Miracle-dz/UniFAR-FTUs huggingface dataset:
Lamphone: Passive Sound Recovery from a Desk Lamp's Light Bulb Vibrations

In this paper, we introduce "Lamphone," an optical side-channel attack used to recover sound from desk lamp light bulbs;such lamps are commonly used in home offices, which became a primary work setting during the COVID-19 pandemic. We show how fluctuations in the air pressure on the surface of a light bulb, which occur in response to sound and cause the bulb to vibrate very slightly (a millidegree vibration), can be exploited by eavesdroppers to recover speech passively, externally, and using equipment that provides no indication regarding its application. We analyze a light bulb's response to sound via an electro-optical sensor and learn how to isolate the audio signal from the optical signal. We compare Lamphone to related methods presented in other studies and show that Lamphone can recover sound at high quality and lower volume levels that those methods. Finally, we show that eavesdroppers can apply Lamphone in order to recover speech at the sound level of a virtual meeting with fair intelligibility when the victim is sitting/working at a desk that contains a desk lamp with a light bulb from a distance of 35 meters.
Design and Evaluation of a GPU Streaming Framework for Visualizing Time-Varying AMR Data

We describe a systematic approach for rendering time-varying simulation data produced by exa-scale simulations, using GPU workstations. The data sets we focus on use adaptive mesh reﬁnement (AMR) to overcome memory bandwidth limitations by representing interesting regions in space with high detail. Particularly, our focus is on data sets where the AMR hierarchy is ﬁxed and does not change over time. Our study is motivated by the NASA Exajet, a large computational ﬂuid dynamics simulation of a civilian cargo aircraft that consists of 423 simulation time steps, each storing 2.5 GB of data per scalar ﬁeld, amounting to a total of 4 TB. We present strategies for rendering this time series data set with smooth animation and at interactive rates using current generation GPUs. We start with an unoptimized baseline and step by step extend that to support fast streaming updates. Our approach demonstrates how to push current visualization workstations and modern visualization APIs to their limits to achieve interactive visualization of exa-scale time series data sets
Financial Exposure and Bank Mergers: Micro and Macro Evidence from the EU

This column studies the links between interbank liability and equity markets (financial exposure), and cross - border mergers and acquisitions (M&As) in the European banking sector, both at the micro and macro level. Using a binary logit model, the column first examines ­– at the micro level – how financial exposures between banks affect the probability of M&A. It finds that financial interlinkages significantly increase the chances of them taking place. Using a gravity model, the column then investigates – at the macro level – whether the micro results hold. Not only are financial links positively and significantly correlated with the number of M&As between countries, but they are also a better predictor than trade – traditionally used in the macro literature on M&A. Finally, a M&A compatibility index is built for each pair of EU countries. The European banking sector is characterised by a wide range of interconnections. These are both legal, through branches and subsidiaries, and financial, through liabilities and equity (henceforth, exposures). This column highlights that the bilateral financial interlinkages favour consolidation between European banks, via cross - border mergers and acquisitions (M&As). To do that, it uses bank - level data for the period 2014 - 20 for all the European Union Member States plus the United Kingdom. The database contains 3,491 M&As (810 cross - border transactions) between 1999 and 2020 which could be match with banks balance sheet data, of which 385 took place in the period 2014 - 2020 (61 cross - border transactions) that could be matched with financial exposure data. Important financial stability benefits may result from financial integration via M&A, and especially cross - border M&A, for example financial risk diversification and risk sharing. Understanding the links between cross - border financial linkages and cross - border M&As is therefore essential.
Multilingual and Multimodal Learning for Brazilian Portuguese

Humans constantly deal with multimodal information, that is, data from different modalities, such as texts and images. In order for machines to process information similarly to humans, they must be able to process multimodal data and understand the joint relationship between these modalities. This paper describes the work performed on the VTLM (Visual Translation Language Modelling) framework from (Caglayan et al., 2021) to test its generalization ability for other language pairs and corpora. We use the multimodal and multilingual corpus How2 (Sanabria et al., 2018) in three parallel streams with aligned English-Portuguese-Visual information to investigate the effectiveness of the model for this new language pair and in more complex scenarios, where the sentence associated with each image is not a simple description of it. Our experiments on the Portuguese-English multimodal translation task using the How2 dataset demonstrate the efficacy of cross-lingual visual pretraining. We achieved a BLEU score of 51.8 and a METEOR score of 78.0 on the test set, outperforming the MMT baseline by about 14 BLEU and 14 METEOR. The good BLEU and METEOR values obtained for this new language pair, regarding the original English-German VTLM, establish the suitability of the model to other languages.
A Study of Music Genre Classification with Bilinear Convolutional Neural Network

