The spreading of urban areas and the growth of human population worldwide raise societal and environmental concerns. To better address these concerns, the monitoring of the acoustic environment in urban as well as rural or wilderness areas is an important matter. Building on the recent development of low cost hardware acoustic sensors, we propose in this paper to consider a sensor grid approach to tackle this issue. In this kind of approach, the crucial question is the nature of the data that are transmitted from the sensors to the processing and archival servers. To this end, we propose an efficient audio coding scheme based on third octave band spectral representation that allows: (1) the estimation of standard acoustic indicators; and (2) the recognition of acoustic events at state-of-the-art performance rate. The former is useful to provide quantitative information about the acoustic environment, while the latter is useful to gather qualitative information and build perceptually motivated indicators using for example the emergence of a given sound source. The coding scheme is also demonstrated to transmit spectrally encoded data that, reverted to the time domain using state-of-the-art techniques, are not intelligible, thus protecting the privacy of citizens. Second, the nodes shall be energy efficient, and, ideally, autonomous, to ease the deployment of the sensor grid to the desired topology. Third, the encoding scheme used to transmit the data from the sensor to the storage and processing servers shall be designed with care in order to guarantee the privacy of the citizens. At the same time, the data stored shall remain as rich as possible, while maintaining a low bitrate for efficient transmission and storage.In the case of urban acoustic monitoring, the data of interest typically consist of standardized high-quality measurements of energetic indicators such as the equivalent sound level ronments , they arronments . Many otronments  includinronments ,9,10.In addition, considering sound sources allows better assessing the human perception of the urban sound environment in terms of pleasantness and other perceptual indicators ,12. For Performing the detection online . The remaining of the paper is organized as follows: To promote reproducible research, the coder as well as the experiments needed to generate the figures is available to the research community . The continuously sampled audio is segmented into either 125 ms or 1 s frames to provide “fast” or “slow” acoustic measurements. The data are zero-padded to the next power of two to improve computational efficiency. The other parameters such as windowing functions and frame overlap are dependant on the specific constraints, and discussed in A Huffman coding scheme  is an efi and n is the numerical base in which the output code is represented. A lower entropy can be obtained with two factors. First, the dictionary size, i.e., the number of symbols must be kept low. This implies performing a quantization on the data resulting in a loss of precision. Second, the data distribution itself is important. Entropy decreases when very few symbols have a very high probability of appearance and is maximum for a uniform distribution.The efficiency of the coding step thus directly depends on the entropy of the transmitted data. It is defined as Considering an estimated PDF for our data, as shown in Huffman encoding is then computed with either a frame-specific symbol-code dictionary or a fixed dictionary generated using a learning dataset. A comparison of both methods is shown in The decoding process is quite straightforward, as both Huffman and A set of metrics is computed to assess the efficiency of the proposed coder scheme and to determine the impact of the degrees of freedom given by the parameters of the proposed algorithm. Those parameters are as follow: (1) the desired word size prior to Huffman encoding, set by quantization for both signal representation choices; (2) the number of considered bands; and (3) the STFT parameters including frame duration, overlap and windowing function usage. This section details experimental protocols for the validation of bitrate, measurement error, audio event recognition and intelligibility developped to best suit the corresponding constraints.The coder’s output bitrate as well as measurement error is computed for both data representations. This metric is composed of the spectral third-octave band analysis error and the additional loss yielded by quantization before the encoding process.ita_toolbox implementation [ita_toolbox in the same experimental conditions, then averaged over time and compared to the toolbox’s measurements on longer 2 s extracts. The experiment is run for Gaussian white noise as well as urban environmental recordings: the former allows direct estimation bias evaluation, while the latter provides a simulation of real operating conditions. As the analysis frames are of short duration, poor frequency resolution and spectral leakage are expected when performing the STFT, particularly in the lower frequencies bands. For this reason, we evaluate the impact of windowing functions on each band measurement error in order to potentially mitigate this loss of precision.To assess the quality of the propoposed scheme’s spectral measurement precision, we compare it to a known reference: the Matlab entation . This toiid. Gaussian noise sequences.To provide relevant statistics, these quantities are estimated with data from the 4500 audio recordings of the UrbanSound8k dataset  describeTo ensure that the proposed scheme allows the recognition of events using state-of-the-art methods, we consider the results achieved by several recognition systems on the UrbanSound8k dataset . It featThe aim of this experiment is two-fold: to evaluate the global loss of information induced by the coding process, and to evaluate the adequacy of third-octave bands indicators for classification. As studying the best performing classical models , deep leC and RBF kernel variance The four classification models are as follow: a support vector machine with a radial basis function kernel, a random forest classifier with 500 trees, a decision tree and a k-nearest neighbors classifier with thors of , that israstamat library [Mel spectrograms are also computed with the  library  to assesIt is important that the proposed scheme ensures a high level of recognition of acoustic events but, as the data are transmitted over the network and potentially stored, the level of intelligibility of speech utterances potentially captured in the decoded stream should be as low as possible. Thus, intelligibility in decoded and reconstructed audio is also an important concern of this study.The use of an audio recording as an evidence is considered by the forensic phonetics  field. TTo decrease the intelligibility, several approaches can be considered. First, a speech versus non speech detector can be implemented on the sensor. If some speech is detected, the data are not transmitted. This approach is however prone to failure of the detector and will lead to unavailability of data during speech time periods, which might compromise the relevance of some indicators.A second approach is to wisely choose the frame rate. Since a phoneme is about 100 ms to 200 ms long ,52, a frThus, the impact of the frame rate parameter of the proposed encoding scheme on intelligibility is evaluated. To do so, a perceptual test is conducted. For the evaluation, a dataset of clean speech utterances recorded in studio conditions is used. The dataset is composed of nine french sentences enunciated by three male and three female speakers. The sentences have a mean duration of 2 s and are composed of 5–12 words, averaging eight words. The 54 extracts are encoded using the proposed approach with four analysis frame rate parameters of, respectively, 50 Hz, 16 Hz, 8 Hz and 4 Hz leading to 216 audio excerpts being tested in total. However, as the recording conditions are the same for all extracts the speaker identity is considered as a source of variability rather than as a necessary factor in the test statistics. As a result, the objective is primarily to evaluate the nine sentences with four encoding frame rates, i.e., 36 parameters.Several subjective intelligibility metrics are standardized in the literature such as the system proposed in . HoweverBeyerdynamics DT 770 headphones. The output level was set by the experimenter at the same level for all subjects. The mean duration of the test was about 8 min.Twelve subjects of age ranging from 17 to 60 which reported normal hearing participated to the listening test. The test was conducted using a Matlab interface displayed with a desktop computer and audio was played through This test requires an implementation of the inverse operation of the coding process to provide the listener with an estimate of the time-domain signal. To do so, a linearly-scaled spectrogram from the band-focused representations is estimated. This estimation is achieved by multiplying the spectral representation by the scaled transpose of the forward transformation matrix. A loss of resolution increasing with frequency is induced due to the shape of the transformation, as illustrated by q, the number of bands and the effect of reducing time-resolution by averaging analysis frames. q. To match third-octave bands computation principle where a 125 ms (fast) or 1 s (slow) analysis is standardized, Mel frames are averaged over time. Because we use the most common parameters, namely 23.2 ms window with 50% overlap, the closest achievable rate considering simple averaging is 7.74 frames per second. Third-octave representation on 31 bands yields an overall higher size than their Mel equivalent, here estimated for 30 bands. It however compares with the 40-Mel bands representation which is the most used in sound event recognition literature. This higher bitrate is likely due to the distribution observed by the data prior to Huffman encoding.The main indicator of performance is the bitrate obtained at the output of the coder. The three varying factors studied are the data word size q can be approximated as a linear function of the representation dimensions for one second of analysis. Small variations are induced by data distributions on a per-frame level and their impact on the Huffman algorithm.A second set of parameters influences directly the time-frequency resolution of the analysis. By choosing a frame rate and number of bands, one can effectively control the size of the periodically transmitted data. We evaluate the bitrate for 10 to 40 Mel bands and a frame rate from 2 to 10 per second, with fixed This experiment aims at an initial assessment of potential tradeoffs between bitrate and preservation of valuable information which will be further discussed in The measurement error is now computed for