Fundamental Tradeoff Research Articles

Environmental, social and reproductive factors influence the risk–reward trade-off in a group-living fish

AbstractAnimals are faced with a fundamental risk-reward trade-off when making decisions about foraging in the presence of predation, yet little is known about how social, reproductive and environmental factors mediate this trade-off. In the marine environment, anemonefishes provide a model system for investigating the determinants of risk–reward trade-offs, because they live in size- and sex-structured groups within protective sea anemones tentacles, yet feed predominantly in the water column where they are at risk of predation. Furthermore, exposure to changing tides means the availability of planktonic food covaries with their risk of predation. Therefore, we examined how tide, sex and status, and the presence of eggs influenced the time that Amphiprion mccullochi spent at different distances from their anemone, a proxy for foraging effort and predation risk. We found that individuals significantly adjusted their time spent far and close to the anemone depending on the tide, status and the presence of eggs, and that these adjustments can be explained in light of threat sensitive behaviour. This study illustrates the relative importance of environmental and social factors on intraspecific variation in foraging and antipredator behaviour and bolsters our understanding of the decision’s individuals make to balance the costs and benefits of foraging over temporal and spatial scales.

Faster-Than-Nyquist Asynchronous NOMA Outperforms Synchronous NOMA

Faster-than-Nyquist (FTN) signaling aided non-orthogonal multiple access (NOMA) is conceived and its achievable rate is quantified in the presence of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">random</i> link delays of the different users. We reveal that exploiting the link delays may potentially lead to a signal-to-interference-plus-noise ratio (SINR) gain, while transmitting the data symbols at FTN rates has the potential of increasing the degree-of-freedom (DoF). We then unveil the fundamental trade-off between the SINR and DoF. In particular, at a sufficiently high symbol rate, the SINR gain vanishes while the DoF gain achieves its maximum, where the achievable rate is almost <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(1+\beta)$ </tex-math></inline-formula> times higher than that of the conventional synchronous NOMA transmission in the high signal-to-noise ratio (SNR) regime, with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> being the roll-off factor of the signaling pulse. Our simulation results verify our analysis and demonstrate considerable rate improvements over the conventional power-domain NOMA scheme.

Resource exploitation efficiency collapses the home range of an apex predator.

Optimizing energy acquisition and expenditure is a fundamental trade-off for consumers, strikingly reflected in how mobile organisms use space. Several studies have established that home range size decreases as resource density increases, but the balance of costs and benefits associated with exploiting a given resource density is unclear. We evaluate how the ability of consumers to exploit their resources through movement (termed "resource exploitation") interacts with resource density to influence home range size. We then contrast two hypotheses to evaluate how resource exploitation influences home range size across a vast gradient of productivity and density of human-created linear features (roads and seismic lines) that are known to facilitate animal movements. Under the Diffusion Facilitation Hypothesis, linear features are predicted to lead to more diffuse space use and larger home ranges. Under the Exploitation Efficiency Hypothesis, linear features are predicted to increase foraging efficiency, resulting in less space being required to meet energetic demands and therefore smaller home ranges. Using GPS telemetry data from 142 wolves (Canis lupus) distributed over more than 500,000 km2 , we found that wolf home range size was influenced by the interaction between resource density and exploitation efficiency. Home range size decreased as linear feature density increased, supporting the Exploitation Efficiency Hypothesis. However, the effect of linear features on home range size diminished in more productive areas, suggesting that exploitation efficiency is of greater importance when resource density is low. These results suggest that smaller home ranges will occur where both linear feature density and primary productivity are higher, thereby increasing regional wolf density.

