Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapeutic Potential of Microalgae-Derived Bioactive Metabolites Is Influenced by Different Large-Scale Culture Strategies

Microalgae have been identified as one of the most promising sources of novel bioactive compounds for biomedical applications, the food industry, and cosmetics. In the last decade, several biotechnological developments have facilitated the identification of a growing number of compounds as well as the study of optimal microalgae culture conditions for the production of biomass enriched in specific molecules of interest. In this study, two common commercial marine microalgae (Nannochloropsis oculata and Porphyridium purpureum) were cultured in standard and nutrient-stressed conditions and the obtained biomass extracts were assessed for their potential to inhibit cancer cell proliferation and migration as well as their antioxidant activity. Results from viability in 2D and 3D cancer cell models showed an enhancement of the antitumour activity of P. purpureum in the 3D model compared to 2D, together with a greater capacity to reduce the migration capacity of cancer cells with the biomass from nutrient-stressed conditions, whereas the antioxidant activity of N. oculata decreased when exposed to nutrient-stressed conditions. To date, this is one of the few studies that proves that controlled changes in large-scale culturing conditions such as nutrient depletion have a relevant impact in the bioactivity of the biomass on cancer cells.
BAYESIAN ANGULAR POWER SPECTRUM ANALYSIS OF INTERFEROMETRIC DATA

We present a Bayesian angular power spectrum and signal map inference engine which can be adapted to interferometric observations of anisotropies in the cosmic microwave background (CMB), 21 cm emission line mapping of galactic brightness fluctuations, or 21 cm absorption line mapping of neutral hydrogen in the dark ages. The method uses Gibbs sampling to generate a sampled representation of the angular power spectrum posterior and the posterior of signal maps given a set of measured visibilities in the uv-plane. We use a mock interferometric CMB observation to demonstrate the validity of this method in the flat-sky approximation when adapted to take into account arbitrary coverage of the uv-plane, mode–mode correlations due to observations on a finite patch, and heteroschedastic visibility errors. The computational requirements scale as where np measures the ratio of the size of the detector array to the inter-detector spacing, meaning that Gibbs sampling is a promising technique for meeting the data analysis requirements of future cosmology missions.
Discrimination strategies for inequivalent classes of multipartite entangled states

How can one discriminate different inequivalent classes of multiparticle entanglement experimentally? We present an approach for the discrimination of an experimentally prepared state from the equivalence class of another state. We consider two possible measures for the discrimination strength of an observable. The first measure is based on the difference of expectation values, the second on the relative entropy of the probability distributions of the measurement outcomes. The interpretation of these measures and their usefulness for experiments with limited resources are discussed. In the case of graph states, the stabilizer formalism is employed to compute these quantities and to find sets of observables that result in the most decisive discrimination.
Genesis and evolution of dust in galaxies in the early Universe - I. Modelling dust evolution in starburst galaxies

Aims. The aim is to elucidate the astrophysical conditions required for generating large amounts of dust in massive starburst galaxies at high redshift. Methods. We have developed a numerical galactic chemical evolution model. The model is constructed such that the effect of a wide range of parameters can be investigated. It takes into account results from stellar evolution models, a differentiation between diverse types of core collapse supemovae (CCSN), and the contribution of asymptotic giant branch (AGB) stars in the mass range 3-8 M ⊙ . We consider the lifetime-dependent yield injection into the interstellar medium (ISM) by all sources, and dust destruction due to supernova (SN) shocks in the ISM. We ascertain the temporal progression of the dust mass and the dust-to-gas and dust-to-metal mass ratios, as well as other physical properties of a galaxy, and study their dependence on the mass of the galaxy, the initial mass function (IMF), dust production efficiencies, and dust destruction in the ISM. Results. The amount of dust and the physical properties of a galaxy strongly depend on the initial gas mass available. Overall, while the total amount of dust produced increases with galaxy mass, the detailed outcome depends on the SN dust production efficiency, the IMF, and the strength of dust destruction in the ISM. Dust masses are higher for IMFs biased towards higher stellar masses, even though these IMFs are more strongly affected by dust destruction in the ISM. The sensitivity to the IMF increases as the mass of the galaxy decreases. SNe are primarily responsible for a significant enrichment with dust at early epochs ( 10 8 M ⊙ . Our preferred scenario is dominated by SN dust production in combination with top-heavy IMFs and moderate dust destruction in the ISM.
The effect of surface geometry on collisions between nanoparticles

