First-order Variables Research Articles

Torsional Newton–Cartan geometry from Galilean gauge theory

Using the recently advanced Galilean gauge theory (GGT) we give a comprehensive construction of torsional Newton–Cartan (NC) geometry. The coupling of a Galilean symmetric model with background NC geometry following GGT is illustrated by a free nonrelativistic scalar field theory. The issue of spatial diffeomorphism (Son and Wingate 2006 Ann. Phys. 321 197–224; Banerjee et al 2015 Phys. Rev. D 91 084021) is focussed from a new angle. The expression of the torsionful connection is worked out, which is in complete parallel with the relativistic theory. Also, smooth transition of the connection to its well known torsionless expression is demonstrated. A complete (implicit) expression of the torsion tensor for the NC spacetime is provided where the first-order variables occur in a suggestive way. The well known result for the temporal part of torsion is reproduced from our expression.

Modeling and Language Extensions

Answer set programming (ASP) has emerged as an approach to declarative problem solving based on the stable model semantics for logic programs. The basic idea is to represent a computational problem by a logic program, formulating constraints in terms of rules, such that its answer sets correspond to problem solutions. To this end, ASP combines an expressive language for high-level modeling with powerful low-level reasoning capacities, provided by off-the-shelf tools. Compact problem representations take advantage of genuine modeling features of ASP, including (first-order) variables, negation by default, and recursion. In this article, we demonstrate the ASP methodology on two example scenarios, illustrating basic as well as advanced modeling and solving concepts. We also discuss mechanisms to represent and implement extended kinds of preferences and optimization. An overview of further available extensions concludes the article.

On decidability of recursive weighted logics

In this paper, we develop and study two recursive weighted logics (RWLs) $$\mathcal {L}^w$$ and $$\mathcal {L}^t$$ , which are multi-modal logics that express qualitative and quantitative properties of labelled weighted transition systems (LWSs). LWSs are transition systems describing systems with quantitative aspects. They have labels with both actions and real-valued quantities representing the costs of transitions with respect to various resources. RWLs use first-order variables to measure local costs. The main syntactic operators are similar to the ones of timed logics for real-time systems. $$\mathcal {L}^w$$ has operators that constrain the value of resource-variables at the current state. $$\mathcal {L}^t$$ extends $$\mathcal {L}^w$$ by having quantitative constraints on the transition modalities as well. This extension makes sure that $$\mathcal {L}^t$$ is adequate, i.e. the semantic equivalence induced by $$\mathcal {L}^t$$ coincides with the weighted bisimilarity of LWSs. In addition, our logic is endowed, with simultaneous recursive equations, which allow encoding of properties of infinite behaviours. We prove that unlike in the case of the timed logics, the satisfiability problems for RWLs are decidable. The proofs use a variant of the region construction technique used in the literature with timed automata, which we adapt to the specific settings of RWLs. For $$\mathcal {L}^t$$ , we also propose an attractive alternative proof which makes use of the algorithm for $$\mathcal {L}^w$$ .

Population pharmacokinetic analysis of patritumab, a HER3 inhibitor, in subjects with advanced non-small cell lung cancer (NSCLC) or solid tumors.

The purpose of this analysis was to develop a population pharmacokinetic (PK) model for patritumab, a fully human monoclonal antibody that targets human epidermal growth factor receptor 3. A total of 833 serum concentrations were included in this analysis; serum concentrations were obtained from 145 subjects (136 with non-small cell lung cancer, nine with solid tumors) treated with patritumab [9 or 18mg/kg intravenously every 3weeks (q3w)] in one phase 1 and one phase 1b/2 study. Data were analyzed by nonlinear mixed-effect modeling. Patritumab PKs were best described through a two-compartment model with first-order elimination and interindividual variability on clearance (CL), volume of the central compartment (V c), distributional clearance, and volume of the peripheral compartment. In the final model, CL and V c were estimated as 0.0238L/h and 3.62L, respectively. Body weight (BW) and baseline albumin were found to be covariates for CL and BW was a covariate for V c. Covariates associated with hepatic and renal impairment were not significant on CL. Simulations showed that BW-based dosing reduced interindividual variability in patritumab exposure compared with fixed dosing. The PK of patritumab was linear at the doses studied and well described by the two-compartment model. Hepatic and renal impairment did not appear to affect PK. Our results support BW-based dosing of patritumab on a q3w schedule.

