Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors associated with glycemic control in children and adolescents with type 1 diabetes mellitus at a tertiary-care center in Thailand: a retrospective observational study

Abstract Background Children and adolescents with type 1 diabetes mellitus (T1D), even those with intensive insulin treatment regimens, often have higher glycated hemoglobin (HbA1c) levels than adults. Objective To delineate the medical and psychosocial factors associated with glycemic control in an unselected pediatric population with T1D. Methods We included a cross-section of 58 adolescents (28 boys and 30 girls) aged 13.6 ± 4.0 years with T1D ≥1 year attending a well-established pediatric diabetes clinic in Thailand. Median diabetes duration was 4.1 years (range 1–18 years). Participants were divided into 2 subgroups according to their average HbA1c level over the past year. Those with good control (HbA1c <8%) (n = 13) were compared with those with poor control (HbA1c ≥8%) (n = 45). Data collected from self-report standardized questionnaires and medical records were used to compare variables between groups. Results Adolescents with good control used significantly less daily insulin and had higher family income, higher scores for family support, and quality of life (QoL) than those in the group with poor control (P < 0.05). Age, sex, puberty, duration of diabetes, insulin regimen, frequency of blood glucose monitoring, and self-report adherence did not differ between groups. By univariate logistic regression, the only factor associated significantly with poor glycemic control was a QoL score <25. Conclusion Adolescents with T1D may be at a higher risk of poor glycemic control if they have poor QoL, impaired family functioning, poor coping skills, and lower socioeconomic status, suggesting that psychosocial interventions could potentially improve glycemic control in this population.
Layered data aggregation with efficient privacy preservation for fog‐assisted IIoT

The emergence of fog computing facilitates industrial Internet of Things (IIoT) to be more real‐time and efficient; in order to achieve secure and efficient data collection and applications in fog‐assisted IIoT, it usually sacrifices great computation and bandwidth resources. From the low computation and communication overheads perspective, this paper proposes a layered data aggregation scheme with efficient privacy preservation (LDA‐EPP) for fog‐assisted IIoT by integrating the Chinese remainder theorem (CRT), modified Paillier encryption, and hash chain technology. In LDA‐EPP scheme, the entire network is divided into several subareas; the fog node and cloud are responsible for local and global aggregations, respectively. Specially, the cloud is able to obtain not only the global aggregation result but also the fine‐grained aggregation results of subareas, which enables that can provide fine‐grained data services. Meanwhile, the LDA‐EPP realizes data confidentiality by the modified Paillier encryption, ensures that both outside attackers and internal semi‐trusted nodes (such as, fog node and cloud) are unable to know the privacy data of individual device, and guarantees data integrity by utilizing simply hash chain to resist tempering and polluting attacks. Moreover, the fault tolerance is also supported in our scheme; ie, even though some IIoT devices or channel links are failure, the cloud still can decrypt incomplete aggregation ciphertexts and derive expected aggregation results. Finally, the performance evaluation indicates that our proposed LDA‐EPP has less computation and communication costs.
The generative adversarial networks and its application in machine vision

ABSTRACT In recent years, the model of improved GAN has been widely applied in the field of machine vision. It not only covers the traditional image processing, but also includes image conversion, image synthesis and so on. Firstly, this paper describes the basic principles and existing problems of GAN, then introduces several improved GAN models, including Info-GAN, DC-GAN, f-GAN, Cat-GAN and others. Secondly, several improved GAN models for different applications in the field of machine vision are described. Finally, the future trend and development of GAN are prospected.
Production of Recombinant Trichoderma Reesei Endoglucanase Protein CEL7B by Using Kluyveromyces Lactis

xvii Chapter 1: Introduction 1 1.1 Motivation 1 1.2 Biofuel production from woody biomass 2 1.2. 1 Thermochemical conversion of plant woody biomass 2 1.2. 2 Biochemical conversion of woody biomass 2 1.3 Hydrolysis Conversion: 3 1.4 Cellulases 3 1.4. 1 Cellulases in endoglucanase structure 4 1.4. 2 Measuring cellulase activity 4 Chapter 2: Kluyveromyces lactis: Properties and culture conditions 5 2.
Role of polymerase chain reaction in the diagnosis of cutaneous tuberculosis

