Asymmetric Underlying Mechanisms of Relation-Based and Property-Based Noun–Noun Conceptual Combination

Conceptual combination is a fundamental human cognitive ability by which people can experience infinite thinking by artfully combining finite knowledge. For example, one can instantly combine “cactus” and “fish” together as “prickly fish” even if one has never previously heard of a “cactus fish.” Although two major combinatorial types—property and relational combinations—have been identified, the underlying processes of each remain elusive. This study investigates the asymmetric processing mechanisms underlying property and relational combinations by examining differential semantic activation during noun–noun conceptual combination. Across two experiments utilizing each combinatorial process as semantic priming and implementing a lexical decision task immediately after combination, we measure and compare the semantic activation patterns of intrinsic and extrinsic semantic features in these two combinatorial types. We found converging evidence that property and relational combinations involve asymmetric semantic information and entail distinct processing mechanisms. In property combination, the intrinsic feature in the modifier concept showed greater activation than the semantic feature of the same dimension in the head concept. In contrast, in relational combination, the extrinsic semantic feature in the head concept and the whole modifier concept showed similar levels of activation. Moreover, our findings also showed that these patterns of semantic activation occurred only when the combinatorial process was complete, indicating that accessing the same lexical-semantic information is not sufficient to observe asymmetric patterns. These findings demonstrate that property combination involves replacing a specific semantic feature of the head noun with that of the modifier noun, whereas relational combination involves completing the semantic feature of the head noun with the whole modifier concept. We discuss the implications of these findings, research limitations, and future research directions.

APPLICATION OF VIBRATION EFFECTS IN BIOFUEL PRODUCTION

The considered effective way of processing by-products of biofuel production. The increase in the productivity of the technological line is achieved through the introduction of new vibration equipment for the primary purification of raw glycerin. This study proposes a new approach to determine the efficient operation of a new machine, which is useful for the purification of glycerol based on the combinatorial process of centrifugation and vibration separation. The mathematical mechanical-rheological evaluations are developed based on the experimental results. Has been proposed to evaluate the rheological characteristics of raw glycerin purification based on the experimental testing. A compression device has been used to determine the value of the unilateral deformation of this material, which allows simulating a condition of a material at various technological modes of processing. In this study, the changes of material properties under centrifugation and vibration separation processes in a vibrocentric machine have been investigated. At a choice of optimum technological parameters of processing of food masses by means of vibration methods of rheology are widely applied. In particular, the interaction of the working body of the machine with the treated environment. In order to find the optimal parameters of the technological regime, the process was considered comprehensively from the standpoint of mechanics and rheology. The methods of mechanics describe the interaction of the working body with the treated environment as a mechanical object; rheology, in turn, allows you to reveal the internal processes in the environment. The system under study can be attributed to the elastic-viscous medium, which is described by a phenomenological model consisting of interconnected elastic and viscous elements.

Integrative Ranking of Enhancer Networks Facilitates the Discovery of Epigenetic Markers in Cancer

Regulation of gene expression through multiple epigenetic components is a highly combinatorial process. Alterations in any of these layers, as is commonly found in cancer diseases, can lead to a cascade of downstream effects on tumor suppressor or oncogenes. Hence, deciphering the effects of epigenetic alterations on regulatory elements requires innovative computational approaches that can benefit from the huge amounts of epigenomic datasets that are available from multiple consortia, such as Roadmap or BluePrint. We developed a software tool named IRENE (Integrative Ranking of Epigenetic Network of Enhancers), which performs quantitative analyses on differential epigenetic modifications through an integrated, network-based approach. The method takes into account the additive effect of alterations on multiple regulatory elements of a gene. Applying this tool to well-characterized test cases, it successfully found many known cancer genes from publicly available cancer epigenome datasets.

Integrative Ranking Of Enhancer Networks Facilitates The Discovery Of Epigenetic Markers In Cancer

Regulation of gene expression through multiple epigenetic components is a highly combinatorial process. Alterations in any of these layers, as is commonly found in cancer diseases, can lead to a cascade of downstream effects on tumor suppressor or oncogenes. Hence, deciphering the effects of epigenetic alterations on regulatory elements requires innovative computational approaches that can benefit from the huge amounts of epigenomic datasets that are available from multiple consortia, such as Roadmap or BluePrint. We developed a software tool named Irene (Integrative Ranking of Epigenetic Network of Enhancers), which performs quantitative analyses on differential epigenetic modifications through an integrated, network-based approach. The method takes into account the additive effect of alterations on multiple regulatory elements of a gene. Applying this tool to well-characterized test cases, it successfully found many known cancer genes from publicly available cancer epigenome datasets.

5-Hydroxyindole-Based EZH2 Inhibitors Assembled via TCCA-Catalyzed Condensation and Nenitzescu Reactions

5-Hydroxyindole derivatives have various demonstrated biological activities. Herein, we used 5-hydroxyindole as a synthetic starting point for structural alterations in a combinatorial process to synthesize 22 different compounds with EZH2 inhibitor pharmacophores. A series of 5-hydroxyindole-derived compounds were screened inhibitory activities against K562 cells. According to molecular modeling and in vitro biological activity assays, the preliminary structure-activity relationship was summarized. Compound L–04 improved both the H3K27Me3 reduction and antiproliferation parameters (IC50 = 52.6 μM). These findings revealed that compound L–04 is worthy of consideration as a lead compound to design more potent EZH2 inhibitors. During the preparation of compounds, we discovered that trichloroisocyanuric acid (TCCA) is a novel catalyst which demonstrates condensation-promoting effects. To gain insight into the reaction, in situ React IR technology was used to confirm the reactivity. Different amines were condensed in high yields with β-diketones or β-ketoesters in the presence of TCCA to afford the corresponding products in a short time (10~20 min), which displayed some advantages and provided an alternative condensation strategy.

More than five-twelfths of the zeros of $$\zeta $$ are on the critical line

The second moment of the Riemann zeta-function twisted by a normalized Dirichlet polynomial with coefficients of the form $$(\mu \star \Lambda _1^{\star k_1} \star \Lambda _2^{\star k_2} \star \cdots \star \Lambda _d^{\star k_d})$$(μ⋆Λ1⋆k1⋆Λ2⋆k2⋆⋯⋆Λd⋆kd) is computed unconditionally by means of the autocorrelation of ratios of $$\zeta $$ζ techniques from Conrey et al. (Proc Lond Math Soc (3) 91:33–104, 2005), Conrey et al. (Commun Number Theory Phys 2:593–636, 2008) as well as Conrey and Snaith (Proc Lond Math Soc 3(94):594–646, 2007). This in turn allows us to describe the combinatorial process behind the mollification of $$\begin{aligned} \zeta (s) + \lambda _1 \frac{\zeta '(s)}{\log T} + \lambda _2 \frac{\zeta ''(s)}{\log ^2 T} + \cdots + \lambda _d \frac{\zeta ^{(d)}(s)}{\log ^d T}, \end{aligned}$$ζ(s)+λ1ζ′(s)logT+λ2ζ′′(s)log2T+⋯+λdζ(d)(s)logdT,where $$\zeta ^{(k)}$$ζ(k) stands for the kth derivative of the Riemann zeta-function and $$\{\lambda _k\}_{k=1}^d$${λk}k=1d are real numbers. Improving on recent results on long mollifiers and sums of Kloosterman sums due to Pratt and Robles (Res Number Theory 4:9, 2018), as an application, we increase the current lower bound of critical zeros of the Riemann zeta-function to slightly over five-twelfths.