Miracle-dz/UniFAR-FTUs huggingface dataset:
Correct-by-construction transformations across design environments for model-based embedded software development

Embedded software design for real time reactive systems has become the bottleneck in their market introduction into complex products such as automobiles, airplanes, and industrial control plant. In particular, functional correctness and reactive performance are increasingly difficult to verify. The advent of model-based design methodologies has alleviated some of the verification-related problems by making the code-generation process flow automatically from the model description. Given the relative infancy of this approach, several companies rely upon design flows based on different tools connected together by file transfer. This way of integrating tools defeats the very purpose of the methodology, introducing a high potential of errors in the transformation from one format to another and preventing formal analysis of the properties of the design. We propose to adopt a formal transformation across different tools and we give an example of this approach by linking two tools that are widely used in the automotive domain, Simulink and ASCET. We believe that this approach can be applied to any embedded software design flow to leverage the power of all the tools in the flow.
Gold Nanotubes as Sensitive, Solution-Suspendable Refractive Index Reporters

We report the synthesis of solution-suspendable hollow gold nanotubes and study their plasmonic properties as both an aligned array and in solution. In solution, we observe the transverse and longitudinal modes expected for anisitropic gold nanostructures, as well as a quadrupole resonance. Gold nanotubes exhibit refractive index sensitivities of 1568 nm/RIU.
Outage Probability and Power Allocation for Two-Way DF Relay Networks with Relay Selection

In this paper, we investigate the outage prob- ability and power allocation for the two-way decode-and- forward (DF) relay networks with relay selection. Specially, we consider independent but not necessarily identical dis- tributed Rayleigh fading channels. Firstly, we derive an exact closed form outage probability expression. To shed light on the relation between the outage probability and the power allocation factor, an upper bound for the outage prob- ability is derived, too. We then propose a power allocation scheme in the sense of minimizing this upper bound. Monte Carlo simulations are conducted to show that the derived outage probability expression excellently matches simulation results, and our proposed power allocation scheme performs effectively.
Use of hospital services by age and comorbidity after an index heart failure admission in England: an observational study

Objectives To describe hospital inpatient, emergency department (ED) and outpatient department (OPD) activity for patients in the year following their first emergency admission for heart failure (HF). To assess the proportion receiving specialist assessment within 2 weeks of hospital discharge, as now recommended by guidelines. Design Observational study of national administrative data. Setting All acute NHS hospitals in England. Participants 82 241 patients with an index emergency admission between April 2009 and March 2011 with a primary diagnosis of HF. Main outcome measures Cardiology OPD appointment within 2 weeks and within a year of discharge from the index admission; emergency department (ED) and inpatient use within a year. Results 15.1% died during the admission. Of the 69 848 survivors, 19.7% were readmitted within 30 days and half within a year, the majority for non-HF diagnoses. 6.7% returned to the ED within a week of discharge, of whom the majority (77.6%) were admitted. The two most common OPD specialties during the year were cardiology (24.7% of the total appointments) and anticoagulant services (12.5%). Although half of all patients had a cardiology appointment within a year, the proportion within the recommended 2 weeks of discharge was just 6.8% overall and varied by age, from 2.4% in those aged 90+ to 19.6% in those aged 18–45 (p<0.0001); appointments in other specialties made up only some of the shortfall. More comorbidity at any age was associated with higher rates of cardiology OPD follow-up. Conclusions Patients with HF are high users of hospital services. Postdischarge cardiology OPD follow-up rates fell well below current National Institute for Health and Care Excellence guidelines, particularly for the elderly and those with less comorbidity.
Scalable multi stage clustering of tagged micro-messages

The growing popularity of microblogging backed by services like Twitter, Facebook, Google+ and LinkedIn, raises the challenge of clustering short and extremely sparse documents. In this work we propose SMSC -- a scalable, accurate and efficient multi stage clustering algorithm. Our algorithm leverages users practice of adding tags to some messages by bootstrapping over virtual non sparse documents. We experiment on a large corpus of tweets from Twitter, and evaluate results against a gold-standard classification validated by seven clustering evaluation measures (information theoretic, paired and greedy). Results show that the algorithm presented is both accurate and efficient, significantly outperforming other algorithms. Under reasonable practical assumptions, our algorithm scales up sublinearly in time.
Domestic Policies, Hidden Protection and the GATT/WTO

