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Magnesium-ion batteries for electric vehicles: Current trends and future perspectives
No full textLithium-ion batteries have enabled electric vehicles to achieve a foothold in the automobile market. Due to an increasing environmental consciousness, electric vehicles are expected to take a larger portion of the market, with the ultimate goal of supplanting traditional vehicles. However, the involved costs, sustainability, and technical limitations of lithium-ion batteries do create substantial obstacles to this goal. Therefore, this article aims at presenting magnesium-ion batteries as a potential replacement for lithium-ion batteries. Though still under development, magnesium-ion batteries show promise in achieving similar volumetric and specific capacities to lithium-ion batteries. Additionally, magnesium is substantially more abundant than lithium, allowing for the batteries to be cheaper and more sustainable. Numerous technical challenges related to cathode and electrolyte selection are yet to be solved for magnesium-ion batteries. This paper discusses the current state-of-the-art of magnesium-ion batteries with a particular emphasis on the material selection. Although, current research indicates that sulfur-based cathodes coupled with a (HMDS)2Mg-based electrolyte shows substantial promise, other options could allow for a better performing battery. This paper addresses the challenges (materials and costs) and benefits associated with developing these batteries. When overcoming these challenges, magnesium-ion batteries are posed to be a groundbreaking technology potentially revolutionizing the vehicle industry
Differences in Lower Extremity Movement Quality by Level of Sport Specialization in Cadets Entering a United States Service Academy.
No full textBACKGROUND: Sport specialization in youth athletes is associated with increased risk for musculoskeletal injury; however, little is known about whether sport specialization is associated with lower extremity movement quality. The purpose of this study was to examine differences in lower extremity movement quality by level of sport specialization in US Service Academy cadets.
HYPOTHESIS: Cadets who report an increased level of sport specialization would have a lower level of movement quality than those who are less specialized.
STUDY DESIGN: Cross-sectional analysis from an ongoing prospective cohort study.
LEVEL OF EVIDENCE: Level 3.
METHODS: Cadets completed the Landing Error Scoring System (LESS) and a baseline questionnaire evaluating level of sport specialization during high school. Data were analyzed using separate 1-way analysis of variance models.
RESULTS: Among all participants (n = 1950), 1045 (53.6%) reported low sport specialization, 600 (30.8%) reported moderate sport specialization, and 305 (15.6%) reported high sport specialization at the time of data collection during the first week. Ages ranged from 17 to 23 years. Men (1491) and women (459) reported comparable specialization levels (
CONCLUSION: Women reporting moderate sport specialization had improved movement quality and significantly better LESS scores compared to those with high/low specialization.
CLINICAL RELEVANCE: Athletes, especially women, should be encouraged to avoid early sport specialization to optimize movement quality, which may affect injury risk
Aesthetic Judgments of Live and Recorded Music: Effects of Congruence Between Musical Artist and Piece
No full textThe COVID-19 pandemic has brought the live music industry to an abrupt halt; subsequently, musicians are looking for ways to replicate the live concert experience virtually. The present study sought to investigate differences in aesthetic judgments of a live concert vs. a recorded concert, and whether these responses vary based on congruence between musical artist and piece. Participants (N = 32) made continuous ratings of their felt pleasure either during a live concert or while viewing an audiovisual recorded version of the same joint concert given by a university band and a United States Army band. Each band played two pieces: a United States patriotic piece (congruent with the army band) and a non-patriotic piece (congruent with the university band). Results indicate that, on average, participants reported more pleasure while listening to pieces that were congruent, which did not vary based on live vs. lab listening context: listeners preferred patriotic music when played by the army band and non-patriotic music when played by the university band. Overall, these results indicate that felt pleasure in response to music may vary based on listener expectations of the musical artist, such that listeners prefer musical pieces that “fit” with the particular artist. When considering implications for concerts during the COVID-19 pandemic, our results indicate that listeners may experience similar degrees of pleasure even while viewing a recorded concert, suggesting that virtual concerts are a reasonable way to elicit pleasure from audiences when live performances are not possible
Performance of Single Board Computers for Vision Processing
No full textWith the increasing complexity of machine vision algorithms and growing applications of image processing, how do computers without a dedicated graphics processor perform? This research discusses the computational abilities of two lowcost single board computers (SBCs) by subjecting them to various Visual Inertial Odometry (VIO) algorithms. The end goal of this research is to identify a SBC which meets the requirements of being employed on an Unmanned Aerial System for autonomous navigation
