Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual Question Answering using Deep Learning

In this project, we have employed a combination of recurrent neural network(RNN) and convolutional neural network (CNN) for a multimodal quesion answering task related to images. Our proposed end-to-end trainable neural network provides a framework for learning the image representation, the sentence representation for question, the inter-modal interaction between the image and question, and also takes into account the sequential nature of the question input for the generation of answer. The proposed model has four components: a Long-Short Term Memory(LSTM) component and a CNN to encode the question,an image CNN to extract the image representation, and one multimodal convolution layer to combine the two modalities of the image and question,which is further used to obtain the joint representation for generating the answer words. We employ our proposed model on DAQUAR, a dataset created for the image question answering (QA).
Thinking, Fast and Slow

Daniel Kahneman, recipient of the Nobel Prize in Economic Sciences for his seminal work in psychology challenging the rational model of judgment and decision making, is one of the world's most important thinkers. His ideas have had a profound impact on many fields - including business, medicine, and politics - but until now, he has never brought together his many years of research in one book. In "Thinking, Fast and Slow", Kahneman takes us on a groundbreaking tour of the mind and explains the two systems that drive the way we think and make choices. One system is fast, intuitive, and emotional; the other is slower, more deliberative, and more logical. Kahneman exposes the extraordinary capabilities - and also the faults and biases - of fast thinking, and reveals the pervasive influence of intuitive impressions on our thoughts and behaviour. The importance of properly framing risks, the effects of cognitive biases on how we view others, the dangers of prediction, the right ways to develop skills, the pros and cons of fear and optimism, the difference between our experience and memory of events, the real components of happiness - each of these can be understood only by knowing how the two systems work together to shape our judgments and decisions. Drawing on a lifetime's experimental experience, Kahneman reveals where we can and cannot trust our intuitions and how we can tap into the benefits of slow thinking. He offers practical and enlightening insights into how choices are made in both our professional and our personal lives-and how we can use different techniques to guard against the mental glitches that often get us into trouble. "Thinking, Fast and Slow" will transform the way you take decisions and experience the world.
Cooperative Concurrent Games

In rational verification, one is interested in understanding which temporal logic properties will hold in a concurrent game, under the assumption that players choose strategies that form an equilibrium. Players are assumed to behave rationally in pursuit of individual goals, typically specified as temporal logic formulae. To date, rational verification has only been studied in noncooperative settings. In this paper, we extend the rational verification framework to cooperative games, in which players may form coalitions to collectively achieve their goals. We base our study on the computational model given by concurrent game structures and focus on the core as our basic solution concept. We show the core of a concurrent game can be logically characterised using ATL*, and study the computational complexity of key decision problems associated with the core, which range from problems in PSPACE to problems in 3EXPTIME. We also discuss a number of variants of the main definition of the core, leading to the issue of credible coalition formations, and a possible implementation of the main reasoning framework.
Estimating heterogeneous treatment effects with right-censored data via causal survival forests

There is fast-growing literature on estimating heterogeneous treatment effects via random forests in observational studies. However, there are few approaches available for right-censored survival data. In clinical trials, right-censored survival data are frequently encountered. Quantifying the causal relationship between a treatment and the survival outcome is of great interest. Random forests provide a robust, nonparametric approach to statistical estimation. In addition, recent developments allow forest-based methods to quantify the uncertainty of the estimated heterogeneous treatment effects. We propose causal survival forests that directly target on estimating the treatment effect from an observational study. We establish consistency and asymptotic normality of the proposed estimators and provide an estimator of the asymptotic variance that enables valid confidence intervals of the estimated treatment effect. The performance of our approach is demonstrated via extensive simulations and data from an HIV study.
Establishing a reference ultrasonic cleaning vessel: Part 1 supporting infrastructure and early measurements.

