Miracle-dz/UniFAR-FTUs huggingface dataset:
Tryptase Regulates the Epigenetic Modification of Core Histones in Mast Cell Leukemia Cells

Mast cells are immune cells that store large amounts of mast cell-restricted proteases in their secretory granules, including tryptase, chymase and carboxypeptidase A3. In mouse mast cells, it has been shown that tryptase, in addition to its canonical location in secretory granules, can be found in the nuclear compartment where it can impact on core histones. Here we asked whether tryptase can execute core histone processing in human mast cell leukemia cells, and whether tryptase thereby can affect the epigenetic modification of core histones. Our findings reveal that triggering of cell death in HMC-1 mast cell leukemia cells is associated with extensive cleavage of core histone 3 (H3) and more restricted cleavage of H2B. Tryptase inhibition caused a complete blockade of such processing. Our data also show that HMC-1 cell death was associated with a major reduction of several epigenetic histone marks, including H3 lysine-4-mono-methylation (H3K4me1), H3K9me2, H3 serine-10-phosphorylation (H3S10p) and H2B lysine-16-acetylation (H2BK16ac), and that tryptase inhibition reverses the effect of cell death on these epigenetic marks. Further, we show that tryptase is present in the nucleus of both viable and dying mast cell leukemia cells. In line with a role for tryptase in regulating nuclear events, tryptase inhibition caused increased proliferation of the mast cell leukemia cells. Altogether, the present study emphasizes a novel principle for how epigenetic modification of core histones is regulated, and provides novel insight into the biological function of human mast cell tryptase.
α-Actinin 4 Links Vasopressin Short-Term and Long-Term Regulation of Aquaporin-2 in Kidney Collecting Duct Cells

Water permeability of the kidney collecting ducts is regulated by the peptide hormone vasopressin. Between minutes and hours (short-term), vasopressin induces trafficking of the water channel protein aquaporin-2 to the apical plasma membrane of the collecting duct principal cells to increase water permeability. Between hours and days (long-term), vasopressin induces aquaporin-2 gene expression. Here, we investigated the mechanisms that bridge the short-term and long-term vasopressin-mediated aquaporin-2 regulation by α-actinin 4, an F-actin crosslinking protein and a transcription co-activator of the glucocorticoid receptor. Vasopressin induced F-actin depolymerization and α-actinin 4 nuclear translocation in the mpkCCD collecting duct cell model. Co-immunoprecipitation followed by immunoblotting showed increased interaction between α-actinin 4 and glucocorticoid receptor in response to vasopressin. ChIP-PCR showed results consistent with α-actinin 4 and glucocorticoid receptor binding to the aquaporin-2 promoter. α-actinin 4 knockdown reduced vasopressin-induced increases in aquaporin-2 mRNA and protein expression. α-actinin 4 knockdown did not affect vasopressin-induced glucocorticoid receptor nuclear translocation, suggesting independent mechanisms of vasopressin-induced nuclear translocation of α-actinin 4 and glucocorticoid receptor. Glucocorticoid receptor knockdown profoundly reduced vasopressin-induced increases in aquaporin-2 mRNA and protein expression. In the absence of glucocorticoid analog dexamethasone, vasopressin-induced increases in glucocorticoid receptor nuclear translocation and aquaporin-2 mRNA were greatly reduced. α-actinin 4 knockdown further reduced vasopressin-induced increase in aquaporin-2 mRNA in the absence of dexamethasone. We conclude that glucocorticoid receptor plays a major role in vasopressin-induced aquaporin-2 gene expression that can be enhanced by α-actinin 4. In the absence of vasopressin, α-actinin 4 crosslinks F-actin underneath the apical plasma membrane, impeding aquaporin-2 membrane insertion. Vasopressin-induced F-actin depolymerization in one hand facilitates aquaporin-2 apical membrane insertion and in the other hand frees α-actinin 4 to enter the nucleus where it binds glucocorticoid receptor to enhance aquaporin-2 gene expression.
Total Laboratory Automation and Three Shifts Reduce Turnaround Time of Cerebrospinal Fluid Culture Results in the Chinese Clinical Microbiology Laboratory

