Miracle-dz/UniFAR-FTUs huggingface dataset:
Using evoked EMG as a synthetic force sensor of isometric electrically stimulated muscle

A method for the estimation of the force generated by electrically stimulated muscle during isometric contraction is developed here. It is based upon measurements of the evoked electromyogram (EMG) [EEMG] signal. Muscle stimulation is provided to the quadriceps muscle of a paralyzed human subject using percutaneous intramuscular electrodes, and EEMG signals are collected using surface electrodes. Through the use of novel signal acquisition and processing techniques, as well, as a mathematical model that reflects both the excitation and activation phenomena involved in isometric muscle force generation, accurate prediction of stimulated muscle forces is obtained for large time horizons. This approach yields synthetic muscle force estimates for both unfatigued and fatigued states of the stimulated muscle. In addition, a method is developed that accomplishes automatic recalibration of the model to account for day-to-day changes in pickup electrode mounting as well as other factors contributing to EEMG gain variations. It is demonstrated that the use of the measured EEMG as the input to a predictive model of muscle torque generation is superior to the use of the electrical stimulation signal as the model input. This is because the measured EEMG signal captures all of the neural excitation, whereas stimulation-to-torque models only reflect that portion of the neural excitation that results directly from stimulation. The time-varying properties of the excitation process cannot be captured by existing stimulation-to-torque models, but they are tracked by the EEMG-to-torque models that are developed here. This work represents a promising approach to the real-time estimation of stimulated muscle force in functional neuromuscular stimulation applications.
Decision Support for Team Building: Incorporating Trust into a Recommender-Based Approach

In this paper we present a novel automated recommendation approach to support the selection of individuals to teams. Recent organizational trends show an increasing importance of team-based work structures and more and more companies use this team-focused structure with the hope to increase organizational effectiveness. Whereas traditional selection systems are focused on finding a match between job requirements and individuals’ abilities, these systems need to be changed in order to reflect the enhanced requirements when selecting individuals to work in teams. This is important as teamwork requires interaction among its members and not just co-action. Our approach is therefore based on two dimensions. First, people need to be matched to jobs for which they possess the right knowledge, skills and abilities to fulfill all tasks. Second, people need to fit with the other people they are supposed to work with in terms of interpersonal compatibility. Based on an adapted probabilistic latent aspect model and a trust computational model we present a first prototype aiming to support the systematic selection of individuals to form effective teams.
Genome-wide identification and characterization of GRAS transcription factors in tomato (Solanum lycopersicum)

Solanum lycopersicum, belonging to Solanaceae, is one of the commonly used model plants. The GRAS genes are transcriptional regulators, which play a significant role in plant growth and development, and the functions of several GRAS genes have been recognized, such as, axillary shoot meristem formation, radial root patterning, phytohormones (gibberellins) signal transduction, light signaling, and abiotic/biotic stress; however, only a few of these were identified and functionally characterized. In this study, a gene family was analyzed comprehensively with respect to phylogeny, gene structure, chromosomal localization, and expression pattern; the 54 GRAS members were screened from tomato by bioinformatics for the first time. The GRAS genes among tomato, Arabidopsis, rice, and grapevine were rebuilt to form a phylogenomic tree, which was divided into ten groups according to the previous classification of Arabidopsis and rice. A multiple sequence alignment exhibited the typical GRAS domain and conserved motifs similar to other gene families. Both the segmental and tandem duplications contributed significantly to the expansion and evolution of the GRAS gene family in tomato; the expression patterns across a variety of tissues and biotic conditions revealed potentially different functions of GRAS genes in tomato development and stress responses. Altogether, this study provides valuable information and robust candidate genes for future functional analysis for improving the resistance of tomato growth.
Quantitative molecular detection of minimal residual head and neck cancer in lymph node aspirates.

