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Inbreeding reduces fitness in spatially structured populations of a threatened rattlesnake
No full textSmall and fragmented populations are at high risk of local extinction, in part because of elevated inbreeding and subsequent inbreeding depression. A major conservation priority is to identify the mechanisms and extent of inbreeding depression in small populations. The eastern massasauga (Sistrurus catenatus) rattlesnake is listed as Federally Threatened in the United States, having experienced significant habitat fragmentation and concomitant population declines over the past 200 years. Here, we use long-term monitoring of two wild populations of eastern massasaugas in Michigan to estimate the extent of inbreeding in each population, identify mechanisms that generate inbreeding, and test for the impact of inbreeding on fitness. Using targeted genomic data and spatial coordinates of capture locations from over 1000 individuals, we find evidence of inbreeding and link inbreeding to spatial kinship structure within populations, possibly driven by limited dispersal. We reconstruct multigenerational pedigrees for each population to measure reproductive output and use long-term capture-recapture data to estimate individual survival (i.e., the two major components of fitness). We find evidence of inbreeding depression in both fitness metrics. The 5% most inbred individuals are 13.5% less likely to have any surviving offspring and have 11.6% lower annual survival compared to all less inbred individuals. By combining genomics and long-term monitoring data, we are able to link the life history of eastern massasaugas to inbreeding and detect relationships between fitness and inbreeding. These insights provide important conservation context for future management and for understanding how spatial structure can generate inbreeding depression even at fine spatial scales.</p
Agriculture (re)-territorialisation:visions, tensions, and transition pathways in European food systems
No full textThe COVID-19 crisis has highlighted the vulnerability of supply chains, bringing the possibility of disruptions to the forefront as a major concern (UN in The impact of COVID-19 on food security and nutrition. https://in.one.un.org/wp-content/uploads/2020/06/SG-Policy-Brief-on-COVID-Impact-on-Food-Security.pdf, 2020). The blockage of the Suez Canal by the Evergreen ship in 2021 and the start of the war in Ukraine in 2022 further intensified issues in food markets and increased food insecurity. These incidents underscore the fragility of our global food systems. Moreover, a paradigm shift is crucial to address the unprecedented loss of biodiversity (IPBES in Communiqué de presse: Le dangereux déclin de la nature: Un taux d’extinction des espèces « sans précédent » et qui s’accélère. https://ipbes.net/news/Media-Release-Global-Assessment-Fr, 2019) and climate change (IPCC in AR6 climate change 2021: the physical science basis. https://www.ipcc.ch/report/ar6/wg1/, 2021). Additionally the well-established link between obesity, undernutrition, and climate change (Swinburn et al. in Lancet, 2019. https://doi.org/10.1016/S0140-6736(18)32822-8) underscores the necessity for a fundamental transformation in our food production systems. To address this, we need food systems that are both robust and adaptable, capable of enduring health crises, geopolitical tensions, and the challenges posed by climate change, declining biodiversity, soil depletion, and the difficulties faced by farmers. This special feature presents a collection of research papers that investigate re-territorialisation and alternative food networks in Europe. The contributions stemming from diverse disciplinary backgrounds, such as sociology, anthropology, geography, and economic sciences, highlight not only the complexity of changes in food systems, but also their multifaceted nature. While re-territorialisation is already in progress, it would greatly benefit from proactive policies that support both the desire and the necessity for change.</p
Synergistic interaction of monodisperse Pt nanoparticles with defect-rich graphene aerogel for efficient acidic hydrogen evolution
