Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between blood pressure during haemodialysis and ambulatory blood pressure in between dialyses.

BACKGROUND Ambulatory blood pressure measurements in haemodialysis patients are relevant in view of the high cardiovascular morbidity and mortality in chronic haemodialysis patients. METHODS Twelve normotensive patients were studied from the beginning of one dialysis until the end of the next (mean 64 h, SD 19 h) using a Spacelabs oscillometric blood-pressure recorder. RESULTS A circadian blood pressure rhythm was present in six of the 12 patients. In seven patients the lowest pressure recorded (including the dialysis sessions) occurred 5-6 h after dialysis (late post-dialysis dip). Blood pressure did not increase sharply in the hours before dialysis although it increased slightly in the interdialytic interval as a whole, at a mean rate of 5.6 mmHg per 24 h (SD 4.1, P < 0.001). We could not find a blood pressure measurement during dialysis (or combination of measurements) which reliably reflects interdialytic blood pressure: the 95% confidence intervals were 25 mmHg or higher. CONCLUSION Ambulatory blood pressure measurements are needed for adequate monitoring of the control of blood pressure in haemodialysis patients.
The satisficing principle in capability learning

Whether an organization has a certain capability is often a matter of degree. Thus, in the context of initial learning of a capability, there is generally no clear‐cut or automatic answer to the question of when an organization should be expected to cut back its learning efforts and affirm that the desired capability has been achieved. This paper offers a simple conceptual model for this question, based on the satisficing principle. More specifically, the question addressed is: ‘When does overt learning stop? ’—where ‘overt’ learning is understood as being marked by observable allocation of attention and resources to the task of acquiring the capability. The model provides the framework for a discussion of various influences on the aspiration level in the satisficing model, and hence on the nature of the capability that has been achieved when learning stops. Overt learning efforts may be resumed at some time later if external factors operate to lift aspiration levels relevant to the capability. The paper discusses how such ‘re‐ignition’ of learning may occur as a result of an organizational crisis, or of the institution of a quality management program. Copyright © 2000 John Wiley & Sons, Ltd.
Addressing the RRAM Reliability and Radiation Soft-Errors in the Memory Systems

With the continuous and aggressive technology scaling, the design of memory systems becomes very challenging. The desire to have high-capacity, reliable, and energy efficient memory arrays is rising rapidly. However, from the technology side, the increasing leakage power and the restrictions resulting from the manufacturing limitations complicate the design of memory systems. In addition to this, with the new machine learning applications, which require tremendous amount of mathematical operations to be completed in a timely manner, the interest in neuromorphic systems has increased in recent years. Emerging NonVolatile Memory (NVM) devices have been suggested to be incorporated in the design of memory arrays due to their small size and their ability to reduce leakage power since they can retain their data even in the absence of power supply. Compared to other novel NVM devices, the Resistive Random Access Memory (RRAM) device has many advantages including its low-programming requirements, the large ratio between its high and low resistive states, and its compatibility with the Complementary Metal Oxide Semiconductor (CMOS) fabrication process. RRAM device suffers from other disadvantages including the instability in its switching dynamics and its sensitivity to process variations. Yet, one of the popular issues hindering the deployment of RRAM arrays in products are the RRAM reliability and radiation soft-errors. The RRAM reliability softerrors result from the diffusion of oxygen vacations out of the conductive channels within the oxide material of the device. On the other hand, the radiation soft-errors are caused by the highly energetic cosmic rays incident on the junction of the MOS device used as a selector for the RRAM cell. Both of those soft-errors cause the unintentional change of the resistive state of the RRAM device. While there is research work in literature to address some of the RRAM disadvantages such as the switching dynamic instability, there is no dedicated work discussing the impact of RRAM soft-errors on the various designs to which the RRAM device is integrated and how the soft-errors can be automatically detected and fixed. In this thesis, we bring the attention to the need of considering the RRAM soft-errors to avoid the degradation in design performance. In addition to this, using previously reported SPICE models, which were experimentally verified, and widely adapted system level simulators and test benches, various solutions are provided to automatically detect and fix the degradation in design performance due to the RRAM soft-errors. The main focus in this work is to propose methodologies which solve or improve the robustness of memory systems to the RRAM soft-errors. These memories are expected to be incorporated in the current and futuristic platforms running the advanced machine learning applications. In more details, the main contributions of this thesis can be summarized as:
Venous Thromboembolism in COVID-19 Compared to Non-COVID-19 Cohorts: A Systematic Review with Meta-Analysis