Background Total laboratory automation (TLA) has the potential to reduce specimen processing time, optimize workflow, and decrease turnaround time (TAT). The purpose of this research is to investigate whether the TAT of our laboratory has changed since the adoption of TLA, as well as to optimize laboratory workflow, improve laboratory testing efficiency, and provide better services of clinical diagnosis and treatment. Materials and Methods Laboratory data was extracted from our laboratory information system in two 6-month periods: pre-TLA (July to December 2019) and post-TLA (July to December 2020), respectively. Results The median TAT for positive cultures decreased significantly from pre-TLA to post-TLA (65.93 vs 63.53, P<0.001). For different types of cultures, The TAT of CSF changed the most (86.76 vs 64.30, P=0.007), followed by sputum (64.38 vs 61.41, P<0.001), urine (52.10 vs 49,57, P<0.001), blood (68.49 vs 66.60, P<0.001). For Ascites and Pleural fluid, there was no significant difference (P>0.05). Further analysis found that the incidence of broth growth only for pre-TLA was 12.4% (14/133), while for post-TLA, it was 3.4% (4/119). The difference was statistically significant (P=0.01). The common isolates from CSF samples were Cryptococcus neoformans, coagulase-negative Staphylococcus, Acinetobacter baumannii, and Klebsiella pneumonia. Conclusion Using TLA and setting up three shifts shortened the TAT of our clinical microbiology laboratory, especially for CSF samples.
Evaluating efficiency of Anti-Malware using Transformation Attacks

In this paper we have reviewed and studied various malware detection tools. There are various attacks are applied on anti-malwares. Such attacks can be detected by anti-malware systems but some of them can't detect unknown and all types of attacks. We have reviewed different techniques of malware samples detection, such as resistance to various common obfuscation techniques are analyzed. The possible solution for improving the current state of malware detection on mobile devices can be found using a larger malware samples.
Telescopic Leg Control Based on the Super -Twisting Observer for Double-Frame Mobile Robot

In this paper, a novel double-frame mobile robot with suction cups for aircraft skin inspection is studied. The double-frame mobile robot's attitude can be adjusted on curved surface through the control of the robot's outrigger cylinder. Initially, the dynamic model of the robot's telescopic leg is established through Newton's law of kinematics. The change of air pressure in cylinder under different working conditions is analyzed. Then, a super-twisting second-order sliding mode algorithm is modified in order to design a velocity observer for telescopic leg systems. The finite time convergence of the observer is proved. Thus, the observer can be designed independently of the controller. Finally, simulation results are given to verify the effectiveness of the proposed super-twisting second-order sliding mode algorithm.
Wideband SIW Cavity-Backed Ring Slot Antenna for 5G Applications

A wideband substrate integrated waveguide (SIW) cavity-backed Ring slot antenna is proposed in this paper. The ring slot mode and the TE210 mode of the SIW cavity are excited by dual slots fed by a TE20 Mode SIW transmission line. A 1×4 array is designed and fabricated. The proposed antenna has a measured impedance bandwidth of 25.89%(from 23.2 GHz to 30.1 GHz). The measured realized gain is above 9 dBi in the whole band. The proposed antenna is suitable for 5G millimeter-wave applications.
Scheduling Rate Constrained traffic in End Systems of Time-Aware Networks

