Miracle-dz/UniFAR-FTUs huggingface dataset:
MARVIN: An Open Machine Learning Corpus and Environment for Automated Machine Learning Primitive Annotation and Execution

In this demo paper, we introduce the DARPA D3M program for automatic machine learning (ML) and JPL's MARVIN tool that provides an environment to locate, annotate, and execute machine learning primitives for use in ML pipelines. MARVIN is a web-based application and associated back-end interface written in Python that enables composition of ML pipelines from hundreds of primitives from the world of Scikit-Learn, Keras, DL4J and other widely used libraries. MARVIN allows for the creation of Docker containers that run on Kubernetes clusters within DARPA to provide an execution environment for automated machine learning. MARVIN currently contains over 400 datasets and challenge problems from a wide array of ML domains including routine classification and regression to advanced video/image classification and remote sensing.
A Deep Learning Method for Detection of Dangerous Equipment

Effective detection of concealed dangerous equipment is a critical need to protect people’ security in crowd public situations. Terahertz (THz) technology is ideally suited for such an application since it is able to see through clothing and packages, and, in addition, THz photons have lower energy than infrared and do not show the ionizing properties of X-ray radiation. There are two key technologies involved in this application: one is to develop THz imaging hardware and the other is to develop corresponding machine vision algorithms. In this paper we address to the latter and develop a deep learning-based method for detection and recognition of the dangerous equipment in THz images. The detection method is implemented with a two-stage classifier, in which the first-stage classifier is for detecting the direct visible dangerous equipment in natural light images, and the second-stage classifier is for detecting the concealed dangerous objects in THz images. In the detection system, when an input image is classified as a natural image, it is directly processed to give final classification result by the first-stage classifier. While the input image is classified as a THz image, it is sent to the second-stage classifier for finer processing and classification. Preliminary experiments conducted in the work show that the proposed method can give satisfactory performance in detection/recognition of dangerous equipment both in nature and THz images.
Scaling up data curation using deep learning: An application to literature triage in genomic variation resources

Manually curating biomedical knowledge from publications is necessary to build a knowledge based service that provides highly precise and organized information to users. The process of retrieving relevant publications for curation, which is also known as document triage, is usually carried out by querying and reading articles in PubMed. However, this query-based method often obtains unsatisfactory precision and recall on the retrieved results, and it is difficult to manually generate optimal queries. To address this, we propose a machine-learning assisted triage method. We collect previously curated publications from two databases UniProtKB/Swiss-Prot and the NHGRI-EBI GWAS Catalog, and used them as a gold-standard dataset for training deep learning models based on convolutional neural networks. We then use the trained models to classify and rank new publications for curation. For evaluation, we apply our method to the real-world manual curation process of UniProtKB/Swiss-Prot and the GWAS Catalog. We demonstrate that our machine-assisted triage method outperforms the current query-based triage methods, improves efficiency, and enriches curated content. Our method achieves a precision 1.81 and 2.99 times higher than that obtained by the current query-based triage methods of UniProtKB/Swiss-Prot and the GWAS Catalog, respectively, without compromising recall. In fact, our method retrieves many additional relevant publications that the query-based method of UniProtKB/Swiss-Prot could not find. As these results show, our machine learning-based method can make the triage process more efficient and is being implemented in production so that human curators can focus on more challenging tasks to improve the quality of knowledge bases.
The Role of Foundations in Open Source Projects

In the last years, a number of Open-Source Systems (OSS) have created parallel foundations, as legal instruments to better articulate the structure, collaboration and financial model for the project. Some examples are Apache, Linux, Mozilla, Eclipse or Django foundations. Nevertheless, foundations largely differ in the kind of mission they have and the support they provide to their project/s. In this paper we study the role of foundations in open source software development. We analyze the nature of 89 software foundations and then focus on the 18 most relevant ones to study their openness and influence in the development practices taking place in the endorsed projects. Our results reveal the existence of a significant number of foundations with the sole purpose of promoting the importance of the free software movement and/or that limit themselves to core legal aspects but do not play any role in the day-to-day operations of the project (e.g., a few of them are just umbrella organizations for a large variety of projects). Therefore, while useful, foundations do not remove the need for specific projects to develop their own governance, contribution and development policies.
A Benes packet network

Benes networks are constructed with simple switch modules and have many advantages, including small latency and requiring only an almost linear number of switch modules. As circuit-switches, Benes networks are rearrangeably non-blocking, which implies that they are full-throughput as packet switches, with suitable routing. Routing in Benes networks can be done by time-sharing permutations. However, this approach requires centralized control of the switch modules and statistical knowledge of the traffic arrivals. We propose a backpressure-based routing scheme for Benes networks, combined with end-to-end congestion control. This approach achieves the maximal utility of the network and requires only four queues per module, independently of the size of the network.
A 3D Finite Element Model of Mastication Muscles to Study the Jaw Movement for TMJ Prosthesis Performance Evaluation