Investigation of micromixing by acoustically oscillated sharp-edges.

Recently, acoustically oscillated sharp-edges have been utilized to achieve rapid and homogeneous mixing in microchannels. Here, we present a numerical model to investigate acoustic mixing inside a sharp-edge-based micromixer in the presence of a background flow. We extend our previously reported numerical model to include the mixing phenomena by using perturbation analysis and the Generalized Lagrangian Mean (GLM) theory in conjunction with the convection-diffusion equation. We divide the flow variables into zeroth-order, first-order, and second-order variables. This results in three sets of equations representing the background flow, acoustic response, and the time-averaged streaming flow, respectively. These equations are then solved successively to obtain the mean Lagrangian velocity which is combined with the convection-diffusion equation to predict the concentration profile. We validate our numerical model via a comparison of the numerical results with the experimentally obtained values of the mixing index for different flow rates. Further, we employ our model to study the effect of the applied input power and the background flow on the mixing performance of the sharp-edge-based micromixer. We also suggest potential design changes to the previously reported sharp-edge-based micromixer to improve its performance. Finally, we investigate the generation of a tunable concentration gradient by a linear arrangement of the sharp-edge structures inside the microchannel.

Instruments for Measuring the Influence of Visual Persuasion: Validity and Reliability Tests

In User Experience (UX) research, the instruments are often measured by means of rating scales such as Likert scale and semantic differential scale. The validity of the findings and conclusions rely heavily on the instruments used in the questionnaires. This paper provides the assessment of the validity and reliability of a new set of measures to evaluate the influence of visual persuasion on web users. The instruments will be used to assess web users' perceptions of credibility, engagement, informativeness, satisfaction, social influences, usability, and visual aesthetic. Firstly, 85 items are pilot tested by expert and novice users in an offline and online settings. Secondly, the exploratory factor analysis is carried out in which 44 items representing 12 latent variables are reduced to 39 items with some of the latent variables are combined into one. The results show: Kaiser-Meyer-Olkin (KMO) of 0.901, significant Bartlett’s test, communalities range between 0.470 - 0.829, nine factors (also known as the latent variables) emerged with eigenvalues greater than 1, explaining more than 60% of the total variance, factor loadings of 0.466 and above, factors correlations of less than 0.7, and Cronbach’s alphas are well above the limit of 0.70. Finally, a confirmatory factor analysis is carried out on the first-order and second-order latent variables using the PLS-SEM. The instruments exceed the minimum requirement of the assessments for the convergent validity, discriminant validity, reliability and collinearity. The findings suggest that the proposed 39 items are valid and reliable for measuring the persuasiveness of visual persuasion.

Product Innovation Process of Chain Restaurants: A New Empirical Perspective Using Statistical Paradigms

This paper presents a recently concluded research study on new product innovation process (PIP) of chain restaurants in Malaysia. The aim of this study was two-folded: First, this study advanced both the theoretical conceptualization and the empirical validation of PIP model that have never been attempted before in hospitality management research. Second, this study then examined the reflective path coefficients of the structural model along with its predictive accuracy (R square) and predictive relevance (Q square). Partial Least Square (PLS) path modeling, using SmartPLS latest version 3.1.8, was used to estimate the higher-order construct (HOC) of PIP by adopting repeated use of manifest variables. Empirically, the result confirms both the second-order constructs of concept development and implementation path coefficients are found significant at ? < 0.01. Nonetheless, in this study, one of the stages of PIP (first-order latent variables) called pre-marketing found not significant, suggesting minimal emphasize on pre-marketing activities. The implication of these findings is then discussed along with its contribution to knowledge for academia and practitioners in a field alike, and limitations and future recommendation.

