Type-2 Model Research Articles

Improving risk-adjusted performance in high frequency trading using interval type-2 fuzzy logic

In this paper, we investigate the ability of higher order fuzzy systems to handle increased uncertainty, mostly induced by the market microstructure noise inherent in a high frequency trading (HFT) scenario. Whilst many former studies comparing type-1 and type-2 Fuzzy Logic Systems (FLSs) focus on error reduction or market direction accuracy, our interest is predominantly risk-adjusted performance and more in line with both trading practitioners and upcoming regulatory regimes. We propose an innovative approach to design an interval type-2 model which is based on a generalisation of the popular type-1 ANFIS model. The significance of this work stems from the contributions as a result of introducing type-2 fuzzy sets in intelligent trading algorithms, with the objective to improve the risk-adjusted performance with minimal increase in the design and computational complexity. Overall, the proposed ANFIS/T2 model scores significant performance improvements when compared to both standard ANFIS and Buy-and-Hold methods. As a further step, we identify a relationship between the increased trading performance benefits of the proposed type-2 model and higher levels of microstructure noise. The results resolve a desirable need for practitioners, researchers and regulators in the design of expert and intelligent systems for better management of risk in the field of HFT.

Inefficient constitutive inhibition of P2X3 receptors by brain natriuretic peptide system contributes to sensitization of trigeminal sensory neurons in a genetic mouse model of familial hemiplegic migraine.

BackgroundOn trigeminal ganglion neurons, pain-sensing P2X3 receptors are constitutively inhibited by brain natriuretic peptide via its natriuretic peptide receptor-A. This inhibition is associated with increased P2X3 serine phosphorylation and receptor redistribution to non-lipid raft membrane compartments. The natriuretic peptide receptor-A antagonist anantin reverses these effects. We studied whether P2X3 inhibition is dysfunctional in a genetic familial hemiplegic migraine type-1 model produced by introduction of the human pathogenic R192Q missense mutation into the mouse CACNA1A gene (knock-in phenotype). This model faithfully replicates several properties of familial hemiplegic migraine type-1, with gain-of-function of CaV2.1 Ca2+ channels, raised levels of the algogenic peptide calcitonin gene-related peptide, and enhanced activity of P2X3 receptors in trigeminal ganglia.ResultsIn knock-in neurons, anantin did not affect P2X3 receptor activity, membrane distribution, or serine phosphorylation level, implying ineffective inhibition by the constitutive brain natriuretic peptide/natriuretic peptide receptor-A pathway. However, expression and functional properties of this pathway remained intact together with its ability to downregulate TRPV1 channels. Reversing the familial hemiplegic migraine type-1 phenotype with the CaV2.1-specific antagonist, ω-agatoxin IVA restored P2X3 activity to wild-type level and enabled the potentiating effects of anantin again. After blocking calcitonin gene-related peptide receptors, P2X3 receptors exhibited wild-type properties and were again potentiated by anantin.ConclusionsP2X3 receptors on mouse trigeminal ganglion neurons are subjected to contrasting modulation by inhibitory brain natriuretic peptide and facilitatory calcitonin gene-related peptide that both operate via complex intracellular signaling. In the familial hemiplegic migraine type-1 migraine model, the action of calcitonin gene-related peptide appears to prevail over brain natriuretic peptide, thus suggesting that peripheral inhibition of P2X3 receptors becomes insufficient and contributes to trigeminal pain sensitization.

Observational constraints on the MSSM braneworld scenario and supergravity corrections

We study the Minimal Supersymmetric Standard Model (MSSM) inflation in the context of the Randall-Sundrum type-2 braneworld model. Using the latest release from the combination of WMAP9, eCMB, BAO, and H0, we show that the inflation observables for the MSSM inflation without any corrections depend only on the number of e-folds N and provide a negligible ratio r .W e also examine the effect of supergravity corrections on inflationary predictions and find that they can alter the values of the ratio r and the brane tension T. Suitable observational values of ns are also obtained for some values of N , T and the coefficient ζ.