PURPOSE Staging of the clinically N(0) neck in patients with head and neck squamous cell carcinoma (HNSCC) using ultrasound-guided, fine needle aspiration cytology (USgFNAC) has a false-negative rate of approximately 20% that might be caused by inaccurate cytology. Molecular analysis of aspirate residues might reduce the false-negative rate, and we therefore set up a quantitative reverse transcription-PCR (Q-RT-PCR) assay based on TaqMan technology using the squamous cell-specific antigen E48 (Ly-6D) as molecular marker. EXPERIMENTAL DESIGN The detection limit of the assay was determined in reconstruction experiments. The sensitivity of the assay was tested on cytological tumor-positive aspirate residues and the specificity on lymph node aspirate residues of noncancer controls. Subsequently, 235 lymph node aspirate residues of 64 HNSCC patients staged with USgFNAC were examined for the presence of E48 mRNA. E48 Q-RT-PCR results of the aspirated lymph nodes were compared with cytology and clinical outcome. RESULTS The detection limit of E48 Q-RT-PCR was a single tumor cell in a background of 10(6) peripheral blood mononuclear cells. From the 41 aspirates that were not evaluable at cytology, 24 (59%) could be diagnosed with E48 Q-RT-PCR. In the 191 aspirates that were tumor negative or not evaluable at cytology, 8 samples from 6 patients were E48 positive. These results were confirmed by histology or clinical outcome in 3 of 6 patients. E48 Q-RT-PCR showed an increase in sensitivity from 56 to 67% and an increase in frequency of reached diagnosis from 97 to 100% compared with cytology. The specificity decreased from 100 to 92%. CONCLUSIONS Real-time E48 Q-RT-PCR is an accurate technique for squamous cell detection in lymph node aspirates of HNSCC patients. The assay shows an increase in sensitivity and frequency of reached diagnosis compared with cytology. The test could be implemented routinely in USgFNAC to diagnose cases for which cytological examination is not conclusive.
Nutrient Availability Alters the Effect of Autophagy on Sulindac Sulfide-Induced Colon Cancer Cell Apoptosis

Autophagy is a catabolic process by which a cell degrades its intracellular materials to replenish itself. Induction of autophagy under various cellular stress stimuli can lead to either cell survival or cell death via apoptotic and/or autophagic (nonapoptotic) pathways. The NSAID sulindac sulfide induces apoptosis in colon cancer cells. Here, we show that inhibition of autophagy under serum-deprived conditions resulted in significant reductions of sulindac sulfide-induced apoptosis in HT-29 colon cancer cells. In contrast, inhibition of autophagy under conditions where serum is available significantly increased sulindac sulfide-induced apoptosis in HT-29 cells. We previously showed that the apoptosis inhibitor, survivin, plays a role in regulating NSAID-induced apoptosis and autophagic cell death. Here, we show that survivin protein half-life is increased in the presence of autophagy inhibitors under serum-deprived conditions, but not under conditions when serum is available. Thus, the increased levels of survivin may be a factor contributing to inhibition of sulindac sulfide-induced apoptosis under serum-deprived conditions. These results suggest that whether a cell lives or dies due to autophagy induction depends on the balance of factors that regulate both autophagic and apoptotic processes.
Power estimation for mobile applications with profile-driven battery traces

It becomes very important to understand power characteristics of mobile applications because more and more complex applications are running on modern smartphones. Although many techniques have been proposed to estimate the power dissipation rate for mobile applications, it typically requires hardware support (i.e., power meters) or complex power models (software profiling or hardware parameters). These techniques might work well in labs with a small set of applications. However, it becomes impractical when we try to estimate the power of mobile applications in an uncontrolled environment. This paper proposes a novel method for estimating the power consumption of mobile applications with profile-based battery traces. Battery traces can be easily collected through a user-level application on any devices. Although it is difficult to achieve accurate results for only a few users because battery changes are coarse-grained, the method is expected to reach an accurate estimation when the number of battery traces reaches a certain scale. Our experiments based on battery traces from more than 80,000 users demonstrate that it is possible to estimate application power with only coarse-grained battery traces. The results are also validated with measured power numbers from a Monsoon power monitor.
Mycoplasma synoviae infection on Newcastle disease vaccination of chickens

Newcastle disease is characterized by respiratory manifestations in association with nervous and/or digestive symptoms. Its prevention is done by vaccination with live attenuated (lentogenic strains) and/or killed vaccines. The lentogenic strains can lead to strong post-vaccination reaction, principally due to the presence of other pathogenic agents. Among them, Mycoplasma synoviae is worldwide important, mainly in Brazil. The dissemination of this agent in poultry flocks has been achieved due to difficulties in diagnosis and disease reproduction, virulence variations among different M.synoviae strains, and attribution of typical M.synoviae disease manifestation to other disease agents. This experimental study in SPF chicks (Gallus gallus), previously infected by M.synoviae and thereafter vaccinated against Newcastle disease, was done with the objective of evaluating M.synoviae pathogenicity through assessment of post-vaccinal respiratory reactions and serologic responses to Newcastle disease virus vaccine in the absence of environmental factors. A total of 86 three days old chicks were used, being 57 infected by eye and nostril drop, with chicken activated M. synoviae strain WVU 1853. Seven days later, 21 mycoplasma infected birds plus 29 not mycoplasma infected ones were vaccinated against Newcastle disease. As results, the not infected and vaccinated birds yielded, significantly, higher and longer lasting serologic responses to Newcastle disease vaccine virus than those infected and vaccinated. Similarly, the infected and vaccinated birds yielded lower serologic reactions to M.synoviae than those only mycoplasma infected. No post-vaccinal respiratory reaction was observed in the vaccinated birds.
Control system plant simulator: A Framework for hardware-in-the-loop simulation

