Miracle-dz/UniFAR-FTUs huggingface dataset:
MiR-195 participates in the placental disorder of preeclampsia via targeting activin receptor type-2B in trophoblastic cells

Objective: Preeclampsia is a pregnancy-related syndrome. Shallow invasion of uterine wall by trophoblast cells has been generally accepted as the major pathological change of this disorder. We previously found downregulation of miR-195 in preeclamptic placentas. Bioinformatic analysis predicted a type II activin receptor, activin receptor type-2B (ActRIIB), as one of the potential targets of miR-195. Considering the key function of activin A on trophoblast cell behaviors and placenta development, we proposed miR-195 may affect trophoblast cell invasion by repressing the expression of ActRIIB. Methods: The colocalization of ActRIIB and miR-195 in human placenta was measured by in-situ hybridization and immunohistochemistry. Western blotting, real-time PCR and dual luciferase assay were performed in human trophoblast cell line, HTR8/SVneo cells, to validate the targeting of ActRIIB by miR-195. Cell invasiveness was analyzed using transwell insert invasion assay in HTR8/SVneo cells. Results: In human placenta, ActRIIB and miR-195 exhibited similar localization in various subtypes of trophoblast cells, including villous and extravillous trophoblasts. The protein expressions of ActRIIB in preeclamptic placenta were significantly higher as compared with the normal controls, which was opposite to the changing pattern of miR-195. In HTR8/SVneo cells, miR-195 could directly target and suppress the expression of ActRIIB. Meanwhile, the invasion-promoting effect of miR-195 on trophoblast cells could be largely impeded by ActRIIB overexpression. Conclusion: In human trophoblast cells, miR-195 could promote cell invasion via directly targeting ActRIIB. The impaired miR-195 expression may contribute to the occurrence or development of preeclampsia through interfering with activin/nodal signaling in the placenta.
Atlas Based Sparsification of Image and Theoretical Estimation ( ABSINTHE )

Introduction: Several authors have recently proposed that one can make the scan time in MR proportional to the amount of information in the image, and not the number of pixels. This concept has now been applied to MR angiography for example. However, no robust implementation has been proposed for static anatomical imaging. We hypothesize that the actual new information in a typical brain MRI scan can be very small, and only related to the pathology with respect to normal anatomy. By removing the portions of the image that are “expected,” i.e. the standard brain, only the pathology remains, resulting in a potentially large decrease in information content, resulting in a reduction in the number of pixels which alias with one another. It has already been shown that higher parallel imaging acceleration factors can be achieved with less noise enhancement when applying the GRAPPA reconstruction [1] to sparse images [2]. The Atlas Based Sparsification of Image aNd THeoretical Estimation (ABSINTHE) method proposed here seeks to combine these ideas. The undersampled brain image to be reconstructed is first sparsified by performing a PCA analysis using a database of brain images to identify the features of the image that are common to the database and to subtract them out. This step leaves a sparse image containing only the differences from the collection of brains in the atlas, which can then be reconstructed using GRAPPA. This abstract demonstrates first results of ABSINTHE in vivo using a small training set of brain images followed by a GRAPPA reconstruction.
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm

We analyze two algorithms for approximating the general optimal transport (OT) distance between two discrete distributions of size $n$, up to accuracy $\varepsilon$. For the first algorithm, which is based on the celebrated Sinkhorn's algorithm, we prove the complexity bound $\widetilde{O}\left({n^2/\varepsilon^2}\right)$ arithmetic operations. For the second one, which is based on our novel Adaptive Primal-Dual Accelerated Gradient Descent (APDAGD) algorithm, we prove the complexity bound $\widetilde{O}\left(\min\left\{n^{9/4}/\varepsilon, n^{2}/\varepsilon^2 \right\}\right)$ arithmetic operations. Both bounds have better dependence on $\varepsilon$ than the state-of-the-art result given by $\widetilde{O}\left({n^2/\varepsilon^3}\right)$. Our second algorithm not only has better dependence on $\varepsilon$ in the complexity bound, but also is not specific to entropic regularization and can solve the OT problem with different regularizers.
Lab-on-Spoon – a 3-D integrated hand-held multi-sensor system for low-cost food quality, safety, and processing monitoring in assisted-living systems