Antisense versus proopiomelanocortin mRNA reduces vascular risk in a murine model of type-2 diabetes following stress exposure in early post-natal life

Mechanisms of vascular complications in type-2 diabetes patients and animal models are matter of debate. We previously demonstrated that a double-stress model applied to male mice during nursing period produces enduring hyperfunction of endogenous opioid and adrenocorticotropin (ACTH)-corticosteroid systems, accompanied by type-2 diabetes-like alterations in adult animals. Administration of the opioid receptor antagonist naloxone, or of an antisense oligodeoxynucleotide versus proopiomelanocortin mRNA, capable to block the pro-opiomelanocortin-derived peptides β-endorphin and ACTH, selectively prevent these alterations. Here, we investigated alterations produced by our stress model on aorta endothelium-dependent relaxation and contractile responses. Mice, stressed during nursing period, showed in the adulthood hormonal and metabolic type-2 diabetes-like alterations, including hyperglycemia, increased body weight and increased plasma ACTH and corticosterone levels. Ex vivo isolated aorta rings, gathered from stressed mice, were less sensitive to noradrenaline-induced contractions versus controls. This effect was blocked by nitric-oxide synthase-inhibitor l-NG-nitroarginine added to bath organ solution. Aorta rings relaxation caused by acetylcholine was enhanced in stressed mice versus controls, but following treatment with the nitric-oxide donor sodium nitroprusside, concentration-relaxation curves in aorta from stressed groups were similar to controls. Therefore, vascular response alterations to physiologic-pharmacologic stimuli were apparently due to nitric-oxide hyperfunction-dependent mechanisms. Aorta functional alterations, and plasma stress hormones enhancement, were prevented in mice stressed and treated with antisense oligodeoxinucleotide, addressed to reduce ACTH- and corticosteroid-mediated hyperfunction. This study demonstrates the key role of ACTH-corticosteroid axis hyperfunction for the triggering of vascular conditions in male adult rodents following postnatal stress in a type-2 diabetes model.

An in vitro biomechanical evaluation of a new commercial titanium-zirconium alloy dental implant: a pilot study.

The study compared the implant mobility and surrounding bone strain between the titanium-zirconium (Ti-Zr) alloy and the commercial pure (CP) Ti implants. The mobility--quantified as the implant stability quotient (ISQ) and Periotest value (PTV)--of implants constructed from Ti-Zr alloy and CP Ti placed into artificial type-2 jawbone models were measured. Specimens were tested by applying 190 N vertically or at 30 degrees laterally. Peak values of the principal strains of bone were recorded by rosette strain gauges with a data acquisition system and were analyzed statistically using Wilcoxon rank-sum test. PTV and ISQ values did not differ significantly between the Ti-Zr and CP Ti implants (P > 0.01). Under vertical loading, the peak bone strains did not differ significantly between the Ti-Zr and CP Ti specimens (P > 0.006). However, the peak strains were 52% lower around the Ti-Zr implant than around the Ti implant on the buccal side of bone under lateral loading (P < 0.001). The implant material (Ti-Zr alloy vs CP Ti) had no effect on the mobility of small-diameter dental implants. However, using Ti-Zr alloy as an implant material decreased the periimplant bone strain under lateral loading in this pilot study.

Interval type-2 fuzzy adaptive tracking control design for PMDC motor with the sector dead-zones

This paper deals with the permanent magnet DC motor system with sector dead-zones and external disturbances via interval type-2 fuzzy adaptive tracking control scheme to achieve H∞ tracking performance. The type-2 fuzzy dynamic model is used to approximate the motor dynamics without constructing sector dead-zone inverse, where the parameters of the fuzzy model are obtained both from the fuzzy inference and online update laws. Based on the Lyapunov criterion and Riccati-inequality, the control scheme is derived to stabilize the closed-loop system such that all states of the system are guaranteed to be bounded and H∞ tracking performance is achieved due to uncertainties, dead-zone nonlinearities, and external disturbances. The advantage of the proposed control scheme is that it can better handle the vagueness or uncertainties inherent in linguistic words using fuzzy set membership functions with adaptation capability by linear analytical results instead of estimating non-linear system functions as the system parameters are unknown. Finally, the simulations of the PMDC motor system with sector dead-zone nonlinearities are used to illustrate the effectiveness of the proposed control scheme and the performance comparisons with the three-dimensional autonomous Ro¨ssler system (Wang and Chua, 2008) are used to validate the H∞ tracking performance of the PMDC motor system.