No full textSolving the problem of aggregation and nonuniform dispersion of platinum (Pt) nanoparticles (NPs) is the key to obtaining high catalytic activity. Graphene aerogels (GAs) with large accessible specific surface area and abundant surface defects are considered to be excellent substrate materials for reducing Pt agglomeration and enhancing catalytic activity. Herein, Pt-based GA composites (Pt-GA-x) featuring homogeneous particle dispersion and high activity were successfully synthesized through a one-step reduction method. Fourier transform infrared (FTIR), Raman, and X-ray photoelectron spectroscopy (XPS) test results indicate that the presence of a large number of oxygen-containing functionalities in GA for anchoring Pt NPs, and the interaction with GA produces electronically structured Pt and defect-rich GA substrates. The obtained electrocatalyst Pt-GA-2 possesses a large specific surface area (443.46 m2·g−1), low Pt loading (3.08 wt%), and uniformly dispersed Pt NPs (average 42 nm). As an advanced hydrogen evolution reaction (HER) electrocatalyst, an overpotential of 34 mV is achieved at a current density of 10 mA·cm−2 in 0.5 M H2SO4 electrolyte, together with a low Tafel slope of 33.2 mV·dec−1. Hence, high mass activity (5623 mA·mgPt−1) and turnover frequency (TOF = 2.57 s−1 at η = 100 mV) can be obtained, which are 6.81 and 6.76 times higher than those of commercial Pt/C catalysts. All these are attributed to enormous surface defects over GA and electron enrichment on Pt NPs. The present study highlights the unique advantages of GA in electrochemical energy conversion and provides new avenues to fabricate advanced HER electrocatalysts.</p
An adaptive self-guarded and risk-aware honeypot using DRL
No full textWe propose a novel adaptive self-guarded honeypot called Asgard2.0, designed to capture shell-based attacks on real Linux-based systems via remote SSH access and to automatically recover when severely compromised. Asgard2.0 leverages Deep Q-Networks (DQN), a Deep Reinforcement Learning (DRL) algorithm, to balance two often conflicting objectives: (i) Collecting attack data and (ii) Preventing deep compromise of the honeypot itself.By employing a rich environmental state representation and risk-aware reward functions, Asgard2.0 develops a nuanced understanding of its operational context, enabling informed and flexible decision-making to learn its objectives. Asgard2.0 was evaluated in a real-world deployment alongside its predecessor Asgard1.0 (a more restricted version), as well as two conventional honeypots: Cowrie, a medium-interaction honeypot (MiHP), and a non-filtered Linux-based system serving as a high-interaction honeypot (HiHP). Experimental results demonstrate that Asgard2.0 effectively collects attack data while significantly reducing the risk of deep compromise compared to the other systems. These findings highlight its ability to strike a well-balanced trade-off between MiHP and HiHP approaches
Electrically reconfigurable heteronuclear dual-atom catalysts
No full textScrutinizing the dynamic reconfiguration mechanism of intermetallic single-atom catalysts reveals the chemical origin of the enhanced electrocatalysis performance.</p
Exploring weak value arguments and Bargmann invariants in N-level quantum systems through the Majorana symmetric representation
No full textThis work examines the argument of weak values for general observables and develops a geometric description on the Bloch sphere. We apply the Majorana symmetric representation to reach this goal. The weak value of a general observable is proportional to the weak value of an effective projector: it is constructed from the application of the observable over the initial state, after normalization by a constant of proportionality that is real. The argument of the weak value of a projector on a pure state of an N-level system corresponds to a symplectic area in the complex projective space ( CP N − 1 ) . This symplectic area cannot be visualized directly but it can be represented geometrically with a sum of N − 1 solid angles on the Bloch sphere using the Majorana stellar representation. By combining these two ideas, we show that the argument of the weak value of any observable (i.e. not just projectors) can be described with the Majorana representation, as the sum of N − 1 solid angles on the Bloch sphere. These two approaches provide two geometrical descriptions, a first one in the complex projective space CP N − 1 and a second one on the Bloch sphere, after mapping the problem from the original N-dimensional quantum state space ( CP N − 1 ) to a multi-qubit description in three-dimensional space by making use of the Majorana representation. These results can also be applied to the argument of the third-order Bargmann invariant, the most fundamental order as the argument of any higher order invariant can be expressed as a sum of the argument of third-order Bargmann invariants, as well as to the argument of the Kirkwood-Dirac quasi-probability distribution. Finally, we focus on the argument of the weak value of a general spin-1 operator when its modulus diverges towards infinity. This divergence amplifies signals with great usefulness in experiments and appears connected to the qubit entanglement in the Majorana representation.</p
