RAND researchers assessed the quality and patient safety review processes for care delivered in military treatment facilities (MTFs) and via operational clinical services (OCSs). MTFs are fixed or permanent medical facilities. OCSs are often provided in austere or operational environments that can be temporary, mobile, or permanent. OCS settings vary widely in their infrastructure and capabilities depending on the operational needs, resources, and location. The authors conducted an assessment of seven quality and patient safety review processes: credentialing and privileging; quality assurance (QA), standard of care (SOC), and incident review; health care provider accountability; clinical quality metrics transparency; eliminating variation in clinical quality metrics; applying clinical quality management (CQM) to operational settings; and CQM organizational roles and responsibilities. They developed and deployed an internal assessment in which representatives from five U.S Department of Defense (DoD) organizations (the Assistant Secretary of Defense for Health Affairs; the Director of the Defense Health Agency [DHA]; and the Surgeons General of the Army, Navy, and Air Force) reported the ways in which they ensure that service members receive high-quality, safe care. The authors also conducted qualitative interviews with 216 personnel across 19 MTFs and OCS settings who had a role in either overseeing CQM processes or providing care. Findings were used to identify potential opportunities for improvement. Recommendations included updating lists of active OCS settings, clarifying quality and patient safety requirements, and addressing institutional knowledge loss.

This study aimed to examine methods for improving global professional certifications to achieve the ultimate goals of emergency management, such as reducing human casualties, economic damages, and psychological impacts.

Accurate behavioral health workforce estimates are essential for workforce planning, shortage designation, and policy development. However, workforce reports often rely on license counts rather than unique providers, which can inflate workforce estimates when clinicians hold multiple licenses. This study examined the prevalence and geographic distribution of multi-licensure among Nevada behavioral health providers and assessed its impact on workforce estimates. A cross-sectional analysis was conducted using administrative licensure data from Nevada licensing boards for Marriage and Family Therapists (MFTs), Clinical Professional Counselors (CPCs), Alcohol and Drug Counselors (ADCs), and Problem Gambling Counselors (PGCs). Active licenses through December 2025 were linked at the individual level to identify unique providers and patterns of multi-licensure. Descriptive statistics summarized licensure combinations, while chi-square tests and logistic regression examined geographic differences by county type. Among 3259 unique providers, 382 (11.7%) held two or more licenses. The most common multi-licensure combinations were MFT/ADC (n = 189) and CPC/ADC (n = 143). Providers collectively held 3660 licenses, meaning license counts alone would overestimate the workforce by approximately 12.3%. In this Nevada methodological demonstration, summing records across four overlapping credentials produced a higher estimate than linking records at the individual level. States using licensing data for workforce surveillance should deduplicate records across boards and distinguish the number of credentials from the number and clinical capacity of unique practitioners. Multi-state replication across a broader set of behavioral health professions is needed.

Cybersecurity has become a critical determinant of patient safety, business continuity, and organizational resilience in health care. Health care organizations are increasingly targeted by ransomware, data theft, and related attacks that disrupt clinical operations, threaten patient safety, delay care, and compromise sensitive information. Although often viewed as technical failures, many incidents originate in routine human behaviors, including phishing responses, credential misuse, unsafe downloads, and inappropriate use of personal devices or applications. This review focuses on clinician-level actions that can reduce both personal and organizational risk, including strong and unique passwords, multifactor authentication, phishing recognition and reporting, timely software updates, secure network use, careful management of personal devices and apps, and avoidance of risky removable media or untrusted downloads. It also emphasizes preparedness for extended network downtime, including familiarity with business continuity processes for documentation, ordering, communication, and care coordination when core digital systems are unavailable.

IoT deployments handle credential hygiene reactively: cloned, replayed, or stale credentials are typically discovered only after misuse, and revocation state is often propagated through centralized lists whose integrity cannot be independently verified. This article introduces the Yang-Baxter IoT Consistency Gateway (YB-IoT-CG), a Zero-Trust admission-control framework that pushes an algebraic layer of credential screening to the edge and anchors security evidence on a modeled permissioned-ledger architecture. YB-IoT-CG operates after conventional secret-based authentication and Yang-Baxter equality is used as an execution-consistency invariant rather than as proof of device identity or message authenticity. Each authenticated message is hashed into a digest and reduced to an algebraic transcript that is verified over two Yang-Baxter traversal paths. Beyond equality checking, chain-proximity metrics inspired by time-memory trade-off analysis, nonce and timestamp freshness heuristics, and contextual risk scoring identify credentials that should be proactively challenged or revoked before telemetry is admitted. The proactive risk component is deterministic and policy-based rather than a learned predictive model. Decisions are batched into Merkle trees whose roots are represented through a permissioned-ledger model, credential revocation is propagated through a modeled on-chain registry, and device identities are bound to W3C Decentralized Identifiers (DIDs) with verifiable credentials. This design provides tamper-evident audit support while keeping ledger interaction off the packet decision path. Validation is based on a controlled Python 3.13.7 packet-level simulation and a parameterized ledger model, not on a physical IoT or live Hyperledger Fabric deployment. Across 60 seeded simulation runs, the complete post-authentication screening pipeline obtained a median incremental decision time of 7.8 μs, 99.4% aggregate decision accuracy for the modeled attack classes, a 0.43% false rejection rate, and a 31.4 ms amortized ledger service-time equivalent per decision for a batch size of 64. The 99.4% value is a property of the composed freshness/context/registry/YB policy and is not a YB-only detection rate; the YB-specific positive guarantee is limited to the isolated fault class of Proposition 7. These results provide simulation-based evidence supporting a lightweight, explainable, auditable, and proactive approach to credential hygiene at the edge.

