Miracle-dz/UniFAR-FTUs huggingface dataset:
An Automaton Model for Scheduling Constraints in Synchronous Machines

We present a finite-state model for scheduling constraints in digital system design. We define a two-level hierarchy of finite-state machines: a behavior FSM's input and output events are partially ordered in time; a register-transfer FSM is a traditional FSM whose inputs and outputs are totally ordered in time. Explicit modeling of scheduling constraints is useful for both high-level synthesis and verification-we can explicitly search the space of register-transfer FSM's which implement a desired schedule. State-based models for scheduling are particularly important in the design of control-dominated systems. This paper describes the BFSM I model, describes several important operations and algorithms on BFSM's and networks of communicating BFSM's, and illustrates the use of BFSM's in high-level synthesis. >
The fourth ICT-based industrial revolution "Industry 4.0" — HMI and the case of CAE/CAD innovation with EPLAN P8

Industry 4.0 transfers the principles of the Internet of Things on the processing industry. Basis for this idea forms the intelligent control unities equipped objects, which are able to communicate interconvertible and exchange self-optimized, autonomously information with other objects. These production unities are called Cyber Physical Systems (CPS). Behind the Industry 4.0 related examples of industrial robot applications also CAE/CAD application with focus on EPLAN P8, which renew the idea of value added chain, will be presented in this paper.
Generating Alignments Using Target Foresight in Attention-Based Neural Machine Translation

Abstract Neural machine translation (NMT) has shown large improvements in recent years. The currently most successful approach in this area relies on the attention mechanism, which is often interpreted as an alignment, even though it is computed without explicit knowledge of the target word. This limitation is the most likely reason that the quality of attention-based alignments is inferior to the quality of traditional alignment methods. Guided alignment training has shown that alignments are still capable of improving translation quality. In this work, we propose an extension of the attention-based NMT model that introduces target information into the attention mechanism to produce high-quality alignments. In comparison to the conventional attention-based alignments, our model halves the Aer with an absolute improvement of 19.1% Aer. Compared to GIZA++ it shows an absolute improvement of 2.0% Aer.
Dataveillance and the False-Positive Paradox

In recent times, we are witnessing an increasing concern by governments and intelligence agencies to deploy mass-surveillance systems that help them fight terrorism. In this paper, we conduct a formal analysis of the overall cost of such surveillance systems. Our analysis starts with a fairly-known result in statistics, namely, the false-positive paradox. We propose a quantitative measure of the total cost of a monitoring program, and study a detection system that is designed to minimize it, subject to a constraint in the number of terrorists the agency wishes to capture. In the absence of real, accurate behavioral models, we perform our analysis on the basis of several simple but insightful examples. With these examples, we illustrate the different parameters involved in the design of the detection system, and provide some indicative and representative figures of the cost of the monitoring program.
Recognition of ambiguous mathematical characters within mathematical expressions

Resolving ambiguity within mathematical symbols is essential for recognition of mathematical expressions. In this paper, we focus on the resolving ambiguities in mathematical symbols and propose a novel recognition technique that has been tested over large number of ambiguous mathematical symbols obtained from different categories including factoring formula, algebra identity, geometric progression, integral expressions, quadratic equations, area function, and geometric progression formulas for mathematical expressions. In this paper, we propose a novel feature extraction technique which helps in reducing the ambiguity within mathematical symbols. First, we have identified ambiguous isolated mathematical symbols from different categories of mathematical expressions. The features are extracted using feature extraction technique which includes Fourier descriptor and chain code. Two different classifiers SVM and K-NN are used for classification purpose. Fivefold cross validation technique has been used for computing recognition results. Overall recognition rate of 97.03 and 96.62% is achieved using SVM and K-NN classification respectively.
Evaluation of the IMPROVE Equation for estimating aerosol light extinction

ABSTRACT The [revised] IMPROVE Equation for estimating light extinction from aerosol chemical composition was evaluated considering new measurements at U.S. national parks. Compared with light scattering (Bsp) measured at seven IMPROVE sites with nephelometer data from 2003–2012, the [revised] IMPROVE Equation over- and underestimated Bsp in the lower and upper quintiles, respectively, of measured Bsp. Underestimation of the worst visibility cases (upper quintile) was reduced by assuming an organic mass (OM)/organic carbon (OC) ratio of 2.1 and hygroscopic growth of OM, based on results from previous field studies. This assumption, however, tended to overestimate low Bsp even more. Assuming that sulfate was present as ammonium bisulfate rather than as ammonium sulfate uniformly reduced estimated Bsp. The split-mode model of concentration- and size-dependent dry mass scattering efficiencies in the [revised] IMPROVE Equation does not eliminate systematic biases in estimated Bsp. While the new measurements of OM/OC and OM hygroscopicity should be incorporated into future iterations of the IMPROVE Equation, the problem is not well constrained due to a lack of routine measurements of sulfate neutralization and the water-soluble fraction of OM in the IMPROVE network. Implications: Studies in U.S. national parks showed that aerosol organics contain more mass and absorb more water as a function of relative humidity than is currently assumed by the IMPROVE Equation for calculating chemical light extinction. Consideration of these results could significantly shift the apportionment of light extinction to water-soluble organic aerosols and therefore better inform pollution control strategies under the U.S. Environmental Protection Agency Regional Haze Rule.
An optimal Takagi-Sugeno Fuzzy PSS for multi- machine power system

