The Universe is worth 64364^3 pixels: Convolution Neural Network and Vision Transformers for Cosmology

We present a novel approach for estimating cosmological parameters, $\Omega_m$, $\sigma_8$, $w_0$, and one derived parameter, $S_8$, from 3D lightcone data of dark matter halos in redshift space covering a sky area of $40^\circ \times 40^\circ$ and redshift range of $0.3 < z < 0.8$, binned to $64^3$ voxels. Using two deep learning algorithms, Convolutional Neural Network (CNN) and Vision Transformer (ViT), we compare their performance with the standard two-point correlation (2pcf) function. Our results indicate that CNN yields the best performance, while ViT also demonstrates significant potential in predicting cosmological parameters. By combining the outcomes of Vision Transformer, Convolution Neural Network, and 2pcf, we achieved a substantial reduction in error compared to the 2pcf alone. To better understand the inner workings of the machine learning algorithms, we employed the Grad-CAM method to investigate the sources of essential information in activation maps of the CNN and ViT. Our findings suggest that the algorithms focus on different parts of the density field and redshift depending on which parameter they are predicting. This proof-of-concept work paves the way for incorporating deep learning methods to estimate cosmological parameters from large-scale structures, potentially leading to tighter constraints and improved understanding of the Universe.Comment: 23 pages, 10 figure

Accounting Conservatism, Changes In Real Investment, And Analysts Earnings Forecasts

This study examines whether sell-side analysts fully incorporate into their earnings forecasts the joint effects between accounting conservatism and changes in real investment on the quality of current earnings. Our results indicate that sell-side analysts do not fully incorporate such effects when they forecast future earnings so that they overestimate (underestimate) future earnings when current earnings are inflated (depressed) by those effects. Thus, we conclude that sell-side analysts do not recognize fully the joint effects between accounting conservatism and real activity on the earnings quality and that they need to mitigate their bias to enhance market efficiency by providing investors with a good benchmark for their earnings expectation

Smart and Safe Vehicle Monitoring with Fuzzy Integral and Haar-like Features

An on-board Android-based smart and safe vehicle monitoring system is presented. The on-board monitoring system (OMS) performs important monitoring functions: Record, Report and Alert (RRA). The Record function records front images of a moving vehicle. During the recording, any accidents or other emergency conditions will be automatically reported via the Report function for an emergency rescue operation. For the detection of shocks or accidents, we use acceleration based shock sensors that utilize fuzzy integral algorithm. The OMS also focuses on drowsiness that is largely regarded as the main cause of most accidents. The Haar-like feature is used to detect any sign of drowsiness and the Alert function is performed to alert the driver. All the vehicle-borne information is stored at a remote server via wireless communication links for later use or post-processing. A test bed has been developed and verified thoroughly for its accurate operations. The proposed smart and safe vehicle monitoring system offers advanced safety features and is expected to substantially reduce fatigue related accidents

2,4-Bis(2-methoxy­phenyl)-3-aza­bicyclo­[3.3.1]nonan-9-one

In the title compound, C22H25NO3, the mol­ecule has a pseudo-mirror plane. The structure is a positional isomer of 2,4-bis(4-methoxy­phenyl)-3-aza­bicyclo­[3.3.1]nonan-9-one [Cox, McCabe, Milne & Sim (1985 ▶). J. Chem. Soc. Chem. Commun. pp. 626–628]. The 3-aza­bicyclo­[3.3.1]nonan-9-one moiety adopts a double chair conformation with equatorial orientations of both 2-methoxy­phenyl substituents on either side of the secondary amino group. The benzene rings are oriented at an angle of 33.86 (4)° with respect to each other and the meth­oxy groups point towards the carbonyl group. The crystal structure is stabilized by intermolecular N—H⋯π inter­actions

A Waveform-Encoded SAR Implementation Using a Limited Number of Cyclically Shifted Chirps

Synthetic aperture radar (SAR) provides high-resolution images of the Earth’s surfaceirrespective of sunlight and weather conditions. In conventional spaceborne SAR, nadir echoescaused by the pulsed operation of SAR may significantly affect the SAR image quality. Therefore,the pulse repetition frequency (PRF) is constrained within the SAR system design to avoid theappearance of nadir echoes in the SAR image. As an alternative, the waveform-encoded SAR conceptusing a pulse-to-pulse variation of the transmitted waveform and dual-focus postprocessing canbe exploited for nadir echo removal and to alleviate the PRF constraints. In particular, cyclicallyshifted chirps have been proposed as a possible waveform variation scheme. However, a largenumber of distinct waveforms is required to enable the simple implementation of the concept.This work proposes a technique based on the Eulerian circuit for generating a waveform sequencestarting from a reduced number of distinct cyclically shifted chirps that can be effectively exploitedfor waveform-encoded SAR. The nadir echo suppression performance of the proposed scheme isanalyzed through simulations using real TerraSAR-X data and a realistic nadir echo model thatshows how the number of distinct waveforms and therefore the system complexity can be reducedwithout significant performance loss. These developments reduce the calibration burden and makethe concept viable for implementation in future SAR systems

High-resolution crystal structure of the non-specific lipid-transfer protein from maize seedlings

AbstractBackground: The movement of lipids between membranes is aided by lipid-transfer proteins (LTPs). Some LTPs exhibit broad specificity, transferring many classes of lipids, and are termed non-specific LTPs (ns-LTPs). Despite their apparently similar mode of action, no sequence homology exists between mammalian and plant ns-LTPs and no three-dimensional structure has been reported for any plant ns-LTP.Results We have determined the crystal structure of ns-LTP from maize seedlings by multiple isomorphous replacement and refined the structure to 1.9 å resolution. The protein comprises a single compact domain with four α-helices and a long C-terminal region. The eight conserved cysteines form four disulfide bridges (assigned as Cys4–Cys52, Cys14–Cys29, Cys30–Cys75, and Cys50–Cys89) resolving the ambiguity that remained from the chemical determination of pairings in the homologous protein from castor bean. Two of the bonds, Cys4–Cys52 and Cys50–Cys89, differ from what would have been predicted from sequence alignment with soybean hydrophobic protein. The complex between maize ns-LTP and hexadecanoate (palmitate) has also been crystallized and its structure refined to 1.8 å resolution.Conclusion The fold of maize ns-LTP places it in a new category of all-α-type structure, first described for soybean hydrophobic protein. In the absence of a bound ligand, the protein has a tunnel-like hydrophobic cavity, which is large enough to accommodate a long fatty acyl chain. In the structure of the complex with palmitate, most of the acyl chain is buried inside this hydrophobic cavity