Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovery of New Microbial Collagenase Inhibitors

Simple Summary Antimicrobial resistance is spreading globally, making healthcare specialists fear “a return to the dark age of medicine”. Great efforts are being made to develop new antimicrobials or to repurpose discontinued or shelved drugs to be used against resistant “superbugs”. Resistance occurs partly because the antibiotics we use kill the bacteria. However, this also induces a high selection pressure: a resistant bacterium will multiply, while its non-resistant competitors will die. Thus, resistance will develop rapidly in the presence of that antibiotic. An alternative is simply disarming bacteria—reducing their ability to infect the host. In other words, we should develop drugs that inhibit bacterial virulence rather than bacterial viability. Bacterial virulence factors such as collagenases emerged as attractive targets for overcoming antimicrobial resistance. Microbial collagenases digest host collagen, ensuring the spread of the pathogen and its toxins into host tissues. In this study, we aimed to identify plant-derived and repurposed drugs which potently inhibit collagenase A. We achieved this by performing extensive screening. We identified capsaicin, 4′,5-dihydroxyflavone, curcumin, dihydrorobinetin, palmatine chloride, biochanin A, 2′-hydroxychalcone, and juglone as promising collagenase inhibitors. Our data indicate these molecules could be used against infections caused by multi-drug-resistant bacterial pathogens which express collagenase A. Abstract Bacterial virulence factors are mediating bacterial pathogenesis and infectivity. Collagenases are virulence factors secreted by several bacterial stains, such as Clostridium, Bacillus, Vibrio and Pseudomonas. These enzymes are among the most efficient degraders of collagen, playing a crucial role in host colonization. Thus, they are an important target for developing new anti-infective agents because of their pivotal roles in the infection process. A primary screening using a fluorescence resonance energy-transfer assay was used to experimentally evaluate the inhibitory activity of 77 compounds on collagenase A. Based on their inhibitory activity and chemical diversity, a small number of compounds was selected to determine the corresponding half maximal inhibitory con-centration (IC50). Additionally, we used molecular docking to get a better understanding of the enzyme–compound interaction. Several natural compounds (capsaicin, 4′,5-dihydroxyflavone, curcumin, dihydrorobinetin, palmatine chloride, biochanin A, 2′-hydroxychalcone, and juglone) were identified as promising candidates for further development into useful anti-infective agents against infections caused by multi-drug-resistant bacterial pathogens which include collagenase A in their enzymatic set.
Future Colorado River Basin Drought and Surplus

Historical and future drought and surplus periods in the Colorado River basin are evaluated based on eight climate scenarios. Unimpaired streamflow from 17 stations in the Colorado River are evaluated based on U.S. Geological Survey, Bureau of Reclamation, and Coupled Modeled Intercomparison Projection 5 downscaled data from 1950–2099. Representative Concentration Pathway (RCP) 4.5 and 8.5 emission scenarios are considered for four climate models (HadGEM2-ES, CNRM-CM5, CanESM2, MI-ROC5). Drought (surplus) quantities, magnitudes, severities, and water year flows are compared for the historical and future periods. Results indicate that there is a significant difference between the historical record and future projections. The results are not consistent in terms of increase of drought or surplus; however, the intensity (as measured by magnitude and duration) will likely increase for both RCP 4.5 and 8.5. The CanESM2 and CNRM-CM5 models project wetter scenarios, and HadGEM2 and MI-ROC5 models project drier scenarios. For the critical Lees Ferry station, models indicate a chance of higher drought and surplus length and magnitude on the order of two times the historical period. In addition, basin wide flow at Lees Ferry had a shift in the future mean ensemble of approximately 3–10% for the water year. Future hydrologic changes will heighten the need for appropriate management and infrastructure options available to adapt to these changes.
Characterization of Glioblastoma Cells Response to Regorafenib

