Miracle-dz/UniFAR-FTUs huggingface dataset:
Mendelian randomization analysis for attention deficit/hyperactivity disorder: studying a broad range of exposures and outcomes

Abstract Background Attention deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder caused by a combination of genetic and environmental factors and is often thought as an entry point into a negative life trajectory, including risk for comorbid disorders, poor educational achievement or low income. In the present study, we aimed to clarify the causal relationship between ADHD and a comprehensive range of related traits. Methods We used genome-wide association study (GWAS) summary statistics for ADHD (n = 53 293) and 124 traits related to anthropometry, cognitive function and intelligence, early life exposures, education and employment, lifestyle and environment, longevity, neurological, and psychiatric and mental health or personality and psychosocial factors available in the MR-Base database (16 067 ≤n ≤766 345). To investigate their causal relationship with ADHD, we used two-sample Mendelian randomization (MR) with a range of sensitivity analyses, and validated MR findings using causal analysis using summary effect estimates (CAUSE), aiming to avoid potential false-positive results. Results Our findings strengthen previous evidence of a causal effect of ADHD liability on smoking and major depression, and are consistent with a causal effect on odds of decreased average total household income [odds ratio (OR) = 0.966, 95% credible interval (CrI) = (0.954, 0.979)] and increased lifetime number of sexual partners [OR = 1.023, 95% CrI = (1.013, 1.033)]. We also found evidence for a causal effect on ADHD for liability of arm predicted mass and weight [OR = 1.452, 95% CrI = (1.307, 1.614) and OR = 1.430, 95% CrI = (1.326, 1.539), respectively] and time spent watching television [OR = 1.862, 95% CrI = (1.545, 2.246)], and evidence for a bidirectional effect for age of first sexual intercourse [beta = −0.058, 95% CrI = (−0.072, −0.044) and OR = 0.413, 95% CrI = (0.372, 0.457), respectively], odds of decreased age completed full-time education [OR = 0.972, 95% CrI = (0.962, 0.981) and OR = 0.435, 95% CrI = (0.356, 0.533), respectively] and years of schooling [beta = -0.036, 95% CrI = (−0.048, −0.024) and OR = 0.458, 95% CrI = (0.411, 0.511), respectively]. Conclusions Our results may contribute to explain part of the widespread co-occurring traits and comorbid disorders across the lifespan of individuals with ADHD and may open new opportunities for developing preventive strategies for ADHD and for negative ADHD trajectories.
Bone conduction transducers and output variability

Bone-conduction transducers for hearing aids are used by thousands of patients that cannot use conventional air-conduction hearing devices. Such bone conduction transducers have also been extensively used in bone conduction audiometry, for example, hearing threshold measurements. The interaction between these transducers output impedance and the patients skin impedance over the temporal bone, which both are in the same range, results in a high variability of the output force, acceleration and power which is directly related to the variability in the patients skin impedances. Because the output force is used as the reference zero standard for bone conduction hearing thresholds, variability in patient skin impedances is a source of error in threshold determination via bone conduction. This work investigates the extent of this variability in the output from one Radioear B71 transducer due to the skin impedances of 30 subjects. In the frequency range 100-10000 Hz, an inter subject standard deviation in the skin impedance, averaging 2.4 dB, gives rise to a standard deviation in force and acceleration output ranging from 0 5 dB. The impedance characteristic of the transducer can be used to predict which frequency regions correspond to increased output variability, as well as to nd "golden" frequency areas having less force and acceleration output variability.
1 BRCA 2-deficient sarcomatoid mammary tumors exhibit multi-drug resistance 1

BRCA2-deficient sarcomatoid mammary tumors exhibit multi-drug resistance 1 Janneke E. Jaspers, Wendy Sol, Ariena Kersbergen, Andreas Schlicker, Charlotte Guyader, 2 Guotai Xu, Lodewyk Wessels, Piet Borst, Jos Jonkers, Sven Rottenberg 3 4 Authors’ affiliations 5 1 Divisions of Molecular Oncology, 2 Molecular Pathology and 3 Molecular Carcinogenesis, 6 Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands; Institute of 7 Animal Pathology, Vetsuisse Faculty, University of Bern, Laengassstrasse 122, 3012 Bern, Switzerland 8 9 Running title 10 Multi-drug resistance of sarcomatoid mouse mammary tumors 11 12 Precis 13 Epithelial-to-mesenchymal transition in murine mammary tumors associates with an 14 acquisition of multi-drug resistance, due to increased expression of genes encoding drug 15 efflux transporters. 16 17
AFFECTIVE AND COGNITIVE RESPONSES TO MUSICAL PERFORMANCES OF EARLY 20 TH CENTURY CLASSICAL SOLO PIANO COMPOSITIONS : THE INFLUENCE OF MUSICAL EXPERTISE AND AUDIO-VISUAL PERCEPTION