: In this paper, we propose a new bilinear neural network (BCNN) and apply it to music genre classification. We use Resnet and Densenet which are pre-trained to construct the proposed model . At the end of the two networks, we fuse their output feature and send it to the classifier. Our experiments are carried out on the GTZAN dataset. We extract the mel spectrogram of all the audio in the dataset as the input feature and use the fully connected layer as the classifier to study whether the output features of the two classical CNNs are complementary and can achieve better results in this task. Under the same experimental environment and hyperparameters, our proposed BCNN model achieves better classification results than Resnet and Densenet and its classification accuracy is about 81.17%
The Automatic Extraction of Linguistic Biomarkers as a Viable Solution for the Early Diagnosis of Mental Disorders

Digital Linguistic Biomarkers extracted from spontaneous language productions proved to be very useful for the early detection of various mental disorders. This paper presents a computational pipeline for the automatic processing of oral and written texts: the tool enables the computation of a rich set of linguistic features at the acoustic, rhythmic, lexical, and morphosyntactic levels. Several applications of the instrument - for the detection of Mild Cognitive Impairments, Anorexia Nervosa, and Developmental Language Disorders - are also briefly discussed.
CTAP for Chinese:A Linguistic Complexity Feature Automatic Calculation Platform

The construct of linguistic complexity has been widely used in language learning research. Several text analysis tools have been created to automatically analyze linguistic complexity. However, the indexes supported by several existing Chinese text analysis tools are limited and different because of different research purposes. CTAP is an open-source linguistic complexity measurement extraction tool, which prompts any research purposes. Although it was originally developed for English, the Unstructured Information Management (UIMA) framework it used allows the integration of other languages. In this study, we integrated the Chinese component into CTAP, describing the index sets it incorporated and comparing it with three linguistic complexity tools for Chinese. The index set includes four levels of 196 linguistic complexity indexes: character level, word level, sentence level, and discourse level. So far, CTAP has implemented automatic calculation of complexity characteristics for four languages, aiming to help linguists without NLP background study language complexity.
The Ellogon Web Annotation Tool: Annotating Moral Values and Arguments

In this paper, we present the Ellogon Web Annotation Tool. It is a collaborative, web-based annotation tool built upon the Ellogon infrastructure offering an improved user experience and adaptability to various annotation scenarios by making good use of the latest design practices and web development frameworks. Being in development for many years, this paper describes its current architecture, along with the recent modifications that extend the existing functionalities and the new features that were added. The new version of the tool offers document analytics, annotation inspection and comparison features, a modern UI, and formatted text import (e.g. TEI XML documents, rendered with simple markup). We present two use cases that serve as two examples of different annotation scenarios to demonstrate the new functionalities. An appropriate (user-supplied, XML-based) annotation schema is used for each scenario. The first schema contains the relevant components for representing concepts, moral values, and ideas. The second includes all the necessary elements for annotating argumentative units in a document and their binary relations.
Barch: an English Dataset of Bar Chart Summaries

We present Barch, a new English dataset of human-written summaries describing bar charts. This dataset contains 47 charts based on a selection of 18 topics. Each chart is associated with one of the four intended messages expressed in the chart title. Using crowdsourcing, we collected around 20 summaries per chart, or one thousand in total. The text of the summaries is aligned with the chart data as well as with analytical inferences about the data drawn by humans. Our datasets is one of the first to explore the effect of intended messages on the data descriptions in chart summaries. Additionally, it lends itself well to the task of training data-driven systems for chart-to-text generation. We provide results on the performance of state-of-the-art neural generation models trained on this dataset and discuss the strengths and shortcomings of different models.
Impacts to Quail Space Use and Demographics from Oil and Gas Development

