Miracle-dz/UniFAR-FTUs huggingface dataset:
Hsa_circ_0008309 May Be a Potential Biomarker for Oral Squamous Cell Carcinoma

Objective Oral squamous cell carcinoma (OSCC) is the most common cancer of the head and neck region. The circular RNA (circRNA) is known to serve an important role in the carcinogenesis of different types of cancer. However, the circRNA role of OSCC remains unclear. Methods 8 pairs of OSCC tissues and adjacent normal tissues were obtained to detect circRNAs expression by high-throughput sequencing, and 45 pairs of OSCC tissues were selected to verify the differentially significant circRNAs by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). To further investigate the role of hsa_circ_0008309, the circRNA-microRNA (miR)-mRNA network was predicted using bioinformatics databases. The expression levels of hsa_circ_0008309, miR-1290, miR-136-5P, and miR-382-5P in SCC-15 and CAL27 cell lines were detected by RT-qPCR. Western blotting was performed to detect the protein level of Ataxin 1 (ATXN1). Results The high-throughput sequencing results demonstrated that circRNAs were abundantly expressed in OSCC, and 16 circRNAs were significantly differentially expressed. Hsa_circ_0008309 was significantly downregulated in 45 pairs of OSCC tissue samples and was statistically correlated with pathological differentiation. The bioinformatics databases suggested that hsa_circ_0008309 could combine with miR-1290, miR-136-5P, and miR-382-5P, respectively, to regulate the expression of ATXN1. It was subsequently identified that hsa_circ_0008309 may inhibit miR-136-5P and miR-382-5P expression and increase ATXN1 expression in the OSCC cell lines. Conclusion In summary, the results of the present study revealed that OSCC tissues have abundant circRNAs and, to the best of our knowledge, we firstly explore the regulatory role of the hsa_circ_0008309-miR-136-5P/hsa-miR-382-5P-ATXN1 network in OSCC. The results indicated that hsa_circ_0008309 may be a potential biomarker for OSCC.
Use of a Purpose-Built Impression Cytology Device for Gene Expression Quantification at the Ocular Surface Using Quantitative PCR and Droplet Digital PCR

Purpose: To describe an impression cytology (IC) technique using a purpose-built, sterile, EYEPRIM IC device that can be coupled with a TRIzol reagent–based RNA extraction protocol to yield sufficient RNA for gene expression analysis. Methods: IC samples using the EYEPRIM device were collected from the bulbar conjunctiva, with and without topical anesthesia, and evaluated for RNA yield, the absence of polymerase chain reaction (PCR) inhibitors, and the ability to detect biomarkers by quantitative real-time PCR and droplet digital PCR. A technique for collecting IC samples in the clinic, while preserving RNA, and a protocol for subsequent laboratory analysis of RNA were developed. Results: The extracted RNA was free of PCR inhibitors and could be synthesized into complementary DNA and used for successful relative quantification of ocular surface biomarkers by quantitative real-time PCR. For gene targets present in low abundance, complementary DNA could also be used for quantification by the relatively new and emerging method of droplet digital PCR. The described method was successfully used to evaluate 3 biomarkers in a clinical trial assessing the tolerability of a proprietary eyelid therapy in 92 IC samples from a study population of 46 participants. Conclusions: IC is a recognized technique for ocular surface cell evaluation and protein biomarker quantification but is infrequently used for quantifying gene expression. The EYEPRIM device allows ease of use and impression-to-impression consistency while accurate gene expression data offers a highly specific and sensitive method of disease characterization for clinician scientists to use in diagnosis.
Enhanced Text-Guided Attention Model for Image Captioning

