Showing papers by "Cornell University published in 2016"

Feature Pyramid Networks for Object Detection

Abstract: Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But recent deep learning object detectors have avoided pyramid representations, in part because they are compute and memory intensive. In this paper, we exploit the inherent multi-scale, pyramidal hierarchy of deep convolutional networks to construct feature pyramids with marginal extra cost. A top-down architecture with lateral connections is developed for building high-level semantic feature maps at all scales. This architecture, called a Feature Pyramid Network (FPN), shows significant improvement as a generic feature extractor in several applications. Using FPN in a basic Faster R-CNN system, our method achieves state-of-the-art single-model results on the COCO detection benchmark without bells and whistles, surpassing all existing single-model entries including those from the COCO 2016 challenge winners. In addition, our method can run at 5 FPS on a GPU and thus is a practical and accurate solution to multi-scale object detection. Code will be made publicly available.

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

deepTools2: a next generation web server for deep-sequencing data analysis

Abstract: We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available.

Clinical Practice Guideline for the Management of Candidiasis: 2016 Update by the Infectious Diseases Society of America

Abstract: It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.

Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade

Abstract: As tumors grow, they acquire mutations, some of which create neoantigens that influence the response of patients to immune checkpoint inhibitors. We explored the impact of neoantigen intratumor heterogeneity (ITH) on antitumor immunity. Through integrated analysis of ITH and neoantigen burden, we demonstrate a relationship between clonal neoantigen burden and overall survival in primary lung adenocarcinomas. CD8+ tumor-infiltrating lymphocytes reactive to clonal neoantigens were identified in early-stage non–small cell lung cancer and expressed high levels of PD-1. Sensitivity to PD-1 and CTLA-4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumors enriched for clonal neoantigens. T cells recognizing clonal neoantigens were detectable in patients with durable clinical benefit. Cytotoxic chemotherapy–induced subclonal neoantigens, contributing to an increased mutational load, were enriched in certain poor responders. These data suggest that neoantigen heterogeneity may influence immune surveillance and support therapeutic developments targeting clonal neoantigens.

Implementing an Antibiotic Stewardship Program: Guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America

Abstract: Evidence-based guidelines for implementation and measurement of antibiotic stewardship interventions in inpatient populations including long-term care were prepared by a multidisciplinary expert panel of the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. The panel included clinicians and investigators representing internal medicine, emergency medicine, microbiology, critical care, surgery, epidemiology, pharmacy, and adult and pediatric infectious diseases specialties. These recommendations address the best approaches for antibiotic stewardship programs to influence the optimal use of antibiotics.

Practice guidelines for the diagnosis and management of aspergillosis: 2016 update by the infectious diseases society of America

Abstract: It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.

Hawk: The Blockchain Model of Cryptography and Privacy-Preserving Smart Contracts

Abstract: Emerging smart contract systems over decentralized cryptocurrencies allow mutually distrustful parties to transact safely without trusted third parties. In the event of contractual breaches or aborts, the decentralized blockchain ensures that honest parties obtain commensurate compensation. Existing systems, however, lack transactional privacy. All transactions, including flow of money between pseudonyms and amount transacted, are exposed on the blockchain. We present Hawk, a decentralized smart contract system that does not store financial transactions in the clear on the blockchain, thus retaining transactional privacy from the public's view. A Hawk programmer can write a private smart contract in an intuitive manner without having to implement cryptography, and our compiler automatically generates an efficient cryptographic protocol where contractual parties interact with the blockchain, using cryptographic primitives such as zero-knowledge proofs. To formally define and reason about the security of our protocols, we are the first to formalize the blockchain model of cryptography. The formal modeling is of independent interest. We advocate the community to adopt such a formal model when designing applications atop decentralized blockchains.

