Miracle-dz/UniFAR-FTUs huggingface dataset:
Pain level measured with visual analogue scale in patients with hirsutism or hypertrichosis undergoing depilation

Smooth skin is an attribute of beauty. Hair is a skin appendage. Hirsutism affects 5-10% of the women. There are different methods of excessive hair removal: with creams or foams, shaving, depilation, epilation, waxing, laser treatment or with use of tweezers. The aim of the study was to assess pain level measured with visual analogue scale (VAS 0-10) in persons with hirsutism and hypertrichosis undergoing depilation. An original questionnaire consisting of 7 questions was used as the tool for examining participants. A total of 125 persons participated in the study. Among them were 106 women (84.8%) and 19 were (15.2%). Depilation is so painful for some patients, that some of them may require painkillers before it, but this issue should be discussed with the physician.
Cardiovascular System Modeling Using Windkessel Segmentation Model Based on Photoplethysmography Measurements of Fingers and Toes

Background: Photoplethysmography (PPG) contains information about the health condition of the heart and blood vessels. Cardiovascular system modeling using PPG signal measurements can represent, analyze, and predict the cardiovascular system. Methods: This study aims to make a cardiovascular system model using a Windkessel model by dividing the blood vessels into seven segments. This process involves the PPG signal of the fingertips and toes for further analysis to obtain the condition of the elasticity of the blood vessels as the main parameter. The method is to find the Resistance, Inductance, and Capacitance (RLC) value of each segment of the body through the equivalent equation between the electronic unit and the cardiovascular unit. The modeling made is focused on PPG parameters in the form of stiffness index, the time delay (△t), and augmentation index. Results: The results of the model simulation using PSpice were then compared with the results of measuring the PPG signal to analyze changes in the behavior of the PPG signal taken from ten healthy people with an average age of 46 years, compared to ten cardiac patients with an average age of 48 years. It is found that decreasing 20% of capacitance value and the arterial stiffness parameter will close to cardiac patients' data. Compared with the measurement results, the correlation of the PPG signal in the simulation model is more than 0.9. Conclusions: The proposed model is expected to be used in the early detection of arterial stiffness. It can also be used to study the dynamics of the cardiovascular system, including changes in blood flow velocity and blood pressure.
Brain Tumor Segmentation using Hierarchical Combination of Fuzzy Logic and Cellular Automata

Background: Magnetic resonance (MR) image is one of the most important diagnostic tools for brain tumor detection. Segmentation of glioma tumor region in brain MR images is challenging in medical image processing problems. Precise and reliable segmentation algorithms can be significantly helpful in the diagnosis and treatment planning. Methods: In this article, a novel brain tumor segmentation method is introduced as a postsegmentation module, which uses the primary segmentation method's output as input and makes the segmentation performance values better. This approach is a combination of fuzzy logic and cellular automata (CA). Results: The BraTS online dataset has been used for implementing the proposed method. In the first step, the intensity of each pixel is fed to a fuzzy system to label each pixel, and at the second step, the label of each pixel is fed to a fuzzy CA to make the performance of segmentation better. This step repeated while the performance saturated. The accuracy of the first step was 85.8%, but the accuracy of segmentation after using fuzzy CA was obtained to 99.8%. Conclusion: The practical results have shown that our proposed method could improve the brain tumor segmentation in MR images significantly in comparison with other approaches.
Artificial intelligence in retinal imaging for cardiovascular disease prediction: current trends and future directions

