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The combination of a geometrically frustrated lattice, and similar energy scales between degrees of freedom endows two-dimensional Kagome metals with a rich array of quantum phases and renders them ideal for studying strong electron correlations and band topology. The Kagome metal, FeGe is a noted example of this, exhibiting A-type collinear antiferromagnetic (AFM) order atT_N ≈ 400 K, then establishes a charge density wave (CDW) phase coupled with AFM ordered moment belowT_CDW ≈ 110 K, and finally forms ac-axis double cone AFM structure aroundT_Canting ≈ 60 K. Here we use neutron scattering to demonstrate the presence of gapless incommensurate spin excitations associated with the double cone AFM structure of FeGe at temperatures well aboveT_CantingandT_CDWthat merge into gapped commensurate spin waves from the A-type AFM order. Commensurate spin waves follow the Bose factor and fit the Heisenberg Hamiltonian, while the incommensurate spin excitations, emerging belowT_Nwhere AFM order is commensurate, start to deviate from the Bose factor aroundT_CDW, and peaks atT_Canting. This is consistent with a critical scattering of a second order magnetic phase transition with decreasing temperature. By comparing these results with density functional theory calculations, we conclude that the incommensurate magnetic structure arises from the nested Fermi surfaces of itinerant electrons and the formation of a spin density wave order.

 

Hydrological systems in the Anthropocene have shown substantial shifts from their natural processes due to human modifications. Consequently, deploying coupled human-water modeling is a critical tool to analyze observed changes. However, the development of socio-hydrological models often requires extensive qualitative data collection in the field and analysis. Despite the advances in developing inter-disciplinary methodologies in utilizing qualitative data for coupled human-water modeling, there is a need to identify influential parameters in these systems to inform data collection. Here, we present an exploratory socio-hydrological model to systemically investigate the feedback system of public infrastructure providers, resource users, and the dynamics of water scarcity at the catchment scale to inform data collection and analysis in the field. Specifically, we propose a novel socio-hydrological model by employing and integrating a top-down hydrological model and an extension of Aqua.MORE Model (an Agent-Based Model designed to simulate dynamics of water supply and demand). Specifically, we model alternate behavioral theories of human decision-making to represent the agents" behavior. Then, we perform sensitivity analysis techniques to identify key socio-economic and behavioral parameters affecting emergence patterns in a stylized human-dominated catchment. We apply the proposed methodology to the Lake Mendocino Watershed in Northern California, US. The results will potentially point which parameters are influential and how they could be mapped to a particular interview or survey question. This study will help us to identify features of decision-making behavior for inclusion in fieldwork, that be might be overlooked in the absence of the proposed modeling. We anticipate that the proposed approach also contributes to the current Panta Rhei Research Initiative of the International Association of Hydrological Sciences (IAHS) which aims at improving the interpretation of the hydrological processes governing the socio-hydrological systems by focusing on their changing dynamics in connection with rapidly changing human systems. 

We propose a simple, fast, and accurate one-stage approach to visual grounding, inspired by the following insight. The performances of existing propose-and-rank twostage methods are capped by the quality of the region candidates they propose in the first stage — if none of the candidates could cover the ground truth region, there is no hope in the second stage to rank the right region to the top. To avoid this caveat, we propose a one-stage model that enables end-to-end joint optimization. The main idea is as straightforward as fusing a text query’s embedding into the YOLOv3 object detector, augmented by spatial features so as to account for spatial mentions in the query. Despite being simple, this one-stage approach shows great potential in terms of both accuracy and speed for both phrase localization and referring expression comprehension, according to our experiments. Given these results along with careful investigations into some popular region proposals, we advocate for visual grounding a paradigm shift from the conventional two-stage methods to the one-stage framework. 

Polymorphic gates are reconfigurable devices that deliver multiple functionalities at different temperature, supply voltage or external inputs. Capable of working in different modes, polymorphic gate is a promising candidate for embedding secret information such as fingerprints. In this paper, we report five polymorphic gates whose functionality varies in response to specific control input and propose a circuit fingerprinting scheme based on these gates. The scheme selectively replaces standard logic cells by polymorphic gates whose functionality differs with the standard cells only on Satisfiability Don’t Care conditions. Additional dummy fingerprint bits are also introduced to enhance the fingerprint’s robustness against attacks such as fingerprint removal and modification. Experimental results on ISCAS and MCNC benchmark circuits demonstrate that our scheme introduces low overhead. More specifically, the average overhead in area, speed and power are 4.04%, 6.97% and 4.15% respectively when we embed 64-bit fingerprint that consists of 32 real fingerprint bits and 32 dummy bits. This is only half of the overhead of the other known approach when they create 32-bit fingerprints.