Miracle-dz/UniFAR-FTUs huggingface dataset:
Lattice constant variation and complex formation in zincblende gallium manganese arsenide

We perform high resolution x-ray diffraction on GaMnAs mixed crystals as well as on GaMnAs/GaAs and GaAs/MnAs superlattices for samples grown by low-temperature molecular-beam epitaxy under different growth conditions. Although all samples are of high crystalline quality and show narrow rocking curve widths and pronounced finite thickness fringes, the lattice constant variation with increasing manganese concentration depends strongly on the growth conditions: For samples grown at substrate temperatures of 220 and 270 °C, the extrapolated relaxed lattice constant of Zincblende MnAs is 0.590 nm and 0.598 nm, respectively. This is in contrast to low-temperature GaAs, for which the lattice constant decreases with increasing substrate temperature.
Efficient Power Characteristic Analysis and Multi-Objective Optimization for an Irreversible Simple Closed Gas Turbine Cycle

On the basis of the established irreversible simple closed gas turbine cycle model, this paper optimizes cycle performance further by applying the theory of finite-time thermodynamics. Dimensionless efficient power expression of the cycle is derived. Effects of internal irreversibility (turbine and compressor efficiencies) and heat reservoir temperature ratio on dimensionless efficient power are analyzed. When total heat conductance of two heat exchangers is constant, the double maximum dimensionless efficient power of a cycle can be obtained by optimizing heat-conductance distribution and cycle pressure-ratio. Through the NSGA-II algorithm, multi-objective optimizations are performed on the irreversible closed gas turbine cycle by taking five performance indicators, dimensionless power density, dimensionless ecological function, thermal efficiency, dimensionless efficient power and dimensionless power output, as objective functions, and taking pressure ratio and heat conductance distribution as optimization variables. The Pareto frontiers with the optimal solution set are obtained. The results reflect that heat reservoir temperature ratio and compressor efficiency have greatest influences on dimensionless efficient power, and the deviation indexes obtained by TOPSIS, LINMAP and Shannon Entropy decision-making methods are 0.2921, 0.2921, 0.2284, respectively, for five-objective optimization. The deviation index obtained by Shannon Entropy decision-making method is smaller than other decision-making methods and its result is more ideal.
A Novel Ketone-Supplemented Diet Improves Recognition Memory and Hippocampal Mitochondrial Efficiency in Healthy Adult Mice

Mitochondrial dysfunction and cognitive impairment are common symptoms in many neurologic and psychiatric disorders, as well as nonpathological aging. Ketones have been suggested as therapeutic for their efficacy in epilepsy and other brain pathologies such as Alzheimer’s disease and major depressive disorder. However, their effects on cognitive function in healthy individuals is less established. Here, we explored the mitochondrial and performative outcomes of a novel eight-week ketone-supplemented ketogenic (KETO) diet in healthy adult male and female mice. In a novel object recognition test, KETO mice spent more time with the novel, compared to familiar, object, indicating an improvement in recognition memory. High-resolution respirometry on permeabilized hippocampal tissue returned significant reductions in mitochondrial O2 consumption. No changes in ATP production were observed, yielding a significantly higher ATP:O2 ratio, a measure of mitochondrial efficiency. Together, these findings demonstrate the KETO diet improves hippocampal mitochondrial efficiency. They add to a growing body of evidence that suggests ketones and ketogenic diets are neuroprotective and metabolically and cognitively relevant, even in healthy adults. They also suggest that ketogenic lifestyle changes may be effective strategies for protecting against cognitive decline associated with aging and disease.
An L Band Spectrum of the Coldest Brown Dwarf

