Miracle-dz/UniFAR-FTUs huggingface dataset:
Chandra Observations of the Three Most Metal Deficient Blue Compact Dwarf Galaxies Known in the Local Universe, SBS 0335–052, SBS 0335–052W, and I Zw 18

We present an X-ray study of the three most metal deficient blue compact dwarf (BCD) galaxies known in the local universe, based on deep Chandra observations of SBS 0335-052 (0.025 Z☉), SBS 0335-052W (0.02 Z☉), and I Zw 18 (0.02 Z☉). All three are detected, with more than 90% of their X-ray emission arising from pointlike sources. The 0.5-10.0 keV luminosities of these point sources are in the range (1.3-8.5) × 1039 ergs s-1. We interpret them to be single or a collection of high-mass X-ray binaries, the luminosities of which may have been enhanced by the low metallicity of the gas. There are hints of faint extended diffuse X-ray emission in both SBS 0335-052 and I Zw 18, probably associated with the superbubbles visible in both BCDs. The spectrum of I Zw 18 shows an O VIII hydrogen-like emission line. The best spectral fit gives an O overabundance of the gas in the X-ray point source by a factor of ~7 with respect to the Sun, or a factor of ~350 with respect to the O abundance determined for the H II region.
DrML: Diagnosing and Rectifying Vision Models using Language

Recent multi-modal contrastive learning models have demonstrated the ability to learn an embedding space suitable for building strong vision classifiers, by leveraging the rich information in large-scale image-caption datasets. Our work highlights a distinct advantage of this multi-modal embedding space: the ability to diagnose vision classifiers through natural language. The traditional process of diagnosing model behaviors in deployment settings involves labor-intensive data acquisition and annotation. Our proposed method, DrML , can discover high-error data slices, identify influential attributes and further rectify undesirable model behaviors, without requiring any visual data. Through a combination of theoretical explanation and empirical verification, we present conditions under which classifiers trained on embeddings from one modality can be equivalently applied to embeddings from another modality. On a range of image datasets with known error slices, we demonstrate that our method can effectively identify the error slices and influential attributes, and can further use language to rectify failure modes of the classifier.
Behavior of Vortex Systems

Progressive application of the Kutta-Joukowsky theorem to the relationship between airfoil lift and circulation affords a number of formulas concerning the conduct of vortex systems. The application of this line of reasoning to several problems of airfoil theory yields an insight into many hitherto little observed relations. This report is confined to plane flow, hence all vortex filaments are straight and mutually parallel (perpendicular to the plane of flow).
Multi-task training of Transformer language models for processing radiology reports

Pre-trained language models based on the Transformer architecture have achieved impressive results in biomedical natural language processing tasks. One speciﬁc area that has raised interest in recent years is radiography, where textual reports are usually generated to describe ﬁndings and impressions from radiography exams. There are several practical applications related to the processing of these documents, such as automated classiﬁcation, summarization or extraction of key ﬁndings. This work proposes a multi-task language model based on the Text-to-Text Transfer Transformer, commonly known as T5, that was trained on diﬀerent text generation, classiﬁcation, and inference tasks involving text from radiology reports. We discuss the data pre-processing and the model training strategy together with its evaluation. The proposed multi-task model achieved very good results, close to state-of-the-art results from models that were individually trained for the summarization, natural language inference, semantic text similarity, and paraphrase identiﬁcation tasks. The results conﬁrm the potential of multi-task and transfer learning for biomedical natural language processing.
Validation of boreal summer tropical–extratropical causal links in seasonal forecasts

Abstract. Much of the forecast skill in the mid-latitudes on seasonal timescales originates from deep convection in the tropical belt. For boreal summer, such tropical–extratropical teleconnections are less well understood compared to winter. Here we validate the representation of boreal summer tropical–extratropical teleconnections in a general circulation model in comparison with observational data. To characterise variability between tropical convective activity and mid-latitude circulation, we identify the South Asian monsoon (SAM)–circumglobal teleconnection (CGT) pattern and the western North Pacific summer monsoon (WNPSM)–North Pacific high (NPH) pairs as the leading modes of tropical–extratropical coupled variability in both reanalysis (ERA5) and seasonal forecast (SEAS5) data. We calculate causal maps based on the Peter and Clark momentary conditional independence (PCMCI) causal discovery algorithm, which identifies causal links in a 2D field, to show the causal effect of each of these patterns on circulation and convection in the Northern Hemisphere. The spatial patterns and signs of the causal links in SEAS5 closely resemble those seen in ERA5, independent of the initialisation date of SEAS5. By performing a subsampling experiment (over time), we analyse the strengths of causal links in SEAS5 and show that they are qualitatively weaker than those in ERA5. We identify those regions for which SEAS5 data well reproduce ERA5 values, e.g. the southeastern USA, and highlight those where the bias is more prominent, e.g. North Africa and in general tropical regions. We demonstrate that different El Niño–Southern Oscillation phases have only a marginal effect on the strength of these links. Finally, we discuss the potential role of model mean-state biases in explaining differences between SEAS5 and ERA5 causal links.
IMPON: Efficient IMPortance sampling with ONline regression for rapid neural network training

