Miracle-dz/UniFAR-FTUs huggingface dataset:
An Instruction Throughput Model of Superscalar Processors

In this paper we describe the methodology and architectureof a flexible modular environment for prototypingdata transmission systems and its application on xDSL systems.The development environment is based on custom andcommercially available software tools and a custom hardwareemulation platform for mapping the basic data-pumpmodules of xDSL systems into hardware/software functionalmodules. The road-map from a high-level xDSL systemmodel to the actual prototype is based on the progressivesubstitution of high-level submodules of the initial modelwith their respective hardware/software counterparts, andtheir integration into a complete functional system. A libraryof custom blocks is used for data exchange and synchronizationbetween the high-level model and the emulationplatform, and for real-time visualization of the criticalparameters of the emulated system as well. The applicationof the proposed development environment in the implementationand testing of an emulator of a bundle of DSL linesand of a centralized bit-loading algorithm for multicarrierADSL systems is also described.
Integration of Proteomics and Metabolomics Revealed Metabolite–Protein Networks in ACTH-Secreting Pituitary Adenoma

An effective treatment for the management of adrenocorticotropic hormone-secreting pituitary adenomas (ACTH-PA) is currently lacking, although surgery is a treatment option. We have integrated information obtained at the metabolomic and proteomic levels to identify critical networks and signaling pathways that may play important roles in the metabolic regulation of ACTH-PA and therefore hopefully represent potential therapeutic targets. Six ACTH-PAs and seven normal pituitary glands were investigated via gas chromatography-mass spectrometry (GC-MS) analysis for metabolomics. Five ACTH-PAs and five normal pituitary glands were subjected to proteomics analysis via nano liquid chromatography tandem-mass spectrometry (nanoLC-MS/MS). The joint pathway analysis and network analysis was performed using MetaboAnalyst 3.0. software. There were significant differences of metabolites and protein expression levels between the ACTH-PAs and normal pituitary glands. A proteomic analysis identified 417 differentially expressed proteins that were significantly enriched in the Myc signaling pathway. The protein–metabolite joint pathway analysis showed that differentially expressed proteins and metabolites were significantly enriched in glycolysis/gluconeogenesis, pyruvate metabolism, citrate cycle (TCA cycle), and the fatty acid metabolism pathway in ACTH-PA. The protein–metabolite molecular interaction network identified from the metabolomics and proteomics investigation resulted in four subnetworks. Ten nodes in subnetwork 1 were the most significantly enriched in cell amino acid metabolism and pyrimidine nucleotide metabolism. Additionally, the metabolite–gene–disease interaction network established nine subnetworks. Ninety-two nodes in subnetwork 1 were the most significantly enriched in carboxylic acid metabolism and organic acid metabolism. The present study clarified the pathway networks that function in ACTH-PA. Our results demonstrated the presence of downregulated glycolysis and fatty acid synthesis in this tumor type. We also revealed that the Myc signaling pathway significantly participated in the metabolic changes and tumorigenesis of ACTH-PA. This data may provide biomarkers for ACTH-PA diagnosis and monitoring, and could also lead to the development of novel strategies for treating pituitary adenomas.
Constructing Early Childhood Science

