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Class B Materials Code Case to include: FY25 - High temperature design methodology, overview of ASME Section III (Division 5), Design for elevated temperature service, Goal to address current gaps, evaluation of proposed rules, allowable stress development, Class A materials (existing ASME approach), variable confidence index, data extrapolation, bounding value for SEE, and next steps.
The optimization of traditional electrocatalysts has reached a point where progress is impeded by fundamental physical factors including inherent scaling relations among thermokinetic characteristics of different elementary reaction steps, non-Nernstian behavior, and electronic structure of the catalyst. This suggests that the currently utilized classes of electrocatalysts may not be adequate for future needs. Our work reports on synthesis and characterization of a new class of materials based on 2D transition metal dichalcogenides including sulfides, selenides, and tellurides of group V and VI transition metals that exhibit excellent catalytic performance for both oxygen reduction and evolution reactions in an aprotic medium with Li salts. The reaction rates are much higher for these materials than previously reported catalysts for these reactions. The reasons for the high activity are found to be the metal edges with adiabatic electron transfer capability and a cocatalyst effect involving an ionic-liquid electrolyte. These new materials are expected to have high activity for other core electrocatalytic reactions and open the way for advances in energy storage and catalysis.
Abstract Sequence variation in related proteins is an important characteristic that modulates activity and selectivity. An example of a protein family with a large degree of sequence variation is that of bacterial sortases, which are cysteine transpeptidases on the surface of gram‐positive bacteria. Class A sortases are responsible for attachment of diverse proteins to the cell wall to facilitate environmental adaption and interaction. These enzymes are also used in protein engineering applications for sortase‐mediated ligations (SML) or sortagging of protein targets. We previously investigated SrtA from Streptococcus pneumoniae , identifying a number of putative β7–β8 loop‐mediated interactions that affected in vitro enzyme function. We identified residues that contributed to the ability of S. pneumoniae SrtA to recognize several amino acids at the P1′ position of the substrate motif, underlined in LPXT G , in contrast to the strict P1′ Gly recognition of SrtA from Staphylococcus aureus . However, motivated by the lack of a structural model for the active, monomeric form of S. pneumoniae SrtA, here, we expanded our studies to other Streptococcus SrtA proteins. We solved the first monomeric structure of S. agalactiae SrtA which includes the C‐terminus, and three others of β7–β8 loop chimeras from S. pyogenes and S. agalactiae SrtA. These structures and accompanying biochemical data support our previously identified β7–β8 loop‐mediated interactions and provide additional insight into their role in Class A sortase substrate selectivity. A greater understanding of individual SrtA sequence and structural determinants of target selectivity may also facilitate the design or discovery of improved sortagging tools.
A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorous assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.
We show that the N=(1,0) superconformal theory on a single M 5 brane on the ALE space of type G = A n , D n , E n , when compactified on T 2 , becomes a class S theory of type G on a sphere with two full punctures and a simple puncture. We study this relation from various viewpoints. Along the way, we develop a new method to study the 4d SCFT arising from the T 2 compactification of a class of 6d N=(1,0) theories we call very Higgsable.
In the present study, we introduced the nitrogenated heterocycles and fluorine atoms into the 2,5′-dibromo-4,5,2′-trihydroxyl diphenylmethanone (LM49), a bromophenol analog previously reported for its strong antioxidant ability involving in the Keap1–Nrf2 pathway. Twenty-seven fluorophenols 6a–6g, 8a–8k, 10a–10g, and 12a–12b were prepared, evaluated for their antioxidant activity in EA.hy926 cells, and investigated their interacted approach and probable mode of action with key protein Keap1 by molecular docking. Fluorophenols 6f, 8d, 8f, 8h, and 8i with EC{sub 50} values ranging from 0.82 to 6.71 µM were found to be more active compared with the standard control quercetin (EC{sub 50} = 18 µM). Among them, compound 8h with an EC{sub 50} value of 0.82 µM showed the identical activity to lead compound LM49 (EC{sub 50} = 0.7 µM). Moreover, the preferable water solubility and forming salt possibility of 8h contribute to its druggability. Further molecular docking of the optimal compound 8h with key protein Keap1 indicated that 8h stably bonded to the receptor protein by the formation of hydrogen bonds, the conjugated six-membered ring was close to the key residue Arg-415 attached to the Nrf2 on Keap1-Kelch, affecting its properties, and the change leaded to the dissociation of Nrf2 from the junction with Keap1-Kelch into the nucleus exerting its antioxidant protective effect. This study introduced a class of fluorophenols containing nitrogenated heterocycles for the development of novel Keap1-Nrf2 protein–protein interaction (PPI) inhibitors. Keap1-Kelch is suggested the most potential target protein for such class of halophenols.