Objective This study was designed to establish polymerase chain reaction (PCR) as a more effective tool for diagnose cutaneous tuberculosis (TB). Methods This cross-sectional study was conducted in the department of Dermatology & Venereology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, over a duration of one year. Thirty clinically diagnosed patients of cutaneous tuberculosis were selected for this study. The selected skin lesion was biopsied and it was divided in two portions, one for histopathological examination and another for bacteriological Ziehl-Neelsen (Z-N) staining, culture and molecular PCR analysis. Results In our study mean age was found 34.5±16.6 years, male to female ratio was 1.3:1. Tuberculosis verrucosa cutis (43%) was the commonest type of skin TB than lupus vulgaris (30%), erythema induratum of Bazin (13.3%) and others cutaneous types (13.3%). Concomitant pulmonary tuberculosis was detected in 10% of examined patients. In histopathological report, maximum 22 (73.3%) samples had typical granuloma without caseous necrosis, 5 (16.7%) cases had granuloma with caseous necrosis and 3 (10.0%) had only inflammatory cell infiltrate. Mantoux test was positive in 76.7% of the cutaneous tuberculosis patients. The evidence of Mycobacterium tuberculosis was negative in microscopy and culture media. PCR was positive in 3 (10.0%) patients. Sensitivity and specificity of PCR for M . tuberculosis was determined as 7.4% and 66.7%, respectively. Accuracy was found 13.3% whereas positive predictive value and negative predictive value were found 66.7% and 7.4% respectively. Conclusion Although higher specificity of cutaneous tuberculosis cases, the low sensitivity of PCR in this study, discourages the use of this method in routine diagnosis of cutaneous tuberculosis .
Diagnosis of Ill-Health in Trees

An introduction to the diagnosis of ill-health in trees host-agent directory the description of pests, diseases and disorders control of amenity tree pests, diseases and disorders decay and safety. Appendices: Hints on collecting and submitting specimens for laboratory examination possible sources of help in the diagnosis of damage to amenity trees and related matters - advisory services with laboratory and other specialist facilities.
Serum Level of Progranulin and Microvascular Complication in Type 2 Diabetes

Background: As the seventh leading cause of death by 2030, diabetes is considered the most common chronic metabolic disease worldwide. Progranulin (PGRN) is a novel protein that involved in chronic inflammatory response and insulin signalling pathway in obesity, metabolic syndrome and Type 2 diabetes millets (T2DM). Objectives: This study aimed to investigate the relation between PRGN and diabetic microvascular complications (nephropathy and retinopathy). Methods: A prospective cross sectional observational study was carried out on 60 T2DM patients with and without microangiopathies and 20 age and sex matched healthy controls. PGRN serum levels and glucose metabolism related laboratory data were measured and recorded. Results: Serum levels of PGRN were significantly higher in T2DM patients compared to normal control and in patients with microangiopathies compared to patients without microangiopathies (simple diabetes millets (SDM)). Serum PGRN levels were positively correlated with duration of diabetes, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triglyceride (TG), low density lipoprotein (LDL), albumin/creatinine ratio (A/C ratio), Glycosylated haemoglobin (HbA1c), fasting blood sugar (FBS), fasting insulin (FINS), Homeostasis Model Assessment for Insulin Resistance (HOMA-IR), while correlated negatively with serum albumin and high density lipoprotein (HDL). PGRN serum levels increased with the progress of diabetic microangiopathies with significantly highest values detectable in advanced nephropathy and retinopathy. Conclusion: PGRN seems to be involved in the pathogenesis of diabetic microangiopathy and might be considered as a biomarker for its severity in T2DM.
High-performance Proximity Query: An Enabling Technique for Improving Safety of Human-robot Interactive Tasks

— This short paper presents software library capable of carrying out proximity query (PQ) implemented on graphics processing units (GPUs), which runs on ROS, for detection of collision, as well as calculation of the minimal Euclidean distance between two non-convex objects, namely the robot and the environment. The flexible operation and computation workflow of this GPU-based PQ is introduced, showing its practical values for improving safety of human-robot interactive tasks.
Inter-Observer Variability of the Apgar Score of Preterm Infants between Neonatologists, Obstetricians and Midwives

