United States Army

A large amount of research in international relations has focused on how regime type affects the behavior of democracies regarding traditional, kinetic conflict. However, less is known regarding how democracies operate in cyberspace as it pertains to cyberaggression. Thus, this study examines the offensive strategies of democratic states that initiated state-sponsored cyberattacks against other states from 2005 through 2020. In examining the cyberattacks initiated by democracies during this period, we aim to better understand the motives behind democratically initiated cyberattacks, the regime types that are likely to be targeted in the attacks, and the types of cyberattacks that democracies are likely to deploy. In conducting this analysis, we find that democracies rarely attack other democratic states in cyberspace and democracies are likely to deploy more aggressive and hostile attacks when targeting authoritarian regimes. We attribute these findings to the effects democratic institutions have on state behavior in the cyber realm. These findings have important implications for considering how democratic institutions affect international relations and cybersecurity.

The recent surge in diverse 3D datasets spanning various scales and applications marks a significant advancement in the field. However, the comprehensive process of data acquisition, refinement, and annotation at a large scale poses a formidable challenge, particularly for individual researchers and small teams. To this end, we present a novel synthetic 3D point cloud generation framework that can produce detailed outdoor aerial photogrammetric 3D datasets with accurate ground truth annotations without the labor-intensive and time-consuming data collection/annotation processes. Our pipeline procedurally generates synthetic environments, mirroring real-world data collection and 3D reconstruction processes. A key feature of our framework is its ability to replicate consistent quality, noise patterns, and diversity similar to real-world datasets. This is achieved by adopting UAV flight patterns that resemble those used in real-world data collection processes (e.g., the cross-hatch flight pattern) across various synthetic terrains that are procedurally generated, thereby ensuring data consistency akin to real-world scenarios. Moreover, the generated datasets are enriched with precise semantic and instance annotations, eliminating the need for manual labeling. Our approach has led to the development and release of the Semantic Terrain Points Labeling—Synthetic 3D (STPLS3D) benchmark, an extensive outdoor 3D dataset encompassing over 16 km2, featuring up to 19 semantic labels. We also collected, reconstructed, and annotated four real-world datasets for validation purposes. Extensive experiments on these datasets demonstrate our synthetic datasets’ effectiveness, superior quality, and their value as a benchmark dataset for further point cloud research.

This work aims to develop a surveillance mission system using unmanned aerial vehicles (UAVs) or drones when Denial-of-Service (DoS) attacks are present to disrupt normal operations for mission systems. In particular, we introduce the concept of cyber deception using honey drones (HDs) to protect the mission system from DoS attacks. HDs exhibit fake vulnerabilities and employ stronger signal strengths to lure DoS attacks, unlike the legitimate drones called mission drones (MDs) deployed for mission execution. This research formulates an optimization problem to identify an optimal set of signal strengths of HDs and MDs to best prevent the system from DoS attacks while maximizing mission performance under the resource constraints of UAVs. To solve this optimization problem, we leverage deep reinforcement learning (DRL) to achieve these multiple objectives of the mission system concerning system security and performance. Particularly, for efficient and effective parallel processing in DRL, we utilize a DRL algorithm called the Asynchronous Advantage Actor-Critic (A3C) algorithm to model attack-defense interactions. We employ a physical engine-based simulation testbed to consider realistic scenarios and demonstrate valid findings from the realistic testbed. The extensive experiments proved that our HD-based approach could achieve up to a 32% increase in mission completion, a 20% reduction in energy consumption, and a 62% decrease in attack success rates compared to existing defense strategies.

Introduction Veno-venous extracorporeal membrane oxygenation (VV ECMO) improves hypoxemia and carbon dioxide clearance in patients with severe respiratory derangements. A greater understanding of the potential benefits of VV ECMO in trauma patients could lead to broader adoption. We hypothesize that trauma patients who receive VV ECMO have improved mortality outcomes when compared to those receiving conventional ventilator management given the rapid stabilization VV ECMO promotes. Methods We performed a single center, propensity score matched cohort study. All trauma patients from January 1, 2014, to October 30, 2023, who were placed on VV ECMO or who would have met institutional guidelines for VV ECMO but were managed with conventional ventilator strategies were matched 1:1. The primary outcome analysis was survival at hospital discharge. Significance was defined as p < 0.05. Results Eighty-one trauma VV ECMO patients and 128 patients who received conventional management met criteria for inclusion. After matching, VV ECMO and conventional treatment cohort characteristics were similar in age and MOI. Matched ISS, SI, lactate levels, and frequency of TBI were also similar. Finally, respiratory parameters including pre-intervention, pH, partial pressure of carbon dioxide (PaCO 2 ), lactate levels, and oxygen saturation were similar between matched groups. VV ECMO patients had higher survival rates at discharge when compared to the matched conventional treatment group (70% v 41%, p < 0.001). Corresponding hazard ratio for VV ECMO use was 0.31 (95%CI 0.18-0.52; p < 0.001). The odds ratio of mortality in matched trauma patients who receive VV ECMO versus conventional treatment was 0.29 (95%CI 0.14-0.58; p < 0.001). Conclusion VV ECMO may represent a safe, alternative treatment approach for appropriately screened trauma patients with acute respiratory failure, however further studies are warranted.

