Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost-Effectiveness of Treatments in Children With Attention-Deficit/Hyperactivity Disorder: A Continuous-Time Markov Modeling Approach

Objectives. This study aimed to assess the cost-effectiveness of treatments for attention-deficit/hyperactivity disorder (ADHD) in children through prevention of serious delinquent behavior. Cost-effectiveness was assessed in net-monetary benefit (NMB). Methods. To evaluate the three major forms of ADHD treatment (medication management, behavioral treatment, and the combination thereof) relative to community-delivered treatment (control condition), we used data from 448 children, aged 7 to 10, who participated in the National Institute of Mental Health’s Multimodal Treatment Study of Children with ADHD. We developed a three-state continuous-time Markov model (no delinquency, minor to moderate delinquency, serious delinquency) to extrapolate the results 10 years beyond the 14-month trial period at a 3% discount rate. Serious delinquency was considered an absorbing state to enable assessment in life-years (LYs) of serious delinquent behavior prevented. The willingness-to-pay (WTP) threshold was set equal to the annual cost associated with serious delinquency in children with ADHD of $12,370. Results. Modeled and observed outcomes matched closely with a mean difference of 6.9% in LYs of serious delinquent behavior prevented. The economic evaluation revealed a NMB of $95,449, $88,553, $90,536 and $98,660 for medication management, behavioral treatment, combined treatment, and routine community care, respectively. Estimates remained stable after linearly increasing the WTP threshold between $0 and $50,000 in the deterministic sensitivity analyses. Conclusions. This study assessed the cost-effectiveness of treatments for ADHD in children using continuous-time Markov modeling. We show that treatment evaluation in broader societal outcomes is essential for policy makers, as the three major forms of ADHD treatment turned out to be inferior to the control condition.
A Dynamical Model with Order Reduction for a Fluidic Bending-Type Soft Actuator*

This work develops an order-reduced dynamical model with the consideration of distributed-mass effect for a fiber-reinforced fluidic bending-type soft actuator. The model is based on the Lagrangian approach and the assumption of constant curvature. The analytical expressions of the strain energy, the gravitational potential energy, the kinetic energy and the generalized force are calculated in regards to the generalized coordinate which is defined as the bending angle of the soft actuator. The functions of the material deformation and the fluidic volume varying with the bending angle are derived and substituted into the dynamical model. Then Taylor series expansions are employed to reduce the model complexity by neglecting the high-order terms reasonably. Finally, an experimental setup for the soft actuator is built and a bending sensor is utilized to detect the bending angle. Experiments under typical inputs are implemented to verify the effectiveness of the dynamical model and the results show that the analytical responses are in good accordance with the measured data. The dynamical model can provide basis to the design of advanced model-based control algorithm for the soft actuator.
THE BREAKAGE OF PINUS RADIATA AT CLEAR-FELLING AND ITS EFFECT ON SAWLOG YIELD

Investigations were undertaken to give a better appreciation of factors that relate standing volume to recoverable sawlog yield. It was noticed during clearfelling that stems of mature Pinus radiata break at a diameter approximately equal to half breast height diameter. This indicates that volume to a 6 in. top diameter is of little value for estimating sawlog yield. Using a graphical method of analysis, it was found that, for the d.b. h, range 10 to 24 in. , stem volume below the point of break was approximately constant at 86% of total stem volume; but this finding takes no account of additional losses caused by stem malformation or wastage. The New Zealand Forest Service, Forest Research Institute, carried out a more detailed analysis of the data, and showed a more precise relationship for diameter at break to d.b. h. Total height was also found to be as effective as d.b. h, for estimating the diameter at point of break. Further developments of this general approach are also suggested.
A New Head Location Method in TMS Treatment

