Baseline State Research Articles

Persistence of tropical herbivores in temperate reefs constrains kelp resilience to cryptic habitats

Abstract Global warming is facilitating the range expansion of tropical herbivores, causing a tropicalization of temperate marine ecosystems, where tropical herbivores can suppress habitat‐forming macrophytes, supporting the resilience of canopy‐free ecosystem states. However, currently we lack a thorough understanding of the mechanisms that, on one hand, support the persistence of tropical herbivores and on the other support the recovery of temperate foundation species in tropicalized ecosystems, a required knowledge to predict potential regime shifts and reversals to the baseline state of the ecosystem. This study tested processes behind the persistence of the tropicalization of temperate reefs which experienced a complete loss of their kelp forests and an influx of tropical herbivores following a marine heatwave in 2011. For this, we assessed the feedback mechanisms that maintain turf‐dominated states (recruitment of tropical herbivores, browsing and grazing rates and turf cover) and those that resist it (kelp recruitment, survival and reproductiveness). We found that the reefs remained tropicalized with high abundances of turf and tropical herbivores after 9 years from the regime shift. The rabbitfish Siganus fuscescens and the chub Kyphosus bigibbus were the most important herbivores whose persistence was supported by the adjacent reef lagoon, where seagrass meadows and the backreef habitats hosted juveniles of both species, particularly rabbitfish. Tropical herbivores exerted a strong top–down control on turf seaweed and kelp during herbivory assays, rapidly consuming kelp individuals in open areas. However, in topographical refuges in the reefs, herbivory was low and kelp individuals survived, with some having reproductive tissue. Synthesis. Our findings incorporate the importance of nursery grounds for tropical herbivores and herbivory refugia for kelp individuals into the tropicalization model, where the former increases the resilience of canopy‐free states and the latter might facilitate recovering kelp populations. The restoration of abundant warm‐resistant kelp populations in shelters could provide local sources of propagules to recolonize open spaces; however, our results suggest that the reduction of herbivory and the provision of turf‐free substratum would be necessary to boost the recovery of kelp forests.

P.329 State anxiety induced by THC and CBD does not change after correcting for baseline anxiety levels

Background: In the last decade, the psychoactive substance delta-9-tetrahydrocannabinol (THC) in cannabis products has risen considerably, which has been associated with increased anxiety [1]. The non-psychoactive cannabis compound cannabidiol (CBD) is suggested to counteract THC-induced anxiety to some extent [2,3], however, these effects are mild [3]. Trait anxiety has been suggested to moderate cannabis-induced anxiety [4]. The present study aimed to examine whether the CBD effects on THC-induced anxiety can be explained by baseline state anxiety levels and/or trait anxiety levels in healthy volunteers. Methods: A placebo-controlled, randomized within-subjects study including 26 healthy recreational cannabis users was set up to test the effects of vaporized cannabis containing THC (11% THC, <1% CBD), CBD (<1% THC, 11% CBD), THC/CBD (11% THC, 11% CBD), and placebo cannabis (<1% THC, <1% CBD) on anxiety measures. Participant ratings of subjective state anxiety using Visual Analogue Scales (VAS) and State-Trait Anxiety Inventory (STAI)-state served as a measure of explicit anxiety, and a computer-based emotional Stroop task was used to assess implicit anxiety. Subjective anxiety state was scored repeatedly over 6 hours, while the STAI-state and emotional Stroop task were administered directly after drug inhalation. Trait anxiety levels (STAI) were measured once prior to the test days and baseline state anxiety level were measured once prior to each drug inhalation. All data were analysed with Linear Mixed Models (LMMs); the VAS ratings of state anxiety were analysed with unstructured covariance structure, and the STAI-state and emotional Stoop data were analysed with compound symmetry as covariance structure. The STAI-trait and anxiety state baseline scores were added as covariates. When a covariate was non-significant, it was removed from the model. In the case of a main Drug effect, planned Bonferonni-corrected pairwise comparisons were performed. Results: There was a main effect of the covariate baseline state anxiety (p< 0.01), a drug by trait anxiety interaction (p= 0.02) and a main Drug effect (p< 0.01) on the subjective state rating of anxiety (VAS). Participants felt more anxious during THC (p< 0.01; 95% CI [-2.02, -0.80]) and THC/CBD (p< 0.05; 95% CI [-1.46, -0.23]) compared to placebo. Both covariates did not show a significant effect on the STAI-state and emotional Stroop and thereby removed from further analyses. There was a main Drug effect on the STAI-state; (p< 0.01) both THC (p< 0.01; 95% CI [-17.20, -9.30]) and THC/CBD (p= 0.03; 95% CI [-10.89, -2.76]) increased state anxiety compared to placebo, however anxiety induced by THC/CBD was less compared to the THC condition (p= 0.02; 95% CI [2.30, 10.54]). There were no significant Drug effect on the emotional Stroop task. Conclusion: The present study shows that trait anxiety partly predicts cannabis induced increments in state anxiety. However, cannabis effects on anxiety are robust as they do not change after correcting for baseline differences in state anxiery. While baseline levels and trait anxiety are both subjective measures, future studies might also include pharmacokinetics and pharmacodynamics modelling in order to include individual differences in metabolism which might explain the cannabis-induced anxiety.