As tariff barriers have fallen worldwide, regulation of domestic policy has become increasingly important in international trade agreements. This has led to the emergence of a theoretical literature addressing the integration of perfectly observable domestic policy into trade agreements. However, the assumption that domestic policy is perfectly observable is problematic since the interpretation and enforcement of domestic policy statutes is often non-transparent. Thus, it may be difficult to determine whether lack of market access is due simply to random shocks or to the use of domestic policies as hidden trade barriers. In this paper, we model international coordination over trade and domestic policy when domestic policy is private information and thus can be used as a form of "hidden protection. " We show that the optimal design of an efficient agreement depends greatly on whether domestic policy is observable or unobservable.
Genetic Polymorphisms Analysis of Pharmacogenomic VIP Variants in Miao Ethnic Group of Southwest China

Background Genetic polymorphisms have a potential clinical role in determining both inter-individual and inter-ethnic differences in drug efficacy, but we have not found any pharmacogenomics information regarding minorities, such as the Miao ethnic group. Our study aimed to screen numbers of the Miao ethnic group for genotype frequencies of VIP variants and to determine differences between the Miao and other human populations worldwide. Material/Methods In this study, we genotyped 66 Very Important Pharmacogene (VIP) variants selected from PharmGKB in 98 unrelated, healthy Miao individuals from the Guizhou province and compared our data with 12 other populations, including 11 populations from the HapMap data set and Xi’an Han Chinese. Results Using the χ2 test, we found that the allele frequencies of the VDR rs1544410 and VKORC1 (rs9934438) variants in the Miao population are quite different from that in other ethnic groups. Furthermore, we found that genotype frequencies of rs1801133 (MTHFR) in the 13 selected populations are significantly different. Population structure and F-statistics (Fst) analysis show that the genetic background of the Miao is relatively close to that of Chinese in metropolitan Denver, CO, USA (CHD). Conclusions Our results help complete the information provided by the pharmacogenomics database of the Miao ethnic group and provide a theoretical basis for safer drug administration, which may be useful for diagnosing and treating diseases in this population.
Institute of Perception, Action and Behaviour Environment Authentication through 3d Structural Analysis Environment Authentication through 3d Structural Analysis Environment Authentication through 3d Structural Analysis

We address the validation of the current sensed environmental state against a model known from earlier perception. Our surface based approach compares 3D range data of a built environment against an a priori scene model with the analysis of identified differences facilitating the hypothesis of causal structural changes within the scene. Experimental results show good success rates in identifying and analysing realistic structural changes introduced across example industrially themed scenes. Permission is granted for this report to be reproduced by others for non-commercial purposes as long as this copyright notice is reprinted in full in any reproduction. Applications to make other use of the material should be addressed in the first instance to Copyright Permissions, Abstract. We address the validation of the current sensed environmental state against a model known from earlier perception. Our surface based approach compares 3D range data of a built environment against an a priori scene model with the analysis of identified differences facilitating the hypothesis of causal structural changes within the scene. Experimental results show good success rates in identifying and analysing realistic structural changes introduced across example industrially themed scenes.
Polymorphic Attacks against Sequence-based Software Birthmarks

Sequence alignment algorithms have recently found a use in detecting code clones, software plagiarism, code theft, and polymorphic malware. This approach involves extracting birthmarks, in this case sequences, from programs and comparing them using sequence alignment, a procedure which has been intensively studied in the field of bioinformatics. This idea seems promising. However, we have shown that an attacker can evade detection by considering the positions of inserted dummy code and/or the frequency of function calls. Moreover, we found that randomly inserting and deleting symbols in the sequence was ineffective. By using birthmark sequences extracted from actual malicious and benign programs, we found that the most effective strategy was to use a hybrid approach incorporating “non-consecutive insertion” and “highest frequency deletion”. We also discuss the implementation costs of such attacks and propose using non-determinism through concurrent programming as an alternative evasion strategy.
Hand-Eye Coordination Predicts Joint Attention.

The present article shows that infant and dyad differences in hand-eye coordination predict dyad differences in joint attention (JA). In the study reported here, 51 toddlers ranging in age from 11 to 24 months and their parents wore head-mounted eye trackers as they played with objects together. We found that physically active toddlers aligned their looking behavior with their parent and achieved a substantial proportion of time spent jointly attending to the same object. However, JA did not arise through gaze following but rather through the coordination of gaze with manual actions on objects as both infants and parents attended to their partner's object manipulations. Moreover, dyad differences in JA were associated with dyad differences in hand following.
RNA-Seq gene expression estimation with read mapping uncertainty