third-octave bands. Results are displayed in When performing a short time analysis, strong errors appear in low frequency bands where the precision of the DFT is poor. The slow analysis yields better estimations as it provides a globally better resolution and thus also reduces the impact of spectral leakage effects in this region. When considering white noise the error is low on the whole frequency range. Its mean over the testing samples is close to zero and its standard deviation increases in low frequencies, confirming the above-mentioned considerations. This effectiveness does not translate well to environmental sound analysis, most likely due to the sound level disparities absent in the former case but omnipresent in the latter. Spectral leakage induces a correlation between close frequency components. In lower frequencies, large differences between adjacent frequency bins can therefore cause important errors on the third-octave bands computation. This issue is however not specific to Fourier transform-based schemes as it is also encountered with a time domain filtering approach.To mitigate this phenomenon, the choice of the window function shall be studied further. For a fast analysis with no overlap, the rectangular window seems a reasonable choice at first because of its energy conservation qualities. While it yields the lowest error in high frequency bands, its important spectral leakage effect makes it unprecise in lower frequency regions. Non-flat windows better account for this issue but require assuming that the signal is stationary in a given frame. The use of overlap then results in better estimates at the cost of an increased data size. For slow measurements, considering the rectangular window is less harmful to band analysis due to an increased frequency resolution.t-test  are considered. Gun shot class with 88.2% for third-octave cepstra and 86.6% for Mel cepstra. Their poorest accuracy is on the Air conditioning class with 32.0% and 38.1% respectively. However, a noticeable difference between them is that on the log-frequency scale the bandwidth of Mel filters narrows as frequency increases, while third-octave are evenly distributed. The effect of this can be seen between classes Drilling and Jackhammer. These sounds involve important low-frequency information which can generally differentiate them, leading third-octave descriptors to perform better. Conversely, using Mel-based cepstra improves globally Air conditioning recognition as most of its defining components are situated in higher frequencies.To further analyze both representations advantages, the confusion matrix is a reliable tool. It aims at providing information regarding class-by-class accuracy and misclassification rates. We thus compute these metrics for the SVM classifier, with predictions accumulated over the ten folds in test configuration. The analogous designs of the two descriptors is highlighted by close one-versus-one differentiation performances, with a slightly lower accuracy for third-octave bands on average. Both representations yield best results for the Both descriptor are thus found to have similar representational capabilities despite minor differences due to their respective designs.https://felixgontier.github.io/cense-coder/) then evaluates the impact of analysis frame rate on intelligibility using the average intelligibility score (AIS) given by the subjects and the intelligibility ratio (IR) computed as the number of correctly transcribed words versus the number of words in the spoken utterance. Given the test conditions presented in The perceptual test , and thus:Efficiency: Using the high precision parameters, the bitrate is about 1.4 kbps and 0.4 kbps for fast and slow modes respectively .Privacy: At all operating modes, the reverted audio signal is found to be inintelligible according to a perceputal test done using clean speech recorded at very low background level. Additionaly, the sensors being typically hanged at 4 m high in a usually very noisy environment, we believe that the intelligibility risk of the proposed approach is negligible .The encoding scheme is designed to be easy to implement and to lead to an efficient data format for storage and sharing across the research community. To encourage its use for other research projects, an open source Matlab and Python implementations of the coder are available.The proposed approach has the following benefits:This scheme will be implemented with a large-scale sensor grid as part of the CENSE project, where sensors are designed to be low-cost and energy efficient. The aim of the project is to create noise maps by linking standard acoustic measurements with novel perceptually motivated metrics. The presented coding scheme will enable a thorough study of the correlation between sound sources and context with pleasantness as perceived by the citizens to better understand the content of urban acoustic scenes and its perception by city dwellers.To do so, future work will focus on the use of such data encoder in a sensor grid approach as part of the CENSE project where its effectiveness will be assessed in field conditions. As far as the proposed encoding scheme is concerned, the usefulness of more sophisticated encoding paradigms should also be studied in order to further improve bitrate efficiency, as well as the effect of multiple channel coding and its interest in sensor grids applications.


Drosophila melanogaster.In nature, insects show impressive adaptation and learning capabilities. The proposed computational model takes inspiration from specific structures of the insect brain: after proposing key hypotheses on the direct involvement of the mushroom bodies (MBs) and on their neural organization, we developed a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is a nonlinear control system based on spiking neurons. MBs are modeled as a nonlinear recurrent spiking neural network (SNN) with novel characteristics, able to memorize time evolutions of key parameters of the neural motor controller, so that existing motor primitives can be improved. The adopted control scheme enables the structure to efficiently cope with goal-oriented behavioral motor tasks. Here, a six-legged structure, showing a steady-state exponentially stable locomotion pattern, is exposed to the need of learning new motor skills: moving through the environment, the structure is able to modulate motor commands and implements an obstacle climbing procedure. Experimental results on a simulated hexapod robot are reported; they are obtained in a dynamic simulation environment and the robot mimicks the structures of  Recent results and experiments performed on insects shed light on their highly developed learning and proto-cognitive capabilities enabling them to adapt extremely well to their natural environment . The mediolateral and the lateral antennal lobe tracts emerge from the antennal lobes as well, but bypass the calyces and project directly to the LH. The LH region controls inborn behavior, whereas the MBs are thought to be involved in learnt behavior. Analysing the interaction between the different neural structures we investigated the emergence of interesting neural activities responsible for specific behaviors in insects, including flies, like attention, expectation, delayed-match to sample tasks, and others  and proposed a computational model for non-elemental learning  proposed by Maass et al. . The infOne fundamental difference between the proposed model and the LSM is the presence of local connectivity among the neurons within the liquid layer. This element of our model deserves particular attention: in fact, the structure configures as a locally connected recurrent neural network which is fairly similar to the Cellular Neural/Nonlinear Network (CNN) structure  is an excitatory center responsible for behavior activations on the basis of visual and mechanosensory inputs. The input signals are here processed through a series of substructures: the protocerebral bridge (PB), the fan-shaped body (FB), and the ellipsoid body (EB) . No information is available on the dynamics of these neurons and electrophysiological data are in short supply. On the other side powerful neurogenetic tools are available for the fruit fly which allow for precise manipulations of the nervous system in order to address links among specific neural substrates, their functions and specific behaviors they are responsible for.Drosophila melanogaster has revealed multiple memory types and phases and recent investigations underlined that not all memory processes occur in MB neurons  structure, as are the MBs . The connectivity percentage used in this work is 15% from the input layer to the KC layer.The hidden layer is a SNN , where each unit is an Izhikevich Class I spiking neuron  and postsynaptic (j) neurons:The fraction of inhibitory neurons in the pool is about 10%. The connections within the lattice are represented by a synaptic weight with a random uniform distribution in the range (0.5–1.5), the input weights are equal to 1. The weights of the read-out map are subject to training. The generation of the inter-layer synaptic connectivity depends on a probabilistic function of the distance whereandCi, j, reported in the previous table, have been chosen according to Maass et al.  was randomly chosen among the values τ = 5, 10, 30, and 50 ms. This variability improves the dynamics potentially shown by the network as will be discussed in the following sections. The values of the synaptic time constant have been chosen to obtain significant dynamics in the simulation time window that is limited to 150 ms.dt = 1.5 ms.The output layer consists of a series of output neurons, modeled with a linear transfer function and fully connected with the hidden lattice. The output weights are randomly initialized in the interval  and are subject to learning. The integration step used for the reported simulations was fixed to Zi, j(t) is the synaptic output of the neuron  at time t and E(t) is the error between the network output neuron and the desired target. Another possibility consists of cumulating the weight variations during the simulation time window, to finally apply the cumulative result during the last simulation step.The time evolution of the target signals that the network need to memorize is generated by shaping the lattice dynamics using read-out maps. An incremental learning rule based on the Least mean square algorithm is adopted to update the synaptic weights of each read-out map. The learning process, resembling the classical delta rule, depends on the lattice activity and on the error between the current output and the desired target. The updating rule of the synaptic weights is here reported:The analysed motor learning process consists of adopting a series of perturbations on specific leg control parameters to reach a success