Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced glycation end products induce neural tube defects through elevating oxidative stress in mice

Our previous study showed an association between advanced glycation end products (AGEs) and neural tube defects (NTDs). To understand the molecular mechanisms underlying the effect of AGEs on neural tube development, C57BL/6 female mice were fed for 4 weeks with commercial food containing 3% advanced glycation end product bovine serum albumin (AGE-BSA) or 3% bovine serum albumin (BSA) as a control. After mating mice, oxidative stress markers including malondialdehyde and H2O2 were measured at embryonic day 7.5 (E7.5) of gestation, and the level of intracellular reactive oxygen species (ROS) in embryonic cells was determined at E8.5. In addition to evaluating NTDs, an enzyme-linked immunosorbent assay was used to determine the effect of embryonic protein administration on the N-(carboxymethyl) lysine reactivity of acid and carboxyethyl lysine antibodies at E10.5. The results showed a remarkable increase in the incidence of NTDs at E10.5 in embryos of mice fed with AGE-BSA (no hyperglycemia) compared with control mice. Moreover, embryonic protein administration resulted in a noticeable increase in the reactivity of N-(carboxymethyl) lysine and N(ε)-(carboxyethyl) lysine antibodies. Malondialdehyde and H2O2 levels in embryonic cells were increased at E7.5, followed by increased intracellular ROS levels at E8.5. Vitamin E supplementation could partially recover these phenomena. Collectively, these results suggest that AGE-BSA could induce NTDs in the absence of hyperglycemia by an underlying mechanism that is at least partially associated with its capacity to increase embryonic oxidative stress levels.
Graphene FET Array Biosensor Based on ssDNA Aptamer for Ultrasensitive Hg2+ Detection in Environmental Pollutants

Invisible mercury ion is an extremely poisonous environmental pollutant, therefore, a fast and highly sensitive detection method is of significant importance. In this study, a liquid-gated graphene field-effect transistor (GFET) array biosensor (6 × 6 GFETs on the chip) was fabricated and applied for Hg2+ quantitate detection based on single-stranded DNA (ssDNA) aptamer. The biosensor showed outstanding selectivity to Hg2+ in mixed solutions containing various metal ions. Moreover, the sensing capability of the biosensor was demonstrated by real-time responses and showed a fairly low detection limit of 40 pM, a wide detection ranged from 100 pM to 100 nM and rapid response time below one second. These results suggest that the GFET array biosensor based on ssDNA aptamer offers a simple fabrication procedure and quite fast method for mercury ion contaminant detection and are promising for various analytical applications.
The Behaviors of Ionospheric Scintillations Around Different Types of Nightside Auroral Boundaries Seen at the Chinese Yellow River Station, Svalbard

Dynamical nightside auroral structures are often observed by the all sky imagers (ASI) at the Chinese Yellow River Station (CYRS) at Ny-Alesund, Svalbard, located in the polar cap near poleward edge of the nightside auroral oval. The boundaries of the nightside auroral oval are stable during quiet geomagnetic conditions, while they often expand poleward and pass through the overhead area of CYRS during the substorm expansion phase. The motions of these boundaries often give rise to strong disturbances of satellite navigations and communications. Two cases of these auroral boundary motions have been introduced to investigate their associated ionospheric scintillations: one is Fixed Boundary Auroral Emissions (FBAE) with stable and fixed auroral boundaries, and another is Bouncing Boundary Auroral Emissions (BBAE) with dynamical and largely expanding auroral boundaries. Our observations show that the auroral boundaries, identified from the sharp gradient of the auroral emission intensity from the ASI images, were clearly associated with ionospheric scintillations observed by Global Navigation Satellite System (GNSS) scintillation receiver at the CYRS. However, amplitude scintillation (S4) and phase scintillation (σφ) respond in an entirely different way in these two cases due to the different generation mechanism as well as different IMF (Interplanetary Magnetic Field) condition. S4 and σφ have similar levels around the FBAE, while σφ was much stronger than S4 around BBAE. The BBAE were associated with stronger particle precipitation during the substorm expansion phase. IU/IL, appeared to be a good indicator of the poleward moving auroral structures during the BBAE as well as FBAE.
Visual microscope for massive genomics datasets, expanded perception and interaction

An innovative fully interactive and ultra-high resolution navigation tool has been developed to browse and analyze gene expression levels from human cancer cells, acting as a visual microscope on data. The tool uses high-performance visualization and computer graphics technology to enable genome scientists to observe the evolution of regulatory elements across time and gain valuable insights from their dataset as never before.
Unifying Fixed Code Mapping, Communication, Synchronization and Scheduling Algorithms for Efficient and Scalable Loop Pipelining

