Miracle-dz/UniFAR-FTUs huggingface dataset:
Biomedical event trigger identification based on the bidirectional gated recurrent unit network

Biomedical Events, which widely exist in biomedical literature, describe dynamical biological progress. Biomedical Event extraction plays a significant role in biomedical research, including biomedical event graph construction, medicine research and base construction. Event Trigger Identification, the very first step of event extraction, is to extract the words or phrases, usually verbs or verb groups, that trigger events from sentences or whole articles. Recently, in biomedical event extraction, the main approach to this task is based on traditional Machine Learning. However, this method relies heavily on human effort and expert experience. It can be very time-consuming. Thus, a more efficient method is needed in terms of decreasing labor and time costs. In this paper, we deal with the problem mentioned above to identify the biomedical event triggers in a new way by utilizing a deep learning-based model. Specifically, we use a Bidirectional Gated Recurrent Unit (Bi-GRU) network, an external version of the original Recurrent Neural Network (RNN), to encode the context, and a linear layer is used to classify the entities and predict the triggers. Finally, a test on the Multiple Level Event Extraction (MLEE) corpus gives a satisfying result (F1-score of around 78%).
A STUDY ON THE APPROACHES OF DEVELOPING A NAMED ENTITY RECOGNITION TOOL

Named entity recognition (NER) is of vital importance in information extraction in natural language processing. Identifying the named entities in a piece of text and classifying them with proper tagging can help in getting a lot of information engraved in the particular text. The following paper presents brief details about the various approaches in developing a NER. Also an overview of the various models and learning methodologies used for the statistical approach is also provided. The various factors that need to be considered in developing this tool are also stated.
Validation of single-step genomic predictions using the linear regression method for milk yield and heat tolerance in a Thai-Holstein population

Abstract Background and Aim: Genomic selection improves accuracy and decreases the generation interval, increasing the selection response. This study was conducted to assess the benefits of using single-step genomic best linear unbiased prediction (ssGBLUP) for genomic evaluations of milk yield and heat tolerance in Thai-Holstein cows and to test the value of old phenotypic data to maintain the accuracy of predictions. Materials and Methods: The dataset included 104,150 milk yield records collected from 1999 to 2018 from 15,380 cows. The pedigree contained 33,799 animals born between 1944 and 2016, of which 882 were genotyped. Analyses were performed with and without genomic information using ssGBLUP and BLUP, respectively. Statistics for bias, dispersion, the ratio of accuracies, and the accuracy of estimated breeding values were calculated using the linear regression (LR) method. A partial dataset excluded the phenotypes of the last generation, and 66 bulls were identified as validation individuals. Results: Bias was considerable for BLUP (0.44) but negligible (−0.04) for ssGBLUP; dispersion was similar for both techniques (0.84 vs. 1.06 for BLUP and ssGBLUP, respectively). The ratio of accuracies was 0.33 for BLUP and 0.97 for ssGBLUP, indicating more stable predictions for ssGBLUP. The accuracy of predictions was 0.18 for BLUP and 0.36 for ssGBLUP. Excluding the first 10 years of phenotypic data (i.e., 1999-2008) decreased the accuracy to 0.09 for BLUP and 0.32 for ssGBLUP. Genomic information doubled the accuracy and increased the persistence of genomic estimated breeding values when old phenotypes were removed. Conclusion: The LR method is useful for estimating accuracies and bias in complex models. When the population size is small, old data are useful, and even a small amount of genomic information can substantially improve the accuracy. The effect of heat stress on first parity milk yield is small.
Successful business systems engineering. II. The time compression paradigm and how simulation supports good BSE

Part 1 of this article (see ibid., February 1997) argued that business systems engineering (BSE) is no more, and no less, than achieving a high standard of `engineering the business process', linking customer need to customer satisfaction by careful total process analysis, design and implementation to enable a win-win scenario. In this second part, the importance of the time compression paradigm as a leveraging tool within BSE is highlighted. The role of simulation as a means whereby both tactical and `big picture' BSE proposals may be evaluated prior to implementation is described. The article concludes with some typical industrial results and a checklist to help ensure that BSE ideas are properly implemented.
The nature of speech and its interpretation