in the assigned task. To apply a smooth perturbation, we adopted as target signal, a cosinusoidal function, whose final value corresponds to the parameter to be applied. In the following simulations we adopted a lattice with 8 x 8 neurons that is a good compromise to obtain a considerable variety of internal dynamics. The learning process needs a series of iterations  to successfully store the information in the read-out maps. In the following analysis we considered 100 epochs with a learning rate η = 0.5. During each epoch the network is simulated for 100 integration steps. A typical activity of the neural lattice is shown in Figure Iin = 5 and 30μA), were learned. During the testing phase, besides the two inputs already used in the learning phase, also other input currents were provided obtaining plausible behaviors that interpolate the dynamics of the two learned target signals.The network allows to interpolate the information acquired during learning as illustrated in Figure Figure The insect brain can be considered as a parallel computing architecture where reflexive paths serve the basic needs for survival, whereas learned paths allow the formation of more complex behaviors.yi = tanh(xi) and the parameters for each cell: μ = 0.23, ε = 0, s1 = s2 = 1, i1 = i2 = 0 generate a stable limit cycle , as follows:j which are nearest neighbor to the neuron i; n is the total number of cells; f represents the reactive dynamics of the i-th uncoupled neurons as reported in Equation (7) and k is the strength of the connections. The sum of terms performs diffusion on adjacent cells and induces phase-locking as a function of rotational matrices  are Heaviside functions and are used to distinguish, within the limit cycle, between the stance and swing phases: this allows to associate suitable modulation parameters to each part of the cycle, depending on the morphology of the leg. The signals are finally merged to generate the position control command for the coxa, femur and tibia joints. A detailed discussion on the CPG structure and behaviors is reported in a previous study  has widely been accepted as being the core unit for locomotion control but its fine-tuning is usually achieved by sensory information. The approach proposed here considers the task of motor learning as that of finding a suitable way for modifying the basic motor trajectories on the single leg joints so as to improve motor-skills in the light of novel conditions imposed by the environment. Using a control approach, we can realize motor-skill learning through a hierarchical adaptive controller, where, when facing novel conditions, some parameters controlling the leg joint trajectories are modulated. These modulations, shaped by the kinematic constrains, realize novel leg trajectories which are then applied to assess their suitability for the task. Once the former locomotion conditions are restored, these modulations are withdrawn and the baseline stable locomotor activity re-emerges. Sets of successful parametric values are retained, so that they can be re-applied whenever similar conditions should be encountered again. The locomotion controller is made up of basically two networks: one is devoted to generate a stable phase displacement among the legs; the other is shaped on the specific kinematic structure of each leg and constituted by several motor neuron structures, as illustrated in Figure The overall network stability was theoretically proven exploiting tools from partial contraction theory on a network made of nonlinear oscillators with Laplacian couplings. As demonstrated in previous studies, the network for gait control has a diffusive, undirected tree-graph configuration, which guarantees asymptotic phase stability independently of any imposed locomotion pattern  and a total of ten read-out maps, one for each parameter to be learned for a specific leg joint. The SNN receives as input a normalized value related to the step height and the lattice dynamics generates a spatio-temporal spiking activity that is transformed in a continuous, non spiking signal, through the output synapses that converge on the output neurons, one for each parameter that is subject to learning.Drosophila body length as 3.2 mm and the average height of the center of mass as to be located at about 1 mm above the ground during forward walking.A series of experiments were performed using a step that is insurmountable unless a gait adaptation is introduced: the height of the step is around 0.9 mm, whereby we chose the simulated The joint angular positions caused by the parameter adaptation in the anterior legs are shown in Figure In the dynamic simulation herewith reported, we adopted an integration time dt = 0.01 s, a stepping cycle of about 1.5 s: these conditions, the parameters reach the steady state within [20–60] integration steps. Looking at the learning process, the RFG generates the new parameters to be tested for the first phase. If the trial is successful the robot is re-placed to the starting position to perform a test: this assures the robustness of this new set of parameters. If the robot succeeds, it can proceed to the second phase, otherwise the parameters are discarded and the first phase is repeated. The trial ends when the robot overcomes the last phase or after a given number of attempts . If this time-out occurs, the parameters just used for the phases are discarded because they are not globally suitable for a complete climbing behavior.In Figure To evaluate the interpolation capabilities of the network we also performed a series of learning sessions with higher obstacles  and subsequently we tested the robot with a step height never provided during learning i.e., 1.2 mm). The best-adapted parameters obtained for the two learned step heights are reported in Figure  mm. The To evaluate the generalization capability of the control system, the previously learned system was tested in a different scenario where a stair-like obstacle was introduced. The robot followed the same climbing procedure as described above, repetitively applied for the three stair steps encountered on its path with height 1.3, 1.1, and 0.9 mm, respectively. The detection of each obstacle produces an effect at the motor level on the basis of the parameter adaptation mechanism induced by the SNN. Figure The results obtained were achieved relying only on the adaptive capabilities of the legs acquired during the learning phase. The body structure was considered rigid as in the fruit fly case. Including in the robotic structure active body joints (Dasgupta et al., In this paper a bio-inspired, embodied, closed-loop neural controller has been designed and implemented in a simulated hexapod robot that is requested to improve its motor-skills to face unknown environments. Taking inspiration from the insect brain and in particular from the fruit fly, the following hypotheses were formulated: relevant role of MB neuropiles in the motor learning task; direct transfer of the important role of transient dynamics in the olfactory leaning from the locust to the fly brain and further extension to motor learning; design of a neuro-computational model based on a LSM-like structure for the implementation of obstacle climbing in a simulated hexapod robot.In details, a computational model for motor-skill learning was developed and realized in a dynamic simulation environment. Inspired by behavioral experimental campaigns of motor learning in real insects, the computational structure consisted in a randomly connected SNN that generates a multitude of nonlinear responses after the presentation of time dependent input signals. By linearly combining the output from the lattice neurons with a weighted function, a reward-based strategy allows to learn the desired target by tuning the weights of a readout map. Looking at MBs in insects, the idea of a pool of neurons enrolled to solve different tasks depending on the specific requested output is next to the concept of Neural Reuse which has a number of biological evidences. The reported results demonstrate that the system can learn, through a reward-driven mechanism, the time evolution of several independent parameters related to the leg movements, to improve the robot climbing capabilities when exposed to the step-climbing task. The robot was also able to deal with step heights never presented before, exploiting the interpolation abilities of the proposed network.All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In this paper, we propose a novel hierarchical framework that combines motion and feature information to implement infrared-visible video registration on nearly planar scenes. In contrast to previous approaches, which involve the direct use of feature matching to find the global homography, the framework adds coarse registration based on the motion vectors of targets to estimate scale and rotation prior to matching. In precise registration based on keypoint matching, the scale and rotation are used in re-location to eliminate their impact on targets and keypoints. To strictly match the keypoints, first, we improve the quality of keypoint matching by using normalized location descriptors and descriptors generated by the histogram of edge orientation. Second, we remove most mismatches by counting the matching directions of correspondences. We tested our framework on a public dataset, where our proposed framework outperformed two recently-proposed state-of-the-art global registration methods in almost all tested videos. With the development of sensors, multi-sensor image fusion has attracted a considerable amount of research interest in recent years. Particular attention has been devoted to infrared-visible sensor fusion ,2,3, whiHowever, it is challenging to find correspondences in infrared-visible images for registration because they reflect different phenomena . InfrareTo solve the above problem, we propose, in this study, a novel automatic registration framework based on curvature scale space (CSS) keypoints  for infrWe propose a new registration framework based on CSS keypoints that improves the accuracy of global homography by combining feature and motion information.We propose a simple method to calculate the motion vectors of targets in coarse registration that transforms the scale and rotation estimation into an easy, homologous keypoint-matching problem.We calculate the normalized location (NL) descriptors and the histogram of edge orientation (HOE) descriptors to strictly match keypoints. Moreover, we count the matching directions of correspondences to eliminate mismatches.We use a reservoir where correspondences that are identified as outliers based on the HOE matching metric are randomly replaced. Compared to the reservoirs proposed in ,14, oursOur contributions in this paper are summarized as follows:The rest of this paper is organized as follows: In the