EFFECTIVE AUDIENCE ENGAGEMENT WITH MUSICAL performance involves social, cognitive and affective elements. We investigate the influence of observers’ musical expertise and instrumental motor expertise on their affective and cognitive responses to complex and unfamiliar classical piano performances of works by Scriabin and Hanson presented in audio and audio-visual formats. Observers gave their felt affect (arousal and valence) and their action understanding responses continuously while observing the performances. Liking and familiarity were rated after each excerpt. As hypothesized: visual information enhanced observers’ action understanding and liking ratings; observers with music training rated their action understanding, liking and familiarity higher than did nonmusicians; observers’ felt affect did not vary according to their musical or motor expertise. Contrary to our hypotheses: visual information had only a slight effect on observers’ arousal felt affect responses and none on valence; musicians’ specific instrumental motor expertise did not influence action understanding responses. We also observed a significant negative relationship between action understanding and felt affect responses. Ideas of empathy in musical interactions motivated the research; the empathy framework in relation to musical performance is discussed. Nonmusician audiences might be sensitized to challenging musical performances through multimodal strategies to build the performer-observer connection and increase understanding of performance.
Microsoft Word-nwab102.docx

The brain network is notably cost-efficient, while the fundamental physical and dynamic mechanisms underlying its economical optimization in network structure and activity have not been determined. In this study, we investigate the intricate cost-efficient interplay between structure and dynamics in biologically plausible spatial modular neuronal network models. We observe that critical avalanche states from excitation-inhibition balance under modular network topology with less wiring cost can also achieve lower costs in firing but with strongly enhanced response sensitivity to stimuli. We derived mean-field equations that govern the macroscopic network dynamics through a novel approximate theory. The mechanism of low firing cost and stronger response in the form of critical avalanches is explained as a proximity to a Hopf bifurcation of the modules when increasing their connection density. Our work reveals the generic mechanism underlying the cost-efficient modular organization and critical dynamics widely observed in neural systems, providing insights into braininspired efficient computational designs.
A multilevel SEM for the interrelationships between mul- tiple latent dimensions of childhood socioeconomic cir- cumstances, partnership transitions and midlife health

Yajing Zhu Department of Statistics, Houghton Street, London School of Economics and Political Science, London, U.K. E-mail: y.zhu18@lse.ac. uk Fiona Steele Department of Statistics, Houghton Street, London School of Economics and Political Science, London, U.K. E-mail: f.a. steele@lse.ac. uk Irini Moustaki Department of Statistics, Houghton Street, London School of Economics and Political Science, London, U.K. E-mail: i.moustaki@lse.ac. uk
University of Birmingham fMRI evidence for areas that process surface gloss in the human visual cortex

Surface gloss is an important cue to the material properties of objects. Recent progress in the study of macaque’s brain has increased our understating of the areas involved in processing information about gloss, however the homologies with the human brain are not yet fully understood. Here we used human functional magnetic resonance imaging (fMRI) measurements to localize brain areas preferentially responding to glossy objects. We measured cortical activity for thirty-two rendered three-dimensional objects that had either Lambertian or specular surface properties. To control for differences in image structure, we overlaid a grid on the images and scrambled its cells. We found activations related to gloss in the posterior fusiform sulcus (pFs) and in area V3B/KO. Subsequent analysis with Granger causality mapping indicated that V3B/KO processes gloss information differently than pFs. Our results identify a small network of mid-level visual areas whose activity may be important in supporting the perception of surface gloss. (cid:2) 2014 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creative-commons.org/licenses/by/4.0/).
Sparse precontrast T 1 mapping for high-resolution whole-brain

1Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA 2General Electric Healthcare, Calgary, Alberta, Canada 3Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada 4Department of Radiology, University of Southern California, Los Angeles, California, USA 5Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada
Studies of plants with mutations in the CRABS CLAW gene indicate that it is involved in suppressing early radial growth of the gynoecium and in promoting its later