In this molecular dynamics study, we examine the local surface geometric effects of the normal impact force between two approximately spherical nanoparticles that collide in a vacuum. Three types of surface geometries, facets, sharp crystal edges, and amorphous surfaces of nanoparticles with radii R < 10 nm are considered, and the impact force is compared with its macroscopic counterpart described by a nonlinear contact force, FN proportional to D with n = 3/2 derived by Hertz (1881), where D is the overlap induced by elastic compression. We study the surface geometry-dependent impact force. For facet-facet impact, the mutual contact surface area does not expand due to the large facet surface, and this in turn leads to a non-Hertz impact force, n < 3/2. A Hertz-like contact force, n = 1.5, is recovered in the edge contact and in the amorphous surface contact, allowing expansion of the mutual contact surface area. The results suggest that collisions of amorphous nanoparticles or nanoparticles with sharp edges may maintain dynamic phenomena, such as breathers and solitary waves, originating from the nonlinear contact force.
Angular momentum transport by thermal emission in black hole accretion disks

We calculate the amount of angular momentum that thermal photons carry out of a viscous black hole accretion disc, due to the strong Doppler shift imparted to them by the high orbital velocity of the radiating disc material. While the emission of radiation can not drive accretion on its own, we find that it does result in a loss of specific angular momentum, thereby contributing to an otherwise viscosity-driven accretion flow. In particular, we show that the fraction of the angular momentum that is lost to thermal emission at a radius r in a standard, multi-color disc is � 0.4rs/r, where rs is the Schwarzschild radius of the black hole. At small radii r & rs, where the velocity of orbiting material approaches the speed of light, the loss of angular momentum may be further enhanced due to higher order contributions to the Doppler shift of the emitted photons, which we do not retain in our simple calculation. Subject headings: accretion discs – black hole physics - radiation mechanisms: thermal
ASSOCIATION OF ELECTRICITY CONSUMPTION, ECONOMIC GROWTH AND FDI IN INDIA

India is one of the largest producer and consumer of electricity in the world owing to being one of the most populous country in the world signifying the demand for electricity is only set to grow further. World has witnessed an era of economic growth aided pertinently by electricity consumption and growing demand. With FDI indorsed downright to this vital utilities sector, it becomes imperative to cognize the relationship of Electricity Consumption, Economic Growth and FDI in India. In this study we investigate the causal direction of relationship among Foreign Direct Investment, Electricity Consumption and Economic Growth in India by using time-series data for the period 1986–2021 and employing econometric models. We find two uni-directional causalities running from Electricity Consumption to Economic Growth and Economic Growth to FDI and a bi-directional causality between Electricity Consumption and FDI. The results of the study provide a novel perspective for policy makers while formulating policies related to the power sector and foreign direct investments in India. The focus of Policy makers should be on enabling electricity service providers to offer best services to commercial and non-commercial participants as it aids in Economic growth of the country. For enhanced economic growth a country like India must have good and world-class infrastructure, efficient and effective regulatory mechanism equitable for all stakeholders, an improved living standard for people of all economic strata and a stable, healthy business friendly environment coupled with policy stability through stable government.
Probing few-excitation eigenstates of interacting atoms on a lattice by observing their collective light emission in the far field

The collective emission from a one-dimensional chain of interacting two-level atoms coupled to a common electromagnetic reservoir is investigated. We derive the system's dissipative few-excitation eigenstates, and analyze their static properties, including the collective dipole moments and branching ratios between different eigenstates. Next, we study the dynamics, and characterize the light emitted or scattered by such a system via different far-field observables. Throughout the analysis, we consider spontaneous emission from an excited state as well as two different pump field setups, and contrast the two extreme cases of non-interacting and strongly interacting atoms. For the latter case, the two-excitation submanifold contains a two-body bound state, and we find that the two cases lead to different dynamics and far-field signatures. Finally we exploit these signatures to characterize the wavefunctions of the collective eigenstates. For this, we identify a direct relation between the collective branching ratio and the momentum distribution of the collective eigenstates' wavefunction. This provides a method to proof the existence of certain collective eigenstates and to access their wave function without the need to individually address and/or manipulate single atoms.
How does radiative feedback from an ultraviolet background impact reionization

An ionizing UV background (UVB) inhibits gas accretion and photo-evaporates gas from the shallow potential wells of small, dwarf galaxies. During cosmological reionization, this effect can result in negative feedback: suppressing star-formation inside HII regions, thus impeding their continued growth. It is difficult to model this process, given the enormous range of scales involved. We tackle this problem using a tiered approach: combining parameterized results from single-halo collapse simulations with large-scale models of reionization. In the resulting reionization models, the ionizing emissivity of galaxies depends on the local values of the reionization redshift and the UVB intensity. We present a physically-motivated analytic expression for the average minimum mass of star-forming galaxies, which can be readily used in modeling galaxy formation. We find that UVB feedback: (i) delays the end stages of reionization by less than 0.5 in redshift; (ii) results in a more uniform distribution of HII regions, peaked on smaller-scales (with large-scale ionization power suppressed by tens of percent); and (iii) suppresses the global photoionization rate per baryon by a factor of < 2 towards the end of reionization. However, the impact is modest, since the hydrodynamic response of the gas to the UVB occurs on a time-scale comparable to reionization. In particular, the popular approach of modeling UVB feedback with an instantaneous transition in the minimum mass of star-forming galaxies, dramatically overestimates its importance. UVB feedback does not significantly affect reionization unless: (i) molecularly-cooled galaxies contribute significantly to reionization; or (ii) internal feedback processes strongly couple with UVB feedback in the early Universe. Since both are considered unlikely, we conclude that there is no significant self-regulation of reionization by UVB feedback.
3-d quantum stabilizer codes with a power law energy barrier