Motivation: RNA-Seq is a promising new technology for accurately measuring gene expression levels. Expression estimation with RNA-Seq requires the mapping of relatively short sequencing reads to a reference genome or transcript set. Because reads are generally shorter than transcripts from which they are derived, a single read may map to multiple genes and isoforms, complicating expression analyses. Previous computational methods either discard reads that map to multiple locations or allocate them to genes heuristically. Results: We present a generative statistical model and associated inference methods that handle read mapping uncertainty in a principled manner. Through simulations parameterized by real RNA-Seq data, we show that our method is more accurate than previous methods. Our improved accuracy is the result of handling read mapping uncertainty with a statistical model and the estimation of gene expression levels as the sum of isoform expression levels. Unlike previous methods, our method is capable of modeling non-uniform read distributions. Simulations with our method indicate that a read length of 20–25 bases is optimal for gene-level expression estimation from mouse and maize RNA-Seq data when sequencing throughput is fixed. Availability: An initial C++ implementation of our method that was used for the results presented in this article is available at http://deweylab.biostat.wisc.edu/rsem. Contact: cdewey@biostat.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics on
Effect of Alloy Composition on the Atmospheric Corrosion Behavior of Steels Based on a Statistical Analysis of the Larrabee-Coburn Data Set

In 1962 C. P. Larrabee and S. K. Coburn published an extensive collection of atmospheric exposure data showing the effect of variations in copper, nickel, chromium, silicon, and phosphorus content on the corrosion resistance of low-alloy steel. Two hundred and seventy steel alloys of different composition were exposed for 15 ½ years at three separate locations representing industrial, semirural, and marine atmospheres. Among these experimental steel compositions there were five levels of copper concentration, two levels of nickel concentration, three levels of chromium concentration, three levels of silicon concentration, and three levels of phosphorus concentration represented. A statistical analysis of these data has been conducted and the results of the analysis are presented and discussed.
Simulation of Ultrasonic Stress During Impact Phase in Wire Bonding

As thermosonic ball bonding is developed for more and more advanced applications in the electronic packaging industry, the control of process stresses induced on the integrated circuits becomes more important. If Cu bonding wire is used instead of Au wire, larger ultrasonic levels are common during bonding. For advanced microchips the use of Cu based wire is risky because the ultrasonic stresses can cause chip damage. This risk needs to be managed by e.g. the use of ultrasound during the impact stage of the ball on the pad (“pre-bleed”) as it can reduce the strain hardening effect, which leads to a softer deformed ball that can be bonded with less ultrasound. To find the best profiles of ultrasound during impact, a numerical model is reported for ultrasonic bonding with capillary dynamics combined with a geometrical model describing ball deformation based on volume conservation and stress balance. This leads to an efficient procedure of ball bond modelling bypassing plasticity and contact pairs. The ultrasonic force and average stress at the bond zone are extracted from the numerical experiments for a 50 μm diameter free air ball deformed by a capillary with a hole diameter of 35 μm at the tip, a chamfer diameter of 51 μm, a chamfer angle of 90, and a face angle of 1. An upper limit of the ultrasonic amplitude during impact is derived below which the ultrasonic shear stress at the interface is not higher than 120 MPa, which can be recommended for low stress bonding.
Wongia gen. nov. (Papulosaceae, Sordariomycetes), a new generic name for two root-infecting fungi from Australia

The classification of two root-infecting fungi, Magnaporthe garrettii and M. griffinii, was examined by phylogenetic analysis of multiple gene sequences. This analysis demonstrated that M. garrettii and M. griffinii were sister species that formed a well-supported separate clade in Papulosaceae (Diaporthomycetidae, Sordariomycetes), which clusters outside of the Magnaporthales. Wongia gen. nov, is established to accommodate these two species which are not closely related to other species classified in Magnaporthe nor to other genera, including Nakataea, Magnaporthiopsis and Pyricularia, which all now contain other species once classified in Magnaporthe.
A Hardware and Thermal Analysis of DVFS in a Multi-core System with Hybrid WNoC Architecture

Evolution of CMOS manufacturing technologies has led to billions of transistors per chip, many core and System-on-Chip (SoC) realizations in current day systems. But maintaining this trend is a significant challenge due to the power and thermal issues. As the devices are scaled and number of transistors on the chip increases, the power density across the chip increases rapidly with each generation. This further results in increased system temperature that can cause damage to the system. Dynamic Voltage/Frequency Scaling (DVFS) schemes reduce the power consumption without significant loss in system performance. In this paper, we design and evaluate a centralized DVFS control mechanism for multi core systems and discuss its merits and overheads. One of the major issues with centralized controller implementation is the long delays associated with signal transmission between the controller and different clusters in the system. To alleviate this issue, we use wireless interfaces for transmitting controller signals along with the data signals. Towards this goal, we design a dual band transceiver & antenna for the wireless interfaces and present their implementation details. Finally the thermal profile of the proposed DVFS mechanism is analyzed and compared with normal operating conditions.
Optimal Decentralized Economical-sharing Scheme in Islanded AC Microgrids with Cascaded Inverters

