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Layered 2D halide perovskites are chemically synthesized realizations of quantum well stacks with giant exciton oscillator strengths, tunable emission spectra and very large exciton binding energies. While these features render 2D halide perovskites a promising platform for room-temperature polaritonics, bosonic condensation and polariton lasing in 2D perovskites have so far remained elusive at ambient conditions. Here, we demonstrate room-temperature cavity exciton-polariton condensation in mechanically exfoliated crystals of the 2D Ruddlesden-Popper iodide perovskite $(BA)_{2}(MA)_{2}Pb_{3}I_{10}$ in an open optical microcavity. We observe a polariton condensation threshold of $P_{th}=6.76 fJ$ per pulse and detect a strong non-linear response. Interferometric measurements confirm the spontaneous emergence of spatial coherence across the condensate with an associated first-order autocorrelation reaching $g^{(1)}\approx 0.6$. Our results lay the foundation for a new class of room-temperature polariton lasers based on 2D halide perovskites with great potential for hetero-integration with other van-der-Waals materials and combination with photonic crystals or waveguides., Comment: 21 pages, 8 figures

The purpose of this document is to provide techniques to assist Department of Defense (DoD) acquisition personnel with the integration of learning technology standards into their Information Technology acquisition processes. This document supports Department of Defense Instruction (DoDI) 1322.26 and the updated DoDI 1322.26 references. This document includes recommendations for how to implement the standards and specifications included in DoDI 1322.26. These standards provide the technical underpinnings of the Total Learning Architecture (TLA), which enables personalized, data-driven, and technology-enabled lifelong learning across the DoD. The TLA is sponsored by the ADL Initiative and was developed in collaboration with stakeholders from across the defense community, professional standards organizations, industry, and academia. It includes a set of technical specifications, standards, and policy guidance that define a uniform approach for integrating current and emerging learning technologies into a learning services ecosystem. Within this ecosystem, multiple services, and learning opportunities (of various modalities and points of delivery) can be managed in an integrated, interoperable 'plug and play' environment.

Spine biomechanics is at a transformation with the advent and integration of machine learning and computer vision technologies. These novel techniques facilitate the estimation of 3D body shapes, anthropometrics, and kinematics from as simple as a single-camera image, making them more accessible and practical for a diverse range of applications. This study introduces a framework that merges these methodologies with traditional musculoskeletal modeling, enabling comprehensive analysis of spinal biomechanics during complex activities from a single camera. Additionally, we aim to evaluate their performance and limitations in spine biomechanics applications. The real-world applications explored in this study include assessment in workplace lifting, evaluation of whiplash injuries in car accidents, and biomechanical analysis in professional sports. Our results demonstrate potential and limitations of various algorithms in estimating body shape, kinematics, and conducting in-field biomechanical analyses. In industrial settings, the potential to utilize these new technologies for biomechanical risk assessments offers a pathway for preventive measures against back injuries. In sports activities, the proposed framework provides new opportunities for performance optimization, injury prevention, and rehabilitation. The application in forensic domain further underscores the wide-reaching implications of this technology. While certain limitations were identified, particularly in accuracy of predictions, complex interactions, and external load estimation, this study demonstrates their potential for advancement in spine biomechanics, heralding an optimistic future in both research and practical applications.

The founding goal of using standards within acquisition of distributed learning content and technology is to reduce cost in both current and future acquisitions and collaborative efforts across organizations. This document explores existing successful acquisitions and supplies that language as well as successful ways to implement best practices of standards and to identify mature standards (as a part of the ADL research portfolio, the Total Learning Architecture (TLA)). It provides a reference both by technical standard, the standards associated technology, and the standards associated use cases as tied to that technology. This document is intended to updated periodically.

A federated Enterprise Learner Record Repository (ELRR) provides the ability to look across many distributed learner records as if they were from a single source and enables the sharing of local and global learner data across the DoD. This learner data will be pulled from authoritative sources for publishing, customizing, and harmonizing individual profiles, performance records, and training records. This document presents the requirements needed to advance the ELRR towards its Initial Operational Capability (IOC).

The human capital supply chain is a complex network of systems with inherent challenges to accommodating Total Learning Architecture (TLA) operability. This document covers the objective end-state for Department of Defense (DoD) learning organizations migrating to TLA compliant data and microservices. This document is organized into sections that describe each data pillar and the systems/interfaces used to manage this data. It introduces the overall requirements for a TLA compliant network of hardware and software resources, data structures and other services maintained within a logical cybersecurity boundary. These boundaries can be organizational (e.g., school, command, business area) or specific to the myriad of different platforms used to deliver training and education experiences in the commercial marketplace (e.g., LMS, LXP, Simulation System). These requirements provide a blueprint for migrating existing Learning and Development tools to the future DoD TLA learning ecosystem. This document is issued as a 2021 update to a 2019 version (ED608976).

