Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative Analysis of CO2 Uptake and Mechanical Properties of Air Lime-Based Materials

In the cement industry, utilization of a sustainable binder that has a lower energy consumption and carbon dioxide (CO2) emission than Portland cement is becoming increasingly important. Air lime is a binder that hardens by absorbing CO2 from the atmosphere, and its raw material, hydrated lime, is manufactured at a lower temperature (around 900 °C) than cement (around 1450 °C). In this study, the amount and rate of CO2 uptake by air lime-based materials are quantitatively evaluated under ambient curing conditions of 20 °C, 60% relative humidity, and 0.04% CO2 concentration. In addition, the effects of the water-to-binder ratio (w/b) and silica fume addition on the material properties of the air lime mortar, such as strength, weight change, carbonation depth, and pore structure, are investigated. Unlike hydraulic materials, such as Portland cement, the air lime mortar did not set and harden under a sealed curing condition, however, once exposed to dry air, the mortar began to harden by absorbing CO2. During the first week, most of the internal water evaporated, thus, the mortar weight was greatly reduced. After that, however, both the weight and the compressive strength consistently increased for at least 180 days due to the carbonation reaction. Based on the 91-day properties, replacing 10% of hydrated lime with silica fume improved the compressive and flexural strengths by 27% and 13% respectively, whereas increasing the w/b from 0.4 to 0.6 decreased both strengths by 29% due to the increased volume of the capillary pores. The addition of silica fume and the change in the w/b had no significant impact on the amount of CO2 uptake, but these two factors were effective in accelerating the CO2 uptake rate before 28 days. Lastly, the air lime-based material was evaluated to be capable of recovering half of the emitted CO2 during the manufacture of hydrated lime within 3 months.
A Novel Spoke-Type PM Machine Employing Asymmetric Modular Consequent-Pole Rotor

This paper proposes a novel spoke-type permanent magnet (PM) machine, which adopts asymmetric modular consequent-pole (AMCP) rotor to enhance the effective PM flux due to the increased flux-focusing effect and reduced leakage flux and to improve the flux-weakening capability due to the increased d-axis inductance. Moreover, the pole-shaping method based on three sectional arcs is proposed to suppress the harmonics of airgap flux density. Since the rotor structure is relatively complex, the finite-element analysis together with multiobjective genetic algorithm is adopted to optimize this design. Furthermore, the electromagnetic performance of the spoke-type PM machine with the proposed AMCP rotor (Spoke-AMCP), including the open-circuit airgap flux density, phase back electromotive force, torque, PM utilization ratio, efficiency, and flux-weakening capability, are compared with two conventional spoke-type PM machines with evenly distributed and alternate flux barriers (Spoke1 and Spoke2) and consequent-pole spoke-type PM machine (Spoke-CP). It is demonstrated that the Spoke-AMCP machine obtains the largest output torque and PM utilization ratio, lowest torque ripple and similar efficiency compared to Spoke1, Spoke2 and Spoke-CP machines. Moreover, although the Spoke-AMCP machine has the largest PM flux linkage, it has slightly better flux-weakening capability than the Spoke1 and Spoke2 machines. Finally, a 12-slot/10-pole Spoke-AMCP machine is built and tested to verify the analyses.
Non-Network Solution Coordinated Voltage Stability Enhancement With STATCOM and UVLS for Wind-Penetrated Power System

This paper proposes an effect orientated approach to enhance the short-term voltage stability for wind-penetrated power systems. The low system stability with high uncertain renewable energy is addressed by coordination of network and non-network solutions, i.e., STATCOM placement and UVLS respectively in this paper. The proposed model considers the uncertainties of power systems, including operating points load dynamics and multiple contingencies. Unlike other methods that try to minimize the cost, the proposed method aims to maximize the voltage stability enhancement with a fixed cost. The high computing burden is alleviated by a net flow-based scenario reduction algorithm. Compared with the conventional approaches, this paper has three major contributions: 1) Device placement is coordinated with demand response. 2) Operating points and type 4 wind turbines are considered. 3) An effect maximizing DP algorithm with a robust scenario reduction method is applied. The effectiveness and efficiency of the proposed method is demonstrated on the New England 39-bus test system.
Propulsion System Modelling for Multi-Satellite Missions Performed by Nanosatellites

