Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages

Extracting geographical tags from webpages is a well-motivated application in many domains. In illicit domains with unusual language models, like human trafficking, extracting geotags with both high precision and recall is a challenging problem. In this paper, we describe a geotag extraction framework in which context, constraints and the openly available Geonames knowledge base work in tandem in an Integer Linear Programming (ILP) model to achieve good performance. In preliminary empirical investigations, the framework improves precision by 28.57% and F-measure by 36.9% on a difficult human trafficking geotagging task compared to a machine learning-based baseline. The method is already being integrated into an existing knowledge base construction system widely used by US law enforcement agencies to combat human trafficking.Comment: 6 pages, GeoRich 2017 workshop at ACM SIGMOD conferenc

Comparison of efficacy and safety of oral azithromycin and oral doxycycline in acne vulgaris

Background: Acne vulgaris is a chronic inflammatory disease of the pilosebaceous unit with considerable psychosocial impact. Oral azithromycin or oral doxycycline can be used for the management of moderate and severe acne vulgaris. However, there is no consensus on which antibiotic is superior and the optimal dose for management.Methods: A prospective randomized interventional study was carried out among 120 patients of moderate to severe acne vulgaris. The patients were randomized into group A and B. While group A was prescribed oral azithromycin 500 mg three times a week, group B was given oral doxycycline 100 mg daily for 12 weeks. Topical clindamycin twice daily application was also given. Global Acne Grading Scale (GAGS) score was recorded at baseline and at 2nd, 4th, 8th and 12th weeks.Results: GAGS score at baseline in azithromycin (n = 53) and doxycycline (n = 55) group was 31.98±4.49 and 30.63±3.78 respectively (p value >0.05). 83.91±6.83% (p 0.05). 15.09% patients in azithromycin group and 20% patients in doxycycline group reported adverse effects. The most commonly reported adverse effect was diarrhoea. All adverse effects were of ‘mild’ category and causality assessment was ‘possible’.Conclusions: Oral azithromycin is equally efficacious but safer alternative to oral doxycycline for the management of acne vulgaris

Node Injection for Class-specific Network Poisoning

Graph Neural Networks (GNNs) are powerful in learning rich network representations that aid the performance of downstream tasks. However, recent studies showed that GNNs are vulnerable to adversarial attacks involving node injection and network perturbation. Among these, node injection attacks are more practical as they don't require manipulation in the existing network and can be performed more realistically. In this paper, we propose a novel problem statement - a class-specific poison attack on graphs in which the attacker aims to misclassify specific nodes in the target class into a different class using node injection. Additionally, nodes are injected in such a way that they camouflage as benign nodes. We propose NICKI, a novel attacking strategy that utilizes an optimization-based approach to sabotage the performance of GNN-based node classifiers. NICKI works in two phases - it first learns the node representation and then generates the features and edges of the injected nodes. Extensive experiments and ablation studies on four benchmark networks show that NICKI is consistently better than four baseline attacking strategies for misclassifying nodes in the target class. We also show that the injected nodes are properly camouflaged as benign, thus making the poisoned graph indistinguishable from its clean version w.r.t various topological properties.Comment: 28 pages, 5 figure

Analysis of a Compact Squeeze Film Damper with Magneto Rheological Fluid

Rotor systems play vital role in many modern day machinery such as turbines, pumps, aeroengines, gyroscopes, to name a few. Due to unavoidable unbalance in the rotor systems, there are lateral and torsional vibrations. Ignoring these effects may cause the system serious damages, which sometimes lead to catastrophic failures. Vibration level in rotor systems is acceptable within a range. Focus in this work is to minimize the vibration level to the acceptable range. One of the ways vibration level can be minimised is by means of providing damping. To accomplish this task in this work a new concept squeeze film damper is made by electro discharge machining which is compact in configuration, is filled with magneto-rheological (MR) fluid and tested out on one support of a Jeffcott rotor. This compact squeeze film damper (SFD) produces damping in a compact volume of the device compared to a conventional SFD. MR fluid is a smart fluid, for which apparent viscosity changes with the application of external magnetic field. This compact damper with MR fluid provides the variable damping force, controlled by an external magnetic field. In this work, proportional controller has been used for providing the control feedback. This MR damper is seen to reduce vibrations in steady state and transient input to the Jeffcott rotor. Parametric study for important design parameters has been done with the help of the simulation model. These controlled dampers can be used for reducing vibrations under different operating conditions and also crossing critical speed