This paper is concerned with well-posedness and energy decay rates to a class of nonlinear viscoelastic Kirchhoff plates. The problem corresponds to a class of fourth order viscoelastic equations of p-Laplacian type which is not locally Lipschitz. The only damping effect is given by the memory component. We show that no additional damping is needed to obtain uniqueness in the presence of rotational forces. Then, we show that the general rates of energy decay are similar to ones given by the memory kernel, but generally not with the same speed, mainly when we consider the nonlinear problem with large initial data.
The hopficity property in a well-known class of Abelian groups—completely decomposable torsion-free groups—as well as in a class of modules over generalized matrix rings is studied. Examples of non-Hopfian completely decomposable torsion-free group are constructed.
Given the explosive growth of the passenger vehicle market and energy demands in China, research on vehicle-use intensity and driver-travel patterns is critical for better assessing travel demand and its implications for alternative fuel vehicles, energy security, and environmental policies. This study attempts to estimate annual vehicle kilometers traveled (AVKT) per privately-owned passenger vehicle and their daily distance patterns by vehicle class and geographic region. The data sample from a survey consists of 169,292 privately owned passenger vehicles, made by 177 car manufacturers during 2003–2018, running in 82 cities from 27 provincial regions. The log-transformed average AVKT is estimated to be 12,377 km with 95% probability ranging from 5490 to 28,579 km. The investigation reveals that vehicles from South China have the highest AVKT at 13,320 km. Generally, vehicles in small cities have higher AVKT than in big cities, except AVKT of tier 1 cities being higher. Another trend is that more expensive or larger vehicles tend to be driven more. A model is fitted for estimating AVKT based on region, city type, automaker, price range, and certain vehicle features including class and age. Data of daily commuting distances in recent years are also analyzed. The average daily commuting distances typically range from 21 to 28 km. Using the validated Gamma distribution method, daily distance distributions are specified for different regions. It is found that 99% of the daily driving distance is no more than 88.0–112.0 km, depending on region. Utility factors of plug-in electric vehicles are also estimated to be much higher than those based on driving data in the USA. Finally, these findings suggest global mitigations strategies on vehicle fuel use, electrification, and greenhouse gases should consider vehicle-use intensity at the regional level.
The hub location and revenue management problems are two interesting research fields in the transportation and network design studies. The hub location model designs the transportation network structure and the revenue management model allocates the network’s capacity for customer classes based on their sensitivity to prices. In this paper, we consider the integrated hub location and revenue management problem in the airline industry to maximize the revenue of transportation network and minimize hub installation costs. p hubs have been chosen from a set of n nodes and connected to a central node based on star–star network design. The capacity of the installed links between the hubs and the central node and the hubs and non-hub nodes is limited. This limited capacity has been allocated to the stochastic demands of customer classes using the revenue management approach. A two-stage stochastic model has been derived to determine the locations of hubs and protection levels in the ticket sale process, and an efficient modification of genetic algorithm has been proposed for the large-scale problems. Numerical experiments have been carried out to assess the effectiveness of the proposed algorithm.
In this paper, we study the continuity of solution functions to a class of fuzzy differential equations (FDEs) in the form y{sup ′}(t)=((φ(t))/((t−α){sup p}))⊙y(t)+ψ(t), where the coefficient function ((φ(t))/((t−α){sup p})) is a discontinuous function at the point t=α and α is an inner point of the interval under study. At first, the continuity of solutions for the crisp case of the problem is investigated and those results are extended to the fuzzy case of the problem from the view point of strongly generalized differentiability (G-differentiability). Next, we obtain explicit formulas of solutions and the conditions of their existence for a special class of these problems. Finally, the results are illustrated by solving some examples.
A generalization of Dirac’s canonical quantization scheme for a system with second-class constraints is proposed, in which the fundamental commutation relations are constituted by all commutators between positions, momenta and Hamiltonian, so they are simultaneously quantized in a self-consistent manner, rather than by those between merely positions and momenta which leads to ambiguous forms of the Hamiltonian and the momenta. The application of the generalized scheme to the quantum motion on a torus leads to a remarkable result: the quantum theory is inconsistent if built up in an intrinsic geometric manner, whereas it becomes consistent within an extrinsic examination of the torus as a submanifold in three dimensional flat space with the use of the Cartesian coordinate system. The geometric momentum and potential are then reasonably reproduced. -- Highlights: •A generalization of Dirac’s canonical quantization is proposed for a system with second-class constraints. •Quantum motion on torus surface is explicitly treated to show how Schrödinger formalism is complementary to the Dirac one. •The embedding effect in quantum mechanics is originated from the quantization.
A novel recipe for exactly solving in finite terms a class of special differential Riccati equations is reported. Our procedure is entirely based on a successful resolution strategy quite recently applied to quantum dynamical time-dependent SU(2) problems. The general integral of exemplary differential Riccati equations, not previously considered in the specialized literature, is explicitly determined to illustrate both mathematical usefulness and easiness of applicability of our proposed treatment. The possibility of exploiting the general integral of a given differential Riccati equation to solve an SU(2) quantum dynamical problem, is succinctly pointed out. - Highlights: • A resolutive strategy for Liouville SU(2) dynamical problems is used to solve DREs. • A new class of exactly solvable Riccati equations is reported. • Many examples illustrate our method and provide explicit solutions of selected DREs.
