Quantum key distribution (QKD) networks provide information-theoretically secure keys for distant parties, emerging as a vital alternative to classical cryptography infrastructures threatened by quantum computing. In QKD networks, the immediacy of key supply service is crucial to the security and performance of applications, as their data must be encrypted before transmission. While key buffering can enable instant key supply services, existing schemes rely on heuristic solutions that incur prohibitive key resource consumption, thus significantly hindering practical deployment. To address this issue, we propose QuIKS, an instant key supply scheme based on adaptive buffering, offering the dominant advantage of near-zero key supply latency while consuming ultra-low key resources (i.e., ultra-low buffer size). Specifically, it is built upon a novel analytical model that determines the minimum buffer size required to guarantee near-zero-latency key supply performance. Guided by this model, QuIKS introduces a lightweight two-phase control algorithm that dynamically determines key relaying requests and adjusts the buffer size by probing real-time application patterns and network conditions. Experiments on a real QKD network testbed demonstrate that QuIKS achieves near-zero key supply latency while providing a more than 10-fold reduction in key buffer size compared to state-of-the-art schemes.
Water is one of the central molecules for the formation and habitability of planets. In particular, the region where water freezes-out, the water snowline, could be a favorable location to form planets in protoplanetary disks. We use high resolution ALMA observations to spatially resolve H$_2$O, H$^{13}$CO$^+$ and SO emission in the HL Tau disk. A rotational diagram analysis is used to characterize the water reservoir seen with ALMA and compare this to the reservoir visible at mid- and far-IR wavelengths. We find that the H$_2$O 183 GHz line has a compact central component and a diffuse component that is seen out to ~75 au. A radially resolved rotational diagram shows that the excitation temperature of the water is ~350 K independent of radius. The steep drop in the water brightness temperature outside the central beam of the observations where the emission is optically thick is consistent with the water snowline being located inside the central beam ($\lesssim 6$ au) at the height probed by the observations. Comparing the ALMA lines to those seen at shorter wavelengths shows that only 0.02%-2% of the water reservoir is visible at mid- and far-IR wavelengths, respectively, due to optically thick dust hiding the emission whereas 35-70% is visible with ALMA. An anti-correlation between the H$_2$O and H$^{13}$CO$^+$ emission is found but this is likely caused by optically thick dust hiding the H$^{13}$CO$^+$ emission in the disk center. Finally, we see SO emission tracing the disk and for the first time in SO a molecular outflow and the infalling streamer out to ~2". The velocity structure hints at a possible connection between the SO and the H$_2$O emission. Spatially resolved observations of H$_2$O lines at (sub-)mm wavelengths provide valuable constraints on the location of the water snowline, while probing the bulk of the gas-phase reservoirs.
Tchougoune Moustapha Mai, Mohamed Hajajji, Catherine Azzaro-Pantel
et al.
A multi-objective framework for hydrogen supply chain (HSC) planning is developed for island contexts, incorporating Mixed-Integer Linear Programming (MILP) over multiple time periods. The model minimizes total system cost, greenhouse gas (GHG) emissions, and a risk index criteria. The case study of Corsica is considered, using Geographic Information Systems (GIS) for spatial analysis and infrastructure locating. The 2050 future design of the HSC is determined including site selection, capacity sizing, and technology choices. The proposed m-TOPSIS-based multi objectives solution shows a decentralized infrastructure with a levelized cost of hydrogen of ___6.55/kg, and greenhouse gas emissions under 2 kgCO___e/kg H___. The study also integrates water availability and tourism-induced demand variation as key drivers of energy planning in insular regions.
