Redundant Signals Research Articles

Function of a multimodal signal: A multiple hypothesis test using a robot frog.

Multimodal communication may evolve because different signals may convey information about the signaller (content-based selection), increase efficacy of signal processing or transmission through the environment (efficacy-based selection), or modify the production of a signal or the receiver's response to it (inter-signal interaction selection). To understand the function of a multimodal signal (aggressive calls+toe flags) emitted by males of the frog Crossodactylus schmidti during territorial contests, we tested two hypotheses related to content-based selection (quality and redundant signal), one related to efficacy-based selection (efficacy backup), and one related to inter-signal interaction selection (context). For each hypothesis we derived unique predictions based on the biology of the study species. In a natural setting, we exposed resident males to a robot frog simulating aggressive calls (acoustic stimulus) and toe flags (visual stimulus), combined and in isolation, and measured quality-related traits from males and local levels of background noise and light intensity. Our results provide support to the context hypothesis, as toe flags (the context signal) are insufficient to elicit a receiver's response on their own. However, when toe flags are emitted together with aggressive calls, they evoke in the receiver qualitatively and quantitatively different responses from that evoked by aggressive calls alone. In contrast, we found no evidence that toe flags and aggressive calls provide complementary or redundant information about male quality, which are key predictions of the quality and redundant signal hypotheses respectively. Finally, the multimodal signal did not increase the receiver's response across natural gradients of light and background noise, a key prediction of the efficacy backup hypothesis. Toe flags accompanying aggressive calls seem to provide contextual information that modify the receiver's response in territorial contests. We suggest this contextual information is increased motivation to escalate the contest, and discuss the benefits to the signallers and receivers of adding a contextual signal to the aggressive display. Examples of context-dependent multimodal signals are rare in the literature, probably because most studies focus on single hypotheses assuming content- or efficacy-based selection. Our study highlights the importance of considering multiple selective pressures when testing multimodal signal function.

Signalling Three-Way Intersections: Is Redundancy Better Than Only Mandatory or Prohibitory Signs?

At intersections, drivers need to infer which ways are allowed by interpreting mandatory and/or prohibitory traffic signs. Time and accuracy in this decision-making process are crucial factors to avoid accidents. Previous studies show that integrating information from prohibitory signs is generally more difficult than from mandatory signs. In Study 1, we compare combined redundant signalling conditions to simple sign conditions at three-way intersections. In Study 2, we carried out a survey among professionals responsible for signposting to test whether common practices are consistent with experimental research. In Study 1, an experimental task was applied (n=24), and in Study 2, the survey response rate was 17%. These included the main cities in Spain such as Madrid and Barcelona. Study 1 showed that inferences with mandatory signs are faster than those with prohibitory signs, and redundant information is an improvement only on prohibitory signs. In Study 2, prohibitory signs were those most frequently chosen by professionals responsible for signposting. In conclusion, the most used signs, according to the laboratory study, were not the best ones for signposting because the faster responses were obtained for mandatory signs, and in second place for redundant signs.

Rolling bearing diagnosis method based on improved standardized variable distance fusion hierarchical state space correlation entropy

In recent years, the machine learning method has been successfully applied to the intelligent health monitoring of rolling bearings. However, its effectiveness depends heavily on the vibration signal time series collected. For the purpose of abundantly excavate the fault feature information in time series, some new multi-scale entropy methods are used to solve this problem. However, the multi-scale entropy only considers the low frequency component of the signal, neglects the high frequency component of the signal, loses some fault signals with modulation phenomenon, and reduces the accuracy of fault classification. Therefore, in order to overcome the shortcomings of multi-scale entropy. In this paper, proposing a new hierarchical state space correlation entropy (HSSCEn) to extract the fault features contained in the signal. At the same time, in practice, the fault features extracted by HSSCEn are usually high and nonlinear. Directly input to the classifier for training and testing will reduce the accuracy of machine learning method recognition. Therefore, an improved standardized variable distance classifier is proposed in this paper. It effectively reduces the feature redundancy of signal and improves the accuracy of original classifier. Finally, in order to verify the validity of the fault diagnosis method based on HSSCEn fusion standardized variable distance classifier, two sets of fault classification experiments are carried out in this paper. Compared with existing fault identification classifier algorithms, the proposed method has more advantages in accuracy and stability of fault classification.

