Miracle-dz/UniFAR-FTUs huggingface dataset:
LIPID PROFILE AND SOLUBLE E-SELECTIN LEVELS DIFFERENCES BETWEEN TYPE 2 DIABETES MELLITUS OVERWEIGHT-OBESE AND UNDER-NORMOWEIGHT PATIENTS PERBEDAAN PROFIL LIPID DAN KADAR SOLUBLE E-SELECTIN ANTARA PASIEN OVERWEIGHT-OBESE DAN UNDER-NORMOWEIGHT DENGAN DIABETES MELLITUS

60-80%. Profil lipid resistensi insulin inflamasi yang terjadi pasien obesitas dengan DMT2. E-Selectin adalah molekul adhesi sel endotel yang dihasilkan dari aktivasi sel endotel yang rusak, mencerminkan perubahan struktur fungsional dinding pembuluh darah. Kadar soluble E-Selectin (sE-selectin) juga dapat berperan sebagai petanda disfungsi endotel Penelitian ini bertujuan untuk membuktikan adanya perbedaan profil lipid kadar sE-selectin pada pasien DMT2 overweight-obese dan under-normoweight. Penelitian ini menggunakan pendekatan ABSTRACT Type-2 diabetes mellitus (T2DM) and obesity increase the risk of coronary artery disease by 60-80%. Lipid profile, one of the atherosclerosis markers, may be disrupted by insulin resistance and inflammation in diabetic obese patients. E-selectin is an adhesion molecule resulting from the activation of damaged endothelial cells and reflects the changes in the blood wall. Soluble E-Selectin (sE-selectin) level is also the marker of endothelial dysfunction. T his study aimed to determine differences in lipid profile and sE-selectin levels between T2DM overweight-obese and under-normoweight patients. This cross-sectional study was conducted on 63 samples since February to June 2020, at the X Community Health Center, Semarang. T2DM subjects were determined from clinicians’ diagnoses. BMI was calculated with the formula, the lipid profile was examined using the colorimetric enzymatic method, and sE-selectin was examined using the ELISA method. Data were analyzed by SPSS program version 22. There were statistically significant differences in the levels of total cholesterol, triglycerides, LDL, HDL, and sE-selectin (p respectively 0.011; 0.043; 0.000; 0.008; 0.001) in T2DM overweight-obese and under-normoweight patients. In conclusion, higher total cholesterol, LDL cholesterol, triglyceride, E-selectin and lower HDL cholesterol are found in T2DM overweight-obese patients than T2DM under-normoweight patients.
Chemical abundances of 1111 FGK stars from the HARPS GTO planet search program - Galactic stellar populations and planets

Context. We performed a uniform and detailed abundance analysis of 12 refractory elements (Na, Mg, Al, Si, Ca, Ti, Cr, Ni, Co, Sc, Mn, and V) for a sample of 1111 FGK dwarf stars from the HARPS GTO planet search program. Of these stars, 109 are known to harbor giant planetary companions and 26 stars are exclusively hosting Neptunians and super-Earths. Aims. The two main goals of this paper are to investigate whether there are any differences between the elemental abundance trends for stars of different stellar populations and to characterize the planet host and non-host samples in terms of their [X/H]. The extensive study of this sample, focused on the abundance differences between stars with and without planets will be presented in a parallel paper. Methods. The equivalent widths of spectral lines were automatically measured from HARPS spectra with the ARES code. The abundances of the chemical elements were determined using an LTE abundance analysis relative to the Sun, with the 2010 revised version of the spectral synthesis code MOOG and a grid of Kurucz ATLAS9 atmospheres. To separate the Galactic stellar populations we applied both a purely kinematical approach and a chemical method. Results. We found that the chemically separated (based on the Mg, Si, and Ti abundances) thin- and thick disks are also chemically disjunct for Al, Sc, Co, and Ca. Some bifurcation might also exist for Na, V, Ni, and Mn, but there is no clear boundary of their [X/Fe] ratios. We confirm that an overabundance in giant-planet host stars is clear for all studied elements.We also confirm that stars hosting only Neptunian-like planets may be easier to detect around stars with similar metallicities than around non-planet hosts, although for some elements (particulary α-elements) the lower limit of [X/H] is very abrupt.
Effects of Energy Drinks on Biochemical and Sperm Parameters in Albino Rats

