Miracle-dz/UniFAR-FTUs huggingface dataset:
Structures of Dwarf Satellites of Milky Way-like Galaxies: Morphology, Scaling Relations, and Intrinsic Shapes

The structure of a dwarf galaxy is an important probe of the effects of stellar feedback and environment. Using an unprecedented sample of 223 low-mass satellites from the ongoing Exploration of Local Volume Satellites survey, we explore the structures of dwarf satellites in the mass range 105.5 < M ⋆ < 108.5 M ⊙. We survey satellites around 80% of the massive, M K < − 22.4 mag, hosts in the Local Volume (LV). Our sample of dwarf satellites is complete to luminosities of M V <−9 mag and surface brightness μ 0,V < 26.5 mag arcsec−2 within at least ∼200 projected kpc of the hosts. For this sample, we find a median satellite luminosity of M V = −12.4 mag, median size of r e = 560 pc, median ellipticity of ϵ = 0.30, and median Sérsic index of n = 0.72. We separate the satellites into late- and early-type (29.6% and 70.4%, respectively). The mass–size relations are very similar between them within ∼5%, which indicates that the quenching and transformation of a late-type dwarf into an early-type one involves only very mild size evolution. Considering the distribution of apparent ellipticities, we infer the intrinsic shapes of the early- and late-type samples. Combining with literature samples, we find that both types of dwarfs are described roughly as oblate spheroids that get more spherical at fainter luminosities, but early-types are always rounder at fixed luminosity. Finally, we compare the LV satellites with dwarf samples from the cores of the Virgo and Fornax clusters. We find that the cluster satellites show similar scaling relations to the LV early-type dwarfs but are roughly 10% larger at fixed mass, which we interpret as being due to tidal heating in the cluster environments. The dwarf structure results presented here are a useful reference for simulations of dwarf galaxy formation and the transformation of dwarf irregulars into spheroidals.
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction

Modern data analytics take advantage of ensemble learning and transfer learning approaches to tackle some of the most relevant issues in data analysis, such as lack of labeled data to use to train the analysis models, sparsity of the information, and unbalanced distributions of the records. Nonetheless, when applied to multimodal datasets (i.e., datasets acquired by means of multiple sensing techniques or strategies), the state-of-theart methods for ensemble learning and transfer learning might show some limitations. In fact, in multimodal data analysis, not all observations would show the same level of reliability or information quality, nor an homogeneous distribution of errors and uncertainties. This condition might undermine the classic assumptions ensemble learning and transfer learning methods rely on. In this work, we propose an adaptive approach for dimensionality reduction to overcome this issue. By means of a graph theory-based approach, the most relevant features across variable size subsets of the considered datasets are identified. This information is then used to set-up ensemble learning and transfer learning architectures. We test our approach on multimodal datasets acquired in diverse research fields (remote sensing, brain-computer interfaces, photovoltaic energy). Experimental results show the validity and the robustness of our approach, able to outperform state-of-the-art techniques.
Information-Centric Wireless Sensor Networking Scheme With Water-Depth-Awareness Content Caching for Underwater IoT

The existing Underwater Internet of Things (UIoT) is based on the IP architecture, which is not conducive to the efficient storage and distribution of huge amounts of content generated in underwater. Actively pushing all content to users causes much unnecessary resource consumption in the UIoT. The information-centric networking (ICN) architecture opens new horizons up for these challenges. However, the slowness of underwater propagation speed makes traditional ICN not suitable for UIoT, especially considering about delay time. In this article, we propose an information-centric wireless sensor networking scheme with water-depth-aware content caching (ICWSN-WDA) to solve the above challenges. First, we design a naming scheme and a hybrid communication mode suitable for ICWSN-WDA. The communication mode in underwater we design is divided into push and pull traffic, which balances energy consumption and delay time. Second, we define a push level to decide which water depth the content actively pushes to, finding a suitable junction point of two modes. Third, as the water depth is deeper, it becomes more difficult to replace the sensor battery. To save energy consumption of deep-water sensors, the water-depth-aware caching mechanism is proposed based on water depth, popularity, and senor energy. Our extensive evaluation confirms the effectiveness of our proposed scheme, and it balances energy consumption constraints and latency.
Bio-Assisted Synthesis of Food-Grade FeOOH Nanoellipsoids as Promising Iron Supplements for Food Fortification