Attention mechanism plays an important role in understanding images and demonstrates its effectiveness in generating natural language descriptions of images. In recent years, with the advance of deep neural networks, visual attention has been well exploited in the encoder-decoder neural network-based framework. On the one hand, existing study shows that guidance captions can help attend to relevant image regions and suppress unimportant ones during the image encoding stage, especially for cluttered images. On the other hand, visual attention has been well exploited during the decoding stage. Observing the naturally complementary property between them, we propose a two-side attention model which combines the attention mechanism seamlessly and associated with a coarse to fine attention mechanism. The original text-guided attention model operates on region-level image feature, which is lack of definite semantic information and causes unsatisfied attention visualization. We alleviate the problem by enabling attention to be calculated at object-level image feature, which helps to obtain performance improvement and more interpretable attention visualization. Experiments conducted on MSCOCO datasets demonstrate the consistent improvement on text-guided attention model for image captioning.
Merge: An Architecture for Interconnected Testbed Ecosystems

In the cybersecurity research community, there is no one-size-fits-all solution for merging large numbers of heterogeneous resources and experimentation capabilities from disparate specialized testbeds into integrated experiments. The current landscape for cyber-experimentation is diverse, encompassing many fields including critical infrastructure, enterprise IT, cyber-physical systems, cellular networks, automotive platforms, IoT and industrial control systems. Existing federated testbeds are constricted in design to predefined domains of applicability, lacking the systematic ability to integrate the burgeoning number of heterogeneous devices or tools that enable their effective use for experimentation. We have developed the Merge architecture to dynamically integrate disparate testbeds in a logically centralized way that allows researchers to effectively discover, and use the resources and capabilities provided the by evolving ecosystem of distributed testbeds for the development of rigorous and high-fidelity cybersecurity experiments.
Microgrid Topology Planning for Enhancing the Reliability of Active Distribution Networks

Loop-based microgrids are signified by their high reliability in islanded and grid-connected operations. This paper proposes an iterative procedure for the optimal design of a microgrid topology in active distribution networks, which applies graph partitioning, integer programming, and performance index for the optimal design. The proposed approach avoids infeasible and non-optimal designs of microgrid structures and provides remedial solutions for enhancing our previous topology design method. The numerical results for a microgrid test system show that the proposed designated steps can optimize a loop-based microgrid structure in an active distribution network.
A Compact Wideband Circular Polarized Fabry-Perot Antenna Using Resonance Structure of Thin Dielectric Slabs

A wideband small-footprint circularly polarized Fabry-Perot resonator antenna is presented in this paper. The design employs a partial reflecting surface (PRS) consisting of thin homogeneous dielectric slabs separated by a small air gap. The PRS is analyzed using transmission line theory, which gives more insightful into the theoretical concept and provides a simple tool for design and optimization. An antenna prototype with overall size of <inline-formula> <tex-math notation="LaTeX">$1.2\lambda _{f_{\text {min}}} \times 1.2\lambda _{f_{\text {min}}} \times 0.6\lambda _{f_{\text {min}}}$ </tex-math></inline-formula> has been fabricated and experimentally validated (<inline-formula> <tex-math notation="LaTeX">$\lambda _{f_{\text {min}}}$ </tex-math></inline-formula> being the free-space wavelength at the minimum operating frequency). The measured impedance matching and axial ratio bandwidths are approximately 55.7% and 47.7%, respectively. In addition, the antenna achieved 3-dB gain bandwidth of 50.9% with a peak gain of 15 dBi. Compared to previous designs targeting similar applications, the antenna proposed here possesses a simple geometry with light weight, ease of optimization and fabrication, as well as enhanced axial ratio bandwidth and 3-dB gain bandwidth.
On the Convergence Properties of Autonomous Demand Side Management Algorithms

In this paper, we focus on the convergence of autonomous demand side management (A-DSM) algorithms which are widely discussed in the literature of smart grid. We prove that the Nash equilibrium of these algorithms is not unique, however, the Nash equilibria form a convex set, and each consumer’s payoff is the same over this set. Moreover, it is proved that the A-DSM program is convergent to the equilibria set if the consumers take turns in the algorithm. When a large number of consumers participate in the A-DSM program, it takes a long time to converge. Therefore, we modify the A-DSM algorithm such that the consumers can make decision in parallel. The proposed algorithm increases the convergence rate by several folds while the scheduled load profile and the system cost remain very close to those of the original A-DSM algorithm.
Characterization of PXI-Based Generators for Impedance Measurement Setups

