Miracle-dz/UniFAR-FTUs huggingface dataset:
Granulocytic Sarcoma as the First Sign of Acute Leukemia in Childhood

Acute myeloid leukemia (AML) may rarely involve the orbit as a solid tumor termed granulocytic sarcoma. This report describes the case of a child who presented with rapidly progressive unilateral proptosis and was diagnosed as rhabdomyosarcoma. However subsequent examination of the peripheral blood film revealed AML. Thus proptosis may present as the initial manifestation of AML.
Optimizing Generalized Rate Metrics through Game Equilibrium

We present a general framework for solving a large class of learning problems with non-linear functions of classification rates. This includes problems where one wishes to optimize a non-decomposable performance metric such as the F-measure or G-mean, and constrained training problems where the classifier needs to satisfy non-linear rate constraints such as predictive parity fairness, distribution divergences or churn ratios. We extend previous two-player game approaches for constrained optimization to a game between three players to decouple the classifier rates from the non-linear objective, and seek to find an equilibrium of the game. Our approach generalizes many existing algorithms, and makes possible new algorithms with more flexibility and tighter handling of non-linear rate constraints. We provide convergence guarantees for convex functions of rates, and show how our methodology can be extended to handle sums of ratios of rates. Experiments on different fairness tasks confirm the efficacy of our approach.
UNIVERSITY OF FLORIDA THESIS OR DISSERTATION FORMATTING TEMPLATE

Chair: Kanika Sharma Inglett Major: Soil and Water Science Extracellular enzyme activity is a rate limiting step of soil organic matter decomposition. These enzyme activities are direct responses of dominant soil microbial communities to nutrient availability, nutrient limitations and the existing external environmental conditions in soils. Soil nutrient limitations also affect microbial biomass and have been shown alter relative abundances of microbial communities thereby, significantly influencing the production and activities of extracellular enzymes. Although there have been few studies investigating enzyme kinetics, most studies have focused on upland soils and there are not many studies on wetland soils. The overall goal of this study was to investigate how the nutrient limitation in soils affects the kinetic parameters of the extracellular enzymes and if these parameters exhibit differences in their temperature sensitivity to soil warming. In this laboratory study, Vmax and Km of six extracellular enzymes (phosphatase, bisphosphatase, ß-D-glucosidase, cellobiohydrolase, leucine aminopeptidase, N-Acetyl-ß-D glucosaminidase) was determined in soils from a subtropical wetland exhibiting an increasing gradient of phosphorus (P). Temperature sensitivity of these enzymes were also determined for the
Macroscopic limits, analytical distributions, and noise structure for stochastic gene expression with coupled feedback loops

Gene expression in individual cells is an inherently stochastic process with large fluctuations. Here we present a comprehensive analysis for stochastic gene expression kinetics in a minimal coupled gene circuit with positive-plus-negative feedback. Our theory unifies and generalizes the discrete and continuous gene expression models proposed previously by viewing the latter as various macroscopic limits of the former. Two types of macroscopic limits are obtained: the Kurtz limit applies to proteins with large burst frequencies and the Levy limit applies to proteins with large burst sizes. We also derive the analytic steady-state distributions of the protein abundance for both the discrete chemical master equation model and its two macroscopic limits. Furthermore, we obtain the analytic time-dependent distribution of the protein concentration for the classical Friedman-Cai-Xie random bursting model. Our analytic results reveal a strong synergistic interaction between positive and negative feedback loops and a critical phase-transition-like phenomenon in the regime of slow promoter switching. Our theory is also applied to study the intrinsic noise structure of stochastic gene expression in coupled gene circuits and a complete decomposition of noise in terms of five different biophysical origins is provided.
A Benchmark for Fact Checking Algorithms Built on Knowledge Bases

Fact checking is the task of determining if a given claim holds. Several algorithms have been developed to check claims with reference information in the form of facts in a knowledge base. While individual algorithms have been experimentally evaluated in the past, we provide the first comprehensive and publicly available benchmark infrastructure for evaluating methods across a wide range of assumptions about the claims and the reference information. We show how, by changing the popularity, transparency, homogeneity, and functionality properties of the facts in an experiment, it is possible to influence significantly the performance of the fact checking algorithms. We introduce a benchmark framework to systematically enforce such properties in training and testing datasets with fine tune control over their properties. We then use our benchmark to compare fact checking algorithms with one another, as well as with methods that can solve the link prediction task in knowledge bases. Our evaluation shows the impact of the four data properties on the qualitative performance of the fact checking solutions and reveals a number of new insights concerning their applicability and performance.
University of Southern Denmark Adrenal activity and metabolic risk during randomized escitalopram or placebo treatment in