In this study, a 3D finite element analysis was performed in order to investigate the movement of lower jaw of an intact mandible in comparison with the mandible having had a TMJ prosthesis replacement surgery. An artificial TMJ was replaced the left condyle of the mandible and the output was explored. The results revealed that the movement of the jaw is congruent with intact model. The geometry of the model was obtained through CT scan images of a healthy skull and seven bundles of muscle fibers were inserted in their appropriate positions following the anatomical data. Finally building the finite element model, the jaw movement was simulated under different muscle activations. In the next step, the TMJ prosthesis was implanted in its proper position and the same simulations were carried out. The results show that both models producing same range of movements under similar muscle activation. Moreover, the replacement of the condyle by TMJ prosthesis manifests that design of the TMJ implant produces kinematical resemblances with real situation, but the resulting stress distribution is completely different especially around the fastening screws. Due to muscle removal by surgery operation the model can predict the effect of muscle force redistribution for producing the same range of motion.
A Study of Crystal Orientation of Solder TSVs

We propose combined solder-TSVs and microbumps for cost reduction of 3-D integration. In this study, we find that crystal orientation of solder TSVs are oriented in the same direction by EBSD and TSVs are filled with single solder grain, i.e. grain boundaries are not observed at TSVs. We investigate the dependence of the cooling rate.
Can We Improve Stavudine's Safety Profile in Children? Pharmacokinetics of Intracellular Stavudine Triphosphate with Reduced Dosing

Stavudine remains a useful replacement option for treatment for HIV+ children. WHO reduced the adult dose to 30 mg twice daily, which maintains efficacy and lowers mitochondrial toxicity. ABSTRACT Stavudine remains a useful replacement option for treatment for HIV+ children. WHO reduced the adult dose to 30 mg twice daily, which maintains efficacy and lowers mitochondrial toxicity. We explored intracellular stavudine triphosphate levels in children receiving a reduced dose of 0.5 to 0.75 mg/kg of body weight twice daily to investigate whether a similar dose optimization can safely be made. A population pharmacokinetic model was developed to describe the pharmacokinetics of intracellular stavudine triphosphate in 23 HIV+ children and 24 HIV+ adults who received stavudine at 0.5 mg/kg and 20 mg twice daily for 7 days, respectively. Simulations were employed to optimize the pediatric dosing regimen to match exposures in adults receiving the current WHO-recommended dose of 30 mg twice daily. A biphasic disposition model with first-order appearance and disappearance described the pharmacokinetics of stavudine triphosphate. The use of allometric scaling with fat-free mass characterized well the pharmacokinetics in both adults and children, and no other significant effect could be detected. Simulations of 30 mg twice daily in adults predicted median (interquartile range [IQR]) stavudine triphosphate minimum drug concentration (Cmin) and maximum drug concentration (Cmax) values of 13 (10 to 19) and 45 (38 to 53) fmol/106 cells, respectively. Targeting this exposure, simulations in HIV+ children were used to identify a suitable weight-band dosing approach (0.5 to 0.75 mg/kg), which was predicted to achieve median (IQR) Cmin and Cmax values of 13 (9 to 18) and 49 (40 to 58) fmol/106 cells, respectively. Weight-band dosing using a stavudine dose of 0.5 to 0.75 mg/kg is proposed, and it shows comparable exposures to adults receiving the current WHO-recommended dose of 30 mg twice daily. Our pharmacokinetic results suggest that the decreased stavudine dose in children >2 years would have a reduced toxic effect while retaining antiretroviral efficacy.
Behavioural Comparison of Systems for Anomaly Detection

The internet is a bottomless cesspool of malicious software that attacks users and their devices or servers that offer services---on a worldwide scale. A defence against this constant barrage of attacks is difficult. While knowledge of previous attacks helps to prevent some new attacks, a determined attacker will almost always succeed. This paper proposes an approach to detect novel attacks via a comparison of system behaviour. A combination of a system-wide events collection and subsequent data analysis fingerprints processes and their file access behaviour. A comparison of these fingerprints results in seven "sameness" categories for processes, sorted from completely identical behaviour to unique and therefore highly suspicious. This categorisation provides guidance for further detailed assessment, if required. Results and insights from a prototype implementation suggest that the presented approach is a strategy for the detection of novel attacks.
Measure of the Ability Dominance of Tournament Systems and Subjective Judgment

