Miracle-dz/UniFAR-FTUs huggingface dataset:
Direction-of-Arrival and Range Estimation of Near-Field Sources Based on Subspace Fitting

A new algorithm is proposed to address the problem of near-field source localization using weighted subspace fitting (WSF) in this paper. Through separating the two parameters of bearings and ranges, the two-dimensional parameter estimation problem is first transformed into one-dimensional parameter estimation problem. The specific method is to construct a Toeplitz-like correlation matrix by using the anti-diagonal elements of the near-field source signal covariance matrix. Then the subspace fitting algorithm of sparse recovery is used to estimate the direction of arrival (DOA). The estimated direction is substituted back to the original near-field source model. After that, the sparse recovery algorithm based on singular value decomposition can be used to calculate the estimated value of the ranges. Computer simulations verify the excellent performance of the algorithm. In addition, the algorithm has lower requirements for SNR and snapshots.
Abnormal Two-Stage Degradation on P-Type Low-Temperature Polycrystalline-Silicon Thin-Film Transistor Under Hot Carrier Conditions

In this study, an abnormal two-stage degradation of low-temperature polycrystalline-silicon (LTPS) thin-film transistors (TFTs) on a polyimide flexible substrate after hot carrier stress was investigated. The degradation mechanism was divided into two stages. In the first stage, the increases in capacitance in the off region and transconductance are caused by impact ionization induced electron trapping into the gate insulator (GI) at the drain edge. Furthermore, the threshold voltage (<inline-formula> <tex-math notation="LaTeX">$\text{V}_{\text {th}}$ </tex-math></inline-formula>) shift in the positive direction is caused by electrons flowing back to the source side and trapping into the buffer that induces source barrier lowing. The second stage of degradation, including a <inline-formula> <tex-math notation="LaTeX">$\text{V}_{\text {th}}$ </tex-math></inline-formula> shift in the negative direction and a decrease in the transconductance is caused by Joule heating induced negative bias temperature instability (NBTI). Furthermore, NBTI hardly occurs behind the pinch off in the channel and fixed oxide charge does not compensate the trapped electron at drain side which is induced in the first stage.
P2P Energy Transaction for Multiple Microgrids Considering Power Flow Constraints

Energy transactions among multiple microgrids (MMGs) can improve economy and reliability of electricity markets. However, power flow constraints (e.g., voltage tolerance and node balance constraints) with respect to distribution networks (DNs) are usually overlooked for reducing the complexity of energy transaction problems in existing studies. This paper models a bi-level energy trading framework between MMGs and DNs. Firstly, in order to guarantee the safety operation while minimizing the total cost of DNs, full alternative current power flow constraints are considered at the upper level. Then a comprehensive energy trading model for MMGs is established at the lower level. Furthermore, analytical target cascading (ATC) algorithm is applied to solve energy trading problems between MMGs and DNs in a distributed manner. Finally, numerical tests on an IEEE 33-bus distribution system are implemented to demonstrate the performance of our distributed energy transactions method.
Autonomous UAV-Based Position and 3D Reconstruction of Structured Indoor Scene

In this paper an optimized scheme for three- dimensions (3D) reconstruction of structured scenes is implemented, which combines mapping and positioning under the same module. Compared with previous pure vision solutions, this solution can obtain accurate location information while building maps. In addition, the intel@realsense D435i and intel@realsense T265 are aligned to use by a 3D-printed components. A classification method based on Robot Operating System (ROS) is used. This method uses camera and SURF method to obtain images and feature points respectively. Subsequently, the input anchor points are classified and stored in different memories to complete the closed-loop detection. In order to reduce errors in the map, the optimization is carried out in the case of using G2O. The realsense-ros provides the driver for both T265 and D435i. The rtabmap-ros is used to get the data from mapping. The ultimate result is shown in the RTAB-Map browser windows. At the end of this manuscript, the effect of the 3D reconstruction on the indoor scene, and the visual positioning results are presented. The 3D reconstruction renderings have obvious object features and strong resolution, and the visual positioning effect can meet the missions of drones for fixed-altitude and fixed-point stable flight.
Reinforcement Learning for Underwater Navigation Subject to Infrequent Position Measurements