domain of image registration, various methods have been studied to reduce computation time  and imprIn intensity-based methods, image region correlation  or mutuaFeature-based methods involve the extraction of a variety of features for registration, such as points, boundaries and so on. Points are the simplest and most universal feature ,22, and For video pairs with moving objects, motion information is provided in addition to intensity and feature information. Hence, methods based on motion information have been discussed ,12,27,28Our proposed method is related to the work in ,14, whicThe locations of the targets between infrared and visible videos are affected by all parameters in a transformation matrix. However, the motion vectors of the targets are not influenced by translations, regardless of the type of matrix. Suppose that at the moment For an affine matrix with scale By obtaining the difference between the target’s positions at different times, the relationship between the motion vectors of targets According to Equation (2), we find that once we obtain a pair of motion vectors of the targets, the scale and rotation can be calculated. Inspired by this idea, we build a hierarchical registration framework where we first calculate the motion vectors of the targets, which is crucial to find an accurate global homography. Even though we adopt an affine matrix with four parameters, our framework is applicable to any 2D homography. When using other matrices, we only need to take advantage of different numbers of motion vectors of the targets in the framework.For a given video pair, keypoints need to be extracted from each image. Foreground detection is first performed using the algorithm proposed in , which sTo estimate scale and rotation for the entire video pair, we propose a simple method to calculate the motion vectors of targets. It is based on matching homologous keypoints in adjacent frames, as described below.Not all adjacent frames are useful for calculating the motion vectors of targets. Hence, we select appropriate adjacent frames using two conditions: (1) For each image in the infrared and corresponding visible adjacent frames, Homologous images reflect the same phenomena of the observed scene. Thus, we adopt HOG  to descrFor the selected adjacent frames, the interframe motion vectors of the targets are obtained based on homologous correspondences. Algorithm 1 shows the steps of calculating the interframe motion vector of the target composed of two loops. In the outer loop, we calculate the motion vector of a correspondence with:If error Algorithm 1. Interframe Motion Vector of Target CalculationRepeattimes . The Euclidean distance errors between the transformed infrared interframe motion vectors and their corresponding visible vectors are then calculated. When the error of a pair of interframe motion vectors is smaller than the threshold T (T = 2), this pair is viewed as an inlier. The scale and rotation with the most inliers are the results of coarse registration.For an infrared or visible video, we obtain multiple interframe motion vectors of the targets. To reduce the influence of false motion vectors, the RANSAC algorithm  is used Since directly matching infrared and visible CSS keypoints yields poor quality, we propose a novel strategy for keypoint matching, as described below.on HOE, ,31,32). ,32. E: IWe re-locate the infrared targets (foregrounds) and keypoints to eliminate the influence of scale and rotation. The targets are first transformed (bilinear interpolation) using the scale and rotation obtained in coarse registration. ith component of an infrared and a visible HOE descriptor, respectively.Having described all infrared and visible keypoints, we need to define some metrics for the matching process:During the matching process, we first consider the normalized Euclidean distance There are a few mismatches in the matched keypoint pairs. For instance, some infrared keypoints are matched to the same one keypoint in the visible image. This situation may occur due to the lack of an obvious difference between an infrared or a visible HOE descriptor and others. Therefore, we need a mechanism to remove mismatches.We define the matching direction of a match as:Algorithm 2. Mismatch Elimination Based on Matching Direction1. Calculate the matching direction of each match.2. Encode every match using its matching direction.3. For every code, count the number of matches with this code to create the histogram of matching direction.4. Find the maximum value of histogram 5. If As introduced in Algorithm 2, we first calculate the matching directions of all matches according to Equation (11). Then, the code of every match is determined by:If we only use matches from a single frame pair for registration, it is not possible to find an accurate global homography, especially when the observed scene is large and does not follow the planar ground assumption. To solve this problem, we can save matches from different frames in a reservoir. However, previously-proposed reservoirs have some certain disadvantages. In , a FIFO For a given reservoir lgorithm .Our scene of interest does not always comply with the planar ground assumption; thus, the goal of our method is to find a best global homography to ensure accuracy of registration, not only for the targets of interest in the given frame, but also those in the entire video pair, even if non-planar registration is involved. To achieve this goal, we use the given global homography to update the best global homography according to the method of homography smoothing described in . The totIn this section, we describe tests on the proposed framework using several nearly planar scenes. The LITIV dataset provided by Torabi  was emplWe compared our framework with two state-of-the-art global registration methods, both of which are based on keypoint matching. The first one directly uses shape contours and a reservoir based on a voting scheme , and thThe parameters used by all methods mainly contain e one in , Cmax=10 used in  can saveTo quantify the performance of these methods, we first needed the binary polygons sets. The construction method was proposed in : for an moothing . It was How our framework performs in the first four video pairs of the studied dataset is shown in We can see that a transformation is found soon after a target first becomes visible in both the infrared and the visible videos (this happens at different moments in each video pair; the earliest results are shown in In our experiments, the overlap error was used to assess our method. To reflect the global performance of our method, we drew error-to-time curves for our method and compared them with those of the other two methods ,14, as sWe can find that our method reaches lower overlap errors at faster convergence speeds than , and staThen, we discuss the comparison results between our method and . For LITOur method succeeds in excelling ground truth homography in all but LITIV-2 and LITIV-3. It is possible and desirable because the ground truth is not perfect. It was found manually because there is a margin of error. Furthermore, the ground truth provides an ideal transformation only for a planar scene, but the binary polygons found on the targets of interest do not fully follow the planar ground assumption. Hence, methods that aim to register these targets can obtain lower errors.As shown in We adopted the average overlap errors to summarize the results, which can intuitively represent the overall capacity of a method. As shown in When operating directly on the foregrounds provided by the target detection algorithm , the aveIn this paper, we presented a hierarchical framework that combines motion and feature information relying on CSS keypoints to register thermal-visible videos. In the framework, we used the motion vectors of the targets to approximate scale and rotation in coarse registration step. Based on the results, a strict strategy of keypoint matching was proposed to accurately calculate the global transformation matrix in a precise registration step. A reservoir updated based on the difference of HOE also allowed our method yield better results. The results of an experiment showed that our method outperformed two recent state-of-the-art global registration methods in almost all tested video pairs. Moreover, it managed to manually align binary polygon sets based on scene structures, the results of which were preferable to the ground truth homography in a majority of sequences.


The graphene oxide (GO) is successfully prepared from a purified natural graphite through a pressurized oxidation method. We experimentally demonstrate that GO as an optical media can be used for spatial light modulation based on plasma channels induced by femtosecond pulses. The modulated beam exhibits good propagation properties in free space. It is easy to realize the spatial modulation on the probe beam at a high concentration of GO dispersion solutions, high power and smaller pulse width of the pump beam. We also find that the spatial modulation on the probe beam can be conveniently adjusted through the power and pulse width of pump lasers, dispersion solution concentration. Graphene, a two-dimensional carbon nanomaterial composed of carbon atoms, has a thickness of single atomic layer, the lateral size can reach to microns or even to millimeters. The graphene is characterized by high charge mobility, high thermal conductivity, high intensity, 2.3% visible light absorption and room-temperature quantum Hall effect. In the last few years, graphenes and GO materials have received enormous interest from the scientific community due to their extraordinary mechanical ,2, electOptical modulation is a technology for manipulating optical signals in amplitude, phase or polarization, which are widely used in photonic circuits ,18, optiIn this work, we demonstrate a novel method for spatial light modulation based on plasma channels generated in the GO dispersion solution. This is a new application of GO. Firstly, we have successfully synthesized GO from a purified natural graphite through a pressurized oxidation method. The morphology and structure of GO are detailedly characterized by transmission electron microscope, optical microscope, atomic force microscope and Raman spectrometer. Then, we experimentally show the spatial light modulation on the probe beam based on plasma channels generated in the GO dispersion solution. We also analyze some influence factors on the spatial modulation, such as, concentration of GO dispersion solution, power and pulse-width of pump lasers. Finally, we study the propagation characters of modulated beam in the free space.In 2004, Geim and Novoselov observed single-layer graphene by the method of microcleaving, in which the single-layer graphene has been peeled off from highly oriented pyrolytic graphite