An integrated design and fabrication strategy for entirely soft, autonomous robots

Abstract: An untethered, entirely soft robot is designed to operate autonomously by combining microfluidic logic and hydrogen peroxide as an on-board fuel supply. Soft robotics have so far necessarily included some 'hard' or metallic elements, in particular in the form of batteries or wiring, to connect them to an external power source. Additionally, external wiring tethering them to a power source places limits on the autonomy of such robots. Now Jennifer Lewis and colleagues have combined a 3D-printed soft polymeric robot with microfluidic logic and hydrogen peroxide as an onboard fuel to produce an eight-armed robot — an 'octobot' — that actuates its arms, without the incorporation of any hard structures. The hydrogen peroxide decomposes in the presence of a platinum catalyst to produce oxygen and a volumetric expansion that fills bladders embedded within the arms of the octobot. The design of the fuel reservoirs, microfluidic channels and vents to release the gas means that two sets of arms actuate cyclically. Soft robots possess many attributes that are difficult, if not impossible, to achieve with conventional robots composed of rigid materials1,2. Yet, despite recent advances, soft robots must still be tethered to hard robotic control systems and power sources3,4,5,6,7,8,9,10. New strategies for creating completely soft robots, including soft analogues of these crucial components, are needed to realize their full potential. Here we report the untethered operation of a robot composed solely of soft materials. The robot is controlled with microfluidic logic11 that autonomously regulates fluid flow and, hence, catalytic decomposition of an on-board monopropellant fuel supply. Gas generated from the fuel decomposition inflates fluidic networks downstream of the reaction sites, resulting in actuation12. The body and microfluidic logic of the robot are fabricated using moulding and soft lithography, respectively, and the pneumatic actuator networks, on-board fuel reservoirs and catalytic reaction chambers needed for movement are patterned within the body via a multi-material, embedded 3D printing technique13,14. The fluidic and elastomeric architectures required for function span several orders of magnitude from the microscale to the macroscale. Our integrated design and rapid fabrication approach enables the programmable assembly of multiple materials within this architecture, laying the foundation for completely soft, autonomous robots.

Deep Networks with Stochastic Depth

Abstract: Very deep convolutional networks with hundreds of layers have led to significant reductions in error on competitive benchmarks. Although the unmatched expressiveness of the many layers can be highly desirable at test time, training very deep networks comes with its own set of challenges. The gradients can vanish, the forward flow often diminishes, and the training time can be painfully slow. To address these problems, we propose stochastic depth, a training procedure that enables the seemingly contradictory setup to train short networks and use deep networks at test time. We start with very deep networks but during training, for each mini-batch, randomly drop a subset of layers and bypass them with the identity function. This simple approach complements the recent success of residual networks. It reduces training time substantially and improves the test error significantly on almost all data sets that we used for evaluation. With stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4.91 % on CIFAR-10).

Tests of general relativity with GW150914

Abstract: The LIGO detection of GW150914 provides an unprecedented opportunity to study the two-body motion of a compact-object binary in the large-velocity, highly nonlinear regime, and to witness the final merger of the binary and the excitation of uniquely relativistic modes of the gravitational field. We carry out several investigations to determine whether GW150914 is consistent with a binary black-hole merger in general relativity. We find that the final remnant’s mass and spin, as determined from the low-frequency (inspiral) and high-frequency (postinspiral) phases of the signal, are mutually consistent with the binary black-hole solution in general relativity. Furthermore, the data following the peak of GW150914 are consistent with the least-damped quasinormal mode inferred from the mass and spin of the remnant black hole. By using waveform models that allow for parametrized general-relativity violations during the inspiral and merger phases, we perform quantitative tests on the gravitational-wave phase in the dynamical regime and we determine the first empirical bounds on several high-order post-Newtonian coefficients. We constrain the graviton Compton wavelength, assuming that gravitons are dispersed in vacuum in the same way as particles with mass, obtaining a 90%-confidence lower bound of 1013 km. In conclusion, within our statistical uncertainties, we find no evidence for violations of general relativity in the genuinely strong-field regime of gravity.

Rapid removal of organic micropollutants from water by a porous β-cyclodextrin polymer