This paper describes the comparison of properties of three commercially available multiphase digital ac voltage sources made as PXI modules. The research concerned their two-phase configuration for use in impedance bridges. Considering the assumed field of application, the most important parameters like the stability of amplitude ratio and phase difference as well as the total harmonic distortion and the spurious-free dynamic range was examined.
Towards Making Distributed RDF Processing FLINKer

In the last decade, the Resource Description Framework (RDF) has become the de-facto standard for publishing semantic data on the Web. This steady adoption has led to a significant increase in the number and volume of available RDF datasets, exceeding the capabilities of traditional RDF stores. This scenario has introduced severe big semantic data challenges when it comes to managing and querying RDF data at Web scale. Despite the existence of various off-the-shelf Big Data platforms, processing RDF in a distributed environment remains a significant challenge. In this position paper, based on an in-depth analysis of the state of the art, we propose to manage large RDF datasets in Flink, a well-known scalable distributed Big Data processing framework.
Invocation-driven Neural Approximate Computing with a Multiclass-Classifier and Multiple Approximators

Neural approximate computing gains enormous energy-efficiency at the cost of tolerable quality-loss. A neural approximator can map the input data to output while a classifier determines whether the input data are safe to approximate with quality guarantee. However, existing works cannot maximize the invocation of the approximator, resulting in limited speedup and energy saving. By exploring the mapping space of those target functions, in this paper, we observe a nonuniform distribution of the approximation error incurred by the same approximator. We thus propose a novel approximate computing architecture with a Multiclass-Classifier and Multiple Approximators (MCMA). These approximators have identica network topologies, and thus can share the same hardware resource in an neural processing unit(NPU) clip. In the runtime, MCMA can swap in the invoked approximator by merely shipping the synapse weights from the on-chip memory to the buffers near MAC within a cycle. We also propose efficient co-training methods for such MCMA architecture. Experimental results show a more substantial invocation of MCMA as well as the gain of energy-efficiency.
Fabrication and Sensitivity Analysis of Guided Beam Piezoelectric Energy Harvester

This paper reports the fabrication of MEMS-based guided two-beam piezoelectric energy harvester for low-frequency operation. A highly c-axis-oriented zinc oxide thin film of 2.5-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> thickness covered with 0.5-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> plasma-enhanced chemical vapor deposition SiO<sub>2</sub> is sandwiched between the aluminum electrodes to form split electrodes on the two beams. A pyramidal-shaped seismic mass that gives a higher electric potential is realized by bulk micromachining using CMOS compatible 25 wt% tetramethyl ammonium hydroxide wet etching. The thickness of the beams is optimized using deep reactive-ion etching to achieve a low-frequency operation. COMSOL Multiphysics has been used to study the stress distribution to optimize the dimension and placement of the split electrodes. The optimized split electrodes give a reduced resonance frequency by 4.2% when compared with previously used electrode pattern ensuring maximum electric potential generation for guided two-beam structure. The resonance frequency of the device measured experimentally using laser Doppler vibrometer comes to be 466 Hz. The packaged device exhibits a maximum sensitivity of 1.5089 mV/m/s<sup>2</sup> in the frequency range from 160 to 1000 Hz.
SPARC acts as a mediator of TGF‐&bgr;1 in promoting epithelial‐to‐mesenchymal transition in A549 and H1299 lung cancer cells