Mitigating damage on heritage structures by continuous conservation using thermal real-time monitoring. Case study of Ziri Wall, city of Granada, Spain

Climate change and anthropogenic causes represent a multidisciplinary problem in urban environments, specifically in the destruction of historical elements of enormous value. Although conventional preservation methods are based on comprehensive conservation measures and periodic inspection, these urban elements sometimes lie in a state of neglect due to lack of means to carry out continuous monitoring. The present work develops a replicable and easy-to-apply multi-analytical methodology, which proposes the use of standard monitoring to automatically diagnose the elements of heritage buildings. Similar approaches are becoming popular in the setting of Structural Health Monitoring, and their application in the field of environmental monitoring is one of the valuable outputs of this work. Diagnosis is based on the development of an inverse characterisation model of the thermal response in a known state of conservation through standard monitoring. This model is calibrated using real measurements. The methodology involves characterising energy response to environmental excitations measured against what is deemed to be a baseline state of conservation. Also, the monitoring system and data processing required is defined and explained in detail. Anomalies detected in the comparison of the baseline to subsequent real-time measurements would highlight the need to bring scheduled on-site inspections forward with an affordable cost. This benchmarking using the estimation of baseline and real measurements is the main result of the methodology. Finally, the methodology developed was validated with an exhaustive study conducted on the Ziri Wall at Granada, Spain, in both summer and winter. The findings revealed a good fit between calculated and experimental data, with mean absolute errors of under 1 °C in both seasons. The proposal can be applied in other fields such as preventive maintenance.

Attracting investment for Africa's protected areas by creating enabling environments for collaborative management partnerships

Africa's Protected Area (PA) estate includes some of the world's most iconic wildlife and wildlands and preserves ecosystem services upon which people depend. However, Africa's PAs are facing a growing array of threats resulting in significant degradation, factors compounded by chronic funding shortages. In this opinion piece, drawing from the available literature and collective experience of the author group, we look at the potential for collaborative management partnerships (CMPs) between state wildlife agencies and Non-Governmental Organisations (NGOs) to attract investment and technical capacity to improve PA performance. The three main CMP models—financial and technical support, co-management, and delegated management—yield median funding that is 1.5, 2.6 and 14.6 times greater than baseline state budgets for PA management. However, several factors limit the scaling of CMPs in Africa. Significant barriers include concerns from African governments, such as reluctance to engage in co-management and delegated CMPs due to perceptions that such partnerships may represent an admission of failure, result in a loss of revenues for government, or undermine sovereignty. There are also constraints associated with NGOs and donors that limit scaling of CMPs. We discuss how these issues might be addressed and propose a reframing of the discourse around CMPs. Specifically, we recommend that governments view CMPs as strategic, proactive tools that will enable them to unlock funding, investment and expertise for conservation and make recommendations to attract such investment. Preliminary evidence and the experience of the author group suggests that expanding CMPs for PAs could; improve PA management; share the costs of protecting Africa's PAs with the global community; build local capacity; help protect the ecosystem services upon which Africa's economies depend; stimulate rural development; and benefit local communities.

