Multicomplex number class for Matlab, with a focus on the accurate calculation of small imaginary terms for multicomplex step sensitivity calculations

A Matlab class for multicomplex numbers was developed with particular attention paid to the robust and accurate handling of smallimaginary components. This is primarily to allow the class to be used to obtainn-order derivative information using the multicomplexstep method for, amongst other applications, gradient-based optimization and optimum control problems. The algebra of multicomplexnumbers is described as is its accurate computational implementation, considering small term approximations and the identification ofprinciple values. The implementation of the method in Matlab is studied, and a class definition is constructed. This new class definitionenables Matlab to handlen-order multicomplex numbers, and perform arithmetic functions. It was found that with this method, thestep size could be arbitrarily decreased toward machine precision. Use of the method to obtain up to the 7th derivative of functions ispresented, as is timing data to demonstrate the efficiency of the class implementation

An evolutionary approach to the delimitation of labour market areas: an empirical application for Chile

An evolutionary approach to the delimitation of labour market areas: an empirical application for Chile. Spatial Economic Analysis. Labour market areas (LMAs) are argued to represent a more appropriate policy framework than administrative units for the analysis of spatial labour market activity. This article develops LMAs for Chile by applying an evolutionary computation approach. This innovative approach defines LMAs through an optimization process by maximization of internal cohesion, subject to restrictions of minimum levels of self-containment and population. To evaluate the appropriateness of the LMAs, comparative analyses are performed between alternative delimitations based on different parameter configurations of the proposed method versus administrative boundaries and the most widely used method for official LMA delimitation, the travel-to-work areas method

Proposing to use artificial neural Networks for NoSQL attack detection

[EN] Relationships databases have enjoyed a certain boom in software worlds until now. These days, with the rise of modern applications, unstructured data production, traditional databases do not completely meet the needs of all systems. Regarding these issues, NOSQL databases have been developed and are a good alternative. But security aspects stay behind. Injection attacks are the most serious class of web attacks that are not taken seriously in NoSQL. This paper presents a Neural Network model approach for NoSQL injection. This method attempts to use the best and most effective features to identify an injection. The features used are divided into two categories, the first one based on the content of the request, and the second one independent of the request meta parameters. In order to detect attack payloads features, we work on character level analysis to obtain malicious rate of user inputs. The results demonstrate that our model has detected more attack payloads compare with models that work black list approach in keyword level

The influence of running wide on the bend on finishing times and positions in men's and women's 800 m finals at major global championships

The aim of this study was to determine the influence of running wide on bends regarding intermediate changes of position, dispersion of athletes, and speed relative to season best (SB) between medalists and non-medalists in men’s and women’s 800 m championship finals. Extra distance covered on bends was measured using official videos. The total distance run was calculated and described as the minimum calculable distance. Theoretical mean speeds, theoretical finishing times and theoretical finishing positions were calculated. In addition, intermediate and total changes of position (on bends and straights) and dispersion between athletes in each 100-m segment were calculated. Finishing times and segment times were calculated relative to SB. Theoretical finishing times were faster than official finishing times (p<.001). Finishing positions were influenced by extra distance covered. Medalists displayed a higher number of positive changes of intermediate positions than non-medalists (p<.001), occurring mainly on the straights (p=.003) and were greatest between 500 and 600 m (p=.003), without differences between groups in total extra distance and in extra distance covered on each bend. Medalists displayed higher total speeds relative to SB (p=.042) and over the 500-600 m segment onwards (p<.05), increasing the dispersion from this segment onwards (p<.001). These findings indicate that running the shortest distance on the bends and being able to accelerate during the last 300 m of the race positively influence finishing position in major championships 800 m finals

Redox-dependent and redox-independent functions of Caenorhabditis elegans thioredoxin 1

Thioredoxins (TRX) are traditionally considered as enzymes catalyzing redox reactions. However, redox-independent functions of thioredoxins have been described in different organisms, although the underlying molecular mechanisms are yet unknown. We report here the characterization of the first generated endogenous redox-inactive thioredoxin in an animal model, the TRX-1 in the nematode Caenorhabditis elegans. We find that TRX-1 dually regulates the formation of an endurance larval stage (dauer) by interacting with the insulin pathway in a redox-independent manner and the cGMP pathway in a redox-dependent manner. Moreover, the requirement of TRX-1 for the extended longevity of worms with compromised insulin signalling or under calorie restriction relies on TRX-1 redox activity. In contrast, the nuclear translocation of the SKN-1 transcription factor and increased LIPS-6 protein levels in the intestine upon trx-1 deficiency are strictly redox-independent. Finally, we identify a novel function of C. elegans TRX-1 in male food-leaving behaviour that is redox-dependent. Taken together, our results position C. elegans as an ideal model to gain mechanistic insight into the redox-independent functions of metazoan thioredoxins, overcoming the limitations imposed by the embryonic lethal phenotypes of thioredoxin mutants in higher organisms

A systematic molecular and pharmacologic evaluation of AKT inhibitors reveals new insight into their biological activity.

Background AKT, a critical effector of the phosphoinositide 3-kinase (PI3K) signalling cascade, is an intensely pursued therapeutic target in oncology. Two distinct classes of AKT inhibitors have been in clinical development, ATP-competitive and allosteric. Class-specific differences in drug activity are likely the result of differential structural and conformational requirements governing efficient target binding, which ultimately determine isoform-specific potency, selectivity profiles and activity against clinically relevant AKT mutant variants.Methods We have carried out a systematic evaluation of clinical AKT inhibitors using in vitro pharmacology, molecular profiling and biochemical assays together with structural modelling to better understand the context of drug-specific and drug-class-specific cell-killing activity.Results Our data demonstrate clear differences between ATP-competitive and allosteric AKT inhibitors, including differential effects on non-catalytic activity as measured by a novel functional readout. Surprisingly, we found that some mutations can cause drug resistance in an isoform-selective manner despite high structural conservation across AKT isoforms. Finally, we have derived drug-class-specific phosphoproteomic signatures and used them to identify effective drug combinations.Conclusions These findings illustrate the utility of individual AKT inhibitors, both as drugs and as chemical probes, and the benefit of AKT inhibitor pharmacological diversity in providing a repertoire of context-specific therapeutic options

The what and where of adding channel noise to the Hodgkin-Huxley equations

One of the most celebrated successes in computational biology is the Hodgkin-Huxley framework for modeling electrically active cells. This framework, expressed through a set of differential equations, synthesizes the impact of ionic currents on a cell's voltage -- and the highly nonlinear impact of that voltage back on the currents themselves -- into the rapid push and pull of the action potential. Latter studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic Hodgkin-Huxley equations. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly Matlab simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl

A scalable analytical framework for spatio-temporal analysis of neighborhood change: A sequence analysis approach

© Springer Nature Switzerland AG 2020. Spatio-temporal changes reflect the complexity and evolution of demographic and socio-economic processes. Changes in the spatial distribution of population and consumer demand at urban and rural areas are expected to trigger changes in future housing and infrastructure needs. This paper presents a scalable analytical framework for understanding spatio-temporal population change, using a sequence analysis approach. This paper uses gridded cell Census data for Great Britain from 1971 to 2011 with 10-year intervals, creating neighborhood typologies for each Census year. These typologies are then used to analyze transitions of grid cells between different types of neighborhoods and define representative trajectories of neighborhood change. The results reveal seven prevalent trajectories of neighborhood change across Great Britain, identifying neighborhoods which have experienced stable, upward and downward pathways through the national socioeconomic hierarchy over the last four decades