PLS-SEM Approach to Second-order Factor of Deviant Behaviour: Constructing Perceived Behavioural Control

Abstract Partial least square structural equation modelling (PLS-SEM) provides researchers with a predictive tool for theory building. In an attempt to understand deviant behaviour which can potentially become a criminal offence, PLS-SEM opens up a valuable mean to analyse latent constructs are designed from a composite of indicators. At its basic, this is called a first-order variable. Using the first-order variable in a basic predictor-criterion research model illuminates in-depth structure on how each component of these variables affects each other. However, as an analysis moves to a more complex level, the first-order variable poses a great challenge to the researchers. This is especially true when the main focus of a study is to look at a general predisposition of a group of related first-order variables with the criterion. Nevertheless, driven by sufficient theories and validated by appropriate statistical tests, related first-order latent variables can be funnelled into a higher-order latent construct. This in turn, helps to reduce complexity of the overall research model allowing more interpretable output and concise discussions.

Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

Development of new bread wheat cultivars needs efficient tools to monitor trait association in a breeding program. This investigation was aimed to characterize grain yield components and some agronomic traits related to bread wheat grain yield. The efficiency of a breeding program depends mainly on the direction of the correlation between different traits and the relative importance of each component involved in contributing to grain yield. Correlation and path analysis were carried out in 56 bread wheat genotypes grown under field conditions of Maragheh, Iran. Observations were recorded on 18 wheat traits and correlation coefficient analysis revealed grain yield was positively correlated with stem diameter, spike length, floret number, spikelet number, grain diameter, grain length and 1000 seed weight traits. According to the variance inflation factor (VIF) and tolerance as multicollinearity statistics, there are inconsistent relationships among the variables and all traits could be considered as first-order variables (Model I) with grain yield as the response variable due to low multicollinearity of all measured traits. In the path coefficient analysis, grain yield represented the dependent variable and the spikelet number and 1000 seed weight traits were the independent ones. Our results indicated that the number of spikelets per spikes and leaf width and 1000 seed weight traits followed by the grain length, grain diameter and grain number per spike were the traits related to higher grain yield. The above mentioned traits along with their indirect causal factors should be considered simultaneously as an effective selection criteria evolving high yielding genotype because of their direct positive contribution to grain yield.

Numerical study of thermoviscous effects in ultrasound-induced acoustic streaming in microchannels.

We present a numerical study of thermoviscous effects on the acoustic streaming flow generated by an ultrasound standing-wave resonance in a long straight microfluidic channel containing a Newtonian fluid. These effects enter primarily through the temperature and density dependence of the fluid viscosity. The resulting magnitude of the streaming flow is calculated and characterized numerically, and we find that even for thin acoustic boundary layers, the channel height affects the magnitude of the streaming flow. For the special case of a sufficiently large channel height, we have successfully validated our numerics with analytical results from 2011 by Rednikov and Sadhal for a single planar wall. We analyzed the time-averaged energy transport in the system and the time-averaged second-order temperature perturbation of the fluid. Finally, we have made three main changes in our previously published numerical scheme to improve the numerical performance: (i) The time-averaged products of first-order variables in the time-averaged second-order equations have been recast as flux densities instead of as body forces. (ii) The order of the finite-element basis functions has been increased in an optimal manner. (iii) Based on the International Association for the Properties of Water and Steam (IAPWS 1995, 2008, and 2011), we provide accurate polynomial fits in temperature for all relevant thermodynamic and transport parameters of water in the temperature range from 10 to 50 °C.

Deformation of debris-ice mixtures

Mixtures of rock debris and ice are common in high-latitude and high-altitude environments and are thought to be widespread elsewhere in our solar system. In the form of permafrost soils, glaciers, and rock glaciers, these debris-ice mixtures are often not static but slide and creep, generating many of the landforms and landscapes associated with the cryosphere. In this review, a broad range of field observations, theory, and experimental work relevant to the mechanical interactions between ice and rock debris are evaluated, with emphasis on the temperature and stress regimes common in terrestrial surface and near-surface environments. The first-order variables governing the deformation of debris-ice mixtures in these environments are debris concentration, particle size, temperature, solute concentration (salinity), and stress. A key observation from prior studies, consistent with expectations, is that debris-ice mixtures are usually more resistant to deformation at low temperatures than their pure end-member components. However, at temperatures closer to melting, the growth of unfrozen water films at ice-particle interfaces begins to reduce the strengthening effect and can even lead to profound weakening. Using existing quantitative relationships from theoretical and experimental work in permafrost engineering, ice mechanics, and glaciology combined with theory adapted from metallurgy and materials science, a simple constitutive framework is assembled that is capable of capturing most of the observed dynamics. This framework highlights the competition between the role of debris in impeding ice creep and the mitigating effects of unfrozen water at debris-ice interfaces.

