Miracle-dz/UniFAR-FTUs huggingface dataset:
Contributions to modelling and control for improved hypoglycaemia and variability mitigation by dual-hormone artificial pancreas systems

People with Type 1 Diabetes lack the ability to secrete insulin and therefore need to regulate their blood glucose with exogenous insulin delivery. The Artificial Pancreas is presented as the ideal technological solution to reach the therapeutic goals of normoglycaemia, freeing the patient from the current burden of self-control and management. Nevertheless, the risk of hypoglycaemia and the high glycaemic variability are still a limiting factors in the current control algorithms integrated in the Artificial Pancreas. The purpose of the present thesis is to delve into knowledge of hypoglycaemia and to advance in the artificial pancreas control algorithms in order to minimise hypoglycaemia incidence and reduce glycaemic variability. After providing an overview of the state of the art in the eld of glucose control and articial pancreas, this thesis addresses issues on modelling and control, with the following contributions: An extension of the Bergman Minimal model accounting for counterregulatory response to hypoglycaemia is presented. This model explains the relationship between the several physiological changes produced during hypoglycaemia, with adrenaline and free fatty acids as main players. As a result, a better understanding of hypoglycaemia is gained, allowing to explain a paradoxical auto-potentiation of hypoglycaemia as modeled through functional approaches in the widespread used UVA-Padova Type 1 Diabetes simulator, which will be used in this thesis for in silico validation of the developed controllers. An assessment of glucose variability metrics and control quality indices is carried out. The evaluation of the glycaemic variability on the controllers performance is necessary; but there is not a gold standard variability metrics yet. Therefore, an analysis of the variability metrics available in literature is conducted in order to define a recommendable set of indicators. Due to the limitations of single-hormone artificial pancreas systems in mitigating hypoglycaemia in challenging scenarios such as exercise, this thesis focuses on the developement of new dual-hormone control algorithms, with concomitant infusion of insulin and glucagon. A coordinated dual-hormone controller with parallel control structures is proposed as a feasible control algorithm for hypoglycaemia mitigation and glycaemic variability reduction, demonstrating superior performance as currently used control structures with independent insulin and glucagon control loops. The controllers are designed and evaluated in-silico under challenging scenarios and their performance are assessed mainly with the set of metrics defined previously as the recommendable ones.
Silent cerebral infarcts following pulmonary vein isolation with different atrial fibrillation ablation techniques – incidence and risk factors

Introduction Silent cerebral infarcts (SCIs) detected by diffusion-weighted magnetic resonance (DW-MRI) following atrial fibrillation (AF) ablation have been reported, with the incidence of 1–38%. We aimed to compare the incidence of SCIs following AF ablation with four different technologies and analyze the risk factors. Material and methods A total of 104 patients (mean age: 59.9 ±9.5 years, 68 males) with symptomatic AF, referred for ablation, were included in the study. The AF ablation was performed with irrigated radiofrequency point-by-point technique (RF group) in 24 patients, and with 3 different single-shot techniques: phased-RF (PVAC) in 46, second-generation cryoballoon (CB) in 24 and irrigated multipolar RF catheter (nMARQ) in 10 patients. In all patients DW-MRI was performed pre- and post-procedurally to evaluate the incidence of SCIs. Procedural parameters, complication rate and post-procedural SCI incidence were compared between the groups. Results Procedure (167.1 vs. 110.5 vs. 106.0 vs. 141.5 min, p < 0.001), fluoroscopy (22.7 vs. 15.9 vs. 16.3 vs. 15.3 min, p = 0.048) and LA dwell (101.5 vs. 53.9 vs. 56.0 vs. 97.0 min, p < 0.001) times compared respectively between RF, PVAC, CB and nMARQ groups were significantly shorter with single-shot techniques. The number of new-onset SCIs was 4/24 (16.7%) in RF, 7/46 (15.2%) in PVAC, 1/24 (4.2%) in CB and 1/10 (10%) in the nMARQ group. Univariate analysis identified procedure duration (p = 0.02), lower LV ejection fraction (p = 0.03), persistent form of arrhythmia (p = 0.007) and intraprocedural cardioversion (p = 0.002) as risk factors of new-onset SCIs. Conclusions Silent cerebral infarcts can be detected following AF ablation regardless of the technology used. Prolonged procedure time, lower ejection fraction, persistent form of arrhythmia and intraprocedural cardioversion increase the risk of SCIs.
Image Denoising Method Based on DCT Over-Complete Dictionary and the MOD Algorithm