Attention Modulated Multiple Object Tracking with Motion Enhancement and Dual Correlation

The one-shot multiple object tracking (MOT) framework has drawn more and more attention in the MOT research community due to its advantage in inference speed. However, the tracking accuracy of current one-shot approaches could lead to an inferior performance compared with their two-stage counterparts. The reasons are two-fold: one is that motion information is often neglected due to the single-image input. The other is that detection and re-identification (ReID) are two different tasks with different focuses. Joining detection and re-identification at the training stage could lead to a suboptimal performance. To alleviate the above limitations, we propose a one-shot network named Motion and Correlation-Multiple Object Tracking (MAC-MOT). MAC-MOT introduces a motion enhance attention module (MEA) and a dual correlation attention module (DCA). MEA performs differences on adjacent feature maps which enhances the motion-related features while suppressing irrelevant information. The DCA module focuses on decoupling the detection task and re-identification task to strike a balance and reduce the competition between these two tasks. Moreover, symmetry is a core design idea in our proposed framework which is reflected in Siamese-based deep learning backbone networks, the input of dual stream images, as well as a dual correlation attention module. Our proposed approach is evaluated on the popular multiple object tracking benchmarks MOT16 and MOT17. We demonstrate that the proposed MAC-MOT can achieve a better performance than the baseline state of the arts (SOTAs).

Melatonin pretreatment does not modify extrasystolic burden in the rat ischemia-reperfusion model.

The mechanism of reentrant ventricular tachyarrhythmias complicating acute myocardial ischemia is largely based on the interaction between an arrhythmogenic substrate and triggers. Melatonin was proposed as an antiarrhythmic medication and was shown to ameliorate the arrhythmogenic substrate. Also, melatonin provides a sympatholytic effect in different settings and might attenuate ectopic activity, which provides reentry triggers. In the present study, we aimed at evaluating the melatonin effects on cardiac sympathetic activity and the incidence of premature ventricular beats during the episode of ischemia-reperfusion. Experiments were done in a total of 26 control and 28 melatonin-treated (10 mg/kg, daily, for 7 days) male rats. Sympathetic fibers density was assessed by glyoxylic acid-induced fluorescence. Continuous electrocardiograms recording was performed during ischemia-reperfusion episodes (5 min/5 min, respectively) induced by reversible coronary occlusion. Myocardial expression of tyrosine hydroxylase, a rate-limiting enzyme of catecholamine biosynthesis was assessed by Western blotting. No differences in the state of sympathetic innervation were observed in histochemical analysis. However, Western blotting analysis demonstrated that melatonin treatment suppressed tyrosine hydroxylase expression in the non-ischemic (p < 0.05 versus control) but not ischemic regions of myocardium. The melatonin-treated animals had longer RR-intervals in the baseline state than the control animals (264 ± 48 ms versus 237 ± 33 ms, p = 0.044, respectively), but this difference decayed during the period of ischemia due to the increase of heart rate in the treated group. The number of premature ventricular beats did not differ between the control and treated groups during the ischemic and reperfusion periods. One-week melatonin pretreatment caused a slight peripheral sympatholytic effect that attenuated during ischemia and completely disappeared by the onset of reperfusion. The slight expression of sympathetic downregulation was associated with the lack of any effect of melatonin on extrasystolic burden. Collectively, the data suggest that melatonin cannot target the triggers of reentrant arrhythmias.

Glycine, a Dispensable Amino Acid, Is Conditionally Indispensable in Late Stages of Human Pregnancy

Recently, we showed that there are higher protein, lysine, and phenylalanine requirements in late stages of pregnancy compared with early stages. Animal studies have suggested an increased dietary need for specific dispensable amino acids in pregnancy; whether such a need exists in human pregnancies is unknown. The objective of the current study was to examine whether healthy pregnant women at midgestation (20-29 wk) and late gestation (30-40 wk) have a dietary demand for glycine, a dispensable amino acid, using the indicator amino acid oxidation method and measurement of plasma 5-oxoproline concentrations. Seventeen healthy women (aged 26-36 y) randomly received different test glycine intakes (range: 5-100 mg·kg-1·d-1) during each study day in midgestation (∼26 wk, n=17 observations in 9 women) and late gestation (∼35 wk, n=19 observations in 8 women). Diets were isocaloric with energy at 1.7 × resting energy expenditure. Protein was given as a crystalline amino acid mixture based on egg protein composition at current estimated average requirement (EAR; 0.88 g·kg-1·d-1). Breath samples were collected at baseline and isotopic steady state to measure oxidation of L-[1-13C]phenylalanine to 13CO2 (F13CO2). Plasma was collected at the sixth hour of the study day. Linear regression crossover analysis and simple linear regression were used to assess responses in F13CO2 and plasma 5-oxoproline concentrations to different glycine intakes. No statistically significant responses were observed in midgestation. However, in late gestation, lower glycine intakes resulted in higher rates of F13CO2 (suggesting low protein synthesis) with a breakpoint for phenylalanine oxidation at >37mgglycine·kg-1·d-1 and higher plasma 5-oxoproline (suggesting low glycine availability) with a breakpoint >27mg glycine·kg-1·d-1. The findings suggest that glycine should be considered a "conditionally" indispensable amino acid during late gestation, especially when protein intakes are at 0.88 g·kg-1·d-1, the current EAR. This trial was registered at clinicaltrials.gov as NCT02149953.

