Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of three breast imaging techniques using 4-AFC human observation study

X-ray mammography is the gold standard for detecting malignancies in a breast cancer screening context. However, limited angle tomosynthesis has now started to be used in screening due to its ability to remove overlying image clutter. However, breast CT is a method, which can potentially remove all overlying clutter through the use of tomographic image reconstruction. The aim of this work is to investigate whether breast cone-beam computed tomography (CBCT) can provide better lesion detectability compared to 2D mammography or digital breast tomosynthesis (DBT). Lesions with a diameter of 4 mm, 5 mm and 6 mm have been inserted in a simulated breast phantom. In total 180 images are analysed, out of which 90 images contain lesions (equally divided between the 4 mm, 5mm and 6mm diameter lesions) and the rest represent normal breast tissues. The TIGRE (Tomographic Iterative GPU-based Reconstruction) has been used to simulate 360 projections and to reconstruct the images using the FeldKamp, Davis and Kress (FDK) algorithm. Scattered radiation and Poisson noise have also been added to the projections prior the image reconstruction. In total 10 observers, some with, and some without experience of mammography images, have been used as observers for this preliminary 4AFC study. The analysis of the 4AFC study shows that the mean minimum detectable lesion size for the breast CBCT is 2.96±0.23 mm with a 95% confidence intervals of [2.73, 3.19].
Online Impulse Buying Behaviour: Case Study On Users Of Tokopedia

This article aims to find out the phenomenon of impulsive buying which is influenced by the ease of use and usefulness of information technology that mediates the pleasure of shopping, in this case the writer chooses tokopedia as the object of research. Unplanned buying behavior is an interesting phenomenon to examine because it is a potential for developing market share. The sample determination method used was 149 respondents. The population in this study is Tokopedia online shop users. Data analysis technique uses descriptive analysis, which is to obtain a picture of the respondent's tendency to answer, and inferential analysis to test the model developed, while the analysis technique used is Structural Equation Modeling (SEM). The test results show that the ease of use and usefulness of technology has a positive effect in supporting shopping pleasure, while shopping pleasure can explain the factors that influence impulsive purchases.
Concept Design and Analysis of Wind-Tracing Floating Offshore Wind Turbines

Most of the existing floating offshore wind turbines (FOWT), whether in concept or built, host a single turbine. Structures that can host multiple turbines have received attention in recent years, mainly with the aim of reducing the overall cost of energy production and maintenance. A concept challenge of placing multiple wind turbines on a single floating platform is that under variable wind directions, the leading turbines may block the wind against the trailing turbines. In this work, concept design of a wind-tracing floating structure accommodating three wind turbines is presented. The triangular-shapefloating platform is made of pre-stressed concrete, and the turbines are located on the corners. The floating structure uses a single-point mooring system which allows for the entire structure to rotate in response to the change of wind direction. Due to the particular configuration of the floating structure, it is essential to consider the wind, wave and current loads, along with the response of the structure, simultaneously. Response of the FOWT to simultaneous environmental loads from different directions is studied by use of the constant panel approach of the Green function method, subject to constant wind loads on the turbines and linear mooring loads. We also consider the elasticity of the structure by use of finite element analysis, coupled with the hydro- and aero-dynamic loads and responses.
Designing Modern Compact Microstrip Planar Quadband Bandpass Filter for Hand Held Wireless Applications

Abstract This paper presents a modern compact quad-band bandpass filter (BPF) using dual-mode stub loaded half wave (λ/2) resonators, where a couple of directly fed resonators are loaded with two identical inner resonators such that the direct fed resonators will act as feeding structure for the loaded resonators. Based on the proposed stub loaded resonators, a modern filter with seven transmission zeros (TZs) is designed by folding the two identical inner resonators. The proposed design has a symmetrical geometry, therefore even-odd mode analysis is used to predict the resonant frequencies of the passbands. The first and second passbands are obtained through fundamental odd and even modes respectively while the third one is achieved by placing loaded inner resonators in the proposed design. The second even harmonic of the direct fed resonators is utilized to achieve the fourth passband and is controlled by the stubs loaded at the middle of the resonators. The filter is simulated and fabricated for the purpose of validation, wherein a good agreement can be seen in both simulated and experimental results.
7 Monocyte subpopulations in patients following st-elevation myocardial infarction: implications for post-infarction left ventricular remodelling and clinical outcomes