Decentralized Finance (DeFi) has reshaped the possibilities of reserve banking in the form of the Collateralized Debt Position (CDP). Key to the safety of CDPs is the money supply architecture that enables issued debt to maintain its value. In traditional markets, and with respect to the United States Dollar system, interest rates are set by the Federal Reserve in an attempt to influence the effects of excessive inflation. DeFi enables a more transparent approach that typically relies on interest rates or other debt recovery mechanisms being directly informed by asset price. This research investigates contemporary DeFi money supply and debt management strategies and their limitations. Furthermore, this paper introduces a time-weighted approach to interest rate management that implements a Proportional-Integral-Derivative control system to constantly adapt to market activities and protect the value of issued currency, while addressing observed limitations.
In recent decades, trade between nations has constituted an important component of global Gross Domestic Product (GDP), with official estimates showing that it likely accounted for a quarter of total global production. While evidence of association already exists in macro-economic data between trade volume and GDP growth, there is considerably less work on whether, at the level of individual granular sectors (such as vehicles or minerals), associations exist between the complexity of trading networks and global GDP. In this paper, we explore this question by using publicly available data from the Atlas of Economic Complexity project to rigorously construct global trade networks between nations across multiple sectors, and studying the correlation between network-theoretic measures computed on these networks (such as average clustering coefficient and density) and global GDP. We find that there is indeed significant association between trade networks' complexity and global GDP across almost every sector, and that network metrics also correlate with business cycle phenomena such as the Great Recession of 2007-2008. Our results show that trade volume alone cannot explain global GDP growth, and that network science may prove to be a valuable empirical avenue for studying complexity in macro-economic phenomena such as trade.
We propose an approach to simulate and render realistic water animation from a single still input photograph. We first segment the water surface, estimate rendering parameters, and compute water reflection textures with a combination of neural networks and traditional optimization techniques. Then we propose an image-based screen space local reflection model to render the water surface overlaid on the input image and generate real-time water animation. Our approach creates realistic results with no user intervention for a wide variety of natural scenes containing large bodies of water with different lighting and water surface conditions. Since our method provides a 3D representation of the water surface, it naturally enables direct editing of water parameters and also supports interactive applications like adding synthetic objects to the scene.
This paper proposes a Networked Micro Water-Energy Nexus (NetMicroWEN) capable of co-optimizing and simultaneously supplying water and energy to local consumers in nearby communities. The system manages different water and energy inputs of different communities in a local network to cooperatively meet their demands. This paper considers a centralized network topology that connects all members of the network under one control system. This paper also proposes a Proportional Exchange Algorithm (PEA) that allows members to benefit equally from exchanging both resources among other members of the NetMicroWEN and the main water and power distribution systems. The co-optimization model is a mixed-integer linear program, involving all necessary power and water related constraints for the network to achieve a feasible and practical solution. The economic benefits of the NetMicroWEN are illustrated by a comparison with separate Micro Water- Energy Nexus (MWEN) systems meeting their own demands individually. The case studies demonstrate that the proposed NetMicroWEN achieves substantially lower operating costs compared to the operation of separate MWEN systems.
The Long Baseline Neutrino Facility (LBNF) will produce the worlds most intense neutrino beam. Three series connected magnetic horns will require 5kV, 300kA, 800$μ$s pulses at a rate of 0.7Hz to focus the beam. Fermilab has designed and built pulsed high current supplies for horns in the past. Pulsed currents of 205 kA for Neutrinos at Main Injector (NuMI - NOvA), focusing a 120 GeV beam, and 170 kA for Booster Neutrino Beam (BNB - MiniBooNE) for focusing an 8 GeV beam have been operational for about 18 years. While the magnetic horns are expected to be replaced, the LBNF horn power supply is expected to last the lifetime of the project, 30 years. A resonant, half sine wave pulser was used for NuMI and BNB and has many practical advantages. The system has impedance limited fault currents by design, albeit large ones. That along with the resonant behavior means that thyristor switches are well suited. Many fault modes of the system have also been calculated. Several circuit changes were incorporated so that a single fault can be tolerated. The supply must be reversable to enable both neutrinos and anti-neutrinos to be produced. These reversal requirements required a significant amount of mechanical design and consideration to allow for quick reversal of all the semiconductors.