Applying Machine Learning to Neutron-Gamma Ray Discrimination from Scintillator Readout Using Wavelength Shifting Fibers
Get PDFAdvances in machine learning have found wide applications including radiation detection. In this work, machine learning is applied to neutron-gamma ray discrimination of an organic liquid scintillator (OLS) readout using wavelength shifting (WLS) fibers. The objective of using WLS fiber is to enable the transfer of the light signal from the scintillation medium, with almost any active volume geometry, to a low-profile photomultiplier. This is a common practice in high-energy physics research and has proven to be very effective for such applications. The drawback of this approach is the light pulses carried to the photomultiplier through the WLS fibers do not perfectly replicate the original OLS light pulses’ intensities or timing. This drawback causes traditional pulse shape discrimination algorithms applied to the degraded light pulses to fail to discriminate between neutron and gamma ray events. However, differences in the degraded light pulses for neutrons and gamma rays still exist and various machine learning algorithms can be applied to identify these differences. An experimental system was constructed to simultaneously capture part of the scintillation medium signal and the corresponding signal through the WLS fibers. Using the known neutron-gamma ray discrimination characteristics directly measured in the scintillation medium to provide the ground truth, supervised machine learning algorithms were applied to the corresponding light pulses carried to the photomultiplier through the WLS fibers. The results indicate that this approach will enable enhanced recovery of neutron-gamma ray discrimination information. This research effort will focus on two aspects of the OLS-WLS system: 1) developing an experimental system to create machine learning training data and 2) applying and evaluating various machine learning algorithms
Artificial Intelligence for Defense Applications
No full textArtificial intelligence (AI) is a set of algorithmic techniques, tools and technologies that provide machines with the ability to perform tasks that normally require human intelligence – to perceive the world, learn from experience, reason about information, represent knowledge, act and adapt. Given the multitude of rapid technological advancements in AI, the defense community has emphasized the importance of leveraging these very technologies to be prepared to fight and win the wars of the future. As one of the ways to modernize key capabilities, the defense community has specifically mentioned the need to invest broadly in the military application of AI, including rapid application of commercial breakthroughs, to gain competitive military advantages. To solve some of the most critical problems facing the defense community, the future force requires the ability to converge capabilities from across multiple domains at speeds and scales beyond human cognitive abilities. This work promotes an understanding of AI for defense applications, as well as provide awareness into some of the state-of-the-art research and development activities in AI that are applicable to defense applications spanning fraud detection for national security, computer vision for satellite imagery analysis, hidden markov modeling for the maritime domain, deep learning for radio frequency systems, representation learning for militarily relevant graphs, and robot swarms for military reconnaissance and surveillance
Adversarial Machine Learning in Network Intrusion Detection Systems
No full textAdversarial examples are inputs to a machine learning system intentionally crafted by an attacker to fool the model into producing an incorrect output. These examples have achieved a great deal of success in several domains such as image recognition, speech recognition and spam detection. In this paper, we study the nature of the adversarial problem in Network Intrusion Detection Systems (NIDS). We focus on the attack perspective, which includes techniques to generate adversarial examples capable of evading a variety of machine learning models. More specifically, we explore the use of evolutionary computation (particle swarm optimization and genetic algorithm) and deep learning (generative adversarial networks) as tools for adversarial example generation. To assess the performance of these algorithms in evading a NIDS, we apply them to two publicly available data sets, namely the NSL-KDD and UNSW-NB15, and we contrast them to a baseline perturbation method: Monte Carlo simulation. The results show that our adversarial example generation techniques cause high misclassification rates in eleven different machine learning models, along with a voting classifier. Our work highlights the vulnerability of machine learning based NIDS in the face of adversarial perturbation
The Case for a Kashmir Peace Deal - Now
No full textKashmir has been at the heart of one of the most intractable conflicts in modern history. Although progress may appear unlikely at first glance, there are three important reasons why Washington may make Kashmir peace talks a foreign policy goal over the next four years: reduction in tensions between two nuclear powers; effective withdrawal from Afghanistan; and support for democratic freedoms and human rights. With a new US administration in the White House and China’s recent moves, now is the time for the United States to showcase its principles, priorities, and power in the Indo-Pacific. Facilitating a Kashmir peace deal would do precisely that.