: Background: The present study evaluates the effects of energy drinks on the reproductive and biochemical parameters of adult male rats.Methods: A total. The animals were divided into four groups and exposed to increasing therapeutic doses (DT) of an energy drink, based on allometric extrapolation, resulting in values (mL/day) per animal of 250 g: DT1 2.36 mL, DT3 7.47 mL, and DT6 14.16 mL. The control group (CTRL) consumed water only. During the treatment, the rats were assessed for signs of toxicity. After treatment, the animals were sacrificed and their organs were weighed. Sperm parameters (motility, concentration, and morphology) were evaluated. The biochemical markers alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, lactic dehydrogenase, urea, creatinine, creatine phosphokinase, and creatine kinase MB fraction were measured, in addition to total cholesterol and testosterone. In our Values represent means ± standard error of the mean. Tested parameters (units in parenthesis): aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), alkaline phosphatase (FAL), creatinine phosphokinase (CPK), and creatine kinase fraction MB (CKMB). Data were evaluated by analysis of (ANOVA) and Tukey’s test for comparison of
Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables

In the development of cell-based cancer therapies, quantitative mathematical models of cellular interactions are instrumental in understanding treatment efficacy. Efforts to validate and interpret mathematical models of cancer cell growth and death hinge first on proposing a precise mathematical model, then analyzing experimental data in the context of the chosen model. In this work, we present the first application of the sparse identification of non-linear dynamics (SINDy) algorithm to a real biological system in order discover cell-cell interaction dynamics in in vitro experimental data, using chimeric antigen receptor (CAR) T-cells and patient-derived glioblastoma cells. By combining the techniques of latent variable analysis and SINDy, we infer key aspects of the interaction dynamics of CAR T-cell populations and cancer. Importantly, we show how the model terms can be interpreted biologically in relation to different CAR T-cell functional responses, single or double CAR T-cell-cancer cell binding models, and density-dependent growth dynamics in either of the CAR T-cell or cancer cell populations. We show how this data-driven model-discovery based approach provides unique insight into CAR T-cell dynamics when compared to an established model-first approach. These results demonstrate the potential for SINDy to improve the implementation and efficacy of CAR T-cell therapy in the clinic through an improved understanding of CAR T-cell dynamics.
AGN and Megamasers

Abstract Luminous extragalactic masers are traditionally referred to as the ‘megamasers’. Those produced by water molecules are associated with accretion disks, radio jets, or outflows in the nuclear regions of active galactic nuclei (AGN). The majority of OH maser sources are instead driven by intense star formation in ultra-luminous infrared galaxies, although in a few cases the OH maser emission traces rotating (toroidal or disk) structures around the nuclear engines of AGN. Thus, detailed maser studies provide a fundamental contribution to our knowledge of the main nuclear components of AGN, constitute unique tools to measure geometric distances of host galaxies, and have a great impact on probing the, so far, paradigmatic Unified Model of AGN.
The set-theoretical program of Quine succeeded, but nobody noticed

1. Abstract. The set theory "New Foundations" or MF introduced by W.V. O. Quine in 1935 is discussed, along with related systems. It is argued that, in spite of the fact that the consistency of NF remains an open question, the relative consistency results for NFU obtained by R. B. Jensen in 1969 demonstrate that Quine* s general approach can be used successfully. The development of basic mathematical concepts in a version of NFU is outlined. The interpretation of set theories of the usual type in extensions of NFU is discussed. The problems with NF itself are discussed, and other fragments of NF known to be consistent are briefly introduced. The relative merits of Quine-style and Zermelo-style set theories are considered from a philosophical standpoint. Finally, systems of untyped combinatory logic or X-calculus related to NF and its fragments are introduced, and their relation to an abstract model of programming is outlined.
Ultra-deep Spitzer Mid-Infrared Spectroscopy of LIRGs and ULIRGs at z ~ 1-2