Introduction In an era of appreciation of inflammatory role in MI, we describe a potential mechanism through which the innate immune system affects both outcome and ventricular remodelling in STEMI patients. Method STEMI patients were recruited within 24 hours of presentation. Monocyte subsets and their phagocytic functional activity were measured by flow cytometry using nuclear differentiation of surface markers: CD14; CD16 and CCR2. Patients underwent echocardiograms during the index events and 6 months post STEMI, to assess LV remodelling and global longitudinal strain (GLS) and global circumferential strain (GCS). Patients were followed up at six months and annually for MACE. Results In total 211 patients with STEMI were recruited ( 69% males; Age 61±11). MACE occurred in 76 patients during a median follow up of 37 months. A multivariate COX regression model indicated total counts of monocytes, Mon 1, and Mon 2 as well as their phagocytic activity were predictive of MACE. High Mon1 and Mon 2 counts in the 3rd and 4th quartiles, were strongly predictive of MACE, an effect that was maintained for more than 2 years. Incorporating Mon1 and Mon2 counts in TIMISTEMI score improved the ability to predict poor clinical outcome in STEMI patients: C-statistics indicated the area under the curve (AUC) improved from 0.67 (for TIMI STEMI score), to an AUC 0.77 when including total monocyte counts (TIMI Mon score). Total monocyte count, Mon 1 and Mon 2 were predictive of negative ventricular remodelling (>15% in LVESVi). GLS and GCS were also significantly correlated with total monocyte, Mon 1 and Mon 2 levels. Conclusion Mon1 and Mon2 through their phagocytic activity alter both patient outcome and ventricular remodelling post STEMI. These results could be a stepping stone into targeted anti-inflammatory therapy in management of myocardial infarction.
Characterizing and Enforcing Consistency of Online Services

While several proposals for the specification and implementation of various consistency models exist, little is known about what is the consistency currently offered by online services with millions of users. Such knowledge is important, not only because it allows for setting the right expectations and justifying the behavior observed by users, but also because it can be used for improving the process of developing applications that use APIs offered by such services and for creating tools that facilitate this process. To fill this gap, in the first part of this thesis, we present a measurement study of the consistency of the APIs exported by four widely used Internet services, the Facebook Feed, Facebook Groups, Blogger, and Google+. To conduct this study, our work develops a simple, yet generic methodology comprising a small number of tests, which probe these services from a user perspective, and try to uncover consistency anomalies, and reports on the analysis of the data obtained from running these tests for a period of several weeks. Our measurement study shows that some of these services do exhibit consistency anomalies, including some behaviors that may appear counter-intuitive for users, such as the lack of session guarantees for write monotonicity. The results show that developers have to deal with consistency anomalies, to provide consistency guarantees they need. To address the challenge of enforcing consistency guarantees on top of existing systems, in the second part of this thesis, we show that it is possible to deploy a middleware between the application and the service, which enables a fine-grained control over the session guarantees that comprise the consistency
A mother’s love knows no bounds: Exploring ‘good mother’ expectations for mothers involved with children’s services due to their partner violence

This article considers the ideology surrounding ‘good mother’ expectations for mothers from British, lower socio-economic classes who have involvement from children’s services due to their (ex) partners’ violent behaviour. What was expected from ‘good mothers’ historically and currently is considered, before specific attention is paid to the expectations set for mothers who are known to children’s services. The research aims were to understand what these mothers themselves consider a ‘good mother’ to be. Fifteen mothers from the UK who had had involvement with Children’s Services were interviewed; all participants defined themselves as working class and their ages ranged from 20 to 48. The majority of participants defined their ethnicity as white, with two participants choosing ‘mixed’. Data were reviewed thematically and five main themes arose. This article explores that, whilst some mothers feel able to re-work the expectations placed on them to make them fit with their daily lives, this was not true for the majority of the participants within this study.
Bound state solutions of the Schrödinger equation with energy-dependent molecular Kratzer potential via asymptotic iteration method

In this paper, we obtained the exact bound state energy spectrum of the Schrodinger equation with energy dependent molecular Kratzer potential using asymptotic iteration method (AIM). The corresponding wave function expressed in terms of the confluent hypergeometric function was also obtained. As a special case, when the energy slope parameter in the energy-dependent molecular Kratzer potential is set to zero, then the well-known molecular Kratzer potential is recovered. Numerical results for the energy eigenvlaues are also obtained for different quantum states, in the presence and absence of the energy slope parameter. These results are discussed extensively using graphical representation. Our results are seen to agree with the results in literature.
Measurement Model of Hospital Performance for Achieving Hospital Mission in Indonesia