Preface, Acknowledgments, To the Student, Chapter 1: Constructing Goals for Early Childhood Science Education. Chapter 2: The Basic Scientific Processes: Observing. Chapter 3: The Basic Scientific Processes: Classifying. Chapter 4: The Basic Scientific Processes: Communicating. Chapter 5: The Basic Scientific Processes: Measuring. Chapter 6: The Basic Scientific Processes: Predicting. Chapter 7: The Basic Scientific processes: Inferring. Chapter 8: The Process-Oriented Objective. Chapter 9: The Integrated Scientific Processes: Identifying and Controlling Variables. Chapter 10: The Integrated Scientific Processes: Formulating and Testing Hypotheses. Chapter 11: The Integrated Scientific Processes: Defining Operationally. Chapter 12: The Integrated Scientific Processes: Interpreting Data. Chapter 13: The Integrated Scientific Processes: Experimenting. Chapter 14: The Integrated scientific Processes: Constructing Models. Chapter 15: Constructivism. Chapter 16: Process-Oriented Inquiry. Chapter 17: Learner Differences. Chapter 18: Assessment. Chapter 19: The Early Childhood Science Education Classroom. Chapter 20: Science Beyond the Classroom. Chapter 21: Technology in Early Childhood Science Education. Chapter 22: Reading, Writing, and Science. Chapter 23: Interdisciplinary Integration. Chapter 24: The Early Childhood Science Education Professional. Appendix 1: Selected Sources of Free and Inexpensive Materials. Appendix 2: Materials for a well-Equipped Early Childhood Science Classroom. Appendix 3: Activities Cross-Referenced to content standards of the National Science Education Standards. Appendix 4: Listing of Children"s Literature Cited.
An implementation programme to improve nursing home staff's knowledge of and adherence to an individualized music protocol

Aim. This paper reports the results of a study evaluating an implementation programme in improving nursing home staff’s knowledge of and adherence to an individualized music protocol for older people with dementia. Background. The major barriers to evidence-based practice identified by nurses are the lack of knowledge and skills on implementing evidence-based practice. Some evidence supports the effectiveness of implementation strategies in facilitating practice change among healthcare professionals but need further testing. Little is known about what is the best way to facilitate nursing home staff’s adoption of evidence-based care. Methods. A one-group pre-post test design was used with a convenience sample of 17 nursing staff from a long-term care facility. The implementation programme consisted of interactive education, reminders, a local opinion leader and audit. Data on nursing staff’s knowledge of music protocol were collected by the music knowledge questionnaire and their adherence to the protocol was assessed by an audit checklist at baseline and week four after the implementation programme. Results. There was a significant improvement in nursing staff’s knowledge (p 0AE05). The mean level of their adherence to the protocol improved from nil at baseline to 72AE35% on the post-test. Conclusions. An innovative implementation programme consisting of interactive education, reminders, use of a local opinion leader and audit led to an improvement in nursing home staff’s knowledge of and adherence to an individualized music protocol in dementia care. Relevance to clinical practice. Multifaceted implementation strategies with careful consideration of local circumstances may be essential in promoting uptake of evidence-based practice among nursing staff in long-term care settings.
Developing a Portfolio Assessment Model for the Teaching and Learning of English in Malaysian L2 Classroom.

Standardized testing is viewed as particularly incompatible to the process of learning due to its summative nature as it measures what students are able to recall and produce. Because of the discrepancy between the process of learning and products of learning, educators today have come to recognize that an alternative form of assessment is required to complement the existing form of assessment. This study intends to determine the techniques ESL teachers use in implementing portfolio as an assessment tool. The techniques ESL teachers employed while implementing the assessment process in the classroom enabled the researchers to propose a model for portfolio assessment. Currently, ESL teachers in Malaysia do not have a specific model or technique to conduct the portfolio assessment process because portfolio is heard of but not widely used. Therefore, this study was carried to scrutinize procedures ESL teachers use as a guide in instructional planning and student evaluation based on their teaching in the L2 classroom. The participants were nine ESL secondary school teachers in Malaysia. Semi-structured interviews, classroom observations and teachers’ individual portfolios were utilized to explore the techniques which served as a guideline for ESL teachers employed for the teaching and learning in the classroom. Findings indicate that the portfolio assessment model developed has provided ESL teachers the opportunity to document individual student’s growth. Furthermore, the teachers divulged that teaching is sustained when teaching materials, teaching techniques and assessment techniques were upgraded to help students in achieving the learning outcomes. The results of the study have implications for assessment, teaching and learning of English as a second language.
RSA Problem for Varying Traffic in Flexible Optical Networks