Abstract: The global occurrence in water resources of organic micropollutants, such as pesticides and pharmaceuticals, has raised concerns about potential negative effects on aquatic ecosystems and human health. Activated carbons are the most widespread adsorbent materials used to remove organic pollutants from water but they have several deficiencies, including slow pollutant uptake (of the order of hours) and poor removal of many relatively hydrophilic micropollutants. Furthermore, regenerating spent activated carbon is energy intensive (requiring heating to 500-900 degrees Celsius) and does not fully restore performance. Insoluble polymers of β-cyclodextrin, an inexpensive, sustainably produced macrocycle of glucose, are likewise of interest for removing micropollutants from water by means of adsorption. β-cyclodextrin is known to encapsulate pollutants to form well-defined host-guest complexes, but until now cross-linked β-cyclodextrin polymers have had low surface areas and poor removal performance compared to conventional activated carbons. Here we crosslink β-cyclodextrin with rigid aromatic groups, providing a high-surface-area, mesoporous polymer of β-cyclodextrin. It rapidly sequesters a variety of organic micropollutants with adsorption rate constants 15 to 200 times greater than those of activated carbons and non-porous β-cyclodextrin adsorbent materials. In addition, the polymer can be regenerated several times using a mild washing procedure with no loss in performance. Finally, the polymer outperformed a leading activated carbon for the rapid removal of a complex mixture of organic micropollutants at environmentally relevant concentrations. These findings demonstrate the promise of porous cyclodextrin-based polymers for rapid, flow-through water treatment.

Improved Bacterial 16S rRNA Gene (V4 and V4-5) and Fungal Internal Transcribed Spacer Marker Gene Primers for Microbial Community Surveys.

Abstract: Designing primers for PCR-based taxonomic surveys that amplify a broad range of phylotypes in varied community samples is a difficult challenge, and the comparability of data sets amplified with varied primers requires attention. Here, we examined the performance of modified 16S rRNA gene and internal transcribed spacer (ITS) primers for archaea/bacteria and fungi, respectively, with nonaquatic samples. We moved primer bar codes to the 5' end, allowing for a range of different 3' primer pairings, such as the 515f/926r primer pair, which amplifies variable regions 4 and 5 of the 16S rRNA gene. We additionally demonstrated that modifications to the 515f/806r (variable region 4) 16S primer pair, which improves detection of Thaumarchaeota and clade SAR11 in marine samples, do not degrade performance on taxa already amplified effectively by the original primer set. Alterations to the fungal ITS primers did result in differential but overall improved performance compared to the original primers. In both cases, the improved primers should be widely adopted for amplicon studies. IMPORTANCE We continue to uncover a wealth of information connecting microbes in important ways to human and environmental ecology. As our scientific knowledge and technical abilities improve, the tools used for microbiome surveys can be modified to improve the accuracy of our techniques, ensuring that we can continue to identify groundbreaking connections between microbes and the ecosystems they populate, from ice caps to the human body. It is important to confirm that modifications to these tools do not cause new, detrimental biases that would inhibit the field rather than continue to move it forward. We therefore demonstrated that two recently modified primer pairs that target taxonomically discriminatory regions of bacterial and fungal genomic DNA do not introduce new biases when used on a variety of sample types, from soil to human skin. This confirms the utility of these primers for maintaining currently recommended microbiome research techniques as the state of the art.

Climate-smart soils

Abstract: Soils are integral to the function of all terrestrial ecosystems and to food and fibre production. An overlooked aspect of soils is their potential to mitigate greenhouse gas emissions. Although proven practices exist, the implementation of soil-based greenhouse gas mitigation activities are at an early stage and accurately quantifying emissions and reductions remains a substantial challenge. Emerging research and information technology developments provide the potential for a broader inclusion of soils in greenhouse gas policies. Here we highlight 'state of the art' soil greenhouse gas research, summarize mitigation practices and potentials, identify gaps in data and understanding and suggest ways to close such gaps through new research, technology and collaboration.

Design principles for electrolytes and interfaces for stable lithium-metal batteries

Abstract: The development of rechargeable batteries that use metallic lithium anodes faces challenges such as dendrite formation. Here the authors review recent advances in preventing the proliferation of dendrite and discuss design principles for electrolytes and interfaces in lithium-metal batteries.

Daratumumab, Bortezomib, and Dexamethasone for Multiple Myeloma

Abstract: BackgroundDaratumumab, a human IgGκ monoclonal antibody that targets CD38, induces direct and indirect antimyeloma activity and has shown substantial efficacy as monotherapy in heavily pretreated patients with multiple myeloma, as well as in combination with bortezomib in patients with newly diagnosed multiple myeloma. MethodsIn this phase 3 trial, we randomly assigned 498 patients with relapsed or relapsed and refractory multiple myeloma to receive bortezomib (1.3 mg per square meter of body-surface area) and dexamethasone (20 mg) alone (control group) or in combination with daratumumab (16 mg per kilogram of body weight) (daratumumab group). The primary end point was progression-free survival. ResultsA prespecified interim analysis showed that the rate of progression-free survival was significantly higher in the daratumumab group than in the control group; the 12-month rate of progression-free survival was 60.7% in the daratumumab group versus 26.9% in the control group. After a median follow-up period ...