Abstract. Distributed integrated sensory systems enjoy increasing impact leveraged by the surging advance of sensor, communication, and integration technology in, e.g., the Internet of Things, cyber-physical systems, Industry 4.0, and ambient intelligence/assisted-living applications. Smart kitchens and "white goods" in general have become an active field of R&D. The goal of our research is to provide assistance for unskilled or challenged consumers by efficient sensory feedback or context on ingredient quality and cooking step results, which explicitly includes decay and contamination detection. As one front end of such a culinary-assistance system, an integrated, multi-sensor, low-cost, autonomous, smart spoon device, denoted as Lab-on-Spoon (LoS), has been conceived. The first realized instance presented here features temperature, color, and impedance spectroscopy sensing in a 3-D-printed spoon package. Acquired LoS data are subject to sensor fusion and decision making on the host system. LoS was successfully applied to liquid ingredient recognition and quality assessment, including contamination detection, in several applications, e.g., for glycerol detection in wine. In future work, improvement to sensors, electronics, and algorithms will be pursued to achieve an even more robust, dependable and self-sufficient LoS system.
Feel force control incorporating velocity feedforward and inverse model observer for control loading system of flight simulator

Flight simulator is an essential rig for training pilot, and the control loading system is one of its important components to simulate control force feel of flying in actual airplane. This article states the key factor of control loading system: the disturbance of the flight control displacement on the accuracy of the force loop, that is, the inner loop of control loading system, which affects the fidelity of control force feel simulation. To reduce the disturbance effectively in the inner loop of control loading system, a new strategy, combining velocity feedforward with inverse model observer, is proposed, and the corresponding robust stability analysis is also provided. A transfer function of nonminimum-phase system inverse model, as the inverse model observer, is designed. In order to verify the practical feasibility of the proposed control strategy, experiment is conducted with hardware-in-the-loop-simulation platform based on RT-LAB rapid control prototype. Experimental results demonstrate that the proposed control strategy improves the performance of the control loading system effectively.
Self-tuning of sensorless switched reluctance motor drives with online parameter identification

The self-tuning capability of sensorless switched reluctance motor (SRM) drives is presented in this paper. A nonlinear machine model with online parameter identification is adapted with a sliding-mode observer (SMO) based sensorless technique. The parameter identification method makes position and speed estimation more accurate and robust towards any measurement noise and model uncertainty. Superior dynamic performance is achieved by updating machine parameters in real time. Online identification enables self-tuning of sensorless SRM drives without the need for a priori knowledge of the machine characteristics.
ARF1 Mediates Paxillin Recruitment to Focal Adhesions and Potentiates Rho-stimulated Stress Fiber Formation in Intact and Permeabilized Swiss 3T3 Fibroblasts

Focal adhesion assembly and actin stress fiber formation were studied in serum-starved Swiss 3T3 fibroblasts permeabilized with streptolysin-O. Permeabilization in the presence of GTPγS stimulated rho-dependent formation of stress fibers, and the redistribution of vinculin and paxillin from a perinuclear location to focal adhesions. Addition of GTPγS at 8 min after permeabilization still induced paxillin recruitment to focal adhesion–like structures at the ends of stress fibers, but vinculin remained in the perinuclear region, indicating that the distributions of these two proteins are regulated by different mechanisms. Paxillin recruitment was largely rho-independent, but could be evoked using constitutively active Q71L ADP-ribosylation factor (ARF1), and blocked by NH2-terminally truncated Δ17ARF1. Moreover, leakage of endogenous ARF from cells was coincident with loss of GTPγS- induced redistribution of paxillin to focal adhesions, and the response was recovered by addition of ARF1. The ability of ARF1 to regulate paxillin recruitment to focal adhesions was confirmed by microinjection of Q71LARF1 and Δ17ARF1 into intact cells. Interestingly, these experiments showed that V14RhoA- induced assembly of actin stress fibers was potentiated by Q71LARF1. We conclude that rho and ARF1 activate complimentary pathways that together lead to the formation of paxillin-rich focal adhesions at the ends of prominent actin stress fibers.
Expression and role of microRNA-1271 in the pathogenesis of osteosarcoma

The aim of the current study was to investigate the expression and role of microRNA (miR)-1271 in the pathogenesis of osteosarcoma, and the associated underlying mechanisms. Tissue samples from 45 patients with osteosarcoma were collected, while the 143B, MG-63 and U-2 OS osteosarcoma cell lines were also cultured. The expression levels of miR-1271 in the tissues and cells were detected with reverse transcription-quantitative polymerase chain reaction, and 143B osteosarcoma cells were subjected to miR-1271 manipulation. In addition, the cell proliferation, cell cycle progression, and migration and invasion abilities were assessed by Cell Counting Kit-8 assay, flow cytometry and Transwell chamber assay, respectively. Tissue inhibitor of metalloproteinases 2 (TIMP2) expression level was also detected with western blot analysis. Dual-luciferase reporter assay was performed to investigate the interaction between miR-1271 and TIMP2. The results revealed that miR-1271 expression was significantly elevated in the osteosarcoma tissue and was closely correlated with the clinical TNM staging. The expression levels of miR-1271 were also upregulated in the osteosarcoma cells, with the highest expression observed in 143B cells. Inhibition of miR-1271 significantly inhibited the cell proliferation, G1/S phase transition, and the migration and invasion abilities of 143B cells, while it also resulted in upregulated TIMP2 expression in these cells. Furthermore, overexpression of TIMP2 significantly inhibited the cell proliferation, G1/S phase transition, and migration and invasion abilities of 143B cells. Dual-luciferase reporter assay demonstrated that miR-1271 targeted on the 3′-untranslated region of TIMP2 mRNA. In conclusion, the expression levels of miR-1271 were significantly elevated in osteosarcoma tissues and cells. miR-1271 downregulated the expression of TIMP2 to promote the proliferation and enhance the migration and invasion abilities of 143B osteosarcoma cells, functioning as an oncogene.
Influence of temperature on the magnetic properties of electroplated Co-rich Co–Pt thick films