Abstract The problem of service time-varying traffic in flexible transparent optical networks, assuming that the incoming connections and their duration are not known in advance, is considered in this work. Time-varying traffic requires dynamic spectrum allocation for connections implemented in the network. In the considered problem, a path with the required spectrum around the reference frequency is determined for each incoming connection by the routing algorithm. In order to take into account the dynamic spectrum allocation for the connections in the network, two spectrum expansion/- contraction schemes have been applied on the basis of which the average blocking probability for the incoming request additional slot was determined.
Students’ perception towards task - based language teaching (TBLT) approach in learning Arabic language: CFS,IIUM experience

Task-Based Language Teaching (TBLT) is a new approach in teaching second language particularly in Arabic language. The approach, which employs student-centred approach, is viewed as more effective than the traditional way. This approach is slowly gaining its popularity among Arabic language educators and learners all around the world. In Malaysia, the Centre for Foundation Studies, International Islamic University Malaysia (CFSIIUM) is one of the first institutions of education to implement this new way in teaching Arabic language. As such, this study was conducted in order to find out the students’ perception towards the implementation of task-based language teaching (TBLT) in this learning institution. 313 respondents were randomly selected from the students in Arabic elementary level studying at CFSIIUM. The instrument used in the survey was survey questionnaires. The quantitative results were used to examine students’ perception towards the implementation of task-based language teaching (TBLT) in Arabic language. The findings indicated that the respondents were positive in learning Arabic language using this approach and they were motivated to learn this language.
Pediatric pedicle screw (In)accuracy based on postoperative computed tomography

Abstract Though pedicle screws are widely used in spinal stabilization, studies evaluating the variables affecting placement accuracy and effects of accuracy on outcome are limited. Using computed tomography (CT), we evaluated the accuracy of pedicle screw placement in pediatric and transitional patient populations. We evaluated screw placement in a series of 276 thoracic, lumbar, and sacral pedicle screws implanted in 41 patients with the assistance of fluoroscopy by a single surgeon at a single institution from September 1, 2007 to December 31, 2012. Postoperative CT was performed and each screw was graded based on relation to neurologic, osseous, and intra thoracic and intra-abdominal landmarks by an independent neuro radiologist: Grade I, entirely intra pedicular; Grade II, violates lateral pedicle but screw tip entirely within the vertebral body; Grade III, tip penetrates the anterior or lateral vertebral body; Grade IV, breaches medial or inferior pedicle; and Grade V, violates pedicle or vertebral body and threatens spinal cord, nerve root, or great vessels, requires immediate revision or removal. The accuracy rate (Grades I and II) was lower than expected (76.8%). Screw misplacements (Grades III, IV, and V) were numerous (23.2%), although the overall complication rate remained low. There was no statistically significant difference in pedicle screw accuracy as a function of surgeon experience, patient age, or patient diagnosis. This suggests the need for advanced intraoperative imaging, such as neuronavigation or CT, to aid placement of spinal instrumentation in the pediatric and transitional patient population. While postoperative CT should be considered gold standard for evaluating pedicle screw placement, further study is warranted to evaluate overall accuracy and assess the need for more extensive intraoperative imaging to improve accuracy.
Effectiveness of Mirror Therapy in Recovery of Functional Movement after Stroke

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The Informative g-Prior vs. Common Reference Priors for Binomial Regression With an Application to Hurricane Electrical Utility Asset Damage Prediction