Potential of miRNA-Based Nanotherapeutics for Uveal Melanoma.

Simple SummaryHuman uveal melanoma (UM) is the most common primary intraocular tumor with high metastatic risk in adults. Currently, no effective treatment is available for metastatic UM; therefore, new therapeutic approaches are needed to improve overall survival. Given the increased understanding of microRNAs (miRNAs) and their roles in UM tumorigenesis and metastasis, miRNA-based therapy may offer the hope of improving therapeutic outcomes. This review summarizes the actions of select miRNAs examined in preclinical studies using miRNAs as therapeutic targets in UM. The focus of this review is the application of established nanotechnology-assisted delivery systems to overcome the limitations of therapeutic miRNAs. A blend of therapeutic miRNAs and nanodelivery systems may facilitate the translation of miRNA therapies to clinical settings.Uveal melanoma (UM) is the most common adult intraocular cancer, and metastatic UM remains deadly and incurable. UM is a complex disease associated with the deregulation of numerous genes and redundant intracellular signaling pathways. As understanding of epigenetic dysregulation in the oncogenesis of UM has increased, the abnormal expression of microRNAs (miRNAs) has been found to be an epigenetic mechanism underlying UM tumorigenesis. A growing number of miRNAs are being found to be associated with aberrant signaling pathways in UM, and some have been investigated and functionally characterized in preclinical settings. This review summarizes the miRNAs with promising therapeutic potential for UM treatment, paying special attention to the therapeutic miRNAs (miRNA mimics or inhibitors) used to restore dysregulated miRNAs to their normal levels. However, several physical and physiological limitations associated with therapeutic miRNAs have prevented their translation to cancer therapeutics. With the advent of nanotechnology delivery systems, the development of effective targeted therapies for patients with UM has received great attention. Therefore, this review provides an overview of the use of nanotechnology drug delivery systems, particularly nanocarriers that can be loaded with therapeutic miRNAs for effective delivery into target cells. The development of miRNA-based therapeutics with nanotechnology-based delivery systems may overcome the barriers of therapeutic miRNAs, thereby enabling their translation to therapeutics, enabling more effective targeting of UM cells and consequently improving therapeutic outcomes.

ET-UMAP integration feature for ECG biometrics using Stacking

In recent years, personal information leakage incidents have occurred frequently. Currently, a safe and efficient identification method is essential to prevent data leakage. The electrocardiogram (ECG) has attracted more and more attention because of its high security. Researchers have made many progresses in the study of ECG identification. However, there is feature redundancy in the original heartbeats, which will lead to low identification accuracy. To address above issues, this paper proposes a new ECG biometrics configuration: the extremely randomized trees (ET) and Uniform Manifold Approximation and Projection (UMAP) integration feature (ETUMAP feature) for ECG biometrics using Stacking. First, we extract the primary features from the ECG signal with the primary learner of Stacked Generalization (Stacking), namely the extremely randomized trees, and then fuse the UMAP dimensionality reduction algorithm to generate the ETUMAP features. Second, the ETUMAP features are fed into Stacking's secondary learner, extreme gradient boosting (XGBoost), to complete the identification. The effectiveness of the proposed method is evaluated on two public databases, namely, ECG-ID and PTB database. Our method can achieve high subject identification accuracies of 98.88% and 95.77% from the ECG-ID (89 individuals) and PTB (71 individuals) database. In addition, the subject identification accuracy reaches 96.88% in classifying above 160 individuals. Experimental results show that our method effectively reduces redundancy of ECG signals, and has preferable performance and generalization of identification.