layer after layer using scotch tape. However, due to the defects of low production rate and high randomness, the preparing method of microcleaving is not conducive to practical application and scientific research. In addition to the use of microcleaving method, the preparation of graphenes also includes SiC epitaxial growth, chemical vapor deposition (CVD) and others. The SiC epitaxial method is to remove carbon atoms from monocrystal SiC to reconstruct graphene by high temperature heating in ultrahigh vacuum. Large-area and high-quality graphene of good compatibility in integrated circuit technology can be achieved by SiC epitaxial method. Chemical vapor deposition (CVD) is a process that inflates the high-temperature furnace with atmosphere of high carbon content so that the carbon atoms resolve from the gas and grow into graphene on the metal substrate materials. The controllable growth of graphene can be achieved by controlling the parameters such as substrate type, growth temperature, gas species, flow rate and so on.Chemical oxidation reduction method shows a unique advantage while the g order of graphene materials are required. In the chemical oxidation reduction method, graphite intercalation compound is obtained at first from graphite as raw material using strong acid treatment in solution, and then graphene is stripped out after oxygen-containing functional group take shape on the surface of graphene while strong oxidant is added in the solution. Large-scale production can be achieved as a result of the cheap raw materials and simple preparation process in this method.3 to oxidize graphite in fuming nitric acid. This method was improved in 1898 by Staudenmaier, who introduced concentrated sulfuric acid into fuming nitric acid and washed GO by hydrochloric acid and water. The improvement of the experimental process makes the oxidation of GO more fully. So far, the experimental scheme proposed by Hummers in 1958 has been in the most commonly use. In the scheme, graphite is oxidized by potassium permanganate and sodium nitrate in concentrated sulfuric acid, then the residual oxidant is reduced by hydrogen peroxide, and finally the GO is achieved through the treatments of filtration, washing and vacuum dewatering. Tour improved the method of Hummers in the year of 2010. In the solution of concentrated sulfuric acid H2SO4 and phosphoric acid H3PO4, potassium permanganate is used as oxidant to oxidize graphite, and then hydrogen peroxide is used to restore the residual oxidant. Compared with the Hummers’ method, the improved method has the following advantages: the reaction process does not release a large amount of heat, the reaction process does not produce toxic or explosive gases, and the reaction products are more fully oxidized. In this paper, GO materials are prepared by the improved method.In 1859, Brodie proposed that GO can be produced by using oxidizing agent KClO4. Then the mixture is heated to 50 °C on the electric heating magnetic stirrer after mixing evenly, and is kept at this temperature for 12 h under stir. The reaction product is cooled to room temperature and then added to the mixed solution of 100 mL ice water and 1 mL 30% H2O2. The product is sifted by a metal sieve of 300 μm pore and then is filtered by polyester fiber filter membrane. The filtrate is centrifuged and washed with water, HCl and ethanol, respectively. After filtration and washing, the product is dried in a vacuum oven for 12 h.Graphite flakes coming from Sigma-Aldrich  is used as starting material. Firstly, 90 mL concentrated sulfuric acid and 10 mL phosphoric acid are added to the mixture including 1 g of graphite flakes and 5 g of KMnOTransmission electron microscopy (TEM) images are obtained on a Tecnai G2 F20 S-TWIN microscope  with an accelerating voltage of 200 kV. Atomic force microscope (AFM) measurements are carried out in a Bruker Multimode 8 system . Raman spectra are obtained by a Witec alpha300R Confocal Raman system  with the excitation laser of 532 nm in air ambient environment. An optical image is obtained to observe the morphology of the GO by Leica 2700 M optical microscope .−1, which originates from the breathing vibration of sp2 atoms in the carbon ring and belongs to the A1g symmetry mode. Usually the D peak is forbidden, and its intensity in graphite powders is very weak. However, due to the presence of surface disorder, especially the defects, the symmetry of the GO is broken, so that the vibration is permitted. Another peak is the G peak at 1580 cm−1. The G peak with the symmetry of E2g originates from the first order Raman scattering process. In addition to the D peak and G peak, there is still a 2D peak at the frequency of 2680 cm−1. However, because of a large number of defects on the surface, the 2D peak cannot be observed in GO.Raman spectroscopy has been widely used in the characterization of two-dimensional nanomaterials. For graphene, the Raman signal will change significantly with the alteration of the number of layers. Then, informations of graphene species, number of layers and others can be determined by observing the change of Raman signals. The dispersion of GO is added to the silicon wafer with 200 nm silicon oxide on the surface, and then the Raman spectrum is measured after vacuum drying. Confocal Raman spectrometer of Witec alpha 300R with optical fiber laser of 532 nm wavelength is used to test the Raman spectra of GO. In order to avoid the damage of the graphene, the laser energy is below 1 mW. It can be observed from y = 0) are shown in Pfs) is 0 mW, the probe beam keeps its initial spatial intensity distribution. Increasing the power to 6 mW, it is easy to see from Pfs is above the ionization threshold. Plasma channels will persist during the experimental session because of femtosecond pulses sequences. Electron density and refractive index distributions in the generated plasma channel are close to Gaussian because of a Gaussian intensity profile of the pump beam. Lasers can only propagate in the plasma where the electron density is below the critical value. The probe beam cannot pass through the center region of plasma channels because of a high electron density of the plasma. According to the Fermat principle, the probe beam is focused when it passing through the periphery of plasma, while the plasma center is defocusing. Similar to a beam passing through a graded-index diverging lens, the probe beam is deflected when it propagates in the periphery of the plasma. The probe beam cannot pass through the center plasma; hence, a circular dark spot at the center region of the probe beam is formed. We only experimentally display the Gaussian distribution of the pump laser intensity, but our method has general character and other non-Gaussian conditions can also be analyzed by this method. If the spatial profile of pump beam can be adjusted conveniently, it is expected that the probe beam is modulated into a beam with any spatial distribution.Pfs continuously (8 mW to 60 mW), the spatial intensity of probe beams at the central zone always decreases and the dark spot size increases. In other words, the modulated area of the probe beam enlarger gradually as Pfs increases. If we continue to increase Pfs, it is expected that the spatial intensity at the center zone reduce to zero and probe beam is modulated into a ring-shaped beam. We can explain the reason as follows. The region in the plasma where probe beams can pass through . DSS is defined as the FWHM of the radial-intensity distribution inside the notch of the modulated beam. Simlar to Pfs increase. Namely, spatial modulation on the probe beam is gradually enhanced as Pfs increase. To generate a same spatial modulation (a same DSS) on the probe beam, the power required in high concentration GO dispersion solutions is lower than that of in low concentration dispersion solutions. For example, an modulated beam with DSS = 0.9 mm will be produced in the dispersion solution at a concentration of 2.5 mg/mL when Pfs is 15 mW, while the power is 46 mW when the concentration is decreased to 625 μg/mL. From a simple physical standpoint, we understand the phenomenon as follows. When pump pulses propagate in a GO dispersion solution, nonlinear effect is enhanced as concentration increases, it is more easily and sensitive to generate a plasma channel. The power required for the generation of a same plasma channel in the low concentration solution is higher than that of in a high concentration solution. So, in order to achieve a same spatial modulation, the needed power is inversely proportional to the concentration of GO dispersion solutions. That is to say, it is easily to obtain a more prominent spatial modulation in the high concentration GO dispersion solution. Pfs and DSS of modulated beam under three pulse-widths of pump lasers. From Then we quantitatively analyze relationships among degree of modulation and dispersion solutions concentration, pulse width of pump lasers, and they are shown in Pfs is 30 mW. The propagation distance D is defined as the length between the glass cuvette and CCD camera. Because the size of modulated beam is beyond the sensing area of CCD when the distance is 500 cm, so we use a digital camera to capture the image of the modulated beam. In the following, we study the propagation of the modulated beam in free space. CCD camera is set to move along the optical axis and then we capture a series of spatial intensity maps of modulated beams. To further quantitatively investigate the divergence of the modulated beam in the free space, initial probe beams are firstly set to pass through air, water and three types of GO dispersion solutions . Their beam widths at different propagation distance are displayed in Pfs, pulse widths of the pump lasers, concentrations of dispersion solutions. Specifically, Pfs is 30 mW (pulse-wdth ~ 126 fs). Results depicted in Pfs, pulse widths of pump lasers are nearly the same. They are the same as depicted in In conclusion, we successfully synthesize and characterize GO, due to the large amount of functional groups on the surface, the GO is hydrophilic so that it can be dispersed in water, and the thickness of fewer layer oxide graphene has been increased to 1 nm. Then, we experimentally demonstrate the spatial light modulation on the probe beam based on plasma channels generated in the GO dispersion solution. In additional, the propagation of modulated beams in the free space is studied. It finds that the modulated beam keeps its initial beam spatial profile almost invariant and exhibits excellent propagation properties. The divergence of modulated beams is not relevant to power and pulse-width of pump lasers, the concentration of GO dispersion solutions. We can easily control the spatial modulation on the probe beam by adjusting power and pulse-width of pump lasers, dispersion solution concentration.