Abstract Progress in miniaturization of satellite components allows complex missions to be performed by small spacecraft. Growing interest in the small satellite sector has led to development of standards such as CubeSat, contributing to lower costs of satellite development and increasing their service competitiveness. Small satellites are seen now as a prospective replacement for conventional sized satellites in the future, providing also services for demanding users. New paradigms of multi-satellite missions such as fractionation and federalization also open up new prospects for applications of small platforms. To perform a comprehensive simulation and analysis of future nanosatellite missions, an adequate propulsion system model must be used. Such model should account for propulsion solutions which can be implemented on nanosatellites and used in multi-satellite missions. In the paper, concepts of distributed satellite systems (constellations, formations, fractionated and federated) are described with a survey of past, on-going and planned multi-satellite nanosatellites missions. Currently developed propulsion systems are discussed and the models of propulsion systems embedded in the WUT satellite simulation model are presented.
Gamma Radiation Induced Effects on the Performance of Piezoresistive Pressure Sensors Fabricated Using Different Technologies

We have carried out experimental investigation of the effect of gamma radiation on the performance of piezoresistive pressure sensors realized using different fabrication processes. These processes included standard diffused piezoresistor process, silicon-on-insulator (SOI) wafer based process, and polysilicon piezoresistor based process. The pressure sensors were irradiated in a 60Co gamma chamber up to a total dose of 30 Mrad(Si). The sensors were characterized after different total dose exposures to measure the sensitivity, offset voltage, and hysteresis. All three types of sensors did not show failure up to the studied dose of 30 Mrad(Si). The sensors fabricated using diffused piezoresistor based and polysilicon piezoresistor based processes have shown insignificant change in the sensitivity. However, a significant change in the sensitivity (~13%) and offset voltage (~9%) was observed for the SOI wafer-based pressure sensor. The comparison of the gamma-induced degradation of three types of sensors shows that the polysilicon piezoresistor-based sensor has the best radiation hardness as it exhibits <1% degradation of the sensitivity, offset voltage, and hysteresis for gamma radiation exposure of 30 Mrad(Si).
Recent Advances and Changing Face of Anatomy Teaching and Learning in Medical Education

Background A sound knowledge of human anatomy is a major requirement for being a good physician or a practicing surgeon. Despite digitalization and modernization of education sector, traditional cadaveric dissection still occupies the leadership of anatomy education. It is becoming an untold truth that no modern technologies such as virtual dissection or 3D model printing could replace cadaveric dissection in its way of teaching students. Methods Recent research studies on modern anatomical teaching methods for medical and non-medical students and their influences are reviewed. Results Despite new technologies, traditional cadaveric dissection helps students to acquire more practical knowledge and still occupies prior position on its way.
Position Control of Parallel Active Link Suspension With Backlash

In this article, a position control scheme for the novel parallel active link suspension (PALS) with backlash is developed to enhance the vehicle ride comfort and road holding. A PALS-retrofitted quarter car test rig is adopted, with the torque flow and backlash effect on the suspension performance is analyzed. An elastic linear equivalent model of the PALS-retrofitted quarter car, which bridges the actuator position and the equivalent force between the sprung and unsprung masses, is proposed and mathematically derived, with both the geometry and backlash nonlinearities compensated. A position control scheme is then synthesized, with an outer loop H$_{\infty}$ control for ride comfort and road holding enhancement and an inner loop cascaded proportional-integral control for the reference position tracking. Experiments with the PALS-retrofitted quarter car test rig are performed over road cases of a harmonic road, a smoothed bump, and frequency swept road excitation. As compared to a conventional torque control scheme, the newly proposed position control maintains the performance enhancement by the PALS, while it notably attenuates the overshoot in the actuator's speed variation, and thereby it benefits the PALS with less power demand and less suspension deflection increment.
ON-Resistance in Vertical Power FinFETs

