A Constitutive Equation of Thermoelasticity for Solid Materials

A new constitutive equation of thermoelasticity for crystals is presented based on the interatomic potential and solid mechanics at finite temperature. Using the new constitutive equation, the calculations for crystal copper and graphene are carried out under different loading paths at different temperatures. The calculated results are in good agreement with those of the previous thermoelasticity constitutive equation based on quantum mechanics, which clearly indicates that our new constitutive equation of thermoelasticity is correct. A lot of comparisons also show that the present theory is more concise and efficient than the previous thermal stress theory in the practical application.     

Nutrient digestibility and endogenous protein losses in the foregut and small intestine of weaned dairy calves fed calf starters with conventional or enzyme-treated soybean meal

The aims of this experiment were (1) to compare the effects of a soybean meal with an enzymatic treatment (ESBM) to reduce the concentration of antinutritional factors versus a standard soybean meal (SBM) on foregut and small intestine digestion in weaned dairy calves and (2) to estimate the endogenous losses of crude protein (CP) in the small intestine. Our hypothesis was that a diet containing ESBM instead of SBM would improve ruminal and small intestine digestion and absorption of nutrients. A T-cannula was placed in the duodenum, and a second T-cannula was installed in the distal ileum of 12 Holstein calves at approximately 3 wk of age. Calves were weaned on d 42, and on d 50 they were assigned randomly to a quadruplicated 3 × 3 Latin square with 10-d periods. Digesta samples were collected on d 7 and 8 from the ileum and d 9 and 10 from the duodenum. The diets were fed for ad libitum intake and consisted of a calf starter (CS) of 20% CP with SBM as the main source of protein (CTRL), and an isonitrogenous CS with an ESBM instead of SBM (ENZT). A third diet with a low content of CP (10%) and no soy protein was fed to estimate endogenous N losses and digestibilities of test ingredients. Flows and digestibilities of nutrients were compared between CTRL and ENZT and their test ingredients (SBM vs. ESBM, respectively). Duodenal net flows of CP and total AA as well as ruminal microbial protein synthesis per kilogram of digested CP were greater, and flow of nonprotein N and CP true (corrected by endogenous and microbial flows) foregut digestibility were lower with ENZT than CTRL. The apparent small intestine digestibilities of CP and total AA were greater for ESBM than SBM, but there were no differences between the CTRL and ENZT diets. We observed no differences in digestibilities at the duodenum or ileum of starch or NDF, but true small intestine digestibilities of CP and all AA were greater with ENZT than CTRL. Total endogenous protein losses in the small intestine estimated from calves fed the low-CP with no soy protein diet were 37 ± 1.5 g of CP and 29 ± 1.4 g of AA/kg of DMI. These values may be considered the basal endogenous losses as they are similar to values obtained with the regression method, which estimates N losses when dietary N is null. Our results indicated that the inclusion of an ESBM improved the efficiency of ruminal microbial protein synthesis per digested kilogram of organic matter and CP, and increased CP and AA absorption in the small intestine despite a greater proportion of undigested dietary protein entering the duodenum.     

Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Stability and thermophysical properties of fly ash nanofluid for heat transfer applications

Improving the performance of heat transfer fluids is altogether significant. The best approach for improving the thermal conductivity is the addition of nanoparticles to the base fluid. In the present study, specific heat, dynamic viscosity, and thermal conductivity of water-based Indian coal fly ash stable nanofluid for 0.1% to 0.5% volume concentration in the temperature range of 30 to 60°C has been investigated. To evaluate an average particle diameter of 11.5 nm, the fly ash nanoparticles were characterized with scanning electron microscopy and dynamic light scattering. Using zeta potential, the stability of nanofluid in the presence of surfactant Triton X-100 was tested. Thermal conductivity and viscosity of fly ash nanofluid increased, while specific heat decreased as volume concentration increased. The effect of temperature on the fly ash nanofluid was directly proportional to its thermal conductivity and specific heat and inversely proportional to viscosity.     

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.