Miracle-dz/UniFAR-FTUs huggingface dataset:
Toll-like receptor 2 induces adenosine receptor A2a and promotes human squamous carcinoma cell growth via extracellular signal regulated kinases ½

Patient treatment for oral squamous cell carcinoma (OSCC) not associated with Human papillomavirus remains problematic. OSCC microenvironment is typically inflamed and colonized by microorganisms, providing ligands for toll-like receptors (TLR). In immune cells TLR2 and TLR4 activate NF-kB and extracellular signal regulated kinase (ERK)1/2 pathways, leading to upregulation of inhibitory adenosine receptors A2a and A2b, and reduction in stimulatory A1 and A3. How TLR and adenosine receptors function in SCC cells is not understood. To address this gap, we evaluated TLR and adenosine receptor expression and function in human OSCC cells and keratinocytes. TLR2 and A2a were co-expressed in pre-cancer and SCC cells of 17 oral specimens. In vitro, 5/6 OSCC lines expressed more TLR2 than TLR1, 4 or 6 mRNA. TLR2 ligands stimulated A2a expression in TLR2-high cell lines, but no A1 or A3 was detected with or without stimuli. In TLR2-high OSCC, TLR2/1, 2/6 and adenosine receptor agonists activated ERK1/2. TLR2-mediated ERK1/2 phosphorylation resulted in accumulation of c-FOS, ERK-dependent cell proliferation and reduced caspase-3 activity. Similar ERK1/2-dependent proliferation and decreased caspase-3 activity were caused by combined TLR2 and adenosine receptor stimuli. We conclude that TLR2 and adenosine receptor agonists, known to be present in the tumor microenvironment, may contribute to OSCC progression in part via direct effects on the ERK1/2 pathway in squamous carcinoma cells.
Surveying and selling: Belief and surplus extraction in auctions Job market paper

I consider the mechanism design problem of a seller who is uninformed about demand, while potential buyers are well-informed. The seller knows that (1) values are private, (2) buyers’ beliefs are consistent with a common prior, and (3) the support of values is bounded relative to the expected efficient surplus. The seller’s goal is to maximize the minimum ratio between expected revenue and the expected efficient surplus, which I term the extraction ratio. I characterize simple mechanisms that maximize the minimum extraction ratio. In these mechanisms, the seller runs a second-price auction and simultaneously surveys the beliefs of buyers about others’ values. Losing bidders’ responses to the survey are used to set the reserve price for the winner. Such mechanisms guarantee the seller a substantial share of the efficient surplus, with the share parametrized by the bound on the highest value. If values can be up to ten times the expected efficient surplus, the seller is guaranteed a 20% revenue-share; up to 1,000 times, and the seller is guaranteed 10%.
Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering

Monocular cameras are one of the most commonly used sensors in the automotive industry for autonomous vehicles. One major drawback using a monocular camera is that it only makes observations in the two dimensional image plane and can not directly measure the distance to objects. In this paper, we aim at filling this gap by developing a multi-object tracking algorithm that takes an image as input and produces trajectories of detected objects in a world coordinate system. We solve this by using a deep neural network trained to detect and estimate the distance to objects from a single input image. The detections from a sequence of images are fed in to a state-of-the art Poisson multi-Bernoulli mixture tracking filter. The combination of the learned detector and the PMBM filter results in an algorithm that achieves 3D tracking using only mono-camera images as input. The performance of the algorithm is evaluated both in 3D world coordinates, and 2D image coordinates, using the publicly available KITTI object tracking dataset. The algorithm shows the ability to accurately track objects, correctly handle data associations, even when there is a big overlap of the objects in the image, and is one of the top performing algorithms on the KITTI object tracking benchmark. Furthermore, the algorithm is efficient, running on average close to 20 frames per second.
A 4 mm2 Double Differential Torsional MEMS Accelerometer Based on a Double-Beam Configuration

This paper reports the design and simulation of a 4 mm2 double differential torsional MEMS accelerometer based on a double-beam configuration. Based on the structure of conventional torsional accelerometers, normally composed of one pair of proof masses and one torsional beam, this work explores the double differential configuration: a torsional accelerometer with two pairs of unbalanced proof masses rotating in reverse. Also, the torsional beam is designed as a double-beam structure, which is a symmetrical structure formed by two torsional beams separated by a certain distance. The device area of the novel accelerometer is more than 50 times smaller than that of a traditional double differential torsional MEMS accelerometer. The FEM simulation results demonstrate that the smaller device does not sacrifice other specifications, such as mechanical sensitivity, nonlinearity and temperature robustness. The mechanical sensitivity and nonlinearity of a ±15 g measuring range is 59.4 fF/g and 0.88%, respectively. Compared with traditional single-beam silicon structures, the novel structure can achieve lower maximum principle stress in critical regions and reduce the possibility of failure when high-g acceleration loading is applied along all three axes. The mechanical noise equivalent acceleration is about 0.13 mg/Hz in the theoretical calculations and the offset temperature coefficient is 0.25 mg/℃ in the full temperature range of −40 ℃ to 60 ℃.
Single cell on-chip whole genome amplification via micropillar arrays for reduced amplification bias

