Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling Working Memory using Deep Recurrent Reinforcement Learning

In cognitive systems, the role of a working memory is crucial for visual reasoning 1 and decision making. Tremendous progress has been made in understanding the 2 mechanisms of the human/animal working memory, as well as in formulating 3 different frameworks of artificial neural networks. In the case of humans, the 4 visual working memory (VWM) task [1] is a standard one in which the subjects are 5 presented with a sequence of images, each of which needs to be identified as to 6 whether it was already seen or not. Our work is a study of multiple ways to learn a 7 working memory model using recurrent neural networks that learn to remember 8 input images across timesteps in supervised and reinforcement learning settings. 9 The reinforcement learning setting is inspired by the popular view in Neuroscience 10 that the working memory in the prefrontal cortex is modulated by a dopaminergic 11 mechanism. We consider the VWM task as an environment that rewards the 12 agent when it remembers past information and penalizes it for forgetting. We 13 quantitatively estimate the performance of these models on sequences of images 14 from a standard image dataset (CIFAR-100 [2]) and their ability to remember 15 and recall. Based on our analysis, we establish that a gated recurrent neural 16 network model with long short-term memory units trained using reinforcement 17 learning is powerful and more efficient in temporally consolidating the input spatial 18 information. This work is an initial analysis as a part of our ultimate goal to model 19 the behavior and information processing of the working memory of the brain and to 20 use brain imaging data captured from human subjects during the VWM cognitive 21 task to understand various memory mechanisms of the brain. 22
A CROSS-PLATFORM DEVELOPMENT TOOLCHAIN FOR JIT-COMPILATION IN MULTIMEDIA SOFTWARE

Given the relative stagnation in single-thread performance of many processors in the recent years, made even worse by the recent security findings such as SPECTRE or L1TF which led to restrictions in existing features and decreased performance for the sake of security, it is necessary to find new ways to improve the run-time performance of dynamic multimedia systems. In this paper, we present the introduction of a just-in-time compiler in the ossia score interactive score authoring and playback software. We discuss in particular the creation of a toolchain and software development kit for C++ just-intime compilation on the three major desktop platforms, the challenges and benefits caused by the use of C++ in terms of standard library requirement, but also the benefits that the system offers in terms of live-coding.
THE PREDICTION OF THE TWO PARAMETER RIDGE ESTIMATOR

biased estimation procedures have been proposed as an alternative to least squares, there has been little analysis of the predictive performance of the resulting equations. Therefore, we discuss the predictive performanceof the Two Parameter Ridge (2PR) estimator compared to ordinary least squares, principal components andridge regression estimators. Also, the theoretical results are illustrated by a numerical example and a regionis established where the 2PR estimator is uniformly superior to the other estimators
LEARNING SUPERVISED BINARY HASHING WITHOUT BINARY CODE OPTIMIZATION

1 Abstract The goal of binary hashing is to learn a hash function that maps highdimensional points to bit codes, which can be used to speed up search on large databases. Most papers use optimization approaches based on a suitable objective function with a difficult and inexact optimization. Recently, it has been shown that the hash function for a code bit may be learned independently from that of the other code bits. One simply optimizes a single-bit objective function defined on a random data sample, and then fits a binary classifier to the resulting codes. We show that it is even possible to dispense with the single-bit optimization, by assigning binary codes to the points based on their similarity to a randomly chosen seed point. This procedure is very simple, scalable, and is competitive with the state-of-the-art methods in retrieval metrics.
Supplementary Material : An Empirical Study on Leveraging Scene Graphs for Visual Question Answering

Human annotated scene graph. We leverage the ground truth scene labels of the Visual Genome (VG) dataset [4] as our human annotated scene graphs1. Machine generated scene graph. The commonly used data split of scene graph generation research is different from qaV G [1]2. Thus we retrain the start-of-the-art Neural Motifs (NM) [8] model only using the training images from qaV G. Specifically, we retrain both object detector and relationship classifier of the NM to ensure the model never uses testing images for training. We run the well-trained NM model on qaV G to obtain the machine generated scene graph by removing entities (<0.2) and relationships (<0.1) with small probabilities. We show the scene graph detection performance in Table 1.
Evaluation of Water-Resistive Barrier Performance Using Simple Ponding and Vapor Diffusion Tests