This paper presents the first analytical model for the ON-resistance (<inline-formula> <tex-math notation="LaTeX">${R}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula>) in vertical power FinFETs. The model allows to extract the channel mobility and series resistance and to separate the current conduction through the bulk fin channel and the accumulation-mode metal–oxide–semiconductor (MOS) channel. The model was validated by experiments and simulations. The extracted series resistance was verified by measuring a diode fabricated in the same wafer with the FinFETs. At the same time, simulations using the extracted channel mobility and series resistance agreed well with the experiments. The model was then used to analyze a 1200 V GaN vertical power FinFET. The main <inline-formula> <tex-math notation="LaTeX">${R}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula> component was identified to be from the drift layer and the substrate, while the gate-modulated channel resistance only accounts for ~13% of the total device <inline-formula> <tex-math notation="LaTeX">${R}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula>. Our model enables parameter extraction from the dc characteristics of a single device, and therefore, provides a fast and easy way to understand, analyze, and design vertical power FinFETs. Our model can also be adjusted to allow for fast and accurate parameter extraction in other power transistors with a vertical gate-modulated channel, such as trench MOSFETs.
Fault Diagnosis in Microelectronics Attachment Via Deep Learning Analysis of 3-D Laser Scans

A common source of defects in manufacturing miniature printed circuits boards (PCBs) is the attachment of silicon die or other wire bondable components on a liquid-crystal polymer substrate. Typically, a conductive glue is dispensed prior to attachment with defects caused either by insufficient or excessive glue. The current practice in electronics industry is to examine the deposited glue by a human operator a process that is both time consuming and inefficient especially in preproduction runs where the error rate is high. In this article, we propose a system that automates fault diagnosis by accurately estimating the volume of glue deposits before and even after die attachment. To this end, a modular scanning system is deployed that produces high-resolution point clouds whereas the actual estimation of glue volume is performed by (R)egression-Net (RNet), a three-dimensional (3-D) convolutional neural network (3DCNN). RNet outperforms other deep architectures and is able to estimate the volume either directly from the point cloud of a glue deposit or more interestingly after die attachment when only a small part of glue is visible around each die. The entire methodology is evaluated under operational conditions where the proposed system achieves accurate results without delaying the manufacturing process.
Collaborative and Participatory Design: Assignment of Team Members to Engineering Projects with the Consideration of Designer’s Expectations

With the trend of global collaboration and development of Internet of Things in industry 4.0, the collaboration relationships between designers is getting more close and important than before. Therefore, when project manager assign designers to design projects, it is very important for them to select design projects with the consider about the expectations of the designers regarding the different projects and collaboration ability for the designers in the projects while it is very important to identify the projects with the consideration of skills, experiences, availabilities and so on. Even though, there are various methods for selecting projects, most of these methods not consider about the expectations of designer and the collaboration ability. Therefore, in this paper, we propose a project selection methodology, which consider about the designers’ expectations to the candidate multi-project and collaboration ability in the candidate multi-project. The main objective of our research is to help project manager to find an adaptable and comfortable multi- project to the designer.
Low-frequency noise suppression for desert seismic data based on a wide inference network