We introduce a new primitive, called welding, for combining two stabilizer codes to produce a new stabilizer code. We apply welding to construct surface codes and then use the surface codes to construct solid codes, a variant of a 3-d toric code with rough and smooth boundaries. Finally, we weld solid codes together to produce a $(O(L^3),1,O(L^{4/3}))$ stabilizer code with an energy barrier of $O(L^{2/3})$, which solves an open problem of whether a power law energy barrier is possible for local stabilizer code Hamiltonians in three-dimensions. The previous highest energy barrier is $O(\log L)$. Previous no-go results are avoided by breaking translation invariance.
Utilizing an Endogenous Progesterone Receptor Reporter Gene for Drug Screening and Mechanistic Study in Endometrial Cancer

Simple Summary In this study, we generate an innovative endogenous progesterone receptor (PR) reporter gene containing endometrial cancer cell lines and use this tool to visualize PR expression in real-time. We also demonstrated two strategies of using this reporter gene: (1). Drug discovery—screening small molecule inducers for PR expression; (2). Mechanistic investigation—screening potential PR repressors using genome-wide CRISPR knockout library. Abstract Expression of progesterone receptor (PR) is a favorable prognostic marker for multiple solid tumors. However, PR expression is reduced or lost in malignant tumors. Thus, monitoring and restoring functional PR expression is important in order to sensitize tumor cells to progesterone therapy in endometrial cancer. We developed stable PR reporter gene containing endometrial cancer cell lines monitoring the endogenous PR expression by inserting mCherry and hygromycin resistant gene at the endogenous PR gene locus by CRISPR/Cas9-mediated genome editing technique. This allows efficient, real-time monitoring of PR expression in its native epigenetic landscape. Reporter gene expression faithfully reflects and amplifies PR expression following treatment with drugs known to induce PR expression. Small molecular PR inducers have been identified from the FDA-approved 1018 drug library and tested for their ability to restore PR expression. Additionally, several candidate PR repressors have been identified by screening the genome-wide CRISPR knockout (GeCKO) library. This novel endogenous PR reporter gene system facilitates the discovery of a new treatment strategy to enhance PR expression and further sensitize progestin therapy in endometrial cancer. These tools provide a systematic, unbiased approach for monitoring target gene expression, allowing for novel drug discovery and mechanistic exploration.
Highly degenerate diffusions for sampling molecular systems

This work is concerned with sampling and computation of rare events in molecular systems. In particular, we present new methods for sampling the canonical ensemble corresponding to the Boltzmann-Gibbs probability measure. We combine an equation for controlling the kinetic energy of the system with a random noise to derive a highly degenerate diffusion (i.e. a diffusion equation where diffusion happens only along one or few degrees of freedom of the system). Next the concept of hypoellipticity is used to show that the corresponding Fokker-Planck equation of the highly degenerate diffusion is well-posed, hence we prove that the solution of the highly degenerate diffusion is ergodic with respect to the Boltzmann-Gibbs measure. We find that the new method is more efficient for computation of dynamical averages such as autocorrelation functions than the commonly used Langevin dynamics, especially in systems with many degrees of freedom. Finally we study the computation of free energy using an adaptive method which is based on the adaptive biasing force technique.
Text to Speech Synthesis: A Systematic Review, Deep Learning Based Architecture and Future Research Direction

—Text to Speech (TTS) synthesis is a process of translating natural language text into speech. Pieces of recorded speech generate synthesized speech and a database is maintained for storing this synthesized speech. A speech synthesizer’s output is determined through its resemblance to the person utter and its capacity to be implied. In recent years between the two main subsections: machine learning and deep learning of Artificial Intelligence (AI), deep learning has achieved huge success in the domain of text to speech synthesis. In this literature, a taxonomy is introduced which represents some of the deep learning-based architectures and models popularly used in speech synthesis. Different datasets that are used in TTS have also been discussed. Further, for evaluating the quality of the synthesized speech some of the widely used evaluation matrices are described. Finally, the paper concludes with the challenges and future directions of the text-to-speech synthesis system.
GAS SLOSHING AND RADIO GALAXY DYNAMICS IN THE CORE OF THE 3C 449 GROUP

