Journal articles on the topic 'Time-varying graph signals'

The paper presents an analysis and overview of vertex–frequency analysis, an emerging area in graph signal processing. A strong formal link of this area to classical time–frequency analysis is provided. Vertex–frequency localization-based approaches to analyzing signals on the graph emerged as a response to challenges of analysis of big data on irregular domains. Graph signals are either localized in the vertex domain before the spectral analysis is performed or are localized in the spectral domain prior to the inverse graph Fourier transform is applied. The latter approach is the spectral form of the vertex–frequency analysis, and it will be considered in this paper since the spectral domain for signal localization is well ordered and thus simpler for application to the graph signals. The localized graph Fourier transform is defined based on its counterpart, the short-time Fourier transform, in classical signal analysis. We consider various spectral window forms based on which these transforms can tackle the localized signal behavior. Conditions for the signal reconstruction, known as the overlap-and-add (OLA) and weighted overlap-and-add (WOLA) methods, are also considered. Since the graphs can be very large, the realizations of vertex–frequency representations using polynomial form localization have a particular significance. These forms use only very localized vertex domains, and do not require either the graph Fourier transform or the inverse graph Fourier transform, are computationally efficient. These kinds of implementations are then applied to classical time–frequency analysis since their simplicity can be very attractive for the implementation in the case of large time-domain signals. Spectral varying forms of the localization functions are presented as well. These spectral varying forms are related to the wavelet transform. For completeness, the inversion and signal reconstruction are discussed as well. The presented theory is illustrated and demonstrated on numerical examples.

This paper considers the problem of adaptive estimation of graph signals under the impulsive noise environment. The existing least mean squares (LMS) approach suffers from severe performance degradation under an impulsive environment that widely occurs in various practical applications. We present a novel adaptive estimation over graphs based on Welsch loss (WL-G) to handle the problems related to impulsive interference. The proposed WL-G algorithm can efficiently reconstruct graph signals from the observations with impulsive noises by formulating the reconstruction problem as an optimization based on Welsch loss. An analysis on the performance of the WL-G is presented to develop effective sampling strategies for graph signals. A novel graph sampling approach is also proposed and used in conjunction with the WL-G to tackle the time-varying case. The performance advantages of the proposed WL-G over the existing LMS regarding graph signal reconstruction under impulsive noise environment are demonstrated.

We develop online graph learning algorithms from streaming network data. Our goal is to track the (possibly) time-varying network topology, and affect memory and computational savings by processing the data on-the-fly as they are acquired. The setup entails observations modeled as stationary graph signals generated by local diffusion dynamics on the unknown network. Moreover, we may have a priori information on the presence or absence of a few edges as in the link prediction problem. The stationarity assumption implies that the observations’ covariance matrix and the so-called graph shift operator (GSO—a matrix encoding the graph topology) commute under mild requirements. This motivates formulating the topology inference task as an inverse problem, whereby one searches for a sparse GSO that is structurally admissible and approximately commutes with the observations’ empirical covariance matrix. For streaming data, said covariance can be updated recursively, and we show online proximal gradient iterations can be brought to bear to efficiently track the time-varying solution of the inverse problem with quantifiable guarantees. Specifically, we derive conditions under which the GSO recovery cost is strongly convex and use this property to prove that the online algorithm converges to within a neighborhood of the optimal time-varying batch solution. Numerical tests illustrate the effectiveness of the proposed graph learning approach in adapting to streaming information and tracking changes in the sought dynamic network.

Time-varying autoregressive (TVAR) models are widely used for modeling of non-stationary signals. Unfortunately, online joint adaptation of both states and parameters in these models remains a challenge. In this paper, we represent the TVAR model by a factor graph and solve the inference problem by automated message passing-based inference for states and parameters. We derive structured variational update rules for a composite “AR node” with probabilistic observations that can be used as a plug-in module in hierarchical models, for example, to model the time-varying behavior of the hyper-parameters of a time-varying AR model. Our method includes tracking of variational free energy (FE) as a Bayesian measure of TVAR model performance. The proposed methods are verified on a synthetic data set and validated on real-world data from temperature modeling and speech enhancement tasks.

The purpose of this paper is to infer a dynamic graph as a global (collective) model of time-varying measurements at a set of network nodes. This model captures both pairwise as well as higher order interactions (i.e., more than two nodes) among the nodes. The motivation of this work lies in the search for a connectome model which properly captures brain functionality across all regions of the brain, and possibly at individual neurons. We formulate it as an optimization problem, a quadratic objective functional and tensor information of observed node signals over short time intervals. The proper regularization constraints reflect the graph smoothness and other dynamics involving the underlying graph’s Laplacian, as well as the time evolution smoothness of the underlying graph. The resulting joint optimization is solved by a continuous relaxation of the weight parameters and an introduced novel gradient-projection scheme. While the work may be applicable to any time-evolving data set (e.g., fMRI), we apply our algorithm to a real-world dataset comprising recorded activities of individual brain cells. The resulting model is shown to be not only viable but also efficiently computable.

This paper proposes an adaptive fuzzy distributed consensus tracking control scheme for a class of uncertain nonlinear dynamic multiagent systems (MASs) with state time-varying delays and state time-varying constraints. The existing controllers with Lyapunov–Krasovskii functions (LKFs) were not suitable to address time-varying delays and time-varying constraints in nonlinear MASs simultaneously. State constraints further increase the difficulty of controller design and stability analysis, especially for nonstrict feedback systems. Fuzzy logic systems (FLSs) tackle the approximation of unknown dynamics functions and parameters. Especially when the distributed consensus tracking error is infinitely close to the origin, although there is no singular value, it would lead to the rapid growth of control rate or uncontrollability. Constructing appropriate piecewise functions can effectively avoid the above occurrence and accelerate convergence. Based on Lyapunov stability theory and algebraic graph theory, the constructed tracking control can ensure states within defined time-varying constraint bounds and eliminate the influence of time delays. All signals in closed-loop systems can be guaranteed semiglobally uniformly ultimately bounded (SUUB). Finally, the validity of the theoretical method is verified by the simulation.

In this brief, we study the distributed adaptive fixed-time tracking consensus control problem for multiple strict-feedback systems with uncertain nonlinearities under a directed graph topology. It is assumed that the leader’s output is time varying and has been accessed by only a small fraction of followers in a group. The distributed fixed-time tracking consensus control is proposed to design local consensus controllers in order to guarantee the consensus tracking between the followers and the leader and ensure the error convergence time is independent of the systems’ initial state. The function approximation technique using radial basis function neural networks (RBFNNs) is employed to compensate for unknown nonlinear terms induced from the controller design procedure. From the Lyapunov stability theorem and graph theory, it is shown that, by using the proposed fixed-time control strategy, all signals in the closed-loop system and the consensus tracking errors are cooperatively semiglobally uniformly bounded and the errors converge to a neighborhood of the origin within a fixed time. Finally, the effectiveness of the proposed control strategy has been proved by rigorous stability analysis and two simulation examples.