Phylogenetic independence in the variations in leaf functional traits among different plant life forms in an arid environment

Leaf traits of global plants reveal the fundamental trade-offs in plant resource acquisition to conservation strategies. However, which leaf traits are consistent, converged, or diverged among herbs, shrubs, and subshrubs in an arid environment remains unclear. In the present study, we evaluated the trade-offs in six leaf functional traits (LFTs): leaf fresh mass (LFM), leaf dry mass (LDM), leaf dry matter content (LDMC), leaf area (LA), specific leaf area (SLA), and leaf thickness (LTh) of 37 desert plant species. LFTs differed between different plant life forms; LFM, LDM, and LA were slightly higher in herbs, LDMC and LTh in shrubs, and SLA in subshrubs. Conversely, the correlations among LFTs were inconsistent in different life forms, which may indicate their different adaptation strategies in an arid environment. Legumes and C3 plants exhibited slightly higher LDMC, LA, and SLA than non-legumes and C4 plants, whereas non-legumes and C4 plants showed higher (nonsignificant) LFM, LDM, and LTh than legumes and C3 plants. A significant phylogenetic signal (PS) and maximum K-value were found for SLA (K = 0.32). LFTs exhibited convergent and divergent variations among different life forms. However, these variations in LFTs were not influenced by phylogeny. Together, these findings increase our understanding of the variations in ecological adaptations of desert plants as well as adaption strategies of different life forms in an arid environment.

Reducing the noise of fiber supercontinuum sources to its limits by exploiting cascaded soliton and wave breaking nonlinear dynamics

The low-noise and phase-coherent nonlinear transformation of a narrowband laser into a broadband supercontinuum (SC) in an optical fiber forms the basis of extremely precise applications ranging from optical frequency comb technology to ultrafast photonics and biomedical imaging. A major challenge of this process is the avoidance of incoherent nonlinear effects that amplify random quantum noise, requiring careful birefringence and dispersion engineering of the fiber. However, fundamental trade-offs exist between working in normal or anomalous dispersion regimes. Here, we combine the benefits of nonlinear dynamics in both regimes by cascading soliton compression and optical wave breaking in a hybrid fiber, formed by joining two widely available, commercial, polarization-maintaining step-index fibers exhibiting anomalous and all-normal dispersion, respectively. We experimentally demonstrate that this hybrid approach results in an ultra-low-noise fiber SC source covering the 930–2130 nm range with phase coherence near unity, spectrally resolved relative intensity noise (RIN) as low as 0.05%, and averaging 0.1% over a bandwidth of 750 nm, approaching the theoretical limits close to the pump laser noise. This corresponds to a doubling of the generated spectral bandwidth and a decrease of RIN by up to 1 order of magnitude compared to direct pumping of the individual fibers, where modulational polarization instabilities play a limiting role. Owing to its simplicity and its scalability to high repetition rates, our hybrid scheme is readily applicable to various laser platforms and could enhance the performance of applications such as hyperspectral nonlinear microscopy, coherent optical communications, and photonic signal processing.

An Axiomatic Perspective on the Performance Effects of End-Host Path Selection

In various contexts of networking research, end-host path selection has recently regained momentum as a design principle. While such path selection has the potential to increase performance and security of networks, there is a prominent concern that it could also lead to network instability (i.e., flow-volume oscillation) if paths are selected in a greedy, load-adaptive fashion. However, the extent and the impact vectors of instability caused by path selection are rarely concretized or quantified, which is essential to discuss the merits and drawbacks of end-host path selection. In this work, we investigate the effect of end-host path selection on various metrics of networks both qualitatively and quantitatively. To achieve general and fundamental insights, we leverage the recently introduced axiomatic perspective on congestion control and adapt it to accommodate joint algorithms for path selection and congestion control, i.e., multi-path congestion-control protocols. Using this approach, we identify equilibria of the multi-path congestioncontrol dynamics and analytically characterize these equilibria with respect to important metrics of interest in networks (the "axioms") such as efficiency, fairness, and loss avoidance. We analyze how these axiomatic ratings for a general network change compared to a scenario without path selection, thereby obtaining an interpretable and quantititative formalization of the performance impact of end-host path-selection. Finally, we show that there is a fundamental trade-off in multi-path congestion-control protocol design between efficiency, stability, and loss avoidance on one side and fairness and responsiveness on the other side.