Single cell whole genome amplification is susceptible to amplification biases that impact the accuracy of single cell sequencing data. To address this, we have developed a microfluidic device for the isolation and purification of genomic DNA from individual cells. The device uses a micropillar array to physically capture single cells and its chromosomal DNA upon extraction. The extracted DNA is immobilized within the micropillar array in a way that allows isothermal amplification. In this system, whole genome amplification of the single cell is carried out under a continual fluid flow within the microfluidic channel. We have demonstrated the process for amplification of individual human cancer cell genomes from the HeLa cell line. By sampling select gene loci along the human genome and performing whole exome sequencing, we demonstrate improved genome coverage and reduced amplification bias compared to amplification of single cells deposited in wells by fluorescence activated cell sorting.
STORIES in Time: A Graph-Based Interface for News Tracking and Discovery

We present the STORIES methods and tool for (a) learning an abstracted story representation from a collection of time-indexed documents; (b) visualising it in a way that encourages users to interact and explore in order to discover temporal “story stages” depending on their interests; and (c) supporting the search for documents and facts that pertain to the user-constructed story stages. In addition, we give an overview of evaluation studies of the tool.
A COMPUTATIONAL MODEL FOR PLOT UNITS

This research revisits plot units, which were developed in the 1980s as a conceptual knowledge structure to represent the affect states of and emotional tensions between characters in narrative stories. We present a fully automated system, called AESOP, that generates plot unit representations for narrative texts. AESOP performs four steps: affect state recognition, character identification, affect state projection, and link creation. We also identify a type of knowledge that seems to be missing from existing lexical resources: verbs that impart positive or negative polarity onto their patients (e.g., “eat” imparts negative polarity because being eaten is bad, whereas “fed” imparts positive polarity because being fed is good). We develop two techniques to automatically harvest these “patient polarity verbs” (PPVs) from a Web corpus, and show that the PPVs improve affect state recognition. Finally, we evaluate AESOP’s performance on a set of fables, and present several analyses to shed light on the capabilities and limitations of current natural language processing technology for plot unit generation.
Strong hydrophobic interaction between graphene oxide and supported lipid bilayers revealed by AFM

Understanding the interaction between graphene oxide (GO) and lipid membranes is of great importance for its various applications in biotechnology. Here, we investigated the interaction between GO and charged supported lipid bilayers (SLBs) by in situ atomic force microscope (AFM) imaging. It was found that GO could peel off a single layer of positively charged SLBs and deposited on the hydrophobic part of the remaining sublayer. Then free lipid molecules would assemble on GO surface and formed 1.5 bilayers in a lipid‐GO‐lipid manner. For negatively charged lipid bilayers, however, GO deposited to the SLBs only when its concentration was very high. These results indicate that, in addition to electrostatic interaction, the hydrophobic interaction plays an important role when GO sheets deposit onto the charged lipid bilayers, and should be helpful to understand possible cytotoxicity and antibiosis of graphene‐related nanomaterials. Microsc. Res. Tech. 79:721–726, 2016. © 2016 Wiley Periodicals, Inc.
Recognition of Atypical Symptoms of Acute Myocardial Infarction: Development and Validation of a Risk Scoring System

Background: Atypical symptom presentation in patients with acute myocardial infarction (AMI) is associated with longer delay in care seeking and poorer prognosis. Symptom recognition in these patients is a challenging task. Objectives: Our purpose in this risk prediction model development study was to develop and validate a risk scoring system for estimating cumulative risk for atypical AMI presentation. Methods: A consecutive sample was recruited for the developmental (n = 300) and validation (n = 97) cohorts. Symptom experience was measured with the validated Chinese version of the Symptoms of Acute Coronary Syndromes Inventory. Potential predictors were identified from the literature. Multivariable logistic regression was performed to identify significant predictors. A risk scoring system was then constructed by assigning weights to each significant predictor according to their b coefficients. Results: Five independent predictors for atypical symptom presentation were older age (≥75 years), female gender, diabetes mellitus, history of AMI, and absence of hyperlipidemia. The Hosmer and Lemeshow test (&khgr;26 = 4.47, P = .62) indicated that this predictive model was adequate to predict the outcome. Acceptable discrimination was demonstrated, with area under the receiver operating characteristic curve as 0.74 (95% confidence interval, 0.67–0.82) (P < .001). The predictive power of this risk scoring system was confirmed in the validation cohort. Conclusions: Atypical AMI presentation is common. A simple risk scoring system developed on the basis of the 5 identified predictors can raise awareness of atypical AMI presentation and promote symptom recognition by estimating the cumulative risk for an individual to present with atypical AMI symptoms.
A Novel Complex-Coefficient In-Band Interference Suppression Algorithm for Cognitive Ultra-Wide Band Wireless Sensors Networks