In this paper, the magnetic properties of 10 µm thick Co-rich Co–Pt films (∼80:20 atomic ratio) hard magnetic films electroplated on silicon substrates are characterized at temperatures from 300 to 1000 K. With an increase in temperature up to 500 K, the coercivity and remanence of the films both decrease rapidly, dropping to only 10% of their respective as-deposited values. Above 500 K, the coercivity and remanence continue declining but at a slower rate, reaching nearly zero at 1000 K. Conversely, the saturation magnetization reduces by only 15% at 800 K and 40% at 1000 K from the as-deposited value. In addition to these measurements at elevated temperature measurements, thermal cycling tests are performed to examine the influence of various thermal exposures. Cycles up to 500 K are shown to have little impact on the film morphology but notably reduce the layer adhesion. Most importantly, a thermal cycle to just 400 K is shown to essentially destroy the hard magnetic properties. Because of these temperature sensitivities, Co-rich Co–Pt films may be significantly limited for end applications.
Multiscale enrichment of a finite volume element method for the stationary Navier–Stokes problem

In this paper, we introduce a finite volume element method for the Navier–Stokes problem. This method is based on the multiscale enrichment and uses the lowest finite element pair P 1/P 0. The stability and convergence of the optimal order in H 1-norm for velocity and L 2-norm for pressure are obtained. Using a dual problem for the Navier–Stokes problem, we establish the convergence of the optimal order in L 2-norm for the velocity.
Evaluation of the short form of “Experience in Close Relationships” (Revised, German Version “ECR-RD12”) - A tool to measure adult attachment in primary care

Attachment theory helps us to understand patients´ health behavior. Attachment styles might explain patient differences in coping behavior, self-treatment, or patient-provider relationships. In primary care time constrains are relevant. A short instrument may facilitate screening and assessment in daily medical practice. The aim of this study was to evaluate a 12-item short version of the Experience in Close Relationships-revised (ECR-R-D) to be used in primary care settings. We included 249 patients from ten general practices in central Germany into a cross-sectional study. Exploratory factor analysis was performed to evaluate the factor structure of the ECR-items. Cronbach’s alpha was used to assess internal consistency. The results related to the short form of the ECR are in line with those of the German full-length version of the measure (ECR-RD 36). Internal consistencies were in an adequate range. The ECR short form can be recommended as a screening measure of attachment styles in primary care.
EARNING TO T EACH

Teaching plays a very important role in our society, by spreading human knowledge and educating our next generations. A good teacher will select appropriate teaching materials, impact suitable methodologies, and set up targeted examinations, according to the learning behaviors of the students. In the field of artificial intelligence, however, one has not fully explored the role of teaching, and pays most attention to machine learning. In this paper, we argue that equal attention, if not more, should be paid to teaching, and furthermore, an optimization framework (instead of heuristics) should be used to obtain good teaching strategies. We call this approach “learning to teach”. In the approach, two intelligent agents interact with each other: a student model (which corresponds to the learner in traditional machine learning algorithms), and a teacher model (which determines the appropriate data, loss function, and hypothesis space to facilitate the training of the student model). The teacher model leverages the feedback from the student model to optimize its own teaching strategies by means of reinforcement learning, so as to achieve teacher-student co-evolution. To demonstrate the practical value of our proposed approach, we take the training of deep neural networks (DNN) as an example, and show that by using the learning to teach techniques, we are able to use much less training data and fewer iterations to achieve almost the same accuracy for different kinds of DNN models (e.g., multi-layer perceptron, convolutional neural networks and recurrent neural networks) under various machine learning tasks (e.g., image classification and text understanding).
BlueID: Enabling robust in-car localization and on-demand personalization using Bluetooth