Диагностика ударных повреждений монолитных и сотовых углепластиков с помощью ультразвуковых волн Лэмба

The paper presents the results on Lamb waves based technique for impact damage detection and severity identification. The PZT network operates in the round-robin mode changing the actuator and sensor roles of the transducers in order to detect the response of the system in the presence of damage. The monitoring is performed via the analysis of three parameters: change of the amplitude (dA), change of the energy (dP) and cross-correlation (NCC) of the signals in baseline and damaged state. Testing of laminate CFRPs shows that the damage location is estimated within the 5–15 mm error, while the computed Damage index linearly is dependent on the applied impact energy. For honeycomb CFRPs the NCC parameter do not provide accurate results, however, the other parameters allow identification within the 5–20 mm error and reflect accurate data on the severity of the damage.

Impact Damage Detection in Laminate and Honeycomb CFRPs using Lamb Wave Ultrasonic Sensing

The paper presents the results on application of Lamb waves based technique for impact damage detection and severity identification. The PZT network operates in the round-robin mode changing the actuator and sensor roles of the transducers in order to detect the response of the system in the presence of damage. The monitoring is performed via the analysis of three parameters: change of the amplitude (dA), change of the energy (dP) and cross-correlation (NCC) of the signals in baseline and damaged state. Testing of laminate CFRPs shows that the damage location is estimated with an error of 5–15 mm, while the computed Damage index is linearly dependent on the applied impact energy. For honeycomb CFRPs the NCC parameter do not provide accurate results, however, other parameters allow identification within the 5–20 mm error and reflect accurate data on the severity of the damage.

Impact of Different Exercise Modalities on the Human Gut Microbiome

In this study we examined changes to the human gut microbiome resulting from an eight-week intervention of either cardiorespiratory exercise (CRE) or resistance training exercise (RTE). Twenty-eight subjects (21 F; aged 18–26) were recruited for our CRE study and 28 subjects (17 F; aged 18–33) were recruited for our RTE study. Fecal samples for gut microbiome profiling were collected twice weekly during the pre-intervention phase (three weeks), intervention phase (eight weeks), and post-intervention phase (three weeks). Pre/post VO2max, three repetition maximum (3RM), and body composition measurements were conducted. Heart rate ranges for CRE were determined by subjects’ initial VO2max test. RTE weight ranges were established by subjects’ initial 3RM testing for squat, bench press, and bent-over row. Gut microbiota were profiled using 16S rRNA gene sequencing. Microbiome sequence data were analyzed with QIIME 2. CRE resulted in initial changes to the gut microbiome which were not sustained through or after the intervention period, while RTE resulted in no detectable changes to the gut microbiota. For both CRE and RTE, we observe some evidence that the baseline microbiome composition may be predictive of exercise gains. This work suggests that the human gut microbiome can change in response to a new exercise program, but the type of exercise likely impacts whether a change occurs. The changes observed in our CRE intervention resemble a disturbance to the microbiome, where an initial shift is observed followed by a return to the baseline state. More work is needed to understand how sustained changes to the microbiome occur, resulting in differences that have been reported in cross sectional studies of athletes and non-athletes.

