Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability analysis and control for composite tape winding process

In the composite winding process of thermal protection materials, the thickness errors of prepreg tape will result in an unstable winding process. In order to alleviate this problem, a control system is required. Therefore, a winding control system had been designed to control the stability by eliminate the winding error based on the analysis of stability winding process. The control system consists a speed controlled rotational roller. The thickness errors of the tape can be detected, and the rotational roller can be controlled to eliminate the errors and maintain the stability of winding process. Experimental results illustrate that the winding speed is converged in 30 second with a 30% initial thickness error, and winding control system could maintain the stability of winding process.
Flower-Shaped C-Dots/Co3O4{111} Constructed with Dual-Reaction Centers for Enhancement of Fenton-Like Reaction Activity and Peroxymonosulfate Conversion to Sulfate Radical

Novel flower-shaped C-dots/Co3O4{111} with dual-reaction centers were constructed to improve the Fenton-like reaction activity and peroxymonosulfate (PMS) conversion to sulfate radicals. Due to the exposure of a high surface area and Co3O4{111} facets, flower-shaped C-dots/Co3O4{111} could provide more Co(II) for PMS activation than traditional spherical Co3O4{110}. Meanwhile, PMS was preferred for adsorption on Co3O4{111} facets because of a high adsorption energy and thereby facilitated the electron transfer from Co(II) to PMS. More importantly, the Co–O–C linkage between C-dots and Co3O4{111} induced the formation of the dual-reaction center, which promoted the production of reactive organic radicals (R•). PMS could be directly reduced to SO4−• by R• over C-dots. On the other hand, electron transferred from R• to Co via Co–O–C linkage could accelerate the redox of Co(II)/(III), avoiding the invalid decomposition of PMS. Thus, C-dots doped on Co3O4{111} improved the PMS conversion rate to SO4−• over the single active site, resulting in high turnover numbers (TONs). In addition, TPR analysis indicated that the optimal content of C-dots doped on Co3O4{111} is 2.5%. More than 99% of antibiotics and dyes were degraded over C-dots/Co3O4{111} within 10 min. Even after six cycles, C-dots/Co3O4{111} still remained a high catalytic activity.
Flexible selections at 30 MHz in the LHCb Upgrade trigger

The first LHCb upgrade will take data at an instantaneous luminosity of 2 × 1033cm−2s−1 starting in 2022. Due to the high rate of beauty and charm signals LHCb has chosen as its baseline to read out the entire detector into a software trigger running at the LHC collision frequency of 30 MHz. This High Level Trigger (HLT) will enable unprecedented flexibility for trigger selections. To provide a flexible trigger, the key features of the trigger selection framework are discussed here as well as the current performance.
Wireless Energy Transfer in Extra-Large Massive MIMO Rician Channels

In application scenarios such as Internet of Things, a large number of energy receivers (ERs) exist and line-of-sight (LOS) propagation could be common. Considering this, we investigate wireless energy transfer (WET) in extra-large massive MIMO Rician channels. We derive analytical expressions of the received net energy for different schemes, including 1) training-based WET, where the ER sends beacon signal for channel training and the energy transmitter (ET) uses the channel estimate for energy beamforming, 2) LOS beamforming, where the ET transmits to the LOS direction of the ER, and 3) energy harvesting, which allows an ER to harvest the training energy from the other ERs. We derive a path loss threshold for switching between training and LOS beamforming-based WET. We further show that the WET scheme selection of one ER is not affected by the other ERs, and the energy harvested from training is minimal in practice. With these insights, we propose an algorithm for the multi-ER scenario, which minimizes the power consumption by iteratively updating the WET scheme selection and power allocation for all ERs. Simulations show that the proposed algorithm achieves near-optimal performance as compared to exhaustive searching, while with much lower implementation complexity.
Application of deep eutectic solvents combined with vortex assisted dispersive liquid-liquid microextraction for five organophosphorus pesticides in juice and green tea beverage

