Miracle-dz/UniFAR-FTUs huggingface dataset:
HXD: Hybrid XSS detection by using a headless browser

Cross-Site Scripting (XSS) is the most prevalent web application vulnerability that occurs when a web application implements insufficient input validation or output sanitation. Adversaries can use XSS to deliver a malicious script which leads to session hijacking, credential theft, privilege escalation, etc. In order to detect XSS attacks, several works have been proposed and implemented. Although the detection of XSS vulnerability is fairly easy via static or dynamic analysis, it still remains nontrivial because most approaches fall into three problems: (1) too slow to analyze tons of URLs, (2) have some missing cases (i.e., false negatives), (3) produce unignorable number of false positives. In this paper, we propose a hybrid XSS detection (HXD) system, a black-box based XSS detection approach using both static string analysis and dynamic browser rendering. We extract URLs from web logs and refine them as proper input URLs. Therefore, HXD does not need to crawl or fuzz URL inputs. HXD uses PhantomJS, a headless browser to execute a javascript and detect XSS flaws so it can detect XSS vulnerabilities in javascript frameworks. The static analyzer of HXD utilizes string analysis based approach to accelerate the detection speed. We evaluate HXD by using web logs of Korean major internet portal (i.e., Naver). Our evaluation result demonstrates that HXD has low false positives and detects XSS flaws missed by other black-box based detectors.
Industrial sludge based adsorbents/ industrial by- products in the removal of reactive dyes - A review

Adsorption has been an effective separation process for non-biodegradable pollutants. Study of recovery of dyes reveals adsorption as an efficacious process. Many textile industries use commercial activated carbon for the treatment of dye waste. The current research is focused on the need to alternate commercial activated carbon with a cost effective, potential adsorbent. The major limitations in using commercial activated carbon in large scale are its regeneration and high cost of operation. Many researchers have studied the feasibility of using low cost adsorbents derived from natural materials, industrial waste materials, agricultural products and biosorbents as precursors. Numerous works have been reported on these adsorbents being used in the removal of heavy metals and dyes. This paper reviews the development of different industrial sludge/by products as adsorbents under various activation methods. The decolourization of reactive dye solutions by the developed adsorbents under batch mode is also discussed. Based on the reviews, development of activated carbon from preliminary tannery sludge is suggested by various activation methods. Key words: Adsorption, reactive dye, activated carbon, tannery sludge.
Style Aggregated Network for Facial Landmark Detection

Recent advances in facial landmark detection achieve success by learning discriminative features from rich deformation of face shapes and poses. Besides the variance of faces themselves, the intrinsic variance of image styles, e.g., grayscale vs. color images, light vs. dark, intense vs. dull, and so on, has constantly been overlooked. This issue becomes inevitable as increasing web images are collected from various sources for training neural networks. In this work, we propose a style-aggregated approach to deal with the large intrinsic variance of image styles for facial landmark detection. Our method transforms original face images to style-aggregated images by a generative adversarial module. The proposed scheme uses the style-aggregated image to maintain face images that are more robust to environmental changes. Then the original face images accompanying with style-aggregated ones play a duet to train a landmark detector which is complementary to each other. In this way, for each face, our method takes two images as input, i.e., one in its original style and the other in the aggregated style. In experiments, we observe that the large variance of image styles would degenerate the performance of facial landmark detectors. Moreover, we show the robustness of our method to the large variance of image styles by comparing to a variant of our approach, in which the generative adversarial module is removed, and no style-aggregated images are used. Our approach is demonstrated to perform well when compared with state-of-the-art algorithms on benchmark datasets AFLW and 300-W. Code is publicly available on GitHub: https://github.com/D-X-Y/SAN
Signaling Game-based Misbehavior Inspection in V2I-enabled Highway Operations