Background: A high incidence of venous thromboembolism (VTE) is reported in hospitalized COVID-19 patients, in particular in patients admitted to the intensive care unit (ICU). In patients with respiratory tract infections, including influenza A (H1N1), many studies have demonstrated an increased incidence of thromboses, but evidence is lacking regarding the risk difference (RD) of the occurrence of VTE between COVID-19 and non-COVID-19 patients. Methods: In this systematic review with meta-analysis, we evaluated the RD of the occurrence of VTE, pulmonary embolism (PE), and deep venous thrombosis (DVT) between COVID-19 and other pulmonary infection cohorts, in particular H1N1, and in an ICU setting. We searched for all studies comparing COVID-19 vs. non-COVID-19 regarding VTE, PE, and DVT. Results: The systematic review included 12 studies and 1,013,495 patients. The RD for VTE in COVID-19 compared to non-COVID-19 patients was 0.06 (95% CI 0.11–0.25, p = 0.011, I2 = 97%), and 0.16 in ICU (95% CI 0.045–0.27, p = 0.006, I2 = 80%). The RD for PE between COVID-19 and non-COVID-19 patients was 0.03 (95% CI, 0.006–0.045, p = 0.01, I2 = 89%). The RD for PE between COVID-19 and non-COVID-19 patients was 0.021 in retrospective studies (95% CI 0.00–0.04, p = 0.048, I2 = 92%) and 0.11 in ICU studies (95% CI 0.06–0.16, p < 0.001, I2 = 0%). Conclusions: The growing awareness and understanding of a massive inflammatory response combined with a hypercoagulable state that predisposes patients to thrombosis in COVID-19, in particular in the ICU, may contribute to a more appropriate strategy of prevention and earlier detection of the thrombotic events.
Exoskeleton Technology: State-of-the-art and -practice of Physical and Cognitive Human Robot Interface

Exoskeletons and orthoses are wearable mobile systems providing mechanical benefits to the users. Despite significant improvements in the last decades, the technology is not fully mature to be adopted for strenuous and non-programmed tasks. To accommodate this insufficiency, different aspects of this technology need to be analysed and improved. Numerous studies have been trying to address some aspects of exoskeletons, e.g. mechanism design, intent prediction, and control scheme. However, most works have focused on a specific element of design or application without providing a comprehensive review framework. This study aims to analyse and survey the contributing aspects to the improvement and broad adoption of this technology. To address this, after introducing assistive devices and exoskeletons, the main design criteria will be investigated from a physical Human-Robot Interface (HRI) perspective. The study will be further developed by outlining several examples of known assistive devices in different categories. In order to establish an intelligent HRI strategy and enabling intuitive control for users, cognitive HRI will be investigated. Various approaches to this strategy will be reviewed, and a model for intent prediction will be proposed. This model is utilised to predict the gate phase from a single Electromyography (EMG) channel input. The outcomes of modelling show the potential use of single-channel input in low-power assistive devices. Furthermore, the proposed model can provide redundancy in devices with a complex control strategy.
A Methodology to Categorize Rapidly Changing Projects of Open Source Software