Profiling Mannheimia haemolytica infection in dairy calves using near infrared spectroscopy (NIRS) and multivariate analysis (MVA)

Bovine respiratory disease (BRD) linked with Mannheimia haemolytica is the principal cause of pneumonia in cattle. Diagnosis of BRD traditionally relies on visual assessment, which can be untimely, insensitive, and nonspecific leading to inadequate treatment and further spread of disease. Near Infrared Spectroscopy (NIRS) is a rapid acquisition vibrational spectroscopy that can profile changes in biofluids, and when used in combination with multivariate analysis, has potential for disease diagnosis. This study characterizes the NIR spectral profile of blood plasma from dairy calves infected with M. haemolytica and validates the spectral biochemistry using standardized clinical and hematological reference parameters. Blood samples were collected for four days prior to (baseline), and 23 days after, a controlled intrabronchial challenge. NIR spectral profiles of blood plasma discriminated and predicted Baseline and Infected states of animal disease progression with accuracy, sensitivity, and specificity ≥ 90% using PCA–LDA models. These results show that physiological and biochemical changes occurring in the bloodstream of dairy calves during M. haemolytica infection are reflected in the NIR spectral profiles, demonstrating the potential of NIRS as a diagnostic and monitoring tool of BRD over time.

The interactive influence of borderline personality disorder symptoms and social comparison orientation on self-esteem

Despite evidence for an association between BPD symptoms and low/unstable self-esteem (SE), no research has examined social factors that may moderate the relation between BPD symptoms and SE difficulties. One factor that may be especially relevant is social comparison orientation (SCO). Across two studies, this research examined the main and interactive effects of BPD symptoms and SCO on several SE outcomes, including trait SE, baseline state SE, and in-the-moment threat to SE following an online social interaction task. In Study 1, a university sample of young women (N = 161) completed questionnaires on BPD symptoms, SCO, and trait SE. In Study 2, a university sample of young adults (N = 108) completed questionnaires on BPD symptoms, SCO, and baseline state SE. Participants engaged in a rejection or inclusion condition of an online social interaction task and reported on in-the-moment threat to their SE. Results revealed significant relations between BPD symptoms and all SE outcomes among young adults with high and mean SCO. Results highlight the relevance of SCO to the relation between BPD symptoms and SE, suggesting that BPD symptoms are associated with lower trait and state SE and greater threat to SE among young adults with average or greater tendencies to socially compare.

Att-Net: Enhanced emotion recognition system using lightweight self-attention module

Speech emotion recognition (SER) is an active research field of digital signal processing and plays a crucial role in numerous applications of Human–computer interaction (HCI). Nowadays, the baseline state of the art systems has quite a low accuracy and high computations, which needs upgrading to make it reasonable for real-time industrial uses such as detection of content from speech data. The main intent for low recognition rate and high computational cost is a scarceness of datasets, model configuration, and patterns recognition that is the supreme stimulating work for building a robust SER system. In this study, we address these problems and propose a simple and lightweight deep learning-based self-attention module (SAM) for SER system. The transitional features map is given to SAM, which produces efficiently the channel and spatial axes attention map with insignificant overheads. We use a multi-layer perceptron (MLP) in channel attention to extracting global cues and a special dilated convolutional neural network (CNN) in spatial attention to extract spatial info from input tensor. Moreover, we merge, spatial and channel attention maps to produce a combine attention weights as a self-attention module. We placed SAM in the middle of convolutional and connected layers and trained it in an end-to-end mode. The ablation study and comprehensive experimentations are accompanied over IEMOCAP, RAVDESS, and EMO-DB speech emotion datasets. The proposed SER system shows consistent improvements in overall experiments for all datasets and shows 78.01%, 80.00%, and 93.00% average recall, respectively.

Magnesium-containing composition influencing morphological parameters and gelatinase B activity in endometrial tissues in experimental chronic endometrial inflammation