With the decline in funding for Viet Nam’s response to the HIV epidemic, there is a need for evidence on the criteria to guide the prioritization of HIV programs. There is a gap in the research on the relative importance of multiple criteria for prioritizing a package of interventions. This study elicits preferences and the trade-offs made between different HIV programs by relevant stakeholders and decision-makers in Viet Nam. It also pays attention to how differences in social and professional characteristics of stakeholders and their agency affiliations shape preferences for HIV program criteria in Viet Nam.This study uses self-explicated ranking and discrete choice experiments to determine the relative importance of five criteria - effectiveness, feasibility, cost-effectiveness, rate of investment and prevention/treatment investment ratio - to stakeholders when they evaluate and select hypothetical HIV programs. The study includes 69 participants from government, civil society, and international development partners.Results of the discrete choice experiment show that overall the feasibility criterion is ranked highest in importance to the participants when choosing a hypothetical HIV program, followed by sustainability, treatment to prevention spending ratio, and effectiveness. The participant’s work in management, programming, or decision-making has a significant effect on the importance of some criteria to the participant. In the self-explicated ranking effectiveness is the most important criterion and the cost-effectiveness criterion ranks low in importance across all groups.This study has shown that the preferred HIV program in Viet Nam is feasible, front-loaded for sustainability, has a higher proportion of investment on prevention, saves more lives and prevents more infections. Similarities in government and civil society rankings of criteria can create common grounds for future policy dialogues between stakeholders. Innovative models of planning should be utilized to allow inputs of informed stakeholders at relevant stages of the HIV program planning process.The online version of this article (10.1186/s12913-017-2679-0) contains supplementary material, which is available to authorized users. The first case of HIV infection in Viet Nam was reported in December 1990 in Ho Chi Minh City. By December 2003, 76,180 infections were reported in Viet Nam and 6550 people had died of AIDS related causes [Viet Nam’s HIV epidemic is concentrated among three key population groups defined by risk behaviors and a high prevalence of HIV: people who inject drugs, men who have sex with men and female sex workers . The maiInternational donors have provided substantial support to Viet Nam’s HIV response. In 2005, The U.S. President’s Emergency Plan for AIDS Relief (PEPFAR), Asian Development Bank, World Bank, UK Department for International Development (DFID), The Global Fund to fight AIDS, Tuberculosis and Malaria (GFATM), and Australian Agency for International Development (AusAID) were financing a significant portion of the HIV programs . Viet NaGlobal shortfalls in funding for the HIV response make it unlikely that the withdrawal of international funding will slow down in Viet Nam. The 2016 report of the Kaiser Family Foundation (KFF) and UNAIDS indicated that donor funding to support the HIV response efforts in low- and middle-income countries, had declined for the first time in five years . “DonorsIn 2012, after a decade of financial support to Viet Nam’s HIV response, the World Bank and DFID ended their funding. Their recommendation for Viet Nam before exiting was to refocus the government funding of HIV prevention programs on provinces in the country based on epidemiological impact, infrastructure, and ability of communities to mobilize resources . In 2014Given the limited funding, there is a growing interest in generating evidence on the criteria to guide priority setting in the HIV response –20. A nuThis study elicits preferences and the trade-offs made between different HIV programs by relevant stakeholders and decision-makers in Viet Nam. In other words, given several criteria for deciding on a HIV program, how much of one criterion are they willing to give up for improvements in another criterion. We also pay attention to how differences in social and professional characteristics of stakeholders and their agency affiliations shape preferences for HIV program criteria in Viet Nam. This study is innovative in its use of discrete choice experiments (DCE) and self-explicated ranking to establish the relative importance of a set of criteria for prioritizing Viet Nam’s HIV response.DCE are based on well-tested theories that provide an explanation of choice behavior . These eThis study contributes to Viet Nam’s HIV policy-making by clarifying what criteria are being considered in prioritizing the programs in the National HIV response, and how different stakeholders view the importance of those criteria. Other countries can adopt this transparent and accountable process during their national HIV planning process and in prioritizing their HIV funding proposals to donors.This study used two methods to elicit stakeholders’ preferences for and choices of HIV programs. The first method was a straightforward self-explicated ranking of criteria. The second method used the DCE method to determine the relative importance of criteria to stakeholders when they evaluate and select HIV programs.DCE is a type of hypothetical experiment that is widely used in the health field to quantify preferences. The experiment imitates a situation when a stakeholder must make a choice between two or more options. Each option has the same set of attributes as the other option but the values of these attributes are varied to make the option different from the other. In this study, the DCE attributes are referred to as “criteria”, which is the common term used in priority setting and operations research. The variance of the criteria was fixed to two levels. To reduce the cognitive burden required by the respondents (stakeholders and decision-makers), the number of choice scenarios presented to them was minimized using orthogonal arrays. Each choice scenario contained two HIV programs. During the experiment, the choice scenarios were presented to the respondents consecutively, and the respondents were asked to take their time to select the HIV program they preferred most in each choice scenario.The most frequently used criteria identified in a systematic review of literature served as a basis for the DCE in this study . The fulAll criteria had dichotomous levels. These criteria levels were generated based on investment case scenarios developed for Viet Nam in 2014 . The invPrior to the DCE, the questionnaire presented an operational definition of each criterion, and asked respondents to manually rank the criteria according to the importance they attached to each of the criteria. This step allowed the comparison of self-explicated ranking with the DCE weighted ordering of the criteria. It also allowed a common understanding of the criteria by the participants prior to starting the DCE.5) possible profiles. A subset of those 32 profiles was chosen on the basis of a fractional experimental designs library of orthogonal arrays [To limit the number of combinations of scenarios and avoid information overload by participants in the DCE, criteria were limited to five with two levels each  respondents had to make while giving a reasonable estimation of the main effects.The survey that presented the DCE also collected information on the respondent’s social and professional characteristics. These data were used to assess how individual factors influence decision-maker’s stated preferences. The assessed characteristics included age, sex, nationality, professional experience, and engagement in decision-making in Viet Nam’s HIV response. The complete survey questionnaire in English and Vietnamese are provided in Additional files The DCE was conducted in Viet Nam, where the HIV response involves development partners, civil society, and the central and provincial state institutions. The study aimed to reach 60 participants who had been involved, or currently are involved, in the decision-making in Viet Nam’s HIV response, with similar number of respondents from government, international development partners, and civil society organizations respectively. The motivation behind selecting these three groups was that they encompass the actors who have a stake in the decision-making in the HIV response. These three groups are referenced by the Greater Involvement of People Living with HIV (GIPA) principle formalized at the 1994 Paris AIDS Summit , and areParticipants were identified in a two-stage selective sampling of individuals knowledgeable or responsible for decision-making. In the first stage, the researchers identified seed individuals in government, civil society, and development partners. Seed individuals are initial study participants who recruit their social or professional peers . In the The DCE was piloted with four participants. As a result of the pilot, the ordering of choice scenarios was revised to start with the simplest task (with two differences between the two profiles) to the most difficult task (with four differences between the two profiles). The choice scenarios were also formatted to be displayed horizontally, compared to the vertical presentation customary in DCE. This allowed the respondents to give equal attention to all criteria of the profile, and reduced the dominance of the criterion on top. Finally, where graphs were used to illustrate the meaning of criteria, footnotes were added to further clarify those graphs.The DCE survey was administered electronically on the LimeSurvey platform using a standardized questionnaire. The participant choices were coded 0 if the basic profile was selected as the preferred profile and coded 1 if the alternative profile was selected as the preferred profile.The data collected were inserted in Excel and cleaned of any inconsistent answers to the DCE scenarios. Two respondents provided a combination of responses that were categorized as inconsistent answers. Firstly, if a respondent selected a high feasibility program over a cost-effective program (choice scenario 2), then selected a program with constantly increasing costs and high proportion of spending on treatment over a cost-effective program (choice scenario 3), and then selected a low feasibility, low proportion of spending on treatment, and decreasing cost program which is highly cost-effective (choice scenario 4), that respondent’s answers were deemed inconsistent. Secondly, if a respondent selected an effective program over a program with decreasing costs (choice scenario 1), then selected a highly feasible program over a cost-effective program (choice scenario 2), and then selected a cost-effective and decreasing cost program over a feasible and effective program (choice scenario 7), that respondent’s answer were deemed inconsistent. The DCE results of the two respondents who provided inconsistent responses were removed from the data set.The cleaned dataset was imported into Stata for analysis. For the analysis of the DCE data, a binary logit regression with random intercepts was used. First, the main-effect model was estimated using the responses of all respondents. Then the responses were disaggregated by group membership – government, civil society, development partners – and the main effects model was estimated for each group, and the results were compared. Data from the self-explicated ranked criteria were analyzed using descriptive statistics, and ordered by the modes of the criteria ranks. The DCE results were compared to the self-explicated ordering of criteria in qualitative terms.p < .05).Social and professional characteristics may have an effect on the choices of stakeholders and decision-makers. Descriptive