Promising anti-diabetes mellitus activity in rats of β-amyrin palmitate isolated from Hemidesmus indicus roots

While evaluating the toxicity of the tuberous root extracts of Hemidesmus indicus, a traditional medicinal plant, the glucose lowering property of the root was observed by the investigators. Therefore, it was thought of interest to isolate the anti-hyperglycemic principle from the root and determine its utility to develop an anti-diabetes mellitus medicine. The active principle was isolated from H. indicus root extract by anti-hyperglycemic activity guided chromatographic techniques. Glucose tolerance test in rats was used to evaluate the anti-hyperglycenic property. Anti-diabetes mellitus property was evaluated in alloxan-induced diabetic rats as well as streptozotocin-induced (type-2 model) diabetic rats. The active principle was isolated and identified with spectral data as β-amyrin palmitate. Although it is a known compound, its presence in H. indicus is not known previously. It was observed for the first time that β-amyrin palmitate has remarkable anti-hyperglycemic activity in orally glucose loaded rats. Further, interestingly, it exhibited excellent anti-diabetes mellitus activity in both alloxan-diabetic and streptozotocin-diabetic rats at a very low concentration (50µg/kg body weight). One of the mechanisms of action of β-amyrin palmitate appears to be blocking the entry of glucose from the intestine. β-Amyrin palmitate is very promising to develop a medicine for diabetes for combination therapy and/or mono-therapy.

Evolutionary design of efficient type-2 fuzzy models from noisy data using hybrid PSO model

This work presents an efficient framework for designing type-2 fuzzy models from noisy data that represent majority of the real-world databases used for building models. The framework is based on the use of a hybrid particle swarm optimisation (PSO) model that combines the traits of gbest and lbest PSO variants for getting fast results and at the same time avoiding premature convergence. Two major components of the framework, i.e., the encoding mechanism, and the hybrid PSO model have been discussed. Further, two benchmark problems that cover major application domains of type-2 FLSs viz. forecasting and classification, have been presented to demonstrate the effectiveness of the proposed methodology. For each noisy benchmark data, type-1 fuzzy model is also designed and its performance is compared with the designed type-2 fuzzy model with an objective to exhibit better noise handling capability of type-2 models.

MSSM braneworld inflation

We consider a Minimal Supersymmetric Standard Model (MSSM) inflation in the context of the Randall-Sundrum type-2 braneworld model. We apply the slow-roll approximations, in high-energy limit, to constraint various inflationary spectrum parameters in relation with recent WMAP9 data. We show that, for some values of the number of efolding N, the MSSM braneworld inflation provides the best fit results according to recent observations.

Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization

In real time, one observation always relies on several observations. To improve the forecasting accuracy, all these observations can be incorporated in forecasting models. Therefore, in this study, we have intended to introduce a new Type-2 fuzzy time series model that can utilize more observations in forecasting. Later, this Type-2 model is enhanced by employing particle swarm optimization (PSO) technique. The main motive behind the utilization of the PSO with the Type-2 model is to adjust the lengths of intervals in the universe of discourse that are employed in forecasting, without increasing the number of intervals. The daily stock index price data set of SBI (State Bank of India) is used to evaluate the performance of the proposed model. The proposed model is also validated by forecasting the daily stock index price of Google. Our experimental results demonstrate the effectiveness and robustness of the proposed model in comparison with existing fuzzy time series models and conventional time series models.

TACHYONIC BRANEWORLD INFLATION AND OBSERVATIONS

We study various tachyonic inflationary spectrum perturbations in the context of the Randall–Sundrum type-2 braneworld model [L. Randall and R. Sundrum, Phys. Rev. Lett.83, 3370 (1999); Phys. Rev. Lett.83, 4690 (1999)]. We consider, in particular, the inverse power law potential [Formula: see text] of the tachyonic field in the high-energy and slow-roll approximations using the recent astronomical observations.