In this study, a new microextraction method based on hydrophobic deep eutectic solvents was developed for the extraction and preconcentration of organophosphorus pesticides from beverage samples. The hydrophobic deep eutectic solvents were synthesized from choline chloride and 4-chlorophenol. Main experimental parameters of the microextraction method were investigated to improve the extraction efficiency. The proposed method achieved a satisfactory linear range between 50 and 2,000 μg L−1 with coefficient of determination greater than 0.9939. The extraction recoveries and enrichment factor of five organophosphorus pesticides at three added levels ranged from 71.68 to 113.18% and 71.43–111.11 were obtained with the acceptable relative standard deviation ranged from 1.37 to 11.92%. Limits of detection and quantification were found to be 0.05–0.3 μg L−1 and 0.17–1 μg L−1, respectively. Finally, the methods were successfully applied for the determination of five organophosphorus pesticide in orange juice and green tea.
Exploring how Prize Challenges Complement an Organization's Innovation Efforts

Increasingly, organizations use prize challenges to innovate: broadcasting a technology problem widely in hopes of getting useful solutions from the crowd. To better understand this tool for innovation, scholars have explored how the crowd solves the problem posed to them. However, less attention has been paid to the interaction between challenges and organizations’ existing innovation processes. To address this gap, we studied the formulation, launch, execution, and outcomes of an important success in NASA’s open innovation ecosystem: the 3D Printed Habitat Challenge (3DPH). As part of that study, we summarize the analytical chronology of our case in this paper. It illustrates how the 3D Printed Habitat Challenge (3DPH) was designed to complement ongoing efforts in NASA’s additive construction ecosystem. We also describe how this case opens the door to new questions in our understanding of prize challenges.
A Systematic Review of the Use of Serious Games in Science Education

The aim of this study was to conduct a systematic literature review on the use of serious games in science education between 2016 and 2020 years. A total of 39 articles were included from Science Citation Index- Expanded (SCI-Expanded), Social Science Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI) and Emerging Sources Citation Index (ESCI) listed in the Web of Science database. The results showed that experiential science was the most emphasized subject area in the articles. The results also indicated that learning/academic achievement was the common examined topic in the articles. For the research designs, more than half of the articles implemented quantitative research design. Considering the data collection tools, achievement tests were the most used data collection tool. Regarding the use of sampling methods, convenience sampling was preferred in more than half of the articles. Secondary and primary school students were the most used sampling groups. The sample size of 31-100-person group was commonly chosen in the articles. Considering the data analysis methods, a majority of articles implemented descriptive analyses methods. It was also found that computer game was the most used game type. Regarding the game genres, adventure was the most preferred one in serious games.
Switch-Based High Cardinality Node Detection

The detection of supernodes with high cardinality is of interest for network monitoring and security. Existing schemes for supernode detection rely on data structures that are independent of the switching functions. This means that for each packet that traverses the switch, both the switching table and the supernode detection structure have to be checked which requires significant memory bandwidth. This can create a bottleneck and reduce the speed of the switch, especially for software implementations. In this letter, a scheme that performs supernode detection as part of Ethernet switching and does not require additional memory accesses nor separated data structures is presented. The scheme has been implemented and compared with the existing methods. The results show that the proposed scheme can reliably identify supernodes while providing a speed up of more than 15% when compared with the existing solutions.
Lithium-Ion Model Behavior in an Ethylene Carbonate Electrolyte Using Molecular Dynamics

The performance of lithium-ion batteries is strongly dependent on the nature of the electrolyte, and a better understanding of the role of the electrolyte in ion transport and the formation of the solid–electrolyte interface is critical for the performance improvement of such batteries. New cathode and anode materials demand new and/or improved electrolytes that are less sensitive to operating conditions and provide higher conductivity and mobility of ions between electrodes. A clear understanding of the solvation of electrolytes in solvents is essential for improving the performance and cycle life of Li-ion batteries. In this work, the behavior of lithium hexafluorophosphate (LiPF6) in ethylene carbonate was characterized using classical molecular dynamics simulations and ab initio density functional theory (DFT) calculations. The solvation structures of both Li+ and PF6– in the electrolyte were analyzed in detail, and the intermolecular and intramolecular potentials were found to produce all of the esse.
Rolling bearing fault diagnosis based on GMCP sparse enhanced signal decomposition and TFM

