GEOMAX: beyond linear compression for three-point galaxy clustering statistics

ABSTRACT We present the GEOMAX algorithm and its python implementation for a two-step compression of bispectrum measurements. The first step groups bispectra by the geometric properties of their arguments; the second step then maximizes the Fisher information with respect to a chosen set of model parameters in each group. The algorithm only requires the derivatives of the data vector with respect to the parameters and a small number of mock data, producing an effective, non-linear compression. By applying GEOMAX to bispectrum monopole measurements from BOSS DR12 CMASS redshift-space galaxy clustering data, we reduce the 68 per cent credible intervals for the inferred parameters (b1, b2, f, σ8) by 50.4, 56.1, 33.2, and 38.3 per cent with respect to standard MCMC on the full data vector. We run the analysis and comparison between compression methods over 100 galaxy mocks to test the statistical significance of the improvements. On average, GEOMAX performs ∼15 per cent better than geometrical or maximal linear compression alone and is consistent with being lossless. Given its flexibility, the GEOMAX approach has the potential to optimally exploit three-point statistics of various cosmological probes like weak lensing or line-intensity maps from current and future cosmological data sets such as DESI, Euclid, PFS, and SKA.

Investigation of Heating and Freezing Pretreatments on Mechanical, Chemical and Spectral Properties of Bulk Sunflower Seeds and Oil

The present study examined the effects of heating and freezing pretreatments on the mechanical, chemical, and spectral characteristics of sunflower seeds and oil under a linear compression process involving a universal compression-testing machine and a pressing vessel of diameter 60 mm with a plunger. The heating temperatures ranged from 40 to 80 °C and freezing temperatures from −2 to −36 °C at constant heating time of 30 min. The pretreated samples of initial height of 80 mm (22.6 × 10−5 m3) were compressed under a preset load of 100 kN and a speed of 5 mm/min. The results showed that oil expression efficiency significantly increased (p < 0.05) with increased heating temperatures but decreased with freezing temperatures. The lowest energy per volume oil of 22.55 ± 0.919 kJ/L was recorded at 80 °C compared to 26.40 ± 0.307 kJ/L noticed at −2 °C and control (25 °C) of 33.93 ± 3.866 kJ/L. The linear regression equations expressing oil expression efficiency, energy per volume oil, peroxide value, and free fatty acid, dependent on heating and freezing temperatures, were described with coefficients of determination between 0.373 and 0.908. Increased heating temperatures increased the UV absorption rate of the oil samples at a wavelength of 350 nm. The study is part of the continuing research on linear compression modeling of all processing factors, whereby the results are intended to be applied to the non-linear process dealing with a mechanical screw press to improve the oil extraction process.

CNN performance dependence on linear image processing

This work reports on convolutional neural network (CNN) performance on an image texture classification task as a function of linear image processing and number of training images. Detection performance of single and multi-layer CNNs (sCNN/mCNN) are compared to optimal observers. Performance is quantified by the area under the receiver operating characteristic (ROC) curve, also known as the AUC. For perfect detection AUC = 1.0 and AUC = 0.5 for guessing. The Ideal Observer (IO) maximizes AUC but is prohibitive in practice because it depends on high-dimensional image likelihoods. The IO performance is invariant to any fullrank, invertible linear image processing. This work demonstrates the existence of full-rank, invertible linear transforms that can degrade both sCNN and mCNN even in the limit of large quantities of training data. A subsequent invertible linear transform changes the images’ correlation structure again and can improve this AUC. Stationary textures sampled from zero mean and unequal covariance Gaussian distributions allow closed-form analytic expressions for the IO and optimal linear compression. Linear compression is a mitigation technique for high-dimension low sample size (HDLSS) applications. By definition, compression strictly decreases or maintains IO detection performance. For small quantities of training data, linear image compression prior to the sCNN architecture can increase AUC from 0.56 to 0.93. Results indicate an optimal compression ratio for CNN based on task difficulty, compression method, and number of training images.

Large negative linear compressibility of a porous molecular co-crystal

Porous 1,2-bis[2-methyl-5-(pyridyl)-3thienyl] cyclopentene cocrystal with 1,4-diiodotetrafluorobenzene exhibits large negative linear compression correlated with the shape of pores.

Modeling of Linear and Non-linear Compression Processes of Sunflower Bulk Oilseeds

The present study aimed at describing the experimental and theoretical force-deformation curves of sunflower bulk oilseeds at varying initial pressing heights and vessel diameters as well as determining the theoretical pressure and energy along the screw press FL 200 pressing chambers. The design of efficient oil expression systems for industry and small-scale application remains a major challenge to engineers and researchers. In attempting to solve the problem, it is important to understand the linear compression process and to transfer the knowledge to the industry involving mechanical screw presses. The universal compression testing machine at a preset load of 200 kN and a speed of 5 mm·min−1, tangent curve model and the screw press FL 200 geometry parameters were applied. The obtained results of pressure and energy along the screw pressing chambers (1–7) ranged from 0.31 to 101.653 MPa and 12.616 to 1231.228 J. Applying the tangent model at n = 1 and n = 2, the cumulative pressure decreased with increasing vessel diameters while energy increased. The study provides useful information for the analysis of other bulk oilseeds and optimizing the processing parameters of screw press FL 200 and the design and development of new oil presses.

The effect of compression rate and slope on the incidence of symptomatic Eustachian tube dysfunction leading to middle ear barotrauma: a Phase I prospective study

Introduction: Symptomatic Eustachian tube dysfunction (ETD) and middle ear barotrauma (MEB) are the most common reported complications during hyperbaric oxygen (HBO2) treatment. There is no standardized rate of compression (ROC) reported to decrease the incidence rates of ETD and MEB during hyperbaric treatments. Few studies actually demonstrate that the ROC decreases the incidence of ETD or MEB. Methods: Our study was designed to determine an optimal hyperbaric chamber compression rate that might reduce the incidence of symptomatic ETD leading to MEB during the compression phase of treatment in a multiplace hyperbaric chamber. Data was collected prospectively over 2,807 elective patient treatments compressed using a U.S. Navy Treatment Table 9 (USN TT9) with a modified ROC. ROC was assigned using two variables, time (10 vs.15 minutes) and slope (linear vs. non-linear compression). Patients were exposed to all four compression schedules in a consecutive daily fashion. We recorded any patient requiring a stop during initial compression due to ear discomfort. Anyone requiring a stop was evaluated post treatment for MEB. Findings were compared to our standard 10-minute linear ROC. Evaluation of the tympanic membrane was accomplished using video otoscopy. Barotrauma when present was classified using both the Teed and O’Neill grading systems. Data was analyzed using basic statistical methods. Results: When comparing four different rates of compression during an elective USN TT9 in a multiplace (Class A) chamber there is a decreased incidence for symptomatic ETD when using a 15-minute linear compression schedule (p-value < 0.05). Conclusion: Using a 15-minute linear compression schedule is associated with less symptomatic ETD and less MEB when performing an elective 45 fsw (USN TT9) hyperbaric treatment in a Class A chamber. Asymptomatic ETD and MEB were not considered in this study.