Vehicle-to-Infrastructure (V2I) communications are increasingly supporting highway operations such as electronic toll collection, carpooling, and vehicle platooning. In this paper we study the incentives of strategic misbehavior by individual vehicles who can exploit the security vulnerabilities in V2I communications and negatively impact the highway operations. We consider a V2I-enabled highway segment facing two classes of vehicles (agent populations), each with an authorized access to one server (subset of lanes). Vehicles are strategic in that they can misreport their class (type) to the system operator and get an unauthorized access to the server dedicated to the other class. This misbehavior causes additional congestion externality on the compliant vehicles, and thus, needs to be deterred. We focus on an environment where the operator is able to inspect the vehicles for misbehavior. The inspection is costly and successful detection incurs a fine on the misbehaving vehicle. We formulate a signaling game to study the strategic interaction between the vehicle classes and the operator. Our equilibrium analysis provides conditions on the cost parameters that govern the vehicles' incentive to misbehave or not. We also determine the operator's equilibrium inspection strategy.
A neural network approach for prediction of bearing performance degradation tendency

Accurate bearing performance degradation indicator and prediction of bearing performance degradation tendency is the foundation of bearing remaining useful life prediction. Artificial neural network (ANN) methods have been widely used in prediction. However, the input of most ANN methods only utilize one condition monitoring data. Since the complexity of the bearing failure situation, we cannot measure the bearing performance degradation only by one indicator. In this paper, 35 performance degradation indicators are established in time domain, frequency domain and time — frequency domain, respectively. And a comprehensive characterization indicator is obtained by PCA method. ANN methods are used to predict the comprehensive characterization indicator which makes a good foundation for bearing remaining useful life prediction.
Occlusion detection and recognizing human face using neural network

Face recognition is one of the most important problems of verifying or identifying a face from query image or input image. This system has emerged as an important field in case of surveillance systems. Face detection is a very powerful tool for video surveillance, human computer interface, face recognition, and image database management. Occlusion means extraneous objects that hinder face recognition, e.g., face covered with scarf, wearing glasses, beard, cap etc., is one of the greatest challenges in face recognition systems. Other issues are illumination, pose, expressions etc. An efficient method is used for detection of occlusions, which specifies the missing information in the occluded face. Method used for face detection is Viola-Jones algorithm, for occlusion detection and reconstruction of face fast weighted PCA is used are Neural Network (NN) is used for face recognition. Other appropriate methods are Principal Component Analysis (PCA), Local Binary Pattern (LBP), Eigenfaces. Propose method which is used will detect occluded face and recognize the face with the help of given same faces from the database.
Mechanisms of HIV Entry into the CNS: Increased Sensitivity of HIV Infected CD14+CD16+ Monocytes to CCL2 and Key Roles of CCR2, JAM-A, and ALCAM in Diapedesis

As HIV infected individuals live longer, the prevalence of HIV associated neurocognitive disorders is increasing, despite successful antiretroviral therapy. CD14+CD16+ monocytes are critical to the neuropathogenesis of HIV as they promote viral seeding of the brain and establish neuroinflammation. The mechanisms by which HIV infected and uninfected monocytes cross the blood brain barrier and enter the central nervous system are not fully understood. We determined that HIV infection of CD14+CD16+ monocytes resulted in their highly increased transmigration across the blood brain barrier in response to CCL2 as compared to uninfected cells, which did not occur in the absence of the chemokine. This exuberant transmigration of HIV infected monocytes was due, at least in part, to increased CCR2 and significantly heightened sensitivity to CCL2. The entry of HIV infected and uninfected CD14+CD16+ monocytes into the brain was facilitated by significantly increased surface JAM-A, ALCAM, CD99, and PECAM-1, as compared to CD14+ cells that are CD16 negative. Upon HIV infection, there was an additional increase in surface JAM-A and ALCAM on CD14+CD16+ monocytes isolated from some individuals. Antibodies to ALCAM and JAM-A inhibited the transmigration of both HIV infected and uninfected CD14+CD16+ monocytes across the BBB, demonstrating their importance in facilitating monocyte transmigration and entry into the brain parenchyma. Targeting CCR2, JAM-A, and ALCAM present on CD14+CD16+ monocytes that preferentially infiltrate the CNS represents a therapeutic strategy to reduce viral seeding of the brain as well as the ongoing neuroinflammation that occurs during HIV pathogenesis.
Radiation damage and repair in breast tissue - an in vivo assessment of a radiobiological model

