Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring deep features from brain tumor magnetic resonance images via transfer learning

Finding appropriate feature representations from radiological images is a vital task for prediction and diagnosis. Deep convolutional neural networks have recently achieved state-of-the-art performance in classification problems from several different domains. Research has also shown the feasibility of using a pre-trained deep neural network as a feature extractor when only a small dataset is available. This paper proposes a novel image feature extraction method for predicting survival time from brain tumor magnetic resonance images using pretrained deep neural networks. Since all tumors are different sizes, we also explore different image resizing methods in the paper. We demonstrate that deep features can result in better survival time prediction with the highest accuracy of 95.45% versus conventional feature extraction methods from magnetic resonance images of the brain.
Employer discrimination and the immutability of ethnic hierarchies

How pervasive is labor market discrimination against immigrants and what options do policymakers and migrants have to reduce it? To answer these questions, we conducted a field experiment on employer discrimination in Sweden. Going beyond existing work, we test for a large range of applicant characteristics using a factorial design. We examine whether migrants can affect their employment chances – by adopting citizenship, acquiring work experience, or signaling religious practice – or whether fixed traits such as country of birth or gender are more consequential. We find no evidence that immigrants can affect their employment chances by any of the tested means. Rather, ethnic hierarchies are critical: callback rates decline precipitously with the degree of ethno-cultural distance, leaving Iraqis and Somalis, especially if they are male, with much reduced employment chances. These findings highlight that immigrants have few tools at their disposal to escape ethnic penalties and that efforts to reduce discrimination must address employer prejudice.
Diabetes Mellitus in Outpatients in Debre Berhan Referral Hospital, Ethiopia

Introduction. Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. Most people with diabetes live in low- and middle-income countries and these will experience the greatest increase in cases of diabetes over the next 22 years. Objective. To assess the prevalence and associated factors of diabetes mellitus among outpatients of Debre Berhan Referral Hospital. Methods and Materials. A cross-sectional study was conducted from April to June 2015 among 385 patients. Random quota sampling technique was used to get individual patients and risk factors assessment. Patients diabetes status was ascertained by World Health Organization Diabetes Mellitus Diagnostic Criteria. The collected data were entered, cleaned, and analyzed and Chi-square test was applied to test any association between dependent and independent variable. Result. Out of the total 385 study patients, 368 have participated in the study yielding a response rate of 95.3%. Concerning clinical presentation of diabetes mellitus, 13.3% of patients reported thirst, 14.4% of patients declared polyurea, and 14.9% of patients ascertained unexplained weight loss. The statistically significant associated factors of diabetes mellitus were hypertensive history, obesity, the number of parities, and smoking history. Conclusion. The prevalence of diabetes mellitus among outpatients in Debre Berhan Referral Hospital was 0.34% and several clinical and behavioral factors contribute to the occurrence of diabetes mellitus which impose initiation of preventive, promotive, and curative strategies.
The valence bond glass phase

We show that a new glassy phase can emerge in the presence of strong magnetic frustration and quantum fluctuations. It is a valence bond glass (VBG). We study its properties solving the Hubbard-Heisenberg model on a Bethe lattice within the large-N limit introduced by Affleck and Marston. We work out the phase diagram that contains Fermi liquid, dimer and valence bond glass phases. This new glassy phase has no electronic or spin gap (although a pseudo-gap is observed), it is characterized by long-range critical valence bond correlations and is not related to any magnetic ordering. As a consequence, it is quite different from both valence bond crystals and spin glasses.
Growth Expectations, Dividend Yields, and Future Stock Returns

According to the dynamic version of the Gordon growth model, the long-run expected return on stocks, stock yield, is the sum of the dividend yield on stocks plus some weighted average of expected future growth rates in dividends. We construct a measure of stock yield based on sell-side analysts' near-term earnings forecasts that predicts US stock index returns well, with an out-of-sample R-squared that is consistently above 2% at monthly frequency over our sample period. Stock yield also predicts future stock index returns in the US and other G7 countries and returns of US stock portfolios formed by sorting stocks based on firm characteristics, at various horizons. The findings are consistent with a single dominant factor driving expected returns on stocks over different holding periods. That single factor extracted from the cross section of stock yields using the Kelly and Pruitt (2013) partial regressions method predicts stock index returns better. The performance of the Binsbergen and Koijen (2010) latent factor model for forecasting stock returns improves significantly when stock yield is included as an imperfect observation of expected return on stocks. Consistent with folk wisdom, stock returns are more predictable coming out of a recession. Our measure performs as well in predicting stock returns as the implied cost of capital, another common stock yield measure that uses additional information.
Motion based remote camera control with mobile devices