VARIOUS phases of this subject have received serious study by phoneticians, otologists, and physicists. On account of its universal interest, it has received attention from men in many branches of science. In spite of the large amount of time devoted to the subject, the progress in understanding its fundamental aspects has been rather slow. At the present time the physical properties which differentiate the various fundamental speech sounds are understood in only a very fragmentary way. Some very interesting and painstaking work has been done on the physical analysis of vowel sounds, but the results to date are far from conclusive. Although several theories have been advanced to explain the way in which the ear interprets sound waves, they are still in the controversial stage.
Rheumatoid arthritis with nontuberculous mycobacterial pulmonary disease: a retrospective, single-centre cohort study.

OBJECTIVES Nontuberculous mycobacterial pulmonary disease (NTM-PD) is a rare but important comorbidity of rheumatoid arthritis (RA). Our objective was to investigate the association between NTM-PD and RA, especially regarding the immunosuppressive treatment of RA such as biological disease-modifying antirheumatic drugs (bDMARDs). METHODS We conducted a retrospective, single-centre cohort study. All RA patients regularly followed up at our rheumatology division in December 2012 were included in the study, and followed for 5 years. RESULTS At baseline, 26 of 1639 RA patients had NTM-PD. During the observation period, 14 were newly diagnosed with NTM-PD. For new diagnosis of NTM-PD, bDMARD use at baseline was not a significant risk factor. Among the 40 patients with NTM-PD, 16 were treated with a total of 27 bDMARDs after NTM-PD diagnosis. They did not present with a greater exacerbation of NTM-PD than those not treated with bDMARDs (25 vs. 17%, p = .52). A total of 55 patients died, but nobody died of NTM-PD. NTM-PD was not associated with worse mortality in multivariate analysis (hazard ratio, 2.0; 95% CI, 0.6-6.4; p = .26). CONCLUSIONS Biological DMARD was not associated with worse prognosis of NTM-PD. Careful use of bDMARDs could be tolerated in RA patients with NTM-PD.
Prediction of ESD robustness in a process using 2D device simulations

The use of 2D device simulations in predicting the ESD robustness of MOS devices is discussed. The merits of using the peak power density, JE, and the second breakdown trigger current, I/sub t2/, as a measure of the relative robustness of MOS devices with varying drain/source profiles, contact to gate spacing, and gate bias conditions, is studied. It is shown that the peak JE correlates with the peak temperature in the device, but it is strongly influenced by variations in the grid. Hence, its applicability is limited to comparing the relative robustness of devices with simulations where the grid does not change drastically. I/sub t2/ is less sensitive to grid variations and is more widely applicable for analyzing the effect of technology variations on ESD robustness. <<ETX>>
Ultrahigh frequency DC-to-DC converters using GaAs power switches

A detailed investigation of the switching characteristics for high frequency power devices based on different technologies has been provided: BJT, MOSFET, and MESFET/HEMT structures are considered. Advantages of GaAs power switches over silicon ones have been established and illustrated. Hybrid technology prototypes of DC-to-DC power converters operating above 10 MHz and exclusively using GaAs components have been realized: for a nonoptimized boost converter operating at 100 MHz, a power efficiency of 54% has been achieved with a 6 V/12 V conversion ratio and an output power of 1.5 W. For optimized prototypes, using high frequency assembly techniques, an efficiency of 80% at 50 MHz, 74% at 100 MHz and 60% at 250 MHz have been obtained with 6 V/12 V and 3 W.
MONOS memory element

The use of metal-nitride-oxide-semiconductor structure as a storage element was reported by Szedon at the 1967 Device Research Conference. When such a structure is used as p-channel enhancement mode device, a positive gate voltage exceeding a certain critical value changes the device into depletion mode. Later when a negative gate voltage of the order of this critical voltage is applied, the device changes back to enhancement mode. This phenomenon has been explained as electron tunneling from the semiconductor through the oxide into the traps in the nitride with a positive gate bias, and from traps into the semiconductor with negative gate bias. This can be used as a nonvolatile memory element.
Feedback control of HIV antiviral therapy with long measurement time