Drones have become a significant threat in both modern warfare and civilian environments, presenting unprecedented security challenges. While hard kill (physical destruction) defense methods exist to counter threat drones, they remain prohibitively expensive and often result in collateral damage. This study focuses on software-based peaceful neutralization as an anti-drone countermeasure, with particular emphasis on optimizing Wi-Fi credential recovery by leveraging exploitable vulnerabilities in threat drone wireless communications. The methodology included extensive performance evaluation experiments to assess vulnerabilities in drone Wi-Fi networks through GPU-accelerated credential recovery. Across the tested GPU platforms, the proposed implementation achieved an average throughput improvement of 8.78% over the Hashcat baseline, with platform-specific gains of 5.0% on H100, 8.77% on A100, 6.53% on RTX PRO 6000, and 14.8% on RTX 4060. The proposed approach represents a preliminary step toward a cost-effective and damage-minimizing alternative, applicable to Wi-Fi-dependent drone platforms under specific operational conditions. Our experimental results suggest the potential feasibility of credential-recovery-based approaches as an enabling step toward software-based neutralization of Wi-Fi-dependent drone systems. This paper contributes to the emerging field of counter-unmanned aerial systems (C-UAS) by establishing a methodology for credential recovery against Wi-Fi-based drone communications, which may contribute to reducing reliance on physical intervention in applicable scenarios.

This study introduces a unified evaluation framework for device-level intrusion detection using power side-channel fingerprints under an open-set threat model. We target post-enrollment device substitution: an adversary replaces a legitimate Commercial Off-The-Shelf (COTS) node with a counterfeit of the same model and firmware after enrollment, during deployment or maintenance, making the substitution invisible to credential-based authentication. To address this scenario, we evaluate seven ESP32-WROOM-32 and seven Arduino Uno R3 devices across four sessions spanning 45 days. Each platform group is drawn from a single manufacturing batch so that measured differences reflect within-batch variation; results are correspondingly established at this scale and for this sourcing. Unlike most prior studies that evaluate fingerprinting under isolated assumptions, this study treats intrusion detection as a system-level problem that requires the joint consideration of temporal stability, open-set recognition, and feature representation. We conduct a two-tier evaluation. Tier 1 characterizes device uniqueness and temporal stability using handcrafted statistical features and neural embeddings trained via triplet + Additive-Margin Softmax (AM-Softmax) loss, analyzed via separation ratios, d' scores, F1-scores, and statistical power. Tier 2 applies embeddings to an open-set intrusion-detection protocol using percentile-based thresholding. This analysis reveals that temporal viability is strongly influenced by feature representation under the evaluated conditions. Over 45 days, under an identical Leave-One-Run-Out protocol and scoring rule, neural embeddings achieve a 93.9% true positive rate at a 9.9% false acceptance rate, whereas the same rule applied to handcrafted statistical features yields 66.4% and 35.8%. When each device identity is withheld from training altogether, embeddings hold a 26.0% false acceptance rate against 39.0% for statistical features. Platform comparison shows that ESP32 achieves a 1.80× higher separation ratio than Arduino (3.06 vs. 1.70), with architecture-dependent discriminability. Statistical power analysis yields 89.1% power at d=0.774. These results identify representation-level robustness as a key requirement for practical power-based intrusion detection, while longer-term validation remains an important direction for future work.

Oncogenic RAS pathway mutations are associated with therapeutic resistance in acute myeloid leukemia, and identification of therapeutic vulnerabilities has been hindered by a lack of clinically relevant models and tractable ex vivo platforms. We utilize a bone marrow endothelial cell co-culture system to perform CRISPR screens on wild-type hematopoietic cells and isogenic leukemias with and without mutant Nras. We credentialed Elovl1, a very long chain fatty acid elongase, as a dependency in RAS pathway mutant leukemia using genetic and pharmacologic approaches. Metabolic and genetic studies in primary leukemias revealed that the fitness defect from Elovl1 loss reflects a mutant-specific dependency on de novo sphingolipid biosynthesis, specifically sphingomyelin production, as Sgms1 deletion phenocopies Elovl1 loss. Sphingomyelin-mediated generation of lipid rafts, key scaffolds for multiple signaling pathways, is essential to the survival of Nras-mutant AML cells. Our work leverages a new leukemia model to identify a targetable dependency in this treatment-refractory leukemia.

Since the General Dental Council ceased registering additional qualifications awarded after December 2007, dentistry in the UK has lacked a formal, national mechanism for recognising practitioners whose capabilities sit between those of the general registrant and the specialist. While NHS commissioning frameworks describe this middle tier as Level 2 complexity care, its application has remained local and inconsistent, potentially leaving patients and referring practitioners reliant on unverified claims of enhanced skills, often shaped by marketing. This article describes the College of General Dentistry's response. The Certified Practitioner scheme is a national credentialling programme that independently assesses a practitioner's knowledge, skills and clinical experience against standards agreed with the relevant professional bodies. The article sets out the rationale for credentialling as well as its relationship to the College's Career Pathways framework and to the specialist lists. The staged assessment process, which encompasses evidence of training, a verified logbook of cases and a peer-reviewed portfolio discussion, leads to five years of certification and entry on a published national register. Written from the author's perspective as a facilitator of the credentialling workstreams, it reflects on the scheme's development, the launch of the first credential in endodontics, and the fields of practice that will follow.

Cardiac point-of-care ultrasound may serve as a bedside screening tool for the early identification of left ventricular systolic dysfunction in children, but paediatric data remain limited in clinical practice. In a retrospective cohort study of children with multisystem inflammatory syndrome in children undergoing cardiac point-of-care ultrasound at presentation, qualitative assessments of left ventricular systolic function by credentialed paediatric emergency medicine physicians were obtained and demonstrated high sensitivity for detecting dysfunction across the spectrum of left ventricular systolic failure.