IF-Over-Fiber Transmission of OFDM Quantum-Noise Randomized PSK Cipher for Physical Layer Encryption of Wireless Signals

This study proposes an intensity modulation/direct detection intermediate frequency-over-fiber (IFoF) system that generates a microwave orthogonal frequency-division multiplexing (OFDM) quantum-noise randomized phase-shift-keying (PSK) cipher. The system directly prevents wireless interception by an eavesdropper without a private key. We theoretically analyze the system and derive a fundamental tradeoff between the security and signal quality at an intermediate frequency (IF). The system achieves balanced security and signal quality. We experimentally demonstrate 4.09-Gbit/s PSK cipher generation at an IF of 3.6 GHz. The cipher has 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">16</sup> phase levels, and more than 100 adjacent signals are masked by quantum noise. The quantum-noise signal masking imposes irreducible uncertainty on illegitimate reception of the cipher, and a symbol error ratio (SER) that an eavesdropper can reach approaches 1. A lower bound of the SER is promised because truly random signal masking by quantum noise cannot be reduced. The error vector magnitude of the IF signals after decryption is maintained at a low value for wireless transmission. The cipher directly and effectively protects the wireless transmission of personal data from interception.

Numerical characterization of support recovery in sparse regression with correlated design

Sparse regression is employed in diverse scientific settings as a feature selection method. A pervasive aspect of scientific data is the presence of correlations between predictive features. These correlations hamper both feature selection and estimation and jeopardize conclusions drawn from estimated models. On the other hand, theoretical results on sparsity-inducing regularized regression have largely addressed conditions for selection consistency via asymptotics, and disregard the problem of model selection, whereby regularization parameters are chosen. In this numerical study, we address these issues through exhaustive characterization of the performance of several regression estimators, coupled with a range of model selection strategies. These estimators and selection criteria were examined across correlated regression problems with varying degrees of signal to noise, distributions of non-zero model coefficients, and model sparsity. Our results reveal a fundamental tradeoff between false positive and false negative control in all regression estimators and model selection criteria examined. Additionally, we numerically explore a transition point modulated by the signal-to-noise ratio and spectral properties of the design covariance matrix at which the selection accuracy of all considered algorithms degrades. Overall, we find that SCAD coupled with BIC or empirical Bayes model selection performs the best feature selection across the regression problems considered.

Stability bounds on superluminal propagation in active structures

Active materials have been explored in recent years to demonstrate superluminal group velocities over relatively broad bandwidths, implying a potential path towards bold claims such as information transport beyond the speed of light, as well as antennas and metamaterial cloaks operating over very broad bandwidths. However, causality requires that no portion of an impinging pulse can pass its precursor, implying a fundamental trade-off between bandwidth, velocity and propagation distance. Here, we clarify the general nature of superluminal propagation in active structures and derive a bound on these quantities fundamentally rooted into stability considerations. By applying filter theory, we show that this bound is generally applicable to causal structures of arbitrary complexity, as it applies to each zero-pole pair describing their response. As the system complexity grows, we find that only minor improvements in superluminal bandwidth can be practically achieved. Our results provide physical insights into the limitations of superluminal structures based on active media, implying severe constraints in several recently proposed applications.

Differential Effects of Fundamental and Longitudinal Life History Trade-Offs on Delay Discounting: An Evolutionary Framework