In the intelligent and automatic TMS treatment system, head location is a difficult problem. In this paper, we present a new method for head location based on Kinect2. First, we used the HOG feature descriptor and SVM algorithm to detect the face in the Kinect2 RGB image, and we determined the pixel position of the facial landmarks using the cascade regression algorithm. Then we used the depth image of Kinect2 to obtain the 3D point cloud of the feature points, we determined the head position by calculating the spatial position of the feature point cloud. And finally, we verified the proposed method through experiments. These experimental results showed the method is reliable and the accuracy is high and the method can be used in the TMS treatment.
Target-based robot autonomous exploration in rescue environments

Basic abilities for robots in rescue environments consisted of autonomous exploration and target recognition. In this essay, we combine these two abilities and propose a target-based robot autonomous exploration method. When no victim is found, robots will explore the rescue environments autonomously using the wall following and frontier-based techniques. Once finding a victim, robots will use the recognized victim as the navigation goal, plan a path use the "timed elastic band" approach, and quickly reach the victim to facilitate further rescuing. By combining the autonomous exploration and the victim recognition, our method can improve the efficiencies of both tasks. Extensive experiments and tests have been conducted on a real rescue robot. The results of experiments prove that our method can enable robots to explore the rescue environments autonomously with high efficiency. In the RoboCup Rescue Robot League (RRL) competitions, we have achieved good results by using this method.
Ultra-Wideband Terahertz Absorption Using Dielectric Circular Truncated Cones

We numerically demonstrate an ultra-wideband terahertz absorber using dielectric circular truncated cones on a non-structured graphene layer supported by a dielectric spacer on a metal reflector in the bottom. The absorber has an ultra-wideband absorption bandwidth from 0.34 to more than 10 THz with an average absorbance of 95.88% and a relative bandwidth of 186% because of the continuous multimode Fabry-Perot (FP) resonances. The absorber also possesses excellent absorption characteristics with polarization independence under normal incidence and angular stability up to 60°. The proposed ultra-wideband absorber may have promising applications in terahertz trapping, imaging, and detecting.
Wave energy potential in the northeast Atlantic : Impact of large-scale atmospheric oscillations

Changes in the wave energy potential of the northeast Atlantic are predicted to occur during this century, which may alter future wave energy extraction processes. Large-scale atmospheric oscillations are known to influence the wave climate of the North Atlantic ocean. For this reason, we are interested in the North Atlantic Oscillation (NAO) teleconnection index which is related to large-scale atmospheric circulation. We carried out a statistical analysis of the NAO using an ensemble of EC-Earth global climate simulations that includes historical periods and projected changes by the end of the 21st century. In addition, we analysed the correlation between this teleconnection and the wave energy flux from an ensemble of EC-EARTH driven WAVEWATCH III (WW3) model projections over Ireland and the northeast Atlantic.
The Search for Security in Muslim Northern Nigeria

The article puts forwards the argument that there is a pervasiveanxiety among Muslims over their security, both physical and spiritual, in today's northern Nigeria. It is an anxiety partly millenarian, partly political, that seeks to recreate a stronger sense of the ‘core North’ as dar al-Islam, with notionally ‘closed’ boundaries – just as it was in the pre-colonial Sokoto Caliphate. This has led first to the re-establishment, within twelve of Nigeria's 36 states, of full shari‘a law and then to the formation of a sometimes large corps of hisba (wrongly called ‘vigilantes’) – this despite Nigeria having a constitution that both is secular and reserves to the federal government institutions like police and prisons. The article explores the various dimensions, past and present, of ‘security’ in Kano and ends with the problem of ‘dual citizenship’ where pious Muslims see themselves at the same time both as Nigerians and as members of the wider Islamic umma. Le vigilantisme, terme souvent utilisé pour décrire toute forme de maintien de l'ordre non-étatique, ressort souvent négatif de l'analyse, associé à la violence et à la violation des droits individuels. Or, un examen plus approfondi de l'origine, de la pratique, de la fonction et de la structure de certains de ces groupes, souvent appelés vigilantes au Nigeria, révèle qu'ils ne correspondent pas tous à notre interprétation des vigilantes en tant que bandes de jeunes infligeant de la violence à leurs victimes et les soumettant à la justice de la jungle. Certains groupes de vigilantes ont leurs racines dans la communauté et sont une forme privilégiée de maintien de l'ordre au Nigeria. Ces groupes sont nombreux dans les États du Nord du Nigeria qui ont introduit la charia, tirant leur légitimité de sources diverses et parfois concurrentes : les Yan'banga de l'establishment traditionnel et communal haoussa, les Hisba de l'establishment religieux et les Yan'achaba de l'establishment politique. Que peut-on dire du fonctionnement, de la structure et de la fonction de ces divers groupes de vigilantes ? Comment la bataille politique et la lutte entre les élites politico-religieuses et traditionalistes haoussa façonnent-elles et reforment-elles les trois formes étudiées ? Quel est l'impact de cette lutte sur les femmes et les personnes vulnérables ? Cet article a deux objectifs. Le premier est de mettre en question la surgénéralisation associée au vigilantisme au Nigeria en analysant trois formes de vigilantisme dans le contexte d'un maintien de l'ordre informel dans les États du Sokoto et du Zamfara. Le second entend situer la question des vigilantes dans le contexte politique du Nord du Nigeria plutôt que dans un simple cadre moral qui les apparente à de violents criminels.
Deep Convolutional Neural Network for Quasar Spectral Identification

