Miracle-dz/UniFAR-FTUs huggingface dataset:
Design, Development and Optimization of a Functional Mammalian Cell-Free Protein Synthesis Platform

In this paper, we describe the stepwise development of a cell-free protein synthesis (CFPS) platform derived from cultured Chinese hamster ovary (CHO) cells. We provide a retrospective summary of the design challenges we faced, and the optimized methods developed for the cultivation of cells and the preparation of translationally active lysates. To overcome low yields, we developed procedures to supplement two accessory proteins, GADD34 and K3L, into the reaction to prevent deactivation of the translational machinery by phosphorylation. We compared different strategies for implementing these accessory proteins including two variants of the GADD34 protein to understand the potential trade-offs between yield and ease of implementation. Addition of the accessory proteins increased yield of turbo Green Fluorescent Protein (tGFP) by up to 100-fold depending on which workflow was used. Using our optimized protocols as a guideline, users can successfully develop their own functional CHO CFPS system, allowing for broader application of mammalian CFPS.
Complex Organic Matter Synthesis on Siloxyl Radicals in the Presence of CO

Heterogeneous phase astrochemistry plays an important role in the synthesis of complex organic matter (COM) as found on comets and rocky body surfaces like asteroids, planetoids, moons and planets. The proposed catalytic model is based on two assumptions: (a) siliceous rocks in both crystalline or amorphous states show surface-exposed defective centers such as siloxyl (Si-O•) radicals; (b) the second phase is represented by gas phase CO molecules, an abundant C1 building block found in space. By means of quantum chemistry; (DFT, PW6B95/def2-TZVPP); the surface of a siliceous rock in presence of CO is modeled by a simple POSS (polyhedral silsesquioxane) where a siloxyl (Si-O•) radical is present. Four CO molecules have been consecutively added to the Si-O• radical and to the nascent polymeric CO (pCO) chain. The first CO insertion shows no activation free energy with ΔG200K = −21.7 kcal/mol forming the SiO-CO• radical. The second and third CO insertions show ΔG200K‡ ≤ 10.5 kcal/mol. Ring closure of the SiO-CO-CO• (oxalic anhydride) moiety as well as of the SiO-CO-CO-CO• system (di-cheto form of oxetane) are thermodynamically disfavored. The last CO insertion shows no free energy of activation resulting in the stable five member pCO ring, precursor to 1,4-epoxy-1,2,3-butanone. Hydrogenation reactions of the pCO have been considered on the SiO oxygen or on the carbons and oxygens of the pCO chains. The formation of the reactive aldehyde SiO-CHO on the siliceous surface is possible. In principle, the complete hydrogenation of the (CO)1−4 series results in the formation of methanol and polyols. Furthermore, all the SiO-pCO intermediates and the lactone 1,4-epoxy-1,2,3-butanone product in its radical form can be important building blocks in further polymerization reactions and/or open ring reactions with H (aldehydes, polyols) or CN (chetonitriles), resulting in highly reactive multi-functional compounds contributing to COM synthesis.
Pharmacokinetics, Biodistribution and Therapeutic Efficacy of Doxorubicin Encapsulated in Stealth® Liposomes (Doxil®)

AbstractDoxil® (Stealth® liposomal doxorubicin HCl) Injection is doxorubicin HCl incorporated into long circulating liposomes that contain surface-grafted polyoxyethylene chains. These surface-grafted polymer chains reduce the interaction of the liposomes with the mononuclear phagocytic system, accounting for the long circulation and altered biodistribution of Stealth liposomes. They also reduce adhesion of the liposomes to cells, blood vessel walls and other surfaces and result in increased vascular permeability of Stealth liposomes compared to conventional liposomes of equal size. Efficacy studies in several tumor models, including human xenograft models, have demonstrated that Doxil is more effective than unencapsulated doxorubicin (Adriamycin) or doxorubicin encapsulated in non-coated conventional liposomes. Doxil exhibits altered plasma pharmacokinetics, with a longer plasma half-life, large AUC and markedly smaller volume of distribution than Adriamycin. Tissue levels of doxorubicin are generally lo.
Do Preschoolers Align Their Preferences With Those of a Powerful Individual?