PurposeA recent innovative technology used in wireless communication is recognized as multiple input multiple output (MIMO) communication system and became popular for quicker data transmission speed. This technology is being examined and implemented for the latest broadband wireless connectivity networks. Though high-capacity wireless channel is identified, there is still requirement of better techniques to get increased data transmission speed with acceptable reliability. There are two types of systems comprising of multi-antennas placed at transmitting and receiving sides, of which first is diversity technique and another is spatial multiplexing method. By making use of these diversity techniques, the reliability of transmitting signal can be improved. The fundamental method of the diversity is to transform wireless channel such as Rayleigh fading into steady additive white Gaussian noise (AWGN) channel which is devoid of any disastrous fading of the signal. The maximum transmission speed that can be achieved by spatial multiplexing methods is nearly equal to channel capacity of MIMO. Conversely, for diversity methods, the maximum speed of broadcasting is much lower than channel capacity of MIMO. With the advent of space–time block coding (STBC) antenna diversity technique, higher-speed data transmission is achievable for spatially multiplexed multiple input multiple output (SM-MIMO) system. At the receiving end, detection of the signal is a complex task for system which exhibits SM-MIMO. Additionally, a link modification method is implemented to decide appropriate coding and modulation scheme such as space diversity technique STBC to use two-way radio resources efficiently. The proposed work attempts to improve detection of signal at receiving end by employing STBC diversity technique for linear detection methods such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC) and maximum likelihood detection (MLD). The performance of MLD has been found to be better than other detection techniques.Design/methodology/approachAlamouti's STBC uses two transmit antennas regardless of the number of receiver antennas. The encoding and decoding operation of STBC is shown in the earlier cited diagram. In the following matrix, the rows of each coding scheme represent a different time instant, while the columns represent the transmitted symbols through each different antenna. In this case, the first and second rows represent the transmission at the first and second time instant, respectively. At a time t, the symbol s1 and symbol s2 are transmitted from antenna 1 and antenna 2, respectively. Assuming that each symbol has duration T, then at time t + T, the symbols –s2* and s1*, where (.)* denotes the complex conjugate, are transmitted from antenna 1 and antenna 2, respectively. Case of one receiver antenna: The reception and decoding of the signal depend on the number of receiver antennas available. For the case of one receiver antenna, the received signals are received at antenna 1 , hij is the channel transfer function from the jth transmit antenna and the ith receiver antenna, n1 is a complex random variable representing noise at antenna 1 and x (k) denotes x at time instant k ( at time t + (k – 1)T.FindingsThe results obtained for maximal ratio combining (MRC) with 1 × 4 scheme show that the BER curve drops to 10–4 for signal-to-noise (SNR) ratio of 10 dB, whereas for MRC 1 × 2 scheme, the BER drops down to 10–5 for SNR of 20 dB. Results obtained in Table 1 show that when STBC is employed for MRC with 1 × 2 scheme (one antenna at transmitter node and two antennas at receiver node), BER curve comes down to 0.0076 for Eb/N0 of 12. Similarly, when MRC with 1 × 4 antenna scheme is implemented, BER drops down to 0 for Eb/N0 of 12. Thus, it can be concluded from the obtained graph that the performance of MRC with STBC gives improved results. When STBC technique is used with 3 × 4 scheme, at SNR of 10 dB, BER comes nearer to 10–6 (figure 7.3). It can be concluded from the analytics observed between AWGN and Rayleigh fading channel that for AWGN channel, BER is found to be equal to 0 for SNR value of 13.5 dB, whereas for Rayleigh fading channel, BER is observed nearer to 10–3 for Eb/N0 = 15. Simulation results (in figure 7.2) from the analytics show BER drops to 0 for SNR value of 12 dB.Research limitations/implicationsOptimal design and successful deployment of high-performance wireless networks present a number of technical challenges. These include regulatory limits on useable radio-frequency spectrum and a complex time-varying propagation environment affected by fading and multipath. The effect of multipath fading in wireless systems can be reduced by using antenna diversity. Previous studies show the performance of transmit diversity with narrowband signals using linear equalization, decision feedback equalization, maximum likelihood sequence estimation (MLSE) and spread spectrum signals using a RAKE receiver. The available IC techniques compatible with STBC schemes at transmission require multiple antennas at the receiver. However, if this not a strong constraint at the base station level, it remains a challenge at the handset level due to cost and size limitation. For this reason, SAIC technique, alternative to complex ML multiuser demodulation technique, is still of interest for 4G wireless networks using the MIMO technology and STBC in particular. In a system with characteristics similar to the North American Digital mobile radio standard IS-54 (24.3 K symbols per sec. with an 81 Hz fading rate), adaptive retransmission with time deviation is not practical.Practical implicationsThe evaluation of performance in terms of bit error rate and convergence time which estimates that MLD technique outperforms in terms of received SNR and low decoding complexity. MLD technique performs well but when higher number of antennas are used, it requires more computational time and thereby resulting in increased hardware complexity. When MRC scheme is implemented for singe input single output (SISO) system, BER drops down to 10–2 for SNR of 20 dB. Therefore, when MIMO systems are employed for MRC scheme, improved results based on BER versus SNR are obtained and are used for detecting the signal; comparative study based on different techniques is done. Initially ZF detection method is utilized which was then modified to ZF with successive interference cancellation (ZFSIC). When successive interference cancellation scheme is employed for ZFSIC, better performance is observed as compared to the estimation of ML and MMSE. For 2 × 2 scheme with QPSK modulation method, ZFSIC requires more computational time as compared to ZF, MMSE and ML technique. From the obtained results, the conclusion is that ZFSIC gives the improved results as compared to ZF in terms of BER ratio. ZF-based decision statistics can be produced by the detection algorithm for a desired sub-stream from the received vector whichs consist of an interference which occurred from previous transmitted sub-streams. Consequently, a decision on the secondary stream is made and contribution of the noise is regenerated and subtracted from the vector received. With no involvement of interference cancellation, system performance gets reduced but computational cost is saved. While using cancellation, as H is deflated, coefficients of MMSE are recalculated at each iteration. When cancellation is not involved, the computation of MMSE coefficients is done only once, because of H remaining unchanged. For MMSE 4 × 4 BPSK scheme, bit error rate of 10–2 at 30 dB is observed. In general, the most thorough procedure of the detection algorithm is the computation of the MMSE coefficients. Complexity arises in the calculation of the MMSE coefficients, when the antennas at the transmitting side are increased. However, while implementing adaptive MMSE receivers on slow channel fading, it is probable to recover the signal with the complications being linear in the antennas of transmitter node. The performance of MMSE and successive interference cancellation of MMSE are observed for 2 × 2 and 4 × 4 BPSK and QPSK modulation schemes. The drawback of MMSE SIC scheme is that the first detected signal observes the noise interference from (NT-1) signals, while signals processed from every antenna later observe less noisy interference as the process of cancellation progresses. This difficulty could be overcome by using OSIC detection method which uses successive ordering of the processed layers in the decreasing power of the signal or by power allocation to the signal transmitted depending on the order of the processing. By using successive scheme, a computation of NT delay stages is desired to bring out the abandoned process. The work also includes comparison of BER with various modulation schemes and number of antennas involved while evaluating the performance. MLD determines the Euclidean distance among the vector signal received and result of all probable transmitted vector signals with the specified channel H and finds the one with the minimum distance. Estimated results show that higher order of the diversity is observed by employing more antennas at both the receiving and transmitting ends. MLD with 8 × 8 binary phase shift keying (BPSK) scheme offers bit error rate near to 10–4 for SNR (16 dB). By using Altamonti space ti.Social implicationsIt should come as no surprise that companies everywhere are pushing to get products to market faster. Missing a market window or a design cycle can be a major setback in a competitive environment. It should be equally clear that this pressure is coming at the same time that companies are pushing towards “leaner” organizations that can do more with less. The trends mentioned earlier are not well supported by current test and measurement equipment, given this increasingly high-pressure design environment: in order to measure signals across multiple domains, multiple pieces of measurement equipment are needed, increasing capital or rental expenses. The methods available for making cross-domain, time-correlated measurements are inefficient, reducing engineering efficiency. When only used on occasion, the learning curve to understand how to use equipment for logic analysis, time domain and RF spectrum measurements often requires an operator to re-learn each piece of separate equipment. The equipment needed to measure wide bandwidth, time-varying spectral signals is expensive, again increasing capital or rental expenses. What is needed is a measurement instrument with a common user interface that integrates multiple measurement capabilities into a single cost-effective tool that can efficiently measure signals in the current wide-bandwidth, time-correlated, cross-domain environments. The market of wireless communication using STBCs has large scope of expansion in India. Therefore, the proposed work has techno-commercial potential and the product can be patented. This project shall in turn be helpful for remote areas of the nearby region particularly in Gadchiroli district and Melghat Tiger reserve project of Amravati district, Nagjira and so on where electricity is not available and there is an all the time problem of coverage in getting the network. In some regions where electricity is available, the shortage is such that they cannot use it for peak hours. In such cases, stand-alone space diversity technique, STBC shall help them to meet their requirements in making connection during coverage problem, thereby giving higher data transmission rates with better QOS (quality of service) with least dropped connections. This trend towards wireless everywhere is causing a profound change in the responsibilities of embedded designers as they struggle to incorporate unfamiliar RF technology into their designs. Embedded designers frequently find themselves needing to solve problems without the proper equipment needed to perform the tasks.Originality/valueWork is original.