Modern-day deep learning models are trained efficiently at scale thanks to the widespread use of stochastic optimizers such as SGD and ADAM. These optimizers update the model weights iteratively based on a batch of uniformly sampled training data at each iteration. However, it has been previously observed that the training performance and overall generalization ability of the model can be significantly improved by selectively sampling training data based on an importance criteria, known as importance sampling . Previous approaches to importance sampling use metrics such as loss, gradient norm etc. to calculate the importance scores. These methods either attempt to directly compute these metric, resulting in increased training time, or aim to approximate these metrics using an analytical proxy, which typically have inferior training performance. In this work, we propose a new sampling strategy called IMPON , which computes importance scores based on an auxiliary linear model that regresses the loss of the original deep model, given the current training context, with minimal additional computational cost. Experimental results show that IMPON is able to achieve a significantly high test accuracy, much faster than prior approaches.
Differential Evolution: A Practical Approach to Global Optimization

Problems demanding globally optimal solutions are ubiquitous, yet many are intractable when they involve constrained functions having many local optima and interacting, mixed-type variables.The differential evolution (DE) algorithm is a practical approach to global numerical optimization which is easy to understand, simple to implement, reliable, and fast. Packed with illustrations, computer code, new insights, and practical advice, this volume explores DE in both principle and practice. It is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimization.
International Journal of Electrical and Computer Engineering (IJECE)

Received Apr 12, 2022 Revised Aug 1, 2022 Accepted Aug 19, 2022 Solar energy is available abundantly, the utilization of solar energy is developing rapidly and the photovoltaic based direct current (DC) microgrid system design is under demand but the stability of the DC voltage is of most important issue, as the variation of the output DC voltage is a common problem when the load or source voltage varies, hence a regulated DC output voltage converter is proposed. This paper presents source-loadvariable (SLV) voltage regulated cascaded DC/DC converter which is used to obtain regulated output voltage of 203.1 V DC at 0.4 duty ratio with ±2% voltage fluctuations for the variation in the input source voltage and ±1.5% voltage fluctuations for the variation in load resistance of the nominal value with lower output voltage ripple and without use of sub circuits. A simulation model of SLV voltage regulated cascaded DC/DC converter in LTspice XVII software environment for the assessment of converter performance at different input source voltages and load resistances are verified.
Breaking degeneracy in jet dynamics: multi-epoch joint modelling of the BL Lac PKS 2155–304

Supermassive black holes can launch powerful jets which can be some of the most luminous multiwavelength sources; decades after their discovery their physics and energetics are still poorly understood. The past decade has seen a dramatic improvement in the quality of available data, but despite this improvement the semi-analytical modelling of jets has advanced slowly: simple one-zone models are still the most commonly employed method of interpreting data, in particular for active galactic nucleus (AGN) jets. These models can roughly constrain the properties of jets but they cannot unambiguously couple their emission to the launching regions and internal dynamics, which can be probed with simulations. However, simulations are not easily comparable to observations because they cannot yet self-consistently predict spectra. We present an advanced semi-analytical model which accounts for the dynamics of the whole jet, starting from a simplified parametrization of relativistic magnetohydrodynamics in which the magnetic flux is converted into bulk kinetic energy. To benchmark the model, we fit six quasi-simultaneous, multiwavelength spectral energy distributions of the BL Lac PKS 2155-304 obtained by the TANAMI (Tracking Active Galactic Nuclei with Austral Milliarc-second Interferometry) program, and we address the degeneracies inherent to such a complex model by employing a state-of-the-art exploration of parameter space, which so far has been mostly neglected in the study of AGN jets. We find that this new approach is much more effective than a single-epoch fit in providing meaningful constraints on model parameters.
The Macroeconomic Implications of Us Market Power in Safe Assets