The number and types of Open Source Software (OSS) are increasing year by year. The information technology (IT) industry uses OSS and utilize intellectual properties and human resources across organizational boundaries. In present OSS expands across industry boundaries and is used in more industries such as the energy industry, automotive industry, medical industry. In addition, some of OSS have been developed with new concepts. Some OSS organizations such as the Linux Foundation, the Cloud Native Computing Foundation and the Japan OSS Promotion Forum provide categories, but contributors in them are also time-consuming to provide the latest information. Meanwhile, it is inconvenient for every Open Source Program Offices (OSPO), which oversees open source software management and strategy, to update manual OSS categorization frequently. Thus, OSPOs want to get a universal methodology to restructure OSS categories. This research provides the current categories of OSS and its methodology in order to build a consistent strategy. This methodology aims to be a methodology to support in the standardization of OSS categorization.
Measuring Cohesion of Software Systems Using Weighted Directed Complex Networks

Network theory has been demonstrated as an effective approach for better understanding and analysis of software systems from a systematic perspective. In this paper, we develop a directed and weighted software dependency network model to analyse software systems from a complex network perspective. In particular, to measure the "High Cohesion and Low Coupling" nature of object-oriented software systems, we propose to use a directed and weighted modularity index, which can better reflect the cohesion of software systems. Experiments are conducted on a series of open source object-oriented software systems with various scales, and the results show that the directed and weighted modularity can better characterize software systems with different cohesion.
picoTrans: A User Interface Using Content Word-based Source Sentence Generation for Machine Translation

This is the abstract of the IUI paper (Song et al., to appear in 2011). Our proposal combines statistical machine translation with the idea of a picture-based translation-aid (Graf, 2009; Meader, 1995; Warrink, 2007; Stillman, 2007; Flanagan, 2008). Picturebased translation-aids have been used in paper book forms and are currently integrated into hand-held devices but remain uncombined with machine translation systems. Briefly, in our proposed system picoTrans, the user taps picture icons appearing on the touch-screen, just like in a picture-based translationaid. The system automatically generates the possible sentences from those selected icons, and feeds them to the machine translation in order that it can display the translated result. For example, suppose a user wished to translate the expression ‘I want to go to the restaurant. ’, with the picture book, the user might point at 2 pictures: ‘I want to to go to ∼’, and ‘restaurant’. A similar scenario for our system is that the user points to a sequence of icons, however, in our case the sequence of icons is maintained on the display for the users to see, and interact with if necessary. When the input is complete, the system generates the full sentence in the source language automatically, which is then translated by the machine translation software and displayed on the screen together with the icon sequence.
Pre-service teachers’ preparedness to use ICT: A Western Australian perspective

VII TABLE OF CONTENTS . IX LIST OF TABLES . XVII LIST OF FIGURES . XIX LIST OF ABBREVIATIONS . XXIII DEFINITION OF TERMS . XXV Chapter One: Introduction . 1 Overview . 1 Background of the study . 2 Teacher education in Australia . 2 Teacher Education institutions in Western Australia . 4 Significance . 6 Research questions . 8 Structure of the thesis . 8 Chapter Two: Literature review . 11 Introduction . 11 ICT: Terms and definitions . 12 ICT application in education . 13 General introduction . 13 Barriers of integrating ICT into education . 15 First order (external) barriers . 17 Second order (internal) barriers . 18 ICT application in school education . 20
The Secret Code of Japanese Candlesticks

Acknowledgements. Introduction. 1. The Truth about Japanese Candlesticks. 2. The Spirit of Sokyu Honma's Method: The Master and the Disciple. 3. The Samni No Den of the Market: The Subjective Part of the Method. 4. The Five Sakata Methods: The Objective Part of the Method. 5. Trading with Sokyu Honma's Method. 6. Japanese Candlesticks: A Precision Tool Within the Market's Great Cycle. 7. Algorithm in Tabular Format for the Five Sakata Methods Within Sokyu Honma's Great Cycle. 8. Thirty-seven Applications Involving Indexes, Stocks, and Futures. 9. Back to the Samni No den. 10. Learning to Analyze the Markets from a Trader's Viewpoint. 11. Your Magic Talisman. 12. Before Taking a Position.Think! 13. How to Exit a Trade. 14. How to Manage Your Risk. 15. All You Will Ever Need to Know about Stops. 16. Putting It All Together in a Simple but Winning Approach. 17. Trade Now! 18. Some Thoughts about Trading Philosophy. Conclusion. Appendix. What Is a Candlestick? Notes. Bibliography. Index.
Applied Medical Code Mapping with Character-based Deep Learning Models and Word-based Logic