An Improved Adaptive Subsurface Phytoplankton Layer Detection Method for Ocean Lidar Data

Phytoplankton, as the foundation of primary production, is of great significant for the marine ecosystem. The vertical distribution of phytoplankton contains key information about marine ecology and the optical properties of water bodies related to remote sensing.The common methods to detect subsurface phytoplankton biomass are often in situ measurements and passive remote sensing; however, the bio-argo measurement is discrete and costly, and the passive remote sensing measurement is limited to obtain the vertical information. As a component of active remote sensing, lidar technology has been proved as an effective method for mapping the vertical distribution of phytoplankton. In the past years, there have been few studies on the phytoplankton layer extraction method for lidar data. The existing subsurface layer extraction algorithms are often non-automatic, which need manual intervention or empirical parameters to set the layer extraction threshold. Hence, an improved adaptive subsurface phytoplankton layer detection method was proposed, which incorporates a curve fitting method and a robust estimation method to determine the depth and thickness of subsurface phytoplankton scattering layer. The combination of robust estimation method can realize automatic calculation of layer detection threshold according to the characteristic of each lidar signal, instead of an empirical fixed value used in previous works. In addition, the noise jamming signal can also be effectively detected and removed. Lidar data and in situ spatio-temporal matching Chlorophyll-a profile data obtained in Sanya Bay in 2018 was used for algorithm verification. The example result of step-by-step process illustrates that the improved method is available for adaptive threshold determination for layer detection and redundant noise signals elimination. Correlation analysis and statistical hypothesis testing shows the retrieved subsurface phytoplankton maximum depth by the improved method and in situ measurement is highly relevant. The absolute difference of layer maximum depth between lidar data and in situ data for all stations is less than 0.75 m, and mean absolute difference of layer thickness difference is about 1.74 m. At last, the improved method was also applied to the lidar data obtained near Wuzhizhou Island seawater, which proves that the method is feasiable and robust for various sea areas.

Simultaneous sparse learning algorithm of structured approximation with transformation analysis embedded in Bayesian framework

Sparse approximation is critical to the applications of signal or image processing, and it is conducive to estimate the sparse signals with the joint efforts of transformation analysis. A simultaneous Bayesian framework is extended for sparse approximation by structured shared support, and a simultaneous sparse learning algorithm of structured approximation is proposed with transformation analysis, which leads to the feasible solutions more sensibly. Then the improvements of sparse Bayesian learning and iterative reweighting are embedded into the framework to achieve rapid convergence and high efficiency with robustness. Furthermore, the iterative optimization and transformation analysis are embedded in the overall learning process to obtain the relative optima for sparse approximation. Finally, compared with conventional reweighting algorithms for simultaneous sparse models with l1 and l2, simulation results present the preponderance of the proposed approach to solve the sparse structure and iterative redundancy in processing sparse signals. The fact indicates that the proposed method will be effective to sparsely approximate the various signals and images, which does accurately analyze the target in optimal transformation. It is envisaged that the proposed model could be suitable for a wide range of data in sparse separation and signal denoising.

Variable selection in the chemometric treatment of food data: A tutorial review

Food analysis covers aspects of quality and detection of possible frauds to ensure the integrity of the food. The arsenal of analytical instruments available for food analysis is broad and allows the generation of a large volume of information per sample. But this instrumental information may not yet give the desired answer; it must be processed to provide a final answer for decision making. The possibility of discarding non-informative and/or redundant signals can lead to models of better accuracy, robustness, and chemical interpretability, in line with the principle of parsimony. Thus, in this tutorial review, we cover aspects of variable selection in food analysis, including definitions, theoretical aspects of variable selection, and case studies showing the advantages of variable selection-based models concerning the use of a wide range of non-informative and redundant instrumental information in the analysis of food matrices.