The Enterprise Learner Record Repository (ELRR) Prototype report details the project design and development activities associated with building the prototype ELRR capability. The ELRR capability is designed to be a a repository composed of local learner profiles that contain data from a diverse set of records, and can be used to follow a service member or DoD civilian throughout their career to optimize their career development. Specifically, this report details lessons learned, best practices, standard operating procedures, and potential future directions.

The Enterprise Learner Record Repository (ELRR) System Architecture Report (SAR) outlines the ELRR solution architecture by describing the specification and deployment of hardware and software, interfaces, and port/protocol usage. This report focuses on the standards, specifications, services, and systems necessary to enable individual DoD organizations to contribute their local, authoritative learning records to an enterprise aggregation of these local, authoritative training records, using a growing number of supporting data services (e.g., course information, identity management, competency data) to federate a learner's portfolio of records into an ELRR capability. The intended audiences for this document are developers or engineers who are familiar with TLA standards and core cloud computing principles.

The scope of the ELRR Prototype Systems Integration Plan (SIP) is to provide technical guidance for integrating ELRR Prototype with ADL TLA sandbox components, such as the Authoritative Learner Record Store (LRS), Competency and Skills System (CaSS), and Enterprise Course Catalog (ECC), along with a recommended resource mixture to conduct the integration activities. The intended audiences for this document are developers or engineers who are familiar with TLA standards and core cloud computing principles.

The dynamic and high-stakes nature of education and training requires reliance on evidence-based practices and policies to make decisions about technology adoption and implementation. In the report, "Science of Learning and Readiness (SoLaR) Recommendation Report: Science of Learning Practices for Distributed Online Environments" (ED612458) provided 16 recommendations for supporting distributed learning along with a learning science evaluation checklist. While that report provided all the tools needed for expert evaluation of learning organizations and courses, it did not provide a practical example of how the checklist can be used. It also did not provide evidence of the type of data that can be obtained in the form of real use cases. This current report provides this evidence by successfully evaluating two DoD training and educational organizations using the proposed Learning Science Checklist. It also provides a summary of how the checklist was implemented and the results of the use case evaluations. This work was conducted to support the greater impact of the learning sciences on readiness. This evaluation provided a concrete operationalization of the review process needed to assess the previous recommendations. The two use case evaluations covered in this report are a test of the recommendation's ability to provide successful application within existing DoD-relevant training and educational organizations. This use case report serves as an example of how the Learning Science Evaluation Checklist could be applied to provide useful and actionable recommendations for improving these recommendations. [This report was produced by the Advanced Distributed Learning Partnership Laboratory at Arizona State University.]

The Enterprise Learner Record Repository (ELRR) is one of three Enterprise Digital Learning Modernization (EDLM) lines of effort supported by the ADL Initiative. Today, learner records for Department of Defense (DoD) personnel are stored in disparate locations, along with inconsistent data formats, which complicates the transport, management, and governance of the learner records across and within DoD organizations. The goal of the ELRR is to aggregate learner records across multiple systems and organizations to provide a centralized location for DoD personnel to view and interact with their learning and development data. The aim of this document is to provide: a summary overview of the ELRR Prototype's initial implementation; guidance on the required interfaces between the ELRR Prototype and the ADL Total Learning Architecture (TLA) reference implementation in an Amazon Web Services (AWS) sandbox environment; a corresponding integration approach; and a stakeholder engagement strategy to support a reference implementation of the ELRR Prototype.

Bandgap engineering and quantum confinement in semiconductor heterostructures provide the means to fine-tune material response to electromagnetic fields and light in a wide range of the spectrum. Nonetheless, forming semiconductor heterostructures on lattice-mismatched substrates has been a challenge for several decades, leading to restrictions for device integration and the lack of efficient devices in important wavelength bands. Here, we show that the van der Waals epitaxy of two-dimensional (2D) GaSe and InSe heterostructures occur on substrates with substantially different lattice parameters, namely silicon and sapphire. The GaSe/InSe heterostructures were applied in the growth of quantum wells and superlattices presenting photoluminescence and absorption related to interband transitions. Moreover, we demonstrate a self-powered photodetector based on this heterostructure on Si that works in the visible-NIR wavelength range. Fabricated at wafer-scale, these results pave the way for an easy integration of optoelectronics based on these layered 2D materials in current Si technology., Comment: 16 Pages, 5 figures. Supplementary Information included in the end (+10 pages, +10 Figures, + 2 Tables). Partially presented at 21st ICMBE - September 2021

