Miracle-dz/UniFAR-FTUs huggingface dataset:
Multifunctional Grid Interactive Solar Photovoltaic Systems: A Comprehensive Review

The multifunctional grid-connected inverter (MFGCIs) has drawn a significant attention among researchers because of its ancillary services such as active power injection into utility grid while also serving as a power quality conditioner. It should be noted that the application of a multifunctional inverter is specifically increased to integrate renewable and sustainable energy sources like solar photovoltaic (SPV) and wind turbine (WT) in distributed energy resources (DERs) and microgrid (MGs) where the aim is to diminish the transmission and distribution losses by generating power at one place and catering the load requirement of nearby localities. In concern to the above, the various configurations used in MFGCIs are presented along with their detailed comparative study. Furthermore, control strategies employed in single and three phase MFGCIs are comprehensively reviewed. In addition, an in-depth illustration, comparison, and discussion on MFGCIs are accomplished. Besides this, the author has also made an attempt to provide a detailed explanation on future scopes of MFGCIs in DERs and MGs.
mmWave Channel Measurements for 3-D Path Loss Analysis and Model Design in Stadiums

A stadium is a multiuser scenario where the wireless system should be able to support real-time service delivery when the stadium is at full capacity during an event. To address radio propagation design for this type of challenging scenario, theoretical and empirical method is needed. Extensive open-space static measurements and research have been conducted at 28 and 60 GHz frequencies in an empty seating area of a stadium with a capacity of 60000 seats. The findings of this work lay a good foundation towards a greater understanding of mmWave channel propagation in a stadium, where a sectorization approach is considered to characterize the path loss behavior in 3D and predict it at unmeasured locations through the Kriging-aided model proposed with only 1 dB RMSE.
Compact High-Efficiency Broadband Rectifier With Multi-Stage-Transmission-Line Matching

This brief proposes a compact high-efficiency broadband microwave rectifier for energy harvesting. The proposed rectifier is designed to operate over a broad bandwidth spanning from 2 to 3 GHz and an input power dynamic range from 0 dBm to 10 dBm. In the proposed structure, a compact broadband low-loss matching network and a dc-pass filter with a broad stopband were designed, leading to a high conversion efficiency in a wide frequency range with compactness. For the matching network, low loss and compact size were achieved by strategically choosing and designing three transmission line segments. Moreover, the proposed dc-pass filter is compact and can effectively block broadband RF signal and its in-band high order harmonics. Theoretical analysis and simulations of the proposed structure were carried out. A prototype was fabricated, which demonstrates a broadband bandwidth of 41.5% (2.0–3.05 GHz) where the RF-dc power conversion efficiency is higher than 70% at an input power of 10 dBm. The measured efficiency remains over 45% within 1.9–3.05 GHz when the input power decreases to 0 dBm. The maximum measured efficiency is 75.8% at an input power of 14 dBm.
Residual Policy Learning Facilitates Efficient Model-Free Autonomous Racing

Motion planning for autonomous racing is a challenging task due to the safety requirement while driving aggressively. Most previous solutions utilize the prior information or depend on complex dynamics modeling. Classical model-free reinforcement learning methods are based on random sampling, which severely increases the training consumption and undermines the exploration efficiency. In this letter, we propose an efficient residual policy learning method for high-speed autonomous racing named ResRace, which leverages only the real-time raw observation of LiDAR and IMU for low-latency obstacle avoiding and navigation. We first design a controller based on the modified artificial potential field (MAPF) to generate a policy for navigation. Besides, we utilize the deep reinforcement learning (DRL) algorithm to generate a residual policy as a supplement to obtain the optimal policy. Concurrently, the MAPF policy effectively guides the exploration and increases the update efficiency. This complementary property contributes to the fast convergence and few required resources of our method. We also provide extensive experiments to illustrate our method outperforms the leading algorithms and reaches the comparable level of professional human players on the five F1Tenth tracks.
Researches on Flow Field's Dynamic Features of Vacuum Switching Arc Based on Optical Flow Field