Simple Summary Glioblastoma is the most aggressive primary brain tumor, characterized by a short survival and by an invariably poor outcome. The clinical management of glioblastoma patients is based on surgery followed by adjuvant radio-chemotherapy. Glioblastoma therapy remained substantially unaltered in the last two decades, due to the lack of significant therapeutic alternatives. Regorafenib, a multikinase inhibitor already used as an anticancer drug for hepatocellular carcinoma, has recently been introduced as a therapy for relapsed glioblastoma, based on the encouraging results of a randomized phase II clinical trial. However, very little is known about the mechanisms governing glioblastoma cells’ response to regorafenib. Here we present an in vitro study, performed on glioblastoma tumor cells and on patient-derived glioma stem cells, aiming at characterizing the cellular response to regorafenib. Overall, the emerging message is that regorafenib limits glioblastoma cell proliferation, but might eventually increase the tumor cells’ migration ability. Abstract Glioblastoma (GBM), the most malignant primary brain tumor in adults. Although not frequent, it has a relevant social impact because the peak incidence coincides with the age of professional maturity. A number of novel treatments have been proposed, yet clinical trials have been disappointing. Recently, a phase II clinical trial (REGOMA) demonstrated that the multikinase inhibitor regorafenib significantly increased the median overall survival (OS) of GBM patients when compared to lomustine-treated patients. On this basis, the National Comprehensive Cancer Network (NCCN) 2020 Guidelines included regorafenib as a preferred regimen in relapsed GBM treatment. Despite the use in GBM patients’ therapy, little is known about the molecular mechanisms governing regorafenib effectiveness on the GBM tumor. Here we report an in vitro characterization of GBM tumor cells’ response to regorafenib, performed both on cell lines and on patient-derived glioma stem cells (GSCs). Overall, regorafenib significantly reduced cell growth of 2D tumor cell cultures and of 3D tumor spheroids. Strikingly, this effect was accompanied by transcriptional regulation of epithelial to mesenchymal transition (EMT) genes and by an increased ability of surviving tumor cells to invade the surrounding matrix. Taken together, our data suggest that regorafenib limits cell growth, however, it might induce an invasive phenotype.
SAR imaging in the presence of spectrum notches via fast missing data IAA

A synthetic aperture radar system operating in congested frequency bands suffers from radio frequency inter ference (RFI) from narrowband sources. When RFI interference is suppressed by frequency notching, gaps are introduced into the fast time phase history. This results in a missing data spectral estimation problem, where the missing data increases sidelobe energy and degrades image quality. The adaptive spectral estimation method Iterative Adaptive Approach (IAA) has been shown to provide higher resolution and lower sidelobes than comparable methods, but at the cost of higher computationally complexity. Current fast IAA algorithms reduce the computational complexity using Toeplitz /Vandermonde structures, but are not applicable for missing data cases because these structures are lost. When the number of missing data samples is small, which often is the case in SAR with RFI, we use a low rank completion to restore the Toeplitz/ Vandermonde structures. We show that the computational complexity of the proposed algorithm is considerably lower than the state-of-the-art and demonstrate the utility on a simulated frequency notched SAR imaging problem.
Determinant Spiritual School Well-Being Factors of Happiness and Job Satisfaction for Teachers in Central Kalimantan

This study aims to analyze the value of happiness and job satisfaction of teachers in Central Kalimantan. Besides that, this study will examine the effect of work for happiness, job satisfaction, the meaning of work, and work engagement on job satisfaction and happiness. The quantitative approach used AMOS software to test the hypothesis by taking a sample of 156 teachers in Central Kalimantan. The research instrument used a measurement scale questionnaire in this study. This study's results indicated that reading and writing literacy could develop prophetic character education for elementary school students.When teachers feel satisfied and happy in their jobs, they tend to pay more attention to the quality of their work and are more committed to students and the institution and have higher retention rates, generally being more productive. The meaning of all this is that teachers have strategic value by improving the quality of work and being more committed to educational institutions.
Multiple Case High Leverage Diagnosis in Regression Quantiles

