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A relation, established by Andras Schubert (Scientometrics 78(3): 559–565, 2009) on the relation between a paper’s h-index and its total number of received citations, is explained. The relation is a concavely increasing power law and is explained based on the Lotkaian model for the h-index, proved by Egghe and Rousseau.

We present a few comments on the paper "Attacking the market split problem with lattice point enumeration" by A. Wasserman, published in Journal of Combinatorial Optimization, vol. 6, pp. 5–16, 2002.

Abstract Keratinase is a robust enzyme that is produced in the presence of keratin substrates. This enzyme has been recognized for its applications in waste management, leather and detergent industries. Our group has isolated a potential keratinase producing strain of Bacillus aerius NSMk2 from poultry dump soil, and its hide dehairing and stain removal applications have been studied. Considering commercial applicability of keratinase, the present study reports the keratinase production in a stirred tank reactor (5 l). Central composite rotatable design of response surface methodology (RSM) was employed to study the effect of most influencing process variables, i.e., aeration (0.5–1.5 vvm), agitation (150–350 rpm) and incubation period (24–48 h) on keratinase production. The quadratic model predicted 15 experimental runs, and the influence of independent variables and their interaction on keratinase production were interpreted using analysis of variance (ANOVA) and t-test statistics. Coefficient of determination (R2) value close to 1 and Fisher F-value of 3743.77 showed good fit of experimental data to second-order polynomial equation. A reasonable agreement between experimental and predicted values showed the accuracy of deduced model. Applying the desirability function, aeration rate of 1.0 vvm, agitation rate of 276.88 rpm and incubation period of 33.68 h supported maximum keratinase production (318.38 U/ml). Confirmatory experiments were performed to evaluate the accuracy of desirability function. Maximum keratinase activity of 318.11 U/ml close to predicted value (318.38 U/ml) validates the model. The present study provides useful guidelines for large-scale production of keratinase that can be used for various commercial applications. Article highlights Keratinase production was optimized in a stirred tank reactor by RSM. The influence of aeration, agitation and incubation period on keratinase production was studied. A significant increase in keratinase production was observed at 1.0 vvm aeration and 276.88 rpm agitation after 33.68 h.

In this paper we develop new tensor methods for unconstrained convex optimization, which solve at each iteration an auxiliary problem of minimizing convex multivariate polynomial. We analyze the simplest scheme, based on minimization of a regularized local model of the objective function, and its accelerated version obtained in the framework of estimating sequences. Their rates of convergence are compared with the worst-case lower complexity bounds for corresponding problem classes. Finally, for the third-order methods, we suggest an efficient technique for solving the auxiliary problem, which is based on the recently developed relative smoothness condition (Bauschke et al. in Math Oper Res 42:330–348, 2017; Lu et al. in SIOPT 28(1):333–354, 2018). With this elaboration, the third-order methods become implementable and very fast. The rate of convergence in terms of the function value for the accelerated third-order scheme reaches the level $$O\left( {1 \over k^4}\right) $$ O 1 k 4 , where k is the number of iterations. This is very close to the lower bound of the order $$O\left( {1 \over k^5}\right) $$ O 1 k 5 , which is also justified in this paper. At the same time, in many important cases the computational cost of one iteration of this method remains on the level typical for the second-order methods.

Hole drilling is one of the major basic operations in part manufacturing. It follows without surprise then that the optimization of this process is of great importance when trying to minimize the total financial and environmental cost of part manufacturing. In multi-hole drilling, 70% of the total process time is spent in tool movement and tool switching. Therefore, toolpath optimization in particular has attracted significant attention in cost minimization. This paper critically reviews research publications on drilling path optimization. In particular, this review focuses on three aspects; problem modeling, objective functions, and optimization algorithms. We conclude that most papers being published on hole drilling are simply basic Traveling Salesman Problems (TSP) for which extremely powerful heuristics exist and for which source code is readily available. Therefore, it is remarkable that many researchers continue developing novel metaheuristics for hole drilling without properly situating those approaches in the larger TSP literature. Consequently, more challenging hole drilling applications that are modeled by the Precedence Constrained TSP or hole drilling with sequence dependent drilling times do not receivemuch research focus. Sadly, these many low quality hole drilling research publications drown out the occasional high quality papers that describe specific problematic problem constraints or objective functions. It is our hope through this review paper that researchers' efforts can be refocused on these problem aspects in order to minimize production costs in the general sense.