Kashmir is a major flash point between two nuclear-armed rivals, India and Pakistan. The two countries were on the brink of nuclear war after a suicide attack in Kashmir in 2019. As the ensuing crisis began “spiraling out of control,” Indian prime minister Narendra Modi reportedly considered a missile strike against Pakistan. Experts are predicting “a resurgence of violent and quasi-violent resistance” in response to India’s post-2019 restrictions in the region, and this could generate another sudden—and potentially more dangerous—crisis, with global implications. A group of scientists recently explored the global consequences of a potential India-Pakistan nuclear confrontation. They found that the direct effects would be devastating for both countries, but the indirect effects on climate would be catastrophic for the world. Surface sunlight would decline by 20–35 percent, cooling the global surface by 2°C–5°C and reducing precipitation by 15–30 percent. Recovery would take more than ten years, while net primary productivity would decline 15–30 percent on land and 5–15 percent in oceans, threatening mass starvation and additional worldwide collateral fatalities. As Business Insider summed up, a nuclear war in South Asia “could trigger Ice-Age temperatures, cause global famine, and kill 125 million people.”
US withdrawal from Afghanistan requires not just “Afghan good enough” security forces and a deal with the Taliban. The security of Afghanistan and Kashmir are interlinked. As one expert observed, “In February 1989, the last Soviet soldier withdrew from Afghanistan. The transformation of Afghan warfare from jihad to chaos in the 1990s propelled an upsurge of violence in Kashmir. . . . When the Russians left Kabul, so did many of the foreign mujahideen, or Islamist fighters. They had to go somewhere. And for many of them, somewhere was Kashmir.”
The combination of instability in Afghanistan and popular discontent, verging on uprising, in Kashmir creates ripe conditions for spillover. Stabilizing Afghanistan but not resolving the Kashmir crisis could once again trigger Afghan and international militant relocation to Kashmir, exacerbating the conflict there and potentially spilling over into other parts of the region, including back to Afghanistan. Preventing battle-hardened Afghan and international jihadists from relocating to Kashmir would make for a more comprehensive US withdrawal plan. As would preventing Kashmiri militants from running training camps inside Afghanistan. This requires not just a military approach but also a diplomatic one. It requires India taking seriously and addressing through negotiations local Kashmiri grievances. New Delhi has productively contributed to the Afghan peace process, and so there is good reason to believe that it is capable of effectively engaging in a Kashmir peace process.
Finally, facilitating a Kashmir peace deal is an opportunity for the United States to make clear its position on democracy and human rights. It would send a message to India and the rest of the world confronting the rise of authoritarianism about the distinctiveness and value of America’s global leadership. Official visits and initiatives, such as the Parliamentary Exchange program led by Congressmen Brad Sherman and George Holding, provide a platform for deepening the countries’ shared democratic values.
“Any time is a good time to treat a festering wound,” a Kashmiri activist and doctor memorably responded to my question about when to tackle the Kashmir crisis. Kashmir is a “festering wound” from the standpoint of democratic freedoms and human rights. The current mental health and women’s reproductive health crises reveal the conflict’s human toll, which has been compounded by the COVID-19 pandemic. A peace deal would drastically improve the lives of millions. And as Nobel Prize–winning Indian economist Amartya Sen reminds us, human flourishing has intrinsic value that does not have to be justified in strategic terms
Product Support in a Maintenance Free Operating Period Strategy
Get PDFApplication of a Maintenance Free Operating Period (MFOP) strategy in a fleet of vertical lift aircraft has profound implications to product support. Previous approaches to MFOP focused on estimating the operating period’s probability of success with modeling techniques and improving results using design elements such as inherent reliability. These approaches were aircraft centric and neglected aspects of the sustainment system external to the airframe. Key external facets addressed are the establishment of metrics that adequately measure MFOP performance as a stochastic process, optimization of the recovery period through a systems approach, transition to risk-based maintenance using high fidelity diagnostic and prognostic systems, establishment of an architecture to facilitate quality data consumed by a digital twin, and construction of maintenance policies suited for MFOP. The study concluded that robust product support surrounding the aircraft provides the best likelihood to achieve MFOP strategy success while delivering an efficient recovery period