This paper explores the Reinforcement Learning (RL) approach in an underwater navigation problem, subject to infrequent position measurements and other unsynchronized observations in the absence of a Doppler velocity log equipment. In particular, an end-to-end History-Window(HW)-RL approach and a classical RL approach are studied and their performances are compared against an anti-windup PID controller. The state used in classical RL and PID is estimated from an Extend-Kalman-Filter (EKF), while the HW-RL utilizes a history of previous measurements as the input to the neural network controller, for the purpose of jointly training an (encoded) state estimator and a controller. Preliminary results have been obtained through numerical simulations conducted in the Webots simulator, showing the HW-RL and the classical RL (with EKF) are able to track given waypoints when the position measurements are infrequent.
Structural Insights into Human Adenovirus Type 4 Virus-Associated RNA I

RNA molecules can adopt specific RNA triplex structures to execute critical biological functions. Human adenoviruses (HAdVs) are abundant pathogens encoding the essential, noncoding virus-associated RNA I (VA RNAI). Here, we employ a triplex-specific probing assay, based on the intercalating and cleaving agent benzoquinoquinoxaline 1, 10-phenanthroline (BQQ–OP), to unravel a potential RNA triplex formation in VA RNAI. The BQQ–OP cleavage of the pathogenic HAdV type 4 (HAdV-4) VA RNAI indicates that a potential triplex is formed involving the highly conserved stem 4 of the central domain and side stem 7. Further, the integrity of the HAdV-4 VA RNAI side stem 7 contributes to a potential triplex formation in vitro and virus growth in vivo. Collectively, we propose that the HAdV-4 VA RNAI can potentially form a biologically relevant triplex structure.
Influence of Graphene Oxide Nanoparticles on Bond-Slip Reponses between Fiber and Geopolymer Mortar

In this study, the influence of graphene oxide nanoparticles on the bond-slip behavior of fiber and fly-ash-based geopolymer paste was examined. Geopolymer paste incorporating a graphene oxide nanoparticle solution was cast in half briquetted specimens and embedded with a fiber. Three types of fiber were used: steel, polypropylene, and basalt. The pullout test was performed at two distinct speeds: 1 mm/s and 3 mm/s. The results showed that the addition of graphene oxide increased the compressive strength of the geopolymer by about 7%. The bond-slip responses of fibers embedded in the geopolymer mixed with graphene oxide exhibited higher peak stress and toughness compared to those embedded in a normal geopolymer. Each fiber type also showed a different mode of failure. Both steel and polypropylene fibers showed full bond-slip responses due to their high ductility. Basalt fiber, on the other hand, because of its brittleness, failed by fiber fracture mode and showed no slip in pullout responses. Both bond strength and toughness were found to be rate-sensitive. The sensitivity was higher in the graphene oxide/geopolymer than in the conventional geopolymer.
Optimisation of Characteristics of CHI-ALG-CaCl2 Nanocarriers Loaded with Non-Volatile Extracts of CymbopogonSp.

Nanotechnology is receiving an intense attention these days due to its potential application in various fields including cosmeceutical and pharmaceutical. Nanoparticles encapsulating natural extract are usually characterised for their particle size and polydispersity index but zeta potential is hardly discussed. The zeta potential is the measurement that shows the aggregation behaviour, reactivity and toxicology. In this study, nanoparticle encapsulating Cymbopogon sp. have been formulated to develop a cosmeceutical product. The antioxidant properties from aqueous extract of Cymbopogon sp. was encapsulated with chitosan/alginate biopolymeric nanoparticles. Central Composite Design (CCD) of Response Surface Methodology (RSM) was employed to investigate and optimise the effects of independent variables such as pH of SA, concentration of non-ionic surfactant concentration of CaCl2 and pH of chitosan on zeta potential and encapsulation efficiency (EE). Following the model, the optimum condition for zeta potential was selected as 6.2 of sodium alginate pH, 0.12% of non-ionic surfactant concentration, 0.05 concentration of CaCl2 and 5.6 of chitosan pH with negative zeta potential of 18.3mV. The zeta potential obtained experimentally was close to its predicted value which is-18.09mV. The model provides a basis on the optimisation of the zeta potential on chitosan/alginate nanoparticle encapsulating Cymbopogon sp. extracts.
An Efficient Approach for Gastric Polyps Detection Based on Improved SSD