Connected car has become one of the fastest growing segments in the IoT market. A key feature of connected car solutions is personalization. An advanced solution shall be able to enable complete personalization for each seat automatically. This paper presents the design and implementation of BlueID — a framework for robust in-car localization and on-demand personalization using Bluetooth Low Energy (BLE) beacons. BlueID identifies a user based on the user's mobile device and characterizes each seat using signals received from a pre-installed BLE beacon array. BlueID features a machine learning engine that can robustly distinguish seats in the presence of various environment and system dynamics such as varied antenna sensitivities and multiple seat occupants. To enable on-demand use cases, BlueID employs a connected car cloud platform to store each vehicle's seat prediction model and each user's personalization profile. The prediction model and the user's personalization profile are retrieved to personalize the environment where the user sits when the user enters the vehicle. We have implemented a prototype of BlueID and evaluated it through extensive experiments. The results show that BlueID achieves satisfactory in-car localization performance with average position accuracy over 98%.
A Transgenic Mouse Model for Detection of Tissue-Specific Thyroid Hormone Action

Thyroid hormone (TH) is present in the systemic circulation and thus should affect all cells similarly in the body. However, tissues have a complex machinery that allows tissue-specific optimization of local TH action that calls for the assessment of TH action in a tissue-specific manner. Here, we report the creation of a TH action indicator (THAI) mouse model to study tissue-specific TH action. The model uses a firefly luciferase reporter readout in the context of an intact transcriptional apparatus and all elements of TH metabolism and transport and signaling. The THAI mouse allows the assessment of the changes of TH signaling in tissue samples or in live animals using bioluminescence, both in hypothyroidism and hyperthyroidism. Beyond pharmacologically manipulated TH levels, the THAI mouse is sufficiently sensitive to detect deiodinase-mediated changes of TH action in the interscapular brown adipose tissue (BAT) that preserves thermal homeostasis during cold stress. The model revealed that in contrast to the cold-induced changes of TH action in the BAT, the TH action in this tissue, at room temperature, is independent of noradrenergic signaling. Our data demonstrate that the THAI mouse can also be used to test TH receptor isoform-specific TH action. Thus, THAI mouse constitutes a unique model to study tissue-specific TH action within a physiological/pathophysiological context and test the performance of thyromimetics. In conclusion, THAI mouse provides an in vivo model to assess a high degree of tissue specificity of TH signaling, allowing alteration of tissue function in health and disease, independently of changes in circulating levels of TH.
Thermal spraying of polymers

Abstract Thermally sprayed polymer coatings are gaining significant attention from many industries, including the petrochemical, automotive, and aircraft industries. They are being used for surface protection against humidity, corrosion, and aggressive chemical environments, as low friction and stable electrical insulation coatings, and as coatings with tailored electrical and magnetic properties. Thermal spraying is a unique, environmentally compliant, technique for the application of polymers and polymer composites because it overcomes processing limitations of other polymer coating techniques. Materials are processed in powder form and therefore the need for solvents is eliminated. Processing is not limited by melt viscosity and/or thermal conductivity of the substrate material. It is an effective method to produce coatings with a large range of thicknesses on a variety of substrate materials. Coating applications are not restricted by the size of the part being coated and coatings can be readily applied in the field, which is an important consideration for industrial use. Spraying is a one step process, with no additional cure time needed. Thermoplastic coatings can be repaired by remelting and applying additional material to the desired location. Many polymers can be applied in high humidity conditions as well as at temperatures below freezing. Successful deposition of polymer coatings by thermal spraying involves careful consideration of material limitations and the capabilities of individual thermal spray processes. Coating performance is strongly influenced by processing parameters and the subsequent coating microstructure that develops. Carefully designed processing conditions are necessary to obtain optimal heat input into the powder and to prevent polymer degradation. Sufficient heat input, optimal substrate preparation, and material changes during deposition must be carefully balanced so that the polymer deforms and adheres well to the substrate. Various thermal spraying techniques available for spraying polymers, and their attributes, are described. Heat transfer and its effects on changes in physical properties of polymers due to spraying are presented. Through the experimental results obtained by various researchers, process-structure-property relationships are discussed. Size, distribution, and filler content effects on polymer composite coatings are introduced. Current and potential fields of application of thermally sprayed polymer coatings are reviewed.
Design Optimal PID Controller for Quad Rotor System

rotor aerial vehicles are one of the most flexible and adaptable platforms for undertaking aerial research. Quad rotor in simplicity is rotorcraft that has four lift-generation propellers (four rotors), two rotors rotate in clockwise and the other two rotate anticlockwise, the speed and direction of Quad rotor can be controlled by varying the speed of these rotors. This paper describes the PID controller has been used for controlling attitude, Roll, Pitch and Yaw direction. In addition, optimal PID controller has been achieving by using particle swarm optimization (PSO), Bacterial Foraging optimization (BFO) and the BF-PSO optimization. Finally, the Quad rotor model has been simulating for several scenarios of testing. Keywordsad rotor, PID controller, particle swarm (PSO), Bacterial Foraging optimization (BFO) and the BF-PSO optimization.