The importance of seismic exploration has been recognized by geophysicists. At present, low-frequency noise usually exists in seismic exploration, especially in desert seismic records. This low-frequency noise shares the same frequency band with effective signals. This leads to the limitation or failure of traditional methods. In order to overcome the shortcomings of traditional denoising methods, we propose a novel desert seismic data denoising method based on a Wide Inference Network (WIN). The WIN aims to minimize the error between the prediction and target by residual learning during training, and it can obtain a set of optimal parameters, such as weights and biases. In this article, we construct a high-quality training set for a desert seismic record and this ensures the effective training of a WIN. In this way, each layer of the trained WIN can automatically extract a set of time–space characteristics without manual adjustment. These characteristics are transmitted layer by layer. Finally, they are utilized to extract effective signals. To verify the effectiveness of the WIN, we apply it to synthetic and real desert seismic records, respectively. In addition, we compare WIN with f – x deconvolution, variational mode decomposition (VMD) and shearlet transform. The results show that WIN has the best denoising performance in suppressing low-frequency noise and preserving effective signals.
Impact of Information and Communication Technology Limitations on Microgrid Operation

This paper provides an extensive review of the conducted research regarding various microgrids (MGs) control techniques and the impact of Information Communication Technology (ICT) degradation on MGs performance and control. Additionally, this paper sheds the light on the research gaps and challenges that are to be explored regarding ICT intrinsic-limitations impact on MGs operations and enhancing MGs control. Based on this assessment, it offers future prospects regarding the impact of ICT latencies on MGs and, consequently, on the smart grid. Finally, this paper introduces a case study to show the significance and examine the effect of wireless communication technologies latency on the converters and the DC bus voltage of a centralized controlled DC MG. A DC microgrid with its communication-based control scheme was modeled to achieve this goal. The MATLAB simulation results show that the latency impact may be severe on the converter switches and the DC bus voltage. Additionally, the results show that the latency impact varies depending on the design of the MG and its operational conditions before the latency occurs.
Retaining users after privacy invasions

The purpose of this paper is to facilitate understanding of how to mitigate the privacy concerns of users who have experienced privacy invasions. ,Drawing on the communication privacy management theory, the authors developed a model suggesting that privacy concerns form through a cognitive process involving threat-coping appraisals, institutional privacy assurances and privacy experiences. The model was tested using data from an empirical survey with 913 randomly selected social media users. ,Privacy concerns are jointly determined by perceived privacy risks and privacy self-efficacy. The perceived effectiveness of institutional privacy assurances in terms of established privacy policies and privacy protection technology influences the perceptions of privacy risks and privacy self-efficacy. More specifically, privacy invasion experiences are negatively associated with the perceived effectiveness of institutional privacy assurances. ,Privacy concerns are conceptualized as general concerns that reflect an individual’s worry about the possible loss of private information. The specific types of private information were not differentiated. ,This paper is among the first to clarify the specific mechanisms through which privacy invasion experiences influence privacy concerns. Privacy concerns have long been viewed as resulting from individual actions. The study contributes to literature by linking privacy concerns with institutional privacy practice.
Calculated rotational and ro-vibrational transitions in the spectrum of H3+

New calculations of line strengths and transition frequencies for the forbidden rotational spectrum and the nu2 fundamental rovibrational band of H3(+) are presented. These first principles calculations use the highly accurate ab initio electronic potential energy surface of Meyer, Botschwina, and Burton (1986), which has previously been shown by the authors to give rovibrational transition frequencies, rotational constants and vibrational fundamentals of spectroscopic accuracy. The line strengths calculated for the pure rotational spectrum in the vibrational ground state are in general agreement with those previously predicted by Pan and Oka (1986), although individual line strengths may differ by as much as 50 percent. The data are presented to assist with the interstellar detection of this astrophysically important molecular ion. 25 references.
Path loss compensated beam switchable antennas with spatially modulated zero‐index metamaterial loading for 5G base stations

To achieve a uniform illumination on the ground in the context of an indoor millimetre-wave 5G base station, path loss compensation is necessary. The gains of the antenna radiating at ±45° require an additional gain of 3 dB to compensate for the additional path loss to maintain the same link budget at those angles. Thus, to enhance the end-fire gain with minimal electrical footprint, spatially modulated zero-index metamaterial is proposed and integrated with a tapered slot antenna. The antenna post integration is analysed for the phase correction of the wavefront leading to a gain of 8.5 dBi and aperture efficiency of 77% at 28 GHz. A co-polarised vertical stacking topology is proposed to achieve path loss compensated beam switchable antennas with an angular coverage of ±65° and mutual coupling <30 dB throughout the band. Detailed simulated and measured results are presented and are in good agreement.
7-Bit Multilayer True-Time Delay up to 1016ps for Wideband Phased Array Antenna