The study of two-dimensional (2D) van der Waals materials has been an active field of research in the development of new optoelectronics and photonic applications over the last decade. Organic-inorganic layered perovskites are currently some of the most promising 2D van der Waals materials, due to their exceptional optical brightness and enhanced excitonic effects. However, low crystal quality and spectral diffusion usually broaden the exciton linewidth, obscuring the fine structure of the exciton in conventional photoluminescence experiments. Here, we propose a mechanical approach for reducing the effect of spectral diffusion by means of hBN-capping on layered perovskites with different thicknesses, revealing the exciton fine structure. We used a stochastic model to link the reduction of the spectral linewidth with the population of active charge fluctuation centres present in the organic spacer taking part in the dynamical Stark shift. Active fluctuation centres are reduced by a factor of 3.7 to 7.1 when we include hBN-capping according to our direct spectral measurements. This rate is in good agreement with the analysis of the overlap between the squared perovskite lattice and the hexagonal hBN lattice. Van der Waals forces between both lattices cause the partial clamping of the perovskite organic spacer molecules, and hence, the amplitude of the dynamical Stark shift characteristic of the spectral diffusion effect is reduced. Our work provides an easy and low-cost solution to the problem of accessing important fine-structure excitonic state information, along with an explanation of the important carrier dynamics present in the organic spacer that affect the quality of the optical emission.

Two-dimensional (2D) van der Waals nanomaterials have attracted considerable attention for potential use in photonic and optoelectronic applications in the nanoscale, due to their outstanding electrical and optical properties, differing from their bulk state. Currently, 2D perovskite belonging to this group of nanomaterials is widely studied for a wide range of optoelectronic applications. Thanks to their excitonic properties, 2D perovskites are also promising materials for photonics and nonlinear devices working at room temperature. Nevertheless, strong excitonic effects can reduce the photocurrent characteristics when using thinner perovskites phases. In this work, we present solid experimental evidence for the presence of single donor-acceptor pair optical transitions in 2D Lead Halide Perovskites, characterized by sub meV linewidths ($\simeq 120 \mu eV$) and long decay times (5-8 ns). Micro-photoluminescence evidence is supported by detailed Photoemission measurements, and a model simulation. The association of Phenethylammonium with Methylammonium cations, the latter molecule being only present in 2D Halide Perovskites with thicker phases $n \geq 2$, has been identified as the source of the donor-acceptor pair formation, corresponding to the displacement of lead atoms and their replacement by methylamonium. Our seminal study of discrete Donor-Acceptor Pair (DAP) sharp and bright optical transitions in 2D Lead Halide Perovskites opens new routes to implement DAP as the carrier sources for novel designs of optoelectronic devices with 2D perovskites, and will foster the development of future outstanding properties in non-linear quantum technologies.

In May of 2020, the Advanced Distributed Learning Initiative (ADL) and the Defense Acquisition University (DAU) partnered with USALearning/PowerTrain to create a practical application of ADL's 2019 TLA Reference Implementation. The purpose of this project was to recreate key components of the Reference Implementation with commercially-available, open source, and customized solutions to demonstrate the value of organizations choosing to adopt the architecture to improve their ability to track competency-based learning. [This report was created with USALearning and PowerTrain.]

Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of international data standards that combine to increase the granularity and fidelity of learner data. Reusable Competency Definitions (IEEE 1484.20.1 RCD) are used to describe the Knowledge, Skills, Abilities, and Other behaviors (KSAOs) that are required in the workplace (e.g., the operational environment). Learning Activity Metadata (IEEE P2881 Learning Activity Metadata) is used to describe the various learning resources an organization uses to train and educate its people. The Experience API (IEEE 9274.1 xAPI) is used to track and manage learner performance both inside and outside a learning activity. An Enterprise Learner Record, currently an IEEE study group, is used to track and manage each learner's level of competency within the organization. Together, this data enables a ledger of learner performance that ties all learning activities that a learner completes to competencies, credentials, and ultimately to the different career trajectories that a learner may pursue. The TLA data strategy includes linkages across the different standards listed above and collectively provide a data foundation for adaptive systems to build upon. This paper and discussion will walk viewers through the different data models that are being used to drive development of these standards.

The DoD's [Department of Defense's] Advanced Distributed Learning (ADL) Initiative is designing a framework of commercial standards, technical specifications, and business rules to enable plug and play interoperability of learning technologies. The Total Learning Architecture (TLA) framework will allow education and training products to interoperate with each other, with existing learning support systems, and with other DoD systems. The purpose of this report is to guide Command decisions toward a shared vision and end-state that benefits every warfighter individually and the entire DoD holistically. It describes and summarizes the research performed by the ADL Initiative in 2019 within the TLA research portfolio. It includes four appendices that detail the TLA's latest functional requirements, recommended draft standards, an initial architecture that conforms to the DoD Architectural Framework (DoDAF), and a Software System Design Document built around the 2019 TLA Reference Implementation. The target audience includes senior DoD leaders, educational institutions, and program managers of DoD training systems.