Öğrenmeye İlişkin Motivasyonel Stratejiler Ölçeği’nin Geçerlik ve Güvenirlik Çalışması

The aim of this study is to determine the validity and reliability of the Motivated Strategies for Learning Question- naire (MSLQ) for high school students. In total, 1605 students (829 girls, 776 boys, average age=15.67±1.19) from three different high schools in the central district of Ankara voluntarily participated in the study. The MSLQ was developed for seventh grade students and adapted for Turkish eighth grade students. The MSLQ is a 7-point Likert-type scale and consists of 44 items. Factor analysis was applied to the data to determine whether the questionnaire showed the same structure for high school students. The results showed a good fit between the model composed of first-order latent variables (self-regulation strategies and motivational beliefs) and second- order latent variables (self-regulation, cognitive strategy use, self-efficacy, intrinsic value, test anxiety) as well as observed variables. Cronbach Alpha-scores, which were used to determine the internal consistency of the scale, were between 0.70 and 0.77 and indicated that the Turkish version of the MSLQ was reliable for use with a high school population.

Validating the Conceptions of Assessment-III Scale in Canadian Preservice Teachers

The purpose of this study was to test the validity of the Teachers' Conceptions of Assessment Scale III-Abridged Version (CoA-IIIA; Brown, 2006), a measure created, validated, and applied outside of North America, in a sample of Canadian preservice teachers (n = 436). This work is important because although we have long known that teachers' beliefs influence the way they teach, research also suggests that teachers' beliefs related to assessment influence the way they assess students. Confirmatory factor analysis of the Canadian data led to a solution slightly different than the New Zealand factor structure, with nine latent first-order variables, each with two or three measured indicators. Although the preservice teachers endorsed the purposes of assessment similarly to several other countries, the factor measuring assessment as “inaccurate” was endorsed more strongly than in previous research. Our discussion highlights the differences and similarities between the current results and previous studies with the CoA-IIIA.

Sulfur isotope budget (32S, 33S, 34S and 36S) in Pacific–Antarctic ridge basalts: A record of mantle source heterogeneity and hydrothermal sulfide assimilation

To better address how Mid-Ocean Ridge Basalt (MORB) sulfur isotope composition can be modified by assimilation and/or by immiscible sulfide fractionation, we report sulfur (S), chlorine (Cl) and copper (Cu) abundances together with multiple sulfur isotope composition for 38 fresh basaltic glasses collected on the Pacific–Antarctic ridge. All the studied glasses – with the exception of 8 off-axis samples – exhibit relatively high Cl/K, as the result of pervasive Cl-rich fluid assimilation. This sample set hence offers an opportunity to document both the upper mantle S isotope composition and the effect of hydrothermal fluids assimilation on the S isotope composition of erupted basalts along segments that are devoid of plume influence.Δ33S and Δ36S yield homogenous values within error of Canyon Diablo Troilite (CDT), whereas δ34S are variable, ranging between −1.57±0.11‰ and +0.60±0.10‰ with a mean value of −0.64±0.40‰ (1σ, versus V-CDT). The geographic distribution of δ34S follows a spike-like pattern, with local 34S-enrichments by up to +1.30‰ compared to a low-δ34S baseline. As hydrothermal massive sulfides are characterized by relative 34S-enrichments, such first-order variability can be accounted for by hydrothermal sulfide assimilation, a process that would occur for a subset of samples (n=10). Excluding these particular samples, the mean δ34S is significantly less variable, averaging at −0.89±0.11‰ (1σ, n=28), a value that we suggest to be representative of the average MORB source value for Pacific–Antarctic basalts. Weak trends between δ34S and 206Pb/204Pb are displayed by such uncontaminated samples suggesting the recycled oceanic crust to have a modest impact on the S budget of the mantle. Their positive signs, however, suggest the depleted mantle to have a δ34S of −1.40±0.50‰. The sub-chondritic 34S/32S value that was previously observed for the South-Atlantic mantle is here extended to the Pacific–Antarctic domain. Such a feature cannot originate from oceanic crust recycling and substantiates the concept of a core–mantle fractionation relict.