The classification and detection of quasars through analysis of spectrum is a major research topic in astronomy. Quasars are not easy to classify due to its noises and dramatic changes in spectra. On the other side, traditional methods of template matching are not effective in quasar recognition. Therefore, by improving the Convolutional Neural Network (CNN) which is widely used in image classification, this paper makes full use of CNN for its excellent performance in feature extraction and applies it to automatically identify spectra of quasars which are in the form of row vectors. The improved method is used for quasar identification in Sloan Digital Sky Survey (SDSS) published data. All data are averaged filtered and normalized before they are trained and tested. It is found that this method presents excellent results and is very promising for project such as Five-hundred-meter Aperture Spherical radio Telescope (FAST).
3D Printed Substrates for the Design of Compact RF Systems

In this paper, Additive Manufacturing (AM) using 3D printing has been shown as a potential candidate for realizing customized compact solutions for RF packaging applications. Cost effective 3D printing based packaging solutions with customized substrates and air gaps allow easier integration of multiple RF components with lower substrate losses. Using a damascene-like conductor patterning process and a LEGO-like assembly process, an amplifier coupled to an air-substrate based patch antenna is demonstrated in a single integrated package. The antenna overlays the amplifier circuit leading to a compact design. The proposed customization of substrates and 3D printing strategies can be extended to multiple-system level stacking for SOP/SIP packaging customized for applications such as 5G.
Modelling of Magnetic Storms Count Data Using Nonlinear Poisson Regression

The paper proposes a prediction model of dynamics of time series of magnetic storms number. The model used nonlinear Poisson regression. The investigated time series were converted from Dst index data for the 1964–2018 time interval. An artificial neural network was used to build a nonlinear autoregressive model. The training procedures were adapted using statistical properties of the investigated time series. It is shown that fluctuations of the number of geomagnetic storms are close to the Poisson distribution. Thus, to estimate the prediction efficiency, we proposed a special quality measure based on the analysis of the standard deviation ratio of the estimated model parameters. The model was used to forecast the number of magnetic storms for a week in advance. It was shown that the prediction accuracy was 20% higher compared to the traditional approaches to training of artificial neural network systems. A similar approach can also be successfully used to forecast dynamics of rare events number in atmospheric and solar-terrestrial physics.
A 180-GHz Super-Regenerative Oscillator with up to 58 dB Gain for Efficient Phase Recovery

This paper reports on the design of a 180-GHz super-regenerative oscillator in a 130nm SiGe BiCMOS technology. The oscillator has a tuning range of 6.5%, an output power of 0.5 dBm, and occupies an area of 0.72 mm2. When operated with a periodic quench signal, the circuit requires a minimum input power of -58 dBm for a phase coherent output, and can be switched at a rate up to 10 GHz. The circuit has a dc power consumption of 8.8 mW, and a maximum regenerative gain of 58 dB. QPSK and 8-PSK modulation up to 3 Gbit/s have been demonstrated at an energy efficiency of 2.9 pJ/bit. To the best knowledge of the authors, this work is the fastest reported phase-sampling super-regenerative oscillator to date.
Real-time Indoor Dense 3D Reconstruction of Integration Inertial Measurements Into Surfels