Background/aims: Polycystic ovary syndrome (PCOS) is associated with insulin resistance, adrenal hyperactivity and decreased mental health. We aimed to investigate the changes in adrenal activity, metabolic status and mental health in PCOS during treatment with escitalopram or placebo. Methods: Forty-two overweight premenopausal women with PCOS and no clinical depression were randomized to 12-week SSRI (20 mg escitalopram/day, n = 21) or placebo (n = 21). Patients underwent clinical examination, fasting blood samples, adrenocorticotroph hormone (ACTH) test, 3-h oral glucose tolerance test (OGTT) and filled in questionnaires regarding mental health and health-related quality of life (HRQoL): WHO Well-Being Index (WHO-5), Major Depression Inventory (MDI), Short Form 36 (SF-36) and PCOS questionnaire. Results: Included women were aged 31 (6) years (mean (s.d.)) and had body mass index (BMI) 35.8 (6.5) kg/m2 and waist 102 (12) cm. Escitalopram was associated with increased waist (median (quartiles) change 1 (0; 3) cm), P = 0.005 vs change during placebo and increased cortisol levels (cortisol 0, cortisol 60, peak cortisol and area under the curve for cortisol during ACTH test), all P < 0.05 vs changes during placebo. Escitalopram had no significant effect on measures of insulin sensitivity, insulin secretion, fasting lipids, mental health or HRQoL. Conclusion: Waist circumference and cortisol levels increased during treatment with escitalopram in women with PCOS and no clinical depression, whereas metabolic risk markers, mental health and HRQol were unchanged.
Galois Field Arithmetics for Linear Network Coding using AVX512 Instruction Set Extensions

Linear network coding requires arithmetic operations over Galois fields, more specifically over finite extension fields. While coding over GF(2) reduces to simple XOR operations, this field is less preferred for practical applications of random linear network coding due to high chances of linear dependencies and therefore redundant coded packets. Coding over larger fields such as GF(16) and GF(256) does not have that issue, but is significantly slower. SIMD vector extensions of processors such as AVX2 on x86-based systems or NEON on ARM-based devices offer the potential to increase performance by orders of magnitude. In this paper we present an implementation of different algorithms and Galois fields based on the AVX512 instruction set extension and integrate it into the finite field library libmoepgf. We compare the performance of the new implementation to the reference implementation based on AVX2, showing a significant increase in throughput. In addition, we provide a survey of the best possible coding performance offered by a variety of different platforms.
The New ( Version 4 ) Calibration of the Nighttime 532 nm Channel of the CALIPSO Lidar * 5

25 The data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of a new (version 4.1) calibration algorithm for all the level 1 products. We present the motivation for and the implementation of the version 4.1 nighttime 532 30 nm parallel channel measurements. This is the most fundamental calibration of CALIOP data since all other measurements, i.e the 532 nm nighttime perpendicular, daytime 532 nm as well as 1064 nm are tied to this calibration. The new calibration is shown to resolve the discrepancies in the earlier version and also leads to an improved representation of the stratospheric aerosols. Initial validation results using ground based and airborne lidar measurements are also presented. 35 https://ntrs.nasa. gov/search.jsp? R=2019002837
Did the UK ’ s Performance-Focused Health Reforms Work ? A Difference in Differences Analysis of Citizen Perceptions

The United Kingdom (UK) instituted a performance framework for the National Health Service (NHS) in the late 1990s that, inspired by the new public management (NPM), employed performance measurement and management in an effort to improve the quality of health services to citizens, in addition to realizing efficiency goals. Using data from the 1996 and 2002 Eurobarometer and a difference in differences approach, we evaluate the impacts of these performance reforms by comparing the UK to other European Union countries in terms of overall citizen satisfaction with the health care system and perceptions of how well the health care system performs. In general our results suggest that citizen satisfaction and performance perceptions in the UK were more favorable after the reforms than what would have occurred, absent the implementation of the reforms. The estimated improvement in satisfaction and perceived performance is both statistically and substantively significant, and thus provides evidence that the UK’s NPM-inspired performance framework did accomplish at least some of its goals. Introduction In the late-1990s, the United Kingdom instituted a performance framework for its National Health Service (NHS) that, in addition to having the perennial efficiency and cost-saving goals, employed a new public management (NPM) strategy to improve the quality of health care and the experiences of system users. Indeed, these reforms have been viewed as a prime example of the performance measurement and management movement in public administration (Pollitt & Bouckart, 2004). Using data from the 1996 and 2002 Eurobarometer, we attempt to evaluate the impacts of these performance reforms by comparing the UK to other European Union countries in terms of overall citizen satisfaction with the health care system and perceptions of how well the health care system performs. To preview our results, we find that
Neural Network to Identify Personal Health Experience Mention in Tweets Using BioBERT Embeddings

