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We study the sets of planes in an even dimensional real vector space $V$ which are simultaneously stabilised by a pair of complex structures on $V$. We completely describe these sets of planes for pairs of orthogonal complex structures. Generically, the number of such planes is finite. We compute this number for orthogonal complex structures and prove that it gives a lower bound for the number of planes simultaneously stabilised by a generic pair of complex structures on $V$.

A recently launched professional development initiative in Arkansas, called Array, is designed to proactively identify early care and education (ECE) programs that could benefit from social-emotional-focused (SE-focused) professional development and support, and to offer assistance tailored to a program's particular needs. Because Array is designed to initiate contact with ECE programs, it has the potential to intervene early and prevent serious escalations of teachers' frustration in response to children's challenging behavior. This report examines results from case studies in three ECE programs that participated in Array between June and December 2022. The results focus on unique features of Array, how it operates, reported benefits to programs, and recommendations for continued improvement.

Given the central importance of positive parent and infant-early childhood mental health to children's long-term mental health and development, it is important to examine a wide range of approaches that show promise for strengthening supports for parent and infant-early childhood mental health in home visiting programs, especially programs serving diverse families. This report provides a view of promising strategies from the perspective of staff in home visiting programs that span multiple types and models and serve families from different cultural, racial/ ethnic, and linguistic backgrounds. Following a brief discussion of the project's methods for identifying and learning from a sample of home visiting programs, the report examines key strategies for promoting parent and child mental health as described by home visiting staff and expert respondents. The report concludes with recommendations for policy, program implementation supports, and research that could help advance the field's understanding and use of the most effective strategies. [Funding for this report was provided by the Perigee Foundation.]

Tabular data have been extensively used in different knowledge domains. Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features (images), outperforming predictive results of traditional models. Recently, several researchers have proposed transforming tabular data into images to leverage the potential of CNNs and obtain high results in predictive tasks such as classification and regression. In this paper, we present a novel and effective approach for transforming tabular data into images, addressing the inherent limitations associated with low-dimensional and mixed-type datasets. Our method, named Low Mixed-Image Generator for Tabular Data (LM-IGTD), integrates a stochastic feature generation process and a modified version of the IGTD. We introduce an automatic and interpretable end-to-end pipeline, enabling the creation of images from tabular data. A mapping between original features and the generated images is established, and post hoc interpretability methods are employed to identify crucial areas of these images, enhancing interpretability for predictive tasks. An extensive evaluation of the tabular-to-image generation approach proposed on 12 low-dimensional and mixed-type datasets, including binary and multi-class classification scenarios. In particular, our method outperformed all traditional ML models trained on tabular data in five out of twelve datasets when using images generated with LM-IGTD and CNN. In the remaining datasets, LM-IGTD images and CNN consistently surpassed three out of four traditional ML models, achieving similar results to the fourth model.

This contribution presents the recent research developments within the Cosmic Ray Extremely Distributed Observatory (CREDO) in the search for resolution of various scientific puzzles, ranging from fundamental physical questions to applications like the determination of earthquake precursors. The state-of-the art theoretical, numerical and computational aspects of these phenomena are addressed, as well as recent experimental developments for detection., Comment: 9 pages, 7 figures. Based on the contribution to the XVIII Mexican Workshop on Particles and Fields in Puebla, Mexico, November 2022. M\'exico

This report presents results of a 50-state policy survey conducted by the National Center for Children in Poverty, Georgetown University McCourt School of Public Policy Center for Children and Families, and Johnson Policy Consulting. The survey asked state Medicaid agency leaders about Medicaid policies related to screenings and services designed to identify, prevent, and treat infant-early childhood mental health problems. The results and recommendations presented in this report can help mental health and early childhood leaders take stock of current Medicaid policies and their potential to support infant-early childhood mental health. [This report was co-produced with Georgetown University McCourt School of Public Policy Center for Children and Families and Johnson Policy Consulting.]