Analysis of homeotic flower mutants has revealed that the identity of floral organs is specified by a limited set of key regulatory genes, acting alone and in combination. A model, now known widely as the ABC model, has been shown to apply to a range of plant species (Coen and Meyerowitz, 1991; Weigel and Meyerowitz, 1994). A key regulatory gene specifying carpel identity in Arabidopsis flowers is AGAMOUS (AG) (Bowman et al., 1989, 1991). This C function gene encodes a transcription factor of the MADS family (Yanofsky et al., 1990). A combination of genetic and molecular experiments, including ectopic expression of AG in transgenic plants, has shown that AG is sufficient for the specification of carpels within the wild-type flower (Bowman et al., 1989, 1991; Mizukami and Ma, 1992). Even so, some carpel properties, such as stigmatic tissue, fusion of floral organs along their margins, and the production of ovules, can arise even in the absence of AG activity (Bowman et al., 1991). Other genes must therefore exist that specify aspects of carpel development in the absence of AGAMOUS gene function. In a screen for mutations that specifically disrupt carpel morphogenesis, two genes, CRABS CLAW (CRC) and SPATULA (SPT), that act in this capacity have been identified (Alvarez and Smyth, 1999). CRC apparently controls the width of the gynoecium and its elongation, whereas SPT promotes development of carpel margins and the tissues that arise from them. In addition, CRC is required for the development of nectaries that arise at the base of the stamens in Arabidopsis flowers (Davis, 1994a; Smyth et al., 1990). In this paper we describe the structure and expression of the CRC gene to further understand its functions. CRC is a member of a family of genes that encode proteins with a zinc fingerlike domain and a putative helix-loop-helix with sequence similarity to part of the HMG box. Thus CRC is likely to act as a transcriptional regulator. CRC mRNA is mostly limited to developing carpels and nectaries. Its expression pattern in wild2387 Development 126, 2387-2396 (1999) Printed in Great Britain © The Company of Biologists Limited 1999 DEV0226
University of Birmingham A study of professional awareness using immersive virtual reality

The art of picking up signs that a child may be suffering from abuse at home is one of those skills that cannot easily be taught, given its dependence on a range of non-cognitive abilities. It is also difﬁcult to study, given the number of factors that may interfere with this skill in a real-life, professional setting. An immersive virtual reality environment provides a way round these difﬁculties. In this study, we recruited 64 general practitioners (GPs), with different levels of experience. Would this level of experience have any impact on general practitioners’ ability to pick up child-safeguarding concerns? Would more experienced GPs ﬁnd it easier to pick up subtle (rather than obvious) signs of child-safeguarding concerns? Our main measurement was the quality of the note left by the GP at the end of the virtual consultation: we had a panel of 10 (all experienced in safeguarding) rate the note according to the extent to which they were able to identify and take the necessary steps required in relation to the child safeguarding concerns. While the level of professional experience was not shown to make any difference to a GP’s ability to pick up those concerns, the parent’s level of aggressive behavior toward the child did. We also manipulated the level of cognitive load (reﬂected in a complex presentation of the patient’s medical condition): while cognitive load did have some impact upon GPs in the “obvious cue” condition (parent behaving particularly aggressively), this effect fell short of signiﬁcance. Furthermore, our results also suggest that GPs who are less stressed, less neurotic, more agreeable and extroverted tend to be better at raising potential child abuse issues in their notes. These results not only point at the considerable potential of virtual reality as a training tool, they also highlight fruitful avenues for further research, as well as potential strategies to support GP’s in their dealing with highly sensitive, emotionally charged situations.
Master Thesis Hyperparameter Optimization for Large-scale Machine Learning

Hyperparameter optimization is a crucial task affecting the final performance of machine learning solutions. This thesis analyzes the properties of different hyperparameter optimization algorithms for machine learning problems with large datasets. In hyperparameter optimization, we repeatedly propose a hyperparameter configuration, train a machine learning model using that configuration and validate the performance of the model. In order to scale in these scenarios, this thesis focuses on the data-parallel approach to evaluate hyperparameter configurations. We utilize Apache Spark, a dataparallel processing system, to implement a selection of hyperparameter optimization algorithms. Moreover, this thesis proposes a novel hyperparameter optimization method, Bayesian Geometric Halving (BGH). It is designed to benefit from the characteristics of dataparallel systems and the properties of existing hyperparameter optimization algorithms. BGH enhances Bayesian methods by combining them with adaptive evaluation. At the same time, it has a time-efficient execution independently of the number of configurations evaluated. Various experiments compare the performance of several hyperparameter optimization algorithms. These experiments extend their theoretical comparison in order to understand under which conditions some algorithms perform better than the others. The experiments show that BGH improves the results of both Bayesian and adaptive evaluation methods. Indeed, one of the variants of BGH achieves the best result in every experiment where they are compared. Hiermit erkläre ich, dass ich die vorliegende Arbeit selbstständig und eigenhändig sowie ohne unerlaubte fremde Hilfe und ausschlielich unter Verwendung der aufgeführten Quellen und Hilfsmittel angefertigt habe.
Studies Utilizing the Portable Electromagnetic Ballistocardiograph