The coldest brown dwarf, WISE 0855, is the closest known planetary-mass, free-floating object and has a temperature nearly as cold as the solar system gas giants. Like Jupiter, it is predicted to have an atmosphere rich in methane, water, and ammonia, with clouds of volatile ices. WISE 0855 is faint at near-infrared wavelengths and emits almost all its energy in the mid-infrared. Skemer et al. presented a spectrum of WISE 0855 from 4.5–5.1 μm (M band), revealing water vapor features. Here, we present a spectrum of WISE 0855 in the L band, from 3.4–4.14 μm. We present a set of atmosphere models that include a range of compositions (metallicities and C/O ratios) and water ice clouds. Methane absorption is clearly present in the spectrum. The mid-infrared color can be better matched with a methane abundance that is depleted relative to solar abundance. We find that there is evidence for water ice clouds in the M band spectrum, and we find a lack of phosphine spectral features in both the L and M band spectra. We suggest that a deep continuum opacity source may be obscuring the near-infrared flux, possibly a deep phosphorous-bearing cloud, ammonium dihyrogen phosphate. Observations of WISE 0855 provide critical constraints for cold planetary atmospheres, bridging the temperature range between the long-studied solar system planets and accessible exoplanets. The James Webb Space Telescope will soon revolutionize our understanding of cold brown dwarfs with high-precision spectroscopy across the infrared, allowing us to study their compositions and cloud properties, and to infer their atmospheric dynamics and formation processes.
ALMA Observations of Asymmetric Molecular Gas Emission from a Protoplanetary Disk in the Orion Nebula

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of molecular line emission from d216-0939, one of the largest and most massive protoplanetary disks in the Orion Nebula Cluster. We model the spectrally resolved HCO+ (4–3), CO (3–2), and HCN (4–3) lines observed at 0. ″5 resolution to fit the temperature and density structure of the disk. We also weakly detect and spectrally resolve the CS (7–6) line but do not model it. The abundances we derive for CO and HCO+ are generally consistent with expected values from chemical modeling of protoplanetary disks, while the HCN abundance is higher than expected. We dynamically measure the mass of the central star to be , which is inconsistent with the previously determined spectral type of K5. We also report the detection of a spatially unresolved high-velocity blueshifted excess emission feature with a measurable positional offset from the central star, consistent with a Keplerian orbit at 60 ± 20 au. Using the integrated flux of the feature in HCO+ (4–3), we estimate the total H2 gas mass of this feature to be at least , depending on the assumed temperature. The feature is due to a local temperature and/or density enhancement consistent with either a hydrodynamic vortex or the expected signature of the envelope of a forming protoplanet within the disk.
Factors Affecting Young Mothers’ Access to Child Healthcare Services: A Behavioural Analysis to Guide the Development of Interventions

Abstract Young mothers are more likely to access healthcare for their children in emergent care settings and less likely to use preventive care. This study examines the healthcare-seeking behaviours of young mothers to inform the design of tailored interventions. Semi-structured interviews with nine young mothers (aged ≤ 25 years) who were attending a supported playgroup in Brisbane, Australia were conducted and explored using the Capability, Opportunity and Motivation and Behaviour (COM-B) model and the Theoretical Domains Framework (TDF). Five behavioural themes were identified (navigating the system, complex referral pathways, delays and long wait times, understanding child development, and connecting to services) and the role of the supported playgroup in shaping young mothers’ understanding of child development and connecting them to services was highlighted. Recommended strategies to address these factors include opportunities for young mothers to learn about child developmental milestones, improving young mothers’ health literacy, increasing young mothers’ skills and/or the availability of support to help them navigate health services, and providing more accessible entry points for child assessments, referrals, or early intervention programs.
A Strange EUV Emission: Scattered Continuum in the Lyman Limit Absorption Edge toward the Quasar SDSS J125903.26+621211.5?

