor (FOS) is interrogated using a broad band optical light source and an optical spectrometer. The sensitivity of the sensor achieved is 0.6cmH2O, excellent for small depth-changes. Experimental measurements with saturated salt water and chlorophyll pigmentation of different standards were tested, to simulate the sub-sea conditions where a stability of 0.7cmH2O was reached with a drift of less than 10% under the simulated conditions.
Wide-bandgap high-mobility ZnO thin-film transistors produced at room temperature

We report high-performance ZnO thin-film transistor (ZnO-TFT) fabricated by rf magnetron sputtering at room temperature with a bottom gate configuration. The ZnO-TFT operates in the enhancement mode with a threshold voltage of 19V, a saturation mobility of 27cm2∕Vs, a gate voltage swing of 1.39V∕decade and an on/off ratio of 3×105. The ZnO-TFT presents an average optical transmission (including the glass substrate) of 80% in the visible part of the spectrum. The combination of transparency, high mobility, and room-temperature processing makes the ZnO-TFT a very promising low-cost optoelectronic device for the next generation of invisible and flexible electronics.
Strain characterization of embedded aerospace smart materials using shearography

The development of smart materials for embedding in aerospace composites provides enhanced functionality for future aircraft structures. Critical flight conditions like icing of the leading edges can affect the aircraft functionality and controllability. Hence, anti-icing and de-icing capabilities are used. In case of leading edges made of fibre metal laminates heater elements can be embedded between composite layers. However this local heating causes strains and stresses in the structure due to the different thermal expansion coefficients of the different laminated materials. In order to characterize the structural behaviour during thermal loading full-field strain and shape measurement can be used. In this research, a shearography instrument with three spatially-distributed shearing cameras is used to measure surface displacement gradients which give a quantitative estimation of the in- and out-of-plane surface strain components. For the experimental part, two GLARE (Glass Laminate Aluminum Reinforced Epoxy) specimens with six different embedded copper heater elements were manufactured: two copper mesh shapes (straight and S-shape), three connection techniques (soldered, spot welded and overlapped) and one straight heater element with delaminations. The surface strain behaviour of the specimens due to thermal loading was measured and analysed. The comparison of the connection techniques of heater element parts showed that the overlapped connection has the smallest effect on the surface strain distribution. Furthermore, the possibility of defect detection and defect depth characterisation close to the heater elements was also investigated.
Monoidal Bicategories and Hopf Algebroids

Why are groupoids such special categories? The obvious answer is because all arrows have inverses. Yet this is precisely what is needed mathematically to model symmetry in nature. The relation between the groupoid and the physical object is expressed by an action. The presence of inverses means that actions of a groupoid G behave much better than actions of an arbitrary category. The totality of actions of G on vector spaces forms a category Mod G of modules. The feature of Mod G which epitomises the fact that G is a groupoid is that the internal hom in Mod G is calculated in a particularly simple way. More precisely, the functor out of Mod G which forgets the actions preserves, not only the monoidal structure but also, the closed structure. With this as a guiding principle, we develop a general concept of ``autonomous pseudomonoid'' which includes ordinary Hopf algebras (indeed, Hopf algebroids) and autonomous (=compact=rigid) monoidal categories. This is intended to elucidate the interaction between Hopf algebras and autonomous monoidal categories in Tannaka duality as appearing in [JS2; D2], for example. Given a topological monoid M, it is explained in [JS2, Section 8] why the monoidal category of finite-dimensional representations of M is equivalent to the monoidal category of finite-dimensional comodules over the bialgebra R(M ) of representative functions on M. This provides evidence that, when regarding a Hopf algebra as a quantum group, it is the finitedimensional comodules (rather than modules) which should be regarded as the representations of the group. In dealing with comodules, we are using the coalgebra structure of the Hopf algebra H. A Hopf algebroid is an additive category (that is, ``algebra with several objects''; that is, algebroid) with a comonoidal structure: modules over a Hopf algebroid make sense but comodules are not appropriate. What we need is a notion where the article no. AI971649
Silicon-Doped Nanostructured Fe80Ni20 Alloys: The Role of Si on the Microstructure, Morphology and Magnetic Properties

