Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Sensor Based on Copper(II) Thiocyanate Pyridine Polymeric Complex for Detection of Catechol

The reaction of copper(I) thiocyanate with triphenylphosphine, in pyridine, in air and at room temperature, led to the formation of the copper(II) thiocyanate pyridine polymeric complex [Cu<sub>2</sub>(<inline-formula> <tex-math notation="LaTeX">$\mu _{\text {3}}$ </tex-math></inline-formula>CO<sub>3</sub>)(NCS)<sub>2</sub>(Py)<sub>4</sub>]<sub>n</sub> in the form of deep blue needle-like crystals. Fourier transform infrared spectroscopy (FTIR), elemental analysis (EA), thermogravimetric analysis (TGA) and single crystal X-ray diffraction analysis (XRD) were performed in order to reveal the identity of the obtained complex. The complex is a coordination polymer that crystallizes in the orthorhombic space group <italic>Pnma</italic> and has a one-dimensional linear structure running along the crystallographic <inline-formula> <tex-math notation="LaTeX">${a}$ </tex-math></inline-formula> axis. Here, we report the investigation of the electrochemical properties of this polymeric compound, collected in acetonitrile solution and KClO<sub>4</sub> as electrolyte, by cyclic voltammetry and square wave voltammetry. The voltammograms showed four peak pairs related to redox processes of copper ion and electroactive ligands. Moreover, we used this compound as modifier of carbon paste electrodes, whose electrochemical properties were studied in different electrolytes and electrochemical redox probes. These studies demonstrate the valuable electrochemical and electrocatalytic properties of the [Cu<sub>2</sub>(<inline-formula> <tex-math notation="LaTeX">$\mu _{\text {3}}$ </tex-math></inline-formula>-CO<sub>3</sub>)(NCS)<sub>2</sub>(Py)<sub>4</sub>]<sub>n</sub>polymerimmobilized in the carbonaceous matrix. The sensor developed by using the carbon paste method has shown excellent sensitivity for catechol, good repeatability, selectivity, stability, and applicability in detection of catechol in water samples.
New Developments In Testosterone Therapy - a Congress Report *

J. REPRODUKTIONSMED. ENDOKRINOL. 2/2008 S progress of the pharmacotherapy for a given indication appears to have come to a halt. The reason for a certain standstill in testosterone therapy was the fact that, for a long time, clinically useful dosage forms were not available. Oral formulations were insufficiently active or hepatotoxic while parenteral formulations had sub-optimal pharmacokinetics. Now, the situation is changing and several suitable testosterone preparations such as oral, transdermal, intramuscular or buccal systems are on the market or in the pipeline.
Robots serve humans in public places—KeJia robot as a shopping assistant

This paper reports the project of a shopping mall service robot, named KeJia, which is designed for customer guidance, providing information and entertainments in a real shopping mall environment. The background, motivations, and requirements of this project are analyzed and presented, which guide the development of the robot system. To develop the robot system, new techniques and improvements of existing methods for mapping, localization, and navigation are proposed to address the challenge of robot motion in a very large, complex, and crowded environment. Moreover, a novel multimodal interaction mechanism is designed by which customers can conveniently interact with the robot either in speech or via a mobile application. The KeJia robot was deployed in a large modern shopping mall with the size of 30,000 m2 and more than 160 shops; field trials were conducted for 40 days where about 530 customers were served. The results of both simulated experiments and field tests confirm the feasibility, stability, and safety of the robot system.
A wideband antenna using metasurface for the 2G/3G/LTE/5G communications

A wideband antenna using metasurface is proposed for the future 5G communications. By using the metasurface and the multi‐layer substrate with high relative permittivity, the height of the proposed antenna can be reduced to 0.11 𝛌c in the operating frequency band. The metasurface including 40 unit cells are arranged on the second layer to improve the gain at the upper frequencies. Besides, by employing the dual arc‐shaped defected ground structure, the impedance bandwidth can also be broaden and the gain can be improved. The measured result shows that an impedance bandwidth of 77.2% (1.63‐3.68 GHz) with a stable gain of 5.1 ± 1.2 dBi can be obtained. Hence, the proposed antenna is potentially suitable for the future 5G communications.
High step‐up isolated dc–dc converter with single input and double output and soft‐switching performance for renewable energy applications

