Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical simulation of flow behind active vortex generators with direct forcing immersed boundary method

The immersed boundary method with discrete direct forcing approach was combined with a direct numerical simulation (DNS) code to study the time-dependent response of boundary-layer flow over a flat plate to the active vortex generators (AVG) that consist of a pair of deployable circular wing lip type blades driven by a pre-defined duty cycle. The DNS code solves the three-dimensional Navier–Stokes equations for compressible flow in general curvilinear coordinates using a fully implicit LU-SGS method. A fourth-order finite difference scheme is used to compute the spatial derivatives. The underlying curvilinear mesh near the vortex generator is designed properly with a large portion of the immersed boundary intersecting with the grid nodes to reduce the number of near-boundary nodes that require interpolation. The current immersed boundary technique was tested and verified on backward-facing step flow and flow past a circular cylinder. Numerical experiments have shown that the discrete direct forcing approach is very effective. In numerical simulation of flow behind the AVG, the computational results are comparable to the experimental data.
Time-domain diffuse fluorescence tomography of CT-analogous scheme: an experimental validation

A fiber-based non-contact scheme of the time-domain diffuse fluorescence yield and lifetime tomography is described that combines the time-correlated single photon counting technique for high-sensitive, time-resolved detection and CT-analogous configuration for high throughput data collection. A pilot validation of the methodology is performed for two-dimensional scenarios using simulated and experimental data. The results demonstrated the potential of the proposed scheme in improving the image quality.
On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots

In gate-defined quantum dot systems, the conductance change of electrostatically coupled sensor dots allows the observation of the quantum dots' charge and spin states. Therefore, the sensor dot must be optimally sensitive to changes in its electrostatic environment. A series of conductance measurements varying the two sensor-dot-forming barrier gate voltages serve to tune the dot into a corresponding operating regime. In this article, we analyze the noise characteristics of the measured data and define a criterion to identify continuous regions with a sufficient signal-gradient-to-noise ratio. Hence, accurate noise estimation is required when identifying the optimal operating regime. Therefore, we evaluate several existing noise estimators, modify them for 1-D data, optimize their parameters, and analyze their quality based on simulated data. The estimator of Chen et al. turns out to be best suited for our application concerning minimally scattering results. Furthermore, using this estimator in an algorithm for flank-of-interest classification in measured data shows the relevance and applicability of our approach.
β-Lactam potentiators to re-sensitize resistant pathogens: Discovery, development, clinical use and the way forward

β-lactam antibiotics are one of the most widely used and diverse classes of antimicrobial agents for treating both Gram-negative and Gram-positive bacterial infections. The β-lactam antibiotics, which include penicillins, cephalosporins, monobactams and carbapenems, exert their antibacterial activity by inhibiting the bacterial cell wall synthesis and have a global positive impact in treating serious bacterial infections. Today, β-lactam antibiotics are the most frequently prescribed antimicrobial across the globe. However, due to the widespread use and misapplication of β-lactam antibiotics in fields such as human medicine and animal agriculture, resistance to this superlative drug class has emerged in the majority of clinically important bacterial pathogens. This heightened antibiotic resistance prompted researchers to explore novel strategies to restore the activity of β-lactam antibiotics, which led to the discovery of β-lactamase inhibitors (BLIs) and other β-lactam potentiators. Although there are several successful β-lactam-β-lactamase inhibitor combinations in use, the emergence of novel resistance mechanisms and variants of β-lactamases have put the quest of new β-lactam potentiators beyond precedence. This review summarizes the success stories of β-lactamase inhibitors in use, prospective β-lactam potentiators in various phases of clinical trials and the different strategies used to identify novel β-lactam potentiators. Furthermore, this review discusses the various challenges in taking these β-lactam potentiators from bench to bedside and expounds other mechanisms that could be investigated to reduce the global antimicrobial resistance (AMR) burden.
Some Examples Related to 4‐Genera, Unknotting Numbers and Knot Polynomials

The paper gives examples of knots with equal knot polynomials, but distinct signatures, 4‐genera, double branched cover homology groups and unknotting numbers. This generalizes some examples given by Lickorish and Millett. It is also shown that there are knots with minimal (crossing number) diagrams of different unknotting number (thus answering a question of Bleiler), and an alternative proof is given of Rudolph's result that there are knots of ⩽ 15n crossings with unit Alexander polynomial and 4‐genus or unknotting number n.
Sequential estimation techniques for quasi-newton algorithms.