A capability maturity model provides a thorough understanding of where the organization is and, perhaps more importantly, where the organization needs to grow. The purpose of this report is to describe the development of the ADL Initiative Distributed Learning Capability Maturity Model (DL-CMM), illustrate its major components, and explain how it can be used to improve processes. [Contributing authors include: Brent Smith, Jerry Gordon, Bojana Andrejevic, and Mike Neeley.]

The Science of Learning and Readiness (SoLaR) project seeks to demonstrate to Defense and other Government stakeholders the "art of the possible" for high-quality distributed learning and to create a practical guide for how to infuse such qualities into the broader Department of Defense (DoD) distributed learning ecosystem. This report is the third in a series of three reports examining the state of the art for advancing the applications of distributed learning. It provides recommendations for setting up modern learning ecosystems that incorporate distributed learning techniques. The DoD can use these specific and actionable recommendations for enhancing its distributed/blended learning institutions (i.e., the overall system), courseware, and associated learning strategies/tactics. The recommendations are based on findings from the two previous reports. The first report, the State of the Art Report (ED612433), was a review of the state of the art for distributed learning environments that searched for best practices with evidence of supporting learning and improving learning organizations. The second report, the Exemplar Report (ED612459), was a review of exemplar learning organizations that have successfully grown their learning enterprise.

The Science of Learning and Readiness (SoLaR) project seeks to demonstrate to Defense and other Government stakeholders the "art of the possible" for high-quality distributed learning and to create a practical guide for how to infuse such qualities into the broader Department of Defense (DoD) distributed learning ecosystem. This report seeks to provide an understanding of a State-of-the-Art Learning Organization. The features of an exemplar learning organization at scale were identified based on a broad review of the literature. The summarized key findings include: (1) Principles of human learning from the learning sciences hold within learning at scale environments; (2) Human learning within these environments must be supported by technology; (3) The technology must provide data on the learning process to the organization; and (4) Learning organizations must use data to support both the learners in the form of learning, social, and academic guidance, and the members of the organization to provide training, support, and recognition. This report gathers real-world examples from exemplar organizations and provides an example of a growth path for an exemplar organization. Examples of exemplar practices in action were identified from interview data spanning academia, non-profit, and industry. From this data, the report describes important factors the organizations used to scale up, identifies generalizable principles, and highlights the characteristics that make each organization uniquely effective. The report concludes with an example of an ideal scaled-up process. This example provides a pathway based on best practices for learning organizations to scale up.

Technology is rapidly transforming how people learn and how training is provided. For example, in higher education, there are estimated to be nearly 6.7 million students enrolled in online education courses (National Center for Education Statistics Fast Facts, 2018). The dynamic and high-stakes nature of education and training software demands that evidence-based practices and policies are relied upon to make decisions about technology adoption and implementation. The purpose of the Science of Learning and Readiness project (SoLaR) is to identify these practices. This State-of-the-Art Report (SoAR) is the first project deliverable and summarizes evidence-based practices and implementation within public, private, and academic sectors. The SoAR also includes specific guidance on metrics-based, most effective, at scale, and blended learning strategies within institutional systems, courseware, and pedagogical methods. Methodologically, this report emerges from a broadly scoped review process comprising over 200 formal database searches. The search strategy was inclusive of academic, military, and industry resources. SoLaR-SoAR consists of a review of the current state of the art for distributed learning environments. To further understand perceived importance and implementation of these practices, learning organizations representing public, private, and academic sectors were surveyed. A consistent discrepancy was observed: respondents reported that actual implementation of best practices fell short (i.e., ratings of implementation were significantly lower than ratings of perceived importance). This pattern was most striking within military organizations. The survey sample was small and thus limited in generalizability. Nonetheless, the consistently high perceived importance of best practices in the public sector--particularly the military--suggests a readiness for a transition to advanced distributed learning methodologies. The report is structured for use by multiple types of end users. The main report provides a 22-page, high-level overview of findings of the current state of the art. This section can serve as a quick reference. The report's Appendixes provide a detailed summary of the empirical literature on state-of-the-art distributed learning ecosystems. These materials enable "deeper dives" into learning organization, technology, and human pedagogy topics. [This report was written with contributing authors, Nancy J. Cooke, Deborah Prewitt, Siyuan Li, Laurie A. Morgan, Yancy V. M. Paredes, Robert F. Siegle, and Ashley Clark.]