Objective To assess the inter-observer variability of the Apgar Score (AS) across various perinatal Health Care Providers (HCP) taking care of newly born premature infants in the delivery room. Methods Design: Prospective observational study. Setting: 4 general hospitals and 3 university hospitals in Switzerland. Subjects: 43 neonatologists, 68 obstetricians and 55 midwives assessed the AS from 15 video sequences showing delivery room stabilisations or resuscitations of 15 preterm infants born below 34 0/7 weeks gestational age. Results Overall and for all observers, the mean inter-observer variability was low (ICC 0.72). There was a significant difference between the professions (p < 0.001) and hospitals (p < 0.001). The AS assigned by neonatologists for this group of preterm infants were significantly higher than the scores given by midwifes (p = 0.001). The scores assigned by obstetricians were the lowest for all infants; the difference from neonatologists being -0.53 (pairwise comparison). There was no significant difference between the AS assessed by professionals working in university hospitals compared to HCPs from general hospitals (p = 0.86). For all observers and in the majority of the sequences, heart rate showed the lowest and skin colour the highest standard deviation. Conclusion Our study revealed a relatively high inter-observer agreement in assessing the AS for premature infants among all perinatal health care professionals for the whole group of infants. A significant difference however was seen between the AS given by the different perinatal professional groups and between hospitals. A clearer definition and assessment method of each Apgar parameter in the setting of infants born premature and of resuscitation measures are needed. This may contribute to reduce the variations between professionals and hospitals, and to increase the value of this scoring within national and international databases to describe study populations for research, for benchmarking in neonatal intensive care and for comparison of outcome data.
Combining data and text mining techniques for analysing financial reports

There is a vast amount of financial information on companies’ financial performance available to investors today. While automatic analysis of financial figures is common, it has been difficult to automatically extract meaning from the textual part of financial reports. The textual part of an annual report contains richer information than the financial ratios. In this paper, we combine data mining methods for analyzing quantitative and qualitative data from financial reports, in order to see if the textual part of the report contains some indication about future financial performance. The quantitative analysis has been performed using selforganizing maps, and the qualitative analysis using prototype-matching text clustering. The analysis is performed on the quarterly reports of three leading companies in the telecommunications sector.
Machine Learning for Bitcoin Pricing - A Structured Literature Review

Bitcoin, as the most popular cryptocurrency, has received increasing attention from both investors and researchers over recent years. One emerging branch of the research on bitcoin focuses on empirical bitcoin pricing. Machine learning methods are well suited for predictive problems, and researchers frequently apply these methods to predict bitcoin prices and returns. In this study, we analyze the existing body of literature on empirical bitcoin pricing via machine learning and structure it according to four different concepts. We show that research on this topic is highly diverse and that the results of several studies can only be compared to a limited extent. We further derive guidelines for future publications in the field to ensure a sufficient level of transparency and reproducibility.
Design of a Modified Stewart Platform Manipulator for Misalignment Correction

This thesis work is about the design of a modified Stewart platform manipulator for misalignment correction. The common version of the Stewart platform uses six actuators. The traditional Stewart platform of this kind has a moving top plate and a fixed base plate. However, in this research, the modified design of the traditional Stewart platform is studied. It is designed to be an easy connect-disconnect platform that can wrap around different structures with different cross sections and symmetrically designed. It is able to adjust position easily by using four identical but independent linear actuators populated evenly in two parts fastened to the top and bottom base by ball joints with each part been symmetrical to the other. To design two symmetrical parts and an adjustable clamp are a major objective of the thesis. One symmetrical part flipped upside down produces the other. The adjustable clamp was printed in 3D and can be used to align regular structural shapes especially circle of various diameter. To correct the misalignment, a failure study was carried out to determine the two equal but opposite loads required to correct misalignment in two plastic beams. Five loads were applied which showed that the smaller the load, the better the misalignment. This study showed that it is better to fix the base at a location where it does not move. To investigate that the modified Stewart platform can resist structure stiffness, the actuator assembly was analyzed using ANSYS software. The results showed that the deformation and maximum stress is less that the structure stiffness, which proves why the assembly can resist structural stiffness. The results support that the modified Stewart platform can be used for misalignment correction. Running head: DESIGN OF A MODIFIED STEWART PLATORM MANIPULATOR iii
Actor-based MapReduce-application for calculating Key Performance Indicators

This report describes a generalized MapReduce-application for calculating KPIs based on graph representations of business structures. The graphs used by this application are created by a secondary application which extracts all relevant data for the calculating KPIs from multiple undefined data sources. For this purpose, the graph creation application only requires meta information defining the structure of the business in question. By making use of the Actor model, the generalized MapReduce-application is capable of parallelizing a large portion of the required steps in calculation KPIs, which results in a great performance increase compared to sequential processing of the data.
Embedded Neural Networks for Continuous Patient Posture Classification

Current hospital protocols dictate patients be turned at least every three hours in the effort of preventing pressure ulcers. To reduce the workload of nurses, Momo Medical has created an embedded sensing device to track the patient's posture and notify nurses when it is time to turn them. The challenge presented and the focus of this thesis is classifying the posture of the patient based on the sensor data sampled, specifically, utilizing neural networks on an embedded platform. Furthermore an optimization inspired by recurrent neural networks and ensemble neural networks is proposed, implemented, and compared against vanilla neural networks and pruned variants.
Learning and Fusing Multiple User Interest Representations for Micro-Video and Movie Recommendations