Performance measurement is an important issue. This reminds that healthcare industry characteristic is unique rather than others. Health care with its all activities is a “high risk” industry. Performance measurement is the centre of quality improvement. From this, many factors or reasons related to excellent services can be identified. This research aimed to get quality dimensions that could be used as performance measurement in hospital as a health care provider. The direction of this performance measurement is as guidance on achieving hospital mission. With limited resources, Hospital needs priority to achieve its mission, so its need to be known wisely the critical dimension that correlate to a hospital mission. The design of this research was an operational research that using both qualitative and quantitative method in the government and private hospital in Indonesia. The result showed that there is a correlation between Patient Centeredness dimension with Clinical Effectiveness, Efficiency, Staff Orientation, Responsive Governance and Design dimensions, where all of dimension (except Responsive Governance) showed a positive correlation to the hospital mission variable. Hereby its correlation of equation: Hospital Mission = 0.118 Clinical Effectiveness + 0.348 Efficiency – 0.034 Responsive Governance + 0.182 Staff Orientation + 0.268 Design. Where the influence of Patient Centeredness dimension to Clinical Effectiveness is about 0.578, Efficiency is about 0.488, Staff Orientation is about 0.478, Responsive Governance is about 0.609 and Design is about 0.351. From structural model equation test with Partial Least Square was summarized that the big affluence dimension to the mission is Efficiency and Design, while Responsive Governance is not a critical dimension in this model due to it has a negative correlation to the mission. The model consists of quality dimensions for hospital performance on achieving hospital mission. This model is called Mission Achievement Tools in Hospital model (MATH). MATH model could be functioned as a management system, strategic management tools, and as a dashboard on hospital organization’s trip to achieve the mission that can be used by The Ministry of Health to develop policy especially in hospital area. Keywords— Performance Measurement, Hospital Mission,
Improving VAEs' Robustness to Adversarial Attack

Variational autoencoders (VAEs) have recently been shown to be vulnerable to adversarial attacks, wherein they are fooled into reconstructing a chosen target image. However, how to defend against such attacks remains an open problem. We make significant advances in addressing this issue by introducing methods for producing adversarially robust VAEs. Namely, we first demonstrate that methods used to obtain disentangled latent representations produce VAEs that are more robust to these attacks. However, this robustness comes at the cost of reducing the quality of the reconstructions. We, therefore, introduce a new hierarchical VAE, the $\textit{Seatbelt-VAE}$, which can produce high-fidelity autoencoders that are also adversarially robust. We confirm the capabilities of the Seatbelt-VAE on several different datasets and with current state-of-the-art VAE adversarial attacks.
Inflammatory and Biochemical Biomarkers in Response to High Intensity Resistance Training in Trained and Untrained Men

Background: A session of resistance training (RT) will lead to metabolic and inflammatory changes. The aim of this study is to investigate metabolic and inflammatory changes in trained and untrained men. Methods: Twenty-eight young healthy men (14 trained and 14 untrained people) participated in this present study. To assess metabolic and inflammatory responses and muscle damage, blood samples were gathered before, immediately and 1 hour after training. Results: The percentage of muscle mass and baseline CK activity were significantly greater within the trained than the untrained group. After conducting a RT session, there was a significant reduction in insulin concentration and resistance within the two groups and in blood glucose only within the untrained group. In addition, RT was also associated with an increase in muscle damage biomarkers, CK, and LDH after training. Unlike CK, the activity of LDH was reduced during 1 hour of training (P < 0.05). Among the different inflammatory markers, only IL-6 concentration significantly increased within the two groups, which remained after 1 hour of training at the untrained group (P < 0.05). Conclusions: The results of this study have shown that a RT session causes metabolic and inflammatory changes. The inflammatory response is significantly greater among subjects within the untrained group. Moreover, blood pressure response was also greater within the untrained group, which is directly related to the training intensity. However, there were no significant differences in metabolic responses and muscle damages between the trained and untrained subjects.
Essays on Advertising Spending During the Great Recession and Real Earnings Management Using Advertising Budgets

In my main dissertation essay, I investigate advertising spending during a recession. Advertising plays an important role in creating awareness, preference and purchase intent for many products and services. However, advertising is often cut when a firm needs to control costs. This empirical study examines a unique set of factors which motivated 553 firms to change their advertising spending during the Great Recession. The first half of the Great Recession had a moderate 2% decline in GDP and 1% to 2% cuts in advertising spending. The seasonality effect was weaker, which indicates that firms were not as likely to carryover spending from the prior year. The peak of the Great Recession had a GDP decline as high as 7%, which is considered severe. Average advertising spending declined by 13%. In addition to the seasonality effect, decreasing sales decreased advertising spending. Increasing firm risk tends to decrease advertising spending during the peak of the Great Recession, but not before. Finally, firms in high advertising intensity industries, where advertising is strategically important, had modest budget cuts. In contrast, firms in low-intensity industries had much larger percentage cuts.The second essay examines real earnings management using advertising budgets” examines. Real earnings management occurs when managers change real activities to meet or beat important earnings benchmarks. Advertising has a limited short-term impact on firm sales for many products. Therefore, when a firm’s earnings are below key benchmarks for a fiscal quarter (year), managers are compelled to reduce advertising expenditures to boost earnings. This study examines factors which persuade firms to manage earnings using advertising budgets. Similar to earlier studies, we find firms suspect of managing earnings upwards reducing advertising expenses. The findings indicate that B2C firms are more likely to manage earnings by reducing advertising expenses than B2B firms. The findings also reveal that suspect firms which spend more in high advertising elasticity mediums such as TV do not reduce advertising spending as much as firms which spend more in low advertising elasticity mediums such as newspapers and magazines. The study also find evidence to suggest that suspect firms which report advertising expenditure in their income statement make smaller advertising spending cuts than firms which don’t report advertising expenditure. Finally, earnings management activity is much stronger during the last quarter of the fiscal year.
Rules of Play