Tournament systems in sports contests need to reflect players’ performance appropriately as well as draw people’s interest. In this study, we formulate the relationship between players’ strengths and winning probabilities based on the Elo rating system. We propose a scale for evaluating the extent to which a tournament system reflects the strength of players. To calculate the scale concretely, we explain three approaches. We then conduct a web survey to investigate people’s judgments of ability dominance and the interestingness of tournament systems. We simulate a number of types of tournament systems to predict the result by using stochastic modeling. The results show that the people’s judgments of ability dominance are consistent with the stochastic scale and that the expected interestingness reflects the uncertainty of winning. Our findings will be helpful for designing and evaluating systems of real sports contests.
A Compact 75GHz PA with 26.3% PAE and 24GHz Bandwidth in 22nm FinFET CMOS

This paper presents the design of an E-band PA in a 22nm FinFET CMOS process. The design utilizes device neutralization and low-k transformers for gain and bandwidth enhancement. A holistic design methodology is employed to further optimize PA efficiency. The PA achieves a peak gain of 18.6dB with a 3dB bandwidth of 62-86GHz (24GHz). At 75GHz, the measured Psat, OPldB and peak PAE are +12.6dBm, +5.7dBm, and 26.3%, respectively. The PA can amplify a 6Gb/s 16-QAM signal at an average Poutof +5dBm with a PAE of 10% and −26dB EVM(rms). Compact layout of the PA yields a core area of 0.054mm2, enabling compact integration into phased array transceivers.
TDC: Tagless DRAM Cache

Advancements in 3D-stacking technology lead to the usage of stacked DRAM as a last level cache. DRAM caches present multiple design challenges. DRAM cache tag management overhead is one of them because of large area requirement and high access time for look-up. Numerous techniques have been proposed to handle the challenges involved with the DRAM caches. We consider a design choice wherein the tag array storage is removed completely. In this work, we propose a Tagless DRAM Cache (TDC), that completely removes tag array from the DRAM cache and instead, uses the tag-array of the SRAM last level cache (LLC) along with DRAM cache way indices to locate data in the DRAM cache. Experimental evaluation, considering 4-core configuration, shows that TDC achieves a speedup of 9.97% when compared to baseline. Further, TDC shows greater promise by providing reduction in average power consumption by 11.22% and average SRAM LLC miss penalty by 30.8%.
Critical Analysis of LPL according to Articles 12 - 14 of the GDPR

On the 25th May 2018 the General Data Protection Regulation (GDPR) will enter into force implying new challenges to both legal and computer sciences. The Layered Privacy Language (LPL) is intended to model privacy policies to enforce policy-based, privacy-preserving processing. In this paper, we identify requirements for privacy policies based on Art. 12 - 14 of the GDPR, analyze LPL according to the derived requirements, and propose improvements for LPL accordingly.
Effects of organism and substrate size on burial mechanics of English sole, Parophrys vetulus

ABSTRACT Flatfishes use cyclic body undulations to force water into the sediment and fluidize substrate particles, displacing them into the water column. When water velocity decreases, suspended particles settle back onto the fish, hiding it from view. Burial may become more challenging as flatfishes grow because the area to be covered increases exponentially with the second power of length. In addition, particle size is not uniform in naturally occurring substrates, and larger particles require higher water velocities for fluidization. We quantified the effects of organism and particle-size scaling on burial behavior of English sole, Parophrys vetulus. We recorded burial events from a size range of individuals (5–32 cm total length, TL), while maintaining constant substrate grain size. Larger fish used lower cycle frequencies and took longer to bury, but overall burial performance was maintained (∼100% coverage). To test the effect of particle size on burial performance, individuals of similar lengths (5.7–8.1 cm TL) were presented with different substrate sizes (0.125–0.710 mm). Particle size did not affect cycle frequency or time to burial, but fish did not achieve 100% coverage with the largest particles because they could not fluidize this substrate. Taken together, these results suggest that both body size and substrate grain size can potentially limit the ability of flatfishes to bury: a very large fish (>150 cm) may move too slowly to fluidize all but the smallest substrate particles and some particles are simply too large for smaller individuals to fluidize. Summary: Disentangling the role of body size and substrate size in scaling of flatfish burial reveals constraints on burial performance with large particles and at large body sizes.
Timed C: An Extension to the C Programming Language for Real-Time Systems

The design and implementation of real-time systems require that both the logical and the temporal behavior are correct. There exist several specialized languages and tools that use the notion of logical time, as well as industrial strength languages such as Ada and RTJS that incorporate direct handling of real time. Although these languages and tools have shown to be good alternatives for safety-critical systems, most commodity real-time and embedded systems are today implemented in the standard C programming language. Such systems are typically targeting proprietary bare-metal platforms, standard POSIX compliant platforms, or open-source operating systems. It is, however, error prone to develop large, reliable, and portable systems based on these APIs. In this paper, we present an extension to the C programming language, called Timed C, with a minimal set of language primitives, and show how a retargetable source-to-source compiler can be used to compile and execute simple, expressive, and portable programs. To evaluate our approach, we conduct a case study of a CubeSat satellite. We implement the core timing aspects in Timed C, and show portability by compiling on-board software to both flight hardware, and to low-cost experimental platforms.
Cxxc Finger Protein 1 Positively Regulates GM-CSF-Derived Macrophage Phagocytosis Through Csf2rα-Mediated Signaling