We identified a peculiar proximate subdamped Lyα absorption system (sub-DLA) at z = 3.234 with a neutral hydrogen column density of toward the quasar SDSS J125903.26+621211.5 in two epoch optical spectra of the Sloan Digital Sky Survey. We detected Lyα residue in the proximate sub-DLA trough at a >8σ level. To our surprise, significant (>4σ) extreme ultraviolet (EUV) continuum emission was detected in the corresponding Lyman limit absorption edge at both of the FUV and NUV bands by the Galaxy Evolution Explorer. The high neutral hydrogen column density should allow a negligible transmission of both the Lyα line photons and EUV continuum photons due to the high optical depth of the gas. The possible scenarios of foreground galaxy contamination, partial coverage, emission from the quasar host galaxy, and extended Lyα emission are excluded in turn, and we speculate that the residual Lyα and EUV emissions are due to photon scattering (broad Lyα and the continuum emission) of electrons residing at a spatial scale larger than that of the proximate sub-DLA. Electron scattering is wavelength-independent, and the scattered light is therefore a copy of the incident spectrum that might originate in the accretion disk. With assistance from the neutral hydrogen absorbers as the “natural coronagraph” and the scatterers as the “natural mirror,” we yielded a very hard EUV spectral index of α = 0.65 ± 0.25 ( ), consistent with the standard picture of the locally heated accretion disk in the inner EUV-emitting radii, as well as in the outer near-infrared-emitting radii suggested by Kishimoto et al.
Molecular Analyses in Peritoneal Metastasis from Colorectal Cancer: A Review-An English Version

Despite a trend showing continued improvement in survival by combing targeted agents in colorectal cancer, the improvement was limited, and clinically meaningful benefits were not achieved in peritoneal metastasis. The role of cytoreductive surgery (CRS) and proportion of the benefit from hyperthermic intraperitoneal chemotherapy (HIPEC) have been questioned. The PRODIGE 7 study aimed to assess the specific contribution of HIPEC to the survival benefit of peritoneal metastasis from colorectal cancer (CRC-PM) by grouping CRS alone versus CRS with oxaliplatin-based HIPEC, but failed to show any survival improvement. Of these criticisms, oxaliplatin resistance was suggested as the main cause of the negative result. In this regard, the relative resistance to oxaliplatin in consensus molecular subtype 4 colorectal cancer (CRC) is of great interest. Recent treatments for metastatic CRC have gradually moved to precision medicine based on individual biological information through high-throughput technology such as next generation sequencing. This review aimed to provide an overview of the current status of studies reporting the molecular knowledge of CRC-PM.
Fault Detection in Induction Motor Using Time Domain and Spectral Imaging-Based Transfer Learning Approach on Vibration Data

The induction motor plays a vital role in industrial drive systems due to its robustness and easy maintenance but at the same time, it suffers electrical faults, mainly rotor faults such as broken rotor bars. Early shortcoming identification is needed to lessen support expenses and hinder high costs by using failure detection frameworks that give features extraction and pattern grouping of the issue to distinguish the failure in an induction motor using classification models. In this paper, the open-source dataset of the rotor with the broken bars in a three-phase induction motor available on the IEEE data port is used for fault classification. The study aims at fault identification under various loading conditions on the rotor of an induction motor by performing time, frequency, and time-frequency domain feature extraction. The extracted features are provided to the models to classify between the healthy and faulty rotors. The extracted features from the time and frequency domain give an accuracy of up to 87.52% and 88.58%, respectively, using the Random-Forest (RF) model. Whereas, in time-frequency, the Short Time Fourier Transform (STFT) based spectrograms provide reasonably high accuracy, around 97.67%, using a Convolutional Neural Network (CNN) based fine-tuned transfer learning framework for diagnosing induction motor rotor bar severity under various loading conditions.
Constraining Quasar Relativistic Reflection Regions and Spins with Microlensing