Graphic abstract Nutritional information of burgers launched in the EU market during 2020 was retrieved from their labels. Products were initially classified into four types: i.e., veggie, red meat-, fish- and poultry-based. Gluten, wheat, and soy were the most declared allergens regardless of the burgers type. Veggie burgers showed levels of energy, fat, and saturate fatty acids (SFA) similar to fish- and poultry-based burgers, but lower than red meat burgers. Compared to conventional burgers, veggie had higher amounts of carbohydrates and sugars and a lower content of proteins, but no difference in salt. Due to the high compositional intra-variability in the veggie burgers, vegetarian and vegan burgers were further analyzed separately. Vegan burgers had higher levels of energy, fat, SFA and protein than vegetarian burgers, but lower carbohydrates and sugars. Once again large differences in the nutritional parameters were observed in both vegan and vegetarian burger categories due to the wide range of ingredients and formulations employed in these types of products. A clear and comprehensive informative labeling is especially needed for vegan and vegetarian burgers to allow the consumer to make a rational decision based on the nutritional facts of these products. Supplementary Information The online version contains supplementary material available at 10.1007/s00217-021-03808-9.

We present three new inequalities tying the signature, the simplicial volume and the Euler characteristic of surface bundles over surfaces. Two of them are true for any surface bundle, while the third holds on a specific family of surface bundles, namely the ones that arise through a ramified covering. These are the main known examples of bundles with non-zero signature., 14 pages. Simplified the proof of Proposition 1.2. This is the final version, accepted in Geometriae Dedicata

This short paper concerns the existence of curves with low gonality on smooth hypersurfaces $$X\subset \mathbb {P}^{n+1}$$ . After reviewing a series of results on this topic, we report on a recent progress we achieved as a product of the Workshop Birational geometry of surfaces, held at University of Rome “Tor Vergata” on January 11th–15th, 2016. In particular, we obtained that if $$X\subset \mathbb {P}^{n+1}$$ is a very general hypersurface of degree $$d\geqslant 2n+2$$ , the least gonality of a curve $$C\subset X$$ passing through a general point of X is $$\mathrm {gon}(C)=d-\left\lfloor \frac{\sqrt{16n+1}-1}{2}\right\rfloor $$ , apart from some exceptions we list.

In this work, the pneumocardiogram signals of nine rats were analysed by scale index, Boltzmann Gibbs entropy and maximum Lyapunov exponents. The scale index method, based on wavelet transform, was proposed for determining the degree of aperiodicity and chaos. It means that the scale index parameter is close to zero when the signal is periodic and has a value between zero and one when the signal is aperiodic. A new entropy calculation method by normalized inner scalogram was suggested very recently. In this work, we also used this method for the first time in an empirical data. We compared the both methods with maximum Lyapunov exponents and observed that using together the scale index and the entropy calculation method by normalized inner scalogram increases the reliability of the pneumocardiogram signal analysis. Thus, the analysis of the pneumocardiogram signals by those methods enables to compare periodical and/or nonlinear aspects for further understanding of dynamics of cardiorespiratory system. © 2020, Springer Nature B.V.

Graph theory analysis on resting state electroencephalographic rhythms disclosed topological properties of cerebral network. In Alzheimer's disease (AD) patients, this approach showed mixed results. Granger causality matrices were used as input to the graph theory allowing to estimate the strength and the direction of information transfer between electrode pairs. The number of edges (degree), the number of inward edges (in-degree), of outgoing edges (out-degree) were statistically compared among healthy controls, patients with mild cognitive impairment due to AD (AD-MCI) and AD patients with mild dementia (ADD) to evaluate if degree abnormality could involve low and/or high degree vertices, the so called hubs, in both prodromal and over dementia stage. Clustering coefficient and local efficiency were evaluated as measures of network segregation, path length and global efficiency as measures of integration, the assortativity coefficient as a measure of resilience. Degree, in-degree and out-degree values were lower in AD-MCI and ADD than the control group for non-hubs and hubs vertices. The number of edges was preserved for frontal electrodes, where patients' groups showed an additional hub in F3. Clustering coefficient was lower in ADD compared with AD-MCI in the right occipital electrode, and it was positively correlated with mini mental state examination. Local and global efficiency values were lower in patients' than control groups. Our results show that the topology of the network is altered in AD patients also in its prodromal stage, begins with the reduction of the number of edges and the loss of the local and global efficiency.