This paper describes a study comparing the water-resistive behavior of two commonly available housewrap products and No. 15 building felt in which the WRB materials were exposed to water (with and without surfactants) and three typical construction scenarios: no contact with OSB sheathing, contact with OSB sheathing, and contact with OSB sheathing combined with a staple fastener.
Structural Health Monitoring and Earthquake Early Warning on 5 G uRLLC Network

This work deals with the development of a permanent structural monitoring system for buildings, based on innovative minimally invasive technologies in order to provide information about the structural behavior under normal conditions and especially in the presence of seismic events. The gathered information will be processed through model based and data based approaches, in order to compare and possibly integrate these techniques. Referring to the 5G vision the SHM system can be considered depending on the operational scenario: in the case of data collection and processing from sensors in monitored buildings, considering the high number of sensors installed, it can refer to the mMTC context. Viceversa, during a seismic event or just after it, the use case requires high reliability connectivity and, sometimes, low latency. Those features refer to the URLL context. It seems interesting to evaluate and experiment the ability of 5G network to dynamically adapt to the changing scenario that this use case can provide. Moreover this paper presents an innovative 5G architecture for Earthquake Early Warning that uses SHM system to detect a seismic event and to propagate a message reporting the event detection to all the buildings that may be damaged by the event.
Microtensile test in dental research. Controversial aspects in statistical analysis (experimental unit and premature failures)

Aims: The aim of this study was to present the controversial aspects in performing inferential statistical analysis with regard to selection of the experimental unit and procedures adopted in the case of pre-test failures. Material and Method: Eighty-seven dissertations and theses in the field of dentistry were evaluated, in which microtensile testing available at three public Universities in the State of Sao Paulo were performed, namely: School of Dentistry, USP; School of Dentistry, Unesp (Araraquara and Sao Jose dos Campos) and the Piracicaba School of Dentistry (Unicamp). Results: As regards the experimental unit, 34 (39.08%) theses and/or dissertations used the “stick” and 53 (60.91%) the “tooth/block” type. With regard to pre-test failures, 9 (10.34%) theses and/or dissertations attributed the value “0”, 6 (6.89%) disregarded the sticks, 2 (2.29%) attributed the minimum value of 2 MPa, 1 (1,14%) the minimum value of 4 MPa, 1 (1.14%) attributed half the minimum value of the group and 68 (78.16%) did not mention the occurrence of pre-test failures. Conclusion: As regards the experimental unit, at present the experimental unit is considered the tooth (or ceramic bloc) and not the stick. With regard to pre-test failures, the following are considered: Attribution of a minimum bond strength value under the experimental condition or in the group considered; expressing the number and percentage of cases of failures under each experimental condition; which failures were included in the statistical analysis and making a comparison between the analysis with exclusion of the sticks and analysis without inclusion of the sticks.
Compression of Electron Bunches applied to Ultrafast Electron Diffraction

The dynamics of atomic scale structures during structural change can be studied by Ultrafast Electron Diffraction (UED). The time resolution needed to reveal the fastest dynamics is 100 fs. Sub-angstrom structural resolution becomes possible with 1-1000 pC of charge necessary for diffraction pattern analysis during subtle structural changes. This combination of requirements cannot currently be realized due to the space-charge temporal broadening inherent to bunches of electrons of high fluence and short temporal duration. Simulations show that the incorporation of a specially designed Radio-Frequncy (RF) cavity into the UED apparatus removes this technical limitation. The RF cavity reverses the near linear position-momentum distribution of the temporally broadened electron bunch, causing the bunch to recompress itself as it propagates. It is found that our proposed method allows for sub-100 fs bunches with maximum charge of 0.6 pC, almost 3 orders of magnitude improvement over today's state of the art.
An Efﬁcient LiDAR-IMU Calibration Method Based on Continuous-Time Trajectory