In this presentation we apply a receding horizon observer to an HIV feedback control problem in order to derive optimal treatments of HIV pro- gression and/or optimal structured treatment interruptions (STI) in antiviral therapy that include drug-free periods of immune-mediated control of HIV. We use a nonlinear differential equation model which has been well-validated with clinical patient data and shown to have reliable predictive capabilities. The basic feedback control problem utilizes a tracking formulation (desired states for viral load and immune effector calculated from a healthy steady state for the model are tracked). Here we assume only very realistic observerables of CD4+ T cell count and viral load. Moreover, we use a second deterministic optimal tracking problem for state estimation as opposed to stochastic filtering approaches. In both of the optimization problems (for optimal feedback control and for state estimator) conjugate gradient algorithms are employed.
Faculty Perceptions of Academe's Evaluation System

This study examined faculty views of the academe's reward system. The study sought to investigate faculty perceptions of the current evaluation system and “how it should be. ” Five hundred six engineering faculty at seven universities responded to a questionnaire regarding the methods used to evaluate teaching, the amount of emphasis placed on research, service and teaching and the flexibility of the present system. The results indicate that faculty perceive discrepancies between the current system and what they prefer. They tend to favor a more flexible system that rewards not only research but also teaching and service activities. Open‐ended comments focused on including broader measures of research activities in the evaluation process and improving the quality of teaching. It is hoped that these findings can serve as a model for many institutions considering changes in the faculty reward system.
Effects of Step Uncertainty on Impact Peaks, Shock Attenuation, and Knee/Subtalar Synchrony in Treadmill Running

The purpose of this research was to determine the effects of step uncertainty on shock attenuation and knee/subtalar synchrony. Uncertainty was manipulated by decreasing the intensity of light and introducing bumps to the running surface. Twelve experienced distance runners ran at their chosen pace on a treadmill with two surfaces (smooth and irregular) and three light intensities (light, medium, dark). Knee angle, subtalar angle, leg impacts, and head impacts were recorded at 1,000 Hz. Heart rate was also monitored. Injury potential was assessed by evaluating the impacts and asynchronous activity between the knee and subtalar joint. Stride length was not influenced by either source of uncertainty. Heart rate increased with the intensity of light on the smooth running surface but decreased with the intensity of light on the irregular surface. The knee was more flexed at heel contact during the irregular surface conditions but was not affected by the intensity of light. This decreased the effective mass of.
The use of third-party logistics services by European industry

Logistics managers in Europe's leading manufacturing and commercial organisations were surveyed regarding their use of third-party logistics (TPL) services. Their responses provide insights into the depth and scope of logistics outsourcing in Europe. Areas specifically addressed in the European survey include; services being used, related implementation problems, the benefits that have emerged and the impact of third-party services on costs, customer satisfaction and employees. The results indicate that logistics outsourcing, at least for basic services, has become well established in Europe. Emphasis on logistics cost reduction, service improvement and flexibility of response are at the centre of most logistics outsourcing decisions. On the downside there is a mixed response on employee morale associated with outsourcing.
Iron deficiency is an independent risk factor of increased myocardial energy expenditure in chronic heart failure patients.