The US government is the dominant supplier of global safe assets and faces a downward sloping demand for its debt. In this paper, we ask if the US exercises its market power when issuing debt and study its macroeconomic consequences. We develop a model of the global economy in which US public debt generates a non-pecuniary value for its holders and analyze the equilibrium in which the US government is the monopoly provider of this safe asset and contrast this with the case in which it acts a price taker. We use variation in estimated demand elasticities for US debt during highand low-volatility regimes to empirically distinguish between these two models and find that the data rejects price-taking behavior in favor of the monopoly one. We then quantify the distortions due to market power and find that it generates a significant under-provision of safe assets, a sizable markup in the convenience yield, and large welfare benefits for the US in detriment of the rest of the world. We also study the implications of increasing competition in safe assets from other sovereigns and private institutions. ∗We thankMarcoDuarte, Zhengyang Jiang, RohanKekre, ArvindKrishnamurthy, RicardoLagos,Matteo Maggiori, Lorenzo Magnolfi, Dmitry Mukhin, Simon Gilchrist, Venky Venkateswaran as well as numerous seminar and conference participants for helpful comments and suggestions. We also thank Duong Dang for superb research assistance.
The prevalence and developmental course of auditory processing differences in autistic children

Auditory processing differences, including hyper‐ or hyposensitivity to sound, aversions to sound, and difficulty listening under noisy, real‐world conditions, are commonly reported in autistic individuals. However, the developmental course and functional impact of these auditory processing differences are unclear. In this study, we investigate the prevalence, developmental trajectory, and functional impact of auditory processing differences in autistic children throughout childhood using a longitudinal study design. Auditory processing differences were measured using the Short Sensory Profile, a caregiver questionnaire, in addition to adaptive behaviors and disruptive/concerning behaviors at 3, 6, and 9 years of age. Our results showed that auditory processing differences were reported in greater than 70% of the autistic children in our sample at all three timepoints, maintained a high prevalence through 9 years of age, and were associated with increased disruptive/concerning behaviors and difficulty with adaptive behaviors. Furthermore, in our sample of children, auditory processing differences at age 3 years predicted disruptive/concerning behaviors and difficulty with adaptive behaviors at age 9 years. These findings warrant further investigations of the potential benefit of incorporating measures of auditory processing during routine clinical evaluations as well as interventions targeting auditory processing differences in autistic children.
Host galaxies and large-scale structures of active galactic nuclei

Abstract Our understanding of the cosmic evolution of supermassive black holes (SMBHs) has been revolutionized by the advent of large multiwavelength extragalactic surveys, which have enabled detailed statistical studies of the host galaxies and large-scale structures of active galactic nuclei (AGN). We give an overview of some recent results on SMBH evolution, including the connection between AGN activity and star formation in galaxies, the role of galaxy mergers in fueling AGN activity, the nature of luminous obscured AGN, and the connection between AGN and their host dark matter halos. We conclude by looking to the future of large-scale extragalactic X-ray and spectroscopic surveys.
Stationary and oscillatory flow through coarse porous media

Measurements in a U-tube tunnel were carried out to study flow through coarse granular material. Tests with stationary flow and tests with oscillatory flow were done to study the differences between both. The coefficients from the extended Forchheimer equation, which is supposed to describe non-stationary porous flow, were determined. It appeared that for oscillatory flow the turbulent resistance is larger than under stationary flow conditions. This additional resistance is depending on the flow-field, expressed by the Keulegan-Carpenter number. The contribution of the inertial resistance is depending on the flow field as well. Its contribution to the total resistance was rather limited. The influence of the non-stationary flow conditions have been implemented in the expressions for the turbulent resistance and the inertial resistance. Comparisons of the results from the stationary flow tests with other measurements show that the results correspond reasonably well. This is not the case for existing expressions for stationary flow. The existing formulae under-predict the a-values while they over-predict the b-values. Further research must be concentrated on the influence of parameters such as grading, the aspect ratio and shape. These dependencies can be determined under stationary flow conditions.
Rental Determination Factors of Super Regional Malls in Greater Kuala Lumpur

Rental rate is significant benchmarking and decision-making indicator for the banking and retail sectors. Determining accurate rental rates for shopping mall is essential and should be given a high priority. There are many opinions on the factors affecting rental rates for retail spaces in shopping malls. Rental data collected from tenancies show differential rental rates for the same type of tenants even though they are located at the same retail floor. This research aims to determine the factors affecting the rental of retail space of selected super regional shopping malls using secondary rental data obtained from NAPIC which are originally collected from property managers returns. Verifications on the rental data are made to ensure consistency with existing tenants before regression analyses are conducted. Two regression analyses using ENTER and STEPWISE methods are carried out. Out of twenty-eight factors examined only ten factors significantly affect retail rentals of super regional malls. Among the key significant factors are size, mall’s characteristics (KLCC, My Town, IOI City Mall Mid Valley), business category (food and beverage), tenancy period and location of retail outlets (corner, atrium and intermediate). The findings of the research may guide property valuers on the significant factors that affect the rental values of regional shopping malls and may improve real estate investors’ decision making.
Blow-up rate estimates for the solutions of the bosonic Boltzmann-Nordheim equation