Gastroscopy is the main method of detecting gastric polyps. Specifically, the doctor observes the gastroscope image with the naked eye to determine the presence and location of polyps. The detection rate of polyps is affected by the doctor’s experience, fatigue, and other factors. There is a certain degree of missed polyps. Therefore, it is necessary to detect polyps by auxiliary means. In this paper, we report a convolutional neural network for gastric polyp detection, which is based on the Single Shot MultiBox Detector (SSD). In order to improve the performance of polyp detection, an excellent feature extractor is essential. We adopt EfficientNet instead of VGG16 as the backbone network of the SSD. In addition, the previous loss function is improved, and the PReLU activation function is introduced into the SSD to achieve better detection performance. We conduct extensive experiments on the gastric polyp dataset. The final experimental results show that the improved SSD network for gastric polyp detection can achieve a precision of 90.3% and a recall rate of 85.7%, which is better than the original SSD network.
The Effects of Instrumental Balance Training on Balance in Individuals with Unilateral Transtibial Amputation: A Pilot Study

ABSTRACT Introduction With the loss of a lower limb, an individual with amputation may face impaired gait and balance. Different rehabilitation techniques can be used to deal with those functional disabilities. The purpose of this study was to determine whether computerized balance training could have any possible effects on balance in individuals with unilateral transtibial amputation. Materials and Methods A total of 16 subjects who used a prosthesis in their daily life and were between 18 and 65 years of age were included in the study. Individuals were randomly divided into two groups: control group (CG) (n = 7) trained with traditional prosthetic rehabilitation and the experimental group (EG) (n = 9) trained with computerized balance training for five sessions for 2 weeks. Percentage of prosthetic weight bearing (PWB) timed up and go test (TUG), single-leg stance test (SLST), postural sway score, and limits of stability (LoS) were evaluated at baseline and posttreatment. Results No significant differences were observed in between-group comparisons after treatment. Within-group comparison showed that PWB, SLST, and LoS score increased in EG, whereas only PWB increased in CG. Conclusions Similar results were revealed with both computerized and traditional prosthetic training. Although there were no significant differences in between-group comparisons, computerized balance training improved the amputated side single-leg stance and stability limits, which are highly related to fall risk in individuals with amputation. Clinical Relevance Clinical relevance: Usage of computerized balance training can be helpful to improve single-leg stance and LoS in individuals with transtibial amputation.
Simultaneous Electrochemical Sensing of Indole-3-Acetic Acid and Salicylic Acid on Poly(L-Proline) Nanoparticles–Carbon Dots–Multiwalled Carbon Nanotubes Composite-Modified Electrode

Sensitive simultaneous electrochemical sensing of phytohormones indole-3-acetic acid and salicylic acid based on a novel poly(L-Proline) nanoparticles–carbon dots composite consisting of multiwalled carbon nanotubes was reported in this study. The poly(L-Proline) nanoparticles–carbon dots composite was facilely prepared by the hydrothermal method, and L-Proline was used as a monomer and carbon source for the preparation of poly(L-Proline) nanoparticles and carbon dots, respectively. Then, the poly(L-Proline) nanoparticles–carbon dots–multiwalled carbon nanotubes composite was prepared by ultrasonic mixing of poly(L-Proline) nanoparticles–carbon dots composite dispersion and multiwalled carbon nanotubes. Scanning electron microscope, transmission electron microscope, Fourier transform infrared spectroscopy, ultraviolet visible spectroscopy, energy dispersive spectroscopy, cyclic voltammetry, electrochemical impedance spectroscopy, and linear sweep voltammetry were used to characterize the properties of the composite. poly(L-Proline) nanoparticles were found to significantly enhance the conductivity and sensing performance of the composite. Under optimal conditions, the composite-modified electrode exhibited a wide linear range from 0.05 to 25 μM for indole-3-acetic acid and from 0.2 to 60 μM for salicylic acid with detection limits of 0.007 μM and 0.1 μM (S/N = 3), respectively. In addition, the proposed sensor was also applied to simultaneously test indole-3-acetic acid and salicylic acid in real leaf samples with satisfactory recovery.
The Impact of Operating Lease Capitalization on Financial Statements in Indonesia