Regression Quantiles (RQs) (see Koenker and Bassett, 1978) can be found as optimal solutions to a Linear Programming (LP) problem. Also, these optimal solutions correspond to specific elemental regressions (ERs). On the other hand, single case ordinary least squares (OLS) leverage statistics can be expressed as weighted averages of ER ones. Using this three-tier relationship amongst RQs, ERs, and OLS leverage statistics some relationships between single case leverage statistics and ER ones are explored and deduced. We build upon these results and propose a multiple-case RQ weighted predictive leverage statistic, TJ. We do this using an ER view of the well-known leverage relationship, , by summing the ER weighted predictive leverage statistics over all ERs (RQs included) instead of over observations, i.e., . As an ad-hoc cut-off value of this statistic we make use of the analog of the Hoaglin and Welsch (1978) one, i.e., high leverage points have . So in the RQ weighted predictive leverage scenario, the cut-off value becomes , where K is the total number of ERs. We then apply this RQ high leverage diagnostic to well-known data sets in the literature. The cut-off value used generally seems too small. Some proposals of cut-off values based on some analytical bounds and a simulation study are therefore given and shown to be reasonable.
Recovering Model Structures from Large Low Rank and Sparse Covariance Matrix Estimation

Many popular statistical models, such as factor and random effects models, give arise a certain type of covariance structures that is a summation of low rank and sparse matrices. This paper introduces a penalized approximation framework to recover such model structures from large covariance matrix estimation. We propose an estimator based on minimizing a non-likelihood loss with separable non-smooth penalty functions. This estimator is shown to recover exactly the rank and sparsity patterns of these two components, and thus partially recovers the model structures. Convergence rates under various matrix norms are also presented. To compute this estimator, we further develop a first-order iterative algorithm to solve a convex optimization problem that contains separa- ble non-smooth functions, and the algorithm is shown to produce a solution within O(1/t^2) of the optimal, after any finite t iterations. Numerical performance is illustrated using simulated data and stock portfolio selection on S&P 100.
X-ray and optical observations of BL Lac objects: 3C 66A (B0219+428) and ON 325 (B1215+303)

We report the results of new observations of the two BL Lac objects 3C 66A and ON 325 performed with Beppo SAX and of nearly simultaneous photometric measurements in the bandpasses from I to B . 3C 66A was observed in January 1999 and in July 2001: its X-ray flux was $F(2{-}10~{\rm keV}) = 2.0^{+0.3}_{-0.5}\times 10^{-12}$ erg cm -2 s -1 in January 1999 and $F(2{-}10~{\rm keV}) = (2.6 \pm 0.6)\times 10^{-12}$ erg cm -2 s -1 in July 2001. In both observations the X-ray spectrum can be fitted by a single power law with an energy index $1.2\pm 0.1$, steeper than that measured in the optical, equal to $0.86\pm 0.05$. The Beppo SAX observation of ON 325 was performed in December 1998 when its X-ray flux was $F(2{-}10~{\rm keV}) = 8^{+3}_{-4}\times10^{-13}$ erg cm -2 s -1 . The X-ray spectrum cannot be fitted by a single power law, but it is found to be well represented by a broken power law with a break energy at around 4 keV and energy indices equal to $1.48\pm0.12$ and $-0.57\pm0.63$. Both sources are characterised by a synchrotron-dominated emission at energies lower than a few keV, with a sharp flattening toward higher energies due to the inverse Compton component. We obtained satisfactory modelling of the overall spectral energy distributions, from the optical to low energy X-rays, with log-parabolic laws.
Impact of Post Hoc Measurement Model Overspecification on Structural Parameter Integrity

In the common two-step structural equation modeling process, modifications are routinely made to the measurement portion of the model prior to assessing structural relations. The effect of such measurement model modifications on the structural parameter estimates, however, is not well known and is the subject of the current investigation. For a five-factor confirmatory factor model, Monte Carlo simulation was used to compare interfactor correlations before and after measurement model respecifications (crossloadings, intrafactor error covariances, and interfactor error covariances) under conditions varying number of indicators per factor, loading magnitude, and sample size. Although results indicate some effect on structural parameter estimates arising under conditions of overspecification in the measurement model, in general, the impact is seen to be quite negligible.
Atomic-scale characterization of perovskite superlattice using chemical lattice imaging and spatially resolved electron energy-loss spectroscopy