As a kind of fluid, the motion of vacuum arc is complicated and various. Its structure and distribution have a significant effect on vacuum interrupters’ comprehensive properties. A method to analyze of arc flow field’s dynamic feature based on optical flow is proposed aiming at complicated flow field of vacuum switch arc’s sequence images. In this paper optical flow field’s basic principle is firstly introduced, and then the noise filtering method to process arc images in different stages is used. Finally, the method of optical flow field estimation to obtain pictures of arc flow field’s motion vector feature in the vacuum gap is adopted. According to the results we can find that in the stage of arc striking, the pressure of metal vapor in the vacuum gap is low, accompanied by an expansion of arc and the formation of several parts of eddy current zones. When the arc is going to be extinguished, with the decreasing of the temperature of vacuum arc column center, the arc plasma converges upon its column center instead of expanding, and the parts of eddy current zone shrinks and disappears. At the same time we can see that the method of optical flow field can obtain vacuum arc optical flow field’s dynamic feature effectively to describe arc particle moving direction and size. Target images can also be divided easily, real-timely, and accurately, which provides a new technical mean to analyze the dynamic feature of vacuum arc flow field. Keywords—vacuum arc; arc flow field; optical flow field; eddy current
Numerical Calculation of Three-Dimensional Ground State Potential Energy Function of Na2F System

We present a new three-dimensional global potential energy surface (PES) for the ground state of Na2F system. A total of about 1460 points were generated for the PES. All of the points have been carried out by using the coupled-cluster single-, double-, and perturbative triple-excitations [CCSD(T)]. Two Jacobi coordinates, R and θ , and the frozen molecular equilibrium geometries were used. We mixed the basis sets of aug-cc-pCVQZ for the sodium atom and the basis sets of aug-cc-pCVDZ for the fluorine atom with an additional (3s3p2d) set of midbond functions; the energies obtained were extrapolated to the complete basis set limit. The whole calculation adopted supramolecular approximation approach. We divided the potential energy surface into three regions, the peak region, the well region, and the long range region, and calculate the single point energy, respectively. Our ab initio calculations will be useful for future studies of the collision-induced absorption for the Na2-F dimer, and it can be used for modeling the dynamical behavior in Na2F system too.
Automated Detection of Improper Sitting Postures in Computer Users Based on Motion Capture Sensors

Prolonged computer-related work can be linked to musculoskeletal disorders (MSD) in the upper limbs and improper posture. In this regard, we report on developing resources supporting improper posture studies based on motion capture sensors. These resources were used to create a baseline detector for the automated detection of improper sitting postures, which was next used to evaluate the applicability of Hjorth’s parameters—Activity, Mobility and Complexity—on the specific classification task. Specifically, based on accelerometer data, we computed Hjorth’s time-domain parameters, which we stacked as feature vectors and fed to a binary classifier (kNN, decision tree, linear SVM and Gaussian SVM). The experimental evaluation in a setup involving two different keyboard types (standard and ergonomic) validated the practical worth of the proposed sitting posture detection method, and we reported an average classification accuracy of up to 98.4%. We deem that this research contributes toward creating an automated system for improper posture monitoring for people working on a computer for prolonged periods.
Queering Mormon Spaces: Talking with God, Critical Love, and Structural Reorganization

The Mormon Church, like other religions, discursively produces hostile, anti-LGBTQIA + spaces. This study uses queer theory to explore how sacred and religious spaces are created and navigated by queer members of the Church. Analyzing data from an online survey and in-depth interviews, the findings reveal patterns of divine communication and organizational perceptions that blend together as a powerful discursive production of thirdspaces deemed religious-sacred spaces. By offering structural and discursive solutions to structural White cisheteronormativity in the Church, the final section introduces some possibilities of reorganization for queering Mormon spaces.
Fibrinogen to Albumin Ratio as Early Serum Biomarker for Prediction of Intra-Hospital Mortality in Neurosurgical Intensive Care Unit Patients with Spontaneous Intracerebral Hemorrhage

