Constituent Pairs Research Articles

Assessing hydrophobic deep eutectic solvents for intramolecular excimer formation.

Intramolecular excimer formation by a dipyrenyl probe, 6-(1-pyrenyl)hexyl-11(1-pyrenyl)-undecanoate [1-Py(CH2)10COO(CH2)61-Py], is used to assess hydrophobic deep eutectic solvents (HDESs) for the purpose. n-Decanoic acid (DA), L(-)-menthol (Men) and thymol (Thy) have been utilized to form HDESs with different pairs of constituents in different molar ratios, namely Men : DA (2 : 1, 1 : 1, and 1 : 2), Thy : DA (2 : 1, 1 : 1, and 1 : 2), and Thy : Men (5 : 1, 2 : 1, 1 : 1, 1 : 2, and 1 : 5). The maximum of the excimer-to-monomer emission intensity ratio, (IE/IM)max, is observed at 343.15-353.15 K for all DESs irrespective of the constitution, and it varies in a narrow range exhibiting no correlation with the dynamic viscosity (η) of the DES which varies between 2.05 and 3.56 mPa s. Excited-state intensity decay data reveal excimer dissociation back to the excited monomer to be negligible in all DESs at lower temperatures (T ≤ 323.15 K); the simplistic Birks scheme is followed at higher temperatures (T > 323.15 K). The rate constant for excimer formation/association, ka, ranges from (3.00 ± 0.50) × 106 s-1 to (103 ± 10) × 106 s-1, which is similar to that reported in other media. The temperature-dependence of the equilibrium constant for excimer formation follows the van't Hoff equation with recovered standard enthalpy (ΔaH*⊖) and standard entropy (ΔaS*⊖) changes, indicating the reversible intramolecular excimer formation to be exothermic and energetically-favorable but entropically unfavorable. A plot of kavs. T/η for all the DES systems investigated exhibits a fairly good linear correlation, indicating the adherence to the Stokes-Einstein formulation within the HDESs further emphasizing the homogeneous nature of the solubilizing media. The work helps to highlight the potential of HDESs for intramolecular excimer formation involving non-polar reactants.

Liquid-liquid equilibrium data for the ternary system based on ionic liquid + organic solvents + water at 298 K and atmospheric pressure applied in antidepressant partitioning

Antidepressants are drugs widely used in nervous disorders, such as anxiety, depression, and panic, and are eliminated through the urinary system. In bodies of water, they present high persistence and toxicity, even at low concentrations, conforming to the classification of emerging micropollutants. This work addresses the construction of phase diagrams for different biphasic systems, based on ionic liquids (ILs) and organic solvents, and their subsequent application in the partitioning of antidepressants such as fluoxetine hydrochloride, paroxetine hydrochloride and sertraline hydrochloride. The phase diagrams were measured gravimetrically at 298.15 ± 1.00 K and atmospheric pressure using the turbidity method. The ILs of the imidazolium family, with shorter chain length [C2mim]+, were the only ones able to form biphasic systems using 1,3-dioxolane. The driving force for phase separation is the comparison of hydrophobic/hydrophilic characteristics between the constituents. In this sense, the pair of constituents [C2min][OAc] and 1,3-dioxolane provided the phase diagram with the largest biphasic area. The partitioning of antidepressants was studied in systems formed by IL (25 wt%) + 1,3-dioxolane (50 wt%) + water (25 wt%) containing 1.05 µg·L−1 of fluoxetine hydrochloride, 1.42 µg·L−1 of paroxetine hydrochloride or 0.23 µg·L−1 sertraline hydrochloride at 298.15 ± 1.00 K and atmospheric pressure. The partitioning followed the characteristics of antidepressant σ-profiles generated through COSMO-RS. The recoveries were high, and the proposed systems were shown to promote the selective isolation of pairs of these antidepressants.