With the continuous innovation and improvement of sensor technology and SLAM methods, visual SLAM methods have been able to achieve dense reconstruction of the surrounding environment, but when the optimization is poorly initialized, the visual SLAM method suffers from a lack of robustness in the tracking step. Inertial Measurement Unit (IMU) can quickly measure the angular velocity and acceleration of the sensor body. Inspired of this performance, we propose a method for tightly-coupled IMU data with camera data and ensure real-time performance on the GPU. Our method is based on the visual method ElasticFusion. When the global consistency is considered, the sensor velocity, pose, IMU biases are jointly optimized and add inertial information into maps, fully dense surfel-based 3D reconstruction of the environment. Through a large number of experiments, we have found that our vision-inertial navigation SLAM method is significantly better than pure-vision methods in terms of real-time reconstruction, closed-loop capability and map drift correction.
Research on Online Reinforcement Learning Method Based on Experience-Replay

As for standard reinforcement learning, the key is that the agent’s next step is directed by the instantaneous and delayed reporting from constant interaction with the environment and trial and error learning. But it makes the convergence rate slower for actual reinforcement learning; at the same time, inconsistency state will occur in the agent learning process. Therefore, it is necessary for the agent to remember what has been learned within the time specified to improve the convergence and robustness of decision making. With regard to the above-mentioned issues, this paper proposes to accelerate the convergence rate of reinforcement learning by using the function approximation ability of neural network and to improve the robustness of reinforcement learning by using the Memory-based Experience-Replay(ER) algorithm. The experimental results show the effectiveness of the proposed method.
Variable Admittance Control Improving Stability in Physical Human-Robot Interaction *

This paper presents a variable admittance controller for eliminating instability in physical Human-Robot Interaction. In order to predict the instability, human hand stiffness is estimated in real time by modeling the level of muscle co-contraction of the human’s arms. A modified time-domain vibration index is then proposed based on the forces applied by the operator on the robot. The virtual damping coefficient in admittance controller is adjusted according to the human hand stiffness and the vibration index to ensure both the performance and stability of the interaction system. The proposed system is evaluated on an experimental set-up using an UR10 robot and the results demonstrate significant improvement in stable and low-effort cooperation.
Scale-aware Monocular SLAM Based on Convolutional Neural Network

Remarkable performance has been achieved using the state-of-the-art monocular Simultaneous Localization and Mapping (SLAM) algorithms. However, due to the scale ambiguity limitation of monocular vision, the existing monocular SLAM systems can not directly restore the absolute scale in unknown environments. Given the amazing results in the field of depth estimation from Convolutional Neural Networks (CNNs), we propose a CNN-based monocular SLAM, where we naturally combine the CNN-predicted depth maps together with the monocular ORB-SLAM, overcoming the scale ambiguity limitation of the monocular SLAM. We test our method using the popular KITTI odometry benchmark, and the experimental results show that the overall performance of average translational and rotational error can reach 2.00% and 0.0051°/m. In addition, our approach can work well under the pure rotation motion, which shows the robustness and high accuracy of the proposed algorithm.
Evaluation of WLP Dielectrics for High Voltage Applications