Background and Objective: Nanostructures of FeOOH are approved substitutions for iron salts in treatment of iron deficiencies. These particles can be promising additives to develop iron fortified foods. Researchers are interested to develop cost-effective techniques for the fabrication of food-grade FeOOH nanostructures. Relatively, polyethylenimine is commonly used to fabricate FeOOH nanoellipsoids. However, food industries need to develop novel protocols, which can be used in food processing. In this study, a simple economic technique was developed for the fabrication of food-grade FeOOH nanoellipsoids. Material and Methods: Ferric chloride hexahydrate (FeCl3.6H2O) was used as iron precursor. BG-11 broth medium was used to cultivate Chlorella vulgaris microalgae. The Chlorella vulgaris culture supernatant was used for the fabrication of FeOOH nanostructures as an approved low-cost medium by the Food and Drug Administration. Nanoellipsoids of FeOOH were synthesized via hydrolysis of ferric ions in culture supernatants with no addition of other chemicals. Results and Conclusion: Results showed that the prepared nanoellipsoids were β-FeOOH with 51.4-nm average length and 9.2-nm average width. The XRD analysis demonstrated that the secretory compound from Chlorella vulgaris included no negative effects on formation of FeOOH nanocrystals. The current developed technique can be introduced as a promising approach in fabrication of food-grade nanoparticles. Furthermore, the prepared structures can be used for the supplement formulation in pharmaceutical industries. Conflict of interest: The authors declare no conflict of interest.
Comparison of different aethalometer correction schemes and a reference multi-wavelength absorption technique for ambient aerosol data

Abstract. Deriving absorption coefficients from Aethalometer attenuation data requires different corrections to compensate for artifacts related to filter-loading effects, scattering by filter fibers, and scattering by aerosol particles. In this study, two different correction schemes were applied to seven-wavelength Aethalometer data, using multi-angle absorption photometer (MAAP) data as a reference absorption measurement at 637 nm. The compensation algorithms were compared to five-wavelength offline absorption measurements obtained with a multi-wavelength absorbance analyzer (MWAA), which serves as a multiple-wavelength reference measurement. The online measurements took place in the Amazon rainforest, from the wet-to-dry transition season to the dry season (June–September 2014). The mean absorption coefficient (at 637 nm) during this period was 1.8 ± 2.1 Mm−1, with a maximum of 15.9 Mm−1. Under these conditions, the filter-loading compensation was negligible. One of the correction schemes was found to artificially increase the short-wavelength absorption coefficients. It was found that accounting for the aerosol optical properties in the scattering compensation significantly affects the absorption Angstrom exponent (aABS) retrievals. Proper Aethalometer data compensation schemes are crucial to retrieve the correct aABS, which is commonly implemented in brown carbon contribution calculations. Additionally, we found that the wavelength dependence of uncompensated Aethalometer attenuation data significantly correlates with the aABS retrieved from offline MWAA measurements.
Medication use and physical assaults in the psychiatric emergency room

Objective: To evaluate the relationship between medications used to treat acute agitation (antipsychotics, mood stabilizers and benzodiazepines) and subsequent assault incidence in the psychiatric emergency room. Methods: Medication orders and assault incident reports were obtained from electronic health records for 17,052 visits to an urban psychiatric emergency room from 2014-2019. Assault risk was modeled longitudinally using Poisson mixed-effect regression. Results: Assaults were reported during 0.5% of visits. Intramuscular medications (IMs) were administered in 23.3% of visits overall, and predominately administered within the first 4-hours of a visit. IM administration was correlated with assault (IRR=24.2 [5.33, 110.0]), often because IM medication was administered immediately subsequent to reported assaults. Interacted with time, IMs were not significantly associated with reduction in future assaults (IRR=0.700 [0.467, 1.04]). Neither benzodiazepines nor mood stabilizers were associated with subsequent changes to the risk of reported assault. By contrast, antipsychotic medications were associated with decreased assault risk across time (IRR=0.583 [0.360, 0.942]). Conclusions: IM order rates are high relative to overall assault incident risk. Of the three major categories of medications administered commonly in the psychiatric emergency setting, only antipsychotic medications were associated with measurable decreases in subsequent assault risk. Careful weighing of the risks and benefits of medications is encouraged; antipsychotic medication can have a significant side effect burden, and other medications (IMs, benzodiazepines, mood stabilizers) were not associated with subsequent reduction in assault risk in this analysis.
PEARL: Parallelized Expert-Assisted Reinforcement Learning for Scene Rearrangement Planning