—Sensor calibration is a prerequisite for multi- sensor fusion system. This paper presents a novel method for calibrating the extrinsic transformation between a multi- beam LiDAR and an Inertial Measurement Unit (IMU) based on continuous-time batch optimization. The continuous-time formulation is well suitable for the problem with a large number of measurements, such as the LiDAR points in this calibration problem. Furthermore, since poses at every time instant are available in this continuous-time formulation, LiDAR distortion even under severe motion can be corrected. Experiments on both simulated and real-world datasets are carried out, which conﬁrms the feasibility and high accuracy of the proposed method.
An Introduction to Evolutionary Computation

Evolutionary Computation (EC) deals with computational methods that incorporate ideas and principles from natural evolution. More specifically, it includes a class of so-called evolutionary algorithms (EAs), which are heuristic search algorithms that can be used to search for good solutions to difficult problems. These algorithms try to “evolve” better and better solutions, as opposed to constructing one from scratch, and are particularly suitable for problems for which no known efficient (polynomial-time) algorithm exists, and for which exhaustive search is impractical. These evolutionary algorithms are fairly simple and general, and can be applied to a wide range of search and optimization problems. However, to get an appreciation for how and why they work, it is useful to understand the basics of genetics and natural evolution.
Two Minds and Emotion

Human behavior can be viewed as the integration of the outputs of Systems 1, i.e., unconscious automatic processes, and System 2, i.e., conscious deliberate processes. System 1 activates a sequence of automatic actions. System 2 monitors System 1’s performance according to the plan it has created, and it activates future possible courses of actions as well. At the same time when these forward processes are working, System 1 and System 2 deal with the outcome of the forward processes by estimating the results of System 1’s and System 2’s performance, i.e., good or bad, and generating emotions depending on the degree of goodness or badness of the estimation. Emotions are generated through the dynamics of the parallel processing of System 1 and System 2, which is called O-PDP, Organic Parallel Distributed Processing. This paper discusses how emotion generation process is integrated with the Kahneman’s System 1 and System 2 model of human decision-making. Keywords–Two Minds; Organic-PDP; Two Minds; Consciousness; Unconsciousness; Emotion.
BCW Design Based P 300 and Path Guidance

The main objective of this paper is to build Smart Brain Controlled wheelchair (SBCW) intended for patient of Amyotrophic Lateral Sclerosis (ALS). Brain control interface (BCI) gave solutions for a patients having a low rate of data exchange, alsoby using the BCIthe user should have the ability to meditate and tension to let the signal get received. Using the BCI continuously is very much exhausted for the patients, Theproposed system is trying to give all handicapped people and ALS patients the simplest way to let them have a life at least near to the normal life. The system will mainly depend on the Electroencephalogram (EEG) signalsand also on the Electromyography (EMG) signals to put the system in command and out of command. The system will interface with user through a tablet and it will be secured by sensors and tracking system to avoid any obstacle. The proposed system is safe and easily built with lower cost compared with other similar systems.
A Low Voltage Low Power Sigma Delta Modulator Design

Bio-medical electronics have made great progress in the past decade. Data converter plays an important role in the whole system, which enables sampling the analog signal from the real world and processing the signal in a stable, fast and simple manner in digital domain. In this work, a discrete-time sigma-delta modulator is presented with low power consumption and sufficient resolution in purpose of ECG signal sampling for pacemaker application. A bulk-driven OTA with 0.8V supply voltage is employed in the whole system, applying the self-cascode technique.
Reasoning on Multi-Hop Questions with HotpotQA

Analysis — Query Attention • HotpotQA [1] is a question-answering (QA) dataset focusing on multi-hop reasoning; the answers to the questions come from aggregating parts of the context • Also requires explanation in the form of “supporting facts” to produce an answer • We augmented the baseline model for HotpotQA, by proposing improvements in learning and optimization, attention, reasoning, and representation Models improving reasoning and attention; Rsn-A, Rsn-B, Att-C
Zr-DFO-Cetuximab as a Molecular Imaging Agent to Identify Cetuximab Resistance in Head and Neck Squamous Cell Carcinoma