Control systems courses are common in undergraduate engineering programs. These courses focus on the design of the controller’s mathematical model but rarely have students explore the practical issues of implementing the controller. Real-time and embedded systems courses focus on these practical issues with students implementing controllers for simplified Hardware-in-theLoop plants such as a digital servo motor. Designing controllers for complex physical plants is difficult due to prohibitive costs or the risk of accidents caused by faulty controllers. These difficulties can be overcome if a simulator replaces the hardware-in-the-loop physical plant. We designed and implemented the Control System Plant Simulator (CSPS) as a flexible framework for simulating plant models in control system implementation projects. The framework allows the user to model continuous and discrete plants defined as transfer functions or systems of state-space equations. This paper describes the design of the CSPS framework by highlighting the expansion and modification flexibility it provides with its operating system, non-real-time user interface, and physical device abstraction layers. The CSPS framework has advantages over commercial tools that can provide a hardware-in-the-loop plant simulation. The framework’s scope of usage is much narrower than the commercial tools making it easier to learn how to use and modify. Also, we distribute the framework as an open-source project making it readily available for use in any course without licensing, and ensuring that deeper and more complex customizations are possible. The paper concludes with a discussion of our successful experience using the framework in real-time systems course projects, and porting to two operating environments (standard Windows XP and Ardence RTX Real-Time Extensions for Windows), two user interfaces (C-based text, Visual Basic GUI), and two data acquisition devices (USB data acquisition, simulated multi-channel IO device).
Multilingual Code-switching Identification via LSTM Recurrent Neural Networks

This paper describes the HHU-UH-G system submitted to the EMNLP 2016 Second Work-shop on Computational Approaches to Code Switching. Our system ranked ﬁrst place for Arabic (MSA-Egyptian) with an F1-score of 0.83 and second place for Spanish-English with an F1-score of 0.90. The HHU-UH-G system introduces a novel uniﬁed neural network architecture for language identiﬁcation in code-switched tweets for both Spanish-English and MSA-Egyptian dialect. The sys-tem makes use of word and character level representations to identify code-switching. For the MSA-Egyptian dialect the system does not rely on any kind of language-speciﬁc knowledge or linguistic resources such as, Part Of Speech (POS) taggers, morphological analyzers, gazetteers or word lists to obtain state-of-the-art performance.
The WebNLG Challenge: Generating Text from DBPedia Data

With the emergence of the linked data initiative and the rapid development of RDF (Resource Description Format) datasets, several approaches have recently been proposed for generating text from RDF data (Sun and Mellish, 2006; Duma and Klein, 2013; Bontcheva and Wilks, 2004; Cimiano et al., 2013; Lebret et al., 2016). To support the evaluation and comparison of such systems, we propose a shared task on generating text from DBPedia data. The training data will consist of Data/Text pairs where the data is a set of triples extracted from DBPedia and the text is a verbalisation of these triples. In essence, the task consists in mapping data to text. Specific subtasks include sentence segmentation (how to chunk the input data into sentences), lexicalisation (of the DBPedia properties), aggregation (how to avoid repetitions) and surface realisation (how to build a syntactically correct and natural sounding text).
Many-core GPU computing with NVIDIA CUDA

In the past, graphics processors were special-purpose hardwired application accelerators, suitable only for conventional graphics applications. Modern GPUs are fully programmable, massively parallel floating point processors. In this talk I will describe NVIDIA's scalable, highly parallel many-core GPU architecture and how CUDA software for GPU computing delivers high throughput for data-intensive processing. I will discuss how CUDA is reinvigorating research on data-parallel algorithms, reducing time to scientific discovery, and enabling a variety of compute-intensive industrial applications of GPUs beyond computer graphics.
A Corpus of Clinical Practice Guidelines Annotated with the Importance of Recommendations

In this paper we present the Corpus of REcommendation STrength (CREST), a collection of HTML-formatted clinical guidelines annotated with the location of recommendations. Recommendations are labelled with an author-provided indicator of their strength of importance. As data was drawn from many disparate authors, we define a unified scheme of importance labels, and provide a mapping for each guideline. We demonstrate the utility of the corpus and its annotations in some initial measurements investigating the type of language constructions associated with strong and weak recommendations, and experiments into promising features for recommendation classification, both with respect to strong and weak labels, and to all labels of the unified scheme. An error analysis indicates that, while there is a strong relationship between lexical choices and strength labels, there can be substantial variance in the choices made by different authors.
Simultaneous position, velocity, attitude, angular rates, and surface parameter estimation using astrometric and photometric observations