Arthur D. Bosman, Edwin A. Bergin, Jenny Calahan
et al.
Mid-infrared spectroscopy is one of the few ways to observe the composition of the terrestial planet forming zone, the inner few au, of proto-planetary disks. The species currently detected in the disk atmosphere, for example CO, CO2, H2O and C2H2, are theoretically enough to constrain the C/O ratio in the disk surface. However, thermo-chemical models have difficulties in reproducing the full array of detected species in the mid-infrared simultaneously. In an effort to get closer to the observed spectra, we have included water UV-shielding as well as more efficient chemical heating into thermo-chemical code Dust And Lines. We find that both are required to match the observed emission spectrum. Efficient chemical heating, in addition to traditional heating from UV photons, is necessary to elevate the temperature of the water emitting layer to match the observed excitation temperature of water. We find that water UV-shielding stops UV photons from reaching deep into the disk, cooling down the lower layers with higher column. These two effects create a hot emitting layer of water with a column of 1-10$\times 10^{18}$ cm$^{-2}$. This is only 1-10% of the water column above the dust $τ=1$ surface at mid-infrared wavelengths in the models and represents <1% of the total water column.
Due to the COVID-19 pandemic, the global supply chain is disrupted at an unprecedented scale under uncertain and unknown trends of labor shortage, high material prices, and changing travel or trade regulations. To stay competitive, enterprises desire agile and dynamic response strategies to quickly react to disruptions and recover supply-chain functions. Although both centralized and multi-agent approaches have been studied, their implementation requires prior knowledge of disruptions and agent-rule-based reasoning. In this paper, we introduce a model-based multi-agent framework that enables agent coordination and dynamic agent decision-making to respond to supply chain disruptions in an agile and effective manner. Through a small-scale simulated case study, we showcase the feasibility of the proposed approach under several disruption scenarios that affect a supply chain network differently, and analyze performance trade-offs between the proposed distributed and centralized methods.
Tobias Reisch, Georg Heiler, Christian Diem
et al.
National economies rest on networks of millions of customer-supplier relations. Some companies -- in the case of their default -- can trigger significant cascades of shock in the supply-chain network and are thus systemically risky. Up to now, systemic risk of individual companies was practically not quantifiable, due to the unavailability of firm-level transaction data. So far, economic shocks are typically studied in the framework of input-output analysis on the industry-level that can't relate risk to individual firms. Exact firm-level supply networks based on tax or payment data exist only for very few countries. Here we explore to what extent telecommunication data can be used as an inexpensive, easily available, and real-time alternative to reconstruct national supply networks on the firm-level. We find that the conditional probability of correctly identifying a true customer-supplier link -- given a communication link exists -- is about 90%. This quality level allows us to reliably estimate a systemic risk profile of an entire country that serves as a proxy for the resilience of its economy. In particular, we are able to identify the high systemic risk companies. We find that 65 firms have the potential to trigger large cascades of disruption in production chains that could cause severe damages in the economy. We verify that the topological features of the inter-firm communication network are highly similar to national production networks with exact firm-level interactions.
Hydration or interfacial water present in biomolecules and inorganic solids have been shown to exhibit a dynamical transition upon supercooling. However, an understanding of the extent of the underlying surface hydrophilicity as well as the local distribution of hydrophilic/hydrophobic patches on the dynamical transition is unexplored. Here, we use molecular dynamics simulations with a TIP4P/2005 water model to study translational and rotational relaxation dynamics of interfacial water on graphene surfaces. The purpose of this study is to investigate the influence of both surface chemistry as well as the extent of hydration on the rotational transitions of interfacial water on graphene oxide (GO) surfaces in the deeply supercooled region. We have considered three graphene-based surfaces; a GO surface with equal proportions of oxidized and pristine graphene regions in a striped topology, a fully oxidized surface and a pristine graphene surface. The dipole relaxation time of interfacial water shows a strong-to-strong, strong, and a fragile-to-strong transition on these surfaces, respectively, in the temperature range of 210-298 K. In contrast, bulk water shows a fragile-to-strong transition upon supercooling. In all these cases at high hydration, interfacial water co-exists with a thick water film with bulk-like properties. To investigate the influence of bulk water on dynamical transitions, we simulated a low hydration regime where only bound water (surface water) is present on the GO surfaces and found that the rotational relaxation of surface water on both the GO and fully oxidized surfaces show a single Arrhenius behavior. Our results indicate that not only does the local extent of surface hydrophilicity play a role in determining the energy landscape explored by the water molecules upon supercooling, but the presence of bulk water also modulates the dynamic transition.