Research on Hybrid Redundancy Voting Algorithm Based on Fuzzy Theory

The hardware redundancy technology is to reduce the basic reliability in exchange for the high reliability and safety of the system, but the failure rate of the system will increase with the increase of the hardware redundancy. Aiming at the disadvantages of hardware redundancy, the article takes the angle of attack(AOA) as the object, and constructs the analytical value of AOA based on the analytical relationship between the sensors of the flight control system; Introduce an equalization algorithm to eliminate the drift error between redundant signals, further proposes a hybrid redundancy voting algorithm based on hardware redundancy and analysis redundancy. The algorithm calculates the weight of the sensor signal based on the difference between the sensor signal and the analytical value, so that the voting value is closer to the true value, thereby improving the safety of the system. At the end of the article, the feasibility of the voting algorithm is verified by simulation; the analytical study of the AOA proves the effectiveness of the hybrid redundancy design scheme and the voting algorithm.

Information out of the blue: phenotypic correlates of abdominal color patches in Sceloporus lizards

Colorful ornaments are important visual signals for animal communication that can provide critical information about the quality of the signaler. In this study, we focused on different color characteristics of the abdominal patches of males of six lizard species from the genus Sceloporus. We addressed three main objectives. First, we examined if size, brightness, saturation, and conspicuousness of these ornaments are indicative of body size, condition, immune function, or levels of testosterone and corticosterone. Second, we evaluated if the distinct components of these abdominal patches (blue or green patches and black stripes) transmit similar information about the signaler, which would support the redundant signal hypothesis, or if these components are related to different phenotypic traits, which would support the multiple message hypothesis. Third, we compared the phenotypic correlates of these ornaments among our six species to understand the degree of conservatism in the signaling patterns or to find species-specific signals. Using data collected from males in natural conditions and a multi-model inference framework, we found that in most species the area of the patches and the brightness of the blue component are positively related to body size. Thus, these color characteristics are presumably indicative of the physical strength and competitive ability of males and these shared signals were likely inherited from a common ancestor. In half of the species, males in good body condition also exhibit relatively larger blue and black areas, suggesting that the expression of these ornaments is condition-dependent. Abdominal patches also provide information about immunocompetence of the males as indicated by different correlations between certain color characteristics and ectoparasite load, counts of heterophils, and the heterophil:lymphocyte ratio. Our findings reveal that area and brightness of the abdominal patches signal the size and body condition of males, whereas blue saturation and conspicuousness with respect to the surrounding substrate are indicative of immune condition, thus supporting the multiple message hypothesis. However, some of these correlations were not shared by all species and, hence, point to intriguing species-specific signals.

Redundant cytokine requirement for intestinal microbiota-induced Th17 cell differentiation in draining lymph nodes.

Differentiation of intestinal T helper 17 (Th17) cells, which contribute to mucosal barrier protection from invasive pathogens, is dependent on colonization with distinct commensal bacteria. Segmented filamentous bacteria (SFB) are sufficient to support Th17 cell differentiation in mouse, but the molecular and cellular requirements for this process remain incompletely characterized. Here, we show that intestine-draining mesenteric lymph nodes (MLNs), not intestine proper, are the dominant site of SFB-induced intestinal Th17 cell differentiation. Subsequent migration of these cells to the intestinal lamina propria is dependent on their upregulation of integrin β7. Stat3-dependent induction of RORγt, the Th17 cell-specifying transcription factor, largely depends on IL-6, but signaling through the receptors for IL-21 and IL-23 can compensate for absence of IL-6 to promote SFB-directed Th17 cell differentiation. These results indicate that redundant cytokine signals guide commensal microbe-dependent Th17 cell differentiation in the MLNs and accumulation of the cells in the lamina propria.