We synthesized life history theory and the antagonistic pleiotropy hypothesis to form an integrative framework for understanding delay discounting (DD). We distinguished between fundamental and longitudinal life history trade-offs to explain individual and age differences of DD. Fundamental life history trade-offs are characterized by life history strategies (LHS), describing how individuals adjust reproductive timing according to childhood environments, while longitudinal life history trade-offs characterize how individuals make trade-offs between early- vs. late-life reproduction as a function of age. Results of a life-span sample (242 Chinese participants) supported several theoretical predictions: (a) slower LHS predicted lower DD; (b) the relationship between chronological age and DD was U-shaped; (c) the effects of age and LHS were differential. Mechanisms underlying fundamental and longitudinal trade-offs were explored. Regarding fundamental trade-offs, LHS mediated the effects of childhood environment on DD. Regarding longitudinal trade-offs, the U-shaped relationship was more evident between physical age and DD: older adults who were in poorer physical health felt older and exhibited a higher DD. Neither the time perspective nor anticipatory time perception mediated the effect of life history trade-offs. We concluded that DD was a product of two distinct life history trade-offs, reflecting both the trait-like quality and age-related development.

Economic policy choices and trade-offs for Unmanned aircraft systems Traffic Management (UTM): Insights from Europe and the United States

Despite expectations of substantial growth in Unmanned Aircraft Systems (UAS, also called drones) there is currently no large-scale system in place to manage UAS operating in shared airspace. Many countries are developing UAS Traffic Management (UTM) concepts which, unlike conventional air traffic management (ATM), seek to foster a competitive market involving many private actors and service providers and which rely on the cooperative and distributed management of UAS. This paper focusses on the economic policy dimensions of UTM. It describes the main participants, activities and commercial interactions of the emerging UTM concepts in the European Union and the United States. Building on these descriptions, we then consider some of the fundamental choices and trade-offs confronting policymakers when developing an economic policy framework for UTM such as: which activities should be competitive; how can access to scarce airspace be allocated in a safe, fair and efficient way; on what commercial terms will data be shared among participants; what infrastructure can cater for large scale UAS operations; and to what extent should the economic regulatory frameworks for UTM and ATM be aligned.

Neurons detect cognitive boundaries to structure episodic memories in humans.

While experience is continuous, memories are organized as discrete events. Cognitive boundaries are thought to segment experience and structure memory, but how this process is implemented remains unclear. We recorded the activity of single neurons in the human medial temporal lobe during the formation and retrieval of memories with complex narratives. Here we show that neurons responded to abstract cognitive boundaries between different episodes. Boundary-induced neural state changes during encoding predicted subsequent recognition accuracy but impaired event order memory, mirroring a fundamental behavioral tradeoff between content and time memory. Furthermore, the neural state following boundaries was reinstated during both successful retrieval and false memories. These findings reveal a neuronal substrate for detecting cognitive boundaries that transform experience into mnemonic episodes and structure mental time travel during retrieval.

Joint Communication and Binary State Detection

We study a basic joint communication and sensing setup from an information theoretic perspective. A transmitter sends an encoded message through a pair of noisy channels connected to a receiver and a sensor. The receiver is interested in decoding the message from its noisy observation. The sensor has access to the message as side information, and instead is interested in estimating an unknown yet fixed binary state of its channel. This basic setup models scenarios where a wireless transceiver broadcasts an information bearing waveform, to be decoded by possibly more than one receiver, and then observes a modulated echo of the waveform from which it wishes to detect an element or object in the environment. We consider binary symmetric and Gaussian settings with multiplicative binary states, and establish the fundamental trade-off between reliable message communication and efficient state detection in these settings. This trade-off is captured by the message communication rate against the state detection error exponent. The results give insights into the benefits of carrying out communication and sensing jointly.

Male alternative reproductive tactics and sperm competition: a meta-analysis.