Eliciting appropriate prior information from experts for a statistical model is no easy task. Expressing this information in terms of hyperparameters of prior distributions on abstract model parameters can be nearly impossible, especially after data augmentation or transformation. In previous work on logistic and binomial regression models, Hanson et al. (2014) assert that ``experts are confident only in their assessment of the population as a whole'' and propose a version of the g-prior which effectively places a standard beta distributed prior on the overall population probability of success. We explore the efficacy of using the informed g-prior in a real prediction problem involving electrical utility asset damages due to hurricanes in Connecticut. Prior information is elicited from a group of engineers at the electrical utility and several methods are used to select hyper-parameters for the g-prior. The out-of-sample predictive accuracy of these informed models is compared to the performance of models constructed under common reference priors (Jeffreys's, Gelman et al. (2008), and a noninformative specification of the g-prior) using IS-LOO (Vehtari et al., 2014; Vehtari and Gelman, 2014), root mean squared error (RMSE), and other statistics. In this application, with carefully selected hyper-parameters, binomial regression models using the informed g-prior match the predictive accuracy of common reference priors and offer no distinct advantage. Careless selection of hyper-parameters can however, lead to substantial reduction in predictive accuracy. Surprisingly, the noninformative specification of the g-prior performed marginally better than all other models tested in this paper; contradicting one of the findings in Hanson et V al. (2014) In addition, we show the predictive accuracy gained by modeling spatial correlation in the residuals and prove that such models substantially outperform some statistical learning models growing in popularity in this field.
Use of the shared frailty model to identify the determinants of child mortality in Rwanda

According to United Nations Development Programme report, achieving the 4th Millennium Development Goal(MDG) means that Rwanda will have to reduce under-five mortality from 196 to 47 deaths per 1000 live births between 2000 and 2015, UNDP(2003). Even though Rwanda had made very considerable progress in improving child survival during 5 years preceding the 2005 RDHS, all the achievements only brought the country indicators around to those of 1990’s, that is before the ravaging 1994 Genocide against Tutsi. Controlling for the effects of unobserved risk factors that would interfere with child mortality, this study aims to identify and rank order the most important factors that contributed to child survival in Rwanda between 2000 and 2005 based on the 2005 RDHS data. The key determinants would be prioritized in order to avoid an eventual misallocation of scarce resources. The analysis of relevant data showed that frailty effects were significant in childhood with child deaths mostly determined by socioeconomic and demographic factors such as household socioeconomic status being the most important. Key words: child mortality, Cox regression, unobserved heterogeneity, shared frailty.
Interruption of people in human-computer interaction

Just because something is new and clever does not necessarily mean that it is good. The utility of a technology must be evaluated strictly in terms of whether it actually helps people succeed. A new technology that is useful for isolated tasks may carry an invisible and costly side-EFFECT. For example, the side-effect of human interruption by machine only manifests itself in real world contexts where people normally perform several complex heterogeneous tasks in parallel. The telephone and email are examples. They are useful by themselves, but in a real work environment they also create annoying interruptions. A newer and more problematic example is the technology of semi-autonomous computer systems such as intelligent agents. These systems can be assigned to do useful things in the background while their human users work on other tasks. However, when an intelligent agent must initiate an interaction with its user it has to first interrupt them from whatever else they are doing. Interruption of people during human-computer interaction (HCI) is problematic because people have cognitive limitations that restrict their ability to work during interruptions. These limitations can cause people to make critical, even life-threatening mistakes when interrupted. Unfortunately, no user interface design guidelines exist for directing solutions to this problem. In fact, no general theoretical tools exist for facilitating basic interdisciplinary investigations of this problem. This dissertation creates two fundamental interdisciplinary theoretical tools for addressing this problem: (1) a Definition of Human Interruption; and (2) a Taxonomy of Human Interruption. These tools are synthesized from the results of a comprehensive analysis of the existing literature of several relevant fields. The utility of these new tools was partially validated by demonstrations of their usefulness. First, the taxonomy was used to structure a discussion of existing literature from several different disciplines relevant to the design of user interfaces for the human interruption problem. Second, the taxonomy was used to guide an experiment with 36 human subjects. The taxonomy guided the creation of a theory-based hypothesis about how to coordinate human interruption during HCI. The results conclusively supported the hypothesis.
Penyebab kesulitan belajar geometri dimensi tiga