Fe(Ni, Si) solid solutions were elaborated by high energy mechanical alloying from elemental Fe, Ni and Si powdersfor a milling time of 72 h. From X-ray diffraction (XRD) analysis, it has been shown that the Fe(Ni, Si) samples present a single phase in the whole range of Si content and exhibit a solid solution of disordered bcc α-Fe. The lattice parameter a (Å) of the new structures and the mean crystallitessize (nm) were found to decrease with increasing Si contents. In contrast, the microstrain behaviour presents two different stages as the Si contents are increased. Scanning Electron Microscopy (SEM) images confirmed the behaviour of the mean crystallites size, where it can be seen that the addition of Si promotes the reduction of the size of powder particles. The saturation magnetization Ms was found to decrease by a factor of almost 1.4 and the coercively was found to increase by a factor of almost 2.4, when the Si content was increased from x= 0 % to x= 20 %. The Mössbauer spectroscopy confirmed the local in site crystal locations of Si and Ni as they diffuse into the matrix of the bcc α-Fe structure to form a solid solution.
Fast quantum key distribution with decoy number states

We investigate the use of photon number states to identify eavesdropping attacks on quantum key distribution (QKD) schemes. The technique is based on the fact that different photon numbers traverse a channel with different transmittivity. We then describe two QKD schemes that utilize this method, one of which overcomes the upper limit on the key generation rate imposed by the dead time of detectors when using a heralded source of photons.
Nanomaterials-Based Electrochemiluminescence Biosensors for Food Analysis: Recent Developments and Future Directions

Developing robust and sensitive food safety detection methods is important for human health. Electrochemiluminescence (ECL) is a powerful analytical technique for complete separation of input source (electricity) and output signal (light), thereby significantly reducing background ECL signal. ECL biosensors have attracted considerable attention owing to their high sensitivity and wide dynamic range in food safety detection. In this review, we introduce the principles of ECL biosensors and common ECL luminophores, as well as the latest applications of ECL biosensors in food analysis. Further, novel nanomaterial assembly strategies have been progressively incorporated into the design of ECL biosensors, and by demonstrating some representative works, we summarize the development status of ECL biosensors in detection of mycotoxins, heavy metal ions, antibiotics, pesticide residues, foodborne pathogens, and other illegal additives. Finally, the current challenges faced by ECL biosensors are outlined and the future directions for advancing ECL research are presented.
Internal Energy Relaxation Processes and Bulk Viscosities in Fluids

Internal energy relaxation processes in fluid models derived from the kinetic theory are revisited, as are related bulk viscosity coefficients. The apparition of bulk viscosity coefficients in relaxation regimes and the links with equilibrium one-temperature bulk viscosity coefficients are discussed. First, a two-temperature model with a single internal energy mode is investigated, then a two-temperature model with two internal energy modes and finally a state-to-state model for mixtures of gases. All these models lead to a unique physical interpretation of the apparition of bulk viscosity effects when relaxation characteristic times are smaller than fluid times. Monte Carlo numerical simulations of internal energy relaxation processes in model gases are then performed, and power spectrums of density fluctuations are computed. When the energy relaxation time is smaller than the fluid time, both the two temperature and the single-temperature model including bulk viscosity yield a satisfactory description. When the energy relaxation time is larger than the fluid time, however, only the two-temperature model is in agreement with Boltzmann equation. The quantum population of a He-H2 mixture is also simulated with detailed He-H2 cross sections, and the resulting bulk viscosity evaluated from the Green–Kubo formula is in agreement with the theory. The impact of bulk viscosity in fluid mechanics is also addressed, as well as various mathematical aspects of internal energy relaxation and Chapman–Enskog asymptotic expansion for a two-temperature fluid model.
Mean-field effects on muon-capture observables

Recently, many realistic shell-model calculations have been performed in order to extract the value of the ratio C P /C A in light nuclei. For a majority of the studied nuclei these calculations fail to reproduce the measured partial capture rates and angular correlation data, and yield values of C P /C A far from the region suggested by the partially conserved axial-vector-current hypothesis. We study the effect of the form of the adopted single-particle wavefunctions on the above-mentioned observables. The radial dependence of the tail of the mean-field wavefunction produces noticeable effects due to large momentum exchange in the muon-capture process, but according to our calculations this alone does not solve the discrepancies between calculations and the experiment.
Preparation and characterization studies of chitosan encapsulated ZnO nanoparticles modified with folic acid and their antibacterial activity against selected bacterial species