Scene Rearrangement Planning (SRP) is an interior task proposed recently. The previous work defines the action space of this task with handcrafted coarse-grained actions that are inflexible to be used for transforming scene arrangement and intractable to be deployed in practice. Additionally, this new task lacks realistic indoor scene rearrangement data to feed popular data-hungry learning approaches and meet the needs of quantitative evaluation. To address these problems, we propose a fine-grained action definition for SRP and introduce a large-scale scene rearrangement dataset. We also propose a novel learning paradigm to efficiently train an agent through self-playing, without any prior knowledge. The agent trained via our paradigm achieves superior performance on the introduced dataset compared to the baseline agents. We provide a detailed analysis of the design of our approach in our experiments.
Self-adjoint Laplacians on partially and generalized hyperbolic attractors

We construct self-adjoint Laplacians and symmetric Markov semigroups on partially hyperbolic attractors and on hyperbolic attractors with singularities, endowed with Gibbs u-measures. If the measure has full support, we can also guarantee the existence of an associated symmetric Hunt diffusion process. In the special case of partially hyperbolic diffeomorphisms induced by geodesic flows on manifolds of negative sectional curvature the Laplacians we consider are self-adjoint extensions of well-known classical leafwise Laplacians.
Detection and Grading of Diabetic Retinopathy in Retinal Images Using Deep Intelligent Systems: A Comprehensive Review

Diabetic Retinopathy (DR) is an eye disease that mainly affects people with diabetes. People affected by DR start losing their vision from an early stage even though the symptoms are identified only at the later stage. Once the vision is lost, it cannot be regained but can be prevented from causing any further damage. Early diagnosis of DR is required for preventing vision loss, for which a trained ophthalmologist is required. The clinical practice is time-consuming and is not much successful in identifying DR at early stages. Hence, Computer-Aided Diagnosis (CAD) system is a suitable alternative for screening and grading of DR for a larger population. This paper addresses the different stages in CAD system and the challenges in identifying and grading of DR by analyzing various recently evolved techniques. The performance metrics used to evaluate the ComputerAided Diagnosis system for clinical practice is also discussed.
Stress-Energy in the Conical Vacuum and its Implications for Topology Change

This dissertation presents a semiclassical analysis of conical topology change in 1 + 1 spacetime dimensions wherein, to lowest order, the ambient spacetime is classical and fixed while the scalar field coupled to it is quantized. The vacuum expectation value of the scalar field stress-energy tensor is calculated via two different approaches. The first of these involves the explicit determination of the so called Sorkin-Johnston state on the cone and an original regularization scheme, while the latter employs the conformal vacuum and the more conventional point-splitting renormalization. It is found that conical topology change seems not to suffer from the same pathologies that trousers-type topology change does. This provides tentative agreement with conjectures due to Sorkin and Borde, which attempt to classify topology changing spacetimes with respect to their Morse critical points and in particular, that the cone and yarmulke in 1 + 1 dimensions lack critical points of unit Morse index.
AutoDebias: Learning to Debias for Recommendation