Deep learning is known to be effective at automating the generation of representations, which eliminates the need for handcrafted features. For the task of personalized recommendation, deep learning-based methods have achieved great success by learning efficient representations of multimedia items, especially images and videos. Previous works usually adopt simple, single-modality representations of user interest, such as user embeddings, which cannot fully characterize the diversity and volatility of user interest. To address this problem, in this paper we focus on learning and fusing multiple kinds of user interest representations by leveraging deep networks. Specifically, we consider efficient representations of four aspects of user interest: first, we use latent representation, i.e. user embedding, to profile the overall interest; second, we propose item-level representation, which is learned from and integrates the features of a user's historical items; third, we investigate neighbor-assisted representation, i.e. using neighboring users’ information to characterize user interest collaboratively; fourth, we propose category-level representation, which is learned from the categorical attributes of a user's historical items. In order to integrate these multiple user interest representations, we study both early fusion and late fusion; where for early fusion, we study different fusion functions. We validate the proposed method on two real-world video recommendation datasets for micro-video and movie recommendations, respectively. Experimental results demonstrate that our method outperforms existing state-of-the-arts by a significant margin. Our code is publicly available.
Pharmacopoeial Standards and Specifications for Pharmaceutical Oral Liquid Preparations

Quality control is an essential operation of the pharmaceutical industry. It is the monitoring process which encompassing specifications, inspections, analysis and recommendations. The appropriate design and formulation of a dosage form requires discretion of the physical, chemical and biological characteristics of active pharmaceutical ingredients (APIs) and inactive pharmaceutical excipients (IPIs) to be used in formulating the pharmaceutical. The drug and others pharmaceutical materials utilized must be compatible with one another to produce a drug product that is stable, efficacious, potent, palatable, easy to administer and well tolerated. The quality of any drug in dosage form depends on its safety, potency, efficacy, stability, patient acceptability and regulatory compliance. In order to claim the pharmaceutical oral liquid preparations as quality drugs it must satisfy the aforementioned criteria. To conform the requirements of pharmaceutical oral liquids during Review Article Uddin et al.; ACRI, 3(2): 1-12, 2016; Article no. ACRI.22675 2 manufacturing, in-process quality control (IPQC) tests are done as per specifications with a view to remove error or if necessary to adjust the process. The quality of final products depends on finished product quality controls (FPQC) test. So the quality of pharmaceutical oral liquids is strongly related to IPQC and FPQC tests. The purpose of this study is to focus on the different in-process and finished products quality control tests for pharmaceutical oral liquid preparations according to pharmacopoeias.
Multi-User Linear Precoding in Massively Distributed Polarized Antenna Systems Under Imperfect CSIT

This paper presents multi-user (MU) linear precoding methods for massively distributed antenna system (DAS) with polarized antennas, where mobile stations (MSs) are spatially grouped and the distributed antenna (DA) ports with a polarized-antenna are connected to a central base station (BS). While the (slowly-changing) long-term channel state information (CSI) (i.e., large scale fading and polarization) can be accurately estimated at the transmit-side, the short-term CSI (instantaneous channel response) is available at the transmit-side with quantization errors due to the limited feedback. Accordingly, the utilization of a large number of DA ports is not always beneficial due to the imperfect short-term CSI at the transmitter (CSIT). In this paper, we first derive the asymptotic achievable rate and signal-to-leakage-and-noise ratio (SLNR) for the MU linear precoding in the massive DAS, which depends on the long-term CSIT and the number of feedback bits, and propose a transmit DA port selection based on the asymptotic SLNR performance. Here, the number of selected DA ports can be also optimized according to the long-term CSIT and the number of feedback bits. Furthermore, we also propose a polarization selection strategy at each DA port (equipped with multi-polarized antennas) so as to exploit the polarization diversity. Through the simulation, we confirm that the proposed MU precoding with the DA port selection outperforms the conventional precoding schemes for the DAS and, furthermore, the proposed polarization selection strategy achieves a rate performance comparable to the DAS with a (single polarized antenna) node density twice as large.
Adaptive repair method for constraint handling in multi-objective optimization based on constraint-variable relation

iii Lay summary . iv Preface. v Table of contents . vi List of tables . ix List of figures . x List of abbreviations . xii List of symbols . xiii Acknowledgments. xv