Special Operations Forces (SOF) soldiers are a small but unique population in the Army. Within Army Special Operations are the Special Forces, or Green Berets, as they are commonly known. Carefully selected and rigorously trained to prepare them for their unique roles, Green Berets are among the most intelligent, capable, competent, adaptable, and resilient people to ever don the uniform. However, due to the nature of their work, Green Berets and other SOF soldiers are also among those most likely to be exposed to inordinate amounts of stress, loss, dangerous situations, and potentially traumatizing events such as combat. Providing quality, evidence-based behavioral health services to these soldiers is and will continue to be critical to support the success of these soldiers both on and off the battlefield. Critical to providing good care, is having a basic understanding of the assessment and selection, training, and culture of SOF soldiers. This chapter provider background information on these aspects of working with Special Operations Forces, identifies challenges in the delivery of BH care to this population, and discusses the personal experiences of one provider in this role with a Special Forces Unit.

On 25–26 March 2023, the U.S. National Council on Radiation Protection and Measurements (NCRP) held its 2024 annual meeting in Bethesda, Maryland, USA. The NCRP dates from 1929, and this meeting celebrated the 60th anniversary of receiving a U.S. Congressional Charter. For this annual meeting the NCRP felt it was essential to provide a briefing about advanced and small modular nuclear reactors (SMRs). The Journal of Radiological Protection is delighted to publish the following synopsis of material presented at the U.S. NCRP meeting. This synopsis is divided into five sections. The first section provides an overview of the whole meeting together with summaries of two context setting overview papers. The following four sessions of this synopsis are specific to advanced and small modular nuclear power reactors. The meeting also included keynote presentations by three of NCRP annual award recipients. The meeting topical areas were Technology Overview and Critical Issues. The individual papers laid the groundwork to understanding reactor technologies, terminology, and the fundamental concepts and processes for electrical generation. The perspectives of the U.S. Environmental Protection Agency and states, through the Conference of Radiation Control Program Directors were provided. The papers included a discussion of diverse topics including potential emergency preparedness considerations, radiological survey requirements, an evaluation of the future of nuclear power, the economics of reactors (both large and small), and the critical issues identified by the recent National Academies of Sciences’ study on advanced reactors. The summary papers were developed to briefly document the major points and concepts presented during the oral papers presented at the 2024 NCRP Annual Meeting. The meeting heralded the dawn of a new era for commercial nuclear power.

Background Social integration (i.e., reciprocal interactions with peers and community members) is a notable challenge for many homeless-experienced adults with serious mental illness (SMI). In this study, we examine a range of housing services offered to homeless-experienced adults with SMI and identify the impacts of supportive services on participants’ social integration outcomes, with the goal of improving services in transitional and permanent housing settings for homeless-experienced adults with SMI. Methods Through semi-structured interviews with homeless-experienced adults with SMI (n = 30), we examine the impacts of housing and service settings on participants’ social integration. Participants received services in a variety of housing settings, including transitional housing with congregate/shared living (n = 10), transitional housing with individual quarters (n = 10), and permanent supportive housing (n = 10). Results Participants expressed caution in developing social relationships, as these could pose barriers to recovery goals (e.g., substance use recovery). For many, social integration was secondary to mental and physical health and/or housing stability goals. Individual quarters gave individuals a place of respite and a sense of control regarding when and with whom they socialized. Meeting recovery goals was strongly related to connecting to and receiving a range of supportive services; interviews suggest that proximity to services was critical for engagement in these resources. Conclusions Programs serving homeless experienced adults with SMI should seek to understand how individuals conceptualize social integration, and how social relationships can either support or hinder participants’ recovery journey.

Women are participating in military and athletic activities in the heat in increasing numbers, but potential sex differences in sequelae from exertional heat illness remain poorly understood. We tested the hypothesis that women suffering from exertional heat stroke (EHS) would have similar severity of organ damage biomarkers compared to men, as measured in a hospital setting. We studied women and men presenting with EHS to the emergency department at Fort Moore, GA. We measured creatinine (CR), creatine kinase (CK), alanine-transaminase (ALT), aspartate aminotransferase (AST), and estimated glomerular filtration rate (eGFR). Core temperature was also assessed by medical personnel. Biomarker data were obtained for 62 EHS cases (11 women). Men were significantly taller, and heavier, had larger BMI and body surface area (p<0.05 for all). Highest recorded body core temperature was not different between groups (women: 41.11°C (40.06,41.67); men: 41.11°C (40.28,41.72), p=0.57). Women had significantly lower peak CR (women: 1.39 (1.2,1.48) mgꞏdL ⁻¹ ; men: 1.75 (1.53,2.16) mgꞏdL ⁻¹ , p<0.01) and peak CK (women: 584 (268,2412) UꞏL ⁻¹ ; men: 2183 (724,5856) U•L ⁻¹ , p=0.02). Peak ALT and AST were not different between groups; during recovery time points, ALT and AST were either similar or lower in women. Women spent approximately half as much time in the hospital following admittance compared to men. Our findings suggest that women may be less susceptible to organ injury resulting from EHS. Further research is necessary to understand the pathophysiology underlying these differences and how biomarkers of end-organ damage severity can differ between women and men following EHS.