With current digital cameras and smartphones, taking photos and videos has never been easier. However, it is still difficult to take a photo of a brief action at the right time. In addition, editing captured videos, such as modifying the playback speed of some parts of a video, remains a time consuming task. In this work we investigate how the motion sensors embedded in mobile devices, such as smartphones, can facilitate camera control. In particular, we show two families of applications: automatic camera trigger control for jump photos and automatic playback speed control (video speed ramping) for action videos. Our approach uses joint devices: a remote camera takes a photo or a video of the scene and it is controlled by the motion sensor of a mobile device, either during or after recording. This allows casual users to achieve visually appealing effects with little effort, even for self portraits.
Practice style traits: do they help explain practice behaviours of stroke rehabilitation professionals?

RATIONALE The gap in knowledge translation from research to clinical practice is under scrutiny in stroke rehabilitation. One possible reason for this gap may be a poor understanding of clinicians' practice style traits and how they influence practice behaviours. OBJECTIVES To identify the prevalence of practice style traits in physical therapists and occupational therapists working in stroke rehabilitation and, to explore associations between these traits and practice behaviours, where practice behaviours are defined as the clinicians' reasons for choosing assessments and interventions used in practice. The influence of more traditional personal and organizational factors on practice behaviours was also explored. DESIGN Cross-sectional survey of a representative random sample of 243 clinicians (117 occupational therapists and 126 physical therapists) working across the continuum of stroke care in Ontario, Canada. METHODS A telephone-administered validated clinical practice survey elicited information in 4 areas: practice style traits using the validated Practice Style Questionnaire, therapists' reasons for choosing assessments and interventions (practice behaviours), personal factors and organizational factors. RESULTS For both disciplines, the most prevalent trait was pragmatist and the least prevalent was seeker. Seekers were the most likely to use evidence-based reasons for choosing assessments, but this finding did not reach significance (chi2 = 5.430, df = 3; p = 0.14). The most typical reason for choosing an intervention was that the clinician had learned it during professional training, an interesting finding given that approximately half of clinicians had more than 10 years of experience. Of the 21 potential explanatory variables examined, few explained clinicians' reasons for choosing assessments or interventions. CONCLUSION While understanding practice traits is not going to be the single solution to closing the knowledge translation gap, it may help to guide best practice implementation strategies.
Research Methodologies in Science Education: Qualitative Data

Tony, a geology graduate student, is going to be observing students in an introductory classroom in an attempt to determine how the course is affecting student learning. He is interested in determining not only the change in students' understanding of geological concepts, but also the effect of the course on student attitudes, opinions, and interactions with their peers. He has also decided to collect examples of student work and interview students at the end of the semester.
MapReduce Triangle Enumeration With Guarantees

We describe an optimal randomized MapReduce algorithm for the problem of triangle enumeration that requires O(E3/2/(M√m) rounds, where m denotes the expected memory size of a reducer and M the total available space. This generalizes the well-known vertex partitioning approach proposed in (Suri and Vassilvitskii, 2011) to multiple rounds, significantly increasing the size of the graphs that can be handled on a given system. We also give new theoretical (high probability) bounds on the work needed in each reducer, addressing the "curse of the last reducer". Indeed, our work is the first to give guarantees on the maximum load of each reducer for an arbitrary input graph. Our experimental evaluation shows the scalability of our approach, that it is competitive with existing methods improving the performance by a factor up to 2X, and that it can significantly increase the size of datasets that can be processed.
Improving interventions for parents of children and young people with autism spectrum disorder (ASD) in CAMHS