Treating rheumatoid arthritis to target: 2014 update of the recommendations of an international task force

Abstract: Background Reaching the therapeutic target of remission or low-disease activity has improved outcomes in patients with rheumatoid arthritis (RA) significantly. The treat-to-target recommendations, formulated in 2010, have provided a basis for implementation of a strategic approach towards this therapeutic goal in routine clinical practice, but these recommendations need to be re-evaluated for appropriateness and practicability in the light of new insights. Objective To update the 2010 treat-to-target recommendations based on systematic literature reviews (SLR) and expert opinion. Methods A task force of rheumatologists, patients and a nurse specialist assessed the SLR results and evaluated the individual items of the 2010 recommendations accordingly, reformulating many of the items. These were subsequently discussed, amended and voted upon by >40 experts, including 5 patients, from various regions of the world. Levels of evidence, strengths of recommendations and levels of agreement were derived. Results The update resulted in 4 overarching principles and 10 recommendations. The previous recommendations were partly adapted and their order changed as deemed appropriate in terms of importance in the view of the experts. The SLR had now provided also data for the effectiveness of targeting low-disease activity or remission in established rather than only early disease. The role of comorbidities, including their potential to preclude treatment intensification, was highlighted more strongly than before. The treatment aim was again defined as remission with low-disease activity being an alternative goal especially in patients with long-standing disease. Regular follow-up (every 1-3 months during active disease) with according therapeutic adaptations to reach the desired state was recommended. Follow-up examinations ought to employ composite measures of disease activity that include joint counts. Additional items provide further details for particular aspects of the disease, especially comorbidity and shared decision-making with the patient. Levels of evidence had increased for many items compared with the 2010 recommendations, and levels of agreement were very high for most of the individual recommendations (=9/10). Conclusions The 4 overarching principles and 10 recommendations are based on stronger evidence than before and are supposed to inform patients, rheumatologists and other stakeholders about strategies to reach optimal outcomes of RA.

Executive Summary: Clinical Practice Guideline for the Management of Candidiasis: 2016 Update by the Infectious Diseases Society of America

Abstract: It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.

Inherited DNA-Repair Gene Mutations in Men with Metastatic Prostate Cancer

Abstract: BackgroundInherited mutations in DNA-repair genes such as BRCA2 are associated with increased risks of lethal prostate cancer. Although the prevalence of germline mutations in DNA-repair genes among men with localized prostate cancer who are unselected for family predisposition is insufficient to warrant routine testing, the frequency of such mutations in patients with metastatic prostate cancer has not been established. MethodsWe recruited 692 men with documented metastatic prostate cancer who were unselected for family history of cancer or age at diagnosis. We isolated germline DNA and used multiplex sequencing assays to assess mutations in 20 DNA-repair genes associated with autosomal dominant cancer-predisposition syndromes. ResultsA total of 84 germline DNA-repair gene mutations that were presumed to be deleterious were identified in 82 men (11.8%); mutations were found in 16 genes, including BRCA2 (37 men [5.3%]), ATM (11 [1.6%]), CHEK2 (10 [1.9% of 534 men with data]), BRCA1 (6 [0.9%]), RAD51D (3 [...

m 6 A RNA methylation promotes XIST -mediated transcriptional repression

Abstract: The long non-coding RNA X-inactive specific transcript (XIST) mediates the transcriptional silencing of genes on the X chromosome. Here we show that, in human cells, XIST is highly methylated with at least 78 N^6-methyladenosine (m^6A) residues—a reversible base modification of unknown function in long non-coding RNAs. We show that m^6A formation in XIST, as well as in cellular mRNAs, is mediated by RNA-binding motif protein 15 (RBM15) and its paralogue RBM15B, which bind the m^6A-methylation complex and recruit it to specific sites in RNA. This results in the methylation of adenosine nucleotides in adjacent m^6A consensus motifs. Furthermore, we show that knockdown of RBM15 and RBM15B, or knockdown of methyltransferase like 3 (METTL3), an m^6A methyltransferase, impairs XIST-mediated gene silencing. A systematic comparison of m^6A-binding proteins shows that YTH domain containing 1 (YTHDC1) preferentially recognizes m^6A residues on XIST and is required for XIST function. Additionally, artificial tethering of YTHDC1 to XIST rescues XIST-mediated silencing upon loss of m^6A. These data reveal a pathway of m^6A formation and recognition required for XIST-mediated transcriptional repression.

Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer

Abstract: An increasingly recognized resistance mechanism to androgen receptor (AR)-directed therapy in prostate cancer involves epithelial plasticity, in which tumor cells demonstrate low to absent AR expression and often have neuroendocrine features. The etiology and molecular basis for this 'alternative' treatment-resistant cell state remain incompletely understood. Here, by analyzing whole-exome sequencing data of metastatic biopsies from patients, we observed substantial genomic overlap between castration-resistant tumors that were histologically characterized as prostate adenocarcinomas (CRPC-Adeno) and neuroendocrine prostate cancer (CRPC-NE); analysis of biopsy samples from the same individuals over time points to a model most consistent with divergent clonal evolution. Genome-wide DNA methylation analysis revealed marked epigenetic differences between CRPC-NE tumors and CRPC-Adeno, and also designated samples of CRPC-Adeno with clinical features of AR independence as CRPC-NE, suggesting that epigenetic modifiers may play a role in the induction and/or maintenance of this treatment-resistant state. This study supports the emergence of an alternative, 'AR-indifferent' cell state through divergent clonal evolution as a mechanism of treatment resistance in advanced prostate cancer.

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

Abstract: Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

Membership Inference Attacks against Machine Learning Models

Abstract: We quantitatively investigate how machine learning models leak information about the individual data records on which they were trained. We focus on the basic membership inference attack: given a data record and black-box access to a model, determine if the record was in the model's training dataset. To perform membership inference against a target model, we make adversarial use of machine learning and train our own inference model to recognize differences in the target model's predictions on the inputs that it trained on versus the inputs that it did not train on. We empirically evaluate our inference techniques on classification models trained by commercial "machine learning as a service" providers such as Google and Amazon. Using realistic datasets and classification tasks, including a hospital discharge dataset whose membership is sensitive from the privacy perspective, we show that these models can be vulnerable to membership inference attacks. We then investigate the factors that influence this leakage and evaluate mitigation strategies.

Stealing Machine Learning Models via Prediction APIs

Abstract: Machine learning (ML) models may be deemed confidential due to their sensitive training data, commercial value, or use in security applications. Increasingly often, confidential ML models are being deployed with publicly accessible query interfaces. ML-as-a-service ("predictive analytics") systems are an example: Some allow users to train models on potentially sensitive data and charge others for access on a pay-per-query basis. The tension between model confidentiality and public access motivates our investigation of model extraction attacks. In such attacks, an adversary with black-box access, but no prior knowledge of an ML model's parameters or training data, aims to duplicate the functionality of (i.e., "steal") the model. Unlike in classical learning theory settings, ML-as-a-service offerings may accept partial feature vectors as inputs and include confidence values with predictions. Given these practices, we show simple, efficient attacks that extract target ML models with near-perfect fidelity for popular model classes including logistic regression, neural networks, and decision trees. We demonstrate these attacks against the online services of BigML and Amazon Machine Learning. We further show that the natural countermeasure of omitting confidence values from model outputs still admits potentially harmful model extraction attacks. Our results highlight the need for careful ML model deployment and new model extraction countermeasures.

Highly stretchable electroluminescent skin for optical signaling and tactile sensing

Abstract: Cephalopods such as octopuses have a combination of a stretchable skin and color-tuning organs to control both posture and color for visual communication and disguise. We present an electroluminescent material that is capable of large uniaxial stretching and surface area changes while actively emitting light. Layers of transparent hydrogel electrodes sandwich a ZnS phosphor-doped dielectric elastomer layer, creating thin rubber sheets that change illuminance and capacitance under deformation. Arrays of individually controllable pixels in thin rubber sheets were fabricated using replica molding and were subjected to stretching, folding, and rolling to demonstrate their use as stretchable displays. These sheets were then integrated into the skin of a soft robot, providing it with dynamic coloration and sensory feedback from external and internal stimuli.