Purpose of review Retinal microvasculature assessment has shown promise to enhance cardiovascular disease (CVD) risk stratification. Integrating artificial intelligence into retinal microvasculature analysis may increase the screening capacity of CVD risks compared with risk score calculation through blood-taking. This review summarizes recent advancements in artificial intelligence based retinal photograph analysis for CVD prediction, and suggests challenges and future prospects for translation into a clinical setting. Recent findings Artificial intelligence based retinal microvasculature analyses potentially predict CVD risk factors (e.g. blood pressure, diabetes), direct CVD events (e.g. CVD mortality), retinal features (e.g. retinal vessel calibre) and CVD biomarkers (e.g. coronary artery calcium score). However, challenges such as handling photographs with concurrent retinal diseases, limited diverse data from other populations or clinical settings, insufficient interpretability and generalizability, concerns on cost-effectiveness and social acceptance may impede the dissemination of these artificial intelligence algorithms into clinical practice. Summary Artificial intelligence based retinal microvasculature analysis may supplement existing CVD risk stratification approach. Although technical and socioeconomic challenges remain, we envision artificial intelligence based microvasculature analysis to have major clinical and research impacts in the future, through screening for high-risk individuals especially in less-developed areas and identifying new retinal biomarkers for CVD research.
Statistics for the behavioral sciences : a first course for students of psychology and education

1. Introduction to Statistics 2. Frequency Distributions 3. Central Tendency 4. Variability 5. z-Scores: Location of Scores and Standardized Distributions 6. Probability 7. Probability and Samples: The Distribution of Sample Means 8. Introduction to Hypothesis Testing 9. Introduction to the t Statistic 10. Hypothesis Tests with Two Independent Samples 11. Hypothesis Tests with Related Samples 12. Estimation 13. Introduction to Analysis of Variance 14. Repeated-Measures Analysis of Variance (ANOVA) 15. Two-Factor Analysis of Variance (Independent Measures) 16. Correlation and Regression 17. The Chi-Square Statistic: Tests for Goodness of Fit and Independence 18. The Binomial Test 19. Statistical Techniques for Ordinal Data: Mann-Whitney and Wilcoxon Tests and Spearman Correlation.
UNIVERSITY OF CALIFORNIA SANTA CRUZ WHEN THE TIME IS RIGHT: REGULATION OF CELL DIVISION IN DROSOPHILA A dissertation submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in MOLECULAR, CELL AND DEVELOPMENTAL BIOLOGY by

39 Introduction 40 Methods and Materials 42 Results 45 Transgenic Nuf phospho-mutants result in partial female sterility . 45 Phosphomimetic Nuf cannot localize to the centrosome . 46 Nuf phospho-mutants disrupt furrow formation . 47 Dosage-sensitive interactions between nuf and Dynactin result in sterility . 49
Could Helicobacterorganisms cause in£ammatory bowel disease?

The discovery of Helicobacter pylori sparked a revolution in the understanding and management of peptic ulcer disease and gastric cancer. Other Helicobacter species are recognized as important pathogenic agents in colitic diseases of rodents and primates, in particular Helicobacter bilis , Helicobacter fennelliae , Helicobacter hepaticus and Helicobacter trogontum . Helicobacter bilis and H. hepaticus are now routinely used to initiate rodent models of inﬂammatory bowel disease (IBD), particularly in immunocompromised hosts. Molecular evidence exists linking various non- pylori Helicobacter spp. with human IBD; however, attempts to culture organisms in this disease cohort have proved unsuccessful to date. Attributing causation has therefore proved elusive. Seven enterohepatic, non- pylori Helicobacter organisms have been successfully cultured from humans, namely Helicobacter canadensis , Helicobacter canis , Helicobacter cinaedi , H. fennelliae , Helicobacter pullorum , Helicobacter winghamensis and Helicobacter sp. ﬂexispira taxon 8 (now classiﬁed as H. bilis) . Of these, H. cinaedi and H. fennelliae are the closest to fulﬁlling Koch’s postulates as causative agents in homosexual proctitis. The possibility that novel Helicobacter organisms have a role in the initiation of human IBD warrants further consideration and targeted investigations. (ATCC 51449) in terms of its activity being either symbiotic or pathogenic to the host organism. This study eloquently showed that wild-type T6SS organisms appear to promote an anti-inﬂammatory environment within intestinal epithelial cells (IECs) while mutant T6SS organisms show increased colonization of the murine intestine, increased intracellular colonization within IECs and, most importantly, a broad and apparently T H 17-based host immune response to the presence of the organism. The study utilized various mouse models and a mouse IEC line. The importance of this study is that intraspecies bacterial heterogeneity has been demonstrated to be as important as host heterogeneity in deﬁning the ultimate host phenotype in an IBD model.
Parametric simulations for residual stresses and distortions of Inconel 625 fabricated by laser powder bed fusion additive manufacturing