To address the economical dispatch problem without communications in islanded AC microgrids consisting of cascaded inverters, this paper proposes an optimal decentralized economical-sharing scheme. In proposed scheme, optimal sharing function of the current is applied to generate the reference voltages. And the frequency is used to drive all distributed generators (DGs) synchronize operation in microgrids. When the microgrid is in steady state, DGs share a single common frequency and current in terms of the proposed scheme. Thus the potential advantages of simplicity and decentralized manner are retained. The AC microgrid model has been developed through simulations and experiments to verify the effectiveness and performance of the proposed scheme.
Tyrosine Phosphorylation Allows Integration of Multiple Signaling Inputs by IKKβ

Signaling regulated by NFκB and related transcription factors is centrally important to many inflammatory and autoimmune diseases, cancer, and stress responses. The kinase that directly regulates the canonical NFκB transcriptional pathway, Inhibitor of κB kinase β (IKKβ), undergoes activation by Ser phosphorylation mediated by NIK or TAK1 in response to inflammatory signals. Using titanium dioxide-based phosphopeptide enrichment (TiO2)-liquid chromatography (LC)-high mass accuracy tandem mass spectrometry (MS/MS), we analyzed IKKβ phosphorylation in human HEK293 cells expressing IKKβ and FGFR2, a Receptor tyrosine kinase (RTK) essential for embryonic differentiation and dysregulated in several cancers. We attained unusually high coverage of IKKβ, identifying an abundant site of Tyr phosphorylation at Tyr169 within the Activation Loop. The phosphomimic at this site confers a level of kinase activation and NFκB nuclear localization exceeding the iconic mutant S177E/S181E, demonstrating that RTK-mediated Tyr phosphorylation of IKKβ has the potential to directly regulate NFκB transcriptional activation.
A linearized model for control of automated polishing process

Automation of polishing process requires control of tool pressure and tool speed. Due to friction between the tool and the part, the tool speed is affected when the tool pressure is changed, and this coupling relationship is nonlinear. In this paper, a linearized model is presented for control of automated polishing process. To do so, first, the contact stress model is introduced based on a Hertzian contact model, which relates the tool pressure to the contact stress of the contact area on the part. Second, the friction torque resulting from the contact area is derived, which relates the tool pressure to the tool speed. Then, the nonlinear coupling system is linearized with respect to the control voltages of the control valves, one for pressure and another for speed. Simulations are carried out to verify the linearized model against the original nonlinear model
Layered Higher Order N-grams for Hardening Payload Based Anomaly Intrusion Detection

Application based intrusion detection involves analysis of network packet payload data. Recently statistical methods for analyzing the payload are being used. Since behavior of every application is not same a different model is necessary for each application. Studies have revealed that higher order n-grams are good for capturing the network profile. In this paper we introduce a concept of layered version of n-gram for payload based anomaly network intrusion detection. Each layer works as an independent anomaly detection system. A packet is declared as normal after passing through all the layers. A packet is declared as anomalous if at any layer it is declared as anomalous and we stop further processing the packet. We create a set of bins and equally distribute the distinct n-grams to each bin. Each such n-gram is a 2 tulle where the first element is byte values of the n-gram and second is the frequency of gram in the entire training data. We assign an anomaly score to each bin based on the frequency of the individual gram in the bin and is termed as coverage of the bin.We evaluate the proposed scheme on normal traffic of DARLA 99 dataset mixed with a set of attacks. Experimental results shows the efficacy of the method with a false alarm rate as low as 0.001\%.
Scaled free-energy based reinforcement learning for robust and efficient learning in high-dimensional state spaces

Free-energy based reinforcement learning (FERL) was proposed for learning in high-dimensional state- and action spaces, which cannot be handled by standard function approximation methods. In this study, we propose a scaled version of free-energy based reinforcement learning to achieve more robust and more efficient learning performance. The action-value function is approximated by the negative free-energy of a restricted Boltzmann machine, divided by a constant scaling factor that is related to the size of the Boltzmann machine (the square root of the number of state nodes in this study). Our first task is a digit floor gridworld task, where the states are represented by images of handwritten digits from the MNIST data set. The purpose of the task is to investigate the proposed method's ability, through the extraction of task-relevant features in the hidden layer, to cluster images of the same digit and to cluster images of different digits that corresponds to states with the same optimal action. We also test the method's robustness with respect to different exploration schedules, i.e., different settings of the initial temperature and the temperature discount rate in softmax action selection. Our second task is a robot visual navigation task, where the robot can learn its position by the different colors of the lower part of four landmarks and it can infer the correct corner goal area by the color of the upper part of the landmarks. The state space consists of binarized camera images with, at most, nine different colors, which is equal to 6642 binary states. For both tasks, the learning performance is compared with standard FERL and with function approximation where the action-value function is approximated by a two-layered feedforward neural network.