Simon Duque Anton, Daniel Fraunholz, Dennis Krummacker
et al.
Advances in industrial control lead to increasing incorporation of intercommunication technologies and embedded devices into the production environment. In addition to that, the rising complexity of automation tasks creates demand for extensive solutions. Standardised protocols and commercial off the shelf devices aid in providing these solutions. Still, setting up industrial communication networks is a tedious and high effort task. This justifies the need for simulation environments in the industrial context, as they provide cost-, resource- and time-efficient evaluation of solution approaches. In this work, industrial use cases are identified and the according requirements are derived. Furthermore, available simulation and emulation tools are analysed. They are mapped onto the requirements of industrial applications, so that an expressive assignment of solutions to application domains is given.
Introduction of the principles of the asymmetrical, short-range O:H-O coupled oscillater pair and the basic rule for water ice, which reconciles the structure and anomalies of water ice.
Didier Beloin‐Saint‐Pierre, Annie Levasseur, Manuele Margni
et al.
Summary This work contributes to the development of a dynamic life cycle assessment (DLCA) methodology by providing a methodological framework to link a dynamic system modeling method with a time‐dependent impact assessment method. This three‐step methodology starts by modeling systems where flows are described by temporal distributions. Then, a temporally differentiated life cycle inventory (TDLCI) is calculated to present the environmental exchanges through time. Finally, time‐dependent characterization factors are applied to the TDLCI to evaluate climate‐change impacts through time. The implementation of this new framework is illustrated by comparing systems producing domestic hot water (DHW) over an 80‐year period. Electricity is used to heat water in the first system, whereas the second system uses a combination of solar energy and gas to heat an equivalent amount of DHW at the same temperature. This comparison shows that using a different temporal precision (i.e., monthly vs. annual) to describe process flows can reverse conclusions regarding which case has the best environmental performance. Results also show that considering the timing of greenhouse gas (GHG) emissions reduces the absolute values of carbon footprint in the short‐term when compared with results from the static life cycle assessment. This pragmatic framework for the implementation of time in DLCA studies is proposed to help in the development of the methodology. It is not yet a fully operational scheme, and efforts are still required before DLCA can become state of practice.
We introduce a mathematical model on the dynamics of demand and supply incorporating collectability and saturation factors. Our analysis shows that when the fluctuation of the determinants of demand and supply is strong enough, there is chaos in the demand-supply dynamics. Our numerical simulation shows that such a chaos is not an attractor (i.e. dynamics is not approaching the chaos), instead a periodic attractor (of period 3 under the Poincaré period map) exists near the chaos, and co-exists with another periodic attractor (of period 1 under the Poincaré period map) near the market equilibrium. Outside the basins of attraction of the two periodic attractors, the dynamics approaches infinity indicating market irrational exuberance or flash crash. The period 3 attractor represents the product's market cycle of growth and recession, while period 1 attractor near the market equilibrium represents the regular fluctuation of the product's market. Thus our model captures more market phenomena besides Marshall's market equilibrium. When the fluctuation of the determinants of demand and supply is strong enough, a three leaf danger zone exists where the basins of attraction of all attractors intertwine and fractal basin boundaries are formed. Small perturbations in the danger zone can lead to very different attractors. That is, small perturbations in the danger zone can cause the market to experience oscillation near market equilibrium, large growth and recession cycle, and irrational exuberance or flash crash.