Logical Observation Identifiers Names and Codes (LOINC) is a standard set of codes that enable clinicians to communicate about medical tests. Laboratories depend on LOINC to identify what tests a doctor orders for a patient. However, clinicians often use site specific, custom codes in their medical records systems that can include shorthand, spelling mistakes, and invented acronyms. Software solutions must map from these custom codes to the LOINC standard to support data interoperability. A key challenge is that LOINC is comprised of six elements. Mapping requires not only extracting those elements, but also combining them according to LOINC logic. We found that character-based deep learning excels at extracting LOINC elements while logic based methods are more effective for combining those elements into complete LOINC values. In this paper, we present an ensemble of machine learning and logic that is currently used in several medical facilities to map from
Meta-analysis of the Effect of Imperfect Alert Automation on System Performance

What performance level must automation reach to be a net benefit to the user? This paper presents a meta-analysis of 34 data points taken from 12 studies in the human factors literature, each representing the effect of an imperfect automation aid on system performance, relative to baseline. Bayesian regression analysis indicated a consistent relationship between automation reliability (i.e., overall percent correct) and performance, with values greater than 67% associated with performance gains. The credible interval for this crossover point ranged from 55 to 75%. There was also a consistent effect of d’, with a crossover point of 1.47 and a credible interval from -0.04 to 2.22. However, we urge caution in using these values as a benchmark criterion, due to the sizeable uncertainty in the crossover estimates and the variability in how researchers compute false alarm and reliability rates. The question “How good is good enough? ” likely does not have a single domain-general answer, with the automation performance threshold varying across task domains and other variables.
A duality between fuzzy domains and strongly completely distributive $L$-ordered sets

The aim of this paper is to establish a fuzzy version of the dualitybetween domains and completely distributive lattices. All values aretaken in a fixed frame $L$. A definition of (strongly) completelydistributive $L$-ordered sets is introduced. The main result inthis paper is that the category of fuzzy domains is dually equivalentto the category of strongly completely distributive $L$-orderedsets. The results in this paper establish close connections amongfuzzy-set approach of quantitative domains and fuzzy topology withmodified $L$-sober spaces and spatial $L$-frames as links. Inaddition, some mistakes in [K.R. Wagner, Liminf convergence in$Omega$-categories, Theoretical Computer Science 184 (1997)61--104] are pointed out.
Sublinear Cost Low Rank Approximation Directed by Leverage Scores

Low rank approximation (hereafter LRA) of a matrix is a major subject of matrix and tensor computations and data mining and analysis. In applications to Big Data it is desired to solve the problem at sublinear cost, that is, by involving much fewer memory cells and arithmetic operations than an input matrix has entries. Unfortunately any sublinear cost algorithm, deterministic or randomized, fails to compute accurate LRA for the worst case input and even for a small matrix families of our Appendix. This makes quite surprising our novel randomized algorithm that at sublinear cost refines a crude but reasonably close LRA. Furthermore, in contrast to the above observation, we prove that sublinear cost variations of some known algorithms compute close LRA of a large subclass of all matrices that admit LRA. In a sense they do this for most of such matrices because, as we proved, with a high probability the algorithms compute accurate LRA of a random matrix that admits LRA.
THE FORM AND FUNCTION OF METAL‐CONTAINING ‘GRANULES’ IN INVERTEBRATE TISSUES

646 . VI . Variation in composition of metal-containing granules . VI I. Formation of metal-containing granules ( I ) Intracellular metal-containing granules . 650 (2) Extracellular metal-containing granules . 655 . VIII. Granule function 656 659 . IX. General discussion and summary X. Acknowledgements . 661 XI. References . 661
The effect of chlorhexidine acetate/xylitol chewing gum on the plaque and gingival indices of elderly occupants in residential homes.