Sequential path analysis for determining interrelationships between yield and related traits in tobacco (Nicotiana tabacum L.) under normal and abiotic stress conditions

In the present work the relationships between yield and its related traits were investigated in tobacco genotypes under normal and abiotic stress conditions (Orobanche aegyptiaca weed) at Urmia Tobacco Research Centre, Iran, during 2006-2009 cropping seasons. The experimental design was a randomized complete block design (RCBD) with three replications in each condition every year. Analysis of variance revealed extent genetic variability among the genotypes for most of the traits studied. In comparison with normal condition, the mean value of studied traits decreased in stress condition. LAI and FD showed the maximum and minimum diminution in the mean values under stress condition compared to normal one so known as more sensitive and more tolerant traits, respectively. Based on CV values, the traits FD and DLYP showed the minimum and maximum variation among traits in both normal and stress conditions. Correlation analysis revealed significant and positive correlations between DLYP with all studied traits in both normal and stress conditions. Path analysis detected the traits including biomass, APDW and DWR as the first-order variables at normal condition and biomass, APDW, DWR and harvest index as the first-order variables under abiotic stress condition. Based on results, the traits such as biomass, APDW, DWR detected as more important factors in both conditions can be used in tobacco breeding programs for increasing yield. Abbreviation: aerial part fresh weight without leaves weight (APFW), aerial part dry weight without leaves weight (APDW), biomass (BIO), coefficient of variation (CV), dry weight of root (DWR), flowering date (FD), fresh weight of leaf (FWL), fresh weight of root (FWR), harvest index (HI), leaf area index (LAI), dry leaf yield per plant (DLYP), number of leaf (NL), plant height (PH), randomized complete block design (RCBD), standard deviation (Std).

Enumeration of monadic second-order queries on trees

We consider the enumeration problem of Monadic Second-Order (MSO) queries with first-order free variables over trees. In Bagan [2006] it was shown that this problem is in CONSTANT-DELAY lin . An enumeration problem belongs to CONSTANT-DELAY lin if for an input structure of size n it can be solved by: —an O ( n ) precomputation phase building an index structure, —followed by a phase enumerating the answers with no repetition and a constant delay between two consecutive outputs. In this article we give a different proof of this result based on the deterministic factorization forest decomposition theorem of Colcombet [2007].

Overcoming organizational inertia to strengthen business model innovation

Purpose – This study aims to examine how open innovation can be effective in changing organizational inertia to create business model innovation and improve firm performance. It also seeks to explore whether the existence of open innovation has a mediating effect and influence. Design/methodology/approach – This study constructs a theoretical model to explore the relationship between latent variables and uses a questionnaire to collect research data. In the conceptual framework, organizational inertia is a second-order latent variable and comprises three first-order latent variables: insight inertia, action inertia, and psychological inertia. Open innovation is also a second-order latent variable, and consists of two first-order latent variables: outbound and inbound open innovation. To clarify the relationship between these latent variables, structural equation modeling (SEM) is used to test the goodness of fit of the theoretical model and research hypotheses. This study uses 141 small to medium-sized manufacturing enterprises (SMEs) in Taiwan as the research subjects. Findings – The SEM analysis revealed that open innovation has a significant mediating effect on the relationship between organizational inertia and business model innovation, and the relationship between organizational inertia and firm performance; business model innovation also has a positive influence on firm performance. Originality/value – This study contributes the empirical analysis of SMEs to illustrate the role of open innovation on business model innovation processes.