Very early on, children understand the hierarchical dimension of the social environment and use a variety of cues to guess who has more power in an interaction. A crucial aspect of power perception lies in the evaluation of high-power and low-power individuals. The current study examined the evaluation of power by preschoolers through social influence. Past research has shown that preschoolers take social category information into account when expressing their preferences. In particular, they tend align their preferences with those of same-gender and same-age individuals. In the current study, 4- and 5-year-old children were presented with a power interaction between two children through body postures and were asked whether they would prefer the same items as those preferred by the high-power child or those preferred by the low-power child. Overall, the participants did not choose the items preferred by the high-power child significantly more often than those preferred by the low-power child. However, unexpected gender effects were found and indicated that the power asymmetry influenced more male than female participants. Indeed, when they saw a power interaction between two boys (Experiments 1 and 2), male participants aligned their choices with those of the high-power boy more than with those of the low-power boy. However, when male participants saw an interaction between two girls (Experiment 3), an opposite pattern was observed: they aligned their choices with those of the low-power girl more than with those of the high-power girl. In contrast, in the three experiments, there were approximately as many girls who aligned their preferences with those of the high-power child as there were girls who aligned their preferences with those of the low-power child. The current study reveals the importance of taking gender into account, both at the level of participants and stimuli, in the evaluation of power by preschoolers.
Phonological networks and new word learning

The first report of a connection between vocabulary learning and phonological short-term memory was published in 1988 (Baddeley, Papagno, & Vallar, 1988). At that time, both Susan Gathercole and I were involved in longitudinal studies, investigating the relation between nonword repetition and language learning. We both found a connection. Now, almost 20 years later, in her Keynote Gathercole (2006) reviews a multitude of data bearing on the interpretation of this often replicated connection. Her main conclusions are three. First, both nonword repetition and word learning are constrained by the quality of temporary storage. She sees this storage as multiply determined, that is, affected by factors like perceptual analysis, phonological awareness (ability to identify and reflect on the speech sounds that make up words). Second, both nonword repetition and word learning are also affected by sensory, cognitive, and motor processes. Third, an impairment of phonological storage is typically associated with specific language impairment (SLI) but may not be a sole causal factor.
The structure of the valence electronic orbitals in uranium trioxide γ-UO3

The role of the U6p,5f electrons in the chemical bond in γ-UO3 was studied on the basis of the low-energy X-ray photoelectron, conversion electron spectra from uranium trioxide, and the calculations for the [UO2O4]6− (D4h) cluster.
Biomassa e atividade microbiana em solo sob diferentes sistemas de manejo na região fisiográfica Campos das Vertentes - MG

Biomass and microbial activity have been suggested as appropriate indicators of changes caused by different land use and management systems. The objective of this study was to evaluate alterations in biomass and microbial activity of a typic acric Red-Yellow Latosol (Oxisol), under native Cerrado and different management systems, in the physiographic region Campos das Vertentes, state of Minas Gerais. The evaluated systems were: conventional tillage with potato (CCB); potato followed by oat in rotation with corn (CBAM); conventional tillage with corn (CCM); no-till with corn (PDM); conventional tillage with eucalyptus (CCE); and native Cerrado (CN) as reference. Soil samples were collected in the layers 0-10, 10-20 and 20-30 cm. The microbial carbon (Cmic) and basal respiration were analyzed, and the metabolic quotient (qCO2) and Cmic/organic carbon ratio were calculated. The biomass and microbial activity were influenced by the different soil management systems and the conditions for soil microbiota were most adequate under NC. The most intensive soil managements with frequent pesticide use, as in the CCB and CBAM systems, resulted in lower amounts of Cmic, lower Cmic/TOC ratio and higher qCO2 values, indicating a probable stress condition for microbial biomass.
A Novel Dynamic Inversion Decouple Cooperative Guidance law against Highly Maneuvering Target