We present an analysis of Chandra spectra of five gravitationally lensed active galactic nuclei. We confirm the previous detections of FeKα emission lines in most images of these objects with high significance. The line energies range from 5.8 to 6.8 keV, with widths from unresolved to 0.6 keV, consistent with emission close to spinning black holes viewed at different inclination angles. We also confirm the positive offset from the Iwasawa–Taniguchi effect, the inverse correlation between the FeKα equivalent width (EW) and the X-ray luminosity in active galactic nuclei, where our measured EWs are larger in lensed quasars. We attribute this effect to microlensing, and perform a microlensing likelihood analysis to constrain the emission size of the relativistic reflection region and the spin of supermassive black holes, assuming that the X-ray corona and the reflection region, responsible for the iron emission line, both follow power-law emissivity profiles. The microlensing analysis yields strong constraints on the spin and emissivity index of the reflection component for Q 2237+0305, with a > 0.92 and n > 5.4. For the remaining four targets, we jointly constrain the two parameters, yielding a = 0.8 ± 0.16 and an emissivity index of n = 4.0 ± 0.8, suggesting that the relativistic X-ray reflection region is ultracompact and very close to the innermost stable circular orbits of black holes, which are spinning at close to the maximal value. We successfully constrain the half-light radius of the emission region to <2.4 rg (rg = GM/c2) for Q 2237+0305 and in the range 5.9–7.4 rg for the joint sample.
Morphology-assisted galaxy mass-to-light predictions using deep learning

Context. One of the most important properties of a galaxy is the total stellar mass, or equivalently the stellar mass-to-light ratio (M/L). It is not directly observable, but can be estimated from stellar population synthesis. Currently, a galaxy’s M/L is typically estimated from global fluxes. For example, a single global g − i colour correlates well with the stellar M/L. Spectral energy distribution (SED) fitting can make use of all available fluxes and their errors to make a Bayesian estimate of the M/L. Aims. We want to investigate the possibility of using morphology information to assist predictions of M/L. Our first goal is to develop and train a method that only requires a g-band image and redshift as input. This will allows us to study the correlation between M/L and morphology. Next, we can also include the i-band flux, and determine if morphology provides additional constraints compared to a method that only uses g- and i-band fluxes. Methods. We used a machine learning pipeline that can be split in two steps. First, we detected morphology features with a convolutional neural network. These are then combined with redshift, pixel size and g-band luminosity features in a gradient boosting machine. Our training target was the M/L acquired from the GALEX-SDSS-WISE Legacy Catalog, which uses global SED fitting and contains galaxies with z ∼ 0.1. Results. Morphology is a useful attribute when no colour information is available, but can not outperform colour methods on its own. When we combine the morphology features with global g- and i-band luminosities, we find an improved estimate compared to a model which does not make use of morphology. Conclusions. While our method was trained to reproduce global SED fitted M/L, galaxy morphology gives us an important additional constraint when using one or two bands. Our framework can be extended to other problems to make use of morphological information.
Characteristics of psychosocial interventions to improve ART adherence in people living with HIV: A systematic review

The HIV/AIDS pandemic continues to be a significant global public health crisis. The main HIV/AIDS treatment is the antiretroviral therapy (ART), which is highly effective but depends on the patient’s adherence to be successful. However, the adherence to antiretroviral therapy remains unsatisfactory across different populations, which raises considerable difficulties at both individual and collective levels. Suboptimal adherence to ART can be overcome through multidisciplinary management that includes evidence-based psychosocial interventions. Existing reviews on these interventions have focused mainly on studies with experimental designs, overlooking valuable interventions whose evidence comes from different study designs. Here, we aimed to carry out a comprehensive review of the current research on psychosocial interventions for ART adherence and their characteristics including studies with different designs. We conducted a systematic review following PRISMA guidelines. We searched five databases (Pubmed, EBSCO, LILACS, WoS and SCIELO) for articles reporting a psychosocial intervention to improve treatment adherence for people living with HIV (adults). The quality of each study was analyzed with standardized tools, and data were summarized using a narrative synthesis method. Twenty-three articles were identified for inclusion, and they demonstrated good to fair quality. Individual counseling was the most frequent intervention, followed by SMS reminders, education, and group support. Most interventions combined different strategies and self-efficacy was the most common underlying theoretical framework. This review provides insight into the main characteristics of current psychosocial interventions designed to improve ART treatment adherence. PROSPERO number: CRD42021252449.
‘Poisoned Chalice?’: the challenges of forensic science and technology for homicide investigations