In recent years, there has been a growing need to analyze the functional connectivity of the human brain. Previous studies have focused on extracting static or time-independent functional networks to describe the long-term behavior of brain activity. However, a static network is generally not sufficient to represent the long term communication patterns of the brain and is considered as an unreliable snapshot of functional connectivity. In this paper, we propose a dynamic network summarization approach to describe the time-varying evolution of connectivity patterns in functional brain activity. The proposed approach is based on first identifying key event intervals by quantifying the change in the connectivity patterns across time and then summarizing the activity in each event interval by extracting the most informative network using principal component decomposition. The proposed method is evaluated for characterizing time-varying network dynamics from event-related potential (ERP) data indexing the error-related negativity (ERN) component related to cognitive control. The statistically significant connectivity patterns for each interval are presented to illustrate the dynamic nature of functional connectivity.

In recent years, the deep learning-based fault diagnosis methods for rotating mechanical equipment have attracted great concern. However, because the data feature distributions present differences in applications with varying working conditions, the deep learning models cannot provide satisfactory performance of fault prediction in such scenarios. To address this problem, this paper proposes a domain adversarial-based rolling bearing fault transfer diagnosis model EMBRNDNMD. First of all, an EEMD-based time-frequency feature graph (EEMD-TFFG) construction method is proposed, and the time-frequency information of nonlinear nonstationary vibration signal is extracted; secondly, a multi-branch ResNet (MBRN) structure is designed, which is used to extract deep features representing the bearing state from EEMD-TFFG; finally, to solve the model domain adaptation transfer problem under varying working conditions, the adversarial network module and MK-MMD distribution difference evaluation method are introduced to optimize MBRN, so as to reduce the probability distribution difference between the deep features of source domain and target domain, and to improve the accuracy of EMBRNDNMD in state diagnosis of target domain. The results of experiments carried out on two bearing fault test platforms prove that EMBRNDNMD can maintain an average accuracy above 97% in fault transfer diagnosis tasks, and this method also has high stability and strong ability of scene adaptation.

This paper discusses the cooperative control for formation keeping of fractionated spacecraft, which is a new concept in recent years. For system of second-order differential equations of formation flying dynamics, knowledge of graph and consensus theory is introduced in study. By means of the idea of sliding mode control, we design a tracking control law for time-varying desired signal. Via exchanging error information among modules, the control law can make errors synchronized up to zero to achieve tracking. Relative velocity information between modules is not needed in this control law, which will efficiently reduce the requirements for relative navigation between modules. Then we prove the stability of the control system. Finally numerical simulation results show the effectiveness of the control law. By configuring the control parameters reasonably, we can achieve high degree of control accuracy.

Classifying mobile applications from encrypted network traffic is a common and basic requirement in network security and network management. Existing works classify mobile applications from flows, based on which application fingerprints and classifiers are created. However, mobile applications often generate concurrent flows with varying degrees of ties, such as low discriminative flows across applications and application-specific flows. So flow-based methods suffer from low accuracy. In this paper, a novel mobile application-classifying method is proposed, capturing relationships between flows and paying attention to their importance. To capture the inter-flow relationships, the proposed method slices raw mobile traffic into traffic chunks to represent flows as nodes, embeds statistical features into nodes, and adds edges according to cross-correlations between the nodes. To pay different attention to the various flows, the proposed method builds a deep learning model based on graph attention networks, implicitly assigning importance values to flows via graph attention layers. Compared to recently developed techniques on a large dataset with 101 popular apps using the Android platform, the proposed method improved by 4–20% for accuracy, precision, recall, and F1 score, and spent much less time training.

A target’s movements and radar cross sections are the key parameters to consider when designing a radar sensor for a given application. This paper shows the feasibility and effectiveness of using 24 GHz radar built-in low-noise microwave amplifiers for detecting an object. For this purpose a supervised machine learning model (SVM) is trained using the recorded data to classify the targets based on their cross sections into four categories. The trained classifiers were used to classify the objects with varying distances from the receiver. The SVM classification is also compared with three methods based on binary classification: a one-against-all classification, a one-against-one classification, and a directed acyclic graph SVM. The level of accuracy is approximately 96.6%, and an F1-score of 96.5% is achieved using the one-against-one SVM method with an RFB kernel. The proposed contactless radar in combination with an SVM algorithm can be used to detect and categorize a target in real time without a signal processing toolbox.

Steel sheet joining were dominantly by resistance spot welding (RSW) method. It is the most implemented in automotive mass production in which the heat is applied to the materials. Joining different material with different properties is a challenge. Thicker material needs more current and time. Meanwhile, the thinner material may burn and weaken if the excessive parameters apply. The purpose of this study is to identify the optimum spot weld parameters for joining dissimilar materials with different thickness that involve high tensile strength steel and low carbon steel in the automotive application. In this study, weld parameters with varying electrode forces, welding currents, and welding times are analyzed by applying a Taguchi robust method for the design of experiment (DOE). The L9 orthogonal array has been chosen due to the particular material specimen and time constraint. In the analysis, the higher value of signal-to-noise (S/N) ratio indicates the good responses of testing parameter when the level changed. Base of the plotted S/N ratio graph for each factor, Taguchi robust method has suggested that A3 (5000V), B3 (25 cycle), and C2 (150N) as the optimum weld parameters. The confirmation test afterward, finally proved that the Taguchi robust method was a liable DOE method and has been successfully optimized the spot weld parameters.

Human activity recognition has been gaining more and more attention from researchers in recent years, particularly with the use of widespread and commercially available devices such as smartphones. However, most of the existing works focus on discriminative classifiers while neglecting the inherent time-series and continuous characteristics of sensor data. To address this, we propose a two-stage continuous hidden Markov model framework, which also takes advantage of the innate hierarchical structure of basic activities. This kind of system architecture not only enables the use of different feature subsets on different subclasses, which effectively reduces feature computation overhead, but also allows for varying number of states and iterations. Experiments show that the hierarchical structure dramatically increases classification performance. We analyze the behavior of the accelerometer and gyroscope signals for each activity through graphs, and with added fine tuning of states and training iterations, the proposed method is able to achieve an overall accuracy of up to 93.18%, which is the best performance among the state-of-the-art classifiers for the problem at hand.

EXO70 is the pivotal protein subunit of exocyst, which has a very crucial role in enhancing the shielding effect of the cell wall, resisting abiotic and hormonal stresses. This experiment aims to identify family members of the EXO70 gene family in grape and predict the characteristics of this gene family, so as to lay the foundation of further exploring the mechanism of resisting abiotic and hormone stresses of VvEXO70s. Therefore, the Vitis vinifera ‘Red Globe’ tube plantlet were used as materials. Bioinformatics was used to inquire VvEXO70 genes family members, gene structure, system evolution, cis-acting elements, subcellular and chromosomal localization, collinearity, selective pressure, codon bias and tissue expression. All of VvEXO70s had the conserved pfam03081 domain which maybe necessary for interacting with other proteins. Microarray analysis suggested that most genes expressed to varying degrees in tendrils, leaves, seeds, buds, roots and stems. Quantitative Real-Time PCR (qRT-PCR) showed that the expression levels of all genes with 5 mM salicylic acid (SA), 0.1 mM methy jasmonate (MeJA), 20% PEG6000 and 4 °C for 24 h were higher than for 12 h. With 20% PEG6000 treatment about 24 h, the relative expression of VvEXO70-02 was significantly up-regulated and 361 times higher than CK. All genes’ relative expression was higher at 12 h than that at 24 h after treatment with 7 mM hydrogen peroxide (H2O2) and 0.1 mM ethylene (ETH). In conclusion, the expression levels of 14 VvEXO70 genes are distinguishing under these treatments, which play an important role in the regulation of anti-stress signals in grape. All of these test results provide a reference for the future research on the potential function analysis and plant breeding of VvEXO70 genes.