Economics of Biobutanol: A Review

ABSTRACT Due to rapid depletion of fossil fuels and fluctuating market prices of crude oil, extensive research is going on worldwide to find out alternative renewable fuels that can either completely replace the fossil fuels or that can be blended in certain proportions with the fossil fuels without having major modifications in the engines. The most popular alternative liquid fuels are biodiesel and ethanol. However, both of these have limitations that they can be blended with petro-diesel and gasoline only up to 20%. They also suffer from other limitations such as separation from petrol at low temperature and low heat content that reduces economy of blended fuel. A new alternative fuel that has emerged in recent past is biobutanol, which overcomes the problems faced with biodiesel and bioethanol. Biobutanol is manufactured through the process of ABE (acetone-butanol-ethanol) fermentation using various substrates. In this review, we have compared various processes and the substrates used by them from viewpoint of unit price of the butanol. This analysis is based on published literature, but still gives a view into the niche areas for improving economy of the ABE fermentation process and the biobutanol fuel

Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients

Bloodstream infections are associated with high morbidity and mortality with rates varying from 10–25% and higher. Appropriate and timely onset of antibiotic therapy influences the prognosis of these patients. It requires the diagnostic accuracy which is not afforded by current gold standards such as blood culture. Moreover, the time from blood sampling to blood culture results is a key determinant of reducing mortality. No established biomarkers exist which can differentiate bloodstream infections from other systemic inflammatory conditions. This calls for studies on biomarkers potential of molecular profiling of plasma as it is affected most by the molecular changes accompanying bloodstream infections. N-glycosylation is a post-translational modification which is very sensitive to changes in physiology. Here we have performed targeted quantitative N-glycoproteomics from plasma samples of patients with confirmed positive blood culture together with age and sex matched febrile controls with negative blood culture reports. Three hundred and sixty eight potential N-glycopeptides were quantified by mass spectrometry and 149 were further selected for identification. Twenty four N-glycopeptides were identified with high confidence together with elucidation of the peptide sequence, N-glycosylation site, glycan composition and proposed glycan structures. Principal component analysis, orthogonal projections to latent structures-discriminant analysis (S-Plot) and self-organizing maps clustering among other statistical methods were employed to analyze the data. These methods gave us clear separation of the two patient classes. We propose high-confidence N-glycopeptides which have the power to separate the bloodstream infections from blood culture negative febrile patients and shed light on host response during bacteremia. Data are available via ProteomeXchange with identifier PXD009048.Peer reviewe

Mass spectrometry-based lipidomics of oral squamous cell carcinoma tissue reveals aberrant cholesterol and glycerophospholipid metabolism - A Pilot study

Lipid metabolic reprogramming is one hallmark of cancer. Lipid metabolism is regulated by numerous enzymes, many of which are targeted by several drugs on the market. We aimed to characterize the lipid alterations in oral squamous cell carcinoma (OSCC) as a basis for understanding its lipid metabolism, thus identifying potential therapeutic targets. We compared lipid species, classes, and glycerophospholipid (GPL) fatty acid species between paired tumor tissue and healthy oral tongue mucosa samples from 10 OSCC patients using a QExactive mass spectrometer. After filtering the 1370 lipid species identified, we analyzed 349 species: 71 were significantly increased in OSCC. The GPL metabolism pathway was most represented by the lipids differing in OSCC (P = .005). Cholesterol and the GPLs phosphatidylcholines, phosphatidylethanolamines, and phosphatidylinositols were most significantly increased in OSCC tissue (FC 1.8, 2.0, 2.1, and 2.3 and, P = .003, P = .005, P = .002, P = .007). In conclusion, we have demonstrated a shift in the lipid metabolism in these OSCC samples by characterizing the detailed landscape. Predominantly, cholesterol and GPL metabolism were altered, suggesting that interactions with sterol regulatory binding proteins may be involved. The FA composition changes of the GPLs suggest increased de novo lipogenesis.Peer reviewe

SIRNN: A Math Library for Secure RNN Inference

Complex machine learning (ML) inference algorithms like recurrent neural networks (RNNs) use standard functions from math libraries like exponentiation, sigmoid, tanh, and reciprocal of square root. Although prior work on secure 2-party inference provides specialized protocols for convolutional neural networks (CNNs), existing secure implementations of these math operators rely on generic 2-party computation (2PC) protocols that suffer from high communication. We provide new specialized 2PC protocols for math functions that crucially rely on lookup-tables and mixed-bitwidths to address this performance overhead; our protocols for math functions communicate up to 423x less data than prior work. Some of the mixed bitwidth operations used by our math implementations are (zero and signed) extensions, different forms of truncations, multiplication of operands of mixed-bitwidths, and digit decomposition (a generalization of bit decomposition to larger digits). For each of these primitive operations, we construct specialized 2PC protocols that are more communication efficient than generic 2PC, and can be of independent interest. Furthermore, our math implementations are numerically precise, which ensures that the secure implementations preserve model accuracy of cleartext. We build on top of our novel protocols to build SIRNN, a library for end-to-end secure 2-party DNN inference, that provides the first secure implementations of an RNN operating on time series sensor data, an RNN operating on speech data, and a state-of-the-art ML architecture that combines CNNs and RNNs for identifying all heads present in images. Our evaluation shows that SIRNN achieves up to three orders of magnitude of performance improvement when compared to inference of these models using an existing state-of-the-art 2PC framework