Recommender systems rely on user behavior data like ratings and clicks to build personalization model. However, the collected data is observational rather than experimental, causing various biases in the data which significantly affect the learned model. Most existing work for recommendation debiasing, such as the inverse propensity scoring and imputation approaches, focuses on one or two specific biases, lacking the universal capacity that can account for mixed or even unknown biases in the data. Towards this research gap, we first analyze the origin of biases from the perspective of risk discrepancy that represents the difference between the expectation empirical risk and the true risk. Remarkably, we derive a general learning framework that well summarizes most existing debiasing strategies by specifying some parameters of the general framework. This provides a valuable opportunity to develop a universal solution for debiasing, e.g., by learning the debiasing parameters from data. However, the training data lacks important signal of how the data is biased and what the unbiased data looks like. To move this idea forward, we propose AotoDebias that leverages another (small) set of uniform data to optimize the debiasing parameters by solving the bi-level optimization problem with meta-learning. Through theoretical analyses, we derive the generalization bound for AutoDebias and prove its ability to acquire the appropriate debiasing strategy. Extensive experiments on two real datasets and a simulated dataset demonstrated effectiveness of AutoDebias. The code is available at https://github.com/DongHande/AutoDebias.
BILROST: Handling Actuators of the Internet of Things through Tweets on Twitter using a Domain- Specific Language

In recent years, many investigations have appeared that combine the Internet of Things and Social Networks. Some of them addressed the interconnection of objects as Social Networks interconnect people, and others addressed the connection between objects and people. However, they usually used interfaces created for that purpose instead of using familiar interfaces for users. Why not integrate Smart Objects in traditional Social Networks? Why not control Smart Objects through natural interactions in Social Networks? The goal of this paper is to make easier to create applications that allow non-experts users to control Smart Objects actuators through Social Networks through the proposal of a novel approach to connect objects and people using Social Networks. This proposal will address how to use Twitter so that objects could perform actions based on Twitter users’ posts. Moreover, it will be presented a Domain-Specific language that could help in the task of defining the actions that objects could perform when people publish specific content on Twitter.
A comparative study of surgical management of surgical neck of humerus fracture in adults by proximal humeral nailing and PHILOS

Fractures of surgical neck of the humerus represent 25% of the proximal part of humerus. Neer described three types of fracture of the surgical neck: angled, translated/separated and comminuted. Proximal humeral nail and PHILOS plate fixation for the surgical neck of humeral fractures offers good anatomic fracture reduction and stable primary fixation to ensure rapid fracture healing and imme­diate post-operative functional therapy without prolonged immobilization. Objective: To assess and compare the functional outcome and the fracture union of surgical neck of humerus fractures using proximal humeral nail and PHILOS plate. Material and Method: Prospective Comparative study was conducted at Bapuji and Chigateri General hospital attached to JJM Medical college, Davangere for a period of two years from July2018 to July 2020.60 adult patients with surgical neck of humerus fractures who were willing for surgery were admitted during the period of study and followed up for 12 months. Result: In our study most patients were Female (60%) out of 60 patient. The mean age being 58 years in Group1 and 47.66 years in Group 2. Most of the case were road traffic accident comprising of 65% in Group 1 and self fall 63% in Group 2. In this study,70% of the patients presented with 2-part fracture, 30% with 3-part fracture in Group 1 and 50% of each fracture pattern in Group 2. In this study, according to Neer’s score of patients had excellent 9(30%), satisfactory outcome 17(56.66%), and unsatisfactory outcome 4(13.33%) in Group 1 patients and, excellent result in 6(20%) cases, 20 cases (66.66%) had satisfactory outcome and unsatisfactory outcome 4(13.33%) in Group 2. Conclusion: Surgical neck of humerus treated with PHN offers minimally invasive, cosmetically acceptable scar, stable and axial fixation with minimal soft tissue damage, early mobilization, where as in PHILOS provide rigid and stable fixation in most of communited fractures.
Formation, stability and structural characterization of ternary MgUO2(CO3)32− and Mg2UO2(CO3)3(aq) complexes

