Applied research by design: an experimental collaborative and interdisciplinary design charrette

This article reports on one experimental case of interdisciplinary collaboration on a design and planning exercise across several scales – local through urban to regional – and sectors – private, public, scholarly, and interest groups. The case is a collaborative and interdisciplinary design charrette on sustainable urbanism for envisioning the future of the Greater Metropolitan Area of Florence in Italy. The experiment entailed the attempt to integrate complex urban conditions via the design charrette in order to create more healthy and sustainable cities. This collaborative work shows how conditions that are at times not addressed comprehensively nor holistically can be combined through doing applied research by design; where design is understood as a process of discovery and creation that results in synthesis. The article details the methodology applied, and provides an initial assessment on the process that the charrette employed. Moreover, it highlights some professional and policy implications of the effort. Finally, it provides a provisional assessment on learning outcomes and addresses opportunities to improve future exercises of this nature

Dynamic force spectroscopy of DNA hairpins. II. Irreversibility and dissipation

We investigate irreversibility and dissipation in single molecules that cooperatively fold/unfold in a two state manner under the action of mechanical force. We apply path thermodynamics to derive analytical expressions for the average dissipated work and the average hopping number in two state systems. It is shown how these quantities only depend on two parameters that characterize the folding/unfolding kinetics of the molecule: the fragility and the coexistence hopping rate. The latter has to be rescaled to take into account the appropriate experimental setup. Finally we carry out pulling experiments with optical tweezers in a specifically designed DNA hairpin that shows two-state cooperative folding. We then use these experimental results to validate our theoretical predictions.Comment: 28 pages, 12 figure

Hydrological Drought Forecasting Using a Deep Transformer Model

Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performance for water resource planning and disaster management. Forecasting of future hydrological drought can assist with mitigation strategies for various stakeholders. This study uses the transformer deep learning model to forecast hydrological drought, with a benchmark comparison with the long short-term memory (LSTM) model. These models were applied to the Apalachicola River, Florida, with two gauging stations located at Chattahoochee and Blountstown. Daily stage-height data from the period 1928–2022 were collected from these two stations. The two deep learning models were used to predict stage data for five different time steps: 30, 60, 90, 120, and 180 days. A drought series was created from the forecasted values using a monthly fixed threshold of the 75th percentile (75Q). The transformer model outperformed the LSTM model for all of the timescales at both locations when considering the following averages: MSE = 0.11, MAE = 0.21, RSME = 0.31, and R2 = 0.92 for the Chattahoochee station, and MSE = 0.06, MAE = 0.19, RSME = 0.23, and R2 = 0.93 for the Blountstown station. The transformer model exhibited greater accuracy in generating the same drought series as the observed data after applying the 75Q threshold, with few exceptions. Considering the evaluation criteria, the transformer deep learning model accurately forecasts hydrological drought in the Apalachicola River, which could be helpful for drought planning and mitigation in this area of contested water resources, and likely has broad applicability elsewhere

A Potential Energy Landscape Study of the Amorphous-Amorphous Transformation in H2_2O

We study the potential energy landscape explored during a compression-decompression cycle for the SPC/E (extended simple point charge) model of water. During the cycle, the system changes from low density amorphous ice (LDA) to high density amorphous ice (HDA). After the cycle, the system does not return to the same region of the landscape, supporting the interesting possibility that more than one significantly different configuration corresponds to LDA. We find that the regions of the landscape explored during this transition have properties remarkably different from those explored in thermal equilibrium in the liquid phase

Potential Energy Landscape Equation of State

Depth, number, and shape of the basins of the potential energy landscape are the key ingredients of the inherent structure thermodynamic formalism introduced by Stillinger and Weber [F. H. Stillinger and T. A. Weber, Phys. Rev. A 25, 978 (1982)]. Within this formalism, an equation of state based only on the volume dependence of these landscape properties is derived. Vibrational and configurational contributions to pressure are sorted out in a transparent way. Predictions are successfully compared with data from extensive molecular dynamics simulations of a simple model for the fragile liquid orthoterphenyl.Comment: RevTeX4, 4 pages, 5 figure

Hamiltonian dynamics of homopolymer chain models

The Hamiltonian dynamics of chains of nonlinearly coupled particles is numerically investigated in two and three dimensions. Simple, off-lattice homopolymer models are used to represent the interparticle potentials. Time averages of observables numerically computed along dynamical trajectories are found to reproduce results given by the statistical mechanics of homopolymer models. The dynamical treatment, however, indicates a nontrivial transition between regimes of slow and fast phase space mixing. Such a transition is inaccessible to a statistical mechanical treatment and reflects a bimodality in the relaxation of time averages to corresponding ensemble averages. It is also found that a change in the energy dependence of the largest Lyapunov exponent indicates the theta-transition between filamentary and globular polymer configurations, clearly detecting the transition even for a finite number of particles.Comment: 11 pages, 8 figures, accepted for publication in Physical Review

Turbulence and Cavity Recirculation in Air-Water Skimming Flows on a Stepped Spillway

Current expertise in air-water turbulent flows on stepped chutes is limited mostly to laboratory experiments at low to moderate Reynolds numbers on chutes with flat horizontal steps. In this study, highly turbulent air-water flows skimming down a large-size stepped chute were investigated with a 1V:2.5H slope. For some experiments, the cavity recirculation was controlled using triangular vanes, or longitudinal ribs, to enhance the interactions between the skimming flow and cavity recirculating region. New experiments were performed with seven configurations. The results demonstrated the strong influence of the vanes on the cavity recirculation patterns and on the air-water flow properties. An increase in flow resistance was observed consistently with maximum rate of energy dissipation achieved with vanes placed in a zigzag pattern

Finite-Size Effects in a Supercooled Liquid

We study the influence of the system size on various static and dynamic properties of a supercooled binary Lennard-Jones liquid via computer simulations. In this way, we demonstrate that the treatment of systems as small as N=65 particles yields relevant results for the understanding of bulk properties. Especially, we find that a system of N=130 particles behaves basically as two non-interacting systems of half the size.Comment: Proceedings of the III Workshop on Non Equilibrium Phenomena in Supercooled Fluids, Glasses and Amorphous Materials, Sep 2002, Pis