BACKGROUND Chronic heart failure (CHF) is a major public health burden and is associated with high morbidity, mortality, and cost. Recent studies demonstrated iron metabolism and myocardial energy metabolism were altered in CHF patients. In this study, we aimed to analyze the effects and correlations of iron metabolism on myocardial energy metabolism in CHF. METHODS One hundred and thirty patients with CHF [age: 66.2±11.5 years, males: 58.5% and New York Heart Association (NYHA) class (II/III/IV): 67/43/20] were included. Serum concentrations of ferritin, transferrin saturation (Tsat), and soluble transferrin receptor (sTfR) were quantified as the indexes of iron metabolism, and echocardiography was used to assess myocardial energy expenditure (MEE) levels. Iron deficiency (ID) was defined as ferritin <100 or 100-300 µg/L with Tsat <20%. RESULTS Patients with CHF were divided into two groups based on iron status. The prevalence of ID in CHF was 36.9%, and increased with the severity of CHF, reaching 80.0% in those with NYHA class IV (NYHA class II/III/IV: 17.9% vs. 46.5% vs. 80.0%, P=0.000). The demographic characteristics [age, sex, body mass index (BMI), blood pressure, and heart rate] and hemoglobin (HGB) concentrations in two groups were similar (all P>0.05). MEE was significantly higher in the ID group (92.7±23.0 vs. 65.6±20.8 cal/min, P=0.000), while NYHA classes II and III was significantly higher in the ID group (71.6±16.4 vs. 60.3±14.8 cal/min, P=0.022; 88.9±10.4 vs. 69.1±20.1 cal/min, P=0.000). In univariable linear regression models, the presence of ID, higher NYHA class, increased N-terminal pro-B-type natriuretic peptide (NT-proBNP), sTfR, left ventricular internal diastolic diameter (LVIDd), as well as reduced ferritin, Tsat levels, and lower left ventricular ejection fraction (LVEF) were associated with elevated MEE levels (all P<0.05). In multivariable regression models, the presence of ID, reduced Tsat. and increased sTfR remained independent predictors of elevated MEE levels after adjustment for all variables that showed a significant association with MEE (all P<0.05). CONCLUSIONS The prevalence of ID is high in CHF and is associated with the severity of cardiac dysfunction. The presence of ID as well as reduced Tsat and increased sTfR concentrations are associated with elevated MEE levels in CHF.
Mobility and orientation aid for blind persons using artificial vision

Blind or vision-impaired persons are limited in their normal life activities. Mobility and orientation of blind persons is an ever-present research subject because no total solution has yet been reached for these activities that pose certain risks for the affected persons. The current work presents the design and development of a device conceived on capturing environment information through stereoscopic vision. The images captured by a couple of video cameras are transferred and processed by configurable and sequential FPGA and DSP devices that issue action signals to a tactile feedback system. Optimal processing algorithms are implemented to perform this feedback in real time. The components selected permit portability; that is, to readily get used to wearing the device.
Analisis Pengaruh Metode Over Sampling dalam Churn Prediction untuk Perusahaan Telekomunikasi

Churn prediction adalah suatu cara untuk memprediksi pelanggan yang berpotensial untuk churn. Data mining, khususnya klasifikasi tampaknya dapat menjadi salah satu alternatif solusi dalam membuat model churn prediction yang akurat. Namun hasil klasifikasi menjadi tidak akurat disebabkan karena data churn bersifat imbalance. Kelas data menjadi tidak stabil karena data akan lebih condong ke bagian data yang memiliki komposisi data yang lebih besar. Salah satu cara untuk menangani permasalahan ini adalah dengan memodifikasi dataset yang digunakan atau yang lebih dikenal dengan metode oversampling. Analisis yang dilakukan pada penelitian ini adalah mengetahui bagaimana pengaruh metode oversampling yang digunakan terhadap akurasi prediksi data churn dengan melakukan penghitungan akurasi model churn prediction yang dinyatakan dalam bentuk lift curve, top decile dan gini coefficient serta f-measure untuk penghitungan akurasi prediksi data sebagai data yang imbalance. Hasil yang didapat dari penelitian menunjukkan bahwa metode oversampling yang menghasilkan data synthetic belum sesuai diterapkan pada data churn, karena cenderung masih menghasilkan nilai top decile yang kecil. Tetapi secara umum metode oversampling ini mampu meningkatkan akurasi untuk memprediksi data minor. Dengan penerapan metode oversampling, data churn yang memiliki tingkat imbalance yang besar dapat diklasifikasi tanpa mengorbankan data minor yang menjadi fokus penelitian. Metode oversampling yang digunakan juga memiliki hasil evaluasi yang berbeda terhadap dataset sebagai data churn dan sebagai data imbalance. Kata kunci: churn prediction, imbalance, sampling, akurasi, evaluasi.
Airport Taxiway Head-On Conflict Prediction and Avoidance in A-SMGCS