A kind of image denoising algorithm based on DCT over-complete dictionary and the MOD algorithm is introduced in this paper.Firstly,the noise image is segmented to some smaller image blocks,then the blocks are decomposed by OMP algorithm with the initialized DCT over-complete dictionary.Secondly,the DCT over-complete dictionary is updated by the MOD dictionary learning algorithm.Finally,this process is repeated to get the sparse representation of the image and then reconstruction to noise image.The experiment results show that this algorithm is more effective for image denoising than some traditional methods.
Complex human action recognition on daily living environments using wearable inertial sensors

The aim of this study is to evaluate how similar a set of human actions are when they are performed under controlled conditions versus the same set of actions when they are performed under uncontrolled conditions, namely in daily living environments such as the users' houses. This research is important for automatic recognition of human actions in daily living environments, mainly using wearable sensors, which is still an open research challenge of the field of pervasive computing. Action recognition is important for various applications of this field, such as, for instance, ambient intelligence, smart devices, and healthcare. In this work, we measure and analyze five human complex actions using wearable sensors in both, structured and daily living environments. Three wearable inertial sensor units were used in this study and they were worn by three healthy young subjects on three points of their upper limbs: the scapula, the upper arm and the forearm. The complex actions involved in this study are: grooming, cooking, eating, doing housework, and mouth care. Dynamic Time Warping algorithm was used to measure the intra and inter test variability of actions in both environments. Additionally, the results of the application of three supervised classification techniques, namely C4.5, Naive Bayes and Logistic Regression, are compared in terms of true positive rate TPR, true negative rate TNR and F-measure metrics. The classification models were based on time-domain and frequency-domain features extracted from orientation signals. According to the analysis cooking and eating are the actions with highest and lowest variability, respectively. Concerning the classification results, Naive Bayes and Logistic Regression obtain a TPR of 0.911 using relevant attributes. Our results provide valuable information to measure the similarity of a set of complex actions in daily living environments and to classify them.
Quality Improvement: Developing a Hospital Program to Reduce Staff Injury Associated with the Care of the Patient with Dementia

6 Problem Description.9 Introduction.9 Problem Background.9 Local Problem.10 Available Knowledge.11 Literature Review.11 Synthesis of the Evidence.11 Rationale.13 Theoretical Model.13 Person-Centered Care Model.14 Adult Learning Theory.14 Project Framework.14 Specific Aims.15 Context.16 Population.16 Local Care Environment.16 Relevant Elements of Project Setting.17 Organizational Culture and Readiness for Change.18 Strengths and Weaknesses.18 Memorandum of Understanding. 21 Interventions.21 HOSPITAL PROGRAM TO REDUCE STAFF INJURY 3 Short-Term Outcomes . 22 Long-Term Outcomes.24 Timeline.25 Measures.26 Project Budget.27 Analysis.28 Quantitative Data Analysis . 28 Qualitative Data Analysis.29 Ethical Considerations.30 Ethical Considerations and Protection of Participants.30 Conflicts of Interest.31 Biases.31 Threats to Quality.32 IRB Application and Project Determination.33 Results.33 Steps of the Intervention.33 Outcomes Results.36 Missing Data.38 Summary.38 Interpretation.39 Contextual Elements.39 Association between Outcomes, Interventions, and Contextual Elements.42 Limitations.43 HOSPITAL PROGRAM TO REDUCE STAFF INJURY 4 Conclusion.44 Usefulness of the Work.44 Sustainability.45 Implications for Practice and Further Study.46 Next Steps.47 Dissemination.48 References.49 Appendices Appendix A: Literature Review Summary Table.53 Appendix B: Person-Centered Care Model.55 Appendix C: Logic Model.57 Appendix D: Memorandum of Understanding.59 Appendix E: Permission Letter for Use of SBMSEP . 60 Appendix F: Self-Perceived Behavior Management Self-Efficacy Profile (SBMSEP) . 61 Appendix G: Dementia Knowledge Questionnaire.63 Appendix H: Expanded-Self-Perceived Behavior Management Self-Efficacy Profile.64 Appendix I: Instruction to Pilot Unit.65 Appendix J: Education Evaluation Survey.66 Appendix K: Audit Tool.67 Appendix L: Timeline.68 Appendix M: Data Table.71 HOSPITAL PROGRAM TO REDUCE STAFF INJURY 5 Appendix N: Two to Three Year Budget Plan.75 Appendix O: Expense Report.77 Appendix P: Statement of Operations.79 Appendix Q: Collaborative Institutional Training Initiative (CITI) . 80 Appendix R: Letter of Determination from IRB.81 Appendix S: Outcomes Evaluation Table.82 Appendix T: Summary of Data Report.87 Appendix U: Completed Survey and Questionnaire Results.88 HOSPITAL PROGRAM TO REDUCE STAFF INJURY 6
THE HOWARD AND MOORE COMPLETE CHECKLIST OF THE BIRDS OF THE WORLD. 4 th EDITION VOLUME 2 (2014)