In this paper, a novel dynamic inverse decouple cooperative guidance law(DIDCGL) based on the decoupled model in the line-of-sight(LOS) and normal LOS direction is proposed, which is suitable for attacking a highly maneuvering target simultaneously with desired angles. Firstly, a method of decoupling the cooperative guidance model based on the adaptive dynamic inverse theory is proposed. Secondly, extended state observers(ESOs) are introduced to estimate the disturbances caused by target maneuver. Then, DIDCGL is designed by using adaptive linear feedback control based on the decoupled guidance model. Finally, numerical simulation results demonstrate the effectiveness and the superiority of proposed cooperative guidance law.
Foreign Body Intrusion Detection Algorithm for Track Surveillance Systems in Smart Cities

As modern science and technology advance, artificial intelligence technology has been widely applied. Among them, the image processing technology based on machine vision represents an essential part of artificial intelligence. Besides, its role in production and life is made increasingly important. A significant research challenge posed to image processing technology is foreign body intrusion detection algorithm. Given the issues with the conventional rail foreign body intrusion recognition systems, a novel and simple algorithm is proposed in this paper that is unified to detect foreign body intrusion from sensors of track surveillance systems. Not only is our method capable to detect object foreign bodies rapidly and accurately, and it is effective in reducing the volume of big data needing to be stored in the track surveillance system.
Two-Phase, Two-Stage, and Single-Stage Anaerobic Process Comparison

In this research, three anaerobic process configurations—namely, two-phase dual sludge (TPDS), two-stage single sludge (TSSS), and single-stage—were evaluated for effluent COD concentration. The same temperature, SRT, and glucose substrate were used in all experiments. In every case, TPDS and TSSS configurations significantly outperformed the single stage. All experiments were carried out at a temperature of 35°C, and all reactors were operated as daily fill-and-draw with HRT = SRT. The following ranges for each design parameter were studied: pH (4.5, 5.5, and 6.5); first stage HRT (3, 8, and 24 h); and floc load (3, 9, and 27 gCOD/gVSS). The overall HRT/SRT of all systems was 30 days, and a pH-Stat system was used to control the pH in the acidification reactors at the desired value. Statistical evaluation of the results indicated that a floc load of 3 in the first reactor of TPDS yielded the lowest effluent COD concentrations under the studied range of parameters, while for the TSSS reactor configuration.
A novel wavelength selection algorithm based on permutation analysis and variable combination

As one of the most important preprocessing procedures in spectral detection, wavelength selection plays an irreplaceable role in reducing the model computation consumption and prediction error. However, many wavelength selection methods only use a mono-directional strategy to capture the synergetic influence between wavelength points, which causes information loss and limits their performance. Herein, a novel algorithm called bidirectional permutation analysis (BPA) is proposed. To completely capture the synergetic influence between each wavelength point, we first modify the permutation analysis to select wavelength points that have a high synergetic effect with any other wavelength points. Then, the variable combinational population analysis (VCPA) is used to select other wavelength points from another direction that whether they are suitable to combine with front selected wavelengths. Benefited from this bidirectional selection structure, BPA could more comprehensively evaluate the synergetic effect between wavelength points and avoid the loss of useful information. The performance of BPA was estimated by using the spectral common dataset of corn oil. The comparison results indicate that our algorithm performs better on both accuracy and stability than four state-of-the-art algorithms: CARS, VCPA, VCPA-GA, and VCPA-IRIV.
A Machine vision method for non-contact Tool Wear Inspection