Abstract This article deals with the preparation of Chitosan (CS) coated Zinc Oxide (ZnO) nanoparticles modified with Folic Acid (FA) via the simple solvothermal method. The physicochemical properties were evaluated through characterization studies such as X-ray diffraction spectroscopy (XRD), Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDAX), UV-Visible spectroscopy (UV-Vis), and Thermogravimetric and differential thermal analysis (TG/DTA). The crystalline size of the nanoparticles examined was 21.45 nm and 16.57 nm. The samples were subjected to antibacterial test (Gram-positive S. aureus, B. subtilis, and Gram-negative E. coli, P. aerugenosa) by the modified Kirby- Bauer well diffusion method and minimum inhibitory concentration (MIC) by using the broth dilution method in 96-well microtiter plate. This method was used to test the susceptibility of microorganisms. At high concentrations, CS-ZnO nanoparticles were found to have the highest zone of inhibition against S. aureus (20 mm) and B. subtilis (20 mm) and the lowest against E. coli (18 mm) and P. aeruginosa (10 mm). The MIC results were determined to be in the order CS-ZnO ˂ FA-CS-ZnO. The zeta potential of nanoparticles was estimated to be −19.1 ± 6.60 mV (CS-ZnO) and −29.3 ± 5.56 mV (FA-CS-ZnO), respectively.
Development of mucosal vaccine delivery: an overview on the mucosal vaccines and their adjuvants

Currently, mucosal infectious diseases are still a very high global health burden, but there are few effective vaccines to prevent mucosal-borne diseases. The development of mucosal vaccines requires the selection of appropriate antigens, delivery system strategies, and adjuvants to increase vaccine efficacy but limited studies have been conducted. The aim of this review is to describe the mucosal immune system, as well as the potential for the development of vaccines and mucosal adjuvants, and their challenges. The study was conducted by applying inclusion criteria for the articles, and a review was conducted by two readers with the agreement. It was known that mucosal vaccination is a potential route to be applied in future preventive efforts through vaccination. However, limited studies have been conducted so far and limited mucosal vaccination has been approved. New technological approaches such as material development involving nano- and micro-patterning are important to intensively open and investigate the potential area of development to provide better vaccination methods.
MALDI Mass Spectrometry Imaging Reveals the Existence of an N-Acyl-homoserine Lactone Quorum Sensing System in Pseudomonas putida Biofilms

Quorum sensing (QS) is generally used to describe the process involving the release and recognition of signaling molecules, such as N-acyl-homoserine lactones, by bacteria to coordinate their response to population density and biofilm development. However, detailed information on the heterogeneity of QS metabolites in biofilms remains largely unknown. Here, we describe the utilization of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to follow the production of specific metabolites, including QS metabolites, during Pseudomonas putida biofilm development. To do so, a method to grow an agar-based biofilm was first established, and MALDI-MSI was used to detect and visualize the distribution of QS metabolites in biofilms at different cultivation times. This study demonstrated that N-acyl-homoserine lactones are homogeneously produced in the early stages of P. putida biofilm formation. In contrast, the spatial distribution of quinolones and pyochelin correlated with the swarming motility of P. putida in mature biofilms. These two metabolites are involved in the production of extracellular polymeric substances and iron chelators. Our study thus contributes to establishing the specific temporal regulation and spatial distribution of N-acyl-homoserine lactone-related metabolites and quinolone and pyochelin in P. putida biofilms.
Dampak Variasi Beban Dan Keterbatasan Pembangkit Terhadap Kontrol Frekuensi Sistem menggunakan Automatic Generation Control