A single-input double-output dc–dc isolated high step-up dc–dc converter with soft-switching feature is presented in this study. The concept is to utilise quadrupler technique to reach high voltage gain without large duty cycle. Additionally, soft-switching operation for all power switches and diodes is realised to reduce overall power losses and increase power conversion efficiency over a broad range. Furthermore, the leakage inductance energy of transformer is recycled to output with an active clamp circuit. Thus, the voltage stress on main switch is reduced and a low-voltage-rated metal–oxide–semiconductor field-effect transistors (with low R DS on ) can be used. Moreover, low input current ripple feature is helpful to lengthen life time of renewable energy power sources. Finally, the analysis is described in detail and performance of the proposed converter has been verified through experimental results.
Durability of alumina silicate concrete based on slag/fly ash blends against corrosion

Purpose The durability of concrete structures, especially built-in corrosive environments, starts to deteriorate after 20–30 years, even though they have been designed for more than 60 years of service life. The durability of concrete depends on its resistance against a corrosive environment. Inorganic Polymer concrete, or geopolymer concrete, has been emerging as a new engineering material with the potential to form an alternative to conventional concrete for the construction industry. The purpose of this paper is to conduct the investigation on corrosion of the geopolymer materials prepared using GGBS blended with low calcium fly ash in different percentages and sodium hydroxide, sodium silicate as activators and cured in ambient conditions (25±5°C). Design/methodology/approach GGBS was replaced by fly ash at different levels from 0 to 50 percent in a constant concentration of 12M. The main parameters of this study are the evaluation of strength characteristics of geopolymer concrete and resistance against corrosion by conducting accelerated corrosion test (Florida method). Findings From the test results it is observed that the strength of the geopolymer concrete with GGBS in ambient curing performs well compared to geopolymer concrete with GGBS blended with fly ash. The GPCE sample (40 percent replacement of fly ash to GGBS) shows better results and the resistance against corrosion was good, compared to all other mixes. Research limitations/implications The outcomes of this investigation will be useful for the researchers and the construction industry. Practical implications This paper results that optimum percentage of fly ash should be blended with GGBS against the corrosion attack. This investigation indicates that GGBS without the combination of fly ash can be utilized in a normal environment. These findings will definitely be useful for the ready-mix concrete manufacturers and the construction Industry. Social implications Disposal of industrial wastes causes pollution to the environment. Industrial wastes are utilized for the production of geopolymer concrete, which is the alternative material for the construction industry. Originality/value From the observation of the previous literature, till now there was no investigation on geopolymer concrete for corrosion under ambient curing conditions, as such this investigation could be considered as the new investigation.
Adaptive metric learning with deep neural networks for video-based facial expression recognition

Abstract. Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.
$\pi$ -SCR Device for Broadband ESD Protection in Low-Voltage CMOS Technology

Electrostatic discharge (ESD) protection design is needed for integrated circuits; however, the ESD protection devices near the I/O pad may cause negative impacts on the high-frequency performance. To achieve both excellent ESD robustness and good broadband performance, a silicon-controlled rectifier (SCR) with trigger diodes, a matching inductor, and a reversed diode to form a novel <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-SCR device is presented in this brief. As compared with the conventional <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-diode in silicon, the <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-SCR can reduce the clamping voltage during the critical positive-to-<inline-formula> <tex-math notation="LaTeX">$V_{\text {SS}}$ </tex-math></inline-formula> (PS) ESD test, and the high-frequency performance is not seriously degraded (insertion loss < 2 dB within 0–20 GHz in this brief). In addition, the <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-SCR device does not suffer the latch-up issue in low-voltage CMOS technology, and it has the potential to further reduce the clamping voltage during other ESD tests. Therefore, the novel <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-SCR device will be a good choice for broadband ESD protection in low-voltage CMOS technology.
Leveraging technology to minimize operational error and hazards—Rise of the Operator 2.0

We are living in a time where operations and reliability are being impacted by the limits of our own humanity. Decades of research in the field of human factors engineering has shown that, often, we as humans are in fact the weakest link in the successful operation of a plant or facility. Complex systems coupled with the human element give rise to a new class of problem, the socio‐technical problem. Fortunately, we now have proven technology to mitigate some of our inherent shortcomings. The use of this technology can radically alter the way we operate and will give rise to what I call the Operator 2.0. Imagine automated work procedures that appear in the operators work environment that guide them through an activity, instant access to remote expertise that guide them through troubleshooting from anywhere in the world, and a technology that can reduce training time for operators and technicians from years, down to months. Imagine sending a drone to perform an inspection in the process, as opposed to sending an operator into harm's way. Think of the implications of not having people in the actual process. This opportunity exists today.
Planning Approximate Exploration Trajectories for Model-Free Reinforcement Learning in Contact-Rich Manipulation