Poster: "2014 CSM / R-0284 / Radiation damage and repair in breast tissue - an in vivo assessment of a radiobiological model" by: "M. Ebert1, B. Dahl2, J. Prunster2, S. McLaren3, N. Zeps2, M. House2, B. Reniers4, F. Verhaegen4, C. Saunders2, D. Joseph1; 1NEDLANDS/AU, 2Crawley/AU, 3Subiaco/AU, 4Maastricht/NL"
Algorithms analysis of mobile robot SLAM based on Kalman and particle filter

Many algorithms of mobile robot SLAM (Simultaneous Localization and Mapping) have been researched at present, however, the SLAM algorithm of mobile robot based on probability is often used in the unknown environment. In this paper, two kinds of SLAM algorithms based on probability are analyzed and compared. One kind is the SLAM algorithm based on Kalman filter: extended Kalman filter SLAM (EKF-SLAM) and unscented Kalman filter SLAM algorithm (UKF-SLAM). Another kind is the SLAM algorithm based on Particle filter: FastSLAM and unscented FastSLAM (UFastSLAM) algorithm. The difference from the four algorithms of SLAM is illustrated in terms of principle and calculation accuracy. Finally, the simulation results show that the UFastSLAM algorithm is superior to other algorithms in robot path and landmark estimation.
Measurement and Analysis of the Reviews in Airbnb

Airbnb, a recently emerged online lodging service that allows house and apartment dwellers to lease out their premises to short-term renters like tourists, is reconstructing the value chain of the traditional hotel industry. It works as a platform that connects hosts and travelers and facilities their interaction and exchange. Studying this service could shed light on understanding the emerging sharing economy from a user-centric perspective. In this work, we collect the profiles of 43.8 million Airbnb users, and analyze the reviews they published online. We model the interactions between Airbnb users using a review graph, and study their mobility patterns by investigating their reviews. To the best of our knowledge, our work is the first measurement study of massive Airbnb users on a global scale, and it provides insights of their activities in both cyberspace and the physical world.
Collagen 1 fibers and hypoxic tumor microenvironments in breast cancer and their effect on transport of molecules within the tumor matrix

Although the mechanisms through which hypoxia influences several phenotypic characteristics such as angiogenesis, selection for resistance to apoptosis, resistance to radiation and chemotherapy, and increased invasion and metastasis are well characterized, the relationship between tumor hypoxia and components of the extracellular matrix (ECM) is relatively unexplored. The collagen I (Col1) fiber matrix of solid tumors is the major structural part of the ECM. Col1 fiber density can increase tumor initiation, progression, and metastasis, with cancer cell invasion occurring along radially aligned Col1 fibers. Here we have investigated the influence of hypoxia on Col1 fiber density in solid breast and prostate tumor models. Second harmonic generation (SHG) microscopy was used to detect differences in Col1 fiber density and volume between hypoxic and normoxic tumor regions. Hypoxic regions were detected by fluorescence microscopy, using tumors derived from human breast and prostate cancer cell lines stably expressing enhanced green fluorescent protein (EGFP) under transcriptional control of the hypoxia response element. In-house fiber analysis software was used to quantitatively analyze Col1 fiber density and volume from the SHG microscopy images. Normoxic tumor regions exhibited a dense mesh of Col1 fibers. In contrast, fewer and structurally altered Col1 fibers were detected in hypoxic EGFP-expressing tumor regions. Microarray gene expression analyses identified increased expression of lysyl oxidase and reduced expression of some matrix metalloproteases in hypoxic compared with normoxic cancer cells. These results suggest that hypoxia mediates Col1 fiber restructuring in tumors, which may impact delivery of macromolecular agents as well as dissemination of cells.
Direct-Chill Casting of AA7449 Aerospace Alloy under Electromagnetic and Ultrasonic Combined Fields