Solar Power Prediction Using Interval Type-2 TSK Modeling

The random nature of solar energy resources is one of the obstacles to their large-scale proliferation in power systems. The most practical way to predict this renewable source of energy is to use meteorological data. However, such data are usually provided in a qualitative form that cannot be exploited using traditional quantitative methods but which can be modeled using fuzzy logic. This paper proposes type-1 and interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy systems for the modeling and prediction of solar power plants. The paper considers TSK models with type-1 antecedents and crisp consequents, type-1 antecedents and consequents, and type-2 antecedents and crisp consequents. The design methodology for tuning the antecedents and consequents of each model is described. Finally, input-output data sets from a solar plant are used to obtain the three TSK models and their prediction results are compared to results from the literature. The results show that type-2 TSK models with type2 antecedents and crisp consequents provide the best performance based on the solar plant data.

The effects of complex herbal medicine composed of Cornus fructus, Dioscoreae rhizoma, Aurantii fructus, and Mori folium in obese type-2 diabetes mice model

Prediabetes, Diabetes and obesity are the metabolic diseases which are closely linked each other to its properties such as hypertension, hyperlipidemia, and abdominal obesity. Many studies tried to find single therapeutic target for treatment of the metabolic syndrome but failed because of its side effects. Therefore, many investigations focus on the reduction of the blood glucose or the body weight. Glucagon-like peptide-1 (GLP-1), a new therapeutic target for type-2 diabetes which caused by insulin resistance and relative insulin deficiency, is issued nowadays. This study aimed to investigate the antidiabetic effect of a complex herbal medicine, JUL04, composed of Cornus fructus (CF), Dioscoreae rhizome (DR), Aurantii fructus (AF), and Mori folium (MF), on the enteroendocrine L cell and on the obese type-2 diabetes mice. Fully differentiated NCI-H716 cells were treated with each herbal samples and GLP-1 ELISA was performed. The animal model was induced by high fat- and high sucrose-diet with or without JUL04 for 8 weeks, and the body and the epididymal fat weight and the size of white adipocyte were measured. Plasma GLP-1 and insulin concentration were also measured by ELISA. The results of the study demonstrate that JUL04 has anti-diabetes and anti-obesity effects in high fat- and high sucrose-diet induced mice model.

Preventive Effect of TU-100 on a Type-2 Model of Colitis in Mice: Possible Involvement of Enhancing Adrenomedullin in Intestinal Epithelial Cells

Purpose. Crohn's disease (CD) and ulcerative colitis (UC), the two major forms of inflammatory bowel disease (IBD), have histopathologically and immunologically different characteristics. We previously reported that a traditional Japanese medicine, daikenchuto (TU-100), ameliorated a trinitrobenzenesulfonic acid- (TNBS-) induced type-1 model colitis exhibiting histopathological features of CD through adrenomedullin (ADM) enhancement. Our current aims were to examine whether TU-100 ameliorates a type-2 model colitis that histologically resembles UC and identify the active ingredients. Methods. TU-100 was administered orally to mice with oxazolone- (OXN-) induced type-2 model colitis. The morbidity was evaluated by body weight loss and the macroscopic score of colonic lesions. ADM was quantified using an EIA kit. Results. TU-100 prevented weight loss and colon ulceration. ADM production by intestinal epithelial cells was increased by TU-100 addition. Screening to identify active ingredients showed that [6]-shogaol and hydroxy α-sanshool enhanced ADM production. Conclusions. TU-100 exerted a protective effect in OXN-induced type-2 model colitis, indicating that TU-100 may be a beneficial agent for treatment of UC.

OBSERVATIONAL CONSTRAINTS ON D-TERM BRANEWORLD INFLATION

We consider a supersymmetric hybrid inflation in the framework of the Randall–Sundrum type-2 braneworld model. We derive an analytical expression for the effective scalar potential and find that the D-term dominates hybrid inflation process. We show that we can eliminate partially the fine tuning problem related to coupling constant λ of the potential and calculate the value of FI-term ξ according to recent WMAP7 observation data. We show also that some inflationary spectrum parameters, in particular, the ratio r and the running [Formula: see text] are widely consistent with WMAP7, BAO and H0 data.