Recent progress in deep reinforcement learning has enabled simulated agents to learn complex behavior policies from scratch, but their data complexity often prohibits real-world applications. The learning process can be sped up by expert demonstrations but those can be costly to acquire. We demonstrate that it is possible to employ model-free deep reinforcement learning combined with planning to quickly generate informative data for a manipulation task. In particular, we use an approximate trajectory optimization approach for global exploration based on an upper confidence bound of the advantage function. The advantage is approximated by a network for Q-learning with separately updated streams for state value and advantage that allows ensembles to approximate model uncertainty for one stream only. We evaluate our method on new extensions to the classical peg-in-hole task, one of which is only solvable by active usage of contacts between peg tips and holes. The experimental evaluation suggests that our method explores more relevant areas of the environment and finds exemplar solutions faster—both on a real robot and in simulation. Combining our exploration with learning from demonstration outperforms state-of-the-art model-free reinforcement learning in terms of convergence speed for contact-rich manipulation tasks.
Efficient Transmit Delay Calculation in Ultrasound Coherent Plane-Wave Compound Imaging for Curved Array Transducers

The recently introduced plane-wave compounding method based on multiple plane-wave excitation has enabled several new applications due to its high frame rate (>1000 Hz). In this paper, a new efficient transmit delay calculation method in plane-wave compound imaging for a curved array transducer is presented. In the proposed method, the transmit delay is only calculated for a steering angle of 0° and is shifted along the element of the transducer to obtain other transmit delays for different steering angles. To evaluate the performance of the proposed method, the computational complexity was measured for various transmission conditions. For the number of elements and plane-wave excitations of 128 and 65, respectively, the number of operations was substantially decreased in the proposed method compared with the conventional method (256 vs. 8320). The benefits of the proposed method were demonstrated with phantom and in vivo experiments, where coherent plane-wave compounding with 65 excitations provided larger CR and CNR values compared to nine excitations (−22.5 dB and 2.7 vs. −11.3 dB and 1.9, respectively). These results indicate the proposed method can effectively reduce the computational complexity for plane-wave compound imaging in curved array transducers.
Elimination of Motion-Induced Phase Based on Double-Time Switching Scheme for SAA FMCW Radar

Due to the low cost and straightforward structure, the switch antenna array (SAA) frequency modulated continuous wave (FMCW) radar has been widely applied in many fields. However, the motion-induced phase always leads to inaccurate direction estimation of moving targets. Here, we proposed an elimination method of the motion-induced phase for the SAA FMCW radar. A double-time switching scheme (DTSS) is used for the reception of echo signals. Elimination of motion-induced phase is completed without estimating velocity, which can avoid the ambiguous velocity estimation problem. Additionally, the direction estimation of the moving target can be obtained by directly using a conventional digital beam forming (DBF) algorithm. The validity of the proposed method has been proved by the simulated and experimental results.
A Highly Linear 8-Bit M–2M Digital-to-Analog Converter for Neurostimulators

M–2M current digital-to-analog converter (DAC) is one of the best architectures for the implantable stimulation systems where the available area near the tissue is restricted. However, due to the nonlinear behavior of the employed transistors, the conventional M–2M DAC does not resemble an accurate resistive R-2R ladder. This is due to the fact that the operating point and therefore the drain-source resistance of each transistor depend not only on its location in the ladder, but also on the selected digital input code. Therefore, in this brief, a highly linear M–2M current DAC is proposed that alleviates the effect of the selected digital input code by replacing the employed fixed resistive dump load with an array of resistors controlled by the input code. Moreover, a correction circuit is utilized to improve the nonlinearity effect caused by the location of each transistor in the ladder. The proposed circuit is designed and simulated in a 0.13-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS technology. Post-layout simulation results show that the proposed M–2M DAC achieves a spurious-free dynamic range (SFDR) of 56.2 dB and signal-to-noise-and-distortion ratio (SNDR) of 46.7 dB at the cost of 25 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power consumption for the reference current of 20 <inline-formula> <tex-math notation="LaTeX">$\mu \text{A}$ </tex-math></inline-formula>.
The Role of Knowledge Management in the Relationship between IT Capability and Interorganizational Performance: An Empirical Investigation