With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been considered as significant solutions to solve the harmonious coexistence issues. UWB wireless sensors can share the spectrum with primary user (PU) systems without harmful interference. The in-band interference of UWB systems should be considered because such interference can severely affect the transmissions of UWB wireless systems. In order to solve the in-band interference issues for UWB wireless sensor networks (WSN), a novel in-band narrow band interferences (NBIs) elimination scheme is proposed in this paper. The proposed narrow band interferences suppression scheme is based on a novel complex-coefficient adaptive notch filter unit with a single constrained zero-pole pair. Moreover, in order to reduce the computation complexity of the proposed scheme, an adaptive complex-coefficient iterative method based on two-order Taylor series is designed. To cope with multiple narrow band interferences, a linear cascaded high order adaptive filter and a cyclic cascaded high order matrix adaptive filter (CCHOMAF) interference suppression algorithm based on the basic adaptive notch filter unit are also presented. The theoretical analysis and numerical simulation results indicate that the proposed CCHOMAF algorithm can achieve better performance in terms of average bit error rate for UWB WSNs. The proposed in-band NBIs elimination scheme can significantly improve the reception performance of low-cost and low-power UWB wireless systems.
Potential prognostic biomarkers identified by DNA methylation profiling analysis for patients with lung adenocarcinoma

Lung adenocarcinoma is frequently occurring type of lung cancer with high metastatic risk. We performed a DNA methylation profiling analysis to identify possible prognostic markers involved in lung adenocarcinoma. DNA methylation profiling data (GSE66386) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially methylated genes were identified using a limma package. GO enrichment analysis was performed to identify vital functions related to differential gene methylation, and pathway analysis was performed to assess the associations between different proteins with regard to regulation of cell function and metabolism. The screening results showed a total of 112,662 differentially methylated genes in lung adenocarcinoma patients compared with those of the normal controls. These CpGs were involved in 16,705 genes. The skeletal system development (P=9.46E-27) and embryonic organ morphogenesis (P=8.67E-24) were found to be involved in lung adenocarcinoma. The cancer (P=3.64E-07), Rap1 signaling (P=9.21E-05) and calcium signaling (P=9.21E-05) pathways constituted the important pathways associated with lung adenocarcinoma. In conclusion, methylated PTPRF, HOXD3, HOXD13 and CACNA1A are potential markers and may be utilized for the diagnosis and therapy of lung adenocarcinoma.
Recurrent Residual Module for Fast Inference in Videos

Deep convolutional neural networks (CNNs) have made impressive progress in many video recognition tasks such as video pose estimation and video object detection. However, CNN inference on video is computationally expensive due to processing dense frames individually. In this work, we propose a framework called Recurrent Residual Module (RRM) to accelerate the CNN inference for video recognition tasks. This framework has a novel design of using the similarity of the intermediate feature maps of two consecutive frames, to largely reduce the redundant computation. One unique property of the proposed method compared to previous work is that feature maps of each frame are precisely computed. The experiments show that, while maintaining the similar recognition performance, our RRM yields averagely 2Ã— acceleration on the commonly used CNNs such as AlexNet, ResNet, deep compression model (thus 8-12Ã— faster than the original dense models using the efficient inference engine), and impressively 9Ã— acceleration on some binary networks such as XNOR-Nets (thus 500Ã— faster than the original model). We further verify the effectiveness of the RRM on speeding up CNNs for video pose estimation and video object detection.
Coordination in Networked Organizations: the Paradigm Approach

An extension of the coordination specication language Paradigm is presented. In this set-up Paradigm models cater for multiple managers sharing the coordination of a set of common employees. A transition system semantics for the language is provided, that allows for reasoning about such constructions as delegation and selfmanagement in matrix and general network organizations. An elaborated example illustrates the expressiveness of the proposed version of Paradigm.
Prevention and Control Strategies to Counter Zika Virus, a Special Focus on Intervention Approaches against Vector Mosquitoes—Current Updates