Pusat pengatur beban menggunakan Automatic Generation Controller (AGC) sebagai regulasi frekuensi real time untuk memastikan keseimbangan antara permintaan beban dengan ketersediaan pembangkitan. Ketidakpastian variasi beban, dan adanya keterbatasan respon pembangkit (GRC) mempengaruhi respon dinamik frekuensi sistem dalam periode menit. Sistem Jawa Bali menerapkan AGC menggunakan metode integrator dengan 51,18 % partisipasi aktif pembangkit. Penelitian ini mengusulkan AGC menggunakan metode PID controller dengan mempertimbangkan variasi karakteristik beban dan keterbatasan ramp rate up/down pembangkit. Pemodelan AGC menggunakan PID controller memberikan respon pemulihan lebih cepat 2,3 detik dibandingkan metode eksisting dan mengelola kenaikan pembebanan lebih besar pada pembangki dengan biaya lebih rendah. Pembatasan ramp rate up/down pembangkit mengakibatkan perbedaan waktu dalam respon pemulihan dan berpengaruh pada fluktuasi frekuensi sistem, sedangkan variasi karakteristik beban tidak banyak mempengaruhi respon dinamik frekuensi sistem. Metode yang diusulkan disimulasikan dengan menggunakan Matlab Simulink dengan pemodelan untuk 2 pembangkit pada kontrol area tunggal dengan variasi karakteristik beban dan pembatasan pembangkit menggunakan data-data Sistem Jawa Bali
Concerning Toponogov’s theorem and logarithmic improvement of estimates of eigenfunctions

We use Toponogov's triangle comparison theorem from Riemannian geometry along with quantitative scale oriented variants of classical propagation of singularities arguments to obtain logarithmic improvements of the Kakeya-Nikodym norms introduced in \cite{SKN} for manifolds of nonpositive sectional curvature. Using these and results from our paper \cite{BS15} we are able to obtain log-improvements of $L^p(M)$ estimates for such manifolds when $2<p<\tfrac{2(n+1)}{n-1}$. These in turn imply $(\log\lambda)^{\sigma_n}$, $\sigma_n\approx n$, improved lower bounds for $L^1$-norms of eigenfunctions of the estimates of the second author and Zelditch~\cite{SZ11}, and using a result from Hezari and the second author~\cite{HS}, under this curvature assumption, we are able to improve the lower bounds for the size of nodal sets of Colding and Minicozzi~\cite{CM} by a factor of $(\log \lambda)^{\mu}$ for any $\mu<\tfrac{2(n+1)^2}{n-1}$, if $n\ge3$.
Multisource Classification of Meridiani Planum's Aeolian Landscape Using HiRISE and Opportunity Images Analysis Based on Deep Learning

The aim of the research was to analyze the possibilities of using deep learning methods for classifying multisource image data for Mars. It should be emphasized that the main goal of the research was to develop a methodology for integrating image data acquired from orbiters (MRO mission's HIRISE camera) and in situ (opportunity rover's NAVCAM camera) and to use their combined analytical potential. We used a VGG-16-based network for this article, which is well-characterized in the literature and has been successfully applied in a wide range of applications. The article proposes a methodology for the supervised classification of landforms on Mars. The proposed solution was evaluated using the Meridiani Planum area, utilizing neural network deep learning and was based on multisource image data. We found that our approach classified aeolian reliefs correctly for more than 94% of the test dataset. The classification accuracy increased to almost 96% when using panoramas developed from opportunity's images and the derivatives of the digital terrain models used during the classification process. It is possible to broaden the proposed concept of multisource classification and the customized deep learning system to the analysis of other regions of Mars and to multispectral imaging without losing the generalizability of the solution.
Hierarchy and NSI study of P2O in its Optimal Configuration

We have studied the hierarchy sensitivity of Protvino to ORCA experiment in standard three flavor oscillation and in the presence of non-standard interactions. It has a baseline of 2595 km, and it is expected to have better sensitivity to mass hierarchy and non-standard interactions compared to the DUNE experiment. Despite having higher appearance events than DUNE, we noticed that it has less sensitivity to hierarchy. The hierarchy sensitivity of Protvino to ORCA experiment becomes equivalent to DUNE for 𝛿 𝐶𝑃 = 195 0 for a background reduction factor of 0.46 and appearance channel background systematic normalization of 4%. We see that 𝜖 𝑒𝜏 ( 𝜖 𝑒𝜇 ) sensitivity of this optimized configuration is better (similar) than DUNE when both 𝜖 𝑒𝜇 and 𝜖 𝑒𝜏 are considered in the analysis. We find that the change in hierarchy sensitivity of Protvino to ORCA experiment is more significant compared to DUNE in the presence of non-standard interactions. Further, the hierarchy sensitivity in this case is higher (lower) than the standard three flavor case for 𝛿 𝐶𝑃 = 270 0 ( 90 0 ) .