statistics were calculated for social and professional characteristics of the respondents. After estimating the main effects, interactions of the criteria with the social and professional characteristics of the respondents were added to the model. A backward stepwise regression procedure was conducted to obtain a reduced model consisting of statistically significant independent variables  agreed and completed the survey. Survey respondents include 31 (44%) females and 38 (56%) males. The majority of respondents (44%) are between 41 and 50 years old. The majority of respondents (76%) are Vietnamese nationals. There are nearly equal proportions of respondents from civil society, government, and development partners, with 20 (29%), 26 (38%), and 23 (33%) representatives respectively. Most respondents (91%) are involved in decision-making and more than one half (65%) are responsible for decision-making. Information on all social and professional characteristics is provided in Table The self-explicated ranking of the criteria based on all responses shows that effectiveness is the most important criterion for respondents with 43% of respondents ranking this criterion very high. Feasibility is the next highest ranked criterion followed by sustainability, cost-effectiveness and treatment to prevention spending ratio. When responses are disaggregated by agency, effectiveness remains the most important criterion and treatment to prevention spending ratio remains the least important criterion. Most civil society respondents (60%) and development partner respondents (48%) select effectiveness as their most important criterion, while government respondents are equally split on feasibility and effectiveness as their top criteria (27 and 27%). The results of the self-explicated ranking are presented in Table Results of the logit regression of the main effect model, after removing the inconsistent responses, are shown in Table Specifically, the reduced model with interactions shows that several interactions of criteria with social and professional characteristics of the respondents have a significant effect Table . The bacDCE analysis results by agency show that development partners, civil society, as well as government respondents all rank the feasibility criterion high. Sustainability, the ratio of treatment to prevention spending, and feasibility are in the top three criteria of both civil society and government respondents. Effectiveness is highly ranked by the development partners only. The coefficients of other criteria do not carry sufficient statistical weight to confidently say how they are ranked. Table All else being equal, participants prefer a program that is most feasible, front-loaded for sustainability, has a higher proportion of investment on prevention, saves more lives and prevents more infections, and is more cost-effective although this latter criterion does not show a statistically significant effect on the choices in the DCE.The self-explicated ranking of criteria finds the “effectiveness” criterion to be the highest ranked criterion by respondents. This is in keeping with previous studies in rating importance of criteria in Asia that also found effectiveness to be the most important criterion for prioritizing interventions in the HIV response , 25. A sAnother finding from the interaction results is the difference in ranking of criteria by respondents who have worked in management of HIV programs. Compared to the average response, those who worked in management rate prevention/treatment ratio lower and rate sustainability of programs higher. These results indicate some theoretical consideration in the decision-making of program managers based on financial models , giving The interaction terms also show that those responsible for decisions rate the feasibility and sustainability criteria lower than the average respondent. This is consistent with the traditional model of public service governance where decision-makers are concerned with the outcomes of the programs they choose, and feasibility and sustainability are considerations for actors at different levels of their hierarchical organization . ProgramFeasibility and sustainability are ranked highly both in the DCE as well as the self-explicated ranking. Although respondents from the civil society and government differ in the ordering of these two criteria in the DCE, their responses indicate that they agree the two criteria are the most important for prioritizing HIV programs. This result can be useful in the advocacy for greater involvement of the civil society in the priority setting process together with the government, since it brings to light that there are more points of agreement than differences between the two groups. While development partners agree with the government and civil society on the importance of the feasibility criterion, they consider the program effectiveness as their second most important criterion. Future priority setting processes may consider the level of importance of these criteria to different stakeholders, and develop program options that cater to their values. The transparency in options and weight of criteria according to different stakeholders will facilitate and focus discussions around trade-offs that need to be made and between whom.The coefficient for the cost-effectiveness criterion was not significant in the regression analysis. In other words, the difference between the preference weight of the more cost-effective program and the less cost-effective program was not statistically significant. There could be two reasons for this: either we are unable to estimate the coefficients efficiently with the model used , or there is too much heterogeneity in the preferences for the cost-effectiveness criterion. The cost-effectiveness criterion however ranks low in self-explicated rankings, across all groups. This seems surprising if we consider the extensive use of the criterion for prioritization in healthcare, and guidelines developed for cost-effectiveness analysis of healthcare programs , 50, 51.Between 2006 and 2010, the national HIV programs resulted in an estimated 401,600 fewer disease adjusted life years (DALY) at an estimated cost of $248 for each DALY averted . The DCEOverall, the DCE method is shown to be effective and feasible in establishing priorities in Viet Nam. It provides additional important information beyond what the self-explicated ranking of criteria provides, such as the comparative importance of one criterion against another. It also explains the direction of criteria that is preferred by the respondents. For example, whether they prefer greater prevention or greater treatment in the prevention/treatment ratio criterion. However, the DCE also requires a large number of respondents to make reliable estimates, which may not be feasible in countries with a small program and few people involved in decision making at the central level to respond to the questionnaire. With few respondents, the number of criteria to be considered may be limited, jeopardizing the validity of the results.This study has several strengths and limitations that need to be acknowledged. The strength of this study is in considering a broad set of criteria relevant to the country, and ranking them with experimental and self-explicated methods for improved accuracy and precision. Our study also involves multiple groups of stakeholders representing the different perspectives of those who should be involved in prioritizing Viet Nam’s HIV response. This study has fewer participants in the DCE than other similar studies. Although we tried to reach a maximum number of actors with experience or expertise in decision-making on HIV programs, the HIV space in Viet Nam is ultimately limited by the size of the epidemic and response. Given the limited number of potential participants, and the desire to minimize the cognitive load of the DCE, a limited number of criteria are considered for prioritization from the full set.This study occurs at a transition period in Viet Nam, as official development assistance to the HIV response is being reduced, and greater domestic investments including social health insurance are being mobilized to cover the gap left by the donors. The stakeholders’ ranking of the criteria for prioritizing HIV programs presented here may be a reflection of the current context in Viet Nam, which could change in the future.Findings of this study show that there are greater similarities between the ranking of criteria by government and civil society than there are differences. The process and results in elicitation of the importance of the criteria can inform future policy dialogues between the stakeholders to find common grounds in priority setting. The results also highlight the need to reconsider the classical hierarchical models of planning in Viet Nam, and utilize innovative models of planning that allow inputs of informed stakeholders at relevant stages of the HIV program planning process. The results may also be useful for other developing countries in a transition period to visit or revisit the criteria used to prioritize their HIV programs. In donor supported countries, the transparent process of eliciting criteria for HIV program prioritization can be an additional requirement for funding proposals that demonstrates wide stakeholder consultation, and evidence-based planning and prioritization.As Viet Nam moves closer to becoming an upper-middle-income country, and donors transition away from direct support of the HIV response, the importance of certain criteria for prioritizing the HIV program package will need to be re-evaluated. Cost-effectiveness is one criterion used prominently in the past investment case analysis of Viet Nam’s HIV response, but ranks lower in this study. Going forward, this criterion should again be considered centrally once programs transition from donor support to domestic financing, and standalone HIV programs integrate back into the general healthcare system, and evidence becomes available on the cost and effectiveness of this newly integrated program structure.Additional file 1:Contains the survey questionnaire in English. (DOCX 348 kb)Additional file 2:Contains the survey questionnaire in Vietnamese. (DOCX 481 kb)


We review a recently discovered developmental mechanism. Anterior-posterior positional information for the vertebrate trunk is generated by sequential interactions between a timer in the early nonorganizer mesoderm (NOM) and the Spemann organizer (SO). The timer is characterized by temporally collinear activation of a series of Hox genes in the early ventral and lateral mesoderm  of the Xenopus gastrula. This early Hox gene expression is transient, unless it is stabilized by signals from the SO. The NOM and the SO undergo timed interactions due to morphogenetic movements during gastrulation, which lead to the formation of an anterior-posterior axial pattern and stable Hox gene expression. When separated from each other, neither the NOM nor the SO is able to induce anterior-posterior pattern formation of the trunk. We present a model describing that the NOM acquires transiently stable hox codes and spatial collinearity, and that morphogenetic movements then continually bring new cells from the NOM within the range of SO signals that cause transfer of the mesodermal pattern to a stable pattern in neurectoderm and, thereby, create patterned axial structures. In doing so, the age of the NOM, but not the age of the SO, defines positional values along the anterior-posterior axis. We postulate that the temporal information from the NOM is linked to mesodermal Hox expression. The role of the SO for trunk patterning turns out to be the induction of neural tissue as prerequisite for neural hox patterning. Apparently, development of a stable anterior-posterior pattern requires neural hox patterning. We believe that this mechanism represents a developmental principle.