With ever increasing recognition and diagnosis of autism spectrum disorders (ASD) in children within mainstream schooling, there was a need for City and Hackney Child and Adolescent Mental Health Services to develop innovative interventions to meet the needs of a large client group, with limited clinician resource. The importance of psychoeducation about ASD for parents of children recently diagnosed is understood; however, feedback from our service users highlighted the additional need for ongoing access to a network of professional support. Using quality improvement (QI) methodology, we aimed to develop a sustainable regular group programme that was relevant for parents. The total number of parents attending each monthly group over a specific period of time was tracked (from February 2015 to May 2017). A service user questionnaire was devised to gain feedback from each group on parental confidence in managing a child with ASD and their satisfaction. These were given to parents at the end of each group. The Plan Do Study Act cycles were applied and evaluated in the QI framework to assess the impact of the following change ideas: letter reminders, a focus group, an email information and reminder system, and a parent co-lead group. Overall, attendance at the monthly groups increased and remained stable. Satisfaction with the groups was high (eg, 91% of the attendees were either ‘Quite Satisfied’ or ‘Extremely Satisfied’). Of those attending, 82% reported increases in their own confidence in managing their child with ASD. The QI approach allowed us to systematically develop efficient systems and cost-effective ways to run interventions within our ASD pathway. Parents reported high levels of satisfaction with the groups and increased confidence in their ability to parent their child with ASD.
Iron Status Predicts Malaria Risk in Malawian Preschool Children

Introduction Iron deficiency is highly prevalent in pre-school children in developing countries and an important health problem in sub-Saharan Africa. A debate exists on the possible protective effect of iron deficiency against malaria and other infections; yet consensus is lacking due to limited data. Recent studies have focused on the risks of iron supplementation but the effect of an individual's iron status on malaria risk remains unclear. Studies of iron status in areas with a high burden of infections often are exposed to bias. The aim of this study was to assess the predictive value of baseline iron status for malaria risk explicitly taking potential biases into account. Methods and materials We prospectively assessed the relationship between baseline iron deficiency (serum ferritin <30 µg/L) and malaria risk in a cohort of 727 Malawian preschool children during a year of follow-up. Data were analyzed using marginal structural Cox regression models and confounders were selected using causal graph theory. Sensitivity of results to bias resulting from misclassification of iron status by concurrent inflammation and to bias from unmeasured confounding were assessed using modern causal inference methods. Results and Conclusions The overall incidence of malaria parasitemia and clinical malaria was 1.9 (95% CI 1.8–2.0) and 0.7 (95% CI 0.6–0.8) events per person-year, respectively. Children with iron deficiency at baseline had a lower incidence of malaria parasitemia and clinical malaria during a year of follow-up; adjusted hazard ratio's 0.55 (95%-CI:0.41–0.74) and 0.49 (95%-CI:0.33–0.73), respectively. Our results suggest that iron deficiency protects against malaria parasitemia and clinical malaria in young children. Therefore the clinical importance of treating iron deficiency in a pre-school child should be weighed carefully against potential harms. In malaria endemic areas treatment of iron deficiency in children requires sustained prevention of malaria.
Roman bondage in graphs

A Roman dominating function on a graph G is a function f : V (G) → {0, 1, 2} satisfying the condition that every vertex u for which f(u) = 0 is adjacent to at least one vertex v for which f(v) = 2. The weight of a Roman dominating function is the value f(V (G)) =
Psychopathology in person with and without co-morbid autism

iv INTRODUCTION . 1 AUTISM SPECTRUM DISORDERS . 2 History. 2 Epidemiology of Autism Spectrum Disorders . 9 Autism Spectrum Disorders and Comorbid Psychopathology . 13 PSYCHOPATHOLOGY IN THOSE WITH ID-ASD . 26 INTELLECTUAL DISABILITY . 30 CURRENT STATUS . 32 Irrelevance of Support Specifiers. 33 DIFFERENTIATION BETWEEN ID AND ASD . 34 PURPOSE . 37 RATIONALE . 39 RESEARCH QUESTIONS AND HYPOTHESES . 40 METHOD . 41 Participants . 41 Power . 43 Measure . 44
Tying by an Essential-Good Monopolist: The Role of Multihoming and the Reversible Tie

We explore an essential-good monopolist's motivations for tying and the role of multihoming and the reversible tie when there are network effects in a complementary market. We consider the configuration where consumers purchase a system sequentially and a subset of consumers multihome. In contrast to the existing argument, we show that the essential-good monopolist may have an incentive to engage in tying. In the case of irreversible tie, tying can be used as a strategic device to restore monopoly power in the essential product market, which is hurt by multihoming consumers. In that case, tying works as a foreclosure mechanism for an existing or potential rival in the competitive segment. Furthermore, we extend our analysis to the case where the tie is reversible. We show that tying can also be made more profitable by squeezing the rival's complementary good price even though tying may not foreclose the rival completely.
2D Fokker–Planck models of rotating clusters