In this paper, we study the behavior of a class of mild solutions of the homogeneous and isotropic bosonic Boltzmann-Nordheim equation near the blow-up. We obtain some estimates on the blow-up rate of the solutions and prove that, as long as a solution is bounded above by the critical singularity 1x (the equilibrium solutions behave like this power law near the origin), it remains bounded in the uniform norm. In Sec. III of the paper, we prove a local existence result for a class of measure-valued mild solutions, which is of independent interest and which allows us to solve the Boltzmann-Nordheim equation for some classes of unbounded densities.
Identification of subsurface damage of 4H-SiC wafers by combining photo-chemical etching and molten-alkali etching

In this work, we propose to reveal the subsurface damage (SSD) of 4H-SiC wafers by photo-chemical etching and identify the nature of SSD by molten-alkali etching. Under UV illumination, SSD acts as a photoluminescence-black defect. The selective photo-chemical etching reveals SSD as the ridge-like defect. It is found that the ridge-like SSD is still crystalline 4H-SiC with lattice distortion. The molten-KOH etching of the 4H-SiC wafer with ridge-like SSD transforms the ridge-like SSD into groove lines, which are typical features of scratches. This means that the underlying scratches under mechanical stress give rise to the formation of SSD in 4H-SiC wafers. SSD is incorporated into 4H-SiC wafers during the lapping, rather than the chemical mechanical polishing (CMP).
The seen and unseen: Exploring place identity of market place in Peninsular Malaysia

The roles of the marketplace in promoting place identity have been the central focus of the UN- Habitat and stakeholders around the globe. The notion of marketplace relating to place identity, place attachment and sense of place have gained attention by Malaysian researchers but much focused on the overt of the marketplaces compared to the covert. This study aims to explore how the seen and unseen elements coexist and enhance place identity. The objective is to discover the influence of overt and covert parameters on marketplace identity through the cultural mapping among four different regions in Peninsular Malaysia. This study employs a qualitative approach through direct non-participant observation and cultural mapping at the four selected marketplaces: Pantai Suri floating market in Tumpat, Kelantan, Pasar Bisik in Penaga, Penang, Pasar Jerami in Sungai Besar, Selangor and Pasar Borneo in Masai, Johor. The overt and covert of each market were carefully observed and mapped, where three substantial outcomes were revealed. First, the social interaction and transaction, social activities and social connectivity at the market portray the covert aspect as vital for place identity. Second, marketplaces have the potentials as dynamic community public spaces to get fresh daily products and promote local heritage and tourism. Third, marketplaces face threats from climate change, pandemic Covid-19, and the diminishing local culture and traditions. In conclusion, the covert and overt of marketplaces should be equally preserved as they become primary components for developing a regional place identity.
Which Factors Contribute to the Homeownership Decision? A Preliminary Study of Malaysia’s Young Adult

Young adults refer to those between 25 and 40 years of age who had established themselves in the society. The increasing house price and interest rates has put homeownership among young adults are at risk. Most of young adults in Malaysia are opted to renting rather than owning the house. This research aims to assess the challenges faced by young adults in owning a house in Klang Valley. Klang Valley is chosen as study area because it is the center for development and economic of Malaysia, thus has been the focus of government policy and developer activities pertaining to housing. The survey was conducted with 385 respondents who stays and work in Klang Valley, by using simple random sampling. The data were collected and analyzed to have a better understanding on the challenges facing by young adults in owning a house in Klang Valley area. The study discovers that the most significant main factor influencing homeownership decision was location factors (M= 3.79), followed by Behavioral Factors (M=3.46) and lastly, Financial & Economic Factors (M=3.22).
Integrability conditions of quasi-Newtonian cosmologies in modified gravity

We investigate the integrability conditions of a class of shear-free perfect-fluid cosmological models within the framework of anisotropic fluid sources, applying our results to f(R) dark energy models. Generalizing earlier general relativistic results for timelike geodesics, we extend the potential and acceleration terms of the quasi-Newtonian formulation of integrable dust cosmological models about a linearized Friedmann–Lemaitre–Robertson–Walker background and derive the equations that describe their dynamical evolutions. We show that in general, models with an anisotropic fluid source are not consistent, but because of the particular form the anisotropic stress πab takes in f(R) gravity, the general integrability conditions in this case are satisfied.