CD40 pathway activation reveals dual function for macrophages in human endometrial cancer cell survival and invasion.

Reproductive malignancies are a major cause of cancer death in women worldwide. CD40 is a TNF receptor family member, which upon activation may mediate tumor regression. However, despite the great potential of CD40 agonists, their use as a therapeutic option for reproductive cancers has never been investigated. Because CD40 ligation is a potent pathway of macrophage activation, an in vitro model of pro-inflammatory type-1 (Mϕ-1) and anti-inflammatory type-2 (Mϕ-2) macrophages was developed to determine whether and how macrophage CD40 pathway activation might influence endometrial tumor cell behavior. Analysis of tumor growth kinetic in the endometrial cancer xenograft model indicates that, when injected once into the growing tumors, CD40-activated Mϕ-1 greatly reduced, while CD40-activated Mϕ-2 increased tumor size when compared to control isotype-activated Mϕ-1 and Mϕ-2, respectively. In vitro assays indicated that CD40-activated Mϕ-2 increased cell viability but failed to promote cell invasion. CD40-activated Mϕ-1, in contrast, decreased cell survival but greatly increased cell invasion in tumor cells less susceptible to cell death by apoptosis; they also induced the expression of some pro-inflammatory genes, such as IL-6, LIF, and TNF-α, known to be involved in tumor promotion and metastasis. The presence of IFN-γ is minimally required for CD40-activated Mϕ-1 to promote tumor cell invasion, a process that is mediated in part through the activation of the PI3K/Akt2 signaling pathway in tumor cells. From these results, we speculate that some functions of CD40 in tumor-associated Mϕs might limit the therapeutic development of CD40 agonists in endometrial cancer malignancies.

Blocking IL-25 signalling protects against gut inflammation in a type-2 model of colitis by suppressing nuocyte and NKT derived IL-13

BackgroundInterleukin-25 (IL-25) is a potent activator of type-2 immune responses. Mucosal inflammation in ulcerative colitis is driven by type-2 cytokines. We have previously shown that a neutralizing anti-IL-25 antibody abrogated airways hyperreactivity in an experimental model of lung allergy. Therefore, we asked whether blocking IL-25 via neutralizing antibodies against the ligand or its receptor IL-17BR could protect against inflammation in an oxazolone-induced mouse model of colitis.MethodsNeutralizing antibodies to IL-25 or IL-17BR were administered to mice with oxazolone-induced colitis, a model of ulcerative colitis. The disease onset was evaluated by weight loss and degree of colon ulceration. Also, lamina propria and mesenteric lymph node (MLN) infiltrates were assessed for mucosal inflammation and cultured in vitro to determine cytokine production.ResultsWe found that in oxazolone colitis IL-25 production derives from intestinal epithelial cells and that IL-17BR+ IL-13-producing natural killer T (NKT) cells and nuocytes drive the intestinal inflammation. Blocking IL-25 signalling considerably improved the clinical aspects of the disease, including weight loss and colon ulceration, and resulted in fewer nuocytes and NKT cells infiltrating the mucosa. The improved pathology correlated with a decrease in IL-13 production by lamina propria cells, a decrease in the production of other type-2 cytokines by MLN cells, and a decrease in blood eosinophilia and IgE.ConclusionIL-25 plays a pro-inflammatory role in the oxazolone colitis model, and neutralizing antibodies to IL-25 or IL-17BR can slow the ongoing inflammation in this disease. Because this model mimics aspects of human ulcerative colitis, these antibodies may represent potential therapeutics for reducing gut inflammation in patients.