Aim: to assess an effect of medicinal magnesium-containing composition on gelatinase B expression intensity and morphological parameters of chronic experimental endometrial inflammation.Materials and Methods. There were conducted experiments with 60 sexually mature female Wistar rats to determine an effect of medicinal magnesium-containing composition (contains magnesium chloride – a natural polymineral Bischofite) on gelatinase B activity in endometrial tissues (counting number of gelatinase-B-positive cells and intensity of gelatinase B expression), morphological parameters of cell infiltration, as well as amount of magnesium in red blood cell mass collected from the inferior vena cava and subclavian vein. All such parameters were assessed in experimental animals from 4 groups: group 1 – animals in baseline state, group 2 – control, group 3 – experimental chronic endometritis (CE), group 4 – experimental CE after treatment with medicinal magnesium-containing composition. Results. It was found that use of medicinal magnesium-containing composition increased amount of erythrocyte magnesium up to the baseline level and increased both number and expression intensity of stromal gelatinase B-positive cells. In addition, magnesium level in erythrocyte mass from the inferior vena cava was increased and accompanied with restored eosinophil-plasmacyte as well as significantly elevated macrophage-lymphocyte infiltration in endometrial tissues compared to CE animals lacking therapy. Conclusion. The results of this study allow us to conclude about importance of gelatinase B in pathogenesis of experimental chronic endometrial inflammation as well as an opportunity of regulating gelatinase B activity by applying medicinal magnesium containing drug in pathogenetic therapy of experimental CE.

Unexpected Diversity in Regenerating Sites Stresses the Importance of Baselines: A Case Study With Bats (Order Chiroptera) on the Osa Peninsula, Costa Rica

Introduction: Background and Research Aims:Assessing biodiversity recovery is key to determine whether the objectives of habitat restoration for conservation are met. Many restoration initiatives use cross-sectional comparisons of wildlife communities to infer restoration impact instead of longitudinal assessments from a baseline state. Using an indicator of biodiversity in the neotropics— bats— we demonstrate how assessing community diversity and composition in an area targeted for restoration prior to implementation, and when compared to surrounding intact forest, provides the groundwork to track changes in the community post-restoration.MethodsWe assessed bat communities by 1) using mist-net surveys to identify species in the family Phyllostomidae (leaf-nosed bats), and 2) conducting acoustic surveys to identify non-phyllostomid species (aerial insectivores).ResultsFor both groups, we found that areas targeted for restoration had similar diversity as the surrounding forest, but the two habitat types differed in community composition. Phyllostomids were captured at higher rates in forest, but aerial insectivores were detected at higher rates in restoration habitat.ConclusionOur baseline assessment revealed unexpected diversity in areas targeted for restoration. The presence of all trophic groups in restoration habitat suggests that bats provide key ecosystem services in the restoration process, such as through seed dispersal, pollination and insect pest control. Implications for Conservation: Conducting a baseline survey of bats in areas targeted for restoration demonstrated that the community was not species poor at the baseline and was different from the surrounding forest, allowing us to better track restoration success and the effects of different restoration treatments.

Emotional State Recognition Performance Improvement on a Handwriting and Drawing Task

In this work we combine time, spectral and cepstral features of the signal captured in a tablet to characterize depression, anxiety, and stress emotional state recognition on the EMOTHAW database. EMOTHAW contains the emotional states of users represented by capturing signals from sensors on the tablet and pen when the user is performing 3 specific handwriting and 4 drawing tasks, which had been categorized into depressed, anxious, stressed, and typical, according to the Depression, Anxiety and Stress Scale (DASS). Each user was characterized with six time-domain features, and the number of spectral-domain and cepstral-domain features for the horizontal and vertical displacement of the pen, the pressure on the paper, and the time spent on-air and off-air, depended on the configuration of the filterbank. As next step, we select the best features using the Fast Correlation-Based Filtering method. Since our dataset has 129 users, then as next step, we augmented the training data by randomly selecting a percentage of the training data and adding a small random Gaussian noise to the extracted features. We then train a radial basis SVM model using the Leave-One-Out (LOO) methodology. The experimental results show an average accuracy classification improvement ranging of 15%, and an accuracy classification improvement ranging from 4% to 34% compared with baseline (state of the art) for specific emotions such as depression, anxiety, stress, and typical emotional states.