This paper describes the system developed by team ASU-NLP for the Social Media Mining for Health Applications(SMM4H) shared task 4. We extract feature embeddings from the BioBERT (Lee et al., 2019) model which has been fine-tuned on the training dataset and use that as inputs to a dense fully connected neural network. We achieve above average scores among the participant systems with the overall F1-score, accuracy, precision, recall as 0.8036, 0.8456, 0.9783, 0.6818 respectively.
Influence of Whatsapp and Facebook Social Media Usage on Academic Performance of Secondary School Students in Port Harcourt Local Government Area , Rivers State , Nigeria . Dr ( Mrs )

This study investigated WhatsApp and facebook social media usage on academic performance of secondary school students in Port Harcourt city local government area of Rivers State, Nigeria. Three hundred senior secondary school two students were used for the study. The study had aim and objectives, two research questions and corresponding hypotheses. It adopted the correlational research design. Two instruments; the “Social Media Questionnaire”(SMQ) and the English Achievement Test‟‟ (EAT) were used for data collection. Reliability of the instrument was 0.94 for the Social Media Questionnaire and 0.82 for the English Achievement Test. Simple and multiple regressions were used to analyze the data generated. Findings were that, WhatsApp has a significant value of 0.01 showing that there is a significant relationship of student‟s usage of this platform on their academic performance, since the proportionate value is less than the alpha level which is 0.05, therefore, the null hypothesis is rejected. On the other hand, facebook had a significant value of 0.19 which has no significant relationship since the p value is high. Furthermore, there was a significant relationship of about 3.9% when all the social media platforms are put together, it affects students‟ academic performance. Based on these, it was recommended among others that government, parents, teachers, counsellors and school administrators should moderate student‟s participation on the social media platform so as to use it positively and harness its gains extensively.
University of Groningen The Astro-WISE optical image pipeline

We have designed and implemented a novel way to process widefield astronomical data within a distributed environment of hardware resources and humanpower. The system is characterized by integration of archiving, calibration, and post-calibration analysis of data from raw, through intermediate, to final data products. It is a true integration thanks to complete linking of data lineage from the final catalogs back to the raw data. This paper describes the pipeline processing of optical wide-field astronomical data from the WFI (http://www.eso.org/lasilla/instruments/wfi/) and OmegaCAM (http://www.astro-wise.org/∼omegacam/) instruments using the Astro-WISE information system (the Astro-WISE Environment or simply AWE). This information system is an environment of hardware resources and humanpower distributed over Europe. AWE is characterized by integration of archiving, data calibration, post-calibration analysis, and archiving of raw, intermediate, and final data products. The true integration enables a complete data processing cycle from the raw data up to the publication of science-ready catalogs. The advantages of this system for very large datasets are in the areas of: survey operations management, quality control, calibration analyses, and massive processing.
An Approach for Risk Estimation in Information Security Using Text Mining and Jaccard Method

Involvement of digital information in almost of enterprise sectors makes information having value that must be protected from information leakage. In order to obtain proper method for protecting sensitive information, enterprise must perform risk analysis of threat. However, enterprises often get limitation in measuring risk related information security threat. Therefore, this paper has goal to give approach for estimating risk by using information value. Techniques for measuring information value in this paper are text mining and Jaccard method. Text mining is used to recognize information pattern based on three classes namely high business impact, medium business impact and low business impact. Furthermore, information is given weight by Jaccard method. The weight represents risk levelof information leakage in enterprise quantitatively. Result of comparative analysis with existing method show that proposed method results more detailed output in estimating risk of information security threat.
Human Computation vs. Machine Learning: an Experimental Comparison for Image Classification

Image classification is a classical task heavily studied in computer vision and widely required in many concrete scientific and industrial scenarios. Is it better to rely on human eyes, thus asking people to classify pictures, or to train a machine learning system to automatically solve the task? The answer largely depends on the specific case and the required accuracy: humans may be more reliable - especially if they are domain experts - but automatic processing can be cheaper, even if less capable to demonstrate an "intelligent" behaviour.In this paper, we present an experimental comparison of different Human Computation and Machine Learning approaches to solve the same image classification task on a set of pictures used in light pollution research. We illustrate the adopted methods and the obtained results and we compare and contrast them in order to come up with a long term combined strategy to address the specific issue at scale: while it is hard to ensure a long-term engagement of users to exclusively rely on the Human Computation approach, the human classification is indispensable to overcome the "cold start" problem of automated data modelling.
Design integration and organisational routines