Background: The prognostic value of the fibrinogen to albumin ratio on intrahospital mortality has been investigated in patients with cardiovascular disease, cancer, sepsis, and ischemic stroke; however, it has not been investigated for neurosurgical patients with spontaneous intracerebral hemorrhage (ICH). The present study investigates the impact of the fibrinogen to albumin ratio upon admission for intrahospital mortality in neurosurgical intensive care unit (ICU) patients with spontaneous ICH. Methods: A total of 198 patients with diagnosis of spontaneous ICH treated from 10/2008 to 12/2017 at our ICU were retrospectively analyzed. Blood samples were drawn upon admission, and the patients’ demographic, medical data, and cranial imaging were collected. Binary logistic regression analysis was performed to identify independent prognostic factors for intrahospital mortality. Results: The total rate of intrahospital mortality was 35.4% (n = 70). In the multivariate regression analysis, higher fibrinogen to albumin ratio (OR = 1.16, CI = 1.02–1.31, p = 0.03) upon admission was an independent predictor of intrahospital mortality in neurosurgical ICU patients with ICH. Moreover, a fibrinogen to albumin ratio cut-off level of >0.075 was related to increased intrahospital mortality (Youden’s index = 0.26, sensitivity = 0.51, specificity = 0.77). Conclusion: A fibrinogen to albumin ratio > 0.075 was significantly associated with increased intrahospital mortality in ICH patients.
Out of the temperate zone: A phylogenomic test of the biogeographical conservatism hypothesis in a contrarian clade of ants

The standard latitudinal diversity gradient (LDG), in which species richness decreases from equator to pole, is a pervasive pattern observed in most organisms. Some lineages, however, exhibit inverse LDGs. Seemingly problematic, documenting and studying contrarian groups can advance understanding of LDGs generally. Here, we identify one such contrarian clade and use a historical approach to evaluate alternative hypotheses that might explain the group's atypical diversity pattern. We focus on the biogeographical conservatism hypothesis (BCH) and the diversification rate hypothesis (DRH).
Study of operation dynamics of building with radiant system

of thesis entitled: Study of Operation Dynamics of Building with Radiant System Submitted by : Hu Rong For the degree of : Doctor of Philosophy at The Hong Kong Polytechnic University in January, 2017. Radiant cooling systems are now widely used throughout the world because they are regarded as suitable mechanisms with numerous advantages in indoor environmental control and energy efficiency. The smaller flow rate required in an accompanied air-conditioning system reduces ductwork dimension, fan size, and energy consumption. The high water temperature in the hydronic system for cooling provides opportunities to directly apply natural low-grade energy sources. Nevertheless, several problems have not been resolved. First, a method that assesses the cooling load for a room with a radiant system has yet to be finalized, and the cooling capacity of a specific category of radiant systems is not fully understood. Both of these issues not only depend on the configuration of radiant system, supply water temperature, and their specific environment, but also relate to the operation strategy. Second, managing radiant system operations remains a concern for many engineers. Several engineers believe that the continuous operation can keep the system running in a steady state and avoid a large amount of transient energy input when the system starts. III Therefore, this thesis investigates the characteristics of radiant systems in dynamic operations through simulation and on-site measurement. It also searches for optimal strategies for different categories of radiant systems, including capillary mats embedded surface cooling system (ESCS) and Polybutylene pipe thermally activated building system (TABS). A typical office building is first assumed for simulation, whose thermal properties must meet the national building regulation and local building energy efficiency standard. The effects of climate conditions and thermal mass on system performances are also considered, and the weather data on both cooling design days and typical days in June in the cities of Beijing and Nanjing are selected. The thermal mass can be varied by changing the concrete layer thickness in the external wall of the assumed building. Six operation strategies are involved in this study, which are separated into two groups according to the operation with or without a thermostat. Finally, three strategies without thermostats are implemented in an existing building. Simulation results reveal significant differences in the system performance between the interior and perimeter zones. The cooling surface reduces the temperature at the inactive surface through radiation heat transfer in the interior zone, which has adiabatic outside faces. Some of the heat gain can be conserved in the inactive surface instead of being removed by the cycling water in the hydronic system. The radiation heat gains, including the solar gain, largely increase in the perimeter zone, whose external construction faces the outdoor environment. Most
Collaborative Robots and Knowledge Management - A Short Review