Pipelining allows the execution of loop iterations with cross-iteration dependences to overlap in time, provided that the loop body is partitioned into stages such that the data dependences are not violated. Then, the stages are mapped onto threads and communication and synchronization between stages is typically achieved using queues. Pipelining techniques that rely on static scheduling perform poorly for load-imbalanced loops. Moreover, previous research efforts that achieve load-balancing are restricted to work-stealing and imply high overhead for fine-grained loops. In this article, we present URTS, a unified runtime system with compiler support that provides a lightweight dynamic scheduler by combining mapping, communication and synchronization algorithms with a suitable data structure and an efficient ticket mechanism. Particularly, URTS shows that it is possible to combine the efficiency of static scheduling with the load-imbalance tolerance of work-stealing by using a unified design that exploits the properties of a novel data structure. The evaluation on 8- and 32-core machines shows that URTS implies low overhead, of the same order as a static scheduler, for a set of benchmarks chosen from widely-used collections. URTS is a scalable solution that performs efficient dynamic scheduling for fine-grained loops, i.e., a class of interesting loops that is poorly handled by the state-of-the-art due to high overhead.
Photonic Crystal Circular-Defect Microcavity Laser Designed for Wavelength Division Multiplexing

Photonic crystal (PC) lasers with circular-defect (CirD) microcavity offer high-potential application in wavelength division multiplexing (WDM), and therefore, are a suitable candidate to realize intrachips optical communications. In this paper, a CirD laser for the WDM applications is designed for the first time by using the three-dimensional finite-difference time-domain method. For the realization of the WDM applications, it is critical to achieve the adequate high-quality (Q)-factor (>7142) in the bandwidth range over 20 nm, which is estimated from the characteristics of the gain medium and the coupling of the CirD cavity with a PC waveguide. After optimizing the laser structure, we achieved a constant high Q-factor of 15 000 within the bandwidth range of 25 nm. A proof-of-principle experiment of the lasing wavelength tuning was conducted by exploiting the CirD lasers with air/AlGaOx cladding layers under optical pumping conditions. The fabricated laser showed a single-mode lasing operation with the linewidth narrower than 0.07 nm (the resolution-limit of the optical spectrum analyzer) and side mode suppression ratio of ∼20 dB. The wavelength tuning of a whispering-gallery mode over 20 nm was confirmed. The present results imply that there is a great potential of CirD laser for larger scale WDM integrated devices.
Perceptually validated analytical BRDFs parameters remapping

The need to manually match the appearance of a material in two or more different rendering tools is common in digital 3D product design, due to the wide range of tools and material models commonly used, and a lack of standards to exchange materials data. Since the effect of BRDF parameters on rendered images is non-uniform, visually matching to a reference is time consuming and error-prone. We present an automatic BRDF remapping technique to match the appearance of a source material model to a target, providing a mapping between their parameter spaces. Our framework, based on Genetic Algorithm optimization and an image space similarity metric, provides a faithful mapping among analytical BRDFs, even when the BRDF models are deeply different. Objective and perceptual evaluations confirm the efficacy of the framework.
Tackling Androids Native Library Malware with Robust, Efficient and Accurate Similarity Measures

Code similarity measures create a comparison metric showing to what degree two code samples have the same functionality, e.g., to statically detect the use of known libraries in binary code. They are both an indispensable part of automated malware analysis, as well as a helper for the detection of plagiarism (IP protection) and the illegal use of open-source libraries in commercial apps. The centroid similarity metric extracts control-flow features from binary code and encodes them as geometric structures before comparing them. In our paper, we propose novel improvements to the centroid approach and apply it to the ARM architecture for the first time. We implement our approach as a plug-in for the IDA Pro disassembler and evaluate it regarding efficiency, accuracy and robustness on Android. Based on a dataset of 508,745 APKs, collected from 18 third-party app markets, we achieve a detection rate of 89% for the use of native code libraries, with an FPR of 10.8%. To test the robustness of our approach against the compiler version, optimization level, and other code transformations, we obfuscate and recompile known open-source libraries to evaluate which code transformations are resisted. Based on our results, we discuss how code re-use can be hidden by obfuscation and conclude with possible improvements.
PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid

For constrained end devices in Internet of Things, such as smart meters (SMs), data transmission is an energy-consuming operation. To address this problem, we propose an efficient and privacy-preserving aggregation system with the aid of Fog computing architecture, named PPFA, which enables the intermediate Fog nodes to periodically collect data from nearby SMs and accurately derive aggregate statistics as the fine-grained Fog level aggregation. The Cloud/utility supplier computes overall aggregate statistics by aggregating Fog level aggregation. To minimize the privacy leakage and mitigate the utility loss, we use more efficient and concentrated Gaussian mechanism to distribute noise generation among parties, thus offering provable differential privacy guarantees of the aggregate statistic on both Fog level and Cloud level. In addition, to ensure aggregator obliviousness and system robustness, we put forward a two-layer encryption scheme: the first layer applies OTP to encrypt individual noisy measurement to achieve aggregator obliviousness, while the second layer uses public-key cryptography for authentication purpose. Our scheme is simple, efficient, and practical, it requires only one round of data exchange among a SM, its connected Fog node and the Cloud if there are no node failures, otherwise, one extra round is needed between a meter, its connected Fog node, and the trusted third party.
Evaluating popularity data for relevance ranking in library information systems

In this poster, we present our work in progress to develop a relevance model for library information systems, which takes non‐textual factors into account. Here we focus on popularity data like citation or usage data. These data contain various biases that need to be corrected so as not to degrade the performance of the relevance model. Further, the different data might be to some extent incommensurable. We make use of the Characteristic Scores and Scales method to achieve two goals: first, remove biases from the raw data, and second, establish a common scale for the different data to support weighing the data against each other.
Nondeterministic Manifest Contracts

We study a manifest contract system---a typed calculus of higher-order contracts where contracts are tightly integrated into a refinement type system---for a functional language with nondeterministic choice. The extension is not trivial, especially in the presence of dependent function types, because a naive extension would lead to inconsistent type equivalence, which makes contract information in refinement types meaningless. To solve the problem, we propose a new kind of nondeterministic choice called coordinated choice, in which each occurrence of a choice operator is given a name and choices of the same name coordinately take the same branch. We introduce the notion of or-thant that helps both intuitive understanding and the development of formal semantics of the new choice. We formalize a manifest contract system λ H||Φ using the coordinated choice and show its basic properties of progress, type preservation, and contract satisfaction, the last of which states correctness of contracts in refinement types.
Non-Adversarial Unsupervised Word Translation

Unsupervised word translation from non-parallel inter-lingual corpora has attracted much research interest. Very recently, neural network methods trained with adversarial loss functions achieved high accuracy on this task. Despite the impressive success of the recent techniques, they suffer from the typical drawbacks of generative adversarial models: sensitivity to hyper-parameters, long training time and lack of interpretability. In this paper, we make the observation that two sufficiently similar distributions can be aligned correctly with iterative matching methods. We present a novel method that first aligns the second moment of the word distributions of the two languages and then iteratively refines the alignment. Extensive experiments on word translation of European and Non-European languages show that our method achieves better performance than recent state-of-the-art deep adversarial approaches and is competitive with the supervised baseline. It is also efficient, easy to parallelize on CPU and interpretable.
Deep thoughts on deep image compression

Deep image compositing has, in the last decade, become an industry standard approach to combining multiple computer-generated elements into a final frame. With rich support for multiple depth-specified samples per-pixel, deep images overcome many of the challenges previously faced when trying to combine multiple images using simple alpha channels and/or depth values. A practical challenge when using deep images, however, is managing the data footprint. The visual fidelity of the computer generated environments, characters and effects is continually growing, typically resulting in both a higher number of elements and greater complexity within each element. It is not uncommon to be using "gigabytes" to describe the size of deep image collections which, as more and more visual effects facilities establish a global presence, introduces a significant concern about timely overseas data transfer. Further, as deep images flow through compositing networks, the high sample count contributes to longer processing times. Our observation is that, with a richer contextual understanding of the target composite, systems - both automatic and artist-controlled - can be built to significantly compress deep images such that there is no perceptual difference in the final result.
Gesture recognition using leap motion: a comparison between machine learning algorithms

In this paper we compare the effectiveness of various methods of machine learning algorithms for real-time hand gesture recognition, in order to find the most optimal way to identify static hand gestures, as well as the most optimal sample size for use during the training step of the algorithms. In our framework, Leap Motion and Unity were used to extract the data. The data was then used to be trained using Python and scikit-learn. Utilizing normalized information regarding the hands and fingers, we managed to get a hit rate of 97% using the decision tree classifier.
The Motivation-Based Promotion of Proactive Control: The Role of Salience Network

It has been shown that reward motivation can facilitate proactive control, a cognitive control mode that is characterized of prior preparation and sustained holding of the goal-relevant information in working memory. However, it remains to be established the neural networks that may be involved in this promotion effect. In this study, participants underwent the AX-Continuous Performance Task (AX-CPT) that measures relative proactive control during functional magnetic resonance imaging (fMRI) scanning. We employed independent component analysis to decompose multiple brain networks and identified the task related network. Results showed that the salience network (SN) was engaged in the AX-CPT protocol. Importantly, our data demonstrated that reward modulated the association between task engagement of SN and proactive control, whereby the positive correlation was particularly observed in the reward condition. Moreover, reward modulated task engagement of the SN in a proactive manner, which may contribute to the behavioral proactive performance. Overall, our data suggest the involvement of SN in the reward facilitation effect of proactive control.
FaceME: Face-to-Machine Proximity Estimation Based on RSSI Difference for Mobile Industrial Human–Machine Interaction