Migration and metastasis of tumor cells greatly contributes to the failure of cancer treatment. Recently, the extracellular protein secreted protein acidic and rich in cysteine (SPARC) has been reported closely related to tumorigenesis. Some articles have suggested that SPARC promoted metastasis in several highly metastatic tumors. However, there are also some studies shown that SPARC acted as an antitumor factor. SPARC-induced epithelial-to-mesenchymal transition (EMT) in melanoma cells and promoted EMT in hepatocellular carcinoma. Therefore, the role of SPARC in tumorigenesis and its relationship with EMT is still unclear. In this study, we investigated the expression change of SPARC in A549 and H1299 lung cancer cells undergoing EMT process. Our study indicated that SPARC was upregulated in A549 and H1299 cells EMT process. We further investigated the function of SPARC on proliferation, migration, and EMT process of A549 and H1299 cells. Overexpression of SPARC promoted the migration and EMT of A549 and H1299 cells. Knockdown SPARC inhibited the EMT of A549 cells. Overexpression of SPARC induced the increased expression of p-Akt and P-ERK. Furthermore, exogenous SPARC peptide promoted transforming growth factor (TGF)-β1-induced EMT of A549 and H1299 cells. SPARC knockdown partially eliminated TGF-β1 function in inducing EMT of A549 cells. SPARC follistatin-like functional domain reduced the expression of E-cadherin, but had no effect on the expression of p-Akt and p-ERK. In conclusion, we elucidated that SPARC contributes to tumorigenesis by promoting migration and EMT of A549 and H1299 lung cancer cells. These results will provide some new suggestion for lung cancer treatment. © 2018 BioFactors, 44(5):453-464, 2018.
Heart rate variability measurement in epilepsy: How can we move from research to clinical practice?

Our objective was to critically evaluate the literature surrounding heart rate variability (HRV) in people with epilepsy and to make recommendations as to how future research could be directed to facilitate and accelerate integration into clinical practice. We reviewed relevant HRV publications including those involving human subjects with seizures. HRV has been studied in patients with epilepsy for more than 30 years and, overall, patients with epilepsy display altered interictal HRV, suggesting a shift in autonomic balance toward sympathetic dominance. This derangement appears more severe in those with temporal lobe epilepsy and drug‐resistant epilepsy. Normal diurnal variation in HRV is also disturbed in at least some people with epilepsy, but this aspect has received less study. Some therapeutic interventions, including vagus nerve stimulation and antiepileptic medications, may partially normalize altered HRV, but studies in this area are sometimes contradictory. During seizures, the changes in HRV may be complex, but the general trend is toward a further increase in sympathetic overactivity. Research in HRV in people with epilepsy has been limited by inconsistent experimental protocols and studies that are often underpowered. HRV measurement has the potential to aid clinical epilepsy management in several possible ways. HRV may be useful in predicting which patients are likely to benefit from surgical interventions such as vagus nerve stimulation and focal cerebral resection. As well, HRV could eventually have utility as a biomarker of risk for sudden unexpected death in epilepsy (SUDEP). However, at present, the inconsistent measurement protocols used in research are hindering translation into clinical practice. A minimum protocol for HRV evaluation, to be used in all studies involving epilepsy patients, is necessary to eventually allow HRV to become a useful tool for clinicians. We propose a straightforward protocol, involving 5‐minute measurements of root mean square of successive differences in wakefulness and light sleep.
Compression of Plenoptic Point Clouds

Point clouds have been recently used in applications involving real-time capture and rendering of 3D objects. In a point cloud, for practical reasons, each point or voxel is usually associated with one single color along with other attributes. The region-adaptive hierarchical transform (RAHT) coder has been proposed for single-color point clouds. The cloud is usually captured by many cameras and the colors are averaged in some fashion to yield the point color. This approach may not be very realistic since, in real world objects, the reflected light may significantly change with the viewing angle, especially if specular surfaces are present. For that, we are interested in a more complete representation, the plenoptic point cloud, wherein every point has associated colors in all directions. Here, we propose a compression method for such a representation. Instead of encoding a continuous function, since there is only a finite number of cameras, it makes sense to compress as many colors per voxel as cameras, and to leave any intermediary color rendering interpolation to the decoder. Hence, each voxel is associated with a vector of color values, for each color component. We have here developed and evaluated four methods to expand the RAHT coder to encompass the multiple colors case. Experiments with synthetic data helped us to correlate specularity with the compression, since object specularity, at a given point in space, directly affects color disparity among the cameras, impacting the coder performance. Simulations were carried out using natural (captured) data and results are presented as rate-distortion curves that show that a combination of Kahunen–Loève transform and RAHT achieves the best performance.
Rested and Restless Bandits With Constrained Arms and Hidden States: Applications in Social Networks and 5G Networks