ABSTRACTIn many animal species, males may exhibit one of several discrete, alternative ways of obtaining fertilisations, known as alternative reproductive tactics (ARTs). Males exhibiting ARTs typically differ in the extent to which they invest in traits that improve their mating success, or the extent to which they face sperm competition. This has led to the widespread prediction that males exhibiting ARTs associated with a high sperm competition risk, or lower investment into traits that improve their competitiveness before mating, should invest more heavily into traits that improve their competitiveness after mating, such as large ejaculates and high‐quality sperm. However, despite many studies investigating this question since the 1990s, evidence for differences in sperm and ejaculate investment between male ARTs is mixed, and there has been no quantitative summary of this field. Following a systematic review of the literature, we performed a meta‐analysis examining how testes size, sperm number and sperm traits differ between males exhibiting ARTs that face either a high or low sperm competition risk, or high or low investment in traits that increase mating success. We obtained data from 92 studies and 67 species from across the animal kingdom. Our analyses showed that male fish exhibiting ARTs facing a high sperm competition risk had significantly larger testes (after controlling for body size) than those exhibiting tactics facing a low sperm competition risk. However, this effect appears to be due to the inappropriate use of the gonadosomatic index as a body‐size corrected measure of testes investment, which overestimates the difference in testes investment between male tactics in most cases. We found no significant difference in sperm number between males exhibiting different ARTs, regardless of whether sperm were measured from the male sperm stores or following ejaculation. We also found no significant difference in sperm traits between males exhibiting different ARTs, with the exception of sperm adenosine triphosphate (ATP) content in fish. Finally, the difference in post‐mating investment between male ARTs was not influenced by the extent to which tactics were flexible, or by the frequency of sneakers in the population. Overall, our results suggest that, despite clear theoretical predictions, there is little evidence that male ARTs differ substantially in investment into sperm and ejaculates across species. The incongruence between theoretical and empirical results could be explained if (i) theoretical models fail to account for differences in overall resource levels between males exhibiting different ARTs or fundamental trade‐offs between investment into different ejaculate and sperm traits, and (ii) studies often use sperm or ejaculate traits that do not reflect overall post‐mating investment accurately or affect fertilisation success.

Military Operations Abroad in the Long Run: An Economic Approach

ABSTRACT In recent decades, many western countries engaged in Military Operations Abroad (MOA), sometimes with over-stretching military engagements such as antiterrorism, peacekeeping, or humanitarian interventions. These aggressive postures pose a heightened risk to future deployment capacities and the ability to ensure a deterrence strategy in the long run. This study investigates a theoretical model to analyze the sustainability of military operations over time. In our setup, we define military capacity as a stock variable that can regenerate itself and deplete when a country engages in MOA. We present a sustainability theorem with the identification of tipping points in the conduct of MOA. Especially, engaging in excessive military operations leads to a relative ‘demilitarization syndrome.’ This underlines a fundamental trade-off between economic conditions and strategic ambitions. The model sheds some light on the dynamics of the military capabilities of a group of major western military powers.

A three-terminal non-volatile ferroelectric switch with an insulator\u2013metal transition channel

Ferroelectrics offer a promising material platform to realize energy-efficient non-volatile memory technology with the FeFET-based implementations being one of the most area-efficient ferroelectric memory architectures. However, the FeFET operation entails a fundamental trade-off between the read and the program operations. To overcome this trade-off, we propose in this work, a novel device concept, Mott-FeFET, that aims to replace the Silicon channel of the FeFET with VO2- a material that exhibits an electrically driven insulator–metal phase transition. The Mott-FeFET design, which demonstrates a (ferroelectric) polarization-dependent threshold voltage, enables the read current distinguishability (i.e., the ratio of current sensed when the Mott-FeFET is in state 1 and 0, respectively) to be independent of the program voltage. This enables the device to be programmed at low voltages without affecting the ability to sense/read the state of the device. Our work provides a pathway to realize low-voltage and energy-efficient non-volatile memory solutions.

Experimental Verification of Dissipation-Time Uncertainty Relation.