Tool wear is usually the most relevant parameter of tool performance detection, which directly affects the product quality and tool life. Online tool condition monitoring can effectively avoid workpiece scrap and machine failure. To solve the problems of using electron microscopes to measure tool wear in real production, a machine vision system for tool wear detection is developed in this paper to reduce testing costs. Through rough positioning by morphology-based Canny operator edge detection and image registration, the tool wear area can be extracted effectively. Sub-pixel edge detection based on Zernike moment is used to improve the measurement accuracy and the principal curve method is used to fit sub-pixel edge points to obtain smooth edge curve. Finally, the tool wear can be detected and measured effectively based on these methods. In the real machining process, the test results show that this system features high response speed, high inspecting accuracy and high automation. This system can be effectively applied to the real-time monitoring of tool wear in industry.
Extrinsic Calibration of a Small FoV LiDAR and a Camera

With Light Detection and Ranging(LiDAR) technology’s development and maturity, various new LiDARs have emerged in recent years, such as the Mid-40 series launched by Livox. Compared with the rotating Velodyne LiDAR, its small scanning range and irregular scanning trajectory pose challenges for SLAM applications. We evaluate the characteristics of Mid-40, and propose a calibration method based on checkerboard patterns. Our calibration method extracts the checkerboard corners’ coordinates from both the point cloud and the image, which are then used to establish 3D-2D matching constraints. By solving the constraints, we can obtain extrinsic parameters between the LiDAR and camera without the need to label the corner features manually. Experimental results suggested that our method is able to solve the extrinsic calibration problem between Livox Mid-40 LiDAR and the monocular camera with high accuracy.
Molecular Mechanism of Polymorphic Transitions

Abstract It is shown that serious problems arise with the usual classification and proposed mechanisms for polymorphic transitions in crystals. On the basis of the investigation of polymorphic transitions in molecular crystals, we propose here an alternative scheme which, we believe, avoids these problems and more successfully explains the behavior of real crystals during polymorphic transitions than previous schemes have done.
Multi-stage Features Sparse Learning Based Scene Recognition of Hyperspectral Image

in this paper, a multi-stage features sparse learning method for hyperspectral image scene recognition is proposed. The hyperspectral image is decomposed into five scales by Gaussian function at eight angles. Gabor visual features are extracted at different scales of each angle. The visual dictionary of hyperspectral image is constructed by sparse coding, and the sparse coding coefficient matrix of multi angle and multi-scale features of hyperspectral image is formed Compared with BoVW or PLSA, the overall accuracy of SVM classifier is improved by 4.47% and 5.39% respectively, and the kappa coefficient is improved by 0.0685 and 0.0768 respectively. The results show that the proposed multi-angle and multi-scale sparse coding method for hyperspectral image scene recognition is more interpretable than the description of hyperspectral image features with BoVW or PLSA, and can effectively improve the effect of hyperspectral image scene recognition.
Video stabilization algorithm based on background feature point matching

Global motion estimation between two successive frames is important to the process of video stabilization. In the proposed approach, the estimation of global motion was based on the background feature points (BFPS). First, feature points were collected from the input video by FAST operator; second, feature point’s descriptor and matching were based on FREAK operator.The MSAC is used to classify the BFPS. Last, the six parameters of the affine transform model to calculate the interframe motion estimation vector. The experiment results show that he proposed method can stabilize inter-frame jitter, in the meanwhile, it improve the video quality effectively.
Detection Method for Tolerable False Data Injection Attack Based on Deep Learning Framework

The electric power system is one of the major infrastructures of a country. The ordinary False Data Injection (FDI) is a classical attack on it, which can obstruct normal operation of the electric power system. But the planning and implement of FDI need strict condition. Therefore, we aim at detecting Tolerable False Data Injection (TFDI) attack, which is more likely to implement. Nonetheless, the detection of such an attack is still an unsolved problem . In this paper, we propose a method based on deep learning framework to detect the TFDI attack. We test our model based on the IEEE 14-bus and 30-bus standard datasets for set load condition and mixed load condition. The results demonstrate the good performance of the model distinguishing the TFDI attack. Besides, it has an excellent generalization ability on different load scenarios.
Data-Driven Parameter Choice for Illumination Artifact Correction of Digital Images