PSAK 73 is a new accounting standard that introduces a single accounting model for lessees, namely recording their rental activities as capital leases. This study aims to determine the impact of operating lease capitalization on financial statements. This research is a type of quantitative research using secondary data in the form of annual reports and company financial statements. The object of this research is a company listed on the Indonesia Stock Exchange for the period 2018-2019 which discloses the value of future minimum lease payments on operating leases in the financial statements. Data analysis methods include descriptive statistical testing and Wilcoxon signed-rank test. The results show that operating lease capitalization has a significant effect on unrecorded lease liability, unrecorded lease assets, equity, and financial ratios. Also, empirical evidence shows that there are tax savings from operating lease capitalization
Alarm deadband design based on the reliable distribution estimation of alarm deviations

Deadbands are widely used in industrial alarm systems to decrease nuisance alarms as much as possible. This paper proposed a way to design deadband widths based on alarm deviations. A key technical issue is to determine an appropriate sample size of alarm deviations, in order to yield a reliable estimation of the probability distribution of alarm deviations. This issue is resolved via Bayesian estimation theory, and an optimal deadband width is designed by exploiting historical data samples in normal operating conditions. Industrial examples are provided to validate the proposed method.
TNF-α is a Novel Biomarker for Predicting Plaque Rupture in Patients with ST-Segment Elevation Myocardial Infarction

Background and Aims Patients with plaque rupture (PR) present with different cardiovascular risks, clinical strategies, and outcomes from those with plaque erosion (PE). However, there are lack of noninvasive biomarkers to distinguish PE from PR. Methods A prospective analysis of 382 patients with ST-segment elevation myocardial infarction (STEMI) was conducted. Of these patients, 262 and 120 presented with PR and PE, respectively. An additional 83 patients diagnosed with stable angina pectoris were enrolled as control group. Peripheral blood monocytes were collected pre-percutaneous coronary intervention and used to evaluate the mRNA expression of IL-4, IL-10, IL-1β, and TNF-α in all patients. Results STEMI patients had higher IL-4, IL-10, IL-1β, and TNF-α expression than the control patients. The mRNA levels of IL-4, IL-1β, and TNF-α were significantly higher in PR patients than PE; however, no significant difference was observed in IL-10 between PE and PR. The areas under the receiver-operating characteristic curves for IL-4, IL-1β, and TNF-α for PR versus PE were 0.685, 0.747, and 0.895, respectively. At the cut-off value of 2.52, TNF-α demonstrated a sensitivity of 70.61% and specificity of 93.33% for discriminating PR from PE patients. When added to the model of established clinical risk factors, TNF-α significantly improved the predictive accuracy of PR. Multivariable logistic regression analysis indicated that TNF-α mRNA level was independently associated with PR (odds ratio, 3.09; 95% confidence interval, 2.29–4.16; p < 0.001). Conclusion The inflammatory response of peripheral blood mononuclear cells in patients with PR was higher than that in patients with PE. TNF-α may be a potential biomarker for predicting PR that could facilitate risk stratification and management in STEMI patients.
Research on collaborative formation of heterogeneous multi-agent systems with nonlinear terms