Generation of Naïve Blastoderm Explants from Zebrafish Embryos

Due to their optical clarity and rapid development, zebrafish embryos are an excellent system for examining cell behaviors and developmental processes. However, because of the complexity and redundancy of embryonic signals, it can be challenging to discern the complete role of any single signal during early embryogenesis. By explanting the animal region of the zebrafish blastoderm, relatively naïve clusters of embryonic cells are generated that can be easily cultured and manipulated ex vivo. By introducing a gene of interest by RNA injection before explantation, one can assess the effect of this molecule on gene expression, cell behaviors, and other developmental processes in relative isolation. Furthermore, cells from embryos of different genotypes or conditions can be combined in a single chimeric explant to examine cell/tissue interactions and tissue-specific gene functions. This article provides instructions for generating zebrafish blastoderm explants and demonstrates that a single signaling molecule - a Nodal ligand - is sufficient to induce germ layer formation and extension morphogenesis in otherwise naïve embryonic tissues. Due to their ability to recapitulate embryonic cell behaviors, morphogen gradients, and gene expression patterns in a simplified ex vivo system, these explants are anticipated to be of great utility to many zebrafish researchers.

Generation of Naïve Blastoderm Explants from Zebrafish Embryos.

Due to their optical clarity and rapid development, zebrafish embryos are an excellent system for examining cell behaviors and developmental processes. However, because of the complexity and redundancy of embryonic signals, it can be challenging to discern the complete role of any single signal during early embryogenesis. By explanting the animal region of the zebrafish blastoderm, relatively naïve clusters of embryonic cells are generated that can be easily cultured and manipulated ex vivo. By introducing a gene of interest by RNA injection before explantation, one can assess the effect of this molecule on gene expression, cell behaviors, and other developmental processes in relative isolation. Furthermore, cells from embryos of different genotypes or conditions can be combined in a single chimeric explant to examine cell/tissue interactions and tissue-specific gene functions. This article provides instructions for generating zebrafish blastoderm explants and demonstrates that a single signaling molecule - a Nodal ligand - is sufficient to induce germ layer formation and extension morphogenesis in otherwise naïve embryonic tissues. Due to their ability to recapitulate embryonic cell behaviors, morphogen gradients, and gene expression patterns in a simplified ex vivo system, these explants are anticipated to be of great utility to many zebrafish researchers.

Abstract 1477: Co-targeting c-Met and c-Src pathways to inhibit metastatic cancer cell migration and invasion

Abstract Overexpression of tyrosine kinases c-Src and c-Met has been shown to be highly associated with disease progression and poor clinical outcomes in many types of cancers. Although small molecule Src or Met inhibitors are being individually evaluated in clinical trials, patient data suggest that single treatment with any of these inhibitors only yield limited effects. One possibility is that redundant signaling pathways in tumor cells may allow tumor cell functions less interrupted upon inhibition of only one pathway. We therefore propose that c-Src and c-Met are two compensatory pathways that may cooperate to promote cancer metastasis. In order to delineate this hypothesis, we studied treatment effects of combining inhibitors targeting c-Src (dasatinib) and c-Met (ASLAN002) on multiple functional behaviors associated with tumor metastasis in c-Src and c-Met expressing metastatic cancer cells. Combination of Src- and Met-inhibitors was found to strongly inhibit cell colony formation by clonogenic survival assay. In a wound-healing assay, compared to either treatment alone, the combinatorial treatment exhibited greater suppression on cell motility. In addition, using a Matrigel-based Transwell assay, dasatinib plus ASLAN002 resulted in significant reduction of cell invasion in the presence or absence of HGF. Western blot analysis demonstrated that co-targeting Met and Src kinases lead to not only inhibition on c-Met and c-Src autophosphorylation but also multiple downstream kinases such as focal adhesion kinase (FAK), Akt and extracellular signal-regulated kinase (ERK). These data indicate that combined application of small molecule Src and Met inhibitors cause significant impairment on functional behaviors associated with cancer metastasis in vitro including survival, migration and invasion, suggesting that this combination intervention modality may serve as a potential anti-metastatic strategy that could be further tested in metastatic models in vivo. Citation Format: Yao Dai, Dietmar W. Siemann. Co-targeting c-Met and c-Src pathways to inhibit metastatic cancer cell migration and invasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1477.

