Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Prevalence of Supermassive Black Holes over Cosmic Time

We investigate the abundance of supermassive black hole (SMBH) seeds in primordial galaxy halos. We explore the assumption that dark matter halos outgrowing a critical halo mass Mc have some probability p of having spawned an SMBH seed. Current observations of local, intermediate-mass galaxies constrain these parameters: for Mc = 1011 M⊙, all halos must be seeded, but when adopting smaller Mc masses the seeding can be much less efficient. The constraints simultaneously put lower limits on the number density of black holes in the local and high-redshift universe. Reproducing z ∼ 6 quasar space densities depends on their typical halo mass, which can be constrained by counting nearby Lyman Break Galaxies and Lyman-alpha emitters. For both observables, our simulations demonstrate that single-field predictions are too diverse to make definitive statements, in agreement with mixed claims in the literature. If quasars are not limited to the most massive host halos, they may represent a tiny fraction (≈10−5) of the SMBH population. Finally, we produce a wide range of predictions for gravitational events from SMBH mergers. We define a new diagnostic diagram for the Laser Interferometer Space Antenna to measure both SMBH space density and the typical delay between halo merger and black hole merger. While previous works have explored specific scenarios, our results hold independent of the seed mechanism, seed mass, obscuration, fueling methods and duty cycle.
Anomalous suppression of the shot noise in a nanoelectromechanical system

In this paper we report a relaxation-induced suppression of the noise for a single level quantum dot coupled to an oscillator with incoherent dynamics in the sequential tunneling regime. It is shown that relaxation induces qualitative changes in the transport properties of the dot, depending on the strength of the electron-phonon coupling and on the applied voltage. In particular, critical thresholds in voltage and relaxation are found such that a suppression below 1 / 2 of the Fano factor is possible. Additionally, the current is either enhanced or suppressed by increasing relaxation, depending on bias being greater or smaller than the above threshold. These results exist for any strength of the electron-phonon coupling and are confirmed by a four states toy model.
The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity: An Empirical Investigation

Three potential consequences of trade liberalisation are often argued to take place: (1) an increase in aggregate productivity, (2) an expansion of the most productive rms and (3) an exit of the least productive rms. In recent years much research within trade has taken place on this phenomenon, mainly due to Melitz (2003). He designed a model in which intraindustry reallocation of production achieves these three results. This paper utilises a natural experiment to test this model as well as alternative models. The experiment in question is the construction of a bridge connecting Malmo in Sweden with Copenhagen in Denmark across the Oresund Strait (previously only connected through a ferry link). The paper nds evidence for an increase in aggregate productivity, an expansion of the most productive rms and an increased likelihood for the most productive rms to become exporters due to the increase in trade that took place after the bridge was opened. It fails to show evidence for an exit of the least productive rms as well as for alternative theories in the literature. Thanks to seminar participants at the International Monetary Fund and to helpful comments by Rikard Forslid, Elhanan Helpman, Doireann Fitzgerald and Nicola Fuchs Schundeln.
Unsupervised User Stance Detection on Twitter

We present a highly effective unsupervised framework for detecting the stance of prolific Twitter users with respect to controversial topics. In particular, we use dimensionality reduction to project users onto a low-dimensional space, followed by clustering, which allows us to find core users that are representative of the different stances. Our framework has three major advantages over pre-existing methods, which are based on supervised or semi-supervised classification. First, we do not require any prior labeling of users: instead, we create clusters, which are much easier to label manually afterwards, e.g., in a matter of seconds or minutes instead of hours. Second, there is no need for domain- or topic-level knowledge either to specify the relevant stances (labels) or to conduct the actual labeling. Third, our framework is robust in the face of data skewness, e.g., when some users or some stances have greater representation in the data. We experiment with different combinations of user similarity features, dataset sizes, dimensionality reduction methods, and clustering algorithms to ascertain the most effective and most computationally efficient combinations across three different datasets (in English and Turkish). We further verified our results on additional tweet sets covering six different controversial topics. Our best combination in terms of effectiveness and efficiency uses retweeted accounts as features, UMAP for dimensionality reduction, and Mean Shift for clustering, and yields a small number of high-quality user clusters, typically just 2–3, with more than 98% purity. The resulting user clusters can be used to train downstream classifiers. Moreover, our framework is robust to variations in the hyper-parameter values and also with respect to random initialization.
Autophagy and renal cell carcinoma: What do we know so far?