The layered structure of a perovskite tricolor superlattice {SrTiO3(STO)∕LaAlO3(LAO)∕La0.6Sr0. 4MnO3(LSMO)}n on an STO substrate is investigated using transmission electron microscopy (TEM) and electron energy-loss spectroscopy (EELS). Conventional TEM imaging is not effective for thickness evaluation, in which both LAO and LSMO layers show the same image contrast because of the similarity in their mean atomic numbers. We observe 001 lattice fringes, which are chemically sensitive in the case of the perovskite structure ABO3, since the 001 structure factor is proportional to the difference between A- and B-site atomic scattering factors. The thickness of each layer is evaluated with an accuracy of one unit cell. We also apply spatially resolved EELS to analyze the depth profile of Ti, Mn, and La contents.
Electronic dispersion compensation based on maximum likelihood sequence estimation for 10 Gb/s optical communication systems

A two-fold oversampling adaptive maximum likelihood sequence estimation (MLSE) receiver based on Viterbi algorithm has been implemented for 10 Gb/s fiber optical communication systems, taking into account the amplified spontaneous emission noise, uncompensated chromatic dispersion, and nonlinearity due to square-law detection. We use the Volterra theory to model the channel nonlinearity, and Recursive Least Square (RLS) algorithm to update the channel characteristics. We estimate the error probability of the adaptive MLSE receiver for return-to-zero (RZ) on-off-keying (OOK) modulation format using standard Monte-Carlo simulation. Our results show that, when propagated along standard single-mode fibre for a bit-error-ratio (BER) of 10-3, the dispersion tolerance for two-fold oversampling adaptive MLSE receiver is 1.7 times of that for optimum threshold receiver employing no electronic dispersion compensation (EDC) for RZ-OOK signal with 60 % duty cycle. We have also compared the effects of two-fold oversampling and synchronous sampling for the adaptive MLSE receiver, and our results show that the error probability of MLSE receiver can be reduced by an order of magnitude for the same system parameters when the two-fold oversampling is used.
On non-perturbative formulation of hydrodynamics using kinetic theory

We show that some hydrodynamics problems can be analyzed by extracting the rich non-equilibrium information available in kinetic theory in a non-perturbative way. Examples include (i) an exactly derived generalized hydrodynamics description of finite Knudsen phenomena and (ii) a description of statistical properties of inhomogeneous turbulent flows. In the first case, for simple flows driven by external force (channel) or moving boundaries (Couette), the exact analytical solutions demonstrate substantial deviation from the classical behavior resulting from the Navier–Stokes equation, due to the presence of strong non-equilibrium effects. In the case of turbulence, the kinetic theoretic approach advocated here represents a coarse-grained statistical description of turbulent eddies with a specified non-constant interaction time. We argue that this approach is advantageous and more general for modeling turbulent flows including strongly non-equilibrium non-homogeneous turbulence phenomena, such as rapid distortion effects and secondary turbulent structures.
PyCPD: Pure NumPy Implementation of the Coherent Point Drift Algorithm

Point cloud registration is a common problem in many areas of computer science, particularly computer vision. Point clouds come from many types of data such as LIDAR commonly used for self-driving vehicles, and other sorts of 3D scanners (e.g., structured light) are commonly used to map the surface of physical objects. Point clouds are also used to represent the surface of an anatomical structure extracted from a medical image. Point cloud registration finds a transformation from one point cloud to another. Point cloud registration has use cases in many fields from self-driving vehicles to medical imaging and virtual reality. Typically, point cloud registration is classified into rigid (only rotations or translations), affine (rigid + shearing and scaling) and non-rigid also called deformable registration (non-linear deformation).
Host range and structural analysis of bat‐origin RshSTT182/200 coronavirus binding to human ACE2 and its animal orthologs