Nowadays, most of cyber-physical systems in avionics, automotive or recent Industry 4.0 domains require networked communication for mixed-critical applications. Ethernet-based networks such as AFDX, TTEthernet or TSN are capable to support transmission of both safety-critical and non-critical flows. This paper focuses on the TTEthernet network compliant with the avionics ARINC 664-P7 standard supporting time-triggered communication (TT) together with rate-constrained (RC) and best-effort (BE) traffic. Due to a global synchronization, TT communication with low latency and minimal jitter is ensured with static schedules computed offline. For event-triggered RC flows, bounded jitter at the source and end-to-end latency are guaranteed with worst-case analysis methods. With the increasing demands of applications, flows with Quality of Service (QoS) requirements such as video or audio may be transmitted as BE flows. However, on current configurations, no guarantees are offered to BE flows. In this paper, we aim at increasing the maximum RC utilization and improving the QoS of BE flows to allow the transmission of video or audio traffic with low jitter and end-to-end delay requirements. For this, we focus on the scheduling mechanisms and propose a scheduling approach based on a static slotted table that is applied at end systems. This table integrates the TT schedules usually obtained with Satisfiability Modulo Theories (SMT) approaches and establishes offsets of RC flows that reduce the end-to-end delay of BE flows. Several strategies for offset computations are proposed based on the distribution of flows locally at end system or globally at switch. We show that local strategies perform better than the global ones to reduce end-to-end delay of BE flows.
On the Relation of Refactoring and Software Defects

This paper analyzes the influence of evolution activities such as refactoring on software defects. In a case study of five open source projects we used attributes of software evolution to predict defects in time periods of six months. We use versioning and issue tracking systems to extract 110 data mining features, which are separated into refactoring and non-refactoring related features. These features are used as input into classification algorithms that create prediction models for software defects. We found out that refactoring related features as well as non-refactoring related features lead to high quality prediction models. Additionally, we discovered that refactorings and defects have an inverse correlation: The number of software defects decreases, if the number of refactorings increased in the preceding time period. As a result, refactoring should be a significant part of both bug fixes and other evolutionary changes to reduce software defects.
On Radio Access Network Uplink Latency and Jitter : Measurements and Analysis

This work studies the latency experienced by a TCP connection in an operational LTE RAN. After exhibiting the well-known downlink bufferbloat phenomenon, our experiments shed some light on the less studied RAN uplink jitter. We explain this uplink jitter by the uplink grant-based access method. These results are reproduced in a lab environment based on the OpenAirInterface software RAN, and demonstrate the importance of RAN configuration and limitations in the current LTE standard. We conclude on open issues in the 5G grant allocation process and the current grant-free access methods.
An Attention-Based Bidirectional Gated Recurrent Unit Network for Location Prediction

Locating trajectories of users has become a popular application in our daily life. How to effectively discriminate the importance of various contextual information is crucial to location prediction. Many works based on Recurrent Neural Network(RNN) models have shown promising performance by modeling the location prediction as a signal sequence processing problem and incorporating diverse characteristics into the hidden state of RNNs. However, these works rarely consider the internal relationship between locations. To overcome this limitation, we firstly propose a feedback mechanism to compensate for forward propagation, which innovatively takes advantage of the regularity of human trajectory. Then, we adopt the bidirectional Gated Recurrent Unit(GRU) network combined with data augmentation to model spatiotemporal information. Moreover, we focus on more significant factors with the attention mechanism during training, which can enhance the reliability of prediction. Experiments evaluate on three popular real-world datasets show that our model yields remarkable improvements over the compared methods.
A Graphical Convolutional Network-based Method for 3D Point Cloud Classification

Point cloud data classification has been widely used in autonomous driving, robot perception, and virtual/augmented reality. Due to its irregularity and disorder, the classification task of point clouds needs to transform the point cloud into a multi-view or voxel grid, and then use the traditional convolution neural network processing. However, this process is not only complex in operation but also low in classification accuracy. To solve this problem, a new point cloud classification method based on the graphical convolutional neural network (GCN) is proposed. Firstly, based on PointNet, KNN graph is introduced to obtain global deep features. Then the 3D point cloud is represented as a directed graph, local features are extracted by edge convolution. Finally, the extracted global and local features are aggregated to represent and classify point clouds. The proposed network is evaluated on the open dataset ModelNet40 and 3DMNIST. Experimental results show that the proposed network can achieve on par or better performance than state-of-the-art, such as PointNet, PointNet++, DGCNN, and PointCNN, for point cloud classification.
A Novel Low-Cost Quadruped Robot with Joint Fault-Tolerant Control