Developments related to the laser powder bed fusion (L-PBF) expanded the application area of the additive manufacturing (AM) for metal alloys, and increased the variety of machines and materials. On the other hand, this increase exposed the need for process development to adapt new materials and shapes with acceptable metallurgical, mechanical and geometrical attributes. In recent years, researchers have sought to reduce the development costs by decreasing these process development needs for some requirements. Among these, modeling and simulations for residual stresses and distortions are common practices. Dedicated software for these applications provided remarkable savings in computational times. Nevertheless, it is still necessary to pay attention to dedicated software, due to the fact that they might have some assumptions which are unknown to the end users. This study provides an in-depth investigation of Simufact Additive software based on L-PBF of Inconel 625 alloy. In this regard, thermo-mechanical simulations were performed by comparing the results with experimental data. Simulation set-ups were fine-tuned according to comparisons, and parametric analyses were conducted. The laser power and scanning speed were found to be the most influential parameters on the resulting residual stresses.
Value Engineering and Agile for building Urgent and Emergency Care

—In health care, combating waste is an emerging issue as clinicians face the complexities of current patient care requiring to apply new technologies as also collaborate with professionals from engineering and computer science background. Answering to that call, during the 1st Semester of 2018, at the Brazilian Aeronautics Institute of Technology (Instituto Tecnológico de Aeronautica - ITA), a successful Collaborative Interdisciplinary Problem-Based Learning (Co-IPBL) experience took place, for conceptualizing, modeling, developing, and testing a Computer System based upon Big Data, Blockchain Hyperledger, Micro-services, and other emerging technologies applied to Urgent and Emergency Care. The Co-IPBL experience had the participation of a medical technical team from the Hospital of Clinics at the Faculty of Medicine of the University of São Paulo. In the present article, we discuss how value engineering, agile and the business model canvas could help improve functionality benefit, reduce cost, combat waste and reduce complexity. We then propose a process to apply a quantitative method to prioritize valuable User Stories, reducing scope and demonstrating real delivered value as proposed in the Business Model Canvas. For the implementation, the Blockchain Hyperledger was used as a common database of health care information that doctors and providers could access.
Autophosphorylation and ATM activation: Additional sites add to the complexity

Sergei V. Kozlov, Mark E. Graham, Burkhard Jakob, Frank Tobias , Amanda W. Kijas, Marcel Tanuji, Philip Chen, Phillip J. Robinson, Gisela Taucher-Scholz , Keiji Suzuki, Sairai So, David Chen, Martin F. Lavin 1 Queensland Institute of Medical Research, Radiation Biology and Oncology, Brisbane, QLD 4029, Australia 2 Children’s Medical Research Institute, The University of Sydney, Westmead NSW 2145, Australia GSI Helmholtzzentrum für Schwerionenforschung GmbH, Biophysik, Planckstraße 1, D-64291 Darmstadt, Germany 4 Department of Molecular Medicine, Nagasaki University Graduate School of Biomedical Sciences, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan The University of Texas, Southwestern Medical Center at Dallas, 5323 Harry Hinea Boulevard, Dallas, Texas University of Queensland Centre for Clinical Research, Brisbane, Australia
Oil palm frond supplementation can change fatty acid composition of rumen fluid, muscle tissue and blood cholesterol level in crossbred male sheep