The problem of rested and restless multi-armed bandits with constrained availability (RMAB-CA) of arms is considered. The states of arms evolve in Markovian manner and the exact states are hidden from the decision maker. First, some structural results on value functions are claimed. Following these results, the optimal policy turns out to be a threshold policy. Furthermore, indexability is established for both rested and restless RMAB-CAs. An index formula is derived for the rested model, while an algorithm is provided for restless case.
Secure Downlink Transmission in the Internet of Things: How Many Antennas Are Needed?

Physical layer security is a promising way to secure the wireless communications in the Internet of Things (IoT). Motivated by the fact that the limited feedback resources in the IoT network would degrade the secrecy advantage of the multiple-antenna technique, we attempt to investigate the problem of how many transmit antennas should be utilized to perform secure communications. In particular, we consider the heterogeneous IoT downlink network and design a multiuser secure transmission scheme. In this scheme, the zero-forcing beamforming technique is adopted to serve the IoT legitimate users, and the remaining spatial freedoms are utilized to send artificial noise (AN) for confusing the passive eavesdroppers. Given the secrecy outage constraints, we derive the closed-form expression for the network secrecy throughput and formulate a non-convex optimization problem with multiple parameters, e.g., the number of transmit antennas, the wiretap codes, the feedback bits allocation strategy, and the power allocation ratio between the information bearing signal and the AN. To effectively tackle this problem, we develop an optimization framework involving the block coordinate descent algorithm and the 1-D search method. Simulation results validate the effectiveness of our proposed optimization framework and show that the optimal number of transmit antennas increases as the secrecy outage constraints become stricter, or the feedback resources become scarcer.
Distributed Lifetime Optimization of Wireless Sensor Networks in Smart Grid

Wireless sensor networks (WSNs) have the potential for realization economical automation systems in a smart grid where the different type of sensors mote can be used to monitor a wide range of the smart grid environment’s parameters. Energy restriction of wireless sensor nodes and consequently lifetime of the network is a real challenge in WSNs applications like the smart grid. The WSN lifetime can be formulated as an optimization problem. In this paper, the alternating direction method of multipliers (ADMM) algorithm is used to implement a novel distributed iterative algorithm for the problem of extending the sensor network lifetime. The proposed algorithm has some striking feature that including use of local information, low overhead of message passing, low computational complexity, fast convergence, and reduced energy consumption. The experiment results related to the convergence and number of iterations required to achieve the stopping criterion presented. As well as, the results of proposed algorithm compared with the subgradient methods. In comparison, the proposed ADMM-based algorithm outperforms the other methods.
A Simulation-Based Policy Improvement Method for Joint-Operation of Building Microgrids With Distributed Solar Power and Battery

This paper investigates the joint-operation of building microgrids with distributed solar power and storage battery. The purpose of this paper is to improve the energy efficiency of the building microgrids taking advantage of the complementary building load profiles. Three major contributions are made in this paper. First, in order to incorporate the uncertainties in both the building load and solar power as well as in the communication system, the operation problem is formulated as a finite-stage event-based optimization model. Second, an on-line simulation-based policy improvement method is developed to improve the given control policy and an action aggregation method is applied to accelerate the computational speed. Third, a balanced battery operation strategy considering the expected life cycles is proposed. Numerical examples based on the building microgrids in a university campus are used to demonstrate the effectiveness of the proposed method in improving the building energy efficiency. The computational time in a practical system is also analyzed.