This document contains a description of the tasks completed within deliverable 4.5. 1 "Establish a reference ultrasonic cleaning vessel" in the NMS Acoustics Programme 1998-2001. It includes the findings of a literature search, details of equipment specifications and performance, and the results of some initial hydrophone measurements carried out to assess the reproducibility of establishing a cavitating field using an ultrasonic cleaning bath.
Study of deﬂection angles, thin accretion structure, and the observational signatures of a static f ( R ) black hole

In this paper, we constrain the linear dark-matter related parameter of a static spherically symmetric f ( R ) black hole spacetime regarding the observed angular diameters of M87* and Sgr A* from the EHT. We then investigate the light deﬂection angles inferred from direct analytical calculation of null geodesics and that obtained from the Gauss-Bonnet theorem. Assuming an optically thin accretion disk for the black hole and after discussing its properties, we conceive different emission proﬁles and investigate the shadow cast of this black hole when it is illuminated by the disk. Furthermore, we simulate the brightness of an infalling spherical accretion in the context of the silhouette imaging of the black hole. We ﬁnd that, excluding some speciﬁc cases, the speciﬁc observed brightness of the accretion disk consists of the direct emission, rather than that for the lensing and photon rings. Furthermore, it is revealed that the linear dark parameter of the black hole has considerable effects on the size of the shadow and its brightness. The discussion is done both analytically and numerically, and ray-tracing methods are employed to generate proper visualizations
Isometric actions on Lp-spaces: dependence on the value of p

We prove that, for every topological group $G$, the following two sets are intervals: the set of real numbers $p>0$ such that every continuous action of $G$ by isometries on an $L_p$ space has bounded orbits, and the set of $p>0$ such that $G$ admits a metrically proper continuous action by isometries on an $L_p$ space. This answers a question by Chatterji--Drutu--Haglund.
Professional Certifications of a University Master’s Degree and Employability: Impact on Students’ Perception

Professional certifications represent for many university degrees, especially postgraduate degrees, a recognition of their academic quality and the future employability of the graduates. This article contributes to the analysis of the impact of external accreditations on students’ perception of employability and satisfaction. We offer a case of study, a Master of Science (MSc) in Banking and Finance that became the first academic degree in Spain to obtain the two professional accreditations required for employees in financial institutions since 2019. A survey to a sample of students who graduated two academic years before and two years after the MSc was recognised is used to measure students' motivations for enrolment and satisfaction. The results provide significant evidence that professional accreditation became a key motivation for students to enrol the master, is associated with a more diverse geographical origin of students, and students highlight the higher quality and better coordination of the teaching staff.
Multi-scale analysis of lead-lag relationships in high-frequency financial markets

We propose a novel estimation procedure for scale-by-scale lead-lag relationships of financial assets observed at high-frequency in a non-synchronous manner. The proposed estimation procedure does not require any interpolation processing of original datasets and is applicable to those with highest time resolution available. Consistency of the proposed estimators is shown under the continuous-time framework that has been developed in our previous work Hayashi and Koike (2018). An empirical application to a quote dataset of the NASDAQ-100 assets identifies two types of lead-lag relationships at different time scales.
Boosting the boost: the effect of tidal stripping on the subhalo luminosity.

In the paradigm of ΛCDM, structures form hierarchically, implying that large structures contain smaller substructures. These so-called subhalos can enhance the dark matter annihilation signal that one expects to see from a given host halo, the effect of which is called the boost factor. In the literature this boost factor is typically calculated assuming a density profile for the substructure, or analogously a concentration-mass relation, corresponding to that of field halos. However, since subhalos accreted in a gravitational potential of their host loose mass through tidal stripping and dynamical friction, they have a quite characteristic density profile, different from that of the field halos of the same mass. In this work we attempt to quantify the effect of tidal stripping on the boost factor. We find that the boost factor increases by a factor few for host halos ranging from sub-galaxy to cluster masses.
Domain decomposition solvers for nonlinear multiharmonic finite element equations

Abstract In many practical applications, for instance, in computational electromagnetics, the excitation is time-harmonic. Switching from the time domain to the frequency domain allows us to replace the expensive time-integration procedure by the solution of a simple elliptic equation for the amplitude. This is true for linear problems, but not for nonlinear problems. However, due to the periodicity of the solution, we can expand the solution in a Fourier series. Truncating this Fourier series and approximating the Fourier coefficients by finite elements, we arrive at a large-scale coupled nonlinear system for determining the finite element approximation to the Fourier coefficients. The construction of fast solvers for such systems is very crucial for the efficiency of this multiharmonic approach. In this paper we look at nonlinear, time-harmonic potential problems as simple model problems. We construct and analyze almost optimal solvers for the Jacobi systems arising from the Newton linearization of the large-scale coupled nonlinear system that one has to solve instead of performing the expensive time-integration procedure.
A Robust Preconditioned MinRes Solver for Time-periodic Eddy Current Problems