This paper presents a rolling bearing fault diagnosis method based on GMCP sparse enhancement signal decomposition and TFM. First, algorithm use the non-convex penalty function that not only increases the sparsity but also maintains the convexity of the cost function, that is, the characteristics of the generalized maximum minimum concave penalty (GMCP) to obtain a more accurate estimate. Then the time-frequency manifold (TFM) is used to process the signal. The advantage of TFM is its powerful noise reduction performance to reduce the noise of the signal. Finally, the fault frequency is extracted to realize the fault diagnosis of the rolling bearing. Through the analysis of experimental data, the excellent performance and application value of the proposed method in the diagnosis of rolling bearings are confirmed.
Does prenatal anxiety or depression symptoms are associated with asthma or atopic diseases throughout the offspring’s childhood? An updated systematic review and meta-analysis

BackgroundAsthma is the most common respiratory disease among children, while atopic diseases such as atopic dermatitis affect about 20% of infants under 2 years old. Recently, studies suggest that they may all be related to prenatal depression or anxiety, but further research and analysis are needed. This study aimed to explore the association between prenatal mental disorders and childhood asthma or atopic disease in a systematic review and meta-analysis of nine studies. MethodsPubMed, Embase, and Cochrane Library were searched up to May 2020. The primary outcome was childhood asthma and childhood atopic dermatitis. Random-effects models were used because of high heterogeneity indicated by I2 >50% and Q-test P<0.10. ResultsA total of 598 studies were initially identified, but nine studies met the inclusion criteria. Prenatal mental disorder was associated with childhood asthma (n=6 studies; ES=1.146, 95%CI: 1.054-1.245, P=0.001; I2=93.5%, Pheterogeneity<0.001) whereas no significant association was found for childhood atopic dermatitis (n=4 studies; ES=1.211, 95%CI: 0.982-1.494, P=0.073; I2=78.5%, Pheterogeneity<0.001). Childhood asthma seems to be related more to depression (n=1 study; ES=1.170, 95%CI: 1.061-1.291, P=0.002) and anxiety/depression (n=4 studies; ES=1.157, 95%CI: 1.050-1.275, P=0.073; I2=95.3%, Pheterogeneity<0.001). ConclusionThis meta-analysis demonstrated that prenatal mental disorders increase the risk of childhood asthma. We limited the included samples to pregnant women to investigate the association between prenatal psychological factors and offspring’s physical health. Future studies should include large high-quality cohort studies to investigate the behavioral, environmental, and genetic causes for this association.
Gas Sensor and its Development

Gas sensors are classified into electrical, optical, electrochemical sensors and the others according to their mechanism of work. The working mechanism and the detecting range and the features of various gas sensors are discusses in the issue. It also discusses the development in discovering new gas elements, making new gas sensors of integrated elements and multifunction, researching the structure and working mechanism of gas sensors. The developing trends of gas detectors on smaller, more intelligent and more common in detected gases, detecting range and detecting ways are put forward in the article.
eGFR Decline after SGLT2 Inhibitor Initiation: The Tortoise and the Hare Reimagined.

