Defence Research and Development Canada

For weak signal detection with direction‐finding (DF), this article presents a new receiver design approach that combines our accumulatively increasing receiver sensitivity (AIRS) signal detection algorithm with the compressive‐sensing (CS)‐based DF‐array/algorithm. The former uses the concept of timeslot (TS)‐based signal threshold detection, whereas the latter employs a frequency‐independent array with randomly located elements, whose bandwidth (BW) largely determines the DF‐array BW. To estimate the direction of a signal, the AIRS algorithm generates the array steering vectors in each TS when the amplitude of any frequency bins exceeds the predetermined threshold of the TS. The aim of this paper is to demonstrate the ability of the new receiver to detect low probability of intercept radar signals with high DF accuracy, fine frequency resolution, and good time‐of‐arrival measurement resolution. To discriminate accurate emitter directions from many false estimations created by the DF‐array in very low signal‐to‐noise ratio environments, K‐means clustering was also applied. In a scenario, the frequency modulated signals from several 165‐mW X‐band radars were in the field of view of a 6‐element DF‐array. Simulation results show that the receiver can accurately estimate all the emitters' directions with root mean squared error of less than 1°, when the separation between the DF‐array and radars is about 100 km.

Background/Objectives: Military aviators can be exposed to extreme physiological stressors, including decompression stress, G-forces, as well as intermittent hypoxia and/or hyperoxia, which may contribute to neurobiological dysfunction/damage. This study aimed to investigate the levels of neurological biomarkers in military aviators to assess the potential risk of long-term brain injury and neurodegeneration. Methods: This cross-sectional study involved 48 Canadian Armed Forces (CAF) aviators and 48 non-aviator CAF controls. Plasma samples were analyzed for biomarkers of glial activation (GFAP), axonal damage (NF-L, pNF-H), oxidative stress (PRDX-6), and neurodegeneration (T-tau), along with S100b, NSE, and UCHL-1. The biomarker concentrations were quantified using multiplexed immunoassays. Results: The aviators exhibited significantly elevated levels of GFAP, NF-L, PRDX-6, and T-tau compared to the CAF controls (p < 0.001), indicating increased glial activation, axonal injury, and oxidative stress. Trends toward higher levels of S100b, NSE, and UCHL-1 were observed but were not statistically significant. The elevated biomarker levels suggest cumulative brain damage, raising concerns about potential long-term neurological impairments. Conclusions: Military aviators are at increased risk for neurobiological injury, including glial and axonal damage, oxidative stress, and early neurodegeneration. These findings emphasize the importance of proactive monitoring and further research to understand the long-term impacts of high-altitude flight on brain health and to develop strategies for mitigating cognitive decline and neurodegenerative risks in this population.

Military breachers are routinely exposed to repetitive low-level blast overpressure, placing them at elevated risk for long-term neurological sequelae. Mounting evidence suggests that circulating brain-reactive autoantibodies, generated following CNS injury, may serve as both biomarkers of cumulative damage and drivers of secondary neuroinflammation. In this study, we compared circulating autoantibody profiles in military breachers (n = 18) with extensive blast exposure against unexposed military controls (n = 19). Using high-sensitivity immunoassays, we quantified IgG and IgM autoantibodies targeting glial fibrillary acidic protein (GFAP), myelin basic protein (MBP), and pituitary (PIT) antigens. Breachers exhibited significantly elevated levels of anti-GFAP IgG (p < 0.001) and anti-PIT IgG (p < 0.001) compared to controls, while anti-MBP autoantibody levels remained unchanged. No significant differences were observed for any IgM autoantibody measurements. These patterns suggest that repetitive blast exposure induces a chronic, adaptive immune response rather than a short-lived acute phase. The elevated IgG autoantibodies highlight the vulnerability of astrocytes, myelin, and the hypothalamic–pituitary axis to ongoing immune-mediated injury following repeated blast insults, likely reflecting sustained blood–brain barrier disruption and neuroinflammatory processes. Our findings underscore the potential of CNS-targeted IgG autoantibodies as biomarkers of cumulative brain injury and immune dysregulation in blast-exposed populations. Further research is warranted to validate these markers in larger, more diverse cohorts, and to explore their utility in guiding interventions aimed at mitigating neuroinflammation, neuroendocrine dysfunction, and long-term neurodegenerative risks in military personnel and similarly exposed groups.