Surface tension and parachor for a new low-GWP refrigerant R1123/R32/R1234yf and its constituent binary pairs

Trifluoroethene R1123 is expected to be a low GWP refrigerant; however, it needs to be mixed with other stable refrigerants to avoid a disproportional reaction. This paper delivers one of the essential thermophysical properties surface tension for a low-GWP refrigerant mixture R1123/R32/1234yf measured by the differential capillary rise method in the temperature range from 225 to 345 K. The propagated uncertainty in surface tension with a 95% confidence level was typically 0.15 mNm−1. From the measured surface tension and calculated saturation densities, the parachor of R32 and R1123 were determined to be 91.6 and 123.3, respectively. The parachor of R1234yf was slightly dependent on a temperature, T, as 181.44−0.0319T. The variation in the surface tension of binary pairs against the composition was predicted by the correlation proposed by Di Nicola et al. (2018) and the parachor method with sufficient accuracy. Furthermore, the surface tension of ternary mixture R1123/R32/1234yf at compositions of 60/22/18 mass% and 22/70/08 mass% was also predicted by the parachor method with sufficient accuracy. Nevertheless, a slight deviation was confirmed at temperatures below 260 K. The prediction would be improved with subsequent studies in phase equilibrium. (191 words).

Dynamical properties of gaussian chains and loops with long-range interactions

Various authors have invoked discretized fractional Brownian motion (fBm) as a model for chain polymers with long-range interaction of monomers along the chain. We show that for these, in contrast to the Brownian case, linear forces are acting between all pairs of constituents, attractive for small Hurst index H and mostly repulsive when H is larger than 1/2. In the second part of this paper, we extend this study to periodic fBm and related models with a view to ring polymers with long range interactions.

Synthesis Route, Microstructural Evolution, and Mechanical Property Relationship of High-Entropy Alloys (HEAs): A Review.

Microstructural phase evolution during melting and casting depends on the rate of cooling, the collective mobility of constituent elements, and binary constituent pairs. Parameters used in mechanical alloying and spark plasma sintering, the initial structure of binary alloy pairs, are some of the factors that influence phase evolution in powder-metallurgy-produced HEAs. Factors such as powder flowability, laser power, powder thickness and shape, scan spacing, and volumetric energy density (VED) all play important roles in determining the resulting microstructure in additive manufacturing technology. Large lattice distortion could hinder dislocation motion in HEAs, and this could influence the microstructure, especially at high temperatures, leading to improved mechanical properties in some HEAs. Mechanical properties of some HEAs can be influenced through solid solution hardening, precipitation hardening, grain boundary strengthening, and dislocation hardening. Despite the HEA system showing reliable potential engineering properties if commercialized, there is a need to examine the effects that processing routes have on the microstructure in relation to mechanical properties. This review discusses these effects as well as other factors involved.

THEORETICAL RESEARCH OF THE RECIPE OF SUPPLEMENTARY MATERIAL OF TECHNOLOGICAL PURPOSE FOR ENSURING ECOLOGICAL BEZ-PEPYKHYRA VYROPYRA

In the manufacture (repair) of products of transport pipeline systems, auxiliary materials are widely used, which play the role of lubricants, cooling, cleaning and other substances. Special requirements are imposed on the composition of such substances, which are developed in accordance with the technological instructions, since they are, as a rule, chemically active, surfactants of organic and inorganic origin. Therefore, not only the quality of processing of structural elements of transport pipeline systems, but also the environmental safety of the techno-logical process of their manufacture (repair) depends on the composition and mass fraction of ingredients in these substances. Of particular importance in solving problems on this problem belongs to the theory of predicting the formation of the composition of effective auxiliary materials, assessed by technological, economic, sanitary and hygienic and other indicators that are directly related to the formulation of these materials. The theoretical foundations and methods for creating auxiliary materials for technological purposes in the practice of specialized enterprises are implemented using the example of a simplified technological scheme. Ac-cording to this scheme, the action of each source of deviations (errors in the composition of the auxiliary material) is evaluated separately, and the other sources are “off,” that is, the principle of superposition is implemented. For a qualitative reflection of the technological uniformity of any two constituent ingredients in terms of their influ-ence coefficients, the concept of "intersection" is used, and all possible intersections between pairs of constituents form a square matrix of intersections of dimensions. The level of effective homogeneity, which predetermines the quality of the auxiliary material for technological purposes, depends on two groups of indicators that equally affect this effective homogeneity. Thus, any variant of the formulation of an auxiliary material consisting of groups of constituents with the maximum level of objective closure always corresponds to a certain variant of an ordered series of ingredients. Keywords: auxiliary material, transport pipeline systems, error, quality, reliability, environmental safety, manufacturing, repair.