Adaptive Path Following Control of Unmanned Surface Vehicles Considering Environmental Disturbances and System Constraints

The current maritime applications have yielded strong demands for the development of advanced unmanned surface vehicles (USVs) with more reliable path following capabilities to greatly extend mission durations and enhance accommodative capabilities of USVs to more hazardous and dynamic environments. This paper presents an adaptive path following control method using a retrofit adaptive tracking control technique with application to a USV with consideration of environmental disturbances (like winds, waves, and currents), while taking into account of the system constraints of USVs, including both turning features (turning rate limit and turning dynamics) and rudder operation constraints (rudder deflection and rate saturation, and its dynamics). In order to guarantee the satisfactory performance of the USV operating in a calm environment, a baseline state feedback tracking controller considering the characteristics of yaw rate and rudder operations, and USV steering and actuator dynamics is first designed. In the presence of time-varying environmental disturbances, a retrofit adaptive disturbance compensating control mechanism is then developed based on the disturbance amplitude estimated from an indirect adaptive disturbance estimator. Finally, a reconfigurable adaptive path following controller is synthesized by combining the baseline controller and the adaptive disturbance compensating mechanism for the proper operation of the USV in the presence of environmental disturbances, while the desired path is successfully followed by the USV within an acceptable deviation boundary and without violating constraints of turning rates as well as amplitude and rate of rudder deflections. To evaluate the effectiveness of the proposed path following control methodology, both numerical simulations on a nonlinear USV model and field experiments on a real-size USV are conducted.

Optimizing Mental Workload Estimation by Detecting Baseline State Using Vector Phase Analysis Approach.

Improper baseline return from the previous task-evoked hemodynamic response (HR) can contribute to a large variation in the subsequent HR, affecting the estimation of mental workload in brain-computer interface systems. In this study, we proposed a method using vector phase analysis to detect the baseline state as being optimal or suboptimal. We hypothesize that selecting neuronal-related HR as observed in the optimal-baseline blocks can lead to an improvement in estimating mental workload. Oxygenated and deoxygenated hemoglobin concentration changes were integrated as parts of the vector phase. The proposed method was applied to a block-design functional near-infrared spectroscopy dataset (total blocks = 1384), measured on 24 subjects performing multiple difficulty levels of mental arithmetic task. Significant differences in hemodynamic signal change were observed between the optimal- and suboptimal-baseline blocks detected using the proposed method. This supports the effectiveness of the proposed method in detecting baseline state for better estimation of mental workload. The results further highlight the need of customized recovery duration. In short, the proposed method offers a practical approach to detect task-evoked signals, without the need of extra probes.

Extending community trajectory analysis: New metrics and representation

Ecological research focuses on the spatio-temporal patterns of ecosystems and communities. The recently proposed framework of Community Trajectory Analysis considers community dynamics as trajectories in a chosen space of community resemblance and utilizes geometrical properties of trajectories to compare and analyse temporal changes. Here, we extend the initial framework, which focused on consecutive trajectory segments, by considering additional metrics with respect to initial or baseline states. Addressing questions about community dynamics and more generally temporal and spatial ecological variability requires synthetic and efficient modes of representation. Hence, we propose a set of innovative maps, charts and trajectory roses to represent trajectory properties and complement the panel of traditional modes of representation used in community ecology. We use four case studies to highlight the complementarity and the ability of the new metrics and innovative figures to illustrate ecological trajectories and to facilitate their interpretation. Finally, we encourage ecologists skilled in multivariate analysis to integrate CTA into their toolbox in order to quantitatively evaluate spatio-temporal changes.

Roles of Very Fast Ripple (500-1000[Formula: see text]Hz) in the Hippocampal Network During Status Epilepticus.

Very fast ripples (VFRs, 500-1000[Formula: see text]Hz) are considered more specific than high-frequency oscillations (80-500[Formula: see text]Hz) as biomarkers of epileptogenic zones. Although VFRs are frequent abnormal phenomena in epileptic seizures, their functional roles remain unclear. Here, we detected the VFRs in the hippocampal network and tracked their roles during status epilepticus (SE) in rats with pilocarpine-induced temporal lobe epilepsy (TLE). All regions in the hippocampal network exhibited VFRs in the baseline, preictal, ictal and postictal states, with the ictal state containing the most VFRs. Moreover, strong phase-locking couplings existed between VFRs and slow oscillations (1-12[Formula: see text]Hz) in the ictal and postictal states for all regions. Further investigation indicated that during VFRs, the build-up of slow oscillations in the ictal state began from the temporal lobe and then spread through the whole hippocampal network via two different pathways, which might be associated with the underlying propagation of epileptiform discharges in the hippocampal network. Overall, we provide a functional description of the emergence of VFRs in the hippocampal network during SE, and we also establish that VFRs may be the physiological representation of the pathological alterations in hippocampal network activity during SE in TLE.