Background: Despite the improvement in clinical outcomes for head and neck squamous cell carcinoma (HNSCC) as the result of cetuximab, patients may present with or develop resistance that increases tumor recurrence rates and limits clinical efficacy. Therefore, identifying those patients who are or become resistant is essential to tailor the best therapeutic approach. Materials and Methods: Cetuximab was conjugated to p-NCS-Bz-DFO and labeled with Zr. The resistance model was developed by treating FaDu cells with cetuximab. Western blotting (WB) and specific binding assays were performed to evaluate epidermal growth factor receptor (EGFR) expression and Zr-DFO-cetuximab uptake in FaDu cetuximab-resistant (FCR) and FaDu cetuximab-sensitive (FCS) cells. Positron emission tomography imaging and biodistribution were conducted in NU/NU nude mice implanted with FCR or FCS cells. Results: Cetuximab was successfully radiolabeled with Zr (‡95%). Binding assays performed in FCR and FCS cells showed significantly lower Zr-DFO-cetuximab uptake in FCR ( p < 0.0001). WB suggests that the resistance mechanism is associated with EGFR downregulation ( p = 0.038). This result is in agreement with the low uptake of Zr-DFO-cetuximab in FCR cells. Tumor uptake of Zr-DFO-cetuximab in FCR was significantly lower than FCS tumors ( p = 0.0340). Conclusions: In this work, the authors showed that Zr-DFO-cetuximab is suitable for identification of EGFR downregulation in vitro and in vivo. This radiopharmaceutical may be useful for monitoring resistance in HNSCC patients during cetuximab therapy.
Description of gold and copper anomalies using fractal and stepwise factor analysis according to stream sediments in Lahrud 1:100,000 sheet, NW Iran

This aim of the study is to describe the copper and gold anomalies, by using the combination of the Concentration–Number (C–N) fractal and the stepwise factor analysis, based on stream sediment samples in Lahrud 1:100,000 sheet, NW Iran. The field of study is situated in Alborz–Azerbaijan belt. According to index ore deposit types, elements related to Au and Cu hydrothermal mineralization were selected for this study. Consequently, all the noise elements were removed after applying four steps of factor analysis and As, Sb, Sn, W, Co, Mn, Zn, Ti, Ba, Ni, Cr, Au, Cu, and B were grouped in the five factors. Cu and Au are grouped on factor 4 of the last step (FAC4–4). The C–N log–log plots for factor scores were plotted and threshold values were determined in order to a generation of elemental geochemical maps. The anomalous areas for metallic elements specifically copper and gold, are located in the NW and SW parts of the region which show a correlation between alteration zones, faults, and intrusions.
Draft Hemipenes eversion behavior : a new form of communication in two Liolaemus lizards

Journal: Canadian Journal of Zoology Manuscript ID cjz-2018-0195.R2 Manuscript Type: Article Date Submitted by the Author: 29-Aug-2018 Complete List of Authors: Ruiz-Monachesi, Mario; Instituto de Bio y Geo Ciencias del NOA Paz, Alejandra; Instituto de Bio y Geo Ciencias del NOA Quipildor, Angel; Instituto de Bio y Geo Ciencias del NOA; Universidad Nacional de Salta, Cátedra Anatomía Comparada Is your manuscript invited for consideration in a Special Issue? : Not applicable (regular submission)
A Qualitative Analysis of Android Taint-Analysis Results

