StyleCounsel: Seeing the (Random) Forest for the Trees in Adversarial Code Stylometry

Authorship attribution has piqued the interest of scholars for centuries, but had historically remained a matter of subjective opinion, based upon examination of handwriting and the physical document. Midway through the 20th Century, a technique known as stylometry was developed, in which the content of a document is analyzed to extract the author's grammar use, preferred vocabulary, and other elements of compositional style. In parallel to this, programmers, and particularly those involved in education, were writing and testing systems designed to automate the analysis of good coding style and best practice, in order to assist with grading assignments. In the aftermath of the Morris Worm incident in 1988, researchers began to consider whether this automated analysis of program style could be combined with stylometry techniques and applied to source code, to identify the author of a program. The results of recent experiments have suggested this code stylometry can successfully identify the author of short programs from among hundreds of candidates with up to 98\% precision. This potential ability to discern the programmer of a sample of code from a large group of possible authors could have concerning consequences for the open-source community at large, particularly those contributors that may wish to remain anonymous. Recent international events have suggested the developers of certain anti-censorship and anti-surveillance tools are being targeted by their governments and forced to delete their repositories or face prosecution. In light of this threat to the freedom and privacy of individual programmers around the world, and due to a dearth of published research into practical code stylometry at scale and its feasibility, we carried out a number of investigations looking into the difficulties of applying this technique in the real world, and how one might effect a robust defence against it. To this end, we devised a system to aid programmers in obfuscating their inherent style and imitating another, overt, author's style in order to protect their anonymity from this forensic technique. Our system utilizes the implicit rules encoded in the decision points of a random forest ensemble in order to derive a set of recommendations to present to the user detailing how to achieve this obfuscation and mimicry attack. In order to best test this system, and simultaneously assess the difficulties of performing practical stylometry at scale, we also gathered a large corpus of real open-source software and devised our own feature set including both novel attributes and those inspired or borrowed from other sources. Our results indicate that attempting a mass analysis of publicly available source code is fraught with difficulties in ensuring the integrity of the data. Furthermore, we found ours and most other published feature sets do not sufficiently capture an author's style independently of the content to be very effective at scale, although its accuracy is significantly greater than a random guess. Evaluations of our tool indicate it can successfully extract a set of changes that would result in a misclassification as another user if implemented. More importantly, this extraction was independent of the specifics of the feature set, and therefore would still work even with a more accurate model of style. We ran a limited user study to assess the usability of the tool, and found overall it was beneficial to our participants, and could be even more beneficial if the valuable feedback we received were implemented in future work

Design and safety analysis of an in-flight, test airfoil

The evaluation of an in-flight airfoil model requires extensive analysis of a variety of structural systems. Determining the safety of the design is a unique task dependant on the aircraft, flight environment, and physical requirements of the airfoil. With some areas of aerodynamic research choosing to utilize flight testing over wind tunnels the need to design and certify safe and reliable designs is a necessity. Commercially available codes have routinely demonstrated an ability to simulate complex systems. The union of three-dimensional design software with finite element programs, such as SolidWorks and COSMOSWorks, allows for a streamlined approach to the iterative task of design and simulation. The iterative process is essential to the safety analysis of the system. Results from finite-element analysis are used to determine material selection and component dimensions. These changes, in turn, produce different stress profiles, which will affect other components. The unique case presented in this study outlines the process required to certify a large swept-wing model mounted to a Cessna O-2 aircraft. The process studies the affect of aerodynamic loading on the hard-point structure inside the wing, as well as the model mounting structure, and support strut. The process does not end when numerical simulations indicate that each system is safe. Following numerical work, a series of static tests are used to verify that no unforeseen failures will occur. Although the process is tailored to one specific example, it outlines an approach that could be applied to any test platform. A different model may create a physically different system, but the safety analysis would remain the same

A Life Skills Toolkit: Curriculum Development for Sustainable Public Health Community Engagement