Let $F$ be a mapping from real $n$-dimensional Euclidean space into itself. In terms of solving for a zero of $F$, the quasi-Newton algorithms are based on the generalized Newton iteration $x_{k+1} = x_{k} B_{k}^{-1}F(x_{k})$, where $\{B_{k}\}$ is a sequence of nonsingular matrices. In this thesis some geometrical sequential estimation techniques are applied to the calculation of a $B_{k}$ as an estimate for the Jacobian matrix $F''(x_{k})$. The resulting estimators manifest themselves as either rank-one or rank-two, symmetric updates for $B_{k}$, together with an update for a matrix which is descriptive of the error $E_{k} = B_{k} F''(x_{k})$. These updates are in fact shown to produce optimal estimates in the sense that they minimize the set size of a certain bound for the error matrix $E_{k}$. It is shown that the use of the new updates in conjunction with the generalized Newton iteration produces locally and Q-superlinearly convergent algorithms. Moreover, under the requirement that the steps taken by the algorithm satisfy a uniform linear independence condition, it is shown that the R-order of convergence associated with the symmetric update is at least as large as the positive root of $t^{n+1} t^{n} 1 = 0$. A similar but somewhat lower rate of convergence bound is proved for the rank-one update. The symmetric update is implemented in an algorithm for unconstrained optimization which employs Powell''s dog-leg step direction/length strategy as a globalization technique. Analysis is presented which, under mild conditions on the function to be minimized, shows that the algorithm is globally and Q-superlinearly convergent. The results of some numerical experiments are presented which show that the algorithm''s performance compares favorably with Powell''s very successful MINFA.
Simulation of closed-loop feedback TMR current sensor

Due to its excellent frequency characteristics, TMR current sensors have been widely used in current state monitoring of power systems. In order to improve the measurement performance of TMR current sensors, they are usually designed as closed-loop feedback structures. Shielding enclosures were also added to TMR current sensors to improve their antiinterference capability. This paper analysed the design parameters of the feedback coil and the shielding enclosures. The influence of position of feedback coils on TMR current sensor was also analysed. When the TMR current sensor is equipped with two layers of shielding, the influence of the size and relative distance of the two layers of shielding on the shielding effect of the TMR current sensor has been analysed. The simulation results show that the position of the feedback coil has little difference in the feedback effect of the TMR current sensor, and the anti-interference ability of the TMR current sensor can be significantly improved with a shielding layer. When the TMR current sensor has two shielding layers, the thickness of the shielding layer should be reduced as much as possible, and the distance between the two shielding layers should be appropriately extended.
Two-dimensional ion temperature measurement by application of tomographic reconstruction to Doppler spectroscopy

A novel 2D ion temperature measurement for toroidal plasmas has been developed by use of cost-effective discrete tomography reconstruction of 2D ion Doppler spectroscopy composed of a polychromator with an ICCD camera and optical fibres. The 2D projection of the line spectrum collected by 35 (7 × 5) optical fibres is transformed into the r–z profile of the local spectrum by means of the Abel inversion at each wavelength and finally into the 2D (r–z) profile of the ion temperature. Numerical tests of its algorithm indicate that the reconstruction error for a peaked temperature profile is smaller than 15% if the chord-integrated signals have noise smaller than 5%. This system successfully measured the peaked ion temperature profile of a torus plasma on the r–z plane under the condition of negligibly small plasma flow.
Quantum wavefunction reconstruction of electron beam in scanning electron microscopy