Foreward by Richard Howard 7 Introduction 9 Avian Higher-level Phylogenetics and the Howard and Moore Checklist of Birds by Joel Cracraft, F. Keith Barker and Alice Cibois 16 The Sequence of Families of Birds 22 Presentation of the List 27 Acknowledgements 29 Checklist of the Birds of the World 31 Appendix I: Matters of Nomenclature 827 Appendix II: Notes on Bibliographic Details 830 List of References 832 Index of Scientific Names 884 Index of English Names 1017
Biomechanical assessment and electromagnetic intervention for diabetic ulcers

Diabetic foot ulceration is a major risk factor for lower limb amputation. Novel assessments and treatments are therefore demanded for better management of diabetic foot ulcers in clinical settings. The present thesis hypothesizes that the novel biomechanical assessment can validly and reliably reflect the tensile properties and underlying collagen of diabetic ulcers whereas the pulsed electromagnetic field intervention can effectively exert changes in diabetic wounds in cellular, molecular and biomechanical aspects. An optical coherence tomography-based air-jet indentation system was recently developed to objectively and quantitatively measure the indentation stiffness of the biological tissues in a non-invasive and non-contact manner. In the first study of the present thesis, a parallel comparison was made between the measurement of indentation stiffness by the indentation system and various tensile properties by conventional ex vivo tensile testing over 3 weeks in a biopsy punched wound model at the hindlimbs of streptozotocin-induced diabetic Sprague-Dawley rats. The relationship between the indentation stiffness and collagen visualized by picro-sirius red staining was also explored. The present study showed that the indentation stiffness was significantly negatively correlated to the tensile properties and the abundance and alignment of collagen fibres in different phases of diabetic wound healing. Previous studies demonstrated that pulsed electromagnetic field (PEMF) could accelerate wound closure, increase myofibroblast population and
Towards Robust Semantic Attribute Learning in Visual Computing

The rapid growth of social media in recent years provides a large amount of usergenerated visual objects, e.g., images and videos. Advanced semantic understanding approaches on such visual objects are desired to better serve applications such as human-machine interaction, image retrieval, etc. Semantic visual attributes have been proposed and utilized in multiple visual computing tasks to bridge the so-called “semantic gap” between extractable low-level feature representations and high-level semantic understanding of the visual objects. Despite years of research, there are still some unsolved problems on semantic attribute learning. First, real-world applications usually involve hundreds of attributes which requires great effort to acquire sufficient amount of labeled data for model learning. Second, existing attribute learning work for visual objects focuses primarily on images, with semantic analysis on videos left largely unexplored. In this dissertation I conduct innovative research and propose novel approaches to tackling the aforementioned problems. In particular, I propose robust and accurate learning frameworks on both attribute ranking and prediction by exploring the correlation among multiple attributes and utilizing various types of label information. Furthermore, I propose a video-based skill coaching framework by extending attribute learning to the video domain for robust motion skill analysis. Experiments on various types of applications and datasets and comparisons with multiple state-of-the-art baseline approaches confirm that my proposed approaches can achieve significant performance improvements for the general attribute learning problem.
Anomaly Detection based on Doubly-Kernelized Scoring and Matrix Kernels