A Phase II Trial of Sirolimus with Standard Induction Chemotherapy in Patients with De Novo Acute Myeloid Leukemia

Background: The initial treatment of FLT3 wild type acute myeloid leukemia (AML) has not significantly changed since induction therapy with Ara-C and anthracyclines was first developed. Preclinical data suggests constitutive activation of the AKT3/mammalian target of rapamycin (mTOR) pathway may play a role in pathogenesis of this disease in a subset of AML patients. Previous data from our group has shown that the presence of phosphorylated ribosomal S6 (pS6) in AML blasts as detected by flow cytometry may predict response to the combination of sirolimus and induction chemotherapy. Here we report the clinical and pharmacodynamics results of a phase II study of the combination of these drugs.Methods: Subjects had newly diagnosed AML based on WHO criteria. Subjects received oral sirolimus starting on day 1 (12 mg loading dose) then 4 mg daily on days 2-10 with idarubicin 12mg/m2 days 4-7 and cytarabine 100mg/m2 days 4-10. Clinical response was assessed at hematologic recovery or by day 42 using IWG for response. Samples for pharmacodynamic studies of blasts were drawn prior to treatment with sirolimus on day 1, and then again prior to dosing of idarubicin and cytarabine on day 4. Assessment of pS6 on gated blasts, a biomarker of mTORC1 activation, was assessed by flow cytometry using previously described methods.Results: 55 patients enrolled on this trial received sirolimus with an average age of 58 years. Toxicity was similar to published 7+3 data and prolonged aplasia without recovery was not observed. Twenty-nine patients (53%) had high risk cytogenetic or molecular mutations, 15 (27%) had intermediate risk disease, and 11 (20%) patients had lower risk disease. As a whole, 35 patients (64%) entered into CR or CRp, 1 had a PR, 17 (27%) were non-responders. Two (4%) patients (ages 64 and 71) died during induction. Thirteen (45%) patients with high risk disease had a CR or CRp, 14 (48%) were non-responders, and 2 died in induction. Of the 15 subjects with intermediate risk disease, 11 (79%) patients had a CR or CRp, 1 had a partial response, and 3 were non-responders. All low risk patients had a CR, and 9 of 11 are alive and in remission at the time of censoring of data with a median time on study of 674 days. One patient with low risk disease subsequently relapsed, went to stem cell transplant, and is currently in CR. Two patients with low risk disease refused to proceed with standard of care consolidation; of these, 1 is alive and in remission 946 days from study entry, and 1 died in relapse. Fifteen patients (27%) subsequently underwent allogeneic stem cell transplantation in CR, and 8 (53%) are still alive an average of 358 days after transplant.Thirty-seven of 55 patients had adequate samples for pharmacodynamic analysis. Surprisingly, all patients demonstrated activation of ribosomal S6 prior to therapy in contrast to 67% positivity seen in previous studies that focused on patients with relapsed AML. mTORC1 was inhibited greater than 40% in 28/37 (76%) of patients. Inhibition did not correlate with either overall survival or age of patients.Conclusions: Sirolimus and 7+3 is a well-tolerated regimen. mTORC1 appears to be activated in almost all patients at the time of diagnosis of AML as assessed by flow cytometric assessment of ribosomal S6. Inhibition of mTORC1 did not correlate with response, suggesting that AML cells may have redundant signaling pathways that regulate chemosensitivity when mTORC1 is inhibited. Given the large percentage of samples with mTORC1 activation in this upfront AML study, future research into dual mTORC inhibitors may prove valuable. DisclosuresCarroll:Astellas Pharmaceuticals: Research Funding; Incyte Pharmaceuticals: Research Funding. Porcu:Innate Pharma: Research Funding; Kura: Research Funding; Miragen: Research Funding; Kiowa: Research Funding; Galderma: Research Funding; Tetralogic: Research Funding; Cell Medica: Research Funding; Celgene: Research Funding. Perl:Arog Pharmaceuticals: Consultancy; Novartis: Other: Advisory Board; Pfizer: Other: Advisory Board; Seattle Genetics: Other: Advisory board; Asana Biosciences: Other: Scientific advisory board; Astellas: Consultancy; Daiichi Sankyo: Consultancy; Actinium Pharmaceuticals: Other: Scientific Advisory Board.