Knowledge management capability (KMC) represents an important link between IT and individual firm performance. We investigate this link in an interorganizational (IO) context—an increasingly important and yet substantially underresearched area. Based on reviewing and integrating the literature, we develop and test a comprehensive empirical conceptualization of KMC that includes knowledge creation, transfer, retention, and application. We collected survey data from supply management professionals at one partner firm (either customer or supplier) in an IO relationship. We tested our research hypotheses using structural equation modeling. We found that partner firms’ KMC was positively associated with IO performance. We also found that IO information technology (IOIT) infrastructure capabilities facilitated KMC through the strength of IO relational capability. Partner interdependence was positively associated with IO relational capability and with KMC. Taking a knowledge management (KM) perspective, our research shows that IT requires relational capability and KMC to bring performance gains to IO partnerships. These insights have theoretical importance for understanding IT-enabled knowledge management in IO settings and practical significance for firms to effectively use their IOIT infrastructure.
A Machine Learning Approach to Genome Assessment

This work was supported in part by Mississippi State University's tuition remission program for employees of the University and in part through USDA Agricultural Research Service Agreements 58-6066-6-046 and 58-6066-6-059 and USDA National Institute of Food and Agriculture Multi-State Hatch project 17810.
Reservoir Computing Using Laser Networks

Reservoir computing is a neuromorphic computing scheme inspired by the human brain. It has found great success as a versatile hardware-compatible application of machine learning concepts. In this paper, we highlight the fundamental working principles and important characteristics of reservoir computing with a particular focus on photonic systems and networks. These systems can further be enhanced by the inclusion of delayed variables to produce complex spatiotemporally mixed “time-multiplexed” networks. We use a simple nonlinear oscillator model, that is not only applicable to lasers, but can also describe a variety of other oscillating systems.
AFODSS: Heart Rate Estimation Method From Photoplethysmographic Signals With Motion Artifacts Using Fourier-Sparse Dual Optimization

Precise heart rate (HR) estimation of individuals during physical exercise from PPG sensors using direct methods often produces erroneous output due to the occurrence of exceedingly high motion artifacts (MAs). The effect of MAs can be neutralized using non-direct algorithms such as optimization techniques using some a priori about MA. In this paper, we propose a dual-optimization technique using adaptive Fourier decomposition in conjunction with sparse spectral reconstruction (AFODSS) using a multiple measurement vectors (MMVs) model and a regularized bi-conjugate gradient focal underdetermined system solver (BCG-FOCUSS) algorithm. Using AFODSS, the average absolute error (AAE) of HR obtained on the dataset recorded from 23 subjects during their intense exercise is 1.35 beats/min. The BCG-FOCUSS algorithm used in this paper helps to speed up the convergence rate and reduce time complexity when compared with other FOCUSS algorithms.
Backstepping Control Associated to Modified Space Vector Modulation for Quasi Z-source Inverter Fed by a PEMFC

Received: 4 January 2019 Accepted: 10 March 2019 In this paper, a backstepping control combined with a modified space vector modulation (MSVM) for a quasi z-source inverter (QZSI) fed by a fuel cell is proposed. The QZSI employs a unique impedance network to couple the main circuit of the inverter to a proton exchange membrane fuel cell (PEMFC). This topology provides an attractive single stage DC-AC conversion with buck-boost capability unlike the traditional voltage source inverter (VSI). The MSVM is used to insert the shoot through state within the traditional switching signals in order to boost the inverter input voltage, and to keep the same performances of the traditional SVM. A DC peak voltage controller using backstepping approach is proposed to overcome the fuel cell voltage fluctuations under load changes, and to reduce the inductor current ripples as well. Comprehensive simulations are presented to prove the effectiveness and the performances of the proposed control strategy under different operating conditions.
Data-Oriented Transmission in Future Wireless Systems: Toward Trustworthy Support of Advanced Internet of Things

Future wireless systems will need to support diverse big data and Internet of Things (IoT) applications with diverse quality-of-service (QoS) requirements. Novel designs across the protocol stack are required for effective and efficient QoS provision. We introduce here a unique data-oriented approach for the design and analysis of advanced wireless transmission technologies. In our approach, unlike the conventional channel-oriented approach, we optimally design transmission strategies for individual data-transmission sessions, considering both the QoS requirement and the instantaneous operating environment. The resulting design can effectively satisfy highly stringent performance and efficiency requirements of future wireless applications.