Sensitivity of plankton biomass and productivity to variations in physical forcing and biological parameters in Chesapeake Bay

A coupled three-dimensional hydrodynamic-biogeochemical model is used to simulate plankton dynamics in Chesapeake Bay and examine its sensitivity to variations in biological parameters and physical forcing. The coupled biophysical model captures observed seasonal cycle and regional distributions of plankton in Chesapeake Bay and predicts the phase lag between the spring chlorophyll maximum and the summer primary productivity maximum. This lag traces to the delivery of dissolved inorganic nutrients in the winter-spring freshet from the Susquehanna River that fuels the spring bloom, whereas regenerated nutrients support high primary productivity in summer. The model shows that episodic wind events commonly associated with frontal passages in summer inject nutrients into the euphotic layer, leading to short periods of elevated primary productivity. Quantitative comparisons between the predicted and observed annual time series of euphotic-layer chlorophyll and primary productivity show that the model possesses reasonable skill. Sensitivity analyses of model simulations for different biological parameter values and alternative formulations of biogeochemical processes suggest that model predictions are robust. To understand the impacts of climate variability and change on Chesapeake Bay, we examine how the plankton system responds to variations in river runoff, wind forcing, temperature and light level. Annual mean chlorophyll (AMC) and annual integrated production (AIP) increase by about 70% for a doubling of river runoff, but only reduce by 30% and 13% for 50% reduction of river runoff, suggesting a nonlinear response of plankton system to changes in river runoff and nutrient loading. Doubling of wind stress results in a small increase in AMC but 28% increase in AIP. For 2°C warming AMC increases from 25.4 to 30 mg m−2 and AIP increases from 180 to 246 g C m−2 yr−1

Superconducting properties of the In-substituted topological crystalline insulator, SnTe

We report detailed investigations of the properties of a superconductor obtained by substituting In at the Sn site in the topological crystalline insulator (TCI), SnTe. Transport, magnetization and heat capacity measurements have been performed on crystals of Sn$_{0.6}$In$_{0.4}$Te, which is shown to be a bulk superconductor with $T_c^{\rm{onset}}$ at $\sim4.70(5)$~K and $T_c^{\rm{zero}}$ at $\sim3.50(5)$~K. The upper and lower critical fields are estimated to be $\mu_0H_{c2}(0)=1.42(3)$~T and $\mu_0H_{c1}(0)=0.90(3)$~mT respectively, while $\kappa=56.4(8)$ indicates this material is a strongly type II superconductor

Nanogenerator comprising piezoelectric semiconducting nanostructures and Schottky conductive contacts

A semiconducting device includes a substrate, a piezoelectric wire, a structure, a first electrode and a second electrode. The piezoelectric wire has a first end and an opposite second end and is disposed on the substrate. The structure causes the piezoelectric wire to bend in a predetermined manner between the first end and the second end so that the piezoelectric wire enters a first semiconducting state. The first electrode is coupled to the first end and the second electrode is coupled to the second end so that when the piezoelectric wire is in the first semiconducting state, an electrical characteristic will be exhibited between the first electrode and the second electrode

Optical music recognition of the singer using formant frequency estimation of vocal fold vibration and lip motion with interpolated GMM classifiers

The main work of this paper is to identify the musical genres of the singer by performing the optical detection of lip motion. Recently, optical music recognition has attracted much attention. Optical music recognition in this study is a type of automatic techniques in information engineering, which can be used to determine the musical style of the singer. This paper proposes a method for optical music recognition where acoustic formant analysis of both vocal fold vibration and lip motion are employed with interpolated Gaussian mixture model (GMM) estimation to perform musical genre classification of the singer. The developed approach for such classification application is called GMM-Formant. Since humming and voiced speech sounds cause periodic vibrations of the vocal folds and then the corresponding motion of the lip, the proposed GMM-Formant firstly operates to acquire the required formant information. Formant information is important acoustic feature data for recognition classification. The proposed GMM-Formant method then uses linear interpolation for combining GMM likelihood estimates and formant evaluation results appropriately. GMM-Formant will effectively adjust the estimated formant feature evaluation outcomes by referring to certain degree of the likelihood score derived from GMM calculations. The superiority and effectiveness of presented GMM-Formant are demonstrated by a series of experiments on musical genre classification of the singer

Short-range anisotropic ferromagnetic correlations in the paramagnetic and antiferromagnetic phases of Gd5Ge4

Signatures of short range anisotropic ferromagnetic correlations and ferromagnetic clustering, manifested as unusually large hysteresis and other anomalies of the low magnetic field dc magnetization and ac magnetic susceptibility, have been observed in both the antiferromagnetic and paramagnetic states of single crystal Gd5Ge4. Ferromagnetic correlations, which are most pronounced in a weak magnetic field applied along the b axis, are readily suppressed by fields exceeding ∼5 kOe and are believed to be related to a Griffiths-like phase that develops in Gd5Ge4 below TG≅240 K

Field step size and temperature effects on the character of the magnetostructural transformation in a Gd5Ge4 single crystal

The critical magnetic fields required to induce the magnetostructural transformation below ∼30 K in Gd5Ge4 are dependent on the size of the magnetic-field step employed during isothermal measurements of magnetization: the smaller the step, the lower the critical field. The influence of the magnetic-field step size on the character of the magnetostructural transition in Gd5Ge4 diminishes as temperature increases, nearly disappearing above ∼30 K. Decreasing the size of the field step also leads to the formation of multiple steps in the magnetization. The steps are reproducible in the same sample at low temperatures (below ∼9 K) but they become stochastic and irreproducible at high temperatures (above ∼20 K). The varying dynamics of both the magnetization and demagnetization processes is associated with approaching true equilibrium states and, therefore, reduction of the size of the magnetic-field step at low temperatures plays a role similar to the dominant role of thermal fluctuations at high temperatures. Similar phenomena are expected to occur in other martensiticlike systems, e.g., the manganites

Free field realization of the exceptional current superalgebra \hat{D(2,1;\a)}_k

The free-field representations of the D(2,1;\a) current superalgebra and the corresponding energy-momentum tensor are constructed. The related screening currents of the first kind are also presented.Comment: Latex file, 10 page

Exploration of High Entropy Ceramics (HECs) with Computational Thermodynamics - A Case Study with LaMnO3±δ

The concept of the new category materials high entropy ceramics (HECs) has been proposed several years ago, which is directly borrowed from high entropy alloys (HEAs). It quickly attracts a lot of interests and displays promising properties. However, there is no clear definition of HECs differentiating it from HEAs, as it is still in its early research stage. In the current work, we are trying to use the classic perovskite LaMnO3±δ (LMO) to demonstrate the fundamental differences between HECs and HEAs. We have adopted the integrated defect chemistry and CALPHAD approach to investigate the mixing behavior and how it is affected by the control parameters, i.e. PO2, T, and composition. We have developed a new way to visualize the mixing behavior of the species including the cations, anions, and defects (vacancies), which linked the mixing behavior to the thermo-chemical properties including enthalpy, entropy, and Gibbs energy. It was found that entropy plays the most important role on the mixing behavior in LMO. The present work paves the way for the HECs investigation and the design of new HECs for the various applications