Introduction: Committee On Temporary Shelter (COTS) is a community organization that provides gateway housing opportunities to fourteen previously homeless veterans through its Canal Street program in Winooski, VT. Many of the residents struggle with physical fitness, poor nutrition, and mental illness, including PTSD. Research has shown that there is an increasing prevalence of overweight or obese veterans returning from service, and these individuals present a particular challenge to primary care physicians as their mental health issues are closely related to their level of fitness. It has been demonstrated that veterans often suffer from ingrained food insecurity, which negatively influences post-service eating behavior, and readjustment solutions are needed to ease reentry into civilian life. While literature recommendations exist outlining the important role of initiating easy-to-use exercise programs and the beneficial impact of exercise in a natural environment on veterans, there has been little research into more holistic approaches to improve the diminished quality of life impacting many individuals with PTSD. Recent literature shows decreased PTSD symptoms after a life skills intervention and that short-term nutritional education interventions have the capacity to favorably change eating behaviors in a low income population. Therefore, we decided that a comprehensive, yet personalized intervention was needed.https://scholarworks.uvm.edu/comphp_gallery/1211/thumbnail.jp

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing

This work provides a solution to the challenge of small amounts of training data in Non-Destructive Ultrasonic Testing for composite components. It was demonstrated that direct simulation alone is ineffective at producing training data that was representative of the experimental domain due to poor noise reconstruction. Therefore, four unique synthetic data generation methods were proposed which use semi-analytical simulated data as a foundation. Each method was evaluated on its classification performance of real experimental images when trained on a Convolutional Neural Network which underwent hyperparameter optimization using a genetic algorithm. The first method introduced task specific modifications to CycleGAN, to learn the mapping from physics-based simulations of defect indications to experimental indications in resulting ultrasound images. The second method was based on combining real experimental defect free images with simulated defect responses. The final two methods fully simulated the noise responses at an image and signal level respectively. The purely simulated data produced a mean classification F1 score of 0.394. However, when trained on the new synthetic datasets, a significant improvement in classification performance on experimental data was realized, with mean classification F1 scores of 0.843, 0.688, 0.629, and 0.738 for the respective approaches.Comment: 16 Page

The HB22.7 Anti-CD22 monoclonal antibody enhances bortezomib-mediated lymphomacidal activity in a sequence dependent manner

Most non-Hodgkin's lymphomas (NHL) initially respond to chemotherapy, but relapse is common and treatment is often limited by chemotherapy-related toxicity. Bortezomib, is a highly selective proteasome inhibitor with anti-NHL activity; it is currently FDA approved for second-line treatment of mantle cell lymphoma (MCL). Bortezomib exerts its activity in part through the generation of reactive oxygen species (ROS) and also by the induction of apoptosis

Studies related to the chloro titanium and zirconium complexes with [η5-Cyclopentadienyldi(silylamido)] Ligands

Trichloro complexes [M{η5-C5H3[SiMe2(NHtBu)]2}Cl3] [M = Zr (2), Ti (3)] have been synthesized by reaction of the corresponding chlorides MCl4 with the lithium salt LiC5H3[SiMe2(NHtBu)]2 (1). Complexes 2 and 3 react with 2 equiv. of TiCl4 in toluene at 110°C to afford the di(chlorosilyl) derivatives [M{η5-C5H3(SiMe2Cl)2}Cl3] [M = Ti (5), Zr (8)]. Intermediate formation of [Ti{η5-C5H3[SiMe2(NHtBu)](SiMe2Cl)}Cl3] (4) has been proven by NMR spectroscopy. Reaction of 1 with TiCl4 (2 equiv.) in toluene at 110 °C in the presence of excess NEt3 has yielded the chloro-silyl complex [Ti{η5-C5H3(SiMe2Cl)(SiMe2-η1-NtBu)}Cl2] (7) through the intermediate formation of the amino-silyl derivative [Ti{η5-C5H3[SiMe2(NHtBu)] (SiMe2-η1-NtBu)}Cl2] (6). Reactions of di-ansa-[M{η5-C5H3(SiMe2-η1-NtBu)2}R] and ansa-[M{η5-C5H3[SiMe2(NHtBu)] (SiMe2-η1-NtBu)}R2] (M = Ti, Zr; R = NMe2, CH2Ph) complexes with NEt3·HCl have afforded the dichloro derivatives [M{η5-C5H3[SiMe2(NHtBu)] (SiMe2-η1-NtBu)}Cl2] [M = Ti (6), Zr (12)], the amine-coordinated zirconium compound [Zr{η5-C5H3 [SiMe2(NHtBu)](SiMe2-η1-NtBu)} Cl2(NMe2H)] (9) and the chloro-benzyl titanium complex [Ti{η5-C5H3[SiMe2(NHtBu)](SiMe2-η1-NtBu)}Cl(CH2Ph)] (11). Formation of the mono-substituted chloroamido zirconium complex [Zr{η5-C5H3[SiMe2 (NHtBu)](SiMe2-η1-NtBu)}Cl(NMe2)] (10) by the reaction of [Zr{η5-C5H3[SiMe2(NHtBu)] (SiMe2-η1-NtBu)}(NMe2)2] with SiClMe3 has been monitored in C6D6 by NMR spectroscopy. All of the new chloro complexes have been characterized by elemental analyses and NMR spectroscopy and the X-ray crystal structure of [Ti(η5-C5H3{SiMe2(NHtBu)}2)Cl3] (3) has been studied by diffraction methods.Ministerio de Educación, Cultura y DeporteComunidad de Madri