We consider the task of simultaneous anomaly detection in a system and its elements by comparing a pair of multivariate data sets. This task corresponds to simultaneously conducting anomaly detection and localization. For solving this task, we estimate scores which represent anomalousness of a whole system and its elements. This scoring is difficult for the following reasons. First, it is not trivial how to estimate the scores by taking into account changes of relationships between the elements, which strongly correlate with each other. Second, it is required that scores of the system and its elements are estimated from a single framework. Otherwise, the relation between the scores is not clear and thus localization becomes difficult. We propose a solution, which is a single framework to simultaneously estimate anomalousness of a system and its elements. The key ideas of the method are the following two. First, we introduce doubly kernelized scores. We construct a score by using difference between kernel matrices defined between elements. Then we represent the difference by using a kernel defined between matrices. Second, we construct matrix kernels, which are defined between different dimensional matrices. This method has the following properties: (1) the method can be applied to any data sets where a kernel can be defined between the elements, (2)can estimate scores of element group of any number, and (3)can be applied to a pair of data sets whose numbers of elements are different. Especially, the second and the third properties are realized by introducing matrix kernels. We demonstrate the effectiveness of the proposed method through the experimental results using three data sets.
Image Retrieval Method Based on Contour Feature Point

Considering the problem of the image retrieval method based on shape,this paper proposes a novel method for image retrieval based on feature points of contour of an interesting object.Mean Shift algorithm is applied to extract an interesting object,then the local maximum points of curvature of the object contour are calculated and the object is described with its eigenvector comprised of these feature points.An effective matching mechanism based distance between the eigenvectors of a retrieve object and a retrieved object is used to carry out matching or recognition between two objects.Experimental results show that the proposed method has a higher recall and precision.
Outcomes of gender-sensitivity educational interventions for healthcare providers: A systematic review

Background: Although gender plays an important role in health, most healthcare providers lack knowledge in providing gender-sensitive care. Offering gender-sensitivity training for healthcare providers can help to address gender-based health inequalities. Method: A mixed-methods systematic review of gender-sensitivity training programmes or interventions for healthcare providers was undertaken to assess their outcomes and to document areas for future research. Comprehensive searches of seven international databases were conducted for peer-reviewed literature published between 1998 and 2018. Eligible studies included at least one outcome related to gender-sensitivity training for healthcare providers. Results: Twenty-nine studies met the inclusion criteria. Fourteen studies focused on gender-sensitivity in reducing gender bias towards men and women, and 15 studies focused on addressing the needs of lesbian, gay, bisexual and transgender (LGBT) patients. Thirty-seven percent of studies showed a significant improvement in gender-related knowledge, attitudes or practice after the training. Multiple training methods were used to teach gender-sensitive care. Common content of the training included learning sex/gender terminology, understanding gender issues and inequalities in health, stigma and discrimination and communication skills. The duration and frequency of interventions ranged considerably. Sex differences in training outcomes also occurred among the learners. Conclusion: Review findings highlight that although gender-sensitivity training for healthcare providers is increasing, there is insufficient evidence to determine its effectiveness. Additional, more rigorously designed studies are needed to assess the long-term implications on learner behaviours and practices, especially across a wide variety of healthcare providers.
Design and Implementation of Unicode Data Warehouse ETL

During the process of loading Unicode data,the phenomenon so-called a loss of information will be encountered while the source characters are not defined in the target character sets. In light of this situation,this paper delivers a fault tolerant ETL solution on how to resolve the source/target character set conversion problem while populating Unicode data from Oracle 9i database to Teradata data warehouse. Practical result proves its efficiency and accuracy.
The lived experience of women with faecal incontinence after childbirth: a thematic synthesis