We present ultra-deep mid-IR spectra of 48 infrared-luminous galaxies in the GOODS-South field obtained with the InfraRed Spectrograph (IRS) on the Spitzer Space Telescope. These galaxies are selected among faint infrared sources (0.14 - 0.5 mJy at 24 um) in two redshift bins (0.76-1.05 and 1.75-2.4) to sample the major contributors to the cosmic infrared background at the most active epochs. We estimate redshifts for 92% of the sample using PAH and Si absorption features. Only few of these galaxies (5% at z~1 and 12% at z~2) have their total infrared luminosity dominated by emission from AGN. The averaged mid-IR spectra of the z~1 LIRGs and of the z~2 ULIRGs are very similar to the averaged spectrum of local starbursts and HII-like ULIRGs, respectively. We find that 6.2um PAH equivalent widths reach a plateau of ~1 um for L(24 mu) < 1E11 L(sun). At higher luminosities, EW (6.2 mu) anti-correlates with L(24 um). Intriguingly, high-z ULIRGs and SMG lie above the local EW (6.2 um) - L(24 um) relationship suggesting that, at a given luminosity, high-z ULIRGs have AGN contributions to their dust emission lower than those of local counterparts. A quantitative analysis of their morphology shows that most of the luminous IR galaxies have morphologies similar to those of IR-quiet galaxies at the same redshift. All z~2 ULIRGs of our sample are IR-excess BzK galaxies and most of them have L(FIR)/L(1600A) ratios higher than those of starburst galaxies at a given UV slope. The ``IR excess'' (Daddi et al. 2007) is mostly due to strong 7.7 um PAH emission and under-estimation of UV dust extinction. On the basis of the AGN-powered L (6 um) continuum measured directly from the mid-IR spectra, we estimate an average intrinsic X-ray AGN luminosity of L(2-10 keV) = (0.1 +/- 0.6) 1E43 erg/s, a value substantially lower than the prediction by Daddi et al. (2007).
INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY: APPLIED BUSINESS AND EDUCATION RESEARCH

This study aimed to capture the lived experiences of Mathematics teachers on modular distance learning. It explored mathematics teachers' perception of modular distance learning, describe the challenges, and struggles in the new normal, unveil the coping mechanisms of mathematics teachers on the demand of modular distance learning, and verify the effects of modular distance learning on students' mathematics performance. This phenomenological study used Colaizzi’s method of data analysis to interpret and analyze the data. Nine (9) teacher-participants were recruited using purposive sampling technique. The study used the interview method in gathering data. In this study, teacher-participants perceived that modular distance learning is one of the best ways to continue students' learning. However, students' mathematics performance using modular distance learning is far below the expected standard. Identified contributing factors were students' attitudes, teachers' workloads, digital infrastructure and gadgets, slow internet connections, lack of parents' support, and students' motivation. The findings of this study can be used as a basis or springboard for revision of implementing guidelines of modular distance learning enactment policies that would provide intervention to the existing identified problem.
Improving the Sample Eﬃciency and Safety of Reinforcement Learning via Monte Carlo Method

The actor-critic RL is widely used in various robotic control tasks. By viewing the actor-critic RL from the perspective of variational inference (VI), the policy network is trained to obtain the approximate posterior of actions given the optimality criteria. However, in practice, the actor-critic RL may yield suboptimal policy estimates due to the amortization gap and insuﬃcient exploration. In this work, inspired by the previous use of Hamiltonian Monte Carlo (HMC) in VI, we propose to integrate the policy network of actor-critic RL with HMC, which is termed as Hamiltonian Policy . As such we propose to evolve actions from the base policy according to HMC, and our proposed method has many beneﬁts. First, HMC can improve the policy distribution to better approximate the posterior and hence reduce the amortization gap. Second, HMC can also guide the exploration more to the regions of action spaces with higher Q values, enhancing the exploration eﬃciency. Further, instead of directly applying HMC into RL, we propose a new leapfrog operator to simulate the Hamiltonian dynamics. Finally, in safe RL problems, we ﬁnd that the proposed method can not only improve the achieved return, but also reduce safety constraint violations by discarding potentially unsafe actions. With comprehensive empirical experiments on continuous control baselines, including MuJoCo and PyBullet Roboschool, we show that the proposed approach is a data-eﬃcient and easy-to-implement improvement over previous actor-critic methods.
Consumptive News Feed Curation on Social Media: A Moderated Mediation Model of News Interest, Affordance Utilization, and Friending