Background Healthcare facilities (HCF) are significant producers of healthcare waste (HCW), which includes hazardous materials such as sharps, pharmaceuticals, infectious substances, and chemical agents. Inadequate management of HCW presents serious risks to human health and the environment, especially in low- and middle-income countries, including Nigeria. Despite global guidelines for HCW management, challenges such as insufficient infrastructure, training, and adherence to regulations persist, particularly in regions like the Bwari Area Council, Abuja. This study evaluates healthcare workers' knowledge, attitudes, and practices (KAP) regarding healthcare waste management, compares practices between private and public healthcare facilities, and assesses adherence to national guidelines. Methods A cross-sectional study was conducted among 425 healthcare workers from ten healthcare facilities (five private, five public) in the Bwari Area Council. A random sampling technique was used, and a self-administered questionnaire assessed the participants' knowledge and practices related to healthcare waste management. Data were analyzed using SPSS version 28.0. Results Private healthcare workers demonstrated significantly better knowledge of waste segregation (92.5% vs. 84.9%, p = 0.012) and identifying vaccine containers as medical waste (80.8% vs. 70.8%, p = 0.016) compared to government workers. In practice, a significantly higher proportion of private workers refrained from flushing liquid medical waste into toilets (71% vs. 65%, p = 0.040). In contrast, government workers exhibited more positive attitudes towards waste management, with 99.3% agreeing that medical waste should be properly handled compared to 97.0% in private facilities (p = 0.016). Both private and government workers displayed high knowledge of color coding for medical waste (94.6% vs. 93.5%, p = 0.650), but only 15.1% correctly identified the green color code for general waste. Conclusion Private healthcare workers demonstrated better knowledge of waste segregation, while government workers showed more positive attitudes toward waste handling. Both sectors had similar practices, with gaps in the liquid waste disposal and general waste color coding. Targeted interventions and consistent training are needed to improve waste management practices across both facility types.

This study evaluated the ability of scores on the self-report Psychache Scale (PAS) to subtly screen pre-existing suicide risk factors in a military population. For 525 Canadian military personnel, PAS normative data were established, and scores demonstrated high internal consistency reliability. Based on associations with a rationally constructed measure of suicidality, PAS scores possessed large effect sizes, convergent validity. The PAS also had significant diagnostic accuracy for identifying previous multiple suicide intent communications and previous multiple suicide attempts, behavioral risk factors for subsequent suicide. Preliminary cut scores for identifying at risk military personnel are provided.

Carrier Aggregation (CA) is a promising technology in LTE and 5G networks that enhances the throughput of the users. However, since each User Equipment (UE) has to continuously monitor the activated Component Carriers (CCs) in CA, the UE energy consumption increases. To reduce the energy consumption while maximizing the throughput of UEs, we propose a dynamic and proactive CC management scheme for 5G, using a Q-Learning algorithm. To address our problem, we first model the corresponding Constrained Multi-agent Markov Decision Process (CMMDP) model and then utilize the Q-Learning algorithm to solve it. The time inter-arrival and the size of the next incoming bursts of data are proactively predicted and, along with the data in the buffer, are considered in the state space and the reward function of the machine learning model. Our proposed scheme is compared to three baseline schemes. In the first and second baseline algorithms, all CCs and only single CC are activated for each UE, respectively. For the last baseline algorithm, we simplify our Reinforcement Learning (RL) algorithm, in which the remaining data in the scheduling buffer of users is not considered and also the throughput and the number of activated CCs is balanced in the low traffic load. Simulation results reveal that our proposed Q-Learning algorithm outperforms the baselines. It achieves the same throughput as the all CC activation algorithm while reducing the UE power consumption by about 20%. These benefits are achieved by dynamically activating and deactivating CCs according to the UE traffic pattern.

Strategic foresight is the systematic exploration of emerging and future developments. Standardization is the process by which a common technical language is created and applied to new concepts and evolving technologies. Both strategic foresight and standardization address long-term technological change across industries, societies, and economies. And yet rarely are the two used in tandem to anticipate emerging standardization priorities that are critical to national interests. Against the backdrop of a global “technological race,” the foresight-to-standards process provides a novel approach to anticipate the nature of emerging technologies and their plausible influence on national, military, and economic interests, and to direct standardization efforts to align with strategic objectives. Our article provides an in-depth exploration of the Standards Council of Canada's experimentation with foresight between 2018 and 2021, informed by first-hand experience and observation. We describe and assess the SCC's use of strategic foresight in standardization, providing insights on capacity building, collaboration, leadership, decision making, and action.

People are often overconfident in their probabilistic judgments of future events or the state of their own knowledge. Some training methods have proven effective at reducing bias, but these usually involve intensive training sessions with experienced facilitators. This is not conducive to a scalable and domain‐general training program for improving calibration. In two experiments ( N 1 = 610, N 2 = 871), we examined the effectiveness of a performance feedback calibration training paradigm based on the Practical scoring rule, a modification of the logarithmic scoring rule designed to be more intuitive to facilitate learning. We examined this training regime in comparison to a control group and an outcome feedback group. Participants were tasked with selecting which of two world urban agglomerations had a higher population and to provide their confidence level. The outcome feedback group received information about the correctness of their choice on a trial‐by‐trial basis as well as a summary of their percent correct after each experimental block. The performance feedback group received this information plus the Practical score on a trial‐by‐trial basis and information about their overall over‐ or underconfidence at the end of each block. We also examined whether Actively Open‐Minded Thinking (AOMT) was predictive of calibration and its change across blocks. We found no improvement in calibration due to either training regime. Good calibration overall was predicted by AOMT, but not its change across blocks. The results shed light on the generalizability of other findings showing positive effects of performance training using the Practical scoring rule.