In viticulture, deficit irrigation strategies are often implemented to control vine canopy growth and to impose stress at critical stages of vine growth to improve wine grape quality. To support deficit irrigation scheduling, remote sensing technologies can be employed in the mapping of evapotranspiration (ET) at the field to sub-field scales, quantifying time-varying vineyard water requirements and actual water use. In the current study, we investigate the utility of ET maps derived from thermal infrared satellite imagery over a vineyard in the Central Valley of California equipped with a variable rate drip irrigation (VRDI) system which enables differential water applications at the 30 × 30 m scale. To support irrigation management at that scale, we utilized a thermal-based multi-sensor data fusion approach to generate weekly total actual ET (ETa) estimates at 30 m spatial resolution, coinciding with the resolution of the Landsat reflectance bands. Crop water requirements (ETc) were defined with a vegetative index (VI)-based approach. To test capacity to capture stress signals, the vineyard was sub-divided into four blocks with different irrigation management strategies and goals, inducing varying degrees of stress during the growing season. Results indicate derived weekly total ET from the thermal-based data fusion approach match well with observations. The thermal-based method was also able to capture the spatial heterogeneity in ET over the vineyard due to a water stress event imposed on two of the four vineyard blocks. This transient stress event was not reflected in the VI-based ETc estimate, highlighting the value of thermal band imaging. While the data fusion system provided valuable information, latency in current satellite data availability, particularly from Landsat, impacts operational applications over the course of a growing season.

Abstract Abstract 2251 Thromboelastography (TEG) was used in ∼200 studies published in 2009, is mainly used for global blood coagulation assessment, and is thrombin and fibrinogen concentration-dependent. Reflecting the time course of fibrin polymerization, TEG measures lag time, rate, and maximum amplitude (MA) of clot stiffness, and is substantially enhanced by platelets. To identify more specific fibrin(ogen) determinants potentially relevant to interpretation we investigated MA under different TEG conditions. The procedure utilizes a polymethylmethacrylate (hydrophobic surface) cup and pin set, the cup oscillating through 4° 45' (6 cycles/minute). The pin (sensor) is suspended via a torsion wire, and transmits a tuning fork-like signal, displayed as a graph, as the clot links pin and cup. Clots cross-linked (by factor XIIIa) were shown insoluble in 6 M urea, and were obtained by adding thrombin to fibrinogen solutions, pH 7.4, containing 8 mM CaCl2 and either 50 nM factor XIII or 30% afibrinogenemic plasma with or without gel-sieved platelets (190,000/μl). Except where otherwise stated, 6 μM fibrinogen was employed. In three sets of experiments without platelets, increasing thrombin (0.001 to 2 U /ml) progressively increased MA. For example, levels of 0.005, 0.1, 0.3, and 0.5 U/ml the yielded respective MAs of 16.7, 49, 62.8, and 65.3 mm. TEG enhancement by platelets reflects mainly their binding of the fibrin(ogen) C-terminal γ dodecapeptide and ensuing clot retraction. Several sets of experiments at different fibrinogen concentrations disclosed that the lower the concentration the more pronounced the platelet enhancement. For example, at of 0.3, 1, 3, and 6 μM fibrinogen (thrombin 0.4 U/ml), the respective control MAs were 0, 2.9, 15.9, 30.4, and 44.9 mm. The presence of platelets increased these to 10.6, 30.4, 44.9, and 64.8 mm, respectively. To test the role of the fibrin(ogen) αC region, two coagulable fibrinogen isolates (termed des-αC) lacking major C-terminal segments of varying length from their αC were prepared as described (Mosesson et al, J Biol Chem 249:4656). They displayed <5% intact Aα chains by gel scanning densitometry (sodium dodecyl sulfate-polyacrylamide electrophoresis of reduced protein bands). Estimated from the size of their Aα core remnants, most des-αC molecules lack the αC domain (Aα392–610) part of αC. Their clots yielded MA <2% that of fibrin with intact αC, n=5. In the presence of platelets, however, the MA was only moderately decreased (e.g. 53% ± 11%, SD, n=4) of controls. Fibrinogen adsorption to hydrophobic surfaces is known to be characteristically tight and to displace other plasma proteins, requires its D region, reaches near maximum of 2–3 molecule thick coating, ∼600 ng/cm2 within 2 minutes, and enhances its coagulability (Koo et al, J Thromb Haemost, 8: 2727–35). Cup and pin (CP) were exposed to intact fibrinogen (100 μg/ml, 2 hours), and washed. In a duplicate experiment, addition and clotting of des-αC fibrinogen again yielded MA <2% of control. Coating with des-αC fibrinogen did not alter the MA of intact fibrin clots. Monoclonal IgG antibodies, anti-Aα518–584 (mAb1), and anti-Aα241–476 (mAb2), of which both moderately decrease clot turbidity but do not impair coagulability, were tested (3 mols/mol fibrin with intact αC, non-coated CP) in the presence of platelets. In two separate sets of experiments, mAb1 decreased MA to 11.6% and 9% and mAb2 to 0.6% and 1.7% of respective non-immune IgG controls. In two other separate experiments, coating of CP with incoagulable intact fibrinogen (Frankfurt XIII, homodimeric AαR16C), followed by addition and clotting normal intact fibrinogen yielded MAs of 31% and 38% of respective normal controls. To evaluate hydrophobic surface effects, the water contact angle was decreased from 68° to 13° by CP exposure to UV ozone plasma (5 minutes, n=2). MA of clots formed in treated CP was 41% and 36% of untreated controls. We conclude that fibrin(ogen) adsorption to the hydrophobic CP surface, coagulability of adsorbed fibrinogen, and the αC domain of adsorbed and non-adsorbed fibrin(ogen) are significant TEG determinants. The results also suggest a significant or auxiliary role by the αC domain in the platelet enhancement of TEG. The pronounced stiffness of clots formed on hydrophobic, relative to hydrophilic, surface is of possible relevance in atherothrombotic lesions and in medical implants with hydrophobic surface. Disclosures: No relevant conflicts of interest to declare.

In this paper we present Active Inference-Based Design Agent (AIDA), which is an active inference-based agent that iteratively designs a personalized audio processing algorithm through situated interactions with a human client. The target application of AIDA is to propose on-the-spot the most interesting alternative values for the tuning parameters of a hearing aid (HA) algorithm, whenever a HA client is not satisfied with their HA performance. AIDA interprets searching for the “most interesting alternative” as an issue of optimal (acoustic) context-aware Bayesian trial design. In computational terms, AIDA is realized as an active inference-based agent with an Expected Free Energy criterion for trial design. This type of architecture is inspired by neuro-economic models on efficient (Bayesian) trial design in brains and implies that AIDA comprises generative probabilistic models for acoustic signals and user responses. We propose a novel generative model for acoustic signals as a sum of time-varying auto-regressive filters and a user response model based on a Gaussian Process Classifier. The full AIDA agent has been implemented in a factor graph for the generative model and all tasks (parameter learning, acoustic context classification, trial design, etc.) are realized by variational message passing on the factor graph. All verification and validation experiments and demonstrations are freely accessible at our GitHub repository.