The closed loop control architecture based on event feedback was proposed for airport taxiway head-on conflict prediction and avoidance in A-SMGCS (Advanced Surface Movement Guidance and Control System). Firstly, resource-oriented controlled colored Petri net was proposed and used to model taxiway operation process. Secondly, the controlled taxiing segment concept was proposed, and rules for generating corresponding sub-model were provided. And then, using cycles and cycle chains contained in the sub-model, the sufficient and necessary condition for head-on conflict-free operation of taxiway was provided. The corresponding avoidance control strategies and algorithm for head-on conflict control were proposed. Finally, the example demonstrated the effectiveness of the proposed algorithm.
Associations between adverse childhood experiences and need and unmet need for care coordination

Introduction Children exposed to adverse childhood experiences (ACEs) may access multiple systems of care to address medical and social complexities. Care coordination (CC) optimizes health outcomes for children with special health care needs who often use multiple systems of care. Little is known about whether ACEs are associated with the need and unmet need for CC. Methods Use of the 2016–2017 National Survey of Children’s Health to identify children who saw ≥1 health care provider in the last 12 months. The study team used weighted logistic regression analyses to examine associations between 9 ACE types, ACE score, and need and unmet need for CC. Results In the sample (N = 39,219, representing 38,316,004 US children), material hardship (adjusted odds ratio (aOR), 1.50; 95% confidence interval (CI), 1.29–1.75), parental mental illness (aOR, 1.31; 95% CI, 1.07–1.60), and neighborhood violence (aOR, 1.33; 95% CI, 1.01–1.74) were significantly associated with an increased need for CC. Material hardship was also associated with an unmet need for CC (aOR, 2.37; 95% CI, 1.80–3.11). Children with ACE scores of 1, 2, 3, and ≥4 had higher odds of need and unmet need for CC than children with 0 ACEs. Discussion Specific ACE types and higher ACE scores were associated with the need and unmet need for CC. Evaluating the unique needs of children who endured ACEs should be considered in the design and implementation of CC processes in the pediatric health care system.
Planar wideband crossover with distortionless response using dual‐mode microstrip patch

A microwave crossover using a dual‐mode microstrip patch is presented. The patch is designed to operate at two orthogonal modes. Each of those modes is used to couple a pair of face‐to‐face ports. The isolation between the two orthogonal modes is enhanced by using symmetrical slits in the microstrip patch. The proposed crossover has the main features of high‐power handling capability and distortionless response due to its extremely low group delay deviation. A prototype is designed to operate at the WLAN band from 5.15 to 5.85 GHz. The simulated and measured results indicate less than 0.06 ns deviation in the group delay, less than 1 dB insertion loss, more than 13 dB return loss and more than 12 dB isolation across the whole band. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:2077–2079, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27028
Wind Turbine Operation Condition Identification Method Based on Variable Optimization Selection and Machine Learning

Effective identification of the operation condition of wind turbines is of great significance to the evaluation of wind turbine power generation performance and the fine management of wind farms. Due to the complex and diverse factors affecting wind turbine operation condition, it is very important to select the appropriate variable set to improve the identification accuracy of wind turbine operation condition. Therefore, a wind turbine operation condition identification method based on variable optimization selection and machine learning is proposed; then, taking the optimal variables under normal operation conditions as input and power as output, the normal behavior model of wind turbines based on BP double hidden layer neural network is constructed; finally, the combined method of DBSCAN clustering algorithm and probability confidence interval is used for residual analysis to realize effective identification of different operation conditions of wind turbines. The results show that the proposed method can deeply dig out the key influencing variables of the wind turbine operation condition, realize the effective identification of the healthy, sub-healthy and abnormal operation conditions, and conform to the actual operation conditions of the wind turbine.
Stochastic segmentation on images with uncertain data

The present work considers a stochastic segmentation method on images in the presence of noise within a PDE‐based image processing framework. Classical methods are not able to capture the error propagation of uncertain estimated input data and their impact on the final segmentation result, which can be of great importance for clinical decisions. Therefore, an intrusive generalized polynomial chaos (gPC) expansion for a stochastic level‐set based geodesic active contours method is proposed. Employing an operator splitting and a stochastic Galerkin projection a deterministic and symmetric non‐linear hyperbolic system can be obtained, which can be treated using common numerical methods.