In the past, researchers have developed a number of popular taint-analysis approaches, particularly in the context of Android applications. Numerous studies have shown that automated code analyses are adopted by developers only if they yield a good "signal to noise ratio", i.e., high precision. Many previous studies have reported analysis precision quantitatively, but this gives little insight into what can and should be done to increase precision further. To guide future research on increasing precision, we present a comprehensive study that evaluates static Android taint-analysis results on a qualitative level. To unravel the exact nature of taint flows, we have designed COVA, an analysis tool to compute partial path constraints that inform about the circumstances under which taint flows may actually occur in practice. We have conducted a qualitative study on the taint flows reported by FlowDroid in 1,022 real-world Android applications. Our results reveal several key findings: Many taint flows occur only under specific conditions, e.g., environment settings, user interaction, I/O. Taint analyses should consider the application context to discern such situations. COVA shows that few taint flows are guarded by multiple different kinds of conditions simultaneously, so tools that seek to confirm true positives dynamically can concentrate on one kind at a time, e.g., only simulating user interactions. Lastly, many false positives arise due to a too liberal source/sink configuration. Taint analyses must be more carefully configured, and their configuration could benefit from better tool assistance.
Why Do Public Firms Issue Public and Private Equity , Convertibles and Debt ? 1

We examine a comprehensive set of private and public security issuance decisions by publicly traded companies. We study private and public issues of debt, convertibles and common equity securities. The market for public firms issuing private securities is large. Of the over 13,000 issues we examine, more than half are in the private market. We find that asymmetric information and moral hazard problems play a large role in the public versus private market choice and the security type choice. Our findings show that asymmetric information impacts security choice in a particular pattern: Conditional on issuing in the public market we find a pecking order of security issuance holds, firms with higher measures of asymmetric information are less likely to issue equity. We find a reversal of this pecking order in the private market, firms with higher measures of asymmetric information are more likely to issue equity. Second, we find risk and investment opportunities are important in determining which security type a firm issues. Firms with high risk, low profitability and good investment opportunities are more likely to choose equity and convertibles and to issue privately. This version: October 2004 Comments Welcome ∗University of Pennsylvania and University of Maryland and NBER respectively. Gomes can be reached at gomes@wharton.upenn. edu and Phillips can be reached at gphillips@rhsmith.umd. edu. We thank Murillo Campello, Mark Chen, Gerry Hoberg and Craig MaKinlay as well as from seminar participants at Cornell, Penn State, UBC and Wharton for helpful comments. We alone are responsible for the conclusions and analysis in this paper. Why Do Public Firms Issue Public and Private Equity, Convertibles and Debt?
PERSPECT IVE Of scales and stationarity in animal movements

E-mail: simon.benhamou@cefe.cnrs. fr Abstract With recent technological advances in tracking devices, movements of numerous animal species can be recorded with a high resolution over large spatial and temporal ranges. This opens promising perspectives for understanding how an animal perceives and reacts to the multi-scale structure of its environment. Yet, conceptual issues such as confusion between movement scales and searching modes prevent us from properly inferring the movement processes at different scales. Here, I propose to build on stationarity (i.e. stability of statistical parameters) to develop a consistent theoretical framework in which animal movements are modelled as a generic composite multiscale multi-mode random walk model. This framework makes it possible to highlight scales that are relevant to the studied animal, the nature of the behavioural processes that operate at each of these different scales, and the way in which the processes involved at any given scale can interact with those operating at smaller or larger scales. This explicitly scale-focused approach should help properly analyse actual movements by relating, for each scale and each mode, the values of the main model parameters (speed, shortand long-term persistences, degree of stochasticity) to the animal’s needs and skills and its response to its environment at multiple scales.
D 4 . 3 Automatic Extraction of Performance-related Parameters from Audio Recordings and Live Performances

Grant Agreement nr 601166 Project title Performances as Highly Enriched aNd Interactive Concert eXperiences Project acronym PHENICX Start date of project (dur.) Feb 1st, 2013 (3 years) Document reference PHENICX-D-WP4-OFAI-140610D4.3 PerformanceParameterExtraction Report availability PU Public Document due Date July 31, 2014 Actual date of delivery July 22, 2014 Leader OFAI Reply to Gerhard Widmer (OFAI) ( gerhard.widmer@ofai.at ) Additional main contributors (authors name / partner acr.) Thassilo Gadermaier (OFAI) Martin Gasser (OFAI) Maarten Grachten (OFAI) Andreas Arzt (JKU) Harald Frostel (JKU) Document status Final