Evaluating feasibility of functional near-infrared spectroscopy in dolphins

SIGNIFICANCE: Using functional near-infrared spectroscopy (fNIRS) in bottlenose dolphins (Tursiops truncatus) could help to understand how echolocating animals perceive their environment and how they focus on specific auditory objects, such as fish, in noisy marine settings. AIM: To test the feasibility of near-infrared spectroscopy (NIRS) in medium-sized marine mammals, such as dolphins, we modeled the light propagation with computational tools to determine the wavelengths, optode locations, and separation distances that maximize sensitivity to brain tissue. APPROACH: Using frequency-domain NIRS, we measured the absorption and reduced scattering coefficient of dolphin sculp. We assigned muscle, bone, and brain optical properties from the literature and modeled light propagation in a spatially accurate and biologically relevant model of a dolphin head, using finite-element modeling. We assessed tissue sensitivities for a range of wavelengths (600 to 1700 nm), source-detector distances (50 to 120 mm), and animal sizes (juvenile model 25% smaller than adult). RESULTS: We found that the wavelengths most suitable for imaging the brain fell into two ranges: 700 to 900 nm and 1100 to 1150 nm. The optimal location for brain sensing positioned the center point between source and detector 30 to 50 mm caudal of the blowhole and at an angle 45 deg to 90 deg lateral off the midsagittal plane. Brain tissue sensitivity comparable to human measurements appears achievable only for smaller animals, such as juvenile bottlenose dolphins or smaller species of cetaceans, such as porpoises, or with source-detector separations ≫100  mm in adult dolphins. CONCLUSIONS: Brain measurements in juvenile or subadult dolphins, or smaller dolphin species, may be possible using specialized fNIRS devices that support optode separations of >100  mm. We speculate that many measurement repetitions will be required to overcome hemodynamic signals originating predominantly from the muscle layer above the skull. NIRS measurements of muscle tissue are feasible today with source-detector separations of 50 mm, or even less.Publisher PDFPeer reviewe

Transfer learning for classification of experimental ultrasonic non-destructive testing images from synthetic data

Lack of experimental training data is a significant challenge for the use of Deep Learning algorithms in Non-Destructive Testing. This work provides a Transfer Learning solution to the challenge of low training data volumes in Non-Destructive Ultrasonic Testing of carbon fibre reinforced polymer composites, which are known for their high structural ultrasonic noise. The performance of Convolutional Neural Networks for classification was initially tested on experimental data when trained on simulated data. The results demonstrated that due to inaccurate noise production the simulated data domain was too far from the experimental test data to provide accurate classification. Different synthetic datasets were then generated using a variety of methods and their effect on classification performance was studied. The primary focus of these datasets were different methods of noise generation for more experimentally accurate simulated images. To allow for the direct comparison of the different synthetic data generation methods, a standardized custom Convolutional Neural Network was developed. To make sure that the Neural Network was complex enough for the solution space hyperparameter optimization was performed on the network using a secondary experimental dataset. The hyperparameter optimization was a variant of Regularized Evolution [1] which was adapted for continuous and integer valued hyperparameters. The algorithm was initialized with a Population of 128 configurations generated via a random search. At each iteration of Regularized Evolution, a parent model was selected from a sample of configurations from the population, with the highest F1 score. A new child configuration was generated by mutating one of the parents hyperparameters. This child model was then trained and prepended to the population with the ‘oldest’ model discarded. The best performing model was then used for comparisons of classification accuracy for different synthetic datasets. The best performing synthetic dataset saw an F1 score increase of 0.34 (0.738-0.394) from the simulated dataset