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In Machine learning (ML) and deep learning (DL), hyperparameter tuning is the process of selecting the combination of optimal hyperparameters that give the best performance. Thus, the behavior of some machine learning (ML) and deep learning (DL) algorithms largely depend on their hyperparameters. While there has been a rapid growth in the application of machine learning (ML) and deep learning (DL) algorithms to Additive manufacturing (AM) techniques, little to no attention has been paid to carefully selecting and optimizing the hyperparameters of these algorithms in order to investigate their influence and achieve the best possible model performance. In this work, we demonstrate the effect of a grid search hyperparameter tuning technique on a Multilayer perceptron (MLP) model using datasets obtained from a Fused Filament Fabrication (FFF) AM process. The FFF dataset was extracted from the MakerBot MethodX 3D printer using internet of things (IoT) sensors. Three (3) hyperparameters were considered – the number of neurons in the hidden layer, learning rate, and the number of epochs. In addition, two different train-to-test ratios were considered to investigate their effects on the AM process data. The dataset consisted of five (5) dominant input parameters which include layer thickness, build orientation, extrusion temperature, building temperature, and print speed and three (3) output parameters: dimension accuracy, porosity, and tensile strength. RMSE, and the computational time, CT, were both selected as the hyperparameter performance metrics. The experimental results reveal the optimal configuration of hyperparameters that contributed to the best performance of the MLP model. 

Three-dimensional (3D) printing is implemented for surface modification of titanium alloy substrates with multilayered biofunctional polymeric coatings. Poly(lactic-co- glycolic) acid (PLGA) and polycaprolactone (PCL) polymers were embedded with amorphous calcium phosphate (ACP) and vancomycin (VA) therapeutic agents to promote osseointegration and antibacterial activity, respectively. PCL coatings revealed a uniform deposition pattern of the ACP-laden formulation and enhanced cell adhesion on the titanium alloy substrates as compared to the PLGA coatings. Scanning electron microscopy and Fourier-transform infrared spectroscopy confirmed a nanocomposite structure of ACP particles showing strong binding with the polymers. Cell viability data showed comparable MC3T3 osteoblast proliferation on polymeric coatings as equivalent to positive controls. In vitro live/dead assessment indicated higher cell attachments for 10 layers (burst release of ACP) as compared to 20 layers (steady release) for PCL coatings. The PCL coatings loaded with the antibacterial drug VA displayed a tunable release kinetics profile based on the multilayered design and drug content of the coatings. Moreover, the concentration of active VA released from the coatings was above the minimum inhibitory concentration and minimum bactericidal concentration, demonstrating its effectiveness against Staphylococcus aureus bacterial strain. This research provides a basis for developing antibacterial biocompatible coatings to promote osseointegration of orthopedic implants. 

We report the methods of and initial scientific inferences from the extraction of precision photometric information for the >800 trans-Neptunian objects (TNOs) discovered in the images of the Dark Energy Survey (DES). Scene-modeling photometry is used to obtain shot-noise-limited flux measures for each exposure of each TNO, with background sources subtracted. Comparison of double-source fits to the pixel data with single-source fits are used to identify and characterize two binary TNO systems. A Markov Chain Monte Carlo method samples the joint likelihood of the intrinsic colors of each source as well as the amplitude of its flux variation, given the time series of multiband flux measurements and their uncertainties. A catalog of these colors and light-curve amplitudesAis included with this publication. We show how to assign a likelihood to the distributionq(A) of light-curve amplitudes in any subpopulation. Using this method, we find decisive evidence (i.e., evidence ratio <0.01) that cold classical (CC) TNOs with absolute magnitude 6 <H_r< 8.2 are more variable than the hot classical (HC) population of the sameH_r, reinforcing theories that the former form in situ and the latter arise from a different physical population. Resonant and scattering TNOs in thisH_rrange have variability consistent with either the HCs or CCs. DES TNOs withH_r< 6 are seen to be decisively less variable than higher-H_rmembers of any dynamical group, as expected. More surprising is that detached TNOs are decisively less variable than scattering TNOs, which requires them to have distinct source regions or some subsequent differential processing.

 

Clusters of galaxies trace the most non-linear peaks in the cosmic density field. The weak gravitational lensing of background galaxies by clusters can allow us to infer their masses. However, galaxies associated with the local environment of the cluster can also be intrinsically aligned due to the local tidal gradient, contaminating any cosmology derived from the lensing signal. We measure this intrinsic alignment in Dark Energy Survey (DES) Year 1 redMaPPer clusters. We find evidence of a non-zero mean radial alignment of galaxies within clusters between redshifts 0.1–0.7. We find a significant systematic in the measured ellipticities of cluster satellite galaxies that we attribute to the central galaxy flux and other intracluster light. We attempt to correct this signal, and fit a simple model for intrinsic alignment amplitude (AIA) to the measurement, finding AIA = 0.15 ± 0.04, when excluding data near the edge of the cluster. We find a significantly stronger alignment of the central galaxy with the cluster dark matter halo at low redshift and with higher richness and central galaxy absolute magnitude (proxies for cluster mass). This is an important demonstration of the ability of large photometric data sets like DES to provide direct constraints on the intrinsic alignment of galaxies within clusters. These measurements can inform improvements to small-scale modelling and simulation of the intrinsic alignment of galaxies to help improve the separation of the intrinsic alignment signal in weak lensing studies.