For most companies, the main problem concerning new product development is integrating industrial design process in NPD. Although its definition and scope is not noticed fully, increasing importance of design for company is a fact and there are respectable amount of different practices to create a structure for design in the company to support and strengthen the corporate vision and long-term competitive advantage. Design integration within a firm requires changes in decision rules or routines. As the routine changing processes are themselves routine guided, first, awareness at top management should be constituted for the highest level strategic decision. Selection between developing a new routine itself and adopting an existing one depends on industry type, company size, ownership for design and type of competitive competence, however much of learning in design is imitation of existing ones and vicarious by engaging with consultancies. On this account, this paper is an attempt to bring insights into this debate first by positioning industrial design in innovation strategy and explicating topic by using different and potential design integration types within various firms. The study interested in explaining different design integration forms, and specifically in understanding what, if any, connections there are between different level of design integration in various firms and organizational routines in innovation management literature.
RAPTOR Plus : Implementing a Robust Systems Architecture foSocial Hierarchical Learning

Much of contemporary robotics research focuses on methods by which robotic agents can operate in environments that have little, if any, human presence. Humanrobot collaboration, where robots perform tasks alongsidea human confederate, has been almost wholly ignored by curren t research. Social Hierarchical Learning is a method by which robots can learn representations for primitive actions, become experts at performing those actions, decompose a complex ta sk into some superset of those skills, and then enter a mixed human-robot environment to begin actively collaborating.The purpose of this independent research project was to aid in th e design and implementation of such a framework, decomposing the complex pipeline described into a set of discrete compon e ts that can be investigated independently of one another or lin ked together to form a robust and flexible system. The result is prototype software for several components in the framework and a detailed architecture for implementing the remaining modules.
An Energy Efficient Resource Allocation Scheme Based on Cloud-Computing in H-CRAN

Compared with the cloud radio access network (C-RAN), heterogeneous C-RAN with the high-power node entity which separates the control and broadcast functionalities from the baseband processing unit (BBU) pool. It makes the user access, resource allocation, load balancing more flexible, which also makes the intralayer interference and interlayer interference more complex. Therefore, the heavy inverse operations for dense matrices and the complicated power allocation algorithms in beamforming perform large floating-point calculations per second in BBU pool. As frequency resources grow scarcer, green communication with high energy efficiency (EE) and low carbon emissions has raised significant concerns. In this paper, we focus on the EE advantages achieved by selectively cooperative transmission and associated power consumption model. A joint channel matrix sparseness and normalized water-filling resource allocation algorithm is proposed and formulated to improve EE at different user density through mathematical derivation. By reducing the computation complexity of cooperative transmission, the proposed scheme decreases the digital baseband power consumption, which is more adaptable for tidal phenomenon. Simulation results show that the proposed algorithm can effectively reduce the energy consumption of baseband and improve the EE of the system.
Centre for Policy Studies University College Cork National University of Ireland Compulsory Voting : What Difference Can Increasing Turnout Make ?

Abstract: A number of previous studies have examined the effects of increasing voter turnout, but have yielded ambiguous results. Much of that debate centers on how preferences of voters differ from those of non-voters. We develop a general measure of the potential effects of increasing turnout that can encompass the entire range of assumptions concerning non-voters’ preferences. Our “turnout competitiveness index” (TCI) and a related “elasticity rule” provide a measure of seat competitiveness that links voluntary voter support for candidates and abstention rates to the potential to alter expected electoral outcomes from increasing turnout alone. This analysis also allows us to create a distinction between what we call the traditional measure of “conventional swing” and our notion of “turnout swing. ” We analyze the properties of the TCI and then, using several stylized examples of competitiveness and turnout rates, we estimate the effects of increasing turnout on seat competitiveness by increasing turnout to 100%. We also demonstrate our analysis in an intuitive graphical form. A number of previous studies have examined the effects of increasing voter turnout, but have yielded ambiguous results. Much of that debate centers on how preferences of voters differ from those of non-voters. We develop a general measure of the potential effects of increasing turnout that can encompass the entire range of assumptions concerning non-voters’ preferences. Our “turnout competitiveness index” (TCI) and a related “elasticity rule” provide a measure of seat competitiveness that links voluntary voter support for candidates and abstention rates to the potential to alter expected electoral outcomes from increasing turnout alone. This analysis also allows us to create a distinction between what we call the traditional measure of “conventional swing” and our notion of “turnout swing. ” We analyze the properties of the TCI and then, using several stylized examples of competitiveness and turnout rates, we estimate the effects of increasing turnout on seat competitiveness by increasing turnout to 100%. We also demonstrate our analysis in an intuitive graphical form.