Diet composition is the major factor influencing the fatty acid composition of products derived from ruminants. Thirty 7-month-old, Barbados Black Belly × Malin crossbred male sheep were used for the trial to determine the effects of dietary supplementation of oil palm (Eleis guineensis) frond (OPF) on the fatty acid profiles of rumen fluid, muscle tissue and blood lipid parameters. Treatment diets were control diet (CON group, n=10), 25% OPF pellet in diet (% w/w) (HAF group, n=10) and 50% OPF pellet in diet (OPF group, n=10). After 100 days of feeding, eight sheep from each group were slaughtered for sampling of rumen fluid and muscle tissues. The CON group showed fluctuating and increasing total saturated fatty acid (SFA) concentrations in the rumen liquor compared to the OPF group and differed significantly ( P <0.05) at different times of measurement. The SFA in the longissimus dorsi , psoas major , gluteus medius , Semimembranosus and triceps brachii muscles of the CON group were also significantly (P<0.05) higher than the OPF group. For all muscles, C18:3n-3 fatty acid was significantly higher (P<0.05) in the OPF group than in the CON group with minimal impact on the C18:2n-6 and total PUFA n-6. The HDL-Cholesterol values of the OPF group was almost 40% higher than those of the CON group (P ˂ 0.05). The results demonstrated a feasible way to alter the fatty acid composition of mutton based on feeding practices using indigenous fiber source.
International in Computer Science and Software Engineering Information Technology Governance Frameworks: Overview of Information Technology Infrastructure Library (ITIL) Implementation Approaches

— the transition from an Information Technology (IT) system used exclusively to streamline the flows and procedures to an information system support of the strategy will not be achieved without the establishment of a specific framework of analysis and an appropriate organizational structure ensuring an optimal decision-making. The IT governance aims to establish best practices for the management of IT operations, the structures to put in place, their functioning, organization and processes to be implemented so that the IT function can support and develop the strategy and objectives company’s. These best practices are identified in COBIT but also CMMI, ITIL, ISO 27001, ISO 38500 . The purpose of this paper is to make an overview of ITIL implementation approaches. Thus we’ll start with a literature review of these approaches by highlighting the strong points and limitations of each approach. Then we analyze an ITIL implementation case study in a company by focusing on the benefits of implementation, limitations and recommendations. Finally we will do a literature review on critical success factors for implementation approaches by classifying them according to the percentage of citation of each factor. governance
thermodynamical cost of some interpretations of quantum theory.

Here we clarify the assumptions made and conclusions reached in our paper “The thermodynamical cost of some interpretations of quantum theory” [Phys. Rev. A 94 , 052127 (2016)], at the light of the criticisms of Prunkl and Timpson [Stud. Hist. Philos. Sci. Part B: Stud. Hist. Philos. Mod. Phys. 63 , 114 (2018)], and Davidsson (Master thesis, Stockholm University, 2018). We point out some misunderstandings and some weaknesses of the counterexample Prunkl and Timpson present to challenge our conclusion. We thus conclude, once more, that interpretations of quantum theory which consider the probabilities of measurement outcomes to be determined by objective properties of the measured system and satisfy the assumption that the measured system only has ﬁnite memory have a thermodynamical cost.
Comparison of Functional and Antigenic Characteristics of Macrophages and Multinucleated Giant Cells *

Multinucleated giant cells (MGC) ~ are found in a variety of inflammatory disease processes (1, 2). Both monocytes and macrophages appear in the lesions of these diseases before the MGC; and monocytes are thought to be the precursor to both the macrophages and multinucleated cells (1-3). The phagocytic capacity of MGC derived in vivo has been studied using cells adherent to coverslips planted under the skin of rodents (1, 3-6), and MGC derived from cultured mouse macrophages have also been shown to be phagocytic (7, 8). It has been reported that human monocytes can form variable numbers of multinucleated cells in vitro (9-12). However, functional capacities of human MGC that might relate to removal of foreign material or microorganisms have not been defined, and such functions have not been thoroughly studied with MGC of any species. We report here some functional and biochemical characteristics of MGC derived from human blood monocytes cultured in vitro. The characteristics examined are potentially important in mediating the resolution of, or in propagating, the variety of pathologic lesions in which these cells are found.
A Traffic Forecasting Modle Using Adaptive BMO Algorithm Trained Neural Network