Massively multiplayer online role-playing games (MMORPGs) constitute social jurisdictions governed by rules of play. When we consider the work of Johan Huizinga and subsequent theorists of human play activities, we find that ludic rules differ from legal rules in important ways. The goals of play also differ from the goals of law. In applying law to MMORPGs and other virtual worlds, it is important to recognize that jurisdictions of play are structured in ways that are fundamentally different from the ways traditional legal rules are structured.
EFFECT OF TEMPERATURE AND RELATIVE HUMIDITY ON THE BEHAVIOR OF CAPYBARAS (Hydrochoerus hydrochaeris) IN AN URBAN AREA

The capybara, Hydrochoerus hydrochaeris (Rodentia, Caviidae), is a species adapted to diverse environments, including urbanized areas, where its populations can reach high densities. In this study, we searched the behavioral pattern of capybaras in urban areas, and investigated the effect of temperature and relative humidity in its activity pattern. The study was conducted in an urban area of the Aquidauana municipality in the state of Mato Grosso do Sul, Brazil. Observations occurred between June 2014 and March 2015, using the scan sampling method. We found that capybaras spent most of your time in aquatic activities and rest. Temperature was positively correlated with the percentage of individuals engaged in aquatic activities. Relative humidity was negatively correlated with the percentage of individuals at rest and positively correlated with aquatic activities. Capybaras exhibit behavioral thermoregulation, which explains the large amount of time spent on aquatic activities with the increase in temperature and relative humidity.
Application of Wavelet Transform in Image Super-Resolution

Most of learning-based super-resolution (SR) methods reconstructed high resolution (HR) image using a very deep convolutional neural network (CNN). CNN-based methods are used to process low resolution images, the predicted image is too smooth and some texture details are ignored. In order to improve the quality of the recovered high resolution image, wavelet transform is applied at the end of our model. Firstly, the prediction image is obtained through the CNN model; then, the predicted image and the ground truth image are processed into four frequency channels by wavelet transform; at last, four frequency channels and original image are considered when calculating loss. Compared with the original CNN model, the results of adding wavelet transform is obviously improved.
Probabilistic Filter and Smoother for Variational Inference of Bayesian Linear Dynamical Systems

Variational inference of a Bayesian linear dynamical system is a powerful method for estimating latent variable sequences and learning sparse dynamic models in domains ranging from neuroscience to audio processing. The hardest part of the method is inferring the model's latent variable sequence. Here, we propose a solution using matrix inversion lemmas to derive what may be considered as the Bayesian counterparts to the Kalman filter and smoother, which are particular forms of the forward-backward algorithm that have known properties of numerical stability and efficiency that lead to cost growing linear with time. Opposed to existing methods, we do not augment the model dimensionality, use Cholesky decompositions or inaccurate numerical matrix inversions. We provide mathematical proof and empirical evidence that the new algorithm respects parameter expected values to more accurately infer latent state statistics. An application to Bayesian frequency estimation of a stochastic sum of sinusoids model is presented and compared with state-of-the-art estimators.
Control performance‐based fault detection and fault‐tolerant control schemes for a class of nonlinear systems

The objective of this paper is to develop performance‐based fault detection (FD) and fault‐tolerant control (FTC) schemes for a class of nonlinear systems. To this end, the representation forms of nonlinear systems with faults and the controller parameterization forms are studied first with the aid of the nonlinear factorization technique. Then, based on the stable kernel representation and the stable image representation of the faulty nonlinear system, the stability performance of the closed‐loop system is addressed, respectively. The so‐called fault‐tolerant margin is defined to evaluate the system fault‐tolerant ability. On this basis, two performance‐based FD schemes are developed aiming at detecting the system performance degradation caused by system faults. Furthermore, to recover the system stability performance, two performance‐based FTC strategies are proposed based on the information provided by the FD unit. In the end, a numerical example and a case study on the three‐tank system are given to demonstrate the proposed results.