The quadruped robots among legged robots have been developed for scientific research and human life due to the better-complicated terrain adaptability. A novel quadruped robot designed with low cost and low energy consumption is proposed in this work, and each leg is actuated by direct drive servos. The three degrees of freedom leg kinematics are calculated, and the trotting gait algorithm is adopted to make the robot capable of walking. Under complex tasks, the multi-joint and multi-degree-of-freedom drive of the robot mean potential failures. A fault-tolerant control strategy for the joint stick is adopted, maintaining part of workability when the fault occurs. The walking experiment has confirmed that when the quadruped robot joint faults, it can still work with the performance degradation. Therefore, the robot has higher reliability and fault tolerance to complete complex tasks and explore extraterrestrial planets instead of wheeled vehicles.
Multi Objective Optimization for Spur Gear Design Using Sheep Flocks Heredity Model Algorithm

In a perspective of stable industrial development to manufacture added consistent and economical industrial product, gears are ever more focus to requirements in terms of power capability, efficiency and compactness etc. In order to increase the performance factors of gears such as transmission capacity, efficiency, gear life, etc. is a difficult criteria for a design engineers as these are all progress in a conflicting behavior. This paper deals with the multi-objective optimization of spur gear drive design with two contradictory objective functions such as maximization of power transmission and minimization of volume of the gear drive. These objectives are approached by an optimization technique based on a Sheep Flocks Heredity Model Algorithm (SFHM) with design constraints like stress, center distance etc. A spur gear problem is solved with traditional trial method and results are compared with proposed algorithm.
A Novel Approach to Characterize the Lipidome of Marine Archaeon Nitrosopumilus maritimus by Ion Mobility Mass Spectrometry

Archaea are differentiated from the other two domains of life by their biomolecular characteristics. One such characteristic is the unique structure and composition of their lipids. Characterization of the whole set of lipids in a biological system (the lipidome) remains technologically challenging. This is because the lipidome is innately complex, and not all lipid species are extractable, separable, or ionizable by a single analytical method. Furthermore, lipids are structurally and chemically diverse. Many lipids are isobaric or isomeric and often indistinguishable by the measurement of mass or even their fragmentation spectra. Here we developed a novel analytical protocol based on liquid chromatography ion mobility mass spectrometry to enhance the coverage of the lipidome and characterize the conformations of archaeal lipids by their collision cross-sections (CCSs). The measurements of ion mobility revealed the gas-phase ion chemistry of representative archaeal lipids and provided further insights into their attributions to the adaptability of archaea to environmental stresses. A comprehensive characterization of the lipidome of mesophilic marine thaumarchaeon, Nitrosopumilus maritimus (strain SCM1) revealed potentially an unreported phosphate- and sulfate-containing lipid candidate by negative ionization analysis. It was the first time that experimentally derived CCS values of archaeal lipids were reported. Discrimination of crenarchaeol and its proposed stereoisomer was, however, not achieved with the resolving power of the SYNAPT G2 ion mobility system, and a high-resolution ion mobility system may be required for future work. Structural and spectral libraries of archaeal lipids were constructed in non-vendor-specific formats and are being made available to the community to promote research of Archaea by lipidomics.
CALIBRATION METHODS FOR SOIL PROPERTY ESTIMATION USING REFLECTANCE SPECTROSCOPY

