This research studies an alternative to the slider-crank mechanism for internal combustion engines, which was proposed by the Wiseman Technologies Inc. Their design involved replacing the crankshaft with a hypocycloid gear assembly. The unique hypocycloid gear arrangement allowed the piston and connecting rod to move in a straight line creating a perfect sinusoidal motion, without any side loads. In this work, the Wiseman hypocycloid engine was modeled in a commercial engine simulation software and compared to slider-crank engine of the same size. The engine’s performance was studied, while operating on diesel, ethanol, and gasoline fuel. Furthermore, a scaling analysis on the Wiseman engine prototypes was carried out to understand how the performance of the engine is affected by increasing the output power and cylinder displacement.

It was found that the existing 30cc Wiseman engine produced about 7% less power at peak speeds than the slider-crank engine of the same size. These results were concurrent with the dynamometer tests performed in the past. It also produced lower torque and was about 6% less fuel efficient than the slider-crank engine. The four-stroke diesel variant of the same Wiseman engine performed better than the two-stroke gasoline version. The Wiseman engine with a contra piston (that allowed to vary the compression ratio) showed poor fuel efficiency but produced higher torque when operating on E85 fuel. It also produced about 1.4% more power than while running on gasoline. While analyzing effects of the engine size on the Wiseman hypocycloid engine prototypes, it was found that the engines performed better in terms of power, torque, fuel efficiency, and cylinder brake mean effective pressure as the displacement increased. The 30 horsepower (HP) conceptual Wiseman prototype, while operating on E85, produced the most optimum results in all aspects, and the diesel test for the same engine proved to be the most fuel efficient.

The effects of dispersed second phase particles on α-ferrite (α) to austenite (γ) transformation at 1140 K in Fe–C alloy were studied by means of phase field simulation. According to the simulated results, it was found that the particle could retard the migration of α/γ interface. Importantly, both the morphology of particles and the interfacial energy of particle/matrix (α or γ) interface affect the magnitude of the retarding effect. More specifically, the particles with smaller aspect ratio bring stronger retarding force, and when the interfacial energy of particle/γ interface is larger than that of particle/α interface, the retarding effect also becomes significant. These phenomena could be explained from the viewpoint of change in the total amount of the interfacial energy of the simulation system.

The net storage heat flux (ΔQ[subscript S]) is important in the urban surface energy balance (SEB) but its determination remains a significant challenge. The hysteresis pattern of the diurnal relation between the ΔQ[subscript S] and net all-wave radiation (Q[superscript ∗]) has been captured in the Objective Hysteresis Model (OHM) parameterization of ΔQ[subscript S]. Although successfully used in urban areas, the limited availability of coefficients for OHM hampers its application. To facilitate use, and enhance physical interpretations of the OHM coefficients, an analytical solution of the one-dimensional advection–diffusion equation of coupled heat and liquid water transport in conjunction with the SEB is conducted, allowing development of AnOHM (Analytical Objective Hysteresis Model). A sensitivity test of AnOHM to surface properties and hydrometeorological forcing is presented using a stochastic approach (subset simulation). The sensitivity test suggests that the albedo, Bowen ratio and bulk transfer coefficient, solar radiation and wind speed are most critical. AnOHM, driven by local meteorological conditions at five sites with different land use, is shown to simulate the ΔQ[subscript S] flux well (RMSE values of ∼ 30 W m[superscript −2]). The intra-annual dynamics of OHM coefficients are explored. AnOHM offers significant potential to enhance modelling of the surface energy balance over a wider range of conditions and land covers.

Protein evolution is most commonly studied by analyzing related protein sequences and generating ancestral sequences through Bayesian and Maximum Likelihood methods, and/or by resurrecting ancestral proteins in the lab and performing ligand binding studies to determine function. Structural and dynamic evolution have largely been left out of molecular evolution studies. Here we incorporate both structure and dynamics to elucidate the molecular principles behind the divergence in the evolutionary path of the steroid receptor proteins. We determine the likely structure of three evolutionarily diverged ancestral steroid receptor proteins using the Zipping and Assembly Method with FRODA (ZAMF). Our predictions are within ∼2.7 Å all-atom RMSD of the respective crystal structures of the ancestral steroid receptors. Beyond static structure prediction, a particular feature of ZAMF is that it generates protein dynamics information. We investigate the differences in conformational dynamics of diverged proteins by obtaining the most collective motion through essential dynamics. Strikingly, our analysis shows that evolutionarily diverged proteins of the same family do not share the same dynamic subspace, while those sharing the same function are simultaneously clustered together and distant from those, that have functionally diverged. Dynamic analysis also enables those mutations that most affect dynamics to be identified. It correctly predicts all mutations (functional and permissive) necessary to evolve new function and ∼60% of permissive mutations necessary to recover ancestral function.

