Miracle-dz/UniFAR-FTUs huggingface dataset:
High-resolution modeling of thermal thresholds and environmental influences on coral bleaching for local and regional reef management

Coral reefs are one of the world’s most threatened ecosystems, with global and local stressors contributing to their decline. Excessive sea-surface temperatures (SSTs) can cause coral bleaching, resulting in coral death and decreases in coral cover. A SST threshold of 1 °C over the climatological maximum is widely used to predict coral bleaching. In this study, we refined thermal indices predicting coral bleaching at high-spatial resolution (1 km) by statistically optimizing thermal thresholds, as well as considering other environmental influences on bleaching such as ultraviolet (UV) radiation, water turbidity, and cooling effects. We used a coral bleaching dataset derived from the web-based monitoring system Sango Map Project, at scales appropriate for the local and regional conservation of Japanese coral reefs. We recorded coral bleaching events in the years 2004–2016 in Japan. We revealed the influence of multiple factors on the ability to predict coral bleaching, including selection of thermal indices, statistical optimization of thermal thresholds, quantification of multiple environmental influences, and use of multiple modeling methods (generalized linear models and random forests). After optimization, differences in predictive ability among thermal indices were negligible. Thermal index, UV radiation, water turbidity, and cooling effects were important predictors of the occurrence of coral bleaching. Predictions based on the best model revealed that coral reefs in Japan have experienced recent and widespread bleaching. A practical method to reduce bleaching frequency by screening UV radiation was also demonstrated in this paper.
At the Border of Acoustics and Linguistics : BagofAudioWords BagofAudioWords BagofAudioWords ofAudioWords ofAudioWords AudioWords AudioWords for the Recognition of Emotions in Speech

Recognition of natural emotion in speech is a challenging task. Different methods have been proposed to tackle this complex task, such as acoustic feature brute-forcing or even endto-end learning. Recently, bag-of-audio-words (BoAW) representations of acoustic low-level descriptors (LLDs) have been employed successfully in the domain of acoustic event classification and other audio recognition tasks. In this approach, feature vectors of acoustic LLDs are quantised according to a learnt codebook of audio words. Then, a histogram of the occurring ‘words’ is built. Despite their massive potential, BoAW have not been thoroughly studied in emotion recognition. Here, we propose a method using BoAW created only of mel-frequency cepstral coefficients (MFCCs). Support vector regression is then used to predict emotion continuously in time and value, such as in the dimensions arousal and valence. We compare this approach with the computation of functionals based on the MFCCs and perform extensive evaluations on the RECOLA database, which features spontaneous and natural emotions. Results show that, BoAW representation of MFCCs does not only perform significantly better than functionals, but also outperforms by far most of recently published deep learning approaches, including convolutional and recurrent networks.
Optimism in reinforcement learning and Kullback-Leibler divergence

We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. In MDPs, optimism can be implemented by carrying out extended value iterations under a constraint of consistency with the estimated model transition probabilities. The UCRL2 algorithm by Auer, Jaksch and Ortner (2009), which follows this strategy, has recently been shown to guarantee near-optimal regret bounds. In this paper, we strongly argue in favor of using the Kullback-Leibler (KL) divergence for this purpose. By studying the linear maximization problem under KL constraints, we provide an efficient algorithm, termed KL-UCRL, for solving KL-optimistic extended value iteration. Using recent deviation bounds on the KL divergence, we prove that KL-UCRL provides the same guarantees as UCRL2 in terms of regret. However, numerical experiments on classical benchmarks show a significantly improved behavior, particularly when the MDP has reduced connectivity. To support this observation, we provide elements of comparison between the two algorithms based on geometric considerations.
Adaptive Skin Color Classificator

A lot of computer vision applications benefit from robust skin color classification. But this is a hard challenge due to the various image conditions like camera settings, illumination, light source, shadows and many more. Furthermore people’s tans and ethnic groups also extend those conditions. In this work we present a parametric skin color classifier that can be adapted to the conditions of each image or image sequence. This is done by evaluating some previously know skin color pixels which are acquired by applying a face detector. This approach can distinguish skin color from very similar color like lip color or eye brow color. Its high speed and high accuracy makes it appropriate for real time applications such as face tracking and mimic recognition.
Social environments, risk-taking and injury in farm adolescents