Aiming at the short-comings of existing short-term traffic flow forecasting methods, such as low precision, Model is too complex and large computational cost, an adaptive BMO algorithm optimized BP neural network （ BMOA-NN ） algorithm is proposed. The algorithm improves the traditional BMO algorithm by introducing adaptive mechanism, The dynamic adjustment of the grouping parameters of the algorithm according to the variance of fitness, make the balance between local search and global search ability; Modeling the short-term traffic flow problem, The simulation model of the algorithm is realized, and the precision of the calculation is improved and the complexity of the calculation is reduced. The experimental results show that the proposed model can reduce the prediction error by 18.2% ~ 23.7% in the same time. ,
Canted structures in the Mn3+/Mn4+ perovskites

Neutron diffraction and magnetization measurements have been performed on numerous systems with the divalent and monovalent substitution, Pr1−xAx2+Mn1−x3+Mnx4+O3 (A=Ca, Sr, Ba) and Pr1−x/2Ax/2+Mn1−x3+Mnx4+O3 (A=Na, K). The study shows that the transition from the Ay-type (layer) antiferromagnetism in pure PrMnO3 to the ferromagnetism in the mixed-valence systems is not continuous. In a range of about 5%–15% of Mn4+ (x∼0.05–0.15), canted magnetic arrangements of the AyFz type are observed. The interlayer coupling is changed gradually from θ=180° for x=0–0.05 to θ∼90° for x=0.15. For about x=0.15–0.20, the canted phase with 90° coupling coexists with a purely ferromagnetic arrangement of the Fy type. The observed behavior is related to an interplay of the magnetic superexchange and the double exchange.
3D Upper-Body Pose Estimation and Classiﬁcation for Detecting Unhealthy Sitting Postures at the Workplace

—Prolonged sitting in an unhealthy posture is a common cause of back pain and other health problems in ofﬁce workers. People are often not aware that they are sitting in an unhealthy way, the problems this can cause in the long term, and how they should improve their posture. We present a system that is able to provide this information by analyzing people’s postures over several days. The system is fully automatic and requires no worn devices. Instead, data from a depth sensor is used for periodic 3D upper-body pose estimation. This pose estimation is carried out by a convolutional neural network that was trained on synthetic depth data to overcome the lack of available real-world datasets. On this basis, each pose is assigned to one of several common classes of healthy and unhealthy sitting poses. This results in a large collection of body poses and classiﬁcation results, which are used to generate a personalized posture report that includes suggestions for improving the sitting posture. We show experimentally that the system is able to estimate 3D poses and perform pose classiﬁcation with high accuracy.
DragID: A Gesture Based Authentication System

With the use of mobile computing devices with touch screens is becoming widespread. Sensitive personal information is often stored in the mobile devices. Smart device users use applications with sensitive personal data such as in online banking. To protect personal information, code based screen unlock methods are used so far. However, these methods are vulnerable to shoulder surfing or smudge attacks. To build a secure unlocking methods we propose DragID, a flexible gesture and biometric based user authentication. Based on the human modeling, DragID authenticates users by using 6 input sources of touch screens. From the input sources, we build 25 fine grained features such as origin of hand, finger radius, velocity, gravity, perpendicular and so on. As modeling the human hand, in our method, features such as radius or origin is difficult to imitate. These features are useful for authentication. In order to authenticate, we use a popular machine learning method, support vector machine. This method prevents attackers reproducing the exact same drag patterns. In the experiments, we implemented DragID on Samsung Galaxy Note2, collected 147379 drag samples from 17 volunteers, and conducted real-world experiments. Our method outperforms Luca’s method and achieves 89.49% and 0.36% of true positive and false positive. In addition, we achieve 92.33% of TPR in case we implement sequence technique.