In this study, we sourced 37 commercial flours from 14 mills based on 7 countries and analysed them with a total of 18 methods, generating 90 single analytical values for each flour. The 18 methods were chosen to cover the analytical practice of most European mills and bakery companies, as well as particle charge detection, GlutoPeak and solvent retention capacity as emerging methods. We investigated the relationship between the data from the individual methods, and performed a principal component analysis to describe the structure of the data set and identify the main underlying flour properties. Four principal components accounted for 64.8% of the total variance. They were interpreted as (PC1) starch gelatinization properties, (PC2) hydration properties, (PC3) dough resistance at variable water amount, and (PC4) dough strength at fixed water amount. From the emerging methods, solvent retention capacity (sodium carbonate and water) was highly correlated with PC2, while the GlutoPeak max torque was highly correlated with PC4.

Box-Behnken designs were used to optimize aprocess for sesame oil extraction by screw-pressing at lowtemperature (50 °C). Experimental designs included seedmoisture content (SMC), pressing speed (PS), and restrictiondie (RD) as the main processing parameters.Extractions at pilot plant scale showed a peak in oil recovery(OR, 71.1 ± 2.80%) at 12.3% SMC, 4 mm RD,and 20 rpm PS. Theoretical models were scanned againstexperimental data in order to scale up the proposed oilextraction process to industrial scale. A fitted model for OR showed a maximum predicted value similar to thehighest experimental value (74.4 ± 1.23%) under the followingconditions: 8.03% SMC, 10 mm RD, and 20 rpmPS. Chemical quality parameters of oils obtained at bothpilot and industrial scales were in the ranges stated inCodex (FAO/WHO) standards for non-refined sesame oil. Fil: Martinez, Marcela Lilian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentina Fil: Bordón, María Gabriela. Universidad Nacional de Córdoba. Facultad de Cs.exactas Físicas y Naturales. Departamento de Química Industrial y Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Lallana, Rebeca Lía. Universidad Nacional de Córdoba. Facultad de Cs.exactas Físicas y Naturales. Departamento de Química Industrial y Aplicada; Argentina Fil: Ribotta, Pablo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentina Fil: Maestri, Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina

Most of local indices of spatial autocorrelation utilize a classical adjacency matrix as interconnection system. In this paper we attempt to use generalized matrix of spatial weights for measuring local autocorrelation. The work concludes with a comparison of local autocorrelation indices according to different hypotheses of neighborhood.

A confusingly wide variety of temporally asymmetric learning rules exists related to reinforcement learning and/or to spike-timing dependent plasticity, many of which look exceedingly similar, while displaying strongly different behavior. These rules often find their use in control tasks, for example in robotics and for this rigorous convergence and numerical stability is required. The goal of this article is to review these rules and compare them to provide a better overview over their different properties. Two main classes will be discussed: temporal difference (TD) rules and correlation based (differential hebbian) rules and some transition cases. In general we will focus on neuronal implementations with changeable synaptic weights and a time-continuous representation of activity. In a machine learning (non-neuronal) context, for TD-learning a solid mathematical theory has existed since several years. This can partly be transferred to a neuronal framework, too. On the other hand, only now a more complete theory has also emerged for differential Hebb rules. In general rules differ by their convergence conditions and their numerical stability, which can lead to very undesirable behavior, when wanting to apply them. For TD, convergence can be enforced with a certain output condition assuring that the delta-error drops on average to zero (output control). Correlation based rules, on the other hand, converge when one input drops to zero (input control). Temporally asymmetric learning rules treat situations where incoming stimuli follow each other in time. Thus, it is necessary to remember the first stimulus to be able to relate it to the later occurring second one. To this end different types of so-called eligibility traces are being used by these two different types of rules. This aspect leads again to different properties of TD and differential Hebbian learning as discussed here. Thus, this paper, while also presenting several novel mathematical results, is mainly meant to provide a road map through the different neuronally emulated temporal asymmetrical learning rules and their behavior to provide some guidance for possible applications.

Kenaf (Hibiscus cannabinus L.) is an annual plant which produces a very high fiber yield per hectare and has demonstrated to be a suitable material for pulping. The crop conditions influence fiber production, but there is no information about their effect on pulp quality. The aim of this work was to study the effect of kenaf varieties and crop conditions (watering dose and harvesting time) on sulfate pulp quality. The study has been made on bast fiber sulfate pulps due to their high added value. The quality criteria were fiber dimensions, chemical composition and pulp quality. Kenaf variety or crop conditions have significant effect on fiber dimensions, holocellulose content, kappa number and breaking strength. To obtain high fiber yield and good delignified pulps it is recommended to grow the Salvador variety and to employ advance harvesting.