Abstract Because the requirements of the customers are more and more high related to quality, quantity, delivery times at lowest costs possible, the industry had to come with automated solutions to improve these requirements. Starting from the automated lines developed by Ford and Toyota, we have now developed automated and self-sustained working lines, which is possible nowadays-using collaborative robots. By using the knowledge management system we can improve the development of the future of this kind of area of research. This paper shows the benefits and the smartness use of the robots that are performing the manipulation activities that increases the work place ergonomically and improve the interaction between human - machine in order to assist in parallel tasks and lowering the physically human efforts.
Evaluation of 3T proton MR spectroscopy in the spinal cord – preliminary results

Purpose 1H-magnetic resonance spectroscopy (1H-MRS) is a non-invasive technique that provides information on tissue metabolism and biochemistry. Because of technical difficulties, this method is rarely used in spinal cord examination. The main goal of this study was to develop a routine protocol for MRS of intramedullary lesions. Material and methods A 1H-MRS protocol was set on a group of healthy volunteers. Forty-eight spectra were acquired in total. Thirty of them were acquired in cervical spinal cord, and the remaining 18 spectra were acquired in the thoracic spinal cord. Results In 1H-MRS of the spinal cord one of the most important problems is small voxel size. Mean voxel size in this study was 7 × 9 × 29 mm, which is much smaller than in brain examinations. Finally, almost 60% of spectra were of acceptable quality in volunteer examinations, which enabled the subsequent examinations. Conclusions Challenges of spinal cord spectroscopy were discussed, and the ability of providing additional diagnostic information was proven.
Deep Learning-based Assessment of Oncologic Outcomes from Natural Language Processing of Structured Radiology Reports.

Purpose To train a deep natural language processing (NLP) model, using data mined structured oncology reports (SOR), for rapid tumor response category (TRC) classification from free-text oncology reports (FTOR) and to compare its performance with human readers and conventional NLP algorithms. Materials and Methods In this retrospective study, databases of three independent radiology departments were queried for SOR and FTOR dated from March 2018 to August 2021. An automated data mining and curation pipeline was developed to extract Response Evaluation Criteria in Solid Tumors-related TRCs for SOR for ground truth definition. The deep NLP bidirectional encoder representations from transformers (BERT) model and three feature-rich algorithms were trained on SOR to predict TRCs in FTOR. Models' F1 scores were compared against scores of radiologists, medical students, and radiology technologist students. Lexical and semantic analyses were conducted to investigate human and model performance on FTOR. Results Oncologic findings and TRCs were accurately mined from 9653 of 12 833 (75.2%) queried SOR, yielding oncology reports from 10 455 patients (mean age, 60 years ± 14 [SD]; 5303 women) who met inclusion criteria. On 802 FTOR in the test set, BERT achieved better TRC classification results (F1, 0.70; 95% CI: 0.68, 0.73) than the best-performing reference linear support vector classifier (F1, 0.63; 95% CI: 0.61, 0.66) and technologist students (F1, 0.65; 95% CI: 0.63, 0.67), had similar performance to medical students (F1, 0.73; 95% CI: 0.72, 0.75), but was inferior to radiologists (F1, 0.79; 95% CI: 0.78, 0.81). Lexical complexity and semantic ambiguities in FTOR influenced human and model performance, revealing maximum F1 score drops of -0.17 and -0.19, respectively. Conclusion The developed deep NLP model reached the performance level of medical students but not radiologists in curating oncologic outcomes from radiology FTOR.Keywords: Neural Networks, Computer Applications-Detection/Diagnosis, Oncology, Research Design, Staging, Tumor Response, Comparative Studies, Decision Analysis, Experimental Investigations, Observer Performance, Outcomes Analysis Supplemental material is available for this article. © RSNA, 2022.
The Transcription Factors TaTDRL and TaMYB103 Synergistically Activate the Expression of TAA1a in Wheat, Which Positively Regulates the Development of Microspore in Arabidopsis