Modern scanning electron microscopes (SEM) have been an excellent tool to probe nature at the nanoscale. Electron beam inspection, metrology, and lithography are some of the many applications of SEMs in the semiconductor industry, material science, etc. In an SEM, the lens system is used to form a focused scanning electron probe (SEP) which scans the specimen. In this work, we report the developments in reconstruction of the wavefunction of the SEP by performing non-interferometric phase retrieval. Firstly, we have explored phase retrieval of the SEP based on defocus variation. A through-focal image series is taken by moving the specimen (Au-C) across a fixed focal plane. These images are used to reconstruct the SEP intensity distributions which serve as the input for iterative phase retrieval. We observe that the defocus variation does not provide enough information diversity causing the reconstructed phase to stagnate. Therefore, we propose an experimental setup that uses a spiral phase plate to generate an electron vortex illumination and introduce substantial information diversity between two intensity measurements. We have shown by simulation that the phase reconstructed by this technique offers a much more robust solution to the phase retrieval problem. Aberration estimation and correction, and low-dose imaging could be some of the direct applications of knowing the complete wavefunction of the SEP. Our goal is the advancement of scanning electron microscopy as a domain where we can completely characterize the beam wavefunction as it is currently possible for transmission and scanning transmission electron microscopes (TEM and STEM).
Metabolic and Transcriptomic Changes in the Mouse Brain in Response to Short-Term High-Fat Metabolic Stress

The chronic consumption of diets rich in saturated fats leads to obesity and associated metabolic disorders including diabetes and atherosclerosis. Intake of a high-fat diet (HFD) is also recognized to dysregulate neural functions such as cognition, mood, and behavior. However, the effects of short-term high-fat diets on the brain are elusive. Here, we investigated molecular changes in the mouse brain following an acute HFD for 10 days by employing RNA sequencing and metabolomics profiling. Aberrant expressions of 92 genes were detected in the brain tissues of acute HFD-exposed mice. The differentially expressed genes were enriched for various pathways and processes such as superoxide metabolism. In our global metabolomic profiling, a total of 59 metabolites were significantly altered by the acute HFD. Metabolic pathways upregulated from HFD-exposed brain tissues relative to control samples included oxidative stress, oxidized polyunsaturated fatty acids, amino acid metabolism (e.g., branched-chain amino acid catabolism, and lysine metabolism), and the gut microbiome. Acute HFD also elevated levels of N-acetylated amino acids, urea cycle metabolites, and uracil metabolites, further suggesting complex changes in nitrogen metabolism. The observed molecular events in the present study provide a valuable resource that can help us better understand how acute HFD stress impacts brain homeostasis.
Analysis of an effective magnetic field in a contact gap of a heavy loaded reed

Studies of a spatial magnetic field variation within a contact gap of the reed operated under heavy load are reported. The influence of such factors as reed and driving coil parameters as well as contact current value have been investigated. The calculations were carried out using the electronic theory of magnetism and were verified by experiment. On the basis of the results, conclusions about the admissible contact loading of the available standard dry reeds are formulated.
Loss of liver kinase B1 in human seminoma

Testicular cancer is a common malignancy of young males and is believed to be originated from defective embryonic or adult germ cells. Liver kinase B1 (LKB1) is a serine/threonine kinase and a tumor suppressor gene. LKB1 is a negative regulator of the mammalian target of rapamycin (mTOR) pathway, often inactivated in many human cancer types. In this study, we investigated the involvement of LKB1 in the pathogenesis of testicular germ cell cancer. We performed immunodetection of LKB1 protein in human seminoma samples. A 3D culture model of human seminoma was developed from TCam-2 cells, and two mTOR inhibitors were tested for their efficacy against these cancer cells. Western blot and mTOR protein arrays were used to show that these inhibitors specifically target the mTOR pathway. Examination of LKB1 showed reduced expression in germ cell neoplasia in situ lesions and seminoma compared to adjacent normal-appearing seminiferous tubules where the expression of this protein was present in the majority of germ cell types. We developed a 3D culture model of seminoma using TCam-2 cells, which also showed reduced levels of LKB1 protein. Treatment of TCam-2 cells in 3D with two well-known mTOR inhibitors resulted in reduced proliferation and survival of TCam-2 cells. Overall, our results support that downregulation or loss of LKB1 marks the early stages of the pathogenesis of seminoma, and the suppression of downstream signaling to LKB1 might be an effective therapeutic strategy against this cancer type.
Anti Self‐Dual Yang‐Mills Connections Over Complex Algebraic Surfaces and Stable Vector Bundles