Penelitian ini bertujuan untuk menyelidiki faktor-faktor yang menyebabkan kesulitan mahasiswa STKIP BBG dalam mempelajari geometri dimensi tiga. Penelitian ini menggunakan metode penelitian kualitatif studi kasus untuk mengkaji proses pembelajaran mahasiswa calon guru matematika di lingkungan STKIP BBG. Subjek dalam penelitian ini adalah 16 orang mahasiswa calon guru matematika STKIP BBG Semester II-IV Tahun Akademik 2016/2017 yang dipilih secara purposive sampling. Pengumpulan data dilakukan dengan menggunakan tehnik angket, tes, dan wawancara. Hasil penelitian menunjukkan bahwa kedua faktor internal dan ekternal memberi pengaruh terhadap kesulitan belajar yang dialami oleh mahasiswa pendidikan matematika STKIP BBG. Faktor internal sebagai penyebab kesulitan adalah faktor minat, bakat dan intelegensi mahasiswa yang memiliki persentase lebih dari 50% tergolong rendah dan sangat rendah. Adapun faktor ekternal, diantaranya adalah aspek penggunaan metode mengajar oleh dosen dimana, penyampaian materi oleh dosen tanpa menyesuaikan kemampuan mahasiswa memiliki peran yang tinggi (68.75%) dalam memunculkan kesulitan terhadap penguasaan konsep-konsep geometri dimensi tiga. Selain itu, pengalaman belajar geometri pada jenjang sekolah sebelumnya juga menjadi faktor lain yang mengakibatkan kesulitan belajar geometri dalam penelitian ini. The cause of difficulty in learning the three-dimensional geometry Abstract This study aims to investigate the factors that cause STKIP BBG’s prospective teachers difficulties in learning three-dimensional geometry. This research uses a case study qualitative research method to assess student learning process of prospective mathematics teachers in mathematics department at STKIP BBG. Subjects in this study were 16 prospective mathematics teachers in semester II - IV academic year 2016/2017 at STKIP BBG. The subjects were selected by purposive sampling. Data collection was done by using questionnaire technique, tests and interviews. The results showed that both internal and external factors had given effects toward learning difficulties experienced by mathematics education students at STKIP BBG. The internal factors are which suspected as the difficulty’s cause are the interest factor; talent and intelligence where 50% of prospective mathematics teachers are in low and very low level. Meanwhile, the external factors, such as the use of teaching methods by lecturers where, the delivery of materials by lecturers without adjusting the ability of students have a high role (68.75%) in raising difficulties on the mastery of three-dimensional geometry concepts. In addition, the experience of learning geometry at the previous school level is also another factor that leads to difficulties in learning geometry in this study.
Deep Convolutional Neural Networks and Learning ECG Features for Screening Paroxysmal Atrial Fibrillation Patients

In this paper, a novel computationally intelligent-based electrocardiogram (ECG) signal classification methodology using a deep learning (DL) machine is developed. The focus is on patient screening and identifying patients with paroxysmal atrial fibrillation (PAF), which represents a life threatening cardiac arrhythmia. The proposed approach operates with a large volume of raw ECG time-series data as inputs to a deep convolutional neural networks (CNN). It autonomously learns representative and key features of the PAF to be used by a classification module. The features are therefore learned directly from the large time domain ECG signals by using a CNN with one fully connected layer. The learned features can effectively replace the traditional ad hoc and time-consuming user’s hand-crafted features. Our experimental results verify and validate the effectiveness and capabilities of the learned features for PAF patient screening. The main advantages of our proposed approach are to simplify the feature extraction process corresponding to different cardiac arrhythmias and to remove the need for using a human expert to define appropriate and critical features working with a large time-series data set. The extensive simulations and case studies conducted indicate that combining the learned features with other classifiers will significantly improve the performance of the patient screening system as compared to an end-to-end CNN classifier. The effectiveness and capabilities of our proposed ECG DL classification machine is demonstrated and quantitative comparisons with several conventional machine learning classifiers are also provided.