This study analyzed a survey sample from China and investigated how (1) news interest, (2) affordance utilization, and (3) friending were associated with consumptive news feed curation (CNFC), a practice of selective exposure, as well as the ways in which these associations were mediated and moderated by psychological factors. Findings showed that all 3 factors were positively associated with CNFC. Media locus of control (MLOC), namely, individuals’ beliefs in their ability to control their information environment, was found to be a positive mediator. Namely, the three independent variables led to greater MLOC before facilitating CNFC. Need for cognition (NFC) was a moderator. That is, the main associations became weaker among those with higher NFC, suggesting that people with a stronger preference for analytical and logical information processing were less likely to curate for consumptive purposes. Moderating effect of NFC was also found on the indirect effects of news interest and affordance utilization on CNFC.
Patterning and growth are coordinated early in the cell cycle

Precise control of cell division is essential for proper patterning and growth during the development of multicellular organisms. Coordination of formative (asymmetric) divisions that generate new tissue patterns with proliferative (symmetric) divisions that promote growth is poorly understood. Here, we employed quantitative 4D light sheet and confocal microscopy to probe in vivo the dynamics of two transcription factors, SHORTROOT (SHR) and SCARECROW (SCR), which are required for asymmetric division in the stem cell niche of Arabidopsis roots [1,2]. Long-term (up to 48 hours), frequent (every 15 minutes) imaging of the two regulators in tandem in single cells, in conjunction with a SHR induction system, enabled us to challenge an existing bistable model[3] of the SHR/SCR gene regulatory network. By directly controlling SHR and SCR expression dynamics, we were able to identify key features that are essential for rescue of asymmetric division in shr mutants. We show that instead of high stable levels of nuclear SHR and SCR, only low transient levels of expression are required. Nuclear SHR kinetics do not follow predictions of the bistable model, and the regulatory relationship between SHR and SCR can be modeled by monostable alternatives. Furthermore, expression of these two regulators early in the cell cycle determines the orientation of the division plane, resulting in either formative or proliferative cell division. Our findings provide evidence for an uncharacterized mechanism by which developmental regulators directly coordinate patterning and growth.
Towards a global estimate for generalized parton distributions

In this thesis, we give an extensive review of the phenomenology of generalized parton distributions (GPDs) utilizing the perturbative framework. Starting from basic principles, we derive the differential cross sections of deeply virtual Compton scattering and deeply virtual meson production (DVMP) in the twist-2 approximation. A special focus lies on the hard scattering amplitudes of DVMP at NLO of perturbation theory. The framework for the global analysis of GPDs relies on the uses of conformal symmetry. We give a short introduction leading to the Mellin-Barnes representation of the hard scattering amplitudes. We then derive the imaginary parts of the hard scattering amplitudes of DVMP. We utilize probability theory as extended logic to estimates GPDs. Therefore, we derive the formulas for the inference from the product and the sum rule. Afterwards, we present the results for the GPDs.
Rethinking Performance Gains in Image Dehazing Networks

Image dehazing is an active topic in low-level vision, and many image dehazing networks have been proposed with the rapid development of deep learning. Although these networks' pipelines work fine, the key mechanism to improving image dehazing performance remains unclear. For this reason, we do not target to propose a dehazing network with fancy modules; rather, we make minimal modifications to popular U-Net to obtain a compact dehazing network. Specifically, we swap out the convolutional blocks in U-Net for residual blocks with the gating mechanism, fuse the feature maps of main paths and skip connections using the selective kernel, and call the resulting U-Net variant gUNet. As a result, with a significantly reduced overhead, gUNet is superior to state-of-the-art methods on multiple image dehazing datasets. Finally, we verify these key designs to the performance gain of image dehazing networks through extensive ablation studies.
Transition from multipolar to dipolar dynamos in stratified systems