The prevalence of faecal incontinence in the general population is estimated to be between 11–15%, with a subgroup of younger women experiencing a higher prevalence linked to childbirth injury. Such injury is estimated to occur in up to 16% of vaginal births, equating to potentially 80,000 affected women a year who experience a variety of symptoms from perineal pain, urgency, incontinence and psychological morbidity. The perspective of women living with faecal incontinence as a result of childbirth injury is largely missing from the data. This project aimed to address the gap by pulling together women’s perspectives through a thematic synthesis. Thematic synthesis of qualitative research was used to direct this project. A database search of CINAHL, PubMed and the British Nursing Index retrieved 434 records. After review four records were included in the synthesis. From the data three categories were synthesised: experiencing a compromised identity, living with secrets and feeling isolated. These categories were contained in an overarching theme of invisibility as a woman in the mother/child dyad. Postnatal faecal incontinence is debilitating and often hidden due to shame, lack of information and support. This synthesis suggests women with postnatal faecal incontinence have similar lived experiences to those with faecal incontinence of different aetiology. The unique difference is the sense of invisibility expressed by the participants of their identity as a woman due to an enduring focus by others on the child’s health and their function as a mother.
ANALYSIS OF LAPROSCOPIC APPENDECTOMY-COMPARISON WITH OPEN APPENDECTOMY WITH RESPECT TO SURGICAL SITE INFECTION

Introduction: Open appendectomy (OA), which was described first by McBurney in 1894, has been accepted as the gold standard of appendectomy for around 100 years. Aims and objectives: The basic aim of the study is to analyze laparoscopic appendectomy in comparison with open appendectomy with respect to surgical site infection. Material and methods: This study was conducted at THQ Hospital, Sadiqabad, Rahim Yar Khan during October 2018 to March 2019. This study includes 100 patients diagnosed as appendicitis and operated. Their mean age was 33.32 ± 20.80 years (range, 2 to 92 years). OA was performed through right lower quadrant transverse muscle-splitting incision. The thread ties were placed on the base of the appendix. Results: Of these 100 patients, 85 (63.4%) had acute appendicitis and 20 (20.1%) appendices were perforated. There were 80 patients in the LA group and 54 in the OA group; however, 9 patients had a conversion to an open procedure. The overall SSI rate was not different between the two groups (2.8% for the OA group vs. 4.6% for the LA group, respectively, P=0.204), but the superficial SSI rate was significantly lower in the LA group. Conclusion: It is concluded that advantages of diagnostic laparoscopy in patients with abdominal pain, combined with the benefits of laparoscopic appendectomy, suggest that all patients with suspected appendicitis should be considered for laparoscopic appendectomy provided appropriately trained personnel and adequate equipment are available.
Brand Image Effect on Selecting Place of Dentures Fabrication at Integrated Specialist Clinic of RSGM FKG UNAIR

Integrated Specialist Clinic of Oral and Dental Hospital, Faculty of Dentistry, Airlangga University (RSGM FKG UNAIR) provides oral and dental health care service ranging from basic medical level up to sub-specialistic covering 8 dental health fields. Based on data from 2012 to 2015, the highest number of patients is permanent tooth extraction patients. The large number of permanent tooth extraction patients is not followed by a large number of patients who return to install denture. The percentage of patience who returns to install the denture is only 24.67% of all permanent tooth extraction patients. The purpose of this study was to determine the effect of brand image factors on the selection of denture making site. The type of this research was analytic observational by using cross sectional approach. The research data was taken during September and October 2017 at place and time mutually agreed between researcher and respondent. The population of this research was permanent tooth extraction patients in Integrated Specialist Clinic RSGM FKG UNAIR in 2016. The sample size was 60 patients. Brand image based on the composite value of types of brand association of Integrated Specialist Clinic of RSGM FKG NAIR has an effect on the selection of denture making site. Keywords: Brand image, denture, Integrated specialist clinic, Permanent tooth extraction