The goal of this work is to detect the onset of material cross-contamination in laser powder bed fusion (L-PBF) additive manufacturing (AM) process using data from in situ sensors. Material cross-contamination refers to trace foreign materials that may be introduced in the powder feedstock used in the process due to reasons such as poor cleaning of the machine after previous builds or inadequate quality control during production and storage of the powder. Material cross-contamination may lead to deleterious changes in the microstructure of the AM part and consequently affect its functional properties. Accordingly, the objective of this work is to develop and apply a spectral graph theoretic approach to detect the occurrence of material cross-contamination in real-time as the part is being built using in-process sensors. The central hypothesis is that transforming the process signals in the spectral graph domain leads to early and more accurate detection of material cross-contamination in L-PBF compared to the traditional delay-embedded Bon-Jenkins stochastic time series analysis techniques, such as autoregressive (AR) and autoregressive moving average (ARMA) modeling. To test this hypothesis, Inconel alloy 625 (UNS alloy 06625) test parts were made at Edison Welding Institute (EWI) on a custom-built L-PBF apparatus integrated with multiple sensors, including a silicon photodetector (with 300 nm to 1100 nm optical wavelength). During the process, two types of foreign contaminant materials, namely, tungsten and aluminum particulates, under varying degrees of severity were introduced. To detect cross-contamination in the part, the photodetector sensor signatures were monitored hatch-by-hatch in the form of spectral graph transform coefficients. These spectral graph coefficients are subsequently tracked on a Hotelling T2 statistical control chart. Instances of Type II statistical error, i.e., probability of failing to detect the onset of material cross-contamination, were verified against X-ray computed tomography (XCT) scans of the part to be within 5% in the case of aluminum contaminant particles. In contrast, traditional stochastic time series modeling approaches, e.g., ARMA, had corresponding Type II error exceeding 15%. Furthermore, the computation time for the spectral graph approach was found to be less than one millisecond, compared to nearly 100 ms for the traditional time series models tested.

Network neuroscience is a thriving and rapidly expanding field. Empirical data on brain networks, from molecular to behavioral scales, are ever increasing in size and complexity. These developments lead to a strong demand for appropriate tools and methods that model and analyze brain network data, such as those provided by graph theory. This brief review surveys some of the most commonly used and neurobiologically insightful graph measures and techniques. Among these, the detection of network communities or modules, and the identification of central network elements that facilitate communication and signal transfer, are particularly salient. A number of emerging trends are the growing use of generative models, dynamic (time-varying) and multilayer networks, as well as the application of algebraic topology. Overall, graph theory methods are centrally important to understanding the architecture, development, and evolution of brain networks.

This paper describes a method for approaching an arbitrary parameter with initial outline, slider and simulation model, systematical and quantitative bond graph model of vehicle dynamic system. It illustrates a typical bond graph and object models using the three basic modules of the software. For brevity, only small problems are considered for simulation of vehicle dynamic system model. Bond graph techniques reveal its strength and beauty in developing a clear and simplified model for vehicle dynamic system. Fast Fourier Transform (FFT) generates discrete Fourier transform of a time-varying signal and stores it into a disk file containing discredited numerical values for all the system states, ranging over the entire simulation interval. In this paper, a vehicle dynamic Modeling and Simulation involving three partners viz., Vehicle model, Vehicle parameter and Vehicle simulator, are taken into consideration. This process consists of both modeling and simulating closely associated with each other. Vehicle dynamics is the science that studies the kinematics of wheeled land vehicles with its dimensions and benefits to mechanisms, suspensions and steering mechanisms. The dynamics of computer models of vehicles using Bond graph technique originated by H. M. Paynter, presents a tool for continuous system modeling in a graphical sense, by generalizing the physical phenomenon such as: Mechanical Dynamic System. The role of computerized modeling and simulation in engineering design continues to increase as companies are striving to gain competitive advantages by reducing the time required to move from concept to final product.

This paper investigates the containment control problem for multiple Euler–Lagrange systems with unknown time-varying disturbances over directed graphs, in which the dynamics of leaders and followers are heterogeneous. First of all, the expected output signals of leaders can only be acquired by some subsystems owing to the limited communication conditions, and the output adjustment errors are obtained indirectly by other subsystems through the network connection. In consequence, a compensator based on relative output information is designed to estimate a trajectory inside the convex hull spanned by states of the leaders. Second, a fully distributed event-triggered adaptive control scheme is proposed, and a disturbance estimator is designed to achieve interference suppression. In addition, the design of the overall control protocol does not use the relative speed of the followers. Finally, a dual-axis manipulator is taken as an example to validate the effectiveness of the proposed control scheme.

High resolution mobility datasets have become increasingly available in the past few years and have enabled detailed models for infectious disease spread including those for COVID-19. However, there are open questions on how such a mobility data can be used effectively within epidemic models and for which tasks they are best suited. In this paper, we extract a number of graph-based proximity metrics from high resolution cellphone trace data from X-Mode and use it to study COVID-19 epidemic spread in 50 land grant university counties in the US. We present an approach to estimate the effect of mobility on cases by fitting an ordinary differential equation based model and performing multivariate linear regression to explain the estimated time varying transmissibility. We find that, while mobility plays a significant role, the contribution is heterogeneous across the counties, as exemplified by a subsequent correlation analysis. We also evaluate the metrics’ utility for case surge prediction defined as a supervised classification problem, and show that the learnt model can predict surges with 95% accuracy and 87% F1-score.

AbstractRecent studies suggested that cerebrovascular micro-occlusions, i.e. microstokes, could lead to ischemic tissue infarctions and cognitive deficits. Due to their small size, identifying measurable biomarkers of these microvascular lesions remains a major challenge. This work aims to simulate potential MRI signatures combining arterial spin labeling (ASL) and multi-directional diffusion-weighted imaging (DWI). Driving our hypothesis are recent observations demonstrating a radial reorientation of microvasculature around the micro-infarction locus during recovery in mice. Synthetic capillary beds, randomly- and radially-oriented, and optical coherence tomography (OCT) angiograms, acquired in the barrel cortex of mice (n = 5) before and after inducing targeted photothrombosis, were analyzed. Computational vascular graphs combined with a 3D Monte-Carlo simulator were used to characterize the magnetic resonance (MR) response, encompassing the effects of magnetic field perturbations caused by deoxyhemoglobin, and the advection and diffusion of the nuclear spins. We quantified the minimal intravoxel signal loss ratio when applying multiple gradient directions, at varying sequence parameters with and without ASL. With ASL, our results demonstrate a significant difference (p < 0.05) between the signal-ratios computed at baseline and 3 weeks after photothrombosis. The statistical power further increased (p < 0.005) using angiograms measured at week 4. Without ASL, no reliable signal change was found. We found that higher ratios, and accordingly improved significance, were achieved at lower magnetic field strengths (e.g., B0 = 3T) and shorter echo time TE (< 16 ms). Our simulations suggest that microstrokes might be characterized through ASL-DWI sequence, providing necessary insights for posterior experimental validations, and ultimately, future translational trials.