Ballstocad(liographic studies were done on 28 subjects with left bundle branch block and on 18 subjects with right bundle branch block. The influence of ventricular as nchronism, and the predominance of left or right ventricular disease, upon the derivation and interpretation of the ballistocar(liograsn, is discussed. The ballistocardiogram was found to be a valuable objective guide in the detection of subjects whose bundle branch blcck was not associated with significant heart (lsease. The ballistocardiogram also provided helpful confirmatoryN evidence of coronary artery oI' hypertensive heart disease when this was the suspected or certain diagnosis in subjects with bundle branch block.
BEST PRACTICES FOR WEARABLE MONITOR CALIBRATION AND VALIDATION

BASSETT D. R. JR., A. ROWLANDS, and S. G. TROST. Calibration and Validation of Wearable Monitors. Med. Sei. Sports Exerc, Vol. 44, No. IS, pp. S32-S38, 2012. Background: Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices: Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions: New methods of calibration now use "pattem recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.
Comparative Analysis Homoscedastic OLS Models

This study considered foreign direct investment (FDI) as response variable while, gross domestic product (GDP), inflation and exchange rate were the predictor variables. The data were obtained from the Central Bank of Nigeria Statistical Bulletin spanning from 1970 to 2019. The study aimed at comparing heteroscedatic and homoscedastic OLS modes. Our findings revealed that the predictor variables in the heteroscedastic OLS model were not significant and were able to account for about 44% of the variation in the response variable. The diagnosis of the fitted regression model using BreuschPagan test showed that the assumption of homoscedasticity was violated. To address the problem of heteroscedasticity, all the variables were converted to log form to stabilise the variance. Our results from the now homoscedstic model revealed that all the predictor variables were significant and able to account for about 82% of the variation in the response variable. Therefore, our study established that when the assumption of homoscedasticity is violated, the model parameters become inefficient, the standard errors biased; and the t statistics and the p-values no more valid. On the other hand, this stu evidently proved that homoscedastic OLS model provide better estimates than heteroscedastic OLS model.
Vessels semantic segmentation with gradient descent optimization

Semantic segmentation is a segmentation based on the accuracy of the pixel. Segmentation of retinal vessels aims to differentiate be-tween vessels and non-vessels. There are many conventional methods of retinal vessels segmentation. Conventional methods should perform feature extraction manually. Currently, there has been widely researching on deep learning. Deep learning performs feature extraction automatically during the training phase. One of the methods of deep learning is the Convolutional Neural Network (CNN). The research used three steps i.e creating network layers, training the network, and evaluation of accuracy. We use ten layers of CNN. The CNN architecture consists of Convolution layers, Rectified Linear Unit layers, MaxPooling Layers, Transpose Convolution Layers and Softmax Layer. Furthermore, training the network include the optimization of the training phase. There are three optimization algorithms used for the training phase. The optimization algorithms are Stochastic Gradient Descent with Momentum (SGDM), Root Means Square Propagation (RMSProp) and Adaptive Moment Optimization (Adam). The dataset used for the experiment is Digital Retinal Image for Vessel Extraction (DRIVE). Computation process using the Graphical Processing Unit. Variation scenarios are performed to get the optimal accuracy. The vessels semantic segmentation average accuracy achieved 91.11% - 98.08%.
Masters Thesis: Motion Planning in the State Space

We introduce a motion planning infrastructure, a new set of distance functions and a steering function. Motion planners are used in robotics in order to plan realistic motions by allowing for variable velocities, as opposed to path planners which either neglect or consider velocities as constant. The main goal of this thesis is to design a planning infrastructure with minimal input, which can solve the motion planning problem for various robots. This all within a reasonable time frame and without preprocessing. Here the state space is the combination of all possible positions and velocities. To find this solution the Rapidly-exploring Random Tree (RRT) [1] motion planner has been adapted for use in the state space and was tested using a UR5 robot arm model. By itself it was shown to be unable to connect two states, even after adding 100000 states to its tree. Thus to verify the commonly used euclidean distance metric a new set of simple diIn conclusion the probabilistically complete motion planner RRT has been adapted for the state space, which in combination with the steering function can find a non optimal connection between two states on the gostance functions has been created, which have been verified by calculating their correlation with actual motions and considering their behavior in RRT. Both strong and weak correlations were observed for these distance functions, yet no connections were established between states. Finally a steering function has been created, PID-connect, which connects both the start and the goal state to a zero velocity state using a PID-controller. PID-connect is able to compute a motion between two states reliably in a short time (0.02± 0.01s, n = 1000). In conclusion a probabilistically complete variant o RRT has been adapted for use in the state space, which in combination with the steering function can find a non optimal motion between two states on the go. This research provides a solid basis from which further advancements in this field can be made. Master of Science Thesis W.W. F. Spierenburg