Novel materials capable of storing hydrogen or/and methane at high gravimetric and volumetric densities are required for hydrogen vehicles to be widely employed as a clean alternative to fossil-based vehicles. Metal-Organic Frameworks (MOFs) are considered as promising candidates to achieve the Department Of Energy (DOE) targets for both, hydrogen and methane storage. Using Grand Canonical Monte Carlo (GCMC) simulations, the hydrogen and methane gravimetric and volumetric storage capacities of two recently synthesized Al-nia MOFs have been studied. Their storage capacities have been compared with the storage capacities of other Al-based MOFs and classical and well-known MOFs, such as IRMOF-5. The two novel Al-nia MOFs have shown high hydrogen and methane gravimetric and volumetric storage capacities at room temperature and moderate pressures, 25-35 MPa, comparable or higher than the storage capacities of classical and Al-based MOFs., Comment: 25 pages

This study aims to assess the composition of scattered particles generated in proton therapy for tumours situated proximal to titanium dental implants. The investigation involves decomposing the mixed field and recording Linear Energy Transfer (LET) spectra to quantify the influence of metallic dental inserts located behind the tumour. A conformal proton beam was used to deliver the treatment plan to an anthropomorphic head phantom with two types of implants (Ti and plastic) inserted in the target volume. The stray radiation resulting during the irradiation was detected by a hybrid semiconductor pixel detector MiniPIX Timepix3 that was placed distal to the Spread-out Bragg peak. Visualization and field decomposition of stray radiation were generated using algorithms trained in particle recognition based on artificial intelligence convolution neural networks (AI CNN). Spectral sensitive aspects of the scattered radiation were collected using two angular positions of the detector relative to the beam direction: 0 and 60{\deg}. Using AI CNN, 3 classes of particles were identified: protons, electrons & photons, ions & fast neutrons. Placing a Ti implant in the beam's path resulted in predominantly electrons and photons, contributing 52.2%, whereas for plastic implants, the contribution was 65.4%. Scattered protons comprised 45.5% and 31.9% with and without Ti inserts, respectively. The LET spectra was derived for each group of particles, with values ranging from 0.01 to 7.5 keV{\mu}m-1 for Ti/plastic implants. The low-LET component was primarily composed of electrons and photons, while the high-LET component corresponded to protons and ions. This method, complemented by directional maps, holds potential for evaluating and validating treatment plans involving stray radiation near organs at risk, offering precise discrimination of the mixt field, enhancing in this way the LET calculation., Comment: 26 pages, 6 figures, 1 table

Ray tracing has long been the holy grail of real time rendering. This technique, commonly used for photo realism, simulates the physical behavior of light, at the cost of being computationally heavy. With the introduction of Nvidia RTX graphic card family, which provides hardware support for ray tracing, this technique started to look like a reality for real time. However, the same problems that afflicted the usage of this technique remain, and even with specialized hardware it is still extremely expensive. To account for these drawbacks, researchers and developers pair this technique with rasterization and denoising. This results in a hybrid system that tries to join the best of both worlds, having both photo realistic quality and real time performance. In this work we intend on further exploring hybrid render systems, offering a review of the state of the art with a special focus on real time ray tracing and our own hybrid implementation with photo realistic quality and real time performance (>30 fps), implemented using the Vulkan API. In this project, we highlight the detailed analysis of the impacts of History Rectification (Variance Color Clamping) on the temporal filter component of the denoising system and how to overcome the introduced artifacts. Additionally, we also highlight the analysis of the introduction of a separable blur on the spatial filter and the introduction of Reinhard Tone Mapping prior to denoising, consequently improving this procedure.

High-quality early care and education (ECE) provides a developmentally supportive environment for children in foster care that can help address early adversities, but recent studies have shown low levels of ECE participation among these children (Klein et al., 2016; Lee, 2020). To address this important issue, the Arkansas Office of Early Childhood (OEC) is collaborating with SRI International, the National Center for Children in Poverty, and the University of Arkansas for Medical Sciences. The partnership team is focused on learning about the supply, quality, and stability of ECE settings for children in foster care, as well as the facilitators and barriers to children in foster care accessing high-quality ECE. This brief presents key findings from focus groups and interviews with resource parents (that is, foster parents), ECE center-based program directors, and ECE home-based providers about their experiences caring for children ages birth through 5 in foster care. Key findings from this report include the following: (1) Working parents report that they cannot accept foster child placements if they lack child care and that children benefit from the developmental supports of high-quality ECE; (2) Resource parents struggle to find child care on their own, with many relying on informal networks of support (e.g., social media, faith-based communities) to find child care; (3) Even when a child can be enrolled in a quality program, their ECE placement is often disrupted during transitions (e.g., reunification); (4) Resource parents and ECE providers report challenges related to using and accepting child care vouchers (e.g., delayed voucher payments); and (5) ECE providers recognize that providing care to children in foster care requires deep commitment and specific skills, and they want specialized training and support to do this. We provide suggestions for how these findings can inform strategies to increase the participation of children in foster care in high-quality ECE. [This paper was created with the Arkansas Office of Early Childhood and the University of Arkansas for Medical Sciences.]