Sodium-glucose cotransporter 2 inhibitors (SGLT2is) have emerged as an effective class of medications to treat CKD and heart failure. SGLT2is improve cardiovascular outcomes in patients with type 2 diabetes mellitus (1⇓–3) and in those with heart failure with reduced ejection fraction (4⇓⇓–7). Moreover, they have been shown to attenuate kidney disease progression in patients with proteinuric CKD, irrespective of diabetes status (8,9). The rapid uptake of SGLT2is into practice necessitates a careful understanding of their risks. Furthermore, clinicians need to know what to expect when prescribing these agents, including an early decline in eGFR after initiation. We aim to put this observation into context, while providing clinicians with a practical approach to managing this scenario. The suggested mechanism of action of the SGLT2is has previously been described (10). These drugs inhibit sodium and glucose reabsorption in the proximal tubule, leading to increased sodium and chloride delivery to the macula densa. This results in afferent arteriolar vasoconstriction secondary to adenosine-mediated myogenic activation, leading to a reduction in the intraglomerular pressure and the GFR (10). Therefore, it is not surprising that the major SGLT2i outcome trials have reported an early decline in eGFR (around 3–6 ml/min per 1.73 m2) shortly after initiating these drugs compared with placebo controls (5,8,9,11,12). These early declines or dips were typically observed at 2–4 weeks after initiation of the SGLT2i, with subsequent partial recovery of the eGFR curve by week 12, and, ultimately, followed by an attenuation of the slope of eGFR decline compared with placebo controls after 52 weeks (Table 1). View this table: Table 1. Randomized controlled trials reporting an initial dip of eGFR How can we reconcile early dips in eGFR with long-term nephroprotection? Maladaptive glomerular hemodynamics play a central …
Three-Dimensional Thermohaline Characteristics of Luzon Cold Eddy with Double-Eddies Structure

A high-resolution three-dimensional thermo-salt-current numerical model was established to study the structure, and evolution of the Luzon cold eddies (LCEs) based on FVCOM. Study findings showed that, because of the double-eddies structure of LCEs, the isotherm and isohaline show the special characteristics of rising on both sides and falling down between them.
Numerical calculation of laser welds nanocomposite formation parameters for solders based on proteins and carbon nanotubes

Laser welding is an alternative method of biological tissues joining. One of the actual tasks of laser welding of biological tissues is to determine the weld depth by a noninvasive method during surgery. The paper presents a model for calculating the duration of the formation of welds depending on the density of laser radiation power and the depth of the joint. The calculations were performed for the laser beam diameter d = 1.1 mm, power density in the range from 10 to 25 W cm1, weld formation depth l in the range from 0.2 to 1 mm and solders based on aqueous dispersions of bovine serum albumin, indocyanin green and single-walled carbon nanotubes.
Social Currency Is a Personal Entity in the Social Media Platform Domain: Sharing and Caring Phenomenon in E-Commerce Platform

Due to the rapid development of information and communication technologies, many daily activities have been merged online, and they have become more flexible and more effective. The massive growth in the number of online users has activated virtual word concepts and created a new phenomenon: the social currency to facilitate e-commerce activities such as buying, selling, and trading on social media. This study aims to recognize how social contacts in 'action' within social media platform permeates sharing and transactions of valuable resources. The active interaction, entertainment, e-WOM traded in social networks are conceptualized as 'social currency' that people owe to each other in social circulation. This study demonstrates the importance of consumers' time-sharing (CTS) concept in the social media environment to earn social reputation (reviews, likes, comments, followers, favorite). A total of eight exploratory semi-structured qualitative depth-interviews were conducted at Dalian China. The data were analyzed using NVivo 12 software. Results suggested that the interaction, entertainment, e-WOM and traded between time and money in social networks are conceptualized as 'social currency' that people owe to each other in social circulation. The current study confirms the importance of the newly developed social currency concept in terms of social circulation.
Bicyclic 1,3a,6a-Triazapentalene Chromophores: Synthesis, Spectroscopy and Their Use as Fluorescent Sensors and Probes

The 1,3a,6a-triazapentalene (TAP) is an aromatic heterocyclic fluorescent dye with interesting features such as its small size, large Stokes shift, solvatochromism, and emission wavelengths that are spread across the visible spectrum. TAPs have been synthesized via different synthetic strategies involving click−cyclization−aromatization domino reactions, gold-catalyzed cyclization of propargyl triazoles or triazolization of acetophenones. As a result, TAPs with diverse substitution patterns were obtained, showing varying fluorescence properties. Based on these properties, several TAPs have been selected and studied as fluorescent imaging probes in living cells and as sensors. This mini review provides an overview of the research on the bicyclic TAPs and does not comment on the literature about benzo or otherwise fused systems. The synthetic methodologies for the preparation of TAPs, the substituent effects on the fluorescence properties, and the behavior of the TAP core as an element of biological imaging probes and sensors are discussed.
Study on rare and endangered plants under climate: maxent modeling for identifying hot spots in northwest China