Abstract. This work is devoted to fast and parameter-robust iterative solvers for frequency domain finite element equations, approximating the time-periodic eddy current problem with multiharmonic or time-periodic excitations in time. We construct a preconditioned MinRes solver for the frequency domain equations, that is robust with respect to the discretization parameters as well as all involved “bad” parameters like the conductivity, the reluctivity and possible regularization parameters.
A systematic review on the effect of ICT on social support measures in healthcare

Background: With increased popularity in the use of ICT in healthcare to provide support to individuals, it is imperative to investigate the impact of ICT on social support measures in health and social care. Objective: This study aims to review literature on the effectiveness of ICT-based tools and intervention on social support measures with reference to health and illness. Methods: Relevant databases (PubMed\MEDLINE, clinicaltrials.gov and Cochrane Library) were systematically searched using a combination of key search terms. To be included in the review, studies had to be published in English language, involve human subjects, be published between 2000 and 2017, apply ICT intervention on a health-related condition and report the effect of ICT on social support measures. Results: The database search returned 4020 articles. After screening, 30 eligible papers were selected for the review. The studies were quite heterogeneous in terms of study design, age of participants, reported outcome, outcome measuring tool and health condition of participants. 20% of included studies were rated as low quality evidence, with a high risk of research bias. Over 75% of reviewed studies reported positive impact of ICT on social support measures. The results show that ICT interventions have a statistically significant positive impact on social support measures. Social network was found to be the ICT intervention with the most impact on social support measures. Conclusion: There is need for more high quality research on the effect of ICT on social support measures. The results of this systematic review suggest that ICT could effectively provide social support to individuals, although the degree of its effect could depend on the nature of ICT tool used and the well-being status of individuals. Further work in the use of ICT to provide social support for preventive healthcare is recommended. Also, more research investigating the effect of using Smartphone-based instant messaging applications (such as WhatsApp and Snapchat) and virtual reality technology on social support is encouraged.
Passive control of the flow around unsteady aerofoils using a self-activated deployable flap

ABSTRACT Self-activated feathers are used by many birds to adapt their wing characteristics to the sudden change of flight incidence angle. In particular, dorsal feathers are believed to pop-up as a consequence of unsteady flow separation and to interact with the flow to palliate the sudden stall breakdown typical of dynamic stall. Inspired by the adaptive character of birds feathers, some authors have envisaged the potential benefits of using of flexible flaps mounted on aerodynamic surfaces to counteract the negative aerodynamic effects associated with dynamic stall. This contribution explores more in depth the physical mechanisms that play a role in the modification of the unsteady flow field generated by a NACA0020 aerofoil equipped with an elastically mounted flap undergoing a specific ramp-up manoeuvre. We discuss the design of flaps that limit the severity of the dynamic stall breakdown by increasing the value of the lift overshoot also smoothing its abrupt decay in time. A detailed analysis on the modification of the turbulent and unsteady vorticity field due to the flap flow interaction during the ramp-up motion is also provided to explain the more benign aerodynamic response obtained when the flap is in use.
Same-sex attraction, social relationships, psychosocial functioning, and schoolperformance in young adolescents

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Finite Time Analysis of Optimal Adaptive Policies for Linear-Quadratic Systems

We consider the classical problem of control of linear systems with quadratic cost. When the true system dynamics are unknown, an adaptive policy is required for learning the model parameters and planning a control policy simultaneously. Addressing this trade-off between accurate estimation and good control represents the main challenge in the area of adaptive control. Another important issue is to prevent the system becoming destabilized due to lack of knowledge of its dynamics. Asymptotically optimal approaches have been extensively studied in the literature, but there are very few non-asymptotic results which also do not provide a comprehensive treatment of the problem. In this work, we establish finite time high probability regret bounds that are optimal up to logarithmic factors. We also provide high probability guarantees for a stabilization algorithm based on random linear feedbacks. The results are obtained under very mild assumptions, requiring: (i) stabilizability of the matrices encoding the system's dynamics, and (ii) degree of heaviness of the noise distribution. To derive our results, we also introduce a number of new concepts and technical tools.
Resting Functional Connectivity Reveals Residual Functional Activity in Alzheimer’s Disease