 

Widefield surveys probe clustered scalar fields – such as galaxy counts, lensing potential, etc. – which are sensitive to different cosmological and astrophysical processes. Constraining such processes depends on the statistics that summarize the field. We explore the cumulative distribution function (CDF) as a summary of the galaxy lensing convergence field. Using a suite of N-body light-cone simulations, we show the CDFs’ constraining power is modestly better than the second and third moments, as CDFs approximately capture information from all moments. We study the practical aspects of applying CDFs to data, using the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the point spread function and reduced shear approximation are $\lesssim 1~{{\ \rm per\ cent}}$ of the total signal. Source clustering effects and baryon imprints contribute 1–10 per cent. Enforcing scale cuts to limit systematics-driven biases in parameter constraints degrade these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We detect correlations between the observed convergence field and the shape noise field at 13σ. The non-Gaussian correlations in the noise field must be modelled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool.

 

We present an alternative calibration of the MagLim lens sample redshift distributions from the Dark Energy Survey (DES) first 3 yr of data (Y3). The new calibration is based on a combination of a self-organizing-map-based scheme and clustering redshifts to estimate redshift distributions and inherent uncertainties, which is expected to be more accurate than the original DES Y3 redshift calibration of the lens sample. We describe in detail the methodology, and validate it on simulations and discuss the main effects dominating our error budget. The new calibration is in fair agreement with the fiducial DES Y3 n(z) calibration, with only mild differences (<3σ) in the means and widths of the distributions. We study the impact of this new calibration on cosmological constraints, analysing DES Y3 galaxy clustering and galaxy–galaxy lensing measurements, assuming a Lambda cold dark matter cosmology. We obtain Ωm = 0.30 ± 0.04, σ8 = 0.81 ± 0.07, and S8 = 0.81 ± 0.04, which implies a ∼0.4σ shift in the Ω − S8 plane compared to the fiducial DES Y3 results, highlighting the importance of the redshift calibration of the lens sample in multiprobe cosmological analyses.

 

The fiducial cosmological analyses of imaging surveys like DES typically probe the Universe at redshifts z < 1. We present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around z ∼ 0.9, 1.2, and 1.5, which extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times higher than those in the DES Year 3 fiducial case. We characterize the redshift uncertainties of the samples, including the usage of various spectroscopic and high-quality redshift samples, and we develop a machine-learning method to correct for correlations between galaxy density and survey observing conditions. The analysis of galaxy clustering measurements, with a total signal to noise S/N ∼ 70 after scale cuts, yields robust cosmological constraints on a combination of the fraction of matter in the Universe Ωm and the Hubble parameter h, $\Omega _m h = 0.195^{+0.023}_{-0.018}$, and 2–3  per cent measurements of the amplitude of the galaxy clustering signals, probing galaxy bias and the amplitude of matter fluctuations, bσ8. A companion paper (in preparation) will present the cross-correlations of these high-z samples with cosmic microwave background lensing from Planck and South Pole Telescope, and the cosmological analysis of those measurements in combination with the galaxy clustering presented in this work.

 

Radiation therapy is a powerful and effective treatment which targets malignant tumors. Thus, improvements in radiation therapy devices such as compensators can have an immediate impact on the treatment of cancer patients. This paper investigates the design and manufacturing of customized radiation modulation devices. This research proposes a thin-walled device design that can use recyclable fillable media such as water. This approach has several advantages including localized radiation exposure, eco-friendly design, and lower fabrication costs. The Fused Deposition Modeling (FDM) technique was used to develop a hollow bottle-like electron bolus with higher precision (μm resolution). The radiation modulation properties of acrylonitrile butadiene styrene (ABS) and polycarbonate (PC) materials were investigated. The compensator devices were subjected to high radiation doses and mechanical loads to check for dimensional deformations which can impact subsequent radiation profiles. Our findings showed that both ABS and PC materials had superior radiation tolerance as evaluated by the dimensional deviation analysis. Further, the devices had adequate mechanical properties as confirmed by deformation tests and finite element analysis. This paper provides a framework for the design and manufacture of custom compensators for radiation therapy. 

Nanoimprinting of polymers lays the foundation for several electronic and biomedical devices. Process parameter optimization have been conducted using thermal nanoimprint (T-NIL) experimentation. However, the underlying deformation mechanism of specific polymers under varying process condition needs further exploration. This research investigates the deformation behavior of poly acrylic acid (PAA) as a thermoplastic resist material for the T-NIL process. Molecular dynamics modeling was conducted on a PAA substrate imprinted with a rigid, spherical indenter. The effect of indenter size, force, and imprinting duration on the indentation depth, penetration depth, recovery depth, and recovery percentage of the polymer was evaluated. The results show that the largest indenter, regardless of force has the most significant impact on deformation behavior. The results of this research lay foundation for explaining the effect of several T-NIL process parameters on virgin PAA thermoplastic resist material. 

We combine photometry of Eris from a 6 month campaign on the Palomar 60 inch telescope in 2015, a 1 month Hubble Space Telescope WFC3 campaign in 2018, and Dark Energy Survey data spanning 2013–2018 to determine a light curve of definitive period 15.771 ± 0.008 days (1σformal uncertainties), with nearly sinusoidal shape and peak-to-peak flux variation of 3%. This is consistent at part-per-thousand precision with theP= 15.785 90 ± 0.00005 day sidereal period of Dysnomia’s orbit around Eris, strengthening the recent detection of synchronous rotation of Eris by Szakáts et al. with independent data. Photometry from Gaia are consistent with the same light curve. We detect a slope of 0.05 ± 0.01 mag per degree of Eris’s brightness with respect to illumination phase averaged acrossg,V, andrbands, intermediate between Pluto’s and Charon’s values. Variations of 0.3 mag are detected in Dysnomia’s brightness, plausibly consistent with a double-peaked light curve at the synchronous period. The synchronous rotation of Eris is consistent with simple tidal models initiated with a giant-impact origin of the binary, but is difficult to reconcile with gravitational capture of Dysnomia by Eris. The high albedo contrast between Eris and Dysnomia remains unexplained in the giant-impact scenario.