A model of low-temperature polar liquids is constructed that accounts for the configurational heat capacity, entropy, and the effect of a strong electric field on the glass transition. The model is based on the Padé-truncated perturbation expansions of the liquid state theory. Depending on parameters, it accommodates an ideal glass transition of vanishing configurational entropy and its avoidance, with a square-root divergent enumeration function at the point of its termination. A composite density-temperature parameter ρ^γ/T, often used to represent combined pressure and temperature data, follows from the model. The theory is in good agreement with the experimental data for excess (over the crystal state) thermodynamics of molecular glass formers. We suggest that the Kauzmann entropy crisis might be a signature of vanishing configurational entropy of a subset of degrees of freedom, multipolar rotations in our model. This scenario has observable consequences: (i) a dynamical crossover of the relaxation time and (ii) the fragility index defined by the ratio of the excess heat capacity and excess entropy at the glass transition. The Kauzmann temperature of vanishing configurational entropy and the corresponding glass transition temperature shift upward when the electric field is applied. The temperature shift scales quadratically with the field strength.

Increasing penetration of energy efficiency programs and distributed renewable energy generation has imposed significant challenges for utilities to recoup their large upfront costs. There is a heated debate on what surcharges should be implemented to help the utilities recover their fixed costs; however, very few studies focus on consumers’ attitudes regarding this topic. This study surveys about 190 residential consumers throughout the United States in November 2015, investigating their preferences and attitudes towards extra demand charges and volumetric energy price increases. We apply probit models and regress consumers’ attitudes on selected socio-demographic and behavioral variables. The results indicate the homeowners are more likely to prefer demand charges when compared to renters. The demographic and behavioral factors impact consumers’ perception of bill savings from energy efficiency programs or solar panel installation and also influence how consumers perceive the fairness of utilities recovering revenue losses by increasing volumetric energy price. In this paper, we demonstrate there is preference heterogeneity among consumers and that policy makers should be aware of such preference heterogeneity and apply policy targeting based on the identified demographics and behavioral factors impacting consumer preferences.

The giant magnetoresistance (GMR) of a point contact between a Co/Cu multilayer and a superconductor tip varies for different bias voltage. Direct measurement of spin polarization by Andreev reflection spectroscopy reveals that the GMR change is due to a change in spin polarization. This work demonstrates that the GMR structure can be utilized as a spin source and that the spin polarization can be continuously controlled by using an external magnetic field.

Mechanical oscillations or vibrations on spacecraft, also called pointing jitter, cause geometric distortions and/or smear in high resolution digital images acquired from orbit. Geometric distortion is especially a problem with pushbroom type sensors, such as the High Resolution Imaging Science Experiment (HiRISE) instrument on board the Mars Reconnaissance Orbiter (MRO). Geometric distortions occur at a range of frequencies that may not be obvious in the image products, but can cause problems with stereo image correlation in the production of digital elevation models, and in measuring surface changes over time in orthorectified images. The HiRISE focal plane comprises a staggered array of fourteen charge-coupled devices (CCDs) with pixel IFOV of 1 microradian. The high spatial resolution of HiRISE makes it both sensitive to, and an excellent recorder of jitter. We present an algorithm using Fourier analysis to resolve the jitter function for a HiRISE image that is then used to update instrument pointing information to remove geometric distortions from the image. Implementation of the jitter analysis and image correction is performed on selected HiRISE images. Resulting corrected images and updated pointing information are made available to the public. Results show marked reduction of geometric distortions. This work has applications to similar cameras operating now, and to the design of future instruments (such as the Europa Imaging System).

Thousands of mothers are at risk of transmitting mitochondrial diseases to their offspring each year, with the most severe form of these diseases being fatal [1]. With no cure, transmission prevention is the only current hope for decreasing the disease incidence. Current methods of prevention rely on low mutant maternal mitochondrial DNA levels, while those with levels close to or above threshold (>60%) are still at a very high risk of transmission [2]. Two novel approaches may offer hope for preventing and treating mitochondrial disease: mitochondrial replacement therapy, and CRISPR/Cas9. Mitochondrial replacement therapy has emerged as a promising tool that has the potential to prevent transmission in patients with higher mutant mitochondrial loads. This method is the subject of many ethical concerns due its use of a donor embryo to transplant the patient’s nuclear DNA; however, it has ultimately been approved for use in the United Kingdom and was recently declared ethically permissible by the FDA. The leading-edge CRISPR/Cas9 technology exploits the principles of bacterial immune function to target and remove specific sequences of mutated DNA. This may have potential in treating individuals with disease caused by mutant mitochondrial DNA. As the technology progresses, it is important that the ethical considerations herein emerge and become more established. The purpose of this review is to discuss current research surrounding the procedure and efficacy of the techniques, compare the ethical concerns of each approach, and look into the future of mitochondrial gene replacement therapy.

Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response.