Background Farm environments are especially hazardous for young people. While much is known about acute physical causes of traumatic farm injury, little is known about social factors that may underlie their aetiology. Objectives In a nationally representative sample of young Canadians aged 11–15 years, we described and compared farm and non-farm adolescents in terms of the qualities of their social environments, engagement in overt multiple risk-taking as well as how such exposures relate aetiologically to their reported injury experiences. Methods Cross-sectional analysis of survey reports from the 2014 (Cycle 7) Canadian Health Behaviour in School-Aged Children study was conducted. Children (n=2567; 2534 weighted) who reported living or working on farms were matched within schools in a 1:1 ratio with children not living or working on farms. Scales examining quality of social environments and overt risk-taking were compared between the two groups, stratified by gender. We then related the occurrence of any serious injury to these social exposures in direct and interactive models. Results Farm and non-farm children reported social environments that were quite similar, with the exception of overt multiple risk-taking, which was demonstrably higher in farm children of both genders. Engagement in overt risk-taking, but not the other social environmental factors, was strongly and consistently associated with risks for serious injury in farm as well as non-farm children, particularly among males. Conclusions Study findings highlight the strength of associations between overt multiple risk-taking and injury among farm children. This appears to be a normative aspect of adolescent farm culture.
Effects of realimentation after nutrient restriction during mid‐ to late gestation on pancreatic digestive enzymes, serum insulin and glucose levels, and insulin‐containing cell cluster morphology

This study examined effects of stage of gestation and nutrient restriction with subsequent realimentation on maternal and foetal bovine pancreatic function. Dietary treatments were assigned on day 30 of pregnancy and included: control (CON; 100% requirements; n = 18) and restricted (R; 60% requirements; n = 30). On day 85, cows were slaughtered (CON, n = 6; R, n = 6), remained on control (CC; n = 12) and restricted (RR; n = 12), or realimented to control (RC; n = 11). On day 140, cows were slaughtered (CC, n = 6; RR, n = 6; RC, n = 5), remained on control (CCC, n = 6; RCC, n = 5) or realimented to control (RRC, n = 6). On day 254, the remaining cows were slaughtered and serum samples were collected from the maternal jugular vein and umbilical cord to determine insulin and glucose concentrations. Pancreases from cows and foetuses were removed, weighed, and subsampled for enzyme and histological analysis. As gestation progressed, maternal pancreatic α-amylase activity decreased and serum insulin concentrations increased (p ≤ 0.03). Foetal pancreatic trypsin activity increased (p < 0.001) with advancing gestation. Foetal pancreases subjected to realimentation (CCC vs. RCC and RRC) had increased protein and α-amylase activity at day 254 (p ≤ 0.02), while trypsin (U/g protein; p = 0.02) demonstrated the opposite effect. No treatment effects were observed for maternal or foetal pancreatic insulin-containing cell clusters. Foetal serum insulin and glucose levels were reduced with advancing gestation (p ≤ 0.03). The largest maternal insulin-containing cell cluster was not influenced by advancing gestation, while foetal clusters grew throughout (p = 0.01). These effects indicate that maternal digestive enzymes are influenced by nutrient restriction and there is a potential for programming of increased foetal digestive enzyme production resulting from previous maternal nutrient restriction.
Non-linear recursive parameter estimation applied to fault detection and diagnosis in real buildings

This paper describes a fault detection and diagnosis scheme based on parameter estimation and presents results from its application to a cooling coil subsystem in a real building. A non-linear adaptation of the Prediction Error Forgetting (PEF), algorithm is employed to estimate the parameters of a simple, steady-state, first principles based cooling coil model. A steady-state detector is used to discard data with excessive transients. Three model parameters represent possible faults; control valve leakage, coil fouling and sensor offset. These parameters are estimated recursively, together with the uncertainty in the estimated values. A significant change in a particular parameter indicates abnormal operation and suggests a diagnosis. The paper describes the first-principle models and their fault parameters, the steady-state detector, and the recursive parameter estimation algorithm. Results from the application of the technique to data measured in a test building demonstrate that valve leakage and coil fouling can be detected and diagnosed. The applicability of the approach to fault detection and diagnosis in real systems is also discussed.
MODELING OF FRICTIONS IN THE TRANSMISSION ELEMENTS OF A ROBOT AXIS FOR ITS IDENTIFICATION