Cytokine Activation of JAK Kinases Rescues FLT3-Mutant AML from FLT3 Inhibition and Requires PIM Kinases

Mutations in the FMS-like tyrosine kinase 3 (FLT3) receptor tyrosine kinase occur in ~30% of acute myeloid leukemias (AMLs) and are associated with a poor prognosis. Activating mutations in FLT3 predominantly occur as internal tandem duplications in the juxtamembrane region (FLT3-ITD), resulting in constitutive activation of canonical signaling pathways including STAT5, RAS/MAPK, and PI3K/mTORC1. Selective, potent 2nd and 3rd generation FLT3 inhibitors have shown significant clinical activity in patients with relapsed FLT3-ITD+ AML; however, clearance of FLT3 mutant clones does not consistently occur and most patients will eventually progress after an initial response. This challenges the model of FLT3 mutant AML being oncogene addicted and suggests that redundant signaling pathways may regulate AML cell survival after FLT3 inhibition. We hypothesized that these cells are resistant to FLT3 inhibition due to cytokines within the bone marrow microenvironment, resulting in low levels of primary resistant cells that will ultimately result in relapse. We have shown that primary FLT3-ITD+ AML cells escape FLT3 inhibition in vitro in the presence of cytokines produced normally in the bone marrow and that this effect is abrogated in patient cells by co-treatment with a JAK kinase inhibitor. To understand the mechanism of this rescue, we have studied a FLT3-ITD+ AML cell line (MV4;11). GM-CSF and IL-3 in particular are able to rescue cells from apoptosis following FLT3 inhibition. Interestingly, despite reactivating the canonical signaling pathways, GM-CSF and IL-3 maintain cell survival without rescuing proliferation, consistent with the clinical scenario. Both GM-CSF and IL-3 signal through JAK kinases. Co-treatment with the JAK1/2 inhibitor, ruxolitinib, or STAT5 knockdown re-sensitized AML cells to FLT3 inhibition when grown in the presence of cytokines. Inhibition of MEK or mTORC1 was unable to fully abrogate cytokine-mediated rescue of cell survival. These data demonstrate that JAK-dependent cytokine signaling mediate rescue from FLT3 inhibition through STAT5, but is not dependent on reactivation of MAPK or mTORC1 pathways. PIM kinases are a non-canonical target downstream of FLT3-ITD and downstream of STATs in cytokine signaling. PIM kinases are transcriptionally regulated. All three PIM isoforms were downregulated upon FLT3 inhibition. Both GM-CSF and IL-3 rescued PIM1 and PIM2 expression versus IL-6, a cytokine that is unable to protect from FLT3 inhibition. Co-treatment with a novel pan-PIM kinase inhibitor (INCB053914), was sufficient to block IL-3 rescue of cell survival. Altogether, these data demonstrate that FLT3-ITD+ AML cells utilize redundant signaling pathways activated by bone marrow cytokines through a JAK-STAT5-PIM axis to escape cell death from FLT3 inhibition. Pre-clinical testing with patient-derived xenografts is planned to validate these findings in an in vivo model and assess the feasibility of these combination approaches to improve clinical responses to FLT3 inhibitor therapy. DisclosuresSung:Radius Health Inc.: Equity Ownership. Koblish:Incyte Corporation: Employment, Equity Ownership. Perl:Seattle Genetics: Other: Advisory board; Astellas: Consultancy; Actinium Pharmaceuticals: Other: Scientific Advisory Board; Daiichi Sankyo: Consultancy; Novartis: Other: Advisory Board; Arog Pharmaceuticals: Consultancy; Pfizer: Other: Advisory Board; Asana Biosciences: Other: Scientific advisory board. Carroll:Incyte Pharmaceuticals: Research Funding; Astellas Pharmaceuticals: Research Funding.