Renal cell carcinoma (RCC) is the most common type of kidney tumor in adults, accounting for approximately 90% of kidney malignances, occurring usually between the ages of 60 and 70. The 5-year overall survival rate for all RCC types is 49%. Since RCCs are resistant to numeorus different radio and chemotherapeutics that act via apoptosis induction, the development of new approaches to RCC treatment is still in the focus of modern urology. In particular, in recent years, autophagy in RCC has been widely studied as a mechanism of cell extinction through which tumor cells can overcome resistance to apoptosis activation therapy. Autophagy is often referred to as a double-edged sword because it can be a process that allows cells of cancer to survive and, on the other hand and under other conditions, it can be a cell dying mechanism, independent or closely related to other cell death modalities, like apoptosis and necrosis. The central role in the tempering of the process of autophagy, in general, belongs to the mTOR complex (mammalian target of rapamycin), which integrates numerous signals that affect autophagy, such as growth factors, nutrients, various stressors and the energy status of the cell. In RCC, the most important is PI3K/AKT/mTOR signaling pathway, since activation of this signaling leads to survival of tumor cells through mTOR activation and thus, autophagy inhibition. Up to now, it was found that autophagy markers such as Beclin-1 and LC3-II can be considered as prognostic markers for RCC since the high level of Beclin-1 was detected in tissues and cells of RCC (A498 and ACHN cell lines) and that tumor cell mobility is promoted by the up-regulated expression of LC3. Therefore, a progress in RCC therapy can be expected from the development and synthesis of specific compounds targeting autophagy, as well as the therapy based on their combination.
Constructing Competency Model for Yemeni Oil and Gas Operators & Technicians Based on Training, Assessment, Motivation and the Role of Skilled Pool Experts

The main objective of this study was to develop a competency model and study the relationships of intensive training, quality assessment, motivation, and skill pool expert on the core competencies of workers serving in the oil and gas industry in Yemen to maintain sustainable productivity, developm ent of the country’s economy, employees’ safety and clean environment in the O&G production. A preliminary study and questionnaire were used to assess the technical trainees' perceptions in operation, maintenance, and safety of five oil companies in Yemen. The sample was 350 trainees in this study. The data were analyzed by using SPSS software and Structural Equation Modelling (SEM). The result found that intensive training, quality assessment motivation has a significant positive effect on employees' core competence, however, the skill pool expert specifically in line supervisor and coach has a strong effect on employees' core competencies. Multiple linear regression analysis was used to test a hypothesis. This study was conducted in five oil companies and among 350 trainees only. For this reason, the results cannot be generalized to other contexts, where the other companies not interested and implemented conventional training programs, characteristics, and peer support from the work environment, were outside the scope of the study. This study will add value to the efforts of the oil exploration and production board in Yemen, by providing an increased understanding of the factors that create competent technicians based on the competency model
Nonlocality Versus Modified Realism

A large number of physicists now admit that quantum mechanics is a non-local theory. The EPR argument and the many experiments (including recent “loop-hole free” tests) showing the violation of Bell’s inequalities seem to have confirmed convincingly that quantum mechanics cannot be local. Nevertheless, this conclusion can only be drawn inside a standard realist framework assuming an ontic interpretation of the wave function and viewing the collapse of the wave function as a real change of the physical state of the system. We show that this standpoint is not mandatory and that if the collapse is not considered an actual physical change it is possible to recover locality.
Spatio-Temporal Analysis of Vegetation Dynamics as a Response to Climate Variability and Drought Patterns in the Semiarid Region, Eritrea

There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.
Factors deterring schools from mixed attainment teaching practice

Abstract Mixed-attainment teaching has strong support from research and yet English schools are far more likely to teach students in ‘ability’ groups. Although research has considered some of the specific benefits of mixed-attainment grouping, there has been little attention to the reasons schools avoid it. This article explores data from the pilot and recruitment phases of a large-scale study into grouping practices and seeks to identify reasons for the low rate of mixed attainment grouping in English secondary schools. We report on our struggle to recruit schools, and explore the different explanations provided by teachers as to why mixed attainment practice is seen as problematic. The difficulties are characterised as a vicious circle where schools are deterred by a paucity of exemplars and resources and the educational climate is characterised as fearful, risk-averse and time-poor. Suggestions are made as to strategies to support schools in taking up mixed attainment practices.
Novel Gumbel-Softmax Trick Enabled Concrete Autoencoder With Entropy Constraints for Unsupervised Hyperspectral Band Selection