Higher-order structure of noncognitive constructs and prediction of PISA 2003 mathematics achievement

The present study investigates higher-order factor structure among fifteen primary variables selected from four broad noncognitive domains of academic self-beliefs, motivation, learning strategy, and attitudes toward school. The PISA 2003 international dataset was analyzed. Several EFA, CFA, and SEM models were tested, hypothesizing the structure among the primary first-order variables and their relationships to the mathematics scores. The analyses indicated no single, general factor at the second-order level, encompassing all fifteen first-order variables. Instead, the fifteen primary variables were best represented by a three-level factor structure with the four salient domain factors at the second-order level and one general noncognitive factor at the third-order. The most plausible SEM model had each of the three self-belief primary variables individually linked to the mathematics achievement scores, independent of the third-order factor. Self-efficacy was the strongest predictor of mathematics achievement and its predictive power was comparable to that of the common part of all 15 primary variables captured by the general noncognitive factor.

Meta-interpretive learning: application to grammatical inference

Despite early interest Predicate Invention has lately been under-explored within ILP. We develop a framework in which predicate invention and recursive generalisations are implemented using abduction with respect to a meta-interpreter. The approach is based on a previously unexplored case of Inverse Entailment for Grammatical Inference of Regular languages. Every abduced grammar H is represented by a conjunction of existentially quantified atomic formulae. Thus ¬H is a universally quantified clause representing a denial. The hypothesis space of solutions for ¬H can be ordered by ?-subsumption. We show that the representation can be mapped to a fragment of Higher-Order Datalog in which atomic formulae in H are projections of first-order definite clause grammar rules and the existentially quantified variables are projections of first-order predicate symbols. This allows predicate invention to be effected by the introduction of first-order variables. Previous work by Inoue and Furukawa used abduction and meta-level reasoning to invent predicates representing propositions. By contrast, the present paper uses abduction with a meta-interpretive framework to invent relations. We describe the implementations of Meta-interpretive Learning (MIL) using two different declarative representations: Prolog and Answer Set Programming (ASP). We compare these implementations against a state-of-the-art ILP system MC-TopLog using the dataset of learning Regular and Context-Free grammars as well learning a simplified natural language grammar and a grammatical description of a staircase. Experiments indicate that on randomly chosen grammars, the two implementations have significantly higher accuracies than MC-TopLog. In terms of running time, Metagol is overall fastest in these tasks. Experiments indicate that the Prolog implementation is competitive with the ASP one due to its ability to encode a strong procedural bias. We demonstrate that MIL can be applied to learning natural grammars. In this case experiments indicate that increasing the available background knowledge, reduces the running time. Additionally ASPM (ASP using a meta-interpreter) is shown to have a speed advantage over Metagol when background knowledge is sparse. We also demonstrate that by combining MetagolR (Metagol with a Regular grammar meta-interpreter) and MetagolCF (Context-Free meta-interpreter) we can formulate a system, MetagolRCF, which can change representation by firstly assuming the target to be Regular, and then failing this, switch to assuming it to be Context-Free. MetagolRCF runs up to 100 times faster than MetagolCF on grammars chosen randomly from Regular and non-Regular Context-Free grammars.

English

In order to study the association among yield components and their direct and indirect effects on the grain yield, 144 experimental maize hybrids in Kermanshah, Iran were evaluated in a lattice design with two replications. Analysis of variance, factor and sequential path analyses were carried out for the studied traits. Results of path analysis showed that two first-order variables, namely; 100 grain weight (100-GW) and total number of kernels per ear (TNK) revealed highest direct effects on total grain weight (TGW), while ear length (EL), ear diameter (ED), number of kernel rows (NR) and number of kernels per row (NKR) were found to fit as second-order variables. Multivariate factorial analyses showed that six independent factors justified 77.852% of total data variations. The first and third justifications that explain 33.155% of the data variation was called yield and yield components. The second factor (14.121%) called traits was related to kernel depth. Other factors were phenology (11.060%), plant growth (11.038%) and tassel (8.478%). We concluded that hybrid number 69 (860002-2) has the highest grain yield. The traits 100 GW and TNK were shown to be the two important factors that affected the maize performance. Moreover, NKR showed the highest direct effect on TNK which showed the highest direct effect on TGW. Therefore, NKR could be used as a suitable index to improve grain yield too. &nbsp; Key words:&nbsp;Correlation, sequential path analysis, indirect selection.