The hybrid architecture of the Timepix (TPX) family of detectors enables the use of different semiconductor sensors, most commonly silicon (Si), as well as high-density materials such as Cadmium Telluride (CdTe) or Gallium Arsenide (GaAs). For this purpose, we explore the potential of a silicon carbide (SiC) sensor bump-bonded on a Timepix3 detector as a radiation imaging and particle tracking detector. SiC stands as a radiation-hard material also with the ability to operate at elevated temperatures up to several hundreds of degrees Celsius. As a result, this sensor material is more suitable for radiation harsh environments compared to conventional e.g., Si sensors. In this work, we evaluate the response for precise radiation spectrometry and high-resolution particle tracking of newly developed SiC Timepix3 detector which is built and operated as a compact radiation camera MiniPIX-Timepix3 with integrated readout electronics. Calibration measurements were conducted with mono-energetic proton beams with energies of 13, 22, and 31 MeV at the U-120M cyclotron at the Nuclear Physics Institute Czech Academy of Science (NPI CAS), Prague, as well as 100 and 226 MeV at the Proton Therapy Center Czech (PTC) in Prague. High-resolution pattern recognition analysis and single-particle spectral tracking are used for detailed inspection and understanding of the sensor response. Results include distributions of deposited energy and linear energy transfer (LET) spectra. The spatial uniformity of the pixelated detector response is examined in terms of homogeneously distributed deposited energy., Comment: 9 pages, proceedings iWoRiD

Hybrid semiconductor pixelated detectors from the Timepix family are advanced detectors for online particle tracking, offering energy measurement and precise time stamping capabilities for particles of various types and energies. This inherent capability makes them highly suitable for various applications, including imaging, medical fields such as radiotherapy and particle therapy, space-based applications aboard satellites and the International Space Station, and industrial applications. The data generated by these detectors is complex, necessitating the development and deployment of various analytical techniques to extract essential information. For this purpose, and to aid the Timepix user community, it was designed and developed the "Data Processing Engine" (DPE) as an advanced tool for data processing designed explicitly for Timepix detectors. The functionality of the DPE is structured into three distinct processing levels: i) Pre-processing: This phase involves clusterization and the application of necessary calibrations and corrections. ii) Processing: This stage includes particle classification, employing machine learning algorithms, and the recognition of radiation fields. iii) Post-processing: Involves various analyses, such as directional analysis, coincidence analysis, frame analysis, Compton directional analysis, and the generation of physics products, are performed. The core of the DPE is supported by an extensive experimental database containing calibrations and referential radiation fields of typical environments, including protons, ions, electrons, gamma rays and X-rays, as well as thermal and fast neutrons. To enhance accessibility, the DPE is implemented into various user interface platforms such as a command-line tool, an application programming interface, and as a graphical user interface in the form of a web portal., Comment: 9 pages, proceedings IWORID

Based on case studies in three states (CO, RI, and TX), this brief examines promising strategies to address the developmental and mental health needs of infants and toddlers involved in Child Welfare (CW). Due to family adversities, trauma, maltreatment, and separation from primary caregivers, these infants and toddlers are at substantial risk of poor social-emotional, behavioral, and learning outcomes. While many systems should be engaged in efforts to promote the well-being of these infants and toddlers, this brief focuses primarily on the roles of state and local CW and Part C Early Intervention (EI) agencies. Additional support from other sectors and settings (e.g., mental health, home visiting) are highlighted in the context of efforts by CW and EI agencies to help connect children and families to programs that meet their needs. The recommendations at the end of this report point to ways that strengthened policies and investments could help ensure wide use of strategies that promote the well-being and healthy development of infants and toddlers experiencing early adversities. [This work was prepared with the assistance of True North Group.]