This work is based on investigation of the influence of electromagnetic fields and ultrasonic vibrations and their combination on the resulting microstructure of an AA7449 aerospace aluminium alloy. The results demonstrate the application of the compound electro-magnetic and ultrasonic fields under optimum conditions delivers not only a refined microstructure but also consistent distribution of chemical composition. It suggests an alternative method for producing high strength aerospace alloys which could not be refined through conventional addition of chemical grain refiners.
Proboscidean Mitogenomics: Chronology and Mode of Elephant Evolution Using Mastodon as Outgroup

We have sequenced the complete mitochondrial genome of the extinct American mastodon (Mammut americanum) from an Alaskan fossil that is between 50,000 and 130,000 y old, extending the age range of genomic analyses by almost a complete glacial cycle. The sequence we obtained is substantially different from previously reported partial mastodon mitochondrial DNA sequences. By comparing those partial sequences to other proboscidean sequences, we conclude that we have obtained the first sequence of mastodon DNA ever reported. Using the sequence of the mastodon, which diverged 24–28 million years ago (mya) from the Elephantidae lineage, as an outgroup, we infer that the ancestors of African elephants diverged from the lineage leading to mammoths and Asian elephants approximately 7.6 mya and that mammoths and Asian elephants diverged approximately 6.7 mya. We also conclude that the nuclear genomes of the African savannah and forest elephants diverged approximately 4.0 mya, supporting the view that these two groups represent different species. Finally, we found the mitochondrial mutation rate of proboscideans to be roughly half of the rate in primates during at least the last 24 million years.
Evaluation of Antigen-Conjugated Fluorescent Beads to Identify Antigen-Specific B Cells

Selection of single antigen-specific B cells to identify their expressed antibodies is of considerable interest for evaluating human immune responses. Here, we present a method to identify single antibody-expressing cells using antigen-conjugated fluorescent beads. To establish this, we selected Folate Receptor alpha (FRα) as a model antigen and a mouse B cell line, expressing both the soluble and the membrane-bound forms of a human/mouse chimeric antibody (MOv18 IgG1) specific for FRα, as test antibody-expressing cells. Beads were conjugated to FRα using streptavidin/avidin-biotin bridges and used to select single cells expressing the membrane-bound form of anti-FRα. Bead-bound cells were single cell-sorted and processed for single cell RNA retrotranscription and PCR to isolate antibody heavy and light chain variable regions. Variable regions were then cloned and expressed as human IgG1/k antibodies. Like the original clone, engineered antibodies from single cells recognized native FRα. To evaluate whether antigen-coated beads could identify specific antibody-expressing cells in mixed immune cell populations, human peripheral blood mononuclear cells (PBMCs) were spiked with test antibody-expressing cells. Antigen-specific cells could comprise up to 75% of cells selected with antigen-conjugated beads when the frequency of the antigen-positive cells was 1:100 or higher. In PBMC pools, beads conjugated to recombinant antigens FRα and HER2 bound antigen-specific anti-FRα MOv18 and anti-HER2 Trastuzumab antibody-expressing cells, respectively. From melanoma patient-derived B cells selected with melanoma cell line-derived protein-coated fluorescent beads, we generated a monoclonal antibody that recognized melanoma antigen-coated beads. This approach may be further developed to facilitate analysis of B cells and their antibody profiles at the single cell level and to help unravel humoral immune repertoires.
Functional MRI of calcium‐dependent synaptic activity: Cross correlation with CBF and BOLD measurements