In the mobile industrial human–machine interaction (HMI), to establish the data connection, the engineer has to manually select the target machine from a long list, which may lead to wrong connection and waste of time. We observe that the engineer should face to the machine during the interaction to ensure that the machine works accurately, and this characteristic makes the proximity estimation algorithm suitable to simplify the data connection. However, due to the densely deployed machines, the existing algorithms cannot provide sufficient accuracy with limited latency. In this paper, we implement a testbed to evaluate the performance in the mobile industrial HMI. Based on the experimental results, we propose the definition of received signal strength indicator (RSSI) difference and then use it to design the face-to-machine proximity estimation (FaceME) algorithm. The experimental results prove that FaceME can provide guaranteed estimation accuracy and low-time complexity.
Audio Transmission of Medical Reports for Visa Processing: A Solution for the Spread of Communicable Diseases by the Immigrant Population

The rapid growth of immigrants is a veritable menace for most state authorities. Aside from the hazards of population overcrowding, they create the risk of health hazards. According to recent medical statistics, international immigrants are the carriers of communicable diseases. In addition to tightened border controls, the strict and transparent visa approval process through proper medical diagnoses may play a vital role in addressing this problem. This requires the safe, secure, and prompt transmission of medical reports from recognized medical centers to embassies without violating the Health Insurance Portability and Accountability Act (HIPAA). This article introduces a novel transfer system of visa applicant medical reports for processing through multilayer security. Both cryptography and steganography are used here to ensure security. This nearly foolproof system helps to reduce the incorrect identification of visa applicants and quickens the visa-processing system. At the same time, it helps to control the spread of communicable diseases.
Pro-inflammatory effects of e-cigarette vapour condensate on human alveolar macrophages

Objective Vaping may increase the cytotoxic effects of e-cigarette liquid (ECL). We compared the effect of unvaped ECL to e-cigarette vapour condensate (ECVC) on alveolar macrophage (AM) function. Methods AMs were treated with ECVC and nicotine-free ECVC (nfECVC). AM viability, apoptosis, necrosis, cytokine, chemokine and protease release, reactive oxygen species (ROS) release and bacterial phagocytosis were assessed. Results Macrophage culture with ECL or ECVC resulted in a dose-dependent reduction in cell viability. ECVC was cytotoxic at lower concentrations than ECL and resulted in increased apoptosis and necrosis. nfECVC resulted in less cytotoxicity and apoptosis. Exposure of AMs to a sub-lethal 0.5% ECVC/nfECVC increased ROS production approximately 50-fold and significantly inhibited phagocytosis. Pan and class one isoform phosphoinositide 3 kinase inhibitors partially inhibited the effects of ECVC/nfECVC on macrophage viability and apoptosis. Secretion of interleukin 6, tumour necrosis factor α, CXCL-8, monocyte chemoattractant protein 1 and matrix metalloproteinase 9 was significantly increased following ECVC challenge. Treatment with the anti-oxidant N-acetyl-cysteine (NAC) ameliorated the cytotoxic effects of ECVC/nfECVC to levels not significantly different from baseline and restored phagocytic function. Conclusions ECVC is significantly more toxic to AMs than non-vaped ECL. Excessive production of ROS, inflammatory cytokines and chemokines induced by e-cigarette vapour may induce an inflammatory state in AMs within the lung that is partly dependent on nicotine. Inhibition of phagocytosis also suggests users may suffer from impaired bacterial clearance. While further research is needed to fully understand the effects of e-cigarette exposure in humans in vivo, we caution against the widely held opinion that e-cigarettes are safe.
Reviewing guppy color vision: integrating the molecular and physiological variation in visual tuning of a classic system for sensory drive

Abstract Sensory drive predicts coevolution of mate choice signals with the sensory systems detecting those signals. Guppies are a classic model for sensory drive as mate preferences based on coloration differ across individuals and populations. A large body of work has identified variation in color vision, yet we lack a direct tie between how such variation in color vision influences variation in color preference. Here we bring together studies that have investigated guppy vision over the past 40 years to: (1) highlight our current understanding of where variation occurs in the guppy color vision pathway and (2) suggest future avenues of research into sources of visual system variation that could influence guppy color preference. This will allow researchers to design careful studies that couple measures of color preference with measures of visual system variation from the same individual or population. Such studies will finally provide important answers as to what sets the direction and speed of mate preference evolution via sensory drive.