We present results from a 140 ks Chandra/ACIS-S observation of the hot gas around the canonical FR I radio galaxy 3C 449. An earlier, shorter 30 ks Chandra observation of the group gas showed an unusual entropy distribution and a surface brightness edge in the gas that could be a strong shock around the inner radio lobes. In our deeper data we find no evidence for a temperature increase inside of the brightness edge, but a temperature decrease across part of the edge. This suggests that the edge is a “sloshing” cold front due to a merger within the last ≲1.3–1.6 Gyr. Both the northern and southern inner jets are bent slightly to the west in projection as they enter their respective lobes, suggesting that the sloshing core is moving to the east. The straight inner jet flares at approximately the position where it crosses the contact edge, suggesting that the jet is entraining and thermalizing some of the hot gas as it crosses the edge. We also detect filaments of X-ray emission around the southern inner radio jet and lobe which we attribute to low entropy entrained gas. The lobe flaring and gas entrainment were originally predicted in simulations of Loken et al. and are confirmed in our deep observation.
Fault Diagnosis of Rolling Bearings Based on WPE by Wavelet Decomposition and ELM

The fault diagnosis classification method based on wavelet decomposition and weighted permutation entropy (WPE) by the extreme learning machine (ELM) is proposed to address the complexity and non-smoothness of rolling bearing vibration signals. The wavelet decomposition based on ‘db3’ is used to decompose the signal into four layers and extract the approximate and detailed components, respectively. Then, the WPE values of the approximate (CA) and detailed (CD) components of each layer are calculated and composed to be the feature vectors, which are finally fed into the extreme learning machine with optimal parameters for classification. The comparative study of the simulations based on WPE and permutation entropy (PE) shows that the classification method of seven kinds of signals of normal bearing signals and six types of fault states (7 mils and 14 mils) based on WPE (CA, CD) with the number of nodes in the hidden layers of ELM determined by the five-fold cross-validation has the best performances, the training accuracy can reach 100%, and the testing accuracy can reach 98.57% with 37 nodes of the hidden layer by ELM. The proposed method using WPE (CA, CD) by ELM provides guidance for the multi-classification of normal bearing signals.
Neoadjuvant Chemotherapy before Nephroureterectomy in High-Risk Upper Tract Urothelial Cancer: A Systematic Review and Meta-Analysis

Simple Summary In muscle-invasive bladder cancer, platinum-based neoadjuvant chemotherapy is a well-established concept, since it contributes to pathological downstaging and improves overall survival. Immunotherapy has become increasingly important in adjuvant and palliative treatment for metastatic urothelial carcinoma, and phase II studies have shown assuring data in neoadjuvant treatment before cystectomy. Although upper urinary tract urothelial cancer usually presents as more invasive at diagnosis than bladder cancer, there is no recommendation for neoadjuvant therapy before nephroureterectomy. This meta-analysis comprises eleven comparative trials on neoadjuvant chemotherapy in this setting and analyzes pathological downstaging as well as oncological outcomes. However, no comparative studies investigating immunotherapy in upper tract urothelial cancer were found. The pathological downstaging and complete response were significantly improved in patients who received neoadjuvant chemotherapy. The data also suggested a benefit in overall survival and progression-free survival in these patients. Prospective studies are needed to confirm these findings and assess the role of immunotherapy in this setting. Abstract Neoadjuvant chemotherapy is a well-established concept in muscle-invasive bladder cancer with known advantages in overall survival. Phase II trials show encouraging response rates for neoadjuvant immunotherapy before radical surgery in urothelial cancer. There is no recommendation for neoadjuvant therapy in upper tract urothelial carcinoma before nephroureterectomy. Our aim was to assess the available data on neoadjuvant chemotherapy and immunotherapy before nephroureterectomy in patients with high-risk upper tract urothelial carcinoma in terms of pathological downstaging and oncological outcomes. Two investigators screened PubMed/Medline for comparative trials in the English language. We identified 368 studies and included eleven investigations in a systematic review and meta-analysis for neoadjuvant chemotherapy and control groups. There were no comparative trials investigating immunotherapy in this setting. All 11 studies reported on overall pathological downstaging with a significant effect in favor of neoadjuvant chemotherapy (OR 5.17; 95%CI 3.82; 7.00). Pathological complete response and non-muscle invasive disease were significantly higher in patients receiving neoadjuvant chemotherapy (OR 12.07; 95%CI 4.16; 35.03 and OR 1.62; 95%CI 1.05; 2.49). Overall survival and progression-free survival data analysis showed a slight benefit for neoadjuvant chemotherapy. Our results show that neoadjuvant chemotherapy is effective in downstaging in upper urinary tract urothelial carcinoma. The selection of patients and chemotherapy regimens are unclear.