Abstract Control in robotics needs more and more precise models of the mechanical parts of the structure and specially for a complex system such as a biped robot. An important but difficult aspect of this work is the modeling of the mechanical loss due to friction in the chain of transmission from the motor to the axis. Each part losses are defined as a sum of three terms, one constant, another depending only on the speed and the last depending on the torque transmitted. The robot joint kinematic chain is modeled with three elements: the motor, the gearbox and a rotational joint at the leg. The results show a good adequacy between measurement and simulation with the proposed identification method in comparison with a classic least square identification method.
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents

We consider the problem of \emph{fully decentralized} multi-agent reinforcement learning (MARL), where the agents are located at the nodes of a time-varying communication network. Specifically, we assume that the reward functions of the agents might correspond to different tasks, and are only known to the corresponding agent. Moreover, each agent makes individual decisions based on both the information observed locally and the messages received from its neighbors over the network. Within this setting, the collective goal of the agents is to maximize the globally averaged return over the network through exchanging information with their neighbors. To this end, we propose two decentralized actor-critic algorithms with function approximation, which are applicable to large-scale MARL problems where both the number of states and the number of agents are massively large. Under the decentralized structure, the actor step is performed individually by each agent with no need to infer the policies of others. For the critic step, we propose a consensus update via communication over the network. Our algorithms are fully incremental and can be implemented in an online fashion. Convergence analyses of the algorithms are provided when the value functions are approximated within the class of linear functions. Extensive simulation results with both linear and nonlinear function approximations are presented to validate the proposed algorithms. Our work appears to be the first study of fully decentralized MARL algorithms for networked agents with function approximation, with provable convergence guarantees.
Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface

Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two‐factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.
Pharmacokinetic and Pharmacodynamic Efficacies of Continuous versus Intermittent Administration of Meropenem in Patients with Severe Sepsis and Septic Shock: A Prospective Randomized Pilot Study

Background: The antibiotic meropenem is commonly administered in patients with severe sepsis and septic shock. We compared the pharmacokinetic, clinical, and bacteriological efficacies of continuous infusion of meropenem versus intermittent administration in such patients. Methods: Patients admitted to the Intensive Care Unit (ICU) with severe sepsis or septic shock who received meropenem were randomly assigned to either the continuous (n = 25) or intermittent groups (n = 25). The continuous group received a loading dose of 0.5 g of meropenem followed by a continuous infusion of 3 g/day; the intermittent group received an initial dose of 1.5 g followed by 1 g for every 8 h. Clinical success, microbiological eradication, superinfection, ICU mortality, length of ICU stay, and duration of meropenem treatment were assessed. Serial plasma meropenem concentrations for the first and third dosing periods (steady state) were also measured. Results: Clinical success was similar in both the continuous (64%) and intermittent (56%) groups (P = 0.564); the rates of microbiological eradication and superinfection (81.8% vs. 66.7% [P = 0.255] and 4% vs. 16% [P = 0.157], respectively) showed improvement in the continuous group. The duration of meropenem treatment was significantly shorter in the continuous group (7.6 vs. 9.4 days; P = 0.035), where a better steady-state concentration was also achieved. Peak and trough concentrations were significantly different between the continuous and intermittent groups both in the first (Cmax: 19.8 mg/L vs. 51.8 mg/L, P = 0.000; Cmin: 11.2 mg/L vs. 0.5 mg/L, P = 0.000) and third dosing periods (Cmax: 12.5 mg/L vs. 46.4 mg/L, P = 0.000; Cmin: 11.4 mg/L vs. 0.6 mg/L, P = 0.000). For medium-susceptibility pathogens, continuous infusion concentrations above the minimal inhibitory concentration were 100%, which was better than that in the intermittent group. Conclusions: Continuous infusion of meropenem provides significantly shorter treatment duration and a tendency for superior bacteriological efficacy than intermittent administration. Continuous infusion may be more optimal against intermediate-susceptibility pathogens.
Acute ischemic stroke with tandem lesions: technical endovascular management and clinical outcomes from the ESCAPE trial