Fault diagnosis of SOFC system based on single cell voltage analysis

The commercialization of Solid Oxide Fuel Cell (SOFC) systems is restricted by the low reliability and durability severely. Generally, a SOFC system includes stack, combustion chamber, fuel heat exchanger, air heat exchanger, steam generator, reformer, and blower, etc. Faults of any part of the SOFC system will affect the performance of the entire system at any time, causing a decrease in the durability and reliability. Therefore, more and more attention has focused on the fault diagnosis technology on the SOFC system lifetime research. However, the practicability of current fault diagnosis algorithm is not enough on account of the redundant fault signals. This paper proposed an improved algorithm for the fault diagnosis using the single cell voltage as the only fault characteristic signal. The voltage signal in time domain with four representative system faults (stack degradation failure, reformer degradation failure, fuel leakage failure, and air leakage failure) are generated by simulation. The fault voltage signal in frequency domain is obtained by Fourier transform of voltage signal in time domain. Then the characteristics of the fault voltage signal in time domain and in frequency domain are extracted, and the voltage performance of fault signal in time domain are analyzed. The single fault and simultaneous fault were diagnosed for four representative system faults and their combination using a suitable classifier. Both types of the fault diagnoses have achieved good recognition effects, which fully verified the feasibility of this improved algorithm.

Метод дифференциального пространственно-временного блокового кодирования для применения в системах подвижной радиосвязи с использованием технологии MIMO.

In radio communication systems, when implementing coherent types of reception, it is assumed that the receiver knows information about the state of the communication channel, which is achieved by introducing signal redundancy (pilot signals). The frequency of sending pilot signals depends on factors that change the state of the communication channel, one of which is the high speed of movement of mobile stations. The use of pilot signals not only hinders the efficient use of the radio frequency resource, but also, in the case of fast fading, does not allow the channel to be estimated and tracked with the required accuracy. These disadvantages can be eliminated by using the differential transmission method, for the implementation of which there is no need to know information about the state of the channel. The application of the principles of differential transmission to space-time coding does not find sufficiently effective solutions that combine low computational complexity and energy efficiency of differential coding methods.

Multiple Sensor Fail-Operational Architecture for Electric Vehicle Powertrain Control System

With the expanding demand to meet specific safety requirements, a new definition of the architecture at the system level is required to keep the powertrain system still operational after the fault emerge of some sensors. This work proposes a fail-operational architecture by integrating battery management and motor control system, which implements heterogeneous sensor signal reconstruction and model-based signal estimation for redundant signal generation and adopts random forest for signal arbitration. The proposed architecture can reduce the system failure rate and allow a fault-toleration of up to three sensors at any given time without increasing costs. Finally, the proposed architecture was verified by comparing the fault detection performance among three arbitration algorithms in a model in the loop (MIL) platform.

Probabilistic reduction and mental accumulation in Japanese: Frequency, contextual predictability, and average predictability

A large number of studies have demonstrated that a linguistic unit with higher frequency and that with higher contextual predictability are realized with reduced speech signals. This effect is known in previous literature as probabilistic reduction. A few studies also demonstrate that these contextual effects may be memorized; that is, average predictability may also influence phonetic redundancy in speech signals. This study aims to investigate the extent to which probabilistic reduction effects extend to morpheme duration in Japanese. It is demonstrated that the production of a morpheme in Japanese is influenced by morpheme frequency, contextual morpheme predictability, and average morpheme predictability. These findings are interpreted to mean that speech signals are influenced by ease of lexical access or they are modified to maximize communicative ease, and the productions are accumulated in the mind of a speaker.