Objective: To rebuild the software that underpins the Global Public Health Intelligence Network using modern natural language processing techniques to support recent and future improvements in situational awareness capability.Introduction: The Global Public Health Intelligence Network is a non-traditional all-hazards multilingual surveillance system introduced in 1997 by the Government of Canada in collaboration with the World Health Organization.1 GPHIN software collects news articles, media releases, and incident reports and analyzes them for information about communicable diseases, natural disasters, product recalls, radiological events and other public health crises. Since 2016, the Public Health Agency of Canada (PHAC) and National Research Council Canada (NRC) have collaborated to replace GPHIN with a modular platform that incorporates modern natural language processing techniques to support more ambitious situational awareness goals.Methods: The updated GPHIN platform assembles several natural language processing tools to annotate incoming data in order to support situational awareness; broadly, GPHIN aims to extract knowledge from data.Data are collected in 10 languages and are machine translated to English. Several of the machine translation models use high performance neural networks. Language models are updated regularly and support external dictionaries for handling emerging domain-specific terms that might not yet exist in the parallel corpora used to train the models.All incoming documents are assigned a relevance score. Machine learning models estimate a score based on similarity to sets of known high-relevance and known low-relevance documents. PHAC analysts provide feedback on the scoring from time to time in the course of their work, and this feedback is used to periodically retrain scoring models.Documents are assigned keywords using two ontologies: an all-hazards multilingual taxonomy hand-compiled at PHAC, and the U.S. National Library of Medicine’s Unified Medical Language System (UMLS).Categories are assigned probabilistically to incoming articles (e.g., human infectious diseases, animal infectious diseases, substance abuse, environmental hazards), largely using affinity scores that correspond to keywords.Dates and times are resolved to canonical forms, so that mentions like last Tuesday get resolved to specific dates; this makes it possible to sequence data about a single event that are released at varying frequencies and with varying timeliness.Cities, states/provinces, and countries are identified in the documents, and gaps in the hierarchical geographic relationships are filled in. Locations are disambiguated based on collocations; the system distinguishes between and correctly resolves Ottawa, KS vs. Ottawa, ON, Canada, for example. Countries are displayed with their socio-economic population statistics (Gini coefficient, human development index, median age, and so on).The system attempts to detect and reconcile near-duplicate articles in order to handle instances where one article is released on a newswire and subsequently gets lightly edited and syndicated in dozens or hundreds of local papers; this improves the signal-to-noise ratio of the data in GPHIN for better productivity. Template-based reports (where the same document may get re-issued with a new number of cases but no other changes, for example) are still a challenge, but whitelisting tools reduce the false positive rate.The system provides tools for constructing arbitrarily detailed searches, tied to colour-coded maps and graphs that update on-the-fly, and offers short extractive summaries of each search result for easy filtering. GPHIN also generates topical knowledge graphs about sets of articles that seek to reveal surprising correlations in the data; for example, graphically reconciling and highlighting cases where several neighbouring countries all have reports of a mysterious disease and where a particular mosquito is mentioned.Next steps in the ongoing rejuvenation involve collating discrete articles and documents into narrative timelines that track an ongoing event: collecting all data about the spread of an infectious disease outbreak or perhaps the aftermath of an earthquake in the developing world. Our research is focussing on how to build line lists from such a stream of news articles about an event and how to detect important change points in the ongoing narrative.Results: The new GPHIN platform was launched in August 2016 in order to support syndromic surveillance activities for the Rio 2016 Olympics, and has been updated incrementally since then to offer further capabilities to professional users in 30 countries. Its modular construction supports current situational awareness activities as well as further research into advanced natural language processing techniques.Conclusions: We improved (and continue to improve) GPHIN with modern natural language processing techniques, including better translations, relevance scoring, categorization, near-duplicate detection, and improved data visualization tools, all towards the goal of more productive and more trustworthy situational awareness.