Background Tandem occlusions of the extracranial carotid and intracranial carotid or middle cerebral artery have a particularly poor prognosis without treatment. Several management strategies have been used with no clear consensus recommendations. We examined subjects with tandem occlusions enrolled in the ESCAPE trial and their outcomes. Methods Data are from the ESCAPE trial. Additional data were sought on interventions for each subject. Results There were 54 (17%) subjects with tandem extracranial and intracranial occlusions. Patients in the endovascular treatment arm (n=30) were more likely to be younger (median age 66 years, p<0.01), male (66.7%, p=0.03), diabetic, and without atrial fibrillation. Subjects with tandem occlusions were more likely to have intracranial internal carotid artery occlusions than M1 occlusions (p<0.01). Of the 30 intervention-arm subjects, 17 (57%) underwent emergency endovascular treatment of the extracranial disease, 10 subjects before and seven subjects after intracranial thrombectomy. Of the remaining 13 subjects, only four required staged carotid revascularization due to persistent severe carotid stenosis; four had cervical pseudo-occlusions with no residual stenosis after large distal carotid thrombus burden aspiration/retrieval. Outcomes were similar between subjects with and without tandem lesions. The use of antithrombotic agents after acute carotid artery stenting was variable but no symptomatic intracerebral hemorrhage was seen in subjects who underwent emergency endovascular treatment of extracranial carotid artery. Conclusions Tandem occlusions occurred in one-sixth of patients and were treated highly variably within the ESCAPE trial. While outcomes were similar, the best method to treat the carotid artery in patients with tandem occlusion awaits further randomized data. Trial registration number NCT01778335.
Phototaxis of Grapholitha molesta (Lepidoptera: Olethreutidae) to Different Light Sources

ABSTRACT The Oriental Fruit Moth Grapholita molesta (Busck) causes substantial damage to stone and pome fruit crops worldwide. Light-based traps offer a potential means for pest monitoring and management. In this study, we tested the preference of G. molesta for the following light sources: monochromatic light produced from light-emitting diodes (LEDs) (red, orange, yellow, green, blue, violet, and white), specific wavelengths of light produced from filters (405, 450, 480, 512, 540, 576, and 610 nm), and polychromatic light produced by different numbers (0, 12, 24, and 36) of green, blue, and violet LEDs. The arrangement of polychromatic lights was based on an orthogonal design matrix of L16 (43). Based on the results of former studies, we further determined the optimal number of green and violet LEDs. The results showed that: 1) G. molesta strongly preferred the green, violet, and blue LEDs; 2) G. molesta significantly preferred light at 405 nm, followed by 540 nm, and showed no phototaxis to 480 nm; 3) for the polychromatic light configuration, violet and green were the factors that determined the preference of G. molesta, and the lamp with 12 violet LEDs captured the most moths; and 4) for the lamps with different light intensities, 36 violet LEDs or 12 green LEDs attracted the most moths, with the former performing better.
Generation of Isthmic Organizer-Like Cells from Human Embryonic Stem Cells

The objective of this study was to induce the production of isthmic organizer (IsO)-like cells capable of secreting fibroblast growth factor (FGF) 8 and WNT1 from human embryonic stem cells (ESCs). The precise modulation of canonical Wnt signaling was achieved in the presence of the small molecule CHIR99021 (0.6 μM) during the neural induction of human ESCs, resulting in the differentiation of these cells into IsO-like cells having a midbrain-hindbrain border (MHB) fate in a manner that recapitulated their developmental course in vivo. Resultant cells showed upregulated expression levels of FGF8 and WNT1. The addition of exogenous FGF8 further increased WNT1 expression by 2.6 fold. Gene ontology following microarray analysis confirmed that IsO-like cells enriched the expression of MHB-related genes by 40 fold compared to control cells. Lysates and conditioned media of IsO-like cells contained functional FGF8 and WNT1 proteins that could induce MHB-related genes in differentiating ESCs. The method for generating functional IsO-like cells described in this study could be used to study human central nervous system development and congenital malformations of the midbrain and hindbrain.