Zika virus (ZIKV) is the most recent intruder that acquired the status of global threat creating panic and frightening situation to public owing to its rapid spread, attaining higher virulence and causing complex clinical manifestations including microcephaly in newborns and Guillain Barré Syndrome. Alike other flaviviruses, the principal mode of ZIKV transmission is by mosquitoes. Advances in research have provided reliable diagnostics for detecting ZIKV infection, while several drug/therapeutic targets and vaccine candidates have been identified recently. Despite these progresses, currently there is neither any effective drug nor any vaccine available against ZIKV. Under such circumstances and to tackle the problem at large, control measures of which mosquito population control need to be strengthened following appropriate mechanical, chemical, biological and genetic control measures. Apart from this, several other known modes of ZIKV transmission which have gained importance in recent past such as intrauterine, sexual intercourse, and blood-borne spread need to be checked and kept under control by adopting appropriate precautions and utmost care during sexual intercourse, blood transfusion and organ transplantation. The virus inactivation by pasteurization, detergents, chemicals, and filtration can effectively reduce viral load in plasma-derived medicinal products. Added to this, strengthening of the surveillance and monitoring of ZIKV as well as avoiding travel to Zika infected areas would aid in keeping viral infection under check. Here, we discuss the salient advances in the prevention and control strategies to combat ZIKV with a focus on highlighting various intervention approaches against the vector mosquitoes of this viral pathogen along with presenting an overview regarding human intervention measures to counter other modes of ZIKV transmission and spread. Additionally, owing to the success of vaccines for a number of infections globally, a separate section dealing with advances in ZIKV vaccines and transmission blocking vaccines has also been included.
Effects of kinetics of light‐induced stomatal responses on photosynthesis and water‐use efficiency

Summary Both photosynthesis (A) and stomatal conductance (g s) respond to changing irradiance, yet stomatal responses are an order of magnitude slower than photosynthesis, resulting in noncoordination between A and g s in dynamic light environments. Infrared gas exchange analysis was used to examine the temporal responses and coordination of A and g s to a step increase and decrease in light in a range of different species, and the impact on intrinsic water use efficiency was evaluated. The temporal responses revealed a large range of strategies to save water or maximize photosynthesis in the different species used in this study but also displayed an uncoupling of A and g s in most of the species. The shape of the guard cells influenced the rapidity of response and the overall g s values achieved, with different impacts on A and W i. The rapidity of g s in dumbbell‐shaped guard cells could be attributed to size, whilst in elliptical‐shaped guard cells features other than anatomy were more important for kinetics. Our findings suggest significant variation in the rapidity of stomatal responses amongst species, providing a novel target for improving photosynthesis and water use.
Development of Antibacterial and Remineralising Composite Bone Cements

The thesis aim is to develop composite cement with (1) optimized curing time/ high reaction rate to prevent cement leakage (1) high monomer conversion to provide good strength, (2) water-sorption to compensate shrinkage and promote anti-bacterial release, (3) release of ions and antimicrobial to remineralise the bone structure and prevent infection, (5), assess the adhesive properties of composites and (4) antibacterial efficacy against various strains of Staphylococcus aureus. Curing time, reaction rate, monomer conversion/ shrinkage was assessed using FTIR and Raman. Water-sorption and anti-bacterial (polylysine and gentamicin) release into deionized water (DW) and simulated body fluid (SBF) were assessed using gravimetrical studies, and UV/ HPLC spectroscopy respectively. Flexural strength, modulus and compressive strength were assessed up to 1 months of SBF storage. Antibacterial efficacy was assessed via bacterial growth in suspension and biofilm formation on disc. Adhesive properties were assessed via pushout and shaerbond test. One way Anova, Two way Anova, Kruskal–Wallis one-way analysis of variance, regression analysis, factorial analysis were used to analyze the data. Increasing initiator and activator concentrations decreased curing time. Furthermore, they enhanced monomer conversion and strength. Addition of calcium phosphate fillers and antimicrobials decreased the curing time and monomer conversion. The major factors enhancing water-sorption were calcium filler and antimicrobial level. Calcium ion and gentamicin (Gen) release was enhanced by the use of deionized water instead of SBF, calcium fillers and polylysine. Higher polylysine (PLS) release was seen with low levels of antibacterial in the filler phase. Flexural strength, modulus and compressive strength were decreased with the addition of calcium fillers and antimicrobials. Lastly, PLS showed reduced bacterial growth in surrounding medium and on set material discs. These materials are therefore promising antibacterial injectable bone composites that could remineralise the bone structure and may prevent postoperative infection. These cements can be used for load bearing areas (vertebroplasty, Hip arthroplasty, dental filling) and non-load bearing areas (bone augmentation etc.).