The dimension two gauge invariant non-local operator A{sub min}{sup 2}, obtained through the minimization of ∫d{sup 4}xA{sup 2} along the gauge orbit, allows to introduce a non-local gauge invariant configuration A{sub μ}{sup h} which can be employed to built up a class of Euclidean massive Yang–Mills models useful to investigate non-perturbative infrared effects of confining theories. A fully local setup for both A{sub min}{sup 2} and A{sub μ}{sup h} can be achieved, resulting in a local and BRST invariant action which shares similarities with the Stueckelberg formalism. Though, unlike the case of the Stueckelberg action, the use of A{sub min}{sup 2} gives rise to an all orders renormalizable action, a feature which will be illustrated by means of a class of covariant gauge fixings which, as much as ’t Hooft’s R{sub ζ}-gauge of spontaneously broken gauge theories, provide a mass for the Stueckelberg field.
Highlights: •The embedding of curved spacetime in higher-dimensional flat spacetime is discussed. •The focus is on two diverse models of embedding class one. •The first model is a complete wormhole solution including the junction conditions. •The second is a new model to explain the flat galactic rotation curves without the need for dark matter. -- Abstract: Embedding theorems have continued to be a topic of interest in the general theory of relativity since these help connect the classical theory to higher-dimensional manifolds. This paper deals with spacetimes of embedding class one, i.e., spacetimes that can be embedded in a five-dimensional flat spacetime. These ideas are applied to two diverse models, a complete solution for a charged wormhole admitting a one-parameter group of conformal motions and a new model to explain the flat rotation curves in spiral galaxies without the need for dark matter.
Highlights: • Latent class analysis identified subgroups of children with unique chemical exposure profiles. • Three subgroups were identified. • One subgroup comprised children with high multiple co-exposures. • Latent classes were sometimes associated with lymphocyte and neutrophil counts. Children are exposed to multiple potentially harmful chemicals simultaneously. Efforts to understand the patterns and consequences of these exposures have been hampered by statistical limitations in estimations of higher order interactions.
Biofuel production from lignocellulosic biomass offers a transformative solution to reduce global fossil fuel dependency. Certain thermophilic anaerobes, including Clostridium thermocellum, show promise for renewable ethanol production due to their ability to break down plant material at high temperatures. However, achieving commercially viable ethanol yields has proven challenging despite extensive engineering efforts. Here, we characterized 27 ferredoxin:NADP + oxidoreductase (Fnor) enzymes for their enzyme activity, nicotinamide cofactor specificity, thermotolerance, and functional expression in C. thermocellum . We identified a subset of 10 of these enzymes as a novel class of Fnor enzymes suited for metabolic pathways aimed at high-titer ethanol production. When expressed in engineered C. thermocellum , these enzymes increased ethanol production up to 2.2-fold. These findings establish a novel ethanol pathway and provide insights into physiological roles and biotechnological applications of this new class of Fnor enzymes.
This study is aimed to test a postprostatectomy volumetric-modulated arc therapy (VMAT) planning class solution. The solution applies to both the progressive resolution optimizer algorithm version 2 (PRO 2) and the algorithm version 3 (PRO 3), addressing the effect of an upgraded algorithm. A total of 10 radical postprostatectomy patients received 68 Gy to 95% of the planning target volume (PTV), which was planned using VMAT. Each case followed a set of planning instructions; including contouring, field setup, and predetermined optimization parameters. Each case was run through both algorithms only once, with no user interaction. Results were averaged and compared against Radiation Therapy Oncology Group (RTOG) 0534 end points. In addition, the clinical target volume (CTV) D{sub 100}, PTV D{sub 99}, and PTV mean doses were recorded, along with conformity indices (CIs) (95% and 98%) and the homogeneity index. All cases satisfied PTV D{sub 95} of 68 Gy and a maximum dose < 74.8 Gy. The average result for the PTV D{sub 99} was 64.1 Gy for PRO 2 and 62.1 Gy for PRO 3. The average PTV mean dose for PRO 2 was 71.4 Gy and 71.5 Gy for PRO 3. The CTV D{sub 100} average dose was 67.7 and 68.0 Gy for PRO 2 and PRO 3, respectively. The mean homogeneity index for both algorithms was 0.08. The average 95% CI was 1.17 for PRO 2 and 1.19 for PRO 3. For 98%, the average results were 1.08 and 1.12 for PRO 2 and PRO 3, respectively. All cases for each algorithm met the RTOG organs at risk dose constraints. A successful class solution has been established for prostate bed VMAT radiotherapy regardless of the algorithm used.