Observations of surface magnetic fields of cool stars reveal a large diversity of configurations. Although there is now a consensus that these fields are generated through dynamo processes occurring within the convective zone, the physical mechanism driving such a variety of field topologies is still debated. This paper discusses the possible origins of dipole and multipole-dominated morphologies using three-dimensional numerical simulations of stratified systems where the magnetic feedback on the fluid motion is significant. Our main result is that dipolar solutions are found at Rossby numbers up to 0.4 in strongly stratified simulations, where previous works suggested that only multipolar fields should exist. We argue that these simulations are reminiscent of the outlier stars observed at Rossby numbers larger than 0.1, whose large-scale magnetic field is dominated by their axisymmetric poloidal component. As suggested in previous Boussinesq calculations, the relative importance of inertial over Lorentz forces is again controlling the dipolar to multipolar transition. Alternatively, we find that the ratio of kinetic to magnetic energies can equally well capture the transition in the field morphology. We test the ability of this new proxy to predict the magnetic morphology of a few M-dwarf stars whose internal structure matches that of our simulations and for which homogeneous magnetic field characterization is available. Finally, the magnitude of the differential rotation obtained in our simulations is compared to actual measurements reported in the literature for M-dwarfs. In our simulations, we find a clear relationship between anti-solar differential rotation and the emergence of dipolar fields.
Floquet Transmission in Weyl/Multi‐Weyl and Nodal‐Line Semimetals through a Time‐Periodic Potential Well

A quantum pumping protocol through which the quasiparticles of Weyl/multi‐Weyl and nodal‐line semimetals are subjected to a time‐periodic rectangular potential well is considered. The presence of an oscillating potential of frequency ω creates equispaced Floquet side‐bands with spacing ℏω$\hbar \omega$ . As a result, a Fano resonance is observed when the difference in the Fermi energy (i.e., the energy of the incident quasiparticle), and the energy of one of the (quasi)bound state levels of the well, coincides with the energy of an integer number of photons (each carrying energy quantum ℏω$\hbar \omega$ ). Using the Floquet theory and the scattering matrix approach in the zero‐temperature non‐adiabatic pumping limit, characteristic Fano resonance patterns are found in the transmission coefficients. The inflection points in the pumped shot noise spectra also serve as a proxy for the corresponding Fano resonances. Therefore, the pumped shot noise is also numerically evaluated. Finally, the existence of the Fano resonance points is correlated to the (quasi)bound states of the well, by explicitly calculating the bound states of the static well (which are a subset of the bound states of the driven system). Since semimetals with anisotropic dispersions are considered, all the features observed depend on the orientation of the potential well.
Do Current Multi-Task Optimization Methods in Deep Learning Even Help?

Recent research has proposed a series of specialized optimization algorithms for deep multi-task models. It is often claimed that these multi-task optimization (MTO) methods yield solutions that are superior to the ones found by simply optimizing a weighted average of the task losses. In this paper, we perform large-scale experiments on a variety of language and vision tasks to examine the empirical validity of these claims. We show that, despite the added design and computational complexity of these algorithms, MTO methods do not yield any performance improvements beyond what is achievable via traditional optimization approaches. We highlight alternative strategies that consistently yield improvements to the performance profile and point out common training pitfalls that might cause suboptimal results. Finally, we outline challenges in reliably evaluating the performance of MTO algorithms and discuss potential solutions.
T3VIP: Transformation-based $3\mathrm{D}$ Video Prediction

For autonomous skill acquisition, robots have to learn about the physical rules governing the 3D world dynamics from their own past experience to predict and reason about plausible future outcomes. To this end, we propose a transformation-based 3D video prediction (T3VIP) approach that explicitly models the 3D motion by decomposing a scene into its object parts and predicting their corresponding rigid transformations. Our model is fully unsupervised, captures the stochastic nature of the real world, and the observational cues in image and point cloud domains constitute its learning signals. To fully leverage all the 2D and 3D observational signals, we equip our model with automatic hyperparameter optimization (HPO) to interpret the best way of learning from them. To the best of our knowledge, our model is the first generative model that provides an RGB-D video prediction of the future for a static camera. Our extensive evaluation with simulated and real-world datasets demonstrates that our formulation leads to interpretable 3D models that predict future depth videos while achieving on-par performance with 2D models on RGB video prediction. Moreover, we demonstrate that our model outperforms 2D baselines on visuomotor control. Videos, code, dataset, and pre-trained models are available at http://t3vip.cs. uni-freiburg.de.