We propose a new procedure for image illumination correction with data-driven parameter choice. This procedure aims at estimating the reflectance image from a corrupted version in which the corruption is due to pointwise multiplicative illumination artifact. The <inline-formula><tex-math notation="LaTeX">$\log \text{-illumination}$</tex-math></inline-formula> artefact consists of “smooth” variations of the intensity which are modelled by a function lying in a finite dimensional space. Then a <inline-formula><tex-math notation="LaTeX">$\gamma$</tex-math></inline-formula>-correction is incorporated. The question of model selection is difficult to solve. We propose an entropy minimization criterion for the selection of both the approximating <inline-formula><tex-math notation="LaTeX">$\log \text{-illumination}$</tex-math></inline-formula> space dimension and the <inline-formula><tex-math notation="LaTeX">$\gamma$</tex-math></inline-formula>-coefficient, so that no parameter tuning is needed. Several experiments are presented using this approach. A comparison to other methods illustrates the relevance of this approach.
Harmonic Suppression Scheme of Inverter Based on 5th and 7th Harmonic Injection Method

As the driving unit of AC motor, frequency conversion device is more and more widely used because of its good energy-saving effect and high speed control accuracy. However, because the circuit topology of the frequency conversion device contains a large number of non-linear switching semiconductor devices, resulting in a large amount of output current, which interferes with the load. Firstly, the mechanism of high-order harmonic generation in frequency converter is analyzed, and the expression of high-order harmonic generation is obtained by mathematical modeling. Secondly, in order to suppress high-order harmonic generation in frequency converter, a harmonic suppression scheme based on specific harmonic injection method is proposed, that is, to inject 5 and 7 harmonic compensation voltage into SPWM sinusoidal signal, so as to reduce the specific harmonic content of output current. The simulation and experiment of MATLAB/Simulink prove that the scheme can effectively reduce the specific sub-high harmonics generated by frequency devices, reduce the harmonic distortion rate and improve the power quality of output current.
Gold Price Prediction and Modelling using Deep Learning Techniques

The demand for gold never ends. The gold rate trend shows that gold is one of the best investment plans. So it is wise to predict the trend of the gold rate. Different statistical models can be used for suitable modelling and prediction of data. This paper summarizes the idea of gold rate prediction using the LSTM Network. It is always visible that the price of gold follows a nonlinear nature. The prediction of prices is commanding for the proper financial and investment plans. The gold rate fluctuation can be modelled as an exponential curve. Convolutional Neural Networks is one of the best solutions for solving nonlinearities in data and among them RNNs are best suited for time series predictions and estimations. The dataset collected from the World Gold Council is used and results have shown that the proposed architecture is one of the best financial forecasting methods.
An Energy-Efficient Temperature Sensor Using CMOS Thyristor Delay Elements

This paper presents a time-based method of measuring temperature using CMOS thyristors and a time-to-digital converter (TDC) akin to algorithmic analog-to-digital converters. By treating time as a signal and as an abundant resource for slow-changing quantities like temperature, slow but energy-efficient topologies like CMOS thyristors could prove useful. Coupled with a TDC that does not scale exponentially with resolution, a significantly lower energy consumption is achieved. This sensor system measures temperature with non-linearity error of ±0.25 °C and resolution of 0.05 °C per LSB from −15 °C to 30 °C while using only 0.4nJ per measurement.
An Application QoS Based Conversion Scheme Between Ethernet/IP and IPv6

Heterogeneous networking is a key feature for Industrial Internet. Protocol conversion is a significant way to achieve heterogeneous interconnection. In this paper, we propose an application Quality of Service (QoS) based conversion scheme between Ethernet/IP and Internet Protocol Version 6 (IPv6), which can connect devices in Ethernet/IP network to Industrail Backhaul Network using IPv6 technology, and guarantee the QoS of applications for Industrial Ethernet. The main components of the conversion scheme are presented in detail, including IP address conversion, application dependency conversion, traffic class mapping, and flow label mapping. Experimental results demonstrate that the proposed scheme can effectively perform protocol conversion between Ethernet/IP and IPv6 with application QoS support.