In this paper, an improved Takagi-Sugeno fuzzy logic PSS is proposed with a novel automatic design method called CDCARLA. As an optimal control system, the proposed PSS can be designed for optimizing any reasonable objective function based on any desired technical requirements. As another advantage of the proposed method, it needs no information about the dynamical model of the power system. And as a consequence, the method is able to consider all nonlinear features of the power system including hard limiters in the excitation system in the PSS design scenario. The proposed system is implemented for both single machine-infinite bus (SMIB) system and multi machine system, and the results are compared with those obtained from two IEEE standard PSS systems. Also, the controller can easily be retuned for any changes in the power system. Simulation results prove the superiority of the designed PSS in terms of both performance and robustness over the conventional PSSs.
Bank Risk: Does Size Matter?

The size of banks is examined as a determinant of bank risk. A wide range of banks are examined across four regions, including Australia, Canada, Europe and the USA. Four risk metrics are considered including Value at Risk (VaR), Conditional Value at Risk (CVaR, which measures risk beyond VaR), Probability of Default (PD) using Merton structural methodology, and Conditional Probability of Default (CPD, the author’s own model which measures risk based on extreme asset value fluctuations. Daily equity and asset value fluctuations are included in the analysis, including pre-GFC and GFC periods. In addition to examining size in isolation as a determinant of bank risk, the paper uses fixed effects panel data regression to examine the significance of size as a risk determinant in conjunction with a range of other independent variables. The study finds mixed results among the four regions with no conclusive evidence of significant association between size and risk.
Sifu: Interactive Crowd-Assisted Language Learning

This paper introduces SIFU, a system that recruits in real time native speakers as online volunteer tutors to help answer questions from Chinese language learners in reading news articles. SIFU integrates the strengths of two effective online language learning methods: reading online news and communicating with online native speakers. SIFU recruits volunteers from an online social network rather than recruits workers from Amazon Mechanical Turk.Initial experiments showed that the proposed approach is able to effectively recruit online volunteer tutors, adequately answer the learners' questions, and efficiently obtain an answer for the learner. Our field deployment illustrates that SIFU is very useful in assisting Chinese learners in reading Chinese news articles and online volunteer tutors are willing to help Chinese learners when they are on social network service.
Energy Introspector : Simulation Infrastructure for Power , Temperature , and Reliability Modeling in Manycore Processors

This paper presents an architectureindependent modeling infrastructure called the Energy Introspector for estimating non-functional aspects of processors such as energy, power, temperature, area, delay, sensor, and reliability. The Energy Introspector supports processor modeling through the integration of various modeling tools. It features structural abstraction of physical and microarchitectural components, standard library format for compatible integration of modeling tools, and synchronization of multiple phenomena models (e.g., time, power, temperature). With the Energy Introspector interface, this paper suggests an analytical processor power estimation method using the instruction-based energy profiling. The analytical power estimation is approximately 4.13 times faster than the cycle-level microarchitecture simulation approach with 2.5% of average error rate. The speed of prediction is especially important in manycore processor modeling, where the simulation time increases drastically as the number of cores increases.
Clinical response to 2 different therapeutic regimens to treat peri-implant mucositis.

BACKGROUND Maintenance of implants is imperative, since implants, like teeth, are susceptible to bacterial plaque accumulation and calculus formation, and thus at risk of developing peri-implant mucositis or peri-implantitis. METHODS This study determined the clinical effects of chlorhexidine treatment on peri-implant mucositis at 1 and 3 months as determined by the modified plaque index, the modified sulcus bleeding index, clinical attachment level, and probing depth. Through DNA probes, the effect of chlorhexidine on the microbial flora of mucositic lesions was also evaluated. The population consisted of 16 adult male and female subjects (ages 34 to 76). After the baseline examination, the subjects received a dental prophylaxis and were randomly assigned to the test or control group. Subjects in the test group received antiseptic therapy (Treatment 1), which included mechanical cleansing and oral hygiene instructions supplemented by the local irrigation with chlorhexidine 0.12%, using a plastic syringe, and the topical application of a 0.12% chlorhexidine gel. The subjects in the control group received only mechanical cleansing and oral hygiene instructions (Treatment 2). RESULTS Both modalities of treatment were effective in reducing peri-implant mucositis and probing depths, and improving attachment levels. The trends suggested that mechanical cleansing alone may be sufficient to treat and reduce peri-implant mucositis at 1 and 3 months after treatment. The addition of chlorhexidine to mechanical debridement did not enhance the results as compared to mechanical debridement alone. CONCLUSIONS Mechanical debridement as well as mechanical debridement supplemented with chlorhexidine can be beneficial to patients with peri-implant mucositis. Both treatments resulted in a reduction of plaque, inflammation, and probing depth, as well as a gain in clinical attachment level, and are effective in suppressing or eradicating the pathogenic bacteria often associated with peri-implant inflammation.
OntologyJam - A Toll for Ontology Reuse