Abstract The formation of ternary Mg-UO2-CO3 complexes under weakly alkaline pH conditions was investigated by time-resolved laser fluorescence spectroscopy (TRLFS) and extended X-ray absorption fine structure (EXAFS) and compared to Ca-UO2-CO3 complexes. The presence of two different Mg-UO2-CO3 complexes was identified by means of two distinct fluorescence lifetimes of 17±2 ns and 51±2 ns derived from the multi-exponential decay of the fluorescence signal. Slope analysis in terms of fluorescence intensity coupled with fluorescence intensity factor as a function of log [Mg(II)] was conducted for the identification of the Mg-UO2-CO3 complexes forming. For the first time, the formation of both MgUO2(CO3)32− and Mg2UO2(CO3)3(aq) species was confirmed and the corresponding equilibrium constants were determined as log β0113=25.8±0.3 and log β0213=27.1±0.6, respectively. Complementarily, fundamental structural information for both Ca-UO2-CO3 and Mg-UO2-CO3 complexes was gained by extended EXAFS revealing very similar structures between these two species, except for the clearly shorter U-Mg distance (3.83 Å) compared with U-Ca distance (4.15 Å). These results confirmed the inner-sphere character of the Ca/Mg-UO2-CO3 complexes. The formation constants determined for MgUO2(CO3)32− and Mg2UO2(CO3)3(aq) species indicate that ternary Mg-UO2-CO3 complexes contribute to the relevant uranium species in carbonate saturated solutions under neutral to weakly alkaline pH conditions in the presence of Mg(II) ions, which will induce notable influences on the U(VI) chemical species under seawater conditions.
Increasing The Total Antioxidant Capacity Bound to Insoluble Dietary Fiber

Bu calisma, cozunmez bugday kepegi ile polifenoller arasindaki etkilesimin arastirilmasini amaclamistir. Tannik asitle muamele edilmesi ile cozunmez bugday kepeginin antioksidan kapasitesi sivi fazdaki cozunur antioksidan konsantrasyonuna bagli olarak attirilmistir. Test edilen icecekler arasinda yesil cay antioksidan kapasiteyi arttirma acisindan en etkili olan cozunur antioksidan kaynagidir. Sicaklik,sure, hava ve oksijenin cozunmez kepek ile polifenoller arasindaki reaksiyon uzerinde oldukca etkili oldugu gorulmustur. Optimum kosullarda (50 °C, pH 9.0, hava akisi yok) yesil cay infuzyonu ile muamele edilen cozunmez bugday kepeginin antioksidan kapasitesi 100 mmol TE.kg-1 degerinin uzerine cikmistir. Reaksiyon sonucunda bugday kepeginin serbest amino grubu onemli olcude (59.5%) azalmistir. Sonuclar polifenollerin alkali kosullarda kinonlara okside oldugunu sonrasinda bugday kepegi yuzeyindeki serbest amino gruplarina baglandigini gostermistir.
Arithmetic-Geometric Spectral Radius of Trees and Unicyclic Graphs

The arithmetic-geometric matrix $A_{ag}(G)$ of a graph $G$ is a square matrix, where the $(i,j)$-entry is equal to $\displaystyle \frac{d_{i}+d_{j}}{2\sqrt{d_{i}d_{j}}}$ if the vertices $v_{i}$ and $v_{j}$ are adjacent, and 0 otherwise. The arithmetic-geometric spectral radius of $G$, denoted by $\rho_{ag}(G)$, is the largest eigenvalue of the arithmetic-geometric matrix $A_{ag}(G)$. Let $S_{n}$ be the star of order $n\geq3$ and $S_{n}+e$ be the unicyclic graph obtained from $S_{n}$ by adding an edge. In this paper, we prove that for any tree $T$ of order $n\geq2$, $\displaystyle 2\cos\frac{\pi}{n+1}\leq\rho_{ag}(P_{n})\leq\rho_{ag}(T)\leq\rho_{ag}(S_{n})=\frac{n}{2},$ with equality if and only if $T\cong P_{n}$ for the lower bound, and if and only if $T\cong S_{n}$ for the upper bound. We also prove that for any unicyclic graph $G$ of order $n\geq3$, $\displaystyle 2=\rho_{ag}(C_{n})\leq\rho_{ag}(G)\leq\rho_{ag}(S_{n}+e),$ the lower (upper, respectively) bound is attained if and only if $T\cong C_{n}$ ($T\cong S_{n}+e$, respectively) and $\displaystyle\rho_{ag}(S_{n}+e)<\frac{n}{2}$ for $n\geq7$.