On presente une correspondance entre la geometrie algebrique et la geometrie differentielle des fibres vectoriels. Soit une surface algebrique projective X qui a un plongement donne X≤CP N et soit ω une metrique de Kahler sur X dont la classe de cohomologie associee est duale a la classe de section d'hyperplan [H]. Un fibre sur X est stable, par rapport au plongement projectif, si et seulement si il admet une connexion irreductible d'Hermite-Einstein par rapport a la metrique ω. Cette connexion est alors unique
Infectious abortions in small domestic ruminants in the Iberian Peninsula: Optimization of sampling procedures for molecular diagnostics

Introduction Infectious abortions have a major impact on small domestic ruminant farms, i.e., sheep and goats, both in terms of profitability and health status. Therefore, rapid and sensitive diagnosis is essential to minimize losses. Currently, molecular techniques, such as qPCR, are routinely used for their diagnosis, which imply the need to manipulate all abortive material, with consequent biosafety risks. Here, we evaluate the frequency of the main abortifacient pathogens in small domestic ruminants in the Iberian Peninsula and also assess an alternative approach for the optimization of sampling for molecular diagnosis. Results A total of 392 clinical cases were analyzed from April 2020 to May 2021, evidencing that the main causative agents of abortion detected were Coxiella burnetii (49.0%), Chlamydia abortus (38.3%) and, to a lesser extent, Toxoplasma gondii (10.2%), Salmonella enterica (7.1%) and Campylobacter spp. (6.1%). An uneven distribution of these pathogens was observed between ruminant species, with a higher frequency (p < 0.05) of T. gondii, S. enterica and Campylobacter spp. in sheep than goat abortions, and among geographic areas, highlighting the higher frequency (p < 0.05) of T. gondii and Campylobacter spp. in the north compared to southeastern Spain. The alternative sampling method, consisting on the use of fetal tongues and placental swabs in replacement of the whole fetus and placental tissue, offered a very good agreement with the classical method for all pathogens, except for low concentrations of C. burnetii, which seems to have a doubtful role in abortion when its concentration in the abortifacient material is low. Conclusions This study reveals a high frequency of infectious etiology in abortions of small domestic ruminants in the Iberian Peninsula and validates for the first time an alternative sampling method for molecular diagnosis that will help to provide rapid and accurate results while minimizing biosafety risks.
Multidisciplinary Educational Design Framework to Facilitate Cross-Boundary Educational Design: Closing Gaps Between Disciplines

The development of multidisciplinary education requires people to communicate, learn, and design beyond the boundaries of their own domains. In this research, an education design framework is developed to facilitate and support university teachers in multidisciplinary educational design. In addition, it serves as an aid to potentially transform domain-specific action-oriented knowledge into domain-integrated action-oriented knowledge by supporting knowledge co-construction across domain boundaries. The educational design framework, grounded in seamless and hybrid learning paradigms and theory on wicked problem solving, is being developed in a design-oriented educational research. This resulted in a multidisciplinary educational design game, which aims to facilitate cross-border communication, knowledge co-construction, and educational design processes during multidisciplinary educational design and improve the quality of the resulting multidisciplinary educational design.
AN ADAPTIVE LEVEL SET METHOD FOR MOVING-BOUNDARY PROBLEMS: APPLICATION TO DROPLET SPREADING AND SOLIDIFICATION