There has been notable growth in the use of ontologies in knowledge management. This occurs because, with the use of ontologies, knowledge is shared and reuse efficiently and clearly among all the resources, such as a person or an application. However, for the ontologies to establish confidence within an extremely competitive and flexible market, they must be created in a way that is swift and has high credibility, portability and scalability. However, there is a noted lack of tools to aid knowledge specialists in the activities of construction of a new ontology. For this purpose, this article presents a tool that enables the performance of concept research in the knowledge entities represented in an ontology, through the import of multiple ontologies. As a result, knowledge can be exported into a brand new ontology. Thus, based on the knowledge reuse, with the aim of extending an ontology so as to make it adequate to its application.
Emergence of Fluoroquinolone Resistance in Mycobacterium tuberculosis during Continuously Dosed Moxifloxacin Monotherapy in a Mouse Model

ABSTRACT Fluoroquinolone resistance in tuberculosis may rapidly emerge. Mice infected with high titers of aerosolized Mycobacterium tuberculosis and treated for 8 weeks with four concentrations of moxifloxacin (0.125, 0.25, 0.50, and 1.0%) mixed into the diet had drug concentrations of 2.4, 4.1, 5.3, and 17.9 μg/ml, respectively, in blood. Selection of fluoroquinolone-resistant mutants occurred in all surviving mice.
Crystal structure of cutinase covalently inhibited by a triglyceride analogue

Cutinase from Fusarium solani is a lipolytic enzyme that hydrolyses triglycerides efficiently. All the inhibited forms of lipolytic enzymes described so far are based on the use of small organophosphate and organophosphonate inhibitors, which bear little resemblance to a natural triglyceride substrate. In this article we describe the crystal structure of cutinase covalently inhibited by (R)‐1,2‐dibutyl‐carbamoylglycero‐3‐O‐p‐nitrophenylbutyl‐phosphonate, a triglyceride analogue mimicking the first tetrahedral intermediate along the reaction pathway. The structure, which has been solved at 2.3 Å, reveals that in both the protein molecules of the asymmetric unit the inhibitor is almost completely embedded in the active site crevice. The overall shape of the inhibitor is that of a fork: the two dibutyl‐carbamoyl chains point towards the surface of the protein, whereas the butyl chain bound to the phosphorous atom is roughly perpendicular to the sn‐1 and sn‐2 chains. The sn‐3 chain is accommodated in a rather small pocket at the bottom of the active site crevice, thus providing a structural explanation for the preference of cutinase for short acyl chain substrates.
Simultaneous Inference for High-Dimensional Linear Models

ABSTRACT This article proposes a bootstrap-assisted procedure to conduct simultaneous inference for high-dimensional sparse linear models based on the recent desparsifying Lasso estimator. Our procedure allows the dimension of the parameter vector of interest to be exponentially larger than sample size, and it automatically accounts for the dependence within the desparsifying Lasso estimator. Moreover, our simultaneous testing method can be naturally coupled with the margin screening to enhance its power in sparse testing with a reduced computational cost, or with the step-down method to provide a strong control for the family-wise error rate. In theory, we prove that our simultaneous testing procedure asymptotically achieves the prespecified significance level, and enjoys certain optimality in terms of its power even when the model errors are non-Gaussian. Our general theory is also useful in studying the support recovery problem. To broaden the applicability, we further extend our main results to generalized linear models with convex loss functions. The effectiveness of our methods is demonstrated via simulation studies. Supplementary materials for this article are available online.
Patient Scenario Identifies Gaps in Breast Cancer Services in a Rural Region

Studies have demonstrated that community-based cancer coalitions can effectively address cancer disparities in rural areas. Scenario plots have been used to assess community needs in health care and public health. The social and medical context of a woman with undetected breast cancer was developed as a patient scenario implemented at a rural cancer coalition meeting to rapidly identify gaps in services. Transportation, fragmentation of cancer care, access to insurance coverage, patient navigation, and survivorship services were identified as gaps in ensuring patient compliance across the continuum of breast cancer care throughout the region. Results will be used to shape coalition priorities.
Modelling Tourism in the Galapagos Islands: An Agent-Based Model Approach