Identifying group contributions in NBA lineups with spectral analysis

We address the question of how to quantify the contributions of groups of players to team success. Our approach is based on spectral analysis, a technique from algebraic signal processing, which has several appealing features. First, our analysis decomposes the team success signal into components that are naturally understood as the contributions of player groups of a given size: individuals, pairs, triples, fours, and full five-player lineups. Secondly, the decomposition is orthogonal so that contributions of a player group can be thought of as pure: Contributions attributed to a group of three, for example, have been separated from the lower-order contributions of constituent pairs and individuals. We present detailed a spectral analysis using NBA play-by-play data and show how this can be a practical tool in understanding lineup composition and utilization.

UsingWomb Grammars for Inducing the Grammar of a Subset of Yorùbá Noun Phrases

We address the problem of inducing the grammar of an under-resourced language, Yorùbá, from the grammar of English using an efficient and, linguistically savvy, constraint solving model of grammar induction –Womb Grammars (WG). Our proposed methodology adapts WG for parsing a subset of noun phrases of the target language Yorùbá, from the grammar of the source language English, which is described as properties between pairs of constituents. Our model is implemented in CHRG (Constraint Handling Rule Grammar) and, it has been used for inducing the grammar of a useful subset of Yorùbá Noun Phrases. Interesting extensions to the original Womb Grammar model are presented, motivated by the specific needs of Yorùbá and, similar tone languages.

Global Longitudinal Strain, Ejection Fraction, Ventriculo‐Arterial Coupling and Their Interrelationships in Heart Failure Patients with Different Phenotypes

Ejection fraction (EF) is a popular metric to evaluate left ventricular (LV) systolic function. The EF is a ratio, based on paired volume measurements, similar as the more recently introduced ventriculo‐arterial coupling (VAC) index, being the ratio of two elastances. Their dimensionless nature requires consideration of the associated companion (i.e., the hypotenuse calculated from the constituent pair and denoted as EFC and VACC, respectively). This insight becomes clear when considering the LV volume domain representation.Global longitudinal strain (GLS) has been advanced as a preferred alternative for EF. Reportedly, the connection between EF and GLS is weak, thus confirming that these ratio‐based metrics focus on partial and likely dissimilar aspects of LV pump function. To overcome these limitations the present study addresses the relationships between GLS and EF or VAC (assuming vanishing intercept), as well as the newly introduced complementary metrics EFC and VACC.In 25 heart failure (HF) patients (43 – 83 years, 9 women) end‐systolic volume (ESV), end‐diastolic volume (EDV), diastolic interventricular septal thickness (IVST), and posterior wall thickness (PWT) were determined by echocardiography. Data are analyzed following informed consent. IVST and PWT were used to derive LV mass (LVM). GLS was obtained via speckle tracking echocardiography. When appropriate, these data were indexed (i) to body surface area (BSA).Significant sex‐specific differences were found for BSA (P<0.0001), LVM (P=0.04) and stroke volume (P=0.02), but the latter not when normalized to BSA. The volume regulation graph (VRG) which relates ESV to EDV yields R=0.92, implying an inverse nonlinear relationship, either logarithmic or of the more robust type EF = 1+c1ESV / (c2+ESV), where c1 and c2 are population‐based constants. These data indicate that a sex‐specific cut‐off at ESVi=30 mL/m2 for men and at ESVi=20 mL/m2 for women separates the two major HF phenotypes, also demonstrating that the current practice of phenotyping via the ratio based metric EF is undesired and not required. LVM correlates (P<0.001) with EDV (R=0.76) and with EFC (R=0.76). GLS moderately correlates with EF (R=−0.63, P<0.001), VAC (R=−0.65, P<0.001), EFC (R=0.49, P=0.025), and with VACC (R=0.43, P=0.03).The interpretation of EF, VAC and GLS in terms of physiology is debatable, as each refers to a ratio without physical dimension(s). In contrast, EFC and VACC carry a clear physical unit (namely mL), comparable to the primary variables ESV and EDV. The fact that GLS only moderately correlates with major clinically used metrics such as EF and VAC, suggests that there is a future place for the GLS companion, which deserves evaluation of its physiology‐based impact.Support or Funding InformationnoneEjection fraction (EF) versus end‐systolic volume index (ESVi) for two heart failure (HF) phenotypes, distinguished on the basis of a criterion applied to ESVi, which differs for women (red line) and men (blue line).Figure 1