A three-dimensional adaptive level set method has been developed for deformable free surface problems with or without solidification. In the new scheme, a three-dimensional multizone adaptive grid generation (MAGG) scheme is employed to track the moving boundaries and a level set method is used to capture the free surface deformation. The effectiveness and robustness of the algorithm are demonstrated by solving the droplet spreading and solidification problem, in which both free surface and solidification interface movements are important.
Driving-laser wavelength dependence of high-order harmonic generation in H 2 + molecules

The electron-nuclear dynamics of one-dimensional ${{\mathrm{H}}_{2}}^{+}$ molecular high harmonic generation is investigated by numerical integration of the non-Born-Oppenheimer time-dependent Schr\"odinger equation. It is found that the nuclear motion and electron ionization are more significant for the longer wavelength and the stronger intensity of the driving laser pulse. When the ground-state ${{\mathrm{H}}_{2}}^{+}$ molecule is driven by a short laser pulse (ten optical cycles in the calculations), a strong signature of nuclear motion is seen in the wavelength scaling ($800--2000$ nm) of harmonic yield, following a ${\ensuremath{\lambda}}^{\ensuremath{-}(7\ensuremath{-}8)}$ scaling law at a constant laser intensity. It is attributed to the fast ground-state depletion induced by the strong nuclear motion, when using the long wavelength. Consequently, the wavelength scaling gives an insight into the nuclear dynamics.
Supervisory Function Analysis of the DPRD on the Tourism Governance Policy of Batu City (Study on the Batu City DPRD)

This study aims to analyze and describe how the implementation of the supervisory function and strategy of the Batu City DPRD towards tourism governance in Batu City. In tourism development projects in Batu City, the DPRD has a role as an actor in making regulations or approvals before the development runs. The supervisory function of regional regulations is very important which provides an opportunity for the DPRD to be more active and creative in responding to various obstacles to the implementation of regional regulations. Supervision of regional administration is a process of activities whose purpose is to ensure that local government runs effectively and efficiently in accordance with the plans and provisions of laws and regulations. Therefore, the author here will analyze the supervisory function of tourism governance policies in Batu City to find out whether the tourism development program is running in accordance with the governance policies known by the DPRD. The research methods applied to this study are qualitative research methods for content analysis and interviews with staff of the Batu City DPRD secretariat regarding the supervisory function. The results of the study revealed that the potential for tourism governance in Batu City has several aspects. The outcomes of the study helped shape and advance the supervisory role, specifically with regards to the execution and administration of tourism in Batu City. The limitation in this study is that the data used is still limited to the type of skunder data, namely documents and journals related to tourism governance in Batu City. The next research needs to use skunder data.
Topic Classification for Political Texts with Pretrained Language Models

Abstract Supervised topic classification requires labeled data. This often becomes a bottleneck as high-quality labeled data are expensive to acquire. To overcome the data scarcity problem, scholars have recently proposed to use cross-domain topic classification to take advantage of preexisting labeled datasets. Cross-domain topic classification only requires limited annotation in the target domain to verify its cross-domain accuracy. In this letter, we propose supervised topic classification with pretrained language models as an alternative. We show that language models fine-tuned with 70% of the small annotated dataset in the target corpus could outperform models trained using large cross-domain datasets by 27% and that models fine-tuned with 10% of the annotated dataset could already outperform the cross-domain classifiers. Our models are competitive in terms of training time and inference time. Researchers interested in supervised learning with limited labeled data should find our results useful. Our code and data are publicly available.1
A note on the influence of pairwise misclassification in two-way tables

The influence of subject misclassification on log-linear analysis of two-way contingency tables is investigated. We define pairwise misclassification and focus on both deviance and Pearson statistics as goodness-of-fit criteria for testing independence between the variables. Attention is paid to the extremal values of the test statistics that can be reached on the basis of the data set. We derive theoretical properties and use them to detect potentially troubling cells in a simple computing routine. Examples illustrate our purpose.