Astrometric and photometric data fusion for the purposes of simultaneous position, velocity, attitude, and angular rate estimation has been demonstrated in the past. This state estimation is extended to include the various surface parameters associated with the bidirectional reflectance distribution function (BRDF). Additionally, a physically consistent BRDF and radiation pressure model is utilized thus enabling an accurate physical link between the observed photometric brightness and the attitudinal dynamics and ultimately the orbital dynamics. An example scenario is then presented where the model is an uncontrolled High Area to Mass Ratio (HAMR) object in geosynchronous Earth orbit and the position, velocity, attitude, angular rates, and surface parameters are estimated simultaneously.
The Best of Both Worlds: Big Data Programming with Both Productivity and Performance

Coarse-grained operators such as map and reduce have been widely used for large-scale data processing. While they are easy to master, over-simplified APIs sometimes hinder programmers from fine-grained control on how computation is performed and hence designing more efficient algorithms. On the other hand, resorting to domain-specific languages (DSLs) is also not a practical solution, since programmers may need to learn how to use many systems that can be very different from each other, and the use of low-level tools may even result in bug-prone programming. In [7] our prior work, we proposed Husky which provides a highly expressive API to solve the above dilemma. It allows developers to program in a variety of patterns, such as MapReduce, GAS, vertex-centric programs, and even asynchronous machine learning. While the Husky C++ engine provides great performance, in this demo proposal we introduce PyHusky and ScHusky, which allow users (e.g., data scientists) without system knowledge and low-level programming skills to leverage the performance of Husky and build high-level applications with ease using Python and Scala.
A Wireless Mesh Network-based System for Hotspots Deployment and Management

In recent years Wireless Local Area Networks (WLANs) or hotspots, as they are commonly known, have emerged as a promising networking platform to extend network connectivity in public venues, providing local coverage for Internet applications on the move in urban areas and rural environments. Wireless hotspots using 802.11-based technology have popped up in corporate offices, coffeehouses, airports, restaurants and bookstores worldwide. For all their utility and ease of use the 802.11 wireless protocol, known as WiFi, has become the mobile connectivity mechanism of choice for business people, travelers, villagers, and everyone else. Unfortunately, even with the protocol's ease of use and its accessibility, there are still technical challenges to be solved toward an ubiquitous connectivity using WiFi hotspots. In this paper we present an experimental wireless system which extends beyond the hotspot's capabilities to provides wireless connectivity at distant areas and at a low cost. The system, combines the promising paradigm of Wireless Mesh Networks with the Captive Portal technology to offer a wide range of Internet-based communication services and applications. We detail the system architecture overseeing its main components and implementation details. Finally, we present some experiments in term of context services and traffic modeling, and demonstrate that the developed system can be easily deployed in term of coverage, management, and offered services.
Levels of Processing in Parent-Child Relationships : Implications for Clinical Assessment and Treatment

shed new light on the nature of parent-child relationships and their potential contribution to child and adolescent psychopathology. Researchers have linked insecure states of mind in the Adult Attachment Interview to increased risk for a variety of symptoms in adults (Dozier, Stovall, & Albus, 1999) while patterns of insecure parent-infant attachment have been associated with increased risk for child and adolescent psychopathology (Greenberg, 1999). Despite, the progress in understanding the relation between attachment and psychopathology, research findings have had several notable limitations for clinicians working with children and their parents.
A novel OFDM-based MAC protocol for wireless LANs

Conventional 802.11 networks perform contention and data transmission serially over the whole channel. This leads to low throughput efficiency. In this paper, we propose a novel CSMA/CQ (carrier sense multiple access/contention queuing) to improve the throughput efficiency. In CSMA/CQ, each node performs contention and data transmission concurrently over two separate subchannels, where a contention queue is introduced to coordinate the concurrency. CSMA/CQ inherits the conventional distributed coordination mechanism on contention, and adopts a centralized control idea on data transmission without requiring strict time synchronization. As a result, CSMA/CQ can achieve far higher throughput than conventional 802.11 networks. Extensive simulations verify that the efficiency of CSMA/CQ.
Earning points for moral behavior: organ allocation based on reciprocity.

Anticipating the reevaluation of the Dutch organ procurement system, in late 2003 the Rathenau Institute published a study entitled 'Gift or Contribution? ' In this study, the author, Govert den Hartogh, carries out a thorough moral analysis of the problem of organ shortage and fair allocation of organs. He suggests there should be a change in mentality whereby organ donation is no longer viewed in terms of charity and the volunteer spirit, but rather in terms of duty and reciprocity. The procurement and allocation of donor organs should be seen as a system of mutually assured help. Fair allocation would imply to give priority to those who recognize and comply with their duty: the registered donors. The idea of viewing organ donation as an undertaking involving mutual benefit rather than as a matter of charity, however, is not new. Notwithstanding the fact that reference to charity and altruism is not required in order for the organ donation to be of moral significance, we will argue against the reciprocity-based scenario. Steering organ allocation towards those who are themselves willing to donate organs is both an ineffective and morally questionable means of attempting to counter organ shortage.