Macrophages have a defensive function against bacteria through phagocytosis and the secretion of cytokines. Histone modifications play an essential role in macrophage functions. Here, we report that Cxxc finger protein 1 (CFP1), a key component of the SETD1 histone methyltransferase complex, promoted the phagocytic and bactericidal activity of GM-CSF-derived macrophages. CFP1-deficient mice were more susceptible to bacterial infection due to the decreased expression of Csf2rα, a subunit of the GM-CSF receptor essential for inflammation and alveolar macrophage development, through the loss of H3K4 modifications in the promoter of the Csf2rα gene. In addition, the lung tissues of CFP1-deficient mice exhibited spontaneous inflammatory symptoms, including both the infiltration of inflammatory cells and the accumulation of surfactant phospholipids and proteins. Furthermore, we showed that Csf2rα and PU.1 can partially rescue the defects in phagocytosis and in the intracellular killing of bacteria. Collectively, our data highlight the importance of CFP1 in the phagocytic and bactericidal activity of macrophages.
On Dual-Path Energy-Harvesting Receivers for IoT With Batteries Having Internal Resistance

Internet of Things (IoT) systems will increasingly rely on energy harvested from their environment, and energy harvesting (EH) techniques necessitate a rethinking of how we design and optimize IoT systems. The performance of EH IoT systems is affected by the battery nonidealities and the energy consumption for transmitting and receiving. While EH considerations at the transmitter have been widely studied, the EH receiver has received relatively much less attention. Motivated by this, we investigate, in this paper, the performance of EH receivers in IoT systems with batteries having non-negligible internal resistance. We first consider a receiver with a dual-path architecture and give an optimal battery management scheme. Then, based on this management scheme, we maximize the amount of information decoded at the receiver for single and multiple block scenarios. In the multiple block scenario, we transform the nonconvex problem into a series of convex problems by exploiting certain structural properties of the nonconvex constraints. Additionally, we present extensive numerical results to validate our analysis and to study the impact of the internal resistance. This paper suggests that the internal resistance significantly impacts the design and performance of EH IoT systems. However, the dual-path architecture can be an efficient way to reduce the performance loss caused by internal resistance. Finally, we discuss implementation considerations.
Efficient In-Situ Creation of Augmented Reality Tutorials

With increasing complexity of system maintenance there is an increased need for efficient tutorials that support easy understanding of the individual steps and efficient visualization at the operation site. This can be achieved through augmented reality, where users observe computer generated 3D content that is spatially consistent with their surroundings. However, generating such tutorials is a tedious process, as they have to be prepared from scratch in a time consuming process. An intuitive interface that allows users to easily place annotations and models could help reduce the complexity of this task. In this paper, we discuss the design of an interface for efficient creation of 3D aligned annotations on a handheld device. We also show how our method could improve the collaboration between a local user and a remote expert in a remote support scenario.
Implicit Parameters for Logic Programming

Implicit parameters allow programmers to omit certain arguments from function calls and have them automatically inferred by the compiler based on their types. At every call site, the compiler determines the values of the implicit parameters based on their declared types and the bindings currently in implicit scope. The programmer controls this mechanism in two ways: by adding bindings to the implicit scope, or by explicitly providing the implicit parameters for the function call. Implicit parameters are known from functional and object-oriented languages such as Haskell and Scala. In recent years, more languages have added support for implicit parameters, including Agda, Coq, and Idris. Implicit parameters have played an impressive role as the foundation for a broad range of language features such as type classes, capability and effect systems, software transactional memory, macros, and more. In this paper, we propose a design of implicit parameters for typed Horn clause based logic programming languages, such as Datalog and Prolog. We illustrate the usefulness of implicit parameters and show how they support logic programming in the large. We explore some of the differences that arise between implicit parameters in functional languages and in logic languages.
Making space for cloth simulations using energy minimization

Geometry interpenetrations are a common issue in creature effects workflows, particularly in cases which require simulations, for example hair and clothing. Production rigs often introduce self intersections in regions like armpits and elbows, which can cause ugly instabilities and undesirable behavior when they interfere with simulated objects such as garments. To achieve visually acceptable results, these simulations often require a small gap to allow sliding between opposing surfaces, and the process of making these modifications can often be quite manual. Here we present a production proven creature effects tool for resolving these issues automatically.