This paper provides the details of a novel systematic design methodology for two-way in-phase filtering Gysel splitter/combiner networks with high selectivity, which finds application in high power amplifier modules. It simultaneously realizes a filtering function and a two-way splitter/combiner function. The proposed five-port filtering device, based on the Gysel topology, is transformed into a ring of coupled resonators. A rigorous coupling matrix describing the network is used to synthesize the integrated filtering and combining functions. This general network can be implemented in any of the available filter technologies. In this paper, a few design examples are provided, and a six-pole prototype utilizing compact combline coaxial resonators is demonstrated. The proposed design provides an integrated dual function module, reducing component counts and system complexity. A design was fabricated and tested demonstrating good experimental results.

LAY SUMMARY This analysis of data from a large population-level survey uncovers a pressing issue related to mental health service use among Canadian Armed Forces members. Although many military members seek help for mental health issues, they often do not complete treatment. Data show that more than one-third of those who sought mental health care in the past year discontinued treatment within the same time frame. Alarmingly, only about 25% of these individuals indicated that they completed the recommended course of treatment. Many dropped out because they felt better, did not see results , or were uncomfortable with the treatment. Factors such as education level, marital status, rank, past trauma, and social support influenced this decision. This research is the first of its kind, providing a detailed look into the prevalence of and underlying reasons for discontinuing mental health treatment among Canadian military personnel. It highlights substantial treatment dropout that warrants the need to further explore barriers to and facilitators of treatment retention.

In an era defined by rapidly evolving and increasingly complex threats, hazards and emergencies, effective information management stands at the core of safeguarding community safety and public order in Canada. As the frequency of events requiring multi-agency response and/or having multi-jurisdictional implications increases, the need to share public safety information between organizations has never been greater. This chapter explores the role of information management (IM) interoperability standards in the Canadian public safety and security context. The chapter focuses on the role of standards in enhancing data and information management interoperability at unclassified tactical and operational levels, enabling collaboration amongst stakeholder organizations and, ultimately, assuring public safety and security for Canadians.

Advances in complex analytic functions and AI methods can improve efficiency and capabilities of police operations. This chapter describes an approach for a police service to expand its scientific skill sets resulting in bespoke technology to improve actionable decisions and officer resource efficiency. Ethical structures and modes of public transparency are described.

This chapter explores the complexities of data analytics as an critical capability for public safety and security organizations analytics can enable data-driven decision making, can enhance operational efficiency and effectiveness, can improve understanding of the operating environment, can facilitate risk management, can measure performance, can drive innovation and can support continuous improvement of business process and strategic outcomes. Analysis is the process of examining data, information and/or evidence to uncover patterns, trends or insights relevant to an organization’s reality. Analytics can be a critical tool used to better understand complex phenomena in an organization’s operational context. Analytics can take a systematic approach to break problems down into smaller pieces to gain a deeper understanding of the whole. Analysis can be a means to understand cause-and-effect relationships and for understanding underlying factors that affect an organization’s desired outcomes. Analysis can evaluate the effectiveness of tactics, strategies or interventions based on organizational outcomes and performance measures. Analysis can be a transformative process that turns raw data into meaningful and actionable knowledge, enabling decision makers to make informed choices. Certain aspects of analytics may have policy, regulatory, legislative constraints or implications, particularly around ethics, privacy and security of information.

Effective management of information stands as a cornerstone for maintaining public safety and security and upholding the principles of justice in Canada and beyond. Our work in this area has long been dedicated to exploring innovative approaches to information management, drawing from both theoretical approaches and from practical perspectives. In this chapter, we focus on specific enabling tools as part of a concept aimed at advancing capability maturity in this space. We will primarily focus our attention on information handling requirements and solutions particular to the Canadian public safety and security environment. We examine the concept of the “information mesh” as a solution that could satisfy expectations for how Canadian safety and security organizations handle their information assets. We begin by defining four critical information management requirements and identify key gaps for each of these information handling requirements in an operational context. We consider a range of solutions that assist Canadian safety and security organization to manage their information as a strategic asset. Finally, we describe practical applications of specific technical solutions through a series of realistic operational vignettes.

The concept for this volume emerged from earlier thinking and writing by Moffatt and Charlebois on the topic of developing strategies for “strategic information management for public safety and security” [1]. This earlier work was motivated by years of research and development supporting a range of Canadian and international public safety and security organizations through our work with Defence Research and Development Canada’s (DRDC) Centre for Security Science (CSS).