Background “The sense of taste,” write Nelson and colleagues in a 2002 issue of Nature, “provides animals with valuable information about the nature and quality of food. Mammals can recognize and respond to a diverse repertoire of chemical entities, including sugars, salts, acids and a wide range of toxic substances” (199). The authors go on to argue that several amino acids—the building blocks of proteins—taste delicious to humans and that “having a taste pathway dedicated to their detection probably had significant evolutionary implications”. They imply, but do not specify, that the evolutionary implications are positive. This may be the case with some amino acids, but contemporary tastes, and changes in them, are far from universally beneficial. Indeed, this article argues that modern food production shapes and distorts human taste with significant implications for health and wellbeing. Take the western taste for fried chipped potatoes, for example. According to Schlosser in Fast Food Nation, “In 1960, the typical American ate eighty-one pounds of fresh potatoes and about four pounds of frozen french fries. Today [2002] the typical American eats about forty-nine pounds of fresh potatoes every year—and more than thirty pounds of frozen french fries” (115). Nine-tenths of these chips are consumed in fast food restaurants which use mass-manufactured potato-based frozen products to provide this major “foodservice item” more quickly and cheaply than the equivalent dish prepared from raw ingredients. These choices, informed by human taste buds, have negative evolutionary implications, as does the apparently long-lasting consumer preference for fried goods cooked in trans-fats. “Numerous foods acquire their elastic properties (i.e., snap, mouth-feel, and hardness) from the colloidal fat crystal network comprised primarily of trans- and saturated fats. These hardstock fats contribute, along with numerous other factors, to the global epidemics related to metabolic syndrome and cardiovascular disease,” argues Michael A. Rogers (747). Policy makers and public health organisations continue to compare notes internationally about the best ways in which to persuade manufacturers and fast food purveyors to reduce the use of these trans-fats in their products (L’Abbé et al.), however, most manufacturers resist. Hank Cardello, a former fast food executive, argues that “many products are designed for ‘high hedonic value’, with carefully balanced combinations of salt, sugar and fat that, experience has shown, induce people to eat more” (quoted, Trivedi 41). Fortunately for the manufactured food industry, salt and sugar also help to preserve food, effectively prolonging the shelf life of pre-prepared and packaged goods. Physiological Factors As Glanz et al. discovered when surveying 2,967 adult Americans, “taste is the most important influence on their food choices, followed by cost” (1118). A person’s taste is to some extent an individual response to food stimuli, but the tongue’s taste buds respond to five basic categories of food: salty, sweet, sour, bitter, and umami. ‘Umami’ is a Japanese word indicating “delicious savoury taste” (Coughlan 11) and it is triggered by the amino acid glutamate. Japanese professor Kikunae Ikeda identified glutamate while investigating the taste of a particular seaweed which he believed was neither sweet, sour, bitter, or salty. When Ikeda combined the glutamate taste essence with sodium he formed the food additive sodium glutamate, which was patented in 1908 and subsequently went into commercial production (Japan Patent Office). Although individual, a person’s taste preferences are by no means fixed. There is ample evidence that people’s tastes are being distorted by modern food marketing practices that process foods to make them increasingly appealing to the average palate. In particular, this industrialisation of food promotes the growth of a snack market driven by salty and sugary foods, popularly constructed as posing a threat to health and wellbeing. “[E]xpanding waistlines [are] fuelled by a boom in fast food and a decline in physical activity” writes Stark, who reports upon the 2008 launch of a study into Australia’s future ‘fat bomb’. As Deborah Lupton notes, such reports were a particular feature of the mid 2000s when: intense concern about the ‘obesity epidemic’ intensified and peaked. Time magazine named 2004 ‘The Year of Obesity’. That year the World Health Organization’s Global Strategy on Diet, Physical Activity and Health was released and the [US] Centers for Disease Control predicted that a poor diet and lack of exercise would soon claim more lives than tobacco-related disease in the United States. (4) The American Heart Association recommends eating no more than 1500mg of salt per day (Hamzelou 11) but salt consumption in the USA averages more than twice this quantity, at 3500mg per day (Bernstein and Willett 1178). In the UK, a sustained campaign and public health-driven engagement with food manufacturers by CASH—Consensus Action on Salt and Health—resulted in a reduction of between 30 and 40 percent of added salt in processed foods between 2001 and 2011, with a knock-on 15 percent decline in the UK population’s salt intake overall. This is the largest reduction achieved by any developed nation (Brinsden et al.). “According to the [UK’s] National Institute for Health and Care Excellence (NICE), this will have reduced [UK] stroke and heart attack deaths by a minimum of 9,000 per year, with a saving in health care costs of at least £1.5bn a year” (MacGregor and Pombo). Whereas there has been some success over the past decade in reducing the amount of salt consumed, in the Western world the consumption of sugar continues to rise, as a graph cited in the New Scientist indicates (O’Callaghan). Regular warnings that sugar is associated with a range of health threats and delivers empty calories devoid of nutrition have failed to halt the increase in sugar consumption. Further, although some sugar is a natural product, processed foods tend to use a form invented in 1957: high-fructose corn syrup (HFCS). “HFCS is a gloopy solution of glucose and fructose” writes O’Callaghan, adding that it is “as sweet as table sugar but has typically been about 30% cheaper”. She cites Serge Ahmed, a French neuroscientist, as arguing that in a world of food sufficiency people do not need to consume more, so they need to be enticed to overeat by making food more pleasurable. Ahmed was part of a team that ran an experiment with cocaine-addicted rats, offering them a mutually exclusive choice between highly-sweetened water and cocaine: Our findings clearly indicate that intense sweetness can surpass cocaine reward, even in drug-sensitized and -addicted individuals. We speculate that the addictive potential of intense sweetness results from an inborn hypersensitivity to sweet tastants. In most mammals, including rats and humans, sweet receptors evolved in ancestral environments poor in sugars and are thus not adapted to high concentrations of sweet tastants. The supranormal stimulation of these receptors by sugar-rich diets, such as those now widely available in modern societies, would generate a supranormal reward signal in the brain, with the potential to override self-control mechanisms and thus lead to addiction. (Lenoir et al.) The Tongue and the Brain One of the implications of this research about the mammalian desire for sugar is that our taste for food is about more than how these foods actually taste in the mouth on our tongues. It is also about the neural response to the food we eat. The taste of French fries thus also includes that “snap, mouth-feel, and hardness” and the “colloidal fat crystal network” (Rogers, “Novel Structuring” 747). While there is no taste receptor for fats, these nutrients have important effects upon the brain. Wang et al. offered rats a highly fatty, but palatable, diet and allowed them to eat freely. 33 percent of the calories in the food were delivered via fat, compared with 21 percent in a normal diet. The animals almost doubled their usual calorific intake, both because the food had a 37 percent increased calorific content and also because the rats ate 47 percent more than was standard (2786). The research team discovered that in as little as three days the rats “had already lost almost all of their ability to respond to leptin” (Martindale 27). Leptin is a hormone that acts on the brain to communicate feelings of fullness, and is thus important in assisting animals to maintain a healthy body weight. The rats had also become insulin resistant. “Severe resistance to the metabolic effects of both leptin and insulin ensued after just 3 days of overfeeding” (Wang et al. 2786). Fast food restaurants typically offer highly palatable, high fat, high sugar, high salt, calorific foods which can deliver 130 percent of a day’s recommended fat intake, and almost a day’s worth of an adult man’s calories, in one meal. The impacts of maintaining such a diet over a comparatively short time-frame have been recorded in documentaries such as Super Size Me (Spurlock). The after effects of what we widely call “junk food” are also evident in rat studies. Neuroscientist Paul Kenny, who like Ahmed was investigating possible similarities between food- and cocaine-addicted rats, allowed his animals unlimited access to both rat ‘junk food’ and healthy food for rats. He then changed their diets. “The rats with unlimited access to junk food essentially went on a hunger strike. ‘It was as if they had become averse to healthy food’, says Kenny. It took two weeks before the animals began eating as much [healthy food] as those in the control group” (quoted, Trivedi 40). Developing a taste for certain food is consequently about much more than how they taste in the mouth; it constitutes an individual’s response to a mixture of taste, hormonal reactions and physiological changes. Choosing Health Glanz et al. conclude their study by commenting that “campaigns attempting to change people’s perception of the importance of nutrition will be interpreted in terms of existing values and beliefs. A more promising strategy might be to stress the good taste of healthful foods” (1126). Interestingly, this is the strategy already adopted by some health-focused cookbooks. I have 66 cookery books in my kitchen. None of ten books sampled from the five spaces in which these books are kept had ‘taste’ as an index entry, but three books had ‘taste’ in their titles: The Higher Taste, Taste of Life, and The Taste of Health. All three books seek to promote healthy eating, and they all date from the mid-1980s. It might be that taste is not mentioned in cookbook indexes because it is a sine qua non: a focus upon taste is so necessary and fundamental to a cookbook that it goes without saying. Yet, as the physiological evidence makes clear, what we find palatable is highly mutable, varying between people, and capable of changing significantly in comparatively short periods of time. The good news from the research studies is that the changes wrought by high salt, high sugar, high fat diets need not be permanent. Luciano Rossetti, one of the authors on Wang et al’s paper, told Martindale that the physiological changes are reversible, but added a note of caution: “the fatter a person becomes the more resistant they will be to the effects of leptin and the harder it is to reverse those effects” (27). Morgan Spurlock’s experience also indicates this. In his case it took the actor/director 14 months