ABSTRACT The challenges accompanying the investigation of homicide have been observed for some time. Although police today can gather evidence in ways not imagined decades ago, the use of forensic science and technology (FST) have created challenges and consequences for modern-day homicide investigations. While ‘digital footprints’ are increasingly expected in court proceedings, the provision of and analysis of FST data falls to the police who face resource shortages and other challenges. We surveyed homicide investigators across Alberta to examine their perceptions of FST and the implications of FST for their work. Participants revealed that data volume, lack of expertise and resource constraints result in frustration with FST and the demands it creates. At the same time, most participants pointed to civilianization as the means through which technology can provide full advantage to homicide (and other) investigations.
Merger rates in hierarchical models of galaxy formation – II. Comparison with N-body simulations

We have made a detailed comparison of the results of N-body simulations with the analytical description of the merging histories of dark matter haloes presented in Lacey & Cole, which is based on an extension of the Press-Schechter method. We find the analytical predictions for the halo mass function, merger rates and formation times to be remarkably accurate. The N-body simulations used 1283 particles and were of self- similar clustering, with Ω=1 and initial power spectra P(k)∝kn with spectral indices n =−2, −1,0. The analytical model is, however, expected to apply for arbitrary Ω and more general power spectra. Dark matter haloes were identified in the simulations using two different methods and at a range of overdensities. For haloes selected at mean overdensities ∼100-200, the analytical mass function was found to provide a good fit to the simulations with a collapse threshold close to that predicted by the spherical collapse model, with a typical error of ≲30 per cent over a range of 103 in mass, which is the full dynamical range of our N-body simulation. This was insensitive to the type of filtering used. Over a range of 102- 103 in mass, there was also good agreement with the analytical predictions for merger rates including their dependence on the masses of the two haloes involved and the time interval being considered, and for formation times, including the dependence on halo mass and formation epoch. The analytical Press-Schechter mass function and its extension to halo lifetimes and merger rates thus provide a very useful description of the growth of dark matter haloes through hierarchical clustering, and should provide a valuable tool in studies of the formation and evolution of galaxies and galaxy clusters.
Multi-Resolution Markov-Chain-Monte-Carlo Approach for System Identification with an Application to Finite-Element Models

Estimating unknown system configurations/parameters by combining system knowledge gained from a computer simulation model on one hand and from observed data on the other hand is challenging. An example of such inverse problem is detecting and localizing potential flaws or changes in a structure by using a finite-element model and measured vibration/displacement data. We propose a probabilistic approach based on Bayesian methodology. This approach does not only yield a single best-guess solution, but a posterior probability distribution over the parameter space. In addition, the Bayesian approach provides a natural framework to accommodate prior knowledge. A Markov chain Monte Carlo (MCMC) procedure is proposed to generate samples from the posterior distribution (an ensemble of likely system configurations given the data). The MCMC procedure proposed explores the parameter space at different resolutions (scales), resulting in a more robust and efficient procedure. The large-scale exploration steps are carried out using coarser-resolution finite-element models, yielding a considerable decrease in computational time, which can be a crucial for large finite-element models. An application is given using synthetic displacement data from a simple cantilever beam with MCMC exploration carried out at three different resolutions.
End-condition for solution small angle X-ray scattering measurements by kernel density estimation

ABSTRACT We develop a method for calculating the minimum X-ray exposure time for X-ray solution scattering experiments using statistical and mathematical approaches to enhance the measurement efficiency while maintaining data quality. Experts can determine the X-ray exposure time for samples by investigating time-series data of scattering profiles and considering the quality of scattering profiles and the samples’ X-ray damage. In this study, we apply a statistical inequality to estimate the kernel density estimation method’s error to determine the minimum X-ray exposure time for protein solution scattering experiments and evaluate the method’s validity using the results of Guinier analysis as an indicator. GRAPHICAL ABSTRACT