Interval type-2 fuzzy modelling and stochastic search for real-world inventory management

Real-world systems present a variety of challenges to the modeller, not least of which is the problem of uncertainty inherent in their operation. In this research, an interval type-2 fuzzy model is applied to a real-world problem, the goal being to discover a suitable optimisation configuration to enable a search for an inventory plan using the model. To this end, a series of simulated annealing configurations and the interval type-2 fuzzy model were used to search for appropriate inventory plans for a large-scale real-world problem. A further set of tests were conducted in which the performance of the interval type-2 fuzzy model was compared with a corresponding type-1 fuzzy model. In these tests the results were inconclusive, though, as will be discussed there are many ways in which type-2 fuzzy logic can be exploited to demonstrate its advantages over a type-1 approach. To conclude, in this research we have shown that a combination of interval type-2 fuzzy logic and simulated annealing is a logical choice for inventory management modelling and inventory plan search, and propose that the benefits that a type-2 model offers, can make it preferable to a corresponding type-1 system.

Estimation of an optimum intake level of epigallocatechin gallate for suppression of inflammation in type 2 diabetic GK rats

Previous studies have suggested that epigallocatechin gallate (EGCG) exerts anti‐oxidative and anti‐inflammatory actions in various tissues, which might be beneficial for reducing risks of development of diabetes. However, it is unknown whether there is an optimum intake level of EGCG. In this study, we have examined the effect of a diet containing various concentrations of EGCG on the expression of inflammation‐related genes in various tissues including visceral adipose tissue and the liver of non‐obese type‐2 diabetes animal model, Goto‐Kakizaki (GK) rats. GK rats at 5 weeks of age were fed a control high‐fat diet (45 energy% as fat) or the high‐fat diet containing 0.1%, 0.2% or 0.5% EGCG for 34 weeks. The mRNA levels of IL‐1β, IL‐18, TNF‐α and resistin were significantly reduced in the adipose tissue of rats fed a diet containing 0.1% EGCG, but not in those fed diets containing 0.2% or more EGCG, as compared with control. The mRNA levels of IL‐1β and IL‐18 in the liver of rats fed a diet containing 0.1% EGCG were also significantly lower than those in the control. These results suggest that there is an optimum range of intake of EGCG, which may suppress the expression of genes involved in inflammation in the adipose tissue and the liver.

ET2FIS: An Evolving Type-2 Neural Fuzzy Inference System

There are two main approaches to design a neural fuzzy system; namely, through expert knowledge, and through numerical data. While the computational structure of a system is manually crafted by human experts in the former case, self-organizing neural fuzzy systems that are able to automatically extract generalized knowledge from batches of numerical training data are proposed for the latter. Nevertheless, both of these approaches are static where only parameters of a system are updated during training. On the other hand, the demands and complexities of real-life applications often require a neural fuzzy system to adapt both its parameters and structure to model the changing dynamics of the environment. To counter these modeling bottlenecks, intense research efforts are subsequently channeled into the studies of evolving/online neural fuzzy systems. There are generally two classes of evolving neural fuzzy systems: the Takagi–Sugeno–Kang (TSK) systems and the Mamdani systems. While most existing literature consists of evolving Type-1 TSK-typed and Type-1 Mamdani-typed models, they may not perform well in noisy environment. To improve the robustness of these neural fuzzy systems, recent efforts have been directed to extend evolving Type-1 TSK-typed neural fuzzy systems to Type-2 models because of their better known noise resistance abilities. In contrast, minimum similar effort has been made for evolving Mamdani-typed models. In this paper, we present a novel evolving Type-2 Mamdani-typed neural fuzzy system to bridge this gap. The proposed system is named evolving Type-2 neural fuzzy inference system (eT2FIS), and it employs a data-driven incremental learning scheme. Issues involving the online sequential learning of the eT2FIS model are carefully examined. A new rule is created when a newly arrived data is novel to the present knowledge encrypted; and an obsolete rule is deleted when it is no longer relevant to the current environment. Highly over-lapping fuzzy labels in the input–output spaces are merged to reduce the computational complexity and improve the overall interpretability of the system. By combining these three operations, eT2FIS is ensured a compact and up-to-date fuzzy rule base that is able to model the current underlying dynamics of the environment. Subsequently, the proposed eT2FIS model is employed in a series of benchmark and real-world applications to demonstrate its efficiency as an evolving neural fuzzy system, and encouraging performances have been achieved.