Due to the excellent mechanical and electrical properties together with a cost efficient processing, the thin film polymers are used in various applications as an interlayer dielectric (ILD) material where the device is generally working at CMOS like low voltages. The integration of high voltages in the redistribution layer becomes more attractive in future to realize higher system miniaturization and integration. Regarding to this, the power transformations could be integrated on wafer level for direct support of the CMOS device without an additional power transformation unit. Also high voltage III-V semiconductor dies will be integrated in Fan-Out packages. Thin film polymers have the potential to meet the demands for high voltage applications like high break down voltage and low leakage current. Well established thin film polymers like CYCLOTENE (Benzocyclotbutene - BCB) show a break down voltage in the range of 530 V/um. Compared with inorganic passivation such as thermal SiO2 with a breakdown voltages from 400 up to 1000 V/µm the BCB is quiet compatible regarding to the processing windows of layer thickness from BCB in the range from 5 to 20 um. BCB has been widely adopted in electronic applications, due to its low dielectric constant, excellent chemical resistance, and high thermal stability (glass transition temperature, T g > 350 °C) after hard-curing. The BCB has several advantages, especially the good process capabilities such as a photo structuring capability, the low temperature and the vacuum-less processing, might be interesting to use it in high voltage applications. This paper contains the profound investigation of the behavior of BCB at high voltages. Regarding the usability analyzing for the BCB as high voltage dielectric the break down voltage behavior was estimated and a time depending breakdown voltage was observed regarding the duration of the voltage application. This behavior is not yet published in the literature for BCB. MIM structures with 1 mm and 5 mm radius were manufactured on wafer level for this investigation. The leakage current of a few pA is measured and the time-dependent dielectric breakdown (TDDB) is extracted from Current-Time characteristics and shown in Weibull-plots. The measurement shows a spectrum from 350 V/µm to 450 V/µm, depending of the duration of the voltage and the level of the applied voltage. It is found that there is an exponential linkage between field strength and the time till the breakthrough occurs. The break through at 450 V/µm occurs after about 280 seconds, while the sample at 350 V/µm withstands longer by the factor of 13. These results will a very important milestone for future high power applications.
Vision-and-Lidar Based Real-time Outdoor Localization for Unmanned Ground Vehicles without GPS

This paper describes a vision-and-lidar based outdoor localization method for Unmanned Ground Vehicles (UGV) without GPS. We present a real-time method for pose estimation by combining visual odometry and lidar odometry. Instead of using a GPS, a laser scanner and a RGB-D camera are mounted on our UGV. Visual odometry and lidar odometry are fused by Extended Kalman Filter (EKF). Bundle Adjustment (BA) is used to optimize the fused odometry and build a 3D map. The method has been evaluated by four test routes set in our university. Experimental results indicate that a combination of visual and laser information on pose estimation is better than using only one of them. In addition to test robustness of the method, experiments are performed both in daytime and at dusk.
Does Capacity or Price affect competition in Liner Shipping ? An empirical investigation in passenger markets

In liner and especially in short sea shipping, ship owners decide which kind of ships they will employ in terms of their carrying capacity speed and qualitative characteristics. Clearly this decision is subject to the requirements of the specific characteristics of their market and the prevailing competitive conditions. Then, at a second stage, they bring these “quantities” to market and they engage in Bertrandlikeprice competition, while they have full and intertemporal access to information relating to other operators‟ market shares per category of passengers and vehicles. This competition theoretically should end up in a Bertrand-likeoutcome with prices equal to marginal cost, generating the competitive solution with the proviso that none of the ship owners can satisfy more demand than they are producing for in the first stage. However, as Kreps and Scheinkman (1983) have shown, this Bertrandlikecompetition may end up in Cournot outcomes due to the form of the game they are engaged in. In this paper we suggest a new test that applies the New Empirical Industrial Organization method (NEIO) and more specifically Conjectural Variation (CV) model in order to identify whether a duopoly game ends up in a Cournot or Bertrand outcome. At the same time we investigate Stackelberg related alternatives or collusive behaviour. We apply our model in short sea passenger shipping. Our findings suggest that rivals compete over both prices and quantities with one of the two firms leading the market. Additionally, the leader presents the highest deviations from marginal cost as suggested by the comparison of the Lerner indices, while he has undertaken the heaviest investment in the market. Thus, there is evidence that the prices charged to passengers are Cournot prices, validating the Kreps and Scheinkman argument. However, in the case of vehicles transportation there is strong evidence of collusion.