Currently tourism is the main driver of change in the Galapagos Islands, affecting the social, terrestrial, and marine sub-systems. Tourism also has direct and indirect consequences for the unique archipelagoâ€™s natural habitats and for the human well-being. Describing the mechanisms that drive and affect most the tourism development in Galapagos is a preliminary condition to developing a better understanding of the interaction structure of factors that shape the Galapagos archipelago as a social-ecological complex system. In this paper, we present a first attempt to represent the touristic market in Galapagos trough an Agent Based Model (ABM) of touristic activity, focusing on touristic offers, reservations, and touristic activities. The model is based on an individual-based representation of touristsâ€™ consumption preferences and touristic accommodation offers in the Galapagos Islands. Tourist agents are created to mimic the real world by assigning average characteristics of individuals who visit the Galapagos Archipelago of Ecuador. The accommodation offers (i.e., hotels and cruises) are generated in accordance with actual conditions derived from data collected through field surveys. The model includes a market agent that can change the prices, create and delete accommodation offers following an evolutionary algorithm. We carried out preliminary simulations that show a close agreement between real world data and model outputs. Furthermore we used the model to generate three â€œwhat ifâ€ scenarios in order to study how emergent patterns in the touristic market in Galapagos are affected by changes in the archipelago environment. In this way we illustrate how the model can be used as a useful tool to help public policy makers to explore the consequences of their decisions.
The Diagnostic Reliability of Sexual Sadism

Previous studies have reported low diagnostic agreement on the paraphilias, especially sexual sadism. In the present study, 34 evaluators throughout the United States reviewed summaries of 12 committed sex offenders. The evaluators agreed more than 90% of the time on whether offenders met criteria for any paraphilia in general and sexual sadism in particular. The authors attribute the low reliability reported in previous studies to different agreement indices, the amount and quality of information available to evaluators, and the prevalence of the respective paraphilic diagnoses in their samples.
A wireless safety detection sensor system

This paper presents a low power Wireless Safety Detection Sensor (WSDS) system to prevent fatal accidents with vehicles on construction sites. It helps providing increased safety for construction workers and eliminates back over accidents. The system employs three combined techniques which are the (1) 868 MHz radio frequency, (2) directional antennas, and (3) 40 kHz ultrasound waves. In order to secure the area behind the vehicle's rear, a sensing unit that ensures good coverage along with a wearable device for construction workers have been designed. The wearable device consists of a radio transceiver, RF wake up sensor, and an alarm actuator while the sensing unit consists of a processor, radio transceivers, directional antennas, and three ultrasound-based distance sensors. When the WSDS system detects a construction worker in a potential of a hazard, it sends the identification information to a visual display unit located in the driver's cab. At the same time, an alarm in the worker's wearable device is activated. To reserve the battery power of the wearable device, an RF wake up sensor is designed. The RF module will gain a new feature to be a hybrid (active/passive) device with a current consumption as low as 0.5 μΑ at 3 V supply.
Emotional Labor of Software Engineers

The concept of emotional labor, introduced by Hochschild in 1983, refers to the “process by which workers are expected to manage their feelings in accordance with organizationally defined rules and guidelines”. For instance, judges are expected to appear impartial, nurses—compassionate and police officers—authoritative. While software development has been traditionally stereotyped as a nerdy “lone wolf” job less likely to induce emotional labor, nowadays software developers become more and more social, on the one hand, and are subject to increasing amount of behavioral expectations, e.g., formulated as codes of conduct. In this position paper we stress that software developers are subject to emotional labor, envision how emotional labor can be identified based on emotion detection techniques applied in software engineering, suggest possible antecedents and consequents of emotional labor and discuss interventions that can be designed to address the challenges of emotional labor.
The nursing assessment of infants with bronchiolitis

Bronchiolitis is the leading cause of morbidity and hospitalization in infants under the age of one year. Supportive treatments and regular assessment remain the mainstay of care for infants admitted to hospital. Nurses play an important role in the assessment of infants with bronchiolitis; however, this is not well described in the literature and consequently little is known about what strategies nurses employ in assessing infants with bronchiolitis. The aim of this study was to explore bronchiolitis assessment in the context of nursing practice. A naturalistic inquiry study was undertaken using think aloud and retrospective probing data collection methods. The results revealed that the information gathered by nurses in their assessment of infants with bronchiolitis was varied and the process of acquiring and evaluating this information was multifaceted and holistic in nature. A close partnership between the nurse and mother was identified, and the mother’s expert knowledge and ability to identify subtle changes in the infant’s clinical condition over time was essential to the assessment process. The assessment partnership with families provides nurses with the most comprehensive and holistic view of the infant’s clinical condition and vital assessment information could be lost if this partnership does not occur.