We present a seven-bit multilayer true-time delay (TTD) circuit operating from 1 to 7 GHz for wideband phased array antennas. By stacking advanced substrates with low dielectric loss, the TTD with PCB process is miniaturized and has low insertion loss. The signal vias with surrounding ground vias are designed to provide impedance matching throughout the band, allowing the overall group delay to be flat. The standard deviation of the TTD for all states is below 19 ps, which is 1.87% of the maximum group delay. The maximum delay is 1016 ps with resolution of 8 ps. The implemented TTD is 36.6× 19.4 mm2 and consumes 0.65 mW at 3.3 V supply for all the delay states. The measured input/output return loss is better than 12.1 dB for the band of 1–7 GHz. key words: true-time delay, wideband phased array, multilayer PCB, signal via
PFCN: a fully convolutional network for point cloud semantic segmentation

It is a challenging task to use deep learning methods to understand point cloud data and assign semantics due to the complexity of point cloud data structure. In this Letter, a fully convolutional network is designed by the authors to perform point cloud semantic segmentation. The proposed network based on PointNet++ takes point cloud data as input and predicts a semantic label for each point. Their network consists of three parts. In the first, different scale features are extracted, the second part reduces the extracted features and then fuses them, and in the third part, more structural information of the point cloud is preserved by up-sampling with deconvolution to reconstruct the point cloud. They have carried out part segmentation and semantic segmentation of ShapeNet and S3DIS datasets, respectively, and the validity of the network has been verified.
Analysis and Design of Ultra-Large Dynamic Range CMOS Transimpedance Amplifier With Automatically-Controlled Multi-Current-Bleeding Paths

In this paper, a fully-integrated transimpedance amplifier with ultra-large dynamic range and automatic gain control function is presented. By first deploying three AGC-controlled current paths in the low noise pre-amplifier, the transimpedance amplifier (TIA) can accommodate a significantly enlarged input current. Meanwhile, the range of automatic transimpedance adjustment is enhanced utilizing the automatic gain control (AGC) circuit, tunable pre-amplifier (PrA), and variable gain amplifier (VGA). Besides the above blocks, the TIA with a size of <inline-formula> <tex-math notation="LaTeX">$1.26\times 1.33$ </tex-math></inline-formula> mm<sup>2</sup> also integrates level shifter, post-amplifier, buffer, DC offset cancellation (DCOC), bandgap reference (BGR), and low-dropout regulator (LDO). With a single 3.3-V external supply voltage, the fully integrated TIA in <inline-formula> <tex-math notation="LaTeX">$0.11~\mu \text{m}$ </tex-math></inline-formula> CMOS achieves a measured input dynamic range up to 7.4 mA@2.5 Gb/s, an input referred noise as low as 137.3 nA and a differential trans-impedance gain of 10 <inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula>. Taking the bandwidth, dynamic range, and trans-impedance gain into account, the fabricated CMOS TIA demonstrates the largest input dynamic range with maintaining competitive comprehensive performance.
WikiBridge: a Semantic Wiki for Archaeological Applications

This paper details the main concepts and the architecture of WikiBridge, a semantic wiki, developed for the project CARE (Corpus Architecturae Religiosae Europeae – IV-X saec.). The aim of the project CARE is the constitution of integrated corpus of the European Christian buildings dated from the 4th to the beginning of the 11th century. A semantic wiki, called WikiBridge, is developed in order to: 1) allow collaborative work of researchers involved in the project and 2) open the corpus to a large public. WikiBridge combines collaborative and traceability aspects of wiki with semantic consistency and query capabilities. Semantics is guaranteed by an application ontology based on CIDOC-CRM.