Dissipation is vital to any cyclic process in realistic systems. Recent research focus on nonequilibrium processes in stochastic systems has revealed a fundamental trade-off, called dissipation-time uncertainty relation, that entropy production rate associated with dissipation bounds the evolution pace of physical processes [Phys. Rev. Lett. 125, 120604 (2020)PRLTAO0031-900710.1103/PhysRevLett.125.120604]. Following the dissipative two-level model exemplified in the same Letter, we experimentally verify this fundamental trade-off in a single trapped ultracold ^{40}Ca^{+} ion using elaborately designed dissipative channels, along with a postprocessing method developed in the data analysis, to build the effective nonequilibrium stochastic evolutions for the energy transfer between two heat baths mediated by a qubit. Since the dissipation-time uncertainty relation imposes a constraint on the quantum speed regarding entropy flux, our observation provides the first experimental evidence confirming such a speed restriction from thermodynamics on quantum operations due to dissipation, which helps us further understand the role of thermodynamical characteristics played in quantum information processing.

Energy–Delay Tradeoff in Adaptive Cooperative Caching for Energy-Harvesting Ultradense Networks

Edge caching in collaborative edge computing (CEC) is a resource-friendly technique to improve energy efficiency and alleviate backhaul link congestion. Caching diverse contents based on the social features among users at energy-harvesting-powered (EH-powered) small base stations can further save on-grid energy, but it may lead to a longer delay to mobile users (MUs). In this article, we focus on an energy–delay tradeoff (EDT) problem in CEC-assisted and EH-powered ultradense networks and propose an EDT-oriented adaptive cooperative caching (EDT-ACC) scheme. We regard delay and energy as two types of cost and introduce a weighted cost function to transform the EDT problem into a cost minimization problem. An alternating optimization based on an improved quantum genetic algorithm (AO-IQGA) is proposed to solve the cost minimization problem. In AO-IQGA, the alternating optimization is utilized to divide the cost minimization problem into two subproblems (adaptive tuning weight subproblem and caching decision subproblem). We improve the quantum genetic algorithm in terms of repairing unfeasible solutions and adaptively updating quantum genes. Numerical results demonstrate the efficiency of the proposed AO-IQGA and illustrate the fundamental tradeoff between delay and energy consumption under different parameters, such as content popularity, storage size, and battery capacity.

Special Issue on The Workshop on MAthematical performance Modeling and Analysis (MAMA 2021)

The complexity of computer systems, networks and applications, as well as the advancements in computer technology, continue to grow at a rapid pace. Mathematical analysis, modeling and optimization have been playing, and continue to play, an important role in research studies to investigate fundamental issues and tradeoffs at the core of performance problems in the design and implementation of complex computer systems, networks and applications.

An Analytics Approach to Guide Randomized Controlled Trials in Hypertension Management

Blood pressure (BP) is a significant controllable risk factor for cardiovascular disease (CVD), the leading cause of death worldwide. BP comprises two interrelated measurements: systolic and diastolic. CVD risk is minimized at intermediate BP values, a notion known as the J-curve effect. The J-curve effect imposes fundamental trade-offs in simultaneous management of systolic and diastolic BP; however, assessing a comprehensive set of joint systolic/diastolic BP treatment thresholds while explicitly considering the J-curve effect via randomized controlled trials (RCTs) is not feasible because of the time and cost-prohibitive nature of RCTs. In this study, we propose an analytics approach to identify promising joint systolic/diastolic BP threshold levels for antihypertensive treatment. More specifically, using one of the largest longitudinal BP progression data sets, we first build and fit Brownian motion processes to capture simultaneous progression of systolic/diastolic BP at the population level and externally validate our BP progression model on unseen data. We then analytically characterize the hazard ratio, which enables us to compute the optimal treatment decisions. Finally, building upon the optimal joint BP treatment thresholds, we devise a practical and easily implementable approximate policy. We estimate the potential impact of our findings through a simulation study, which indicates that the impact of explicitly considering the J-curve effect and joint systolic/diastolic BP in treatment decisions could be substantial. Specifically, we estimate that between approximately 3,000 and 9,000 premature deaths from cardiovascular disease in the United States could be prevented annually, a finding that could be tested empirically in randomized trials. This paper was accepted by Stefan Scholtes, healthcare management.