Mohammad Gholizadeh, Majid Zerafat Angiz L., Seyed Mahmoud Davoodi
et al.
Coastal marine waters are ranked among the most important aquatic ecosystems on earth in terms of ecological and economic significance. Since the Industrial Revolution, human activities have drastically changed coastal marine ecosystems. The development of rules and regulations to protect these ecosystems against human activities requires availability of environmental assessment standard. This necessitates the identification of the key parameters that reflect condition of the coastal water ecosystem. Macrobenthic assemblages are recognized to rapidly respond to changes in the quality of water or habitat. Therefore, it would be useful to study the population of macrobenthos and assess the influential factors on the growth of this species. This study is categorized as multidisciplinary approach which contains two perspectives, ecological and mathematical. In the ecological section, the effect of the water quality parameters (e.g. pH, temperature, dissolved oxygen and salinity) and the sediment characteristics on the macrobenthic abundance is studied. A total of 432 samples were collected and analyzed from four touristic costal locations (at various distances form the coast) of Penang National Park to investigate the spatial change of macrobenthic assemblage. In a mathematical perspective, this paper pursues a new algorithm based on the performance evaluation methods. For this purpose, first, Data Envelopment Analysis (DEA) is employed to evaluate a group of Decision Making Units (DMUs). Consequently, inputs of the mentioned DMUs are considered as alternatives (or candidates), and using a modified DEA model that is categorized as aggregating preference ranking method, the influence of inputs in efficiency of DMUs is investigated.
Markus Rosenstihl, Kerstin Kämpf, Felix Klameth
et al.
We use molecular dynamics computer simulations and nuclear magnetic resonance experiments to investigate the dynamics of water at interfaces of molecular roughness and low mobility. We find that, when approaching such interfaces, the structural relaxation of water, i.e., the $α$ process, slows down even when specific attractive interactions are absent. This prominent effect is accompanied by a smooth transition from Vogel to Arrhenius temperature dependence and by a growing importance of jump events. Consistently, at protein surfaces, deviations from Arrhenius behavior are weak when free water does not exist. Furthermore, in nanoporous silica, a dynamic crossover of liquid water occurs when a fraction of solid water forms near 225 K and, hence, the liquid dynamics changes from bulk-like to interface-dominated. At sufficiently low temperatures, water exhibits a quasi-universal $β$ process, which is characterized by an activation energy of $E_a\!=\!0.5$ eV and involves anisotropic reorientation about large angles. As a consequence of its large amplitude, the faster $β$ process destroys essentially all orientational correlation, rendering observation of a possible slower $α$ process difficult in standard experiments. Nevertheless, we find indications for the existence of structural relaxation down to a glass transition of interfacial water near 185 K. Hydrated proteins show a highly restricted backbone motion with an amplitude, which decreases upon cooling and vanishes at comparable temperatures, providing evidence for a high relevance of water rearrangements in the hydration shell for secondary protein relaxations.
Paul R. Jones, Xiuqing Hao, Eduardo R. Cruz-Chu
et al.
Rough surfaces immersed under water remain practically dry if the liquid-solid contact is on roughness peaks, while the roughness valleys are filled with gas. Mechanisms that prevent water from invading the valleys are well studied. However, to remain practically dry under water, additional mechanisms need consideration. This is because trapped gas (e.g. air) in the roughness valleys can dissolve into the water pool, leading to invasion. Additionally, water vapor can also occupy the roughness valleys of immersed surfaces. If water vapor condenses, that too leads to invasion. These effects have not been investigated, and are critically important to maintain surfaces dry under water. In this work, we identify the critical roughness scale below which it is possible to sustain the vapor phase of water and/or trapped gases in roughness valleys - thus keeping the immersed surface dry. Theoretical predictions are consistent with molecular dynamics simulations and experiments.