As an important topic in hyperspectral image (HSI) analysis, band selection has attracted increasing attention in the last two decades for dimensionality reduction in HSI. With the great success of deep learning (DL)-based models recently, a robust unsupervised band selection (UBS) neural network is highly desired, particularly due to the lack of sufficient ground truth information to train the DL networks. Existing DL models for band selection either depend on the class label information or have unstable results via ranking the learned weights. To tackle these challenging issues, in this article, we propose a Gumbel-Softmax (GS) trick enabled concrete autoencoder-based UBS framework (CAE-UBS) for HSI, in which the learning process is featured by the introduced concrete random variables and the reconstruction loss. By searching from the generated potential band selection candidates from the concrete encoder, the optimal band subset can be selected based on an information entropy (IE) criterion. The idea of the CAE-UBS is quite straightforward, which does not rely on any complicated strategies or metrics. The robust performance on four publicly available datasets has validated the superiority of our CAE-UBS framework in the classification of the HSIs.
Job Market Signaling Through Occupational Licensing

Among men, the black-white wage gap is as large today as it was in 1950. We test whether the black-white wage gap is due to asymmetric information using newly collected data on occupational licensing laws that ban workers with criminal records. We find evidence supporting this hypothesis. The licensing premiums for black men are largest in licensed occupations that restrict felons—particularly in states with Banthe-Box laws and at small firms. In these contexts where a worker's criminal history is difficult to infer, we find that occupational licensing reduces asymmetric information and reduces the racial wage gap.
Augmented Neural ODEs

We show that Neural Ordinary Differential Equations (ODEs) learn representations that preserve the topology of the input space and prove that this implies the existence of functions Neural ODEs cannot represent. To address these limitations, we introduce Augmented Neural ODEs which, in addition to being more expressive models, are empirically more stable, generalize better and have a lower computational cost than Neural ODEs.
RURAL CREDIT MARKETS

We model the role of the informal credit sector in developing countries. The informational advantage of informal lenders is portrayed as the ability to monitor borrowers. Monitoring reduces the incentive problem and allows for contracts with lower collateral. This enables informal lenders to serve both individuals who cannot post the collateral required by the formal sector and those who are able but do not want to post collateral. The model is consistent with the conventional view of the informal sector as recipient of spillover demand from the formal sector. It also shows that the informal sector may provide partial insurance as the lower collateral requirement implies greater consumption smoothing for borrowers.
Measuring the slope of the intrinsic alignment amplitude as a function of mass using simulation and real data

Tidal gravitational forces can modify the shape of galaxies and clusters of galaxies, thus correlating their orientation with the surrounding density field. We study the dependence of this phenomenon, known as intrinsic alignment (IA), on the mass of the dark matter haloes that host these bright structures, analysing the Millennium and Millennium-XXL N-body simulations. We closely follow the observational approach, measuring the halo position-halo shape alignment and subsequently dividing out the dependence on halo bias. We derive a theoretical scaling of the IA amplitude with mass in a dark matter universe, and predict a power-law with slope s_M in the range 1/3 to 1/2, depending on mass scale. We find that the simulation data agree with each other and with the theoretical prediction, with the joint analysis yielding an estimate of s_M = 0.36+0.01-0.01, and that this result does not depend on redshift or on the details of the halo shape measurement. We repeat the analysis using observational data, obtaining a significantly higher value, s_M = 0.56+0.05-0.05. We discuss possible reasons for this discrepancy, which could be investigated with large hydrodynamical simulations.
Pedestal study across a deuterium fuelling scan for high δ ELMy H-mode plasmas on JET with the carbon wall