Identification of UNIQUAC binary interaction parameters in liquid-liquid equilibrium

An algorithm is presented for the estimation of the UNIQUAC interaction parameters for liquid-liquid equilibrium of ternary systems. The algorithm is based on two optimization levels. In the inner level the algorithm performs the minimization of an objective function based on the isoactivity conditions. The outer level aims to minimize the error between calculated and experimental compositions. The Common Tangent Plane condition is checked at the end to guarantee a thermodynamically consistent representation of the phase behavior of ternary liquid systems.The algorithm is challenged with a historical Type 1 ternary liquid-liquid equilibrium system from the seminal study of Anderson and Prausnitz in which the authors showed the limitations of the original UNIQUAC model and justified its amendment in the modified UNIQUAC model. The present algorithm makes available single temperature and temperature-dependent interaction parameters enabling accurate and thermodynamically correct description of the experimental data with the original UNIQUAC model, therefore without the need of any model modification. This outcome does not change when the interaction parameters from the binary partially miscible constituent pair are first regressed and kept constant during the estimation of the remaining parameters on ternary equilibrium data. This investigation confirms that a model cannot be judged if the correctness of the model parameters has not been proved first.

Word Reordering for Translation into Korean Sign Language Using Syntactically-guided Classification

Machine translation aims to break the language barrier that prevents communication with others and increase access to information. Deaf people face huge language barriers in their daily lives, including access to digital and spoken information. There are very few digital resources for sign language processing. In this article, we present a transfer-based machine translation system for translating Korean-to-Korean Sign Language (KSL) glosses, mainly composed of (1) dictionary-based lexical transfer and (2) a hybrid syntactic transfer based on a data-driven model. In particular, we formulate complicated word reordering problems in syntactic transfer as multi-class classification tasks and propose “syntactically guided” data-driven syntactic transfer. The core part of our study is a neural classification model for reordering order-important constituent pairs with a reordering task that is newly designed for Korean-to-KSL translation. The experiment results evaluated on news transcript data show that the proposed system achieves a BLEU score of 0.512 and a RIBES score of 0.425, significantly improving upon the baseline system performance.

Tunable On‐Chip Sources with Aperiodic Metasurface

AbstractSurface plasmons show tremendous capability in integrated communication, quantum computing and sensing. Excitations and manipulations of surface plasmons are essential in developing integrated photonic devices. Here, a systematic study of tunable emission of surface plasmons with an eightfold quasicrystal metasurface, which acts as an on‐chip source, is presented. It is shown that the quasicrystal structure can switch on or off the surface plasmons propagation channels in the desired direction. Meanwhile, such a quasicrystal structure can be polarization‐dependent or polarization‐independent based on different constituent slit pairs. The proposed quasicrystal design provides more freedom for steering surface plasmons in the launching process. Thus, it may significantly simplify the design and fabrication of integrated plasmonic devices.

Gestational weight gain impacts on DNA methylation and protein expression of leptin receptor in the newborn

The present study examines the extent to which stronger belief in either extrasensory perception, psychokinesis or life-after-death is associated with a proneness to making conjunction errors (CEs). One hundred and sixty members of the UK public read eight hypothetical scenarios and for each estimated the likelihood that two constituent events alone plus their conjunction would occur. The impact of paranormal belief plus constituents’ conditional relatedness type, estimates of the subjectively less likely and more likely constituents plus relevant interaction terms tested via three Generalized Linear Mixed Models. General qualification levels were controlled for. As expected, stronger PK beliefs and depiction of a positively conditionally related (verses conditionally unrelated) constituent pairs predicted higher CE generation. ESP and LAD beliefs had no impact with, surprisingly, higher estimates of the less likely constituent predicting fewer - not more - CEs. Theoretical implications, methodological issues and ideas for future research are discussed.