In this work, we use deep neural autoencoders to segment oil spills from Side-Looking Airborne Radar (SLAR) imagery. Synthetic Aperture Radar (SAR) has been much exploited for ocean surface monitoring, especially for oil pollution detection, but few approaches in the literature use SLAR. Our sensor consists of two SAR antennas mounted on an aircraft, enabling a quicker response than satellite sensors for emergency services when an oil spill occurs. Experiments on TERMA radar were carried out to detect oil spills on Spanish coasts using deep selectional autoencoders and RED-nets . Different configurations of these networks were evaluated and the best topology significantly outperformed previous approaches, correctly detecting 100% of the spills and obtaining an  A quick response from governments is required in situations of marine pollution due to oil spills . When anThe SLAR used in this work is a SAR mounted on an aircraft instead of a satellite and it has two radar antennas. SLAR and SAR sensors have some differences as mentioned in . On the The oil-spill detection strategies using SAR can be categorized into two groups. The first contains all the approaches that use the raw signals of the radar as well as polarimetric (PolSAR) or interferometric features (InSAR), and so forth to discriminate the oil slicks ,8. The sIn the state of the art, there are many works which address oil spill detection using machine learning techniques. These methods include Tree Forests , SupportIn some previous works, image processing and computer vision algorithms were used to automatically extract features and segment regions from radar images. These data can be fed to a network such as in , in whicMore recently, many approaches based on deep learning techniques have been proposed to increase the success rate in image classification tasks. The main motivation for using deep convolutional neural networks (CNN) is their ability to extract suitable features for the task at hand, as it is very difficult to properly select the features that can allow us to discriminate between oil spills and other natural phenomena due to the similarity of their representations as dark areas in the image. In this line, Chen et al.  selectedThere are many oil slick detection methods that use SAR imagery as input. However, it is uncommon to find detection methods using SLAR imagery. Two recent works in this line were presented in ,25. The Unlike the previous works using SLAR, we propose an approach that is able to detect oil slicks even in the presence of look-alikes. Our method, which is an extension of a previous study presented in , is focuThe rest of the paper is structured as follows: Autoencoders were proposed decades ago by Hinton and Zemel [nd Zemel , and sinnd Zemel . Autoencencoder) receives the input and creates a latent (or encoded) representation of it, and the second part (the decoder) takes this intermediate representation and tries to reconstruct the input. Formally speaking, given an input x, the network must minimize the divergence f and g represent the encoder and decoder functions, respectively. The encoder function provides a meaningful compact representation, which might be of great interest as regards feature learning or dimensionality reduction [eduction .denoising autoencoders [x from a corrupted version  of it, denoted as Some variations of autoencoders have been proposed in the literature to solve other kinds of problems. For example, encoders  are an ehe noise ,32,33.Autoencoders, and particularly denoising autoencoders, have been successfully used in many fields such as music, character recognition or medical image segmentation, but, in addition, they are currently being used in remote sensing to perform recognition and scene classification. For example, Zhao et al.  combinedIn this paper, we propose using autoencoders that receive as input the signal of SLAR sensors and return as output the areas detected as oil spills.denoising autoencoders, we use a type of segmentation autoencoder as proposed in [Selectional AutoEncoder (SelAE). The SelAE is trained to perform a function such that Based on the idea of posed in  but specFollowing the autoencoder scheme, the network is divided into encoding and decoding stages, where the encoder and decoder functions can be seen as a translator between the input, the intermediate representation, and the desired segmentation. The topology of a SelAE can be quite varied. However, we have considered only convolutional models because they have been applied with great success to many kinds of problems with structured data, such as images, video, or audio, demonstrating a performance that is close (or even superior in some cases) to the human level .Max Pooling layers until reaching an intermediate layer in which the encoded representation of the input is attained. It then follows a series of convolutional plus upsampling layers that generates the output image with the same input size. All layers have Batch Normalization [Dropout [ReLU as activation function [The topology of the network consists of a series of convolutional plus lization  and Drop[Dropout , and usefunction .selectional level The last layer consists of a set of neurons with sigmoid activations that predict a value in the range of In addition, in this work, we incorporate into this architecture a series of residual connections as proposed in . This tygrid-search technique [We applied a echnique  in orderreconstruction loss in autoencoders) can be defined as the squared error between the ground truth and the generated output. In this case, we use the cross-entropy loss function to perform the optimization of the network weights during a maximum of 100 epochs, with a mini-batch size of eight samples. The training process is stopped if the loss does not decrease during 10 epochs.As autoencoders are feed-forward networks, they can be trained by using conventional optimization algorithms such as gradient descent. In this case, the tuning of the network parameters is performed by means of stochastic gradient descent  considera) and its corresponding ground truth (b) with the oil spills labeled in black.In order to train the network, we generated a ground truth marking those pixels of the SLAR input images that correspond to oil spills. In this work, the network is fed with the raw data and the ground truth segmentations, so it must learn to discriminate the areas with oil spills from the rest of the data. That is, no preprocessing is performed on these images to eliminate the noise, as happens in other approaches such as in , nor is The next section details all the information about the dataset and the SLAR images used.In order to validate the effectiveness of the proposed method, we used a dataset containing 38 flight sequences supplied by the Spanish Maritime Safety and Rescue Agency (SASEMAR). SASEMAR is the public authority responsible for monitoring the Exclusive Economic Zones (EEZ) in Spain and its procedures are based on reports from the European Maritime Safety Agency (EMSA). The data provided by the SLAR sensor of each of these sequences was digitized in images with a resolution of 1,150×481 pixels.The SLAR samples were acquired by a TERMA SLAR-9000 mounted on a variant of the EADS-CASA CN-235-300 aircraft for search-and rescue missions see . This aiThe dataset was captured by the aircraft on Spanish coasts at an approximate average altitude of 3271 feet  and with a wind speed ranging between 0 and 32 kn, the most usual being 14 kn.As stated before, for the ground truth, we used a binary mask for each SLAR image, delimiting the pixels corresponding to oil spills. It is important to note that this labeling is performed at a pixel level since the goal is to evaluate both the detection and the precise location of the spills. This way, we can provide relevant information such as the position, the size and the shape of oil slicks in order to track them.From the 38 flight sequences, 22 contain examples of oil spills and 4 of look-alikes. Within these examples, the spots only represent 0.32% of the pixels in the image, which creates a very unbalanced dataset. To evaluate the method properly in the presence of unbalanced data, we use the n-fold cross validation  with two 2.1 GHz, 18-core Intel(R) Xeon E5-2695 (Broadwell) and 256 GB RAM. The computational resources from this machine were mainly exploited to parallelize the grid-search process in order to explore several network configurations.Three evaluation metrics widely used for this kind of tasks were chosen to evaluate the performance of the proposed method: Precision, Recall, and It should be noted that the p) to the ground-truth (g) bounding box with which it has a maximum IoU overlap. Bounding boxes are calculated to include the groups of pixels (or blobs) marked as 1 in the network output after applying the selectional threshold or in the ground-truth images. A detection is considered as TP if the area of overlap , rotations ” [“(SegSM)” : It firsOnce the best configuration and parameter settings for each network were selected, we evaluated the results using the different metrics. Moreover, we compared these results with three state-of-the-art methods for oil slick segmentation in SLAR images:Details regarding the implementation and the parameters used in these methods can be found in the corresponding references.The best results were obtained in all cases using the RED-Net architecture, which shows a higher These figures help to visualize the accuracy of the proposed model and to understand where the errors of each target class occur. As can be seen, wrong detections are typically made only at the contours of the oil spills.In this work, we present a method that uses deep convolutional autoencoders for the detection of oil spills from SLAR imagery. Two different network topologies have been analyzed, conducting extensive experiments to get the best type of data normalization, to know the impact of data augmentation on the results, and to obtain the most suitable hyperparameters for both networks.A dataset with a total of 28 flight sequences was gathered on Spanish coasts using TERMA SLAR radar, with labeled the ground-truth in order to train both selectional autoencoders and RED-Nets. It is composed of oil spills acquired in a wide variety of sea conditions dependent on weather  and geographic location as well as of flight conditions such as altitude and type of motion.The proposed approach is able to segment accurately oil slicks despite the presence of other dark spots such as biogenic look-alikes, low wind, which also introduces a lot of look-alikes, and noise due to bad radar measurements caused by the aircraft maneuvers. Results show that the RED-Net achieves an excellent Future work includes increasing the dataset size by adding more labeled samples from additional missions. In addition, Generative Adversarial Networks (GAN) such as Pix2Pix  could beReferences