to lose the 11.1 kg (13 percent of his body mass) that he gained in the 30 days of his fast-food-only experiment. Trivedi was more fortunate, stating that, “After two weeks of going cold turkey, I can report I have successfully kicked my ice cream habit” (41). A reader’s letter in response to Trivedi’s article echoes this observation. She writes that “the best way to stop the craving was to switch to a diet of vegetables, seeds, nuts and fruits with a small amount of fish”, adding that “cravings stopped in just a week or two, and the diet was so effective that I no longer crave junk food even when it is in front of me” (Mackeown). Popular culture indicates a range of alternative ways to resist food manufacturers. In the West, there is a growing emphasis on organic farming methods and produce (Guthman), on sl called Urban Agriculture in the inner cities (Mason and Knowd), on farmers’ markets, where consumers can meet the producers of the food they eat (Guthrie et al.), and on the work of advocates of ‘real’ food, such as Jamie Oliver (Warrin). Food and wine festivals promote gourmet tourism along with an emphasis upon the quality of the food consumed, and consumption as a peak experience (Hall and Sharples), while environmental perspectives prompt awareness of ‘food miles’ (Weber and Matthews), fair trade (Getz and Shreck) and of land degradation, animal suffering, and the inequitable use of resources in the creation of the everyday Western diet (Dare, Costello and Green). The burgeoning of these different approaches has helped to stimulate a commensurate growth in relevant disciplinary fields such as Food Studies (Wessell and Brien). One thing that all these new ways of looking at food and taste have in common is that they are options for people who feel they have the right to choose what and when to eat; and to consume the tastes they prefer. This is not true of all groups of people in all countries. Hiding behind the public health campaigns that encourage people to exercise and eat fresh fruit and vegetables are the hidden “social determinants of health: The conditions in which people are born, grow, live, work and age, including the health system” (WHO 45). As the definitions explain, it is the “social determinants of health [that] are mostly responsible for health iniquities” with evidence from all countries around the world demonstrating that “in general, the lower an individual’s socioeconomic position, the worse his or her health” (WHO 45). For the comparatively disadvantaged, it may not be the taste of fast food that attracts them but the combination of price and convenience. If there is no ready access to cooking facilities, or safe food storage, or if a caregiver is simply too time-poor to plan and prepare meals for a family, junk food becomes a sensible choice and its palatability an added bonus. For those with the education, desire, and opportunity to break free of the taste for salty and sugary fats, however, there are a range of strategies to achieve this. There is a persuasive array of evidence that embracing a plant-based diet confers a multitude of health benefits for the individual, for the planet and for the animals whose lives and welfare would otherwise be sacrificed to feed us (Green, Costello and Dare). Such a choice does involve losing the taste for foods which make up the lion’s share of the Western diet, but any sense of deprivation only lasts for a short time. The fact is that our sense of taste responds to the stimuli offered. It may be that, notwithstanding the desires of Jamie Oliver and the like, a particular child never will never get to like broccoli, but it is also the case that broccoli tastes differently to me, seven years after becoming a vegan, than it ever did in the years in which I was omnivorous. When people tell me that they would love to adopt a plant-based diet but could not possibly give up cheese, it is difficult to reassure them that the pleasure they get now from that specific cocktail of salty fats will be more than compensated for by the sheer exhilaration of eating crisp, fresh fruits and vegetables in the future. Conclusion For decades, the mass market food industry has tweaked their products to make them hyper-palatable and difficult to resist. They do this through marketing experiments and consumer behaviour research, schooling taste buds and brains to anticipate and relish specific cocktails of sweet fats (cakes, biscuits, chocolate, ice cream) and salty fats (chips, hamburgers, cheese, salted nuts). They add ingredients to make these products stimulate taste buds more effectively, while also producing cheaper items with longer life on the shelves, reducing spoilage and the complexity of storage for retailers. Consumers are trained to like the tastes of these foods. Bitter, sour, and umami receptors are comparatively under-stimulated, with sweet, salty, and fat-based tastes favoured in their place. Western societies pay the price for this learned preference in high blood pressure, high cholesterol, diabetes, and obesity. Public health advocate Bruce Neal and colleagues, working to reduce added salt in processed foods, note that the food and manufacturing industries can now provide most of the calories that the world needs to survive. “The challenge now”, they argue, “is to have these same industries provide foods that support long and healthy adult lives. And in this regard there remains a very considerable way to go”. If the public were to believe that their sense of taste is mutable and has been distorted for corporate and industrial gain, and if they were to demand greater access to natural foods in their unprocessed state, then that journey towards a healthier future might be far less protracted than these and many other researchers seem to believe. References Bernstein, Adam, and Walter Willett. “Trends in 24-Hr Sodium Excretion in the United States, 1957–2003: A Systematic Review.” American Journal of Clinical Nutrition 92 (2010): 1172–1180. Bhaktivedanta Book Trust. The Higher Taste: A Guide to Gourmet Vegetarian Cooking and a Karma-Free Diet, over 60 Famous Hare Krishna Recipes. Botany, NSW: Bhaktivedanta Book Trust, 1987. Brinsden, Hannah C., Feng J. He, Katharine H. Jenner, & Graham A. MacGregor. “Surveys of the Salt Content in UK Bread: Progress Made and Further Reductions Possible.” British Medical Journal Open 3.6 (2013). 2 Feb. 2014 ‹http://bmjopen.bmj.com/content/3/6/e002936.full›. Coughlan, Andy. “In Good Taste.” New Scientist 2223 (2000): 11. Dare, Julie, Leesa Costello, and Lelia Green. “Nutritional Narratives: Examining Perspectives on Plant Based Diets in the Context of Dominant Western Discourse”. Proceedings of the 2013 Australian and New Zealand Communication Association Conference. Ed. In Terence Lee, Kathryn Trees, and Renae Desai. Fremantle, Western Australia, 3-5 Jul. 2013. 2 Feb. 2014 ‹http://www.anzca.net/conferences/past-conferences/159.html›. Getz, Christy, and Aimee Shreck. “What Organic and Fair Trade Labels Do Not Tell Us: Towards a Place‐Based Understanding of Certification.” International Journal of Consumer Studies 30.5 (2006): 490–501. Glanz, Karen, Michael Basil, Edward Maibach, Jeanne Goldberg, & Dan Snyder. “Why Americans Eat What They Do: Taste, Nutrition, Cost, Convenience, and Weight Control Concerns as Influences on Food Consumption.” Journal of the American Dietetic Association 98.10 (1988): 1118–1126. Green, Lelia, Leesa Costello, and Julie Dare. “Veganism, Health Expectancy, and the Communication of Sustainability.” Australian Journal of Communication 37.3 (2010): 87–102 Guthman, Julie. Agrarian Dreams: the Paradox of Organic Farming in California. Berkley and Los Angeles, CA: U of California P, 2004 Guthrie, John, Anna Guthrie, Rob Lawson, & Alan Cameron. “Farmers’ Markets: The Small Business Counter-Revolution in Food Production and Retailing.” British Food Journal 108.7 (2006): 560–573. Hall, Colin Michael, and Liz Sharples. Eds. Food and Wine Festivals and Events Around the World: Development, Management and Markets. Oxford, UK: Routledge, 2008. Hamzelou, Jessica. “Taste Bud Trickery Needed to Cut Salt Intake.” New Scientist 2799 (2011): 11. Japan Patent Office. History of Industrial Property Rights, Ten Japanese Great Inventors: Kikunae Ikeda: Sodium Glutamate. Tokyo: Japan Patent Office, 2002. L’Abbé, Mary R., S. Stender, C. M. Skeaff, Ghafoorunissa, & M. Tavella. “Approaches to Removing Trans Fats from the Food Supply in Industrialized and Developing Countries.” European Journal of Clinical Nutrition 63 (2009): S50–S67. Lenoir, Magalie, Fuschia Serre, Lauriane Cantin, & Serge H. Ahmed. “Intense Sweetness Surpasses Cocaine Reward.” PLOS One (2007). 2 Feb. 2014 ‹http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0000698›. Lupton, Deborah. Fat. Oxford, UK: Routledge, 2013. MacGregor, Graham, and Sonia Pombo. “The Amount of Hidden Sugar in Your Diet Might Shock You.” The Conversation 9 January (2014). 2 Feb. 2014 ‹http://theconversation.com/the-amount-of-hidden-sugar-in-your-diet-might-shock-you-21867›. Mackeown, Elizabeth. “Cold Turkey?” [Letter]. New Scientist 2787 (2010): 31. Martindale, Diane. “Burgers on the Brain.” New Scientist 2380 (2003): 26–29. Mason, David, and Ian Knowd. “The Emergence of Urban Agriculture: Sydney, Australia.” The International Journal of Agricultural Sustainability 8.1–2 (2010): 62–71. Neal, Bruce, Jacqui Webster, and Sebastien Czernichow. “Sanguine About Salt Reduction.” European Journal of Preventative Cardiology 19.6 (2011): 1324–1325. Nelson, Greg, Jayaram Chandrashekar, Mark A. Hoon, Luxin Feng, Grace Zhao, Nicholas J. P. Ryba, & Charles S. Zuker. “An Amino-Acid Taste Receptor.” Nature 416 (2002): 199–202. O’Callaghan, Tiffany. “Sugar on Trial: What You Really Need to Know.” New Scientist 2954 (2011): 34–39. Rogers, Jenny. Ed. The Taste of Health: The BBC Guide to Healthy Cooking. London, UK: British Broadcasting Corporation, 1985. Rogers, Michael A. “Novel Structuring Strategies for Unsaturated Fats—Meeting the Zero-Trans, Zero-Saturated Fat Challenge: A Review.” Food Research International 42.7 August (2009): 747–753. Schlosser, Eric. Fast Food Nation. London, UK: Penguin, 2002. Super Size Me. Dir. Morgan Spurlock. Samuel Goldwyn Films, 2004. Stafford, Julie. Taste of Life. Richmond, Vic: Greenhouse Publications Ltd, 1983. Stark, Jill. “Australia Now World’s Fattest Nation.” The Age 20 June (2008). 2 Feb. 2014 ‹http://www.theage.com.au/news/health/australia-worlds-fattest-nation/2008/06/19/1213770886872.html›. Trivedi, Bijal. “Junkie Food: Tastes That Your Brain Cannot Resist.” New Scientist 2776 (2010): 38–41. Wang, Jiali, Silvana Obici, Kimyata Morgan, Nir Barzilai, Zhaohui Feng, & Luciano Rossetti. “Overfeeding Rapidly Increases Leptin and Insulin Resistance.” Diabetes 50.12 (2001): 2786–2791. Warin, Megan. “Foucault’s Progeny: Jamie Oliver and the Art of Governing Obesity.” Social Theory & Health 9.1 (2011): 24–40. Weber, Christopher L., and H. Scott Matthews. “Food-miles and the Relative Climate Impacts of Food Choices in the United States.” Environmental Science & Technology 42.10 (2008): 3508–3513. Wessell, Adele, and Donna Lee Brien. Eds. Rewriting the Menu: the Cultural Dynamics of Contemporary Food Choices. Special Issue 9, TEXT: Journal of Writing and Writing Programs October 2010. World Health Organisation. Closing the Gap: Policy into Practice on Social Determinants of Health [Discussion Paper]. Rio de Janeiro, Brazil: World Conference on Social Determinants of Health, World Health Organisation, 19–21 October 2011.