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•Machine learning assisted fuel discovery.•High-throughput screening of 319,895 hydrocarbon molecules.•28 new hydrocarbon molecules has been proposed as new high density fuel.
Next ...generation high energy density hydrocarbon (HEDH) fuels are urgently demanded to extend the range of propulsion system and meet additional requirements of new engines. We develop a facile and efficient methodology based on machine learning enabled high-throughput screening to accelerate the design of next generation fuels, and present a proof-of-concept study for discovering new HEDH fuels. This approach screens 319,895 hydrocarbon molecules using the key properties of fuel as the threshold values, and a group of 28 highly potent hydrocarbon molecules with high net heat of combustion, high specific impulse, high density and low melting point has been identified. The as-discovered molecules possess distinctive ring composition and unique spatial structure, which direct the synthetic efforts toward next generation HEDH fuels. This strategy not only discovers a new group of polycyclic molecules as competitive fuel candidates but also accelerates the development of new HEDH fuels.
The Kidney as an Endocrine Organ Acharya, Vinay; Olivero, Juan
Methodist DeBakey cardiovascular journal,
10/2018, Letnik:
14, Številka:
4
Journal Article
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The column in this issue is supplied by Vinay Acharya, D.O., and Juan Jose Olivero, M.D. Dr. Acharya is a nephrology fellow at Houston Methodist Hospital. He earned his Doctor of Osteopathic Medicine ...degree at Arizona College of Osteopathic Medicine and completed an internal medicine residency at Houston Methodist Hospital. Dr. Olivero is a nephrologist at Houston Methodist Hospital and a member of the hospital's Nephrology Training Program. He obtained his medical degree from the University of San Carlos School of Medicine in Guatemala and completed his residency and nephrology fellowship at Baylor College of Medicine in Houston, Texas.
To evaluate stiffness of infraspinatus muscle tissue, both with and without latent trigger points, using ultrasound shear wave elastography (SWE). The primary hypothesis is that muscle with a latent ...trigger point will demonstrate a discrete region of increased shear wave speed. The secondary hypothesis is that shear wave speed (SWS) in the region with the trigger point will be higher in patients compared with controls, and will be similar between the two groups in the uninvolved regions.
Case-control.
Hospital-based outpatient physical therapy center.
Convenience sample (N=18) of patients (6 female, 3 male, mean age=44) (range=31-61y) diagnosed with latent trigger points in infraspinatus and matched controls without trigger points.
Shear wave speed (m/s).
SWS of the latent trigger point (mean=4.09±SD1.4 m/s) did not differ from the adjacent muscle tissue (3.92±1.6 m/s, P>.05), but was elevated compared to corresponding tissue in controls (2.8±0.75 m/s, P=.02). SWS was generally greater in patients' uninvolved tissue (3.83±1.6 m/s) when compared to corresponding tissue in controls (2.62±0.2 m/s, P=.05).
Although discrete regions of increased SWS corresponding to the trigger point were not observed in patients, evidence of generally increased muscle stiffness in infraspinatus was exhibited compared to healthy controls. Further study of additional muscles with SWE is warranted.
The 2022 Canadian Council On Animal Care (CCAC) guidelines: Identification of Scientific Endpoints, Human Intervention Points, and Cumulative Endpoints (CCAC Guide) supplements existing laboratory ...animal humane endpoint theory according to the latest available literature. This article summarized the main content of the 2022 CCAC Guide, and elaborated and analyzed the determination, implementation and supervision of the scientific endpoints, humane intervention points, and cumulative endpoints of animal experiments, in order to provide useful reference and information.
Outlier detection is a statistical procedure that aims to find suspicious events or items that are different from the normal form of a dataset. It has drawn considerable interest in the field of data ...mining and machine learning. Outlier detection is important in many applications, including fraud detection in credit card transactions and network intrusion detection. There are two general types of outlier detection: global and local. Global outliers fall outside the normal range for an entire dataset, whereas local outliers may fall within the normal range for the entire dataset, but outside the normal range for the surrounding data points. This paper addresses local outlier detection. The best-known technique for local outlier detection is the Local Outlier Factor (LOF), a density-based technique. There are many LOF algorithms for a static data environment; however, these algorithms cannot be applied directly to data streams, which are an important type of big data. In general, local outlier detection algorithms for data streams are still deficient and better algorithms need to be developed that can effectively analyze the high velocity of data streams to detect local outliers. This paper presents a literature review of local outlier detection algorithms in static and stream environments, with an emphasis on LOF algorithms. It collects and categorizes existing local outlier detection algorithms and analyzes their characteristics. Furthermore, the paper discusses the advantages and limitations of those algorithms and proposes several promising directions for developing improved local outlier detection methods for data streams.
Abstract
Despite recent advancements in mechanochemical polymerization, understanding the unique mechanochemical reactivity during the ball milling polymerization process still requires extensive ...investigations. Herein, solid-state anionic ring-opening polymerization is used to synthesize polyethers from various functional epoxide monomers. The critical parameters of the monomers are investigated to elucidate the unique reactivity of ball milling polymerization. The controllable syntheses of the desired polyethers are characterized via NMR, GPC, and MALDI-ToF analyses. Interestingly, bulky monomers exhibit faster conversions in the solid-state in clear contrast to that observed for solution polymerization. Particularly, a close linear correlation is observed between the conversion of the ball milling polymerization and melting point of the functional epoxide monomers, indicating melting point as a critical predictor of mechanochemical polymerization reactivity. This study provides insights into the efficient design and understanding of mechanochemical polymerization.
The mechanisms involved in the formation/dissociation of methane hydrate confined at the nanometer scale are unraveled using advanced molecular modeling techniques combined with a mesoscale ...thermodynamic approach. Using atom-scale simulations probing coexistence upon confinement and free energy calculations, phase stability of confined methane hydrate is shown to be restricted to a narrower temperature and pressure domain than its bulk counterpart. The melting point depression at a given pressure, which is consistent with available experimental data, is shown to be quantitatively described using the Gibbs-Thomson formalism if used with accurate estimates for the pore/liquid and pore/hydrate interfacial tensions. The metastability barrier upon hydrate formation and dissociation is found to decrease upon confinement, therefore providing a molecular-scale picture for the faster kinetics observed in experiments on confined gas hydrates. By considering different formation mechanisms-bulk homogeneous nucleation, external surface nucleation, and confined nucleation within the porosity-we identify a cross-over in the nucleation process; the critical nucleus formed in the pore corresponds either to a hemispherical cap or to a bridge nucleus depending on temperature, contact angle, and pore size. Using the classical nucleation theory, for both mechanisms, the typical induction time is shown to scale with the pore volume to surface ratio and hence the pore size. These findings for the critical nucleus and nucleation rate associated with such complex transitions provide a means to rationalize and predict methane hydrate formation in any porous media from simple thermodynamic data.
We study electronic instabilities of a kagome metal with a Fermi energy close to saddle points at the hexagonal Brillouin zone face centers. Using parquet renormalization group, we determine the ...leading and subleading instabilities, finding superconducting, charge, orbital moment, and spin density waves. We then derive and use Landau theory to discuss how different primary density wave orders give rise to charge density wave modulations, as seen in the AV3Sb5 family, with A = K, Rb, Cs. The results provide strong constraints on the mechanism of charge ordering and how it can be further refined from existing and future experiments.
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