Epilepsy surgery remains the only chance of becoming seizure–free for many patients with focal epilepsies refractory to medical treatment. In those cases where plan of surgery cannot be formulated on the basis of non–invasive studies (MRI, scalp videotelemetry, neuropsycholgy, CT PET, MEG), intracranial EEG (ICEEG) recording can often identify seizure onset zone and make surgery possible. In the UK, the most commonly used ICEEG technique is implantation of subdural grids/strips+depth electrodes, the latter usually implanted into the mesial temporal structures. Until recently electrocorticography using subdural grids/strips combined with mesial temporal depth electrodes was routinely used in our centre. Since November 2011 we have switched to stereoEEG (sEEG) technique with robotic stereotactic implantation of multiple depth electrodes using Renishaw Neuromate robot. So far we have carried out sEEG implantation in 11 cases. The indications for sEEG included: Non–lesional TLE (n=4) Focal cortical dysplasia in proximity to eloquent cortex, e.g. L frontal lobe close to the motor strip or parietal lobe close to the primary sensory cortex (n=2) Dual pathology (n=1) Multiple lesions (tuberous sclerosis) (n=1) Bitemporal epilepsy (n=1) Re–investigation of previous unsuccessful resection (n=2) SEEG identified seizure onset zone in 10/11 of patients. In 1 patient (tuberous sclerosis with multiple tubers) ICEEG data were not sufficient to proceed to surgery and further studies are pending. Seven patients have undergone surgery and 3 patients are awaiting surgery. Seizure–free (Engel I) outcome has been seen in 5/7 patients who had surgery (follow up period 5–14 months, mean 9.8 months). In one case of bitemporal epilepsy (80% seizures originating in one temporal lobe and associated with ictal asystole), where surgery was undertaken with palliative intent, Engel III outcome has been seen. In 1 case only subjective events have been reported (possible non–epileptic attacks, awaiting further evaluation). No surgical complications of sEEG have been seen. The procedure is very well tolerated. The average time of recording (including stimulation studies) has been 9 days. Robotic sEEG has been a safe intracranial EEG technique that permits exploration of remote/ discontinuous brain regions and, importantly, the deep structures not accessible to subdural grid recording. Its advantages include: no need for craniotomy well tolerated by patients low risk of infection and bleeding complications electrodes can be removed and surgery planned electively at a later date it can be carried out in patients with history of previous subdural grid implantation/ neurosurgery The disadvantages are that cortical stimulation studies may be more limited (relative disadvantage) and the need for specialised equipment (expense).
Web Appendix: Online Reputation Mechanisms and the Decreasing Value of Chain Affiliation

This appendix accompanies “Online Reputation Mechanisms and the Decreasing Value of Chain Affiliation. ” It presents further evidence for the main effects, namely the differential effect on independent and chain firm revenues of added information via online reviews. This includes use of instrumental variables constructed from two exogenous changes in TripAdvisor.com’s review policies as well as instruments constructed from lagged number of reviews and other robustness checks. I also perform a number of tests to rule out reverse causality in the results in Section 4.
Evolutionary analysis across mammals reveals distinct classes of long non-coding RNAs

Background: Recent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across many species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: identifying truly non-coding genes from de novo reconstructed transcriptomes, and prioritizing the hundreds of resulting putative lncRNAs for downstream experimental interrogation. Results: We present slncky, a lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-sequencing data and further uses evolutionary constraint to prioritize lncRNAs that are likely to be functionally important. Our automated filtering pipeline is comparable to manual curation efforts and more sensitive than previously published computational approaches. Furthermore, we developed a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for analyzing sequence and transcript evolution. Our analysis reveals that evolutionary selection acts in several distinct patterns, and uncovers two notable classes of intergenic lncRNAs: one showing strong purifying selection on RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript. Conclusion: Our results highlight that lncRNAs are not a homogenous class of molecules but rather a mixture of multiple functional classes with distinct biological mechanism and/or roles. Our novel comparative methods for lncRNAs reveals 233 constrained lncRNAs out of tens of thousands of currently annotated transcripts, which we make available through the slncky Evolution Browser.
An efficient quantum teleportation of six-qubit state via an eight-qubit cluster state

We present a scheme for teleporting a certain class of six-particle state via an eight-particle cluster state as quantum channel. In our scheme, the sender merely needs to perform an eight-particle von-Neumann projective measurement, and the receiver gives a corresponding general evolution to restore the original state. Our scheme is a deterministic scheme. Compared with other schemes proposed before, our scheme possesses higher intrinsic efficiency.