Local structure and vibrational properties of molten lead halides PbX2 (X = Cl, Br, I) from ab initio molecular dynamics

Ab initio molecular dynamics (AIMD) was applied to calculate the local structure and dynamics parameters of molten lead halides PbX2 (X = Cl, Br, I). The thoroughness of our approach is substantiated by the variation of both cell size and temperature. The total duration of AIMD runs amounted to 600 ps. It was found that molten lead chlorides exhibit weak binding of the local structure. The latter was analyzed by means of radial distribution functions for each pair of salt constituents. The radial distribution functions exhibit pronounced liquid-like damped oscillations and weakly depend on the cell size. In terms of vibrational properties, we highlight the frequencies of 125 cm−1 and 80 cm−1 which relate to the Pb-Br and Pb-I vibrations respectively, both of a short lifetime. These results are additionally supported by the calculated self-diffusion coefficients which concur closely with experimental values.

Are there effects of a match between learning style and teaching style in an EFL classroom?

ABSTRACTPurpose. This study aimed to explore whether a match between learning style and teaching style in English as a foreign language (EFL) class affects two student variables: proficiency and motivation to learn English. Design/methodology/approach. Participants consisted of nine EFL teachers and 331 Japanese undergraduate students who were required to take EFL courses. To examine learning style and teaching style, we applied the Kolb Learning Style Inventory and the Kolb Educator Role Profile, respectively. Findings. We created groups for student-teacher match and student-teacher mismatch (i.e., student’s learning style vs. teacher’s teaching style). The match group including four matched learning style–teaching style pairs was significantly related to proficiency and motivation, while the mismatch group including all other pairs was also significantly related to them. When further analysing the four constituent pairs within the match group, results varied in effect, depending on not only the pair of learning and teaching style but also the variables. Originality/value. This study was the first to examine how specific matched learning style–teaching style pairs affect proficiency and motivation. The results add to the literature on the mixed effects of matched versus mismatched styles, highlighting the complexity of the relationship and the possible reasons for some of the effects.

Diversity in Mechanical Response in Donor–Acceptor Coupled Cocrystal Stoichiomorphs Based on Pyrene and 1,8-Dinitroanthraquinone Systems

Cocrystals are an emerging class of molecular materials that can achieve desirable properties by selecting suitable constituent molecules and can also exhibit polymorphism, but a different stoichiometry of the constituent molecular pairs can also give different structures having different properties, which is of interest. With an aim of understanding the influence of the stoichiometric ratio of the π-conjugated donor and acceptor in altering the crystal packing and their mechanical properties, we have synthesized two stoichiomorphs, namely, DQP1 (1A:1D) and DQP2 (1A:0.5D), along with their polymorphs, DQP3 (1A:2*0.5D) and DQP4 (2A:1D), respectively, involving pyrene as the donor (D) and 1,8-dinitroanthraquinone as an acceptor (A). Both stoichiomorphs have a layered structure with different packing patterns. DQP1 and DQP3 have −ADADAD– type, whereas DQP2 and DQP4 have −ADAADA– type of layered packing. DQP4 shows a thermosalient effect, and on heating converts into the polymorph DQP2 via single crystal to s...

Deep learning improves prediction of drug–drug and drug–food interactions

Drug interactions, including drug-drug interactions (DDIs) and drug-food constituent interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug events (ADEs), with causal mechanisms often unknown. Several computational methods have been developed to better understand drug interactions, especially for DDIs. However, these methods do not provide sufficient details beyond the chance of DDI occurrence, or require detailed drug information often unavailable for DDI prediction. Here, we report development of a computational framework DeepDDI that uses names of drug-drug or drug-food constituent pairs and their structural information as inputs to accurately generate 86 important DDI types as outputs of human-readable sentences. DeepDDI uses deep neural network with its optimized prediction performance and predicts 86 DDI types with a mean accuracy of 92.4% using the DrugBank gold standard DDI dataset covering 192,284 DDIs contributed by 191,878 drug pairs. DeepDDI is used to suggest potential causal mechanisms for the reported ADEs of 9,284 drug pairs, and also predict alternative drug candidates for 62,707 drug pairs having negative health effects. Furthermore, DeepDDI is applied to 3,288,157 drug-food constituent pairs (2,159 approved drugs and 1,523 well-characterized food constituents) to predict DFIs. The effects of 256 food constituents on pharmacological effects of interacting drugs and bioactivities of 149 food constituents are predicted. These results suggest that DeepDDI can provide important information on drug prescription and even dietary suggestions while taking certain drugs and also guidelines during drug development.