Pollen fertility plays an important role in the application of heterosis in wheat (Triticum aestivum L.). However, the key genes and mechanisms underlying pollen abortion in K-type male sterility remain unclear. TAA1a is an essential gene for pollen development in wheat. Here, we explored the mechanism involved in its transcriptional regulation during pollen development, focusing on a 1315-bp promoter region. Several cis-acting elements were identified in the TAA1a promoter, including binding motifs for Arabidopsis thaliana AtAMS and AtMYB103 (CANNTG and CCAACC, respectively). Evolutionary analysis indicated that TaTDRL and TaMYB103 were the T. aestivum homologs of AtAMS and AtMYB103, respectively, and encoded nucleus-localized transcription factors containing 557 and 352 amino acids, respectively. TaTDRL and TaMYB103 were specifically expressed in wheat anthers, and their expression levels were highest in the early uninucleate stage; this expression pattern was consistent with that of TAA1a. Meanwhile, we found that TaTDRL and TaMYB03 directly interacted, as evidenced by yeast two-hybrid and bimolecular fluorescence complementation assays, while yeast one-hybrid and dual-luciferase assays revealed that both TaTDRL and TaMYB103 could bind the TAA1a promoter and synergistically increase its transcriptional activity. Furthermore, TaTDRL-EAR and TaMYB103-EAR transgenic Arabidopsis plants displayed abnormal microspore morphology, reduced pollen viability, and lowered seed setting rates. Additionally, the expression of AtMS2, a TAA1a homolog, was significantly lower in the two repressor lines than in the corresponding overexpression lines or WT plants. In summary, we identified a potential transcriptional regulatory mechanism associated with wheat pollen development.
Early Teacher–Child Relationships Promote Self-Regulation Development in Prekindergarten

Children’s experiences during the prekindergarten period are critical for shaping their emerging self-regulation skills. The purpose of this study was to examine the contribution of teacher–child relationship quality to children’s performance on a self-regulation task at the end of prekindergarten. Teachers rated the conflict, closeness, and dependency in their relationships with 104 children in the fall of prekindergarten, and children’s self-regulation was independently measured with a visual attention task in the spring of prekindergarten. In addition, teachers and parents rated children’s temperamental self-regulation (i.e., effortful control). Results indicate that greater teacher–child dependency predicted children’s longer time on the visual attention task, and greater teacher–child closeness predicted children’s lower accuracy on the visual attention task. In addition, children who were rated as more self-regulated by parents were more accurate on the visual attention task. The implications of the results are discussed.
Silicon-photonic interferometric biosensor using active phase demodulation

Silicon photonics is becoming a consolidated technology, mainly in the telecom/datacom sector, but with a great potential in the chemical and biomedical sensor market too, mainly due to its CMOS compatibility, which allows massfabrication of huge numbers of miniaturized devices at a very low cost per chip. Integrated photonic sensors, typically based on resonators, interferometers, or periodic structures, are easy to multiplex as the light is confined in optical waveguides. In this work, we present a silicon-photonic sensor capable of measuring refractive index and chemical binding of biomolecules on the surface, using a low-cost phase interrogation scheme. The sensor consists of a pair of balanced Mach-Zehnder interferometers with interaction lengths of 2.5 mm and 22 mm, wound to a sensing area of only 500 μm x500 μm. The phase interrogation is performed with a fixed laser and an active phase demodulation approach based on a phase generated carrier (PGC) technique using a phase demodulator integrated within the chip. No laser tuning is required, and the technique can extract the univocal phase value with no sensitivity fading. The detection only requires a photo-receiver per interferometer, analog-to-digital conversion, and simple processing performed in real-time. We present repeatable and linear refractive index measurements, with a detection limit down to 4.7·10-7 RIU. We also present sensing results on a chemically-functionalized sample, where anti-BSA to BSA (bovine serum albumin) binding curves are clearly visible for concentrations down to 5 ppm. Considering the advantages of silicon photonics, this device has great potential over several applications in the chemical/biochemical sensing industry.