Globular clusters rotate significantly, and with the increasing amount of detailed morphological and kinematical data obtained in recent years on galactic globular clusters many interesting features show up. We show how our theoretical evolutionary models of rotating clusters can be used to obtain fits, which at least properly model the overall rotation and its implied kinematics in full 2D detail (dispersions, rotation velocities). Our simplified equal mass axisymmetric rotating model provides detailed two-dimensional kinematical and morphological data for star clusters. The degree of rotation is not dominant in energy, but also non-negligible for the phase-space distribution function, shape and kinematics of clusters. Therefore, the models are well applicable for galactic globular clusters. Since previously published papers on that matter by us made it difficult to do detailed comparisons with observations, we provide a much more comprehensive and easy-to-use set of data here, which uses as entries dynamical age and flattening of observed cluster and then offers a limited range of applicable models in full detail. The method, data structure and some exemplary comparison with observations are presented. Future work will improve modelling and data base to take a central black hole, a mass spectrum and stellar evolution into account.
A qualitative investigation of obese men's experiences with their weight.

OBJECTIVES To investigate obese men's health behaviors and strategies for change. METHODS Qualitative interviews with 36 men (BMI 30 and over). RESULTS All men felt personally responsible for their weight gain. Sedentary lifestyles, stress, lack of worklife balance and weight-based stigma were all significant causes of weight gain and barriers to weight loss. These factors also contributed to men's unwillingness to seek help for their over-weight. CONCLUSION Addressing the self-blame and stigma associated with obesity is important in developing strategies to improve the health and well-being of obese men.
Galectin-3 in diabetic patients

Abstract Galectin-3 is a versatile molecule which exerts several and sometimes opposite functions in various pathophysiological processes. Recently, galectin-3 has gained attention as a powerful predictor of heart failure and mortality, thus becoming a useful prognostic marker in clinical practice. Moreover, though not specifically investigated in diabetic cohorts, plasma levels of galectin-3 correlated with the prevalence of diabetes and related metabolic conditions, thus suggesting that pharmacological blockade of this lectin might be successful for treating heart failure especially in subjects suffering from these disorders. Indeed, galectin-3 is considered not only as a marker of heart failure, but also as a mediator of the disease, due to its pro-fibrotic action, though evidence comes mainly from studies in galectin-3 deficient mice. However, these studies have provided contrasting results, with either attenuation or acceleration of organ fibrosis and inflammation, depending on the experimental setting and particularly on the levels of advanced glycation endproducts (AGEs)/advanced lipoxidation endproducts (ALEs), of which galectin-3 is a scavenging receptor. In fact, under conditions of increased AGE/ALE levels, galectin-3 ablation was associated with tissue-specific outcomes, reflecting the AGE/ALE-receptor function of this lectin. Conversely, in experimental models of acute inflammation and fibrosis, galectin-3 deficiency resulted in attenuation of tissue injury. There is a need for prospective studies in diabetic patients specifically investigating the relation of galectin-3 levels with complications and for further animal studies in order to establish the effective role of this lectin in organ damage before considering its pharmacological blockade in the clinical setting.
Detecting and reducing redundancy in alarm networks

Alarm systems are vital for the safe operation of almost all large-scale industrial and technical installations, such as chemical plants or power stations. The optimization of alarm systems has great potential to improve the safety of these installations, and also to increase their profitability through the reduction of automated shut-downs and suboptimal operation modes. In this work we present a new approach to alarm system optimization through the identification of redundant alarms. Our approach is based on a ranking of alarms by their connectivity in the alarm network. We also propose an overall redundancy measure for the alarm system which can be used to monitor performance improvements after redundant alarms have been removed. We present an example demonstrating that our ranking technique provides operational staff with useful information, allowing them to enhance the effectiveness of their existing alarm systems.
Forming project groups while learning about matching and network flows in algorithms

The matching problem in bipartite graphs is the basis for many applications that have become especially prominent with the advent of online markets that connect two entities (e.g., job-seekers and employers). Its algorithmic basis is the max-flow problem in networks, a topic that is often covered in introductory algorithms texts and courses. Separately, the Computer Science education literature is abundant with examples which indicate that the quality of the experience in the implementation of programming tasks is enhanced when done in groups. In this paper, we describe the application of a network-flow-based matching algorithm in bipartite graphs to form project groups in the algorithms course at the Colorado School of Mines (CSM). This activity simultaneously provides students with an immersive experience in a bipartite matching application. We present a small exploratory study on the effectiveness of the activity.