Background: Climate warming has caused substantial changes in temporal and spatial environmental patterns. The study on hot spots of rare and endangered plants in Northwest China under predicted climate change can provide a scientific reference for the restoration and reconstruction of those degraded habitats, as well as the improvement of the protection system in Northwest China. Results: Based on MaxEnt algorithm, 813 effective distribution records and 11 environmental factor variables of rare and endangered plants in Northwest China, this study identified the changes of biodiversity hotspots of rare and endangered plants in Northwest China under predicted climate change. The results showed that: (1) the prediction accuracy of MaxEnt model is high, the area under the curve (AUC) is 0.876, and the total suitable area for potential geographical distribution of rare and endangered plants in Northwest China is 137.96×104km 2 , mainly including Western and Southwestern Xinjiang, Southern Gansu, parts of Eastern and Southern Qinghai Province, and Southern Shaanxi Province; (2) altitude, temperature and precipitation are the main environmental factors affecting the hot spots of rare and endangered plants in Northwest China; (3) under four climate change scenarios in the future, with the increase of emission scenarios from low to high forcing, Xinjiang would have the most obvious loss of hot spots of rare and endangered plants in Northwest China, and the most obvious increase of which would occur in Qinghai and Gansu provinces. Conclusion: Under the climate change scenario in the future, with the emission scenario increasing from low forcing to high forcing, the most obvious loss of the hot spots of rare and endangered plants in Northwest China happens in Xinjiang Province, and that of the most obvious increase occurs in Qinghai and Gansu provinces.
An experimental and comparative study of the self-loosening of bolted-joints under cyclic transverse loading

The capabilities of analytic models in predicting the experimental critical displacements of the self-loosening of bolted-joints were investigated experimentally and numerically. The experimental loosening rates were determined in a Junker test bench at a constant transverse displacement amplitude (0.45 mm) and under varying initial clamp force and clamp length and controlled bearing and thread friction coefficients. The analytic critical displacements were then calculated using experimental parameters. In addition, a three-dimensional accompanying finite element (FE) model was developed in order to calculate the ratio of spring constants engaging the thread to spring. The results showed relatively low capabilities of present analytic model in the prediction of the critical displacements of the self-loosening of bolted-joints. The efforts to modify the nut reaction moment and the inclination compliance of bolt head portion in the investigated equations however resulted moderate increase in the appropriate predictions. On the other side, the use of the reaction moment determined by FE model increased the appropriate prediction from 58.3 to 73.4%. The accuracy of the equations was further increased by the use of an appropriate kw value, but the increase in this case was only ~4%.
Analyzing the association between emotions and socioeconomic characteristics of census tracts via user‐generated content

Environmental and socioeconomic characteristics of places continuously influence human emotions. To understand the quality of human life, human emotions must be effectively evaluated and their connections with socioeconomic characteristics must be determined. Social computing tools can extract emotional information from massive user‐generated content (UGC); thus, we proposed an approach that correlates residents' emotions with the socioeconomic characteristics of place based on census tracts from New York State. First, demographic and economic characteristic data from census tracts were obtained and clustered; then, an emotion recognition technique extracted human emotions quantitatively from the UGC. Applying the Apriori algorithm and logistic regression analysis showed that the socioeconomic characteristics that may significantly influence residents’ emotions include family situation, race, and economic status. Local policymakers can use the proposed approach to compare the quality of human life in different regions over a large scale via UGC and identify socioeconomic characteristics to formulate policies to improve residents’ well‐being and welfare.