Layer‐by‐Layer Assembly of κ‐Casein Amyloid Fibrils for the Preparation of Hollow Microcapsules

AbstractAmyloids are known to self‐assemble into fibril forms derived from natural or artificial proteins exhibiting superior mechanical properties, stability, and biocompatibility. However, few studies have investigated the applications of amyloid fibrils. Herein, the layer‐by‐layer growth of zwitterionic κ‐casein amyloid fibrils (κCFs) to prepare stable hollow microcapsules is investigated, which is potentially applicable to drug delivery systems. The growth of κCFs increases linearly when electrostatic interactions between the constituent pair become more prominent, for instance, cationic κCFs paired with poly(sodium 4‐styrenesulfonate) (PSS), and anionic κCFs paired with poly(diallyldimethylammonium chloride). In contrast, the increase in film thickness shows the exponential‐to‐linear transition when hydrogen bonding is responsible for adsorption between cationic κCFs and poly(acrylic acid) (PAA). It is thus concluded that stable κCF/PSS hollow microcapsules are prepared by using the electrostatic interaction. However, the κCF/PAA hollow microcapsules are ruptured due to the breakage of hydrogen bonding upon removal of sacrificial templates.

Paranormal belief and errors of probabilistic reasoning: The role of constituent conditional relatedness in believers' susceptibility to the conjunction fallacy.

The present study examines the extent to which stronger belief in either extrasensory perception, psychokinesis or life-after-death is associated with a proneness to making conjunction errors (CEs). One hundred and sixty members of the UK public read eight hypothetical scenarios and for each estimated the likelihood that two constituent events alone plus their conjunction would occur. The impact of paranormal belief plus constituents' conditional relatedness type, estimates of the subjectively less likely and more likely constituents plus relevant interaction terms tested via three Generalized Linear Mixed Models. General qualification levels were controlled for. As expected, stronger PK beliefs and depiction of a positively conditionally related (verses conditionally unrelated) constituent pairs predicted higher CE generation. ESP and LAD beliefs had no impact with, surprisingly, higher estimates of the less likely constituent predicting fewer - not more - CEs. Theoretical implications, methodological issues and ideas for future research are discussed.

Syntax- and semantic-based reordering in hierarchical phrase-based statistical machine translation

A syntax-based reordering model (RM) for SMT system is proposed.Our RM predicts the orientation between syntactic dependants of the source sentence.We enrich the proposed RM with semantic features, so it can perform semantic generalization.Our RM outperforms the baseline and two competing RMs in terms of BLEU and TER. We present a syntax-based reordering model (RM) for hierarchical phrase-based statistical machine translation (HPB-SMT) enriched with semantic features. Our model brings a number of novel contributions: (i) while the previous dependency-based RM is limited to the reordering of head and dependant constituent pairs, we also model the reordering of pairs of dependants; (ii) Our model is enriched with semantic features (Wordnet synsets) in order to allow the reordering model to generalize to pairs not seen in training but with equivalent meaning. (iii) We evaluate our model on two language directions: English-to-Farsi and English-to-Turkish. These language pairs are particularly challenging due to the free word order, rich morphology and lack of resources of the target languages.We evaluate our RM both intrinsically (accuracy of the RM classifier) and extrinsically (MT). Our best configuration outperforms the baseline classifier by 529% on pairs of dependants and by 1230% on head and dependant pairs while the improvement on MT ranges between 1.6% and 5.5% relative in terms of BLEU depending on language pair and domain. We also analyze the value of the feature weights to obtain further insights on the impact of the reordering-related features in the HPB-SMT model. We observe that the features of our RM are assigned significant weights and that our features are complementary to the reordering feature included by default in the HPB-SMT model.