In order to study a heterogeneous multi-agent consisting of a first-order linear agent and an agent with second- order nonlinear terms, a multi-agent system is designed under action of the one order virtual navigator and according to the conformance protocol. The distributed formation control algorithm of the system uses the Lyapunov function theory and model conversion to analyze the stability of the multi-agent system(MAS). A sufficient condition for the formation control stability of multi-agents is given and expressed as linear matrix inequality. The validity of the theory is verified by numerical simulation.
In-Party Like, Out-Party Dislike and Propensity to Vote in Spain

ABSTRACT Do affectively polarised people vote or stay home on election day? Although there is an increasing number of comparative studies focusing on the origins of partisan affective polarisation, our knowledge about its impact on individuals’ decision to vote is still limited. This article takes a closer look at the relationship between propensity to vote and partisan affective polarisation by distinguishing those produced by in-party like and by out-party dislike. The results show that both in-group like and out-group hate sentiments increase people’s propensity to vote, and that the effects of the latter are more accentuated. The argument presented in the following pages is based on the analysis of a two-wave panel study conducted in Spain between April and May 2019.
Blockchain Technology in Innovation Ecosystems for Sustainable Purchases through the Perception of Public Managers

The success of organizational processes is increasingly related to sustainable innovation. The concern with sustainable public purchases has been gaining strength over the years. However, several barriers are found to implementing this practice. At the same time, blockchain advances as technology part of the innovation of industry 4.0 and as a proposal to solve these difficulties. The study aimed to identify the perception of public procurement managers on the use of information systems with characteristic features of this technology, to reduce these barriers and elaborate a proposal for the use of blockchain in open innovation systems. The research developed is qualitative, quantitative and applied, being carried out through the application of a structured questionnaire to purchasing managers using the 92 prefectures of the State of Rio de Janeiro, located in Brazil, with subsequent analysis through descriptive statistics. The results of this work present relevant findings for public procurement through innovation and blockchain technology with the possibility of tracking the entire supply chain, allowing the verification of possible environmental and social damages such as the use of child or slave labor, the use of deforestation wood, counterfeit products, unethical agents, in addition to providing more transparency to the process of acquisition.
Assessment of CVD Risk Factors in Secondary Prevention after Ischemic Stroke Using the ICF

Background: Patients after undergoing ischemic stroke have a high risk of further cardiovascular disease (CVD) incidents. Monitoring risk factors is critical to prevent the recurrence of CVD. Objective: The aim of the study was to determine differences in the incidence of risk factors for CVD in a post-ischemic stroke patient group (SG) compared to the control group, which had not undergone ischemic stroke (CG), and to characterize them using the ICF (International Classification of Functioning, Disability and Health) classification system. Materials and Methods: The incidence of risk factors for recurrent CVD events were retrospectively analyzed in 55 patients in SG and 55 patients in CG. The results were translated into categories from the ICF classification system. Results: Atrial fibrillation (p = 0.013), carotid artery stenosis > 50% (p < 0.001), LDL > 71 mg/dL (p < 0.001), heart rate > 80/min (p = 0.007), taking NOAC (p = 0.008) and NSAIDs (p < 0.001) as well as nicotinism (p = 0.001) were significantly more common in SG compared to CG. The value of the distribution of the total incidence of CVD risk factors were observed to be higher for SG than for CG. In SG, both for males (p < 0.001) and females (p < 0.001) more risk factors for recurrent CVD incidents were observed compared to CG. Conclusions: Patients in SG differ in the occurrence of risk factors for CVD event compared to CG. The use of a single tool, such as the ICF assessment sheet, can be useful in assessing and analyzing risk factors for recurrent CVD events. This may help to reduce the risk of subsequent CVD events in secondary prevention.
Feedforward-Control-Oriented Identification: A Robust Iterative Learning Approach

Feedforward controller plays an important role in the achievement of high servo performance in the field of industrial electromechanical systems. Although existing instrumental-variables-based iterative feedforward tuning (IFT) methods show a promising prospect on improving estimation accuracy, the robust approaches have not developed. In this paper, a robust IFT approach is proposed through a combination of instrumental-variables-based system identification and learning control. It transforms the feedforward controller design to a system identification problem, and then to a typical H2 state feedback problem. A simulation example is provided to confirm its superiority.