We present the results from a new fuelling scan database consisting of 14 high triangularity (δ ∼ 0.41), type I ELMy H-mode JET plasmas. As the fuelling level is increased from low, (ΓD ∼ 0.2 × 1022 el s−1, ne,ped/nGW = 0.7), to high dosing (ΓD ∼ 2.6 × 1022 el s−1, ne,ped/nGW = 1.0) the variation in ELM behaviour is consistent with a transition from ‘pure type I’ to ‘mixed type I/II’ ELMs (Saibene et al 2002 Plasma Phys. Control. Fusion 44 1769). However, the pulses in this new database are better diagnosed in comparison to previous studies and most notable have pedestal measurements provided by the JET high resolution Thomson scattering (HRTS) system. We continue by presenting, for the first time, the role of pedestal structure, as quantified by a least squares mtanh fit to the HRTS profiles, on the performance across the fuelling scan. A key result is that the pedestal width narrows and peak pressure gradient increases during the ELM cycle for low fuelling plasmas, whereas at high fuelling the pedestal width and peak pressure gradient saturates towards the latter half of the ELM cycle. An ideal MHD stability analysis shows that both low and high fuelling plasmas move from stable to unstable approaching the ideal ballooning limit of the finite peeling–ballooning stability boundary. Comparison to EPED predictions show on average good agreement with experimental measurements for both pedestal height and width however when presented as a function of pedestal density, experiment and model show opposing trends. The measured pre-ELM pressure pedestal height increases by ∼20% whereas EPED predicts a decrease of 25% from low to high fuelling. Similarly the measured pressure pedestal width widens by ∼55%, in poloidal flux space, whereas EPED predicts a decrease of 20% from low to high fuelling. We give two possible explanations for the disagreement. First, it may be that EPED under predicts the critical density, which marks the transition from kink-peeling to ballooning-limited plasmas. Second, the stronger broadening of the experimental pedestal width than predicted by EPED is an indication that other transport related processes contribute to defining the pedestal width such as enhanced inter-ELM transport as observed at high fuelling, for mixed type I/II ELMy pulses.
Comparative tests on different multi-electrode arrays using models in near-surface geophysics

In this paper, the response of different synthetic models to geoelectrical multi-electrode surveys is studied. The models considered are related to two main problems, which are very common in geophysical research regarding hydrogeology and engineering. The first class of models represents buried walls, similar archaeological remains or remains of buried foundations; the other class corresponds to a sea-water intrusion of a fresh water aquifer, which is generally studied in hydrogeophysics. A set of 2D simulations, starting from the synthetic models, was carried out to compare the behaviour of the different arrays when acquiring measurements of electrical resistivity tomography. For each model, the apparent resistivity data—and relative pseudo-sections—were calculated for common electrode arrays (Wenner, dipole–dipole, Wenner–Schlumberger). Furthermore, a 'non-classical' configuration (i.e. the linear grid) was also tested. The synthetic data, after adding different levels of Gaussian noise, were inverted using RES2DINV software; then the interpretative models were compared with the initial synthetic models using different parameters to estimate the quality of the matching. Finally, the comparison between the results obtained using the various arrays is presented. Furthermore, the effectiveness of the various arrays is evaluated for each problem, also taking into account some other characteristics of the arrays, including the associated practical advantages in time consumption and noise level. Results on synthetic data were also confirmed by two field tests: one at an archaeological site survey and one at a coastal aquifer study.
Effects of Propolis on Immune System

OZ: Propolis, bal arilari tarafindan toplanan bitki recinelerinden elde edilen dogal bir urundur. Arilar tutkal, genel amacli sizdirmazlik maddesi ve ari kovanlari icin taslak ekstruzyon makinesi olarak kullanilir. Propolis yuzyillardir halk tibbinda kullanilmistir. Propolis'in anti-mikrobik, antioksidatif, anti-ulser ve anti-tumor aktivitelerine sahip oldugu bilinmektedir. Bu nedenle, propolis son yillarda tip ve kozmetik urunlerinde kullanilan yararli veya potansiyel bir madde olarak dikkat cekmistir. Dahasi, artik insan sagligini koruyabilecegi veya gelistirdigi iddiasiyla gida kumlari iceceklerinde yaygin bir sekilde kullanilmaktadir. Propolisin kimyasal bilesimi oldukca karmasiktir. Propolis orneklerinde polifenoller, fenolik aldehitler, sekuiterpen kininler, kumarinler, amino asitler, steroid inorganik bilesikler gibi 300'den fazla bilesik tespit edilmistir. Icerik, toplanma yerine, zamana ve bitki kaynagina gore degisebilir. Sonuc olarak, farkli fitocografik bolgelerin farkli donemlerinden toplanan propolisin biyolojik faaliyetleri buyuk olcude degisir. Propolisin kimyasal bilesimi ve faydali ozellikleri, fitocografik alanlara, mevsimlik toplama suresine ve botanik kaynaga bagli olarak buyuk olcude degisir. Meyve ve sebzelerde bulunan polifenoller, noral hucrelerin oksidatif stres ve normal yaslanmaya ve kronik alyuvar hastaliklarina bagli noroinflamasyona karsi korunmada yasamsal rolu bulunur.