Spatial specificities of the calcium‐dependent synaptic activity, hemodynamic‐based blood oxygenation level‐dependent (BOLD) and cerebral blood flow (CBF) fMRI were quantitatively compared in the same animals. Calcium‐dependent synaptic activity was imaged by exploiting the manganese ion (Mn++) as a calcium analog and an MRI contrast agent at 9.4 T. Following forepaw stimulation in α‐chloralose anesthetized rat, water T1 of the contralateral forepaw somatosensory cortex (SI) was focally and markedly reduced from 1.99 ± 0.03 sec to 1.30 ± 0.18 sec (mean ± SD, N = 7), resulting from the preferential intracellular Mn++ accumulation. Based on an in vitro calibration, the estimated contralateral somatosensory cortex [Mn++] was ∼100μM, which was 2–5‐fold higher than the neighboring tissue and the ipsilateral SI. Regions with the highest calcium activities were localized around cortical layer IV. Stimulus‐induced BOLD and CBF changes were 3.4 ± 1.6% and 98 ± 33%, respectively. The T1 synaptic activity maps extended along the cortex, whereas the hemodynamic‐based activation maps extended radially along the vessels. Spatial overlaps among the synaptic activity, BOLD, and CBF activation maps showed excellent co‐registrations. The center‐of‐mass offsets between any two activation maps were less than 200 μm, suggesting that hemodynamic‐based fMRI techniques (at least at high field) can be used to accurately map the spatial loci of synaptic activity. Magn Reson Med 43:383–392, 2000. © 2000 Wiley‐Liss, Inc.
CRISPR system for genome engineering: the application for autophagy study

CRISPR/Cas9 is the latest tool introduced in the field of genome engineering and is so far the best genome-editing tool as compared to its precedents such as, meganucleases, zinc finger nucleases (ZFNs) and transcription activator-like effectors (TALENs). The simple design and assembly of the CRISPR/Cas9 system makes genome editing easy to perform as it uses small guide RNAs that correspond to their DNA targets for high efficiency editing. This has helped open the doors for multiplexible genome targeting in many species that were intractable using old genetic perturbation techniques. Currently, The CRISPR system is revolutionizing the way biological researches are conducted and paves a bright future not only in research but also in medicine and biotechnology. In this review, we evaluated the history, types and structure, the mechanism of action of CRISPR/Cas System. In particular, we focused on the application of this powerful tool in autophagy research.
Model predictive control of nonlinear singularly perturbed systems: Application to a reactor-separator process network

This work focuses on model predictive control of nonlinear singularly perturbed systems. A composite control system using multirate sampling (i.e., fast sampling of the fast state variables and slow sampling of the slow state variables) and consisting of a “fast” feedback controller that stabilizes the fast dynamics and a model predictive controller that stabilizes the slow dynamics and enforces desired performance objectives in the slow subsystem is designed. Using stability results for nonlinear singularly perturbed systems, sufficient conditions for closed-loop system stability are derived. A nonlinear reactor-separator process network which exhibits two-time-scale behavior is used to demonstrate the controller design.
Climate‐driven change in plant–insect interactions along elevation gradients

Summary Global warming is predicted to dramatically alter communities' composition through differential colonization abilities, such as between sessile plants and their mobile herbivores. Novel interactions between previously non-overlapping species may, however, also be mediated by altered plants' responses to herbivore attack. Syndromes of plant defences and tolerance are driven by inherited functional traits, biotic and abiotic conditions, and the geographical and historical contingencies affecting the community. Therefore, understanding climate change-driven herbivore responses and evolution towards a particular plant defence syndrome is key to forecasting species interactions in the near future. In this paper, we first document variations in herbivory, and plant defences along altitudinal gradients that act as ‘natural experiments’. We then use an empirical model to predict how specialist herbivore abundance may shift with respect to elevation in the near future. Our field surveys and field experiment showed a decrease in herbivory with elevation. However, contrary to expectations, our meta-regression analyses showed that plant defences, particularly leaf toughness and flavonoid compounds, tend to be higher at high elevations, while secondary metabolites showed no clear trend with elevation. Based on those results, we discuss how plant communities and species-specific plant defence syndromes will change in response to the climate-driven herbivore colonization of higher altitudes. Particularly, plant from high elevation, due to high protection against abiotic stress may be already ecologically fitted to resist the sudden increase in herbivory pressure that they will likely experience during global change.