The purpose of this study was to determine the difference between estimated energy expenditure (EE) and self-reported dietary intake (EI), and factors associated with energy balance in deployed U.S. Army Special Operations Forces (SOF) Soldiers. Methods: Forty-six SOF Soldiers (age: 30.1 ± 3.5 yrs, body mass index: 27.7 ± 4.1 kg/m²) completed surveys on demographic data, mission activity characteristics, gastrointestinal issues, ration consumption, resilience, mood state, and dietary intake using a 127-question food frequency questionnaire at the end of a six-month deployment. EE was estimated using a SOF-specific prediction equation with a physical activity factor of 2.1. A paired t-test compared reported energy intake (EI) with estimated energy expenditure (EE). Pearson correlations identified significant variables associated with energy balance, which were then incorporated into a multiple linear regression model. The regression analysis included Profile of Mood States (POMS) anger and POMS depression as predictor variables to determine their influence on energy balance. Results: Reported mean EI was 2512 ± 1059 kcal·d⁻¹, while estimated mean EE was 5272 ± 525 kcal·d⁻¹. The mean energy imbalance was −2854 kcal/d (95% CI: −2655 to −3055, p < 0.001), with all participants in negative energy balance (range: −492 to −3813 kcal/d). POMS depression (r = 0.517, p < 0.01) and POMS anger (r = 0.363, p = 0.020) were associated with energy balance. The regression model was significant (R² = 0.23, F (2, 38) = 7.02, p < 0.01), with POMS depression significantly predicting energy balance (β = 50.76, p = 0.011). Conclusions: Deployed SOF Soldiers reported high EE and limited EI, which may negatively impact performance. Higher POMS depression scores were associated with lower energy deficits. Future studies should investigate the relationship between mood and energy balance, using direct measures of EI and EE.

Blast loads are extremely detrimental to structural elements of a building and can result in minor damage to complete failure of a building. Finite element analysis (FEA) is an effective tool to study the behavior of structural elements exposed to blast loading. The focus of this study was to evaluate the performance of three concrete material models available in LS-DYNA and compare the results to experimental results from blast loaded reinforced concrete (RC) panel supported on four sides (two-way bending). Concrete material models chosen for this study were Winfrith (MAT_84-85), Karagozian & Case (MAT_072R3), and Continuous Surface Cap Model (MAT_159). These are widely used in finite element modeling related to civil structures and can account for strain rate dependent properties. Each concrete material model was implemented with and without strain rate effects. The finite element model had concrete material as solid elements and steel reinforcement material as beam elements with simply supported boundary conditions. Results from two different blast loading methods are presented: (1) blast pulse load curve from experimental data (2) blast input by defining type, location, and amount of explosive in terms of TNT. The finite element models were evaluated by comparing fundamental period, peak displacement, and residual displacement to experimental results. In this study, the model using MAT_072R3 most closely matched experimental behavior in comparison to MAT_84-85 and MAT_159. Additional discussion is presented about: (1) single degree of freedom (SDOF) analysis, (2) comparison of numerical and experimental crack patterns, and (3) behavior of concrete material models accounting for compressive and tensile dynamic increase factors (DIFs).

Empirical research aimed at understanding public awareness and opinion on climate change has focused heavily on media coverage. Nearly all prior media studies focus on the United States and on a small number of elite news sources, notably the national newspapers of record. To widen the aperture, we take advantage of a database (MediaCloud) that covers a much larger array of print and word media: 168 million articles about all subjects, derived from 9000 unique U.S. news sources. Coverage of climate change from the “heartland” sources—dominated by state and local news outlets far from the headquarters of national newspapers of record—has risen 144% from 2011 until 2022. Elite news coverage, however, has risen at twice that pace (299%). Over time, the propensity to cover climate change has diverged. In 2011 there were 104 days when the heartland news sources had more coverage of climate change than elite news outlets such as The New York Times and The Wall Street Journal. By 2022 there were only 11 such days. That year, elite news outlets produced roughly three times the coverage of climate change as heartland news outlets. We also find some differences in the topics covered by these two categories of news sources. Such disparities in the intensity of attention to climate change, along with apparently more subtle variations in topical coverage, are variations that deserve future explanation. They are also a reminder that analysis of climate coverage should choose data sources with care since the narrative around what the public is learning about climate appears to vary substantially between heartland and elite new sources.