Optical diffuse reflectance sensing is a potential approach for rapid and reliable on-site estimation of soil properties. One issue with this sensing approach is whether additional calibration is necessary when the sensor is applied under conditions (e.g., soil types or soil moisture conditions) different from those used to generate an initial calibration, and if so, how many sample points are required in this additional calibration. In this study, these issues were addressed using data from ten fields in five states in the U.S. Corn Belt. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on the ratio of standard deviation to RMS error (RPD), a statistic commonly used in spectral analysis. When sample data from the field where calibrations were to be applied (i.e., test field) were included in the calibration stage (full information calibration), RPD values of prediction models were increased by an average of 0.55 (from 1.08 to 1.63) compared with results from models not including data from the test field (calibration without field-specific information). Including some samples from the test field (hybrid calibration) generally increased RPD to 90% of that from full information calibration (average increase = 0.49) by using data from 8 to 20 soil cores, with little further improvement given additional data. Using test field points as a bias adjustment (two-stage calibration) increased RPD by an average of 0.29 with two to six sample points, a finding that was confirmed by Monte Carlo simulation. These results show the importance of including in a calibration set samples similar (i.e., obtained from the same or similar fields) to those in the test set. These similar samples could be included directly in the calibration or could be used to implement a post-calibration bias adjustment. Although results were more accurate with the recalibration approach, the bias adjustment approach was more efficient computationally and required less data. Thus, either might be preferred depending on specific circumstances.
Subspace model identification of guided wave propagation in metallic plates

In this study, a data-driven subspace system identification approach is proposed for modeling guided wave propagation in plate media. In the data-driven approach, the subspace system identification estimates a mathematical model fitted to experimentally measured data, but the black-box model identified captures the dynamics of wave propagation. To demonstrate the versatility of the black-box model, wave motions in various shapes of aluminum plates are investigated in the study. In addition, a waveform predictor and temperature change indicator are proposed as applications of the black-box models, to further promote the modeling approach to guided wave propagation.
Proper semirings and proper convex functors

Esik and Maletti introduced the notion of a proper semiring and proved that some important (classes of) semirings – Noetherian semirings, natural numbers – are proper. Properness matters as the equivalence problem for weighted automata over proper and finitely and effectively presented semirings is decidable. Milius generalised the notion of properness from a semiring to a functor. As a consequence, a semiring is proper if and only if its associated “cubic functor” is proper. Moreover, properness of a functor renders soundness and completeness proofs of axiomatizations of equivalent behaviour. In this paper we provide a method for proving properness of functors, and instantiate it to cover both the known cases and several novel ones: (1) properness of the semirings of positive rationals and positive reals, via properness of the corresponding cubic functors; and (2) properness of two functors on (positive) convex algebras. The latter functors are important for axiomatizing trace equivalence of probabilistic transition systems. Our proofs rely on results that stretch all the way back to Hilbert and Minkowski.
Heritability and the genetic correlation of heart rate variability and blood pressure in >29 000 families: the Lifelines Cohort Study

Dysregulation of the cardiac autonomic nervous system, as indexed by reduced heart rate variability (HRV), has been associated with the development of high blood pressure (BP). However, the underlying pathological mechanisms are not yet fully understood. This study aimed to estimate heritability of HRV and BP and to determine their genetic overlap. We used baseline data of the three-generation Lifelines population-based cohort study (n=149,067, mean age=44.5). In-house software was used to calculate root mean square of successive differences and SD of normal-to-normal intervals as indices of HRV based on 10-second resting ECGs. BP was recorded with an automatic BP monitor. We estimated heritabilities and genetic correlations with variance components methods in ASReml software. We additionally estimated genetic correlations with bivariate linkage disequilibrium score regression using publicly available genome-wide association study data. The heritability (SE) estimates were 15.6% (0.90%) for SD of normal-to-normal intervals and 17.9% (0.90%) for root mean square of successive differences. For BP measures, they ranged from 24.4% (0.90%) for pulse pressure to 30.3% (0.90%) for diastolic BP. Significant negative genetic correlations (all P<0.0001) of RMSSD/SDNN with systolic BP (-0.20/-0.16) and with diastolic BP (-0.15/-0.13) were observed. LD score regression showed largely consistent genetic correlation estimates of root mean square of successive differences/SD of normal-to-normal intervals with systolic BP (range: -0.08 to -0.23) and diastolic BP (range: -0.20 to -0.27). Our study shows a substantial contribution of genetic factors in explaining the variance of HRV and BP measures in the general population. The significant negative genetic correlations between HRV and BP indicate that genetic pathways for HRV and BP partially overlap.