Bat‐origin RshSTT182 and RshSTT200 coronaviruses (CoV) from Rhinolophus shameli in Southeast Asia (Cambodia) share 92.6% whole‐genome identity with SARS‐CoV‐2 and show identical receptor‐binding domains (RBDs). In this study, we determined the structure of the RshSTT182/200 receptor binding domain (RBD) in complex with human angiotensin‐converting enzyme 2 (hACE2) and identified the key residues that influence receptor binding. The binding of the RshSTT182/200 RBD to ACE2 orthologs from 39 animal species, including 18 bat species, was used to evaluate its host range. The RshSTT182/200 RBD broadly recognized 21 of 39 ACE2 orthologs, although its binding affinities for the orthologs were weaker than those of the RBD of SARS‐CoV‐2. Furthermore, RshSTT182 pseudovirus could utilize human, fox, and Rhinolophus affinis ACE2 receptors for cell entry. Moreover, we found that SARS‐CoV‐2 induces cross‐neutralizing antibodies against RshSTT182 pseudovirus. Taken together, these findings indicate that RshSTT182/200 can potentially infect susceptible animals, but requires further evolution to obtain strong interspecies transmission abilities like SARS‐CoV‐2.
A field compensated interference spectrometer for spectroscopy of the night airglow in the visible region

A Michelson Fourier-transform spectrometer has been constructed for the visible and near infrared regions. An etendue of 0.1 cm2 sr has been achieved by field-compensating glass prisms. This is about 1000 times greater than that available with the best grating spectrometers in the same conditions. The instrument has been used to obtain several spectra of the Night Airglow from 4300 Å to 6000 Å at resolving powers of up to 104.
A Sturdy Reduced-Bias Extreme Quantile (VaR) Estimator

Please see the supplementary material for an important correction. The main objective of statistics of extremes lies in the estimation of quantities related to extreme events. In many areas of application, such as statistical quality control, insurance, and finance, a typical requirement is to estimate a high quantile, that is, the value at risk at a level p (VaRp), high enough so that the chance of an exceedance of that value is equal to p, small. In this article we deal with the semiparametric estimation of VaRp for heavy tails. The classical semiparametric estimators of parameters characterizing the tail behavior of the underlying model F usually exhibit a high bias for low thresholds, that is, for large values of k, the number of top order statistics used for the estimation. We shall here deal with bias reduction techniques for heavy tails, trying to improve the performance of the classical high quantile estimators through the use of an adequate bias-corrected tail index estimator. The new high quantile estimators have a mean squared error smaller than that of the classical estimators, even for small values of k. They are, thus, alternatives to the classical estimators not only around optimal levels but also for other levels. The asymptotic distributional properties of the proposed classes of estimators are derived. The estimators are compared with alternative ones, not only asymptotically but also for finite samples, through Monte Carlo techniques. An application to the analysis of different datasets in the field of finance is also provided.
Fertility of hybrids of dromedary and Bactrian camels: A possible role of conserved architecture of zinc finger domain of recombination regulator PRDM9

Recombination regulator, PRDM9, has been regarded as the most rapidly evolving gene in the genomes of many metazoans, in addition to being acknowledged as the sole speciation gene in vertebrates. It has become the focus of many scientific investigations because of exceptional numerical and sequence variability in its zinc finger (ZF) domain within and across species that contributes to reproductive isolation between species. This study is the maiden attempt to explore the architecture of PRDM9 ZF domain in two Camelid species (Camelus dromedarius and Camelus bactrianus). Sequence analysis revealed highly conserved domain architecture with presence of 3 and 4 ZFs in dromedary and Bactrian camels, respectively. Typical evolutionary features of PRDM9 ZF domain i.e. concerted evolution and positive selection were invariably absent in both the one-humped dromedary and the two-humped Bactrian camels. Fertility of hybrids of dromedary and Bactrian camels, despite being taxonomically distinct species can be attributed to the lack of sequence variability in PRDM9 in these species. Phylogenetic analysis underpinned clear demarcation of camels from other livestock species. The results of the present study defy what has been learnt so far about PRDM9 and add to the enigma surrounding the most intriguing gene in the genome.