AIM A randomised, controlled, double-blind, clinical trial was conducted to investigate the effect of a chlorhexidine acetate/xylitol gum (ACHX) on the plaque and gingival indices of 111 elderly occupants in residential homes. A gum containing xylitol alone (X) and a no gum (N) group was included. Participants' opinions about chewing gum were also investigated. METHODS Subjects chewed 2 pellets, for 15 min, 2x daily for 12 months. RESULTS In the ACHX group, the plaque and gingival indices significantly decreased (p<0.001) over the 12 months. In the X group, only the plaque score significantly decreased (p<0.05) and in the N control group, both indices remained high and did not change significantly. The acceptance of both chewing gums was high but more participants in the ACHX group felt that the gum kept their mouth healthy (p<0.05). The effect of the ACHX gum on plaque and gingival indices was significantly greater than for the X gum. CONCLUSION The long-term use of a chlorhexidine acetate/xylitol chewing gum may therefore support oral hygiene routines for an elderly dependent population.
Offenders, deviants, or patients? : an introduction to the study of socio-forensic problems

Acknowledgements. Foreword. Preface. List of Tables and Figures. Part I: Legal and Administrative Frameworks. Problem Areas Revisited. Responsibility (Liability) for Crime. Systems of Disposal. Part II: Clinical Considerations. Mental Disturbance and Criminality. Psychopathic Disorder - A Useful Lable? Violence and Homicide. Fire Raising. Sexual Behaviour and Misbehaviour. Will They Do It Again? Training: Enhancing Understanding. Concluding Comments. Name Index. Subject Index.
Association of Hepcidin mRNA Expression With Hepatocyte Iron Accumulation and Effects of Antiviral Therapy in Chronic Hepatitis C Infection

Background: Iron overload is frequently observed in patients with chronic hepatitis C (CHC) and is associated with the increased risk of liver fibrosis and carcinogenesis. Hepcidin is a regulator of iron homeostasis and a component of innate immunity. Based on experimental studies, iron overload might be a result of low hepcidin synthesis in CHC. Objectives: The aim of this case-control study was to assess hepcidin mRNA expression in liver tissue of patients with CHC in terms of iron metabolism parameters, hemochromatosis (HFE) gene mutations, disease activity, and efficacy of antiviral treatment with pegylated interferon and ribavirin. Patients and Methods: A total of 31 patients with CHC, who were qualified for antiviral therapy, were compared with 19 patients with chronic hepatitis B (CHB). In both groups, liver function tests and serum iron parameters were assayed and hepcidin mRNA expression was measured in liver specimens using real time PCR with normalization to reference genes mRNA of stable expression. Results: Patients with CHC had lower hepcidin mRNA expression and more frequently iron deposits in hepatocytes than subjects with CHB did. In CHC group, hepcidin mRNA expression was positively correlated with alanine aminotransferase activity and serum iron concentration. Low expression of hepcidin had no correlation with tissue iron overload in those with CHC. In univariate analysis, HCV viral load and efficacy of antiviral treatment were not significantly associated with hepcidin mRNA expression. Conclusions: Further studies on the role of hepcidin in pathogenesis of CHC are needed to assess the potency of its use in antiviral treatment.
Simple measures to reduce the rate of contamination of blood cultures in Accident and Emergency

Objectives: To reduce the contamination rate of blood cultures taken in the Accident and Emergency (A&E) department. Methods: The standard blood culture sampling kit was supplemented with an instruction sheet on the optimal method for drawing blood cultures and a large 62% ethyl alcohol impregnated wipe. Results: There was a statistically significant reduction in the number of contaminants (p = 0.03). Conclusions: Simple measures to encourage skin disinfection and appropriate sampling technique will reduce the incidence of contamination of blood cultures in the A&E department.