Southern Texas contains some of the last relatively unfragmented habitat for northern bobwhite (Colinus virginianus; hereafter, bobwhite) and scaled quail (Callipepla squamata) in the United States. Development of the Eagle Ford Shale hydrocarbon formation in this region could negatively impact quail and their habitat. Our objective was to examine the indirect effects of oil and gas activity (traffic and noise) on bobwhite and scaled quail on 2 private ranches in southern Texas. In 2015 and 2016, we radio-marked bobwhite and scaled quail in 2 areas where oil and gas activity was occurring (disturbed treatment) and 2 areas where little oil and gas activity occurred (undisturbed treatment). We measured vehicle passages and modeled noise propagation from oil and gas infrastructure at 2 biologically relevant frequencies (250 Hz and 1,000 Hz) in our study area to quantify oil and gas disturbance and examine its effects on quail space use (site selection and home range size) and demographics (survival, nest success, and density). Bobwhite and scaled quail selected areas 0–200 m and >425 m, respectively, from the primary, high-traffic roads in the disturbed treatment. In the undisturbed treatment, bobwhite and scaled quail selected areas 0–425 m and 0–300 m from primary roads, respectively. Bobwhite and scaled quail selected areas with sound levels 0–1.6 and 0–2.2 dB above ambient levels at the 250-Hz frequency level, respectively. At 1,000 Hz, bobwhite and scaled quail selected areas with sound levels 0–2 and 0–3.2 dB above ambient levels, respectively. We found no evidence that disturbance variables affected bobwhite and scaled quail home range size, survival, or density. We found bobwhite nest success decreased as sound levels (dB) at 250 Hz increased; we found no relationship between nest success and disturbance for scaled quail, possibly as they avoided major oil and gas disturbances. In calculations of the total footprint of quail habitat loss, indirect loss due to oil and gas activity needs to be considered in addition to direct loss due to conversion of rangeland to oil and gas infrastructure. Citation: Davis, K. R. , E. D. Grahmann, F. Hernández, C. R. Currie, T. E. Fulbright, D. B. Wester, and H. L. Perotto-Baldivieso. 2022. Impacts to quail space use and demographics from oil and gas development. National Quail Symposium Proceedings 9 76–91:. https:// doi.org/10.7290/nqsp09cSPv
Leveraging Pre-trained Language Models for Gender Debiasing

Studying and mitigating gender and other biases in natural language have become important areas of research from both algorithmic and data perspectives. This paper explores the idea of reducing gender bias in a language generation context by generating gender variants of sentences. Previous work in this field has either been rule-based or required large amounts of gender balanced training data. These approaches are however not scalable across multiple languages, as creating data or rules for each language is costly and time-consuming. This work explores a light-weight method to generate gender variants for a given text using pre-trained language models as the resource, without any task-specific labelled data. The approach is designed to work on multiple languages with minimal changes in the form of heuristics. To showcase that, we have tested it on a high-resourced language, namely Spanish, and a low-resourced language from a different family, namely Serbian. The approach proved to work very well on Spanish, and while the results were less positive for Serbian, it showed potential even for languages where pre-trained models are less effective.
Occupant ’ s Spontaneous Behavior During Disaster : Indoor and Outdoor

Indonesia is a country that is prone to natural disaster. With the position in the Pacific Ring of Fire zone and surrounded by three tectonic plates, the situation contributes to most natural disaster occurances in Indonesia, such as earthquakes, tsunami, and volcanic eruptions. Human behavior is difficult to predict when in a tense and chaotic emergency such as a natural disaster. Observation of spontaneous actions during a disaster enables to identify the safety measurements taken during an emergency. These observations can provide knowledge of how behavior patterns occur during natural disasters. The purpose of this study is to examine and understand any behavior in spontaneous actions that are worthy to be studied by architects. This study uses a qualitative-quantitative approach that is exploratory and explanatory. In a qualitative approach, the data in previous studies were analyzed using open coding, axial coding, and selective coding. The quantitative method approach is carried out using principal component analysis (PCA), factor analysis, and analysis of variance (Anova). Data obtained through online questionnaires, distributed with snowball sampling techniques. The results obtained show seven dimensions of spontaneous action during natural disasters, with two actions that have significant differences in indoor and outdoor approaches.
Cross-Level Semantic Similarity for Serbian Newswire Texts

Cross-Level Semantic Similarity (CLSS) is a measure of the level of semantic overlap between texts of different lengths. Although this problem was formulated almost a decade ago, research on it has been sparse, and limited exclusively to the English language. In this paper, we present the first CLSS dataset in another language, in the form of CLSS.news. sr – a corpus of 1000 phrase-sentence and 1000 sentence-paragraph newswire text pairs in Serbian, manually annotated with fine-grained semantic similarity scores using a 0–4 similarity scale. We describe the methodology of data collection and annotation, and compare the resulting corpus to its preexisting counterpart in English, SemEval CLSS, following up with a preliminary linguistic analysis of the newly created dataset. State-of-the-art pre-trained language models are then fine-tuned and evaluated on the CLSS task in Serbian using the produced data, and their settings and results are discussed. The CLSS.news. sr corpus and the guidelines used in its creation are made publicly available.
Lowering Barriers to Remote Education: Experimental Impacts on Parental Responses and Learning

We conduct a randomized controlled trial with households of secondary school students to investigate how parents adjust their investments in response to three educational interventions: an informational campaign about an educational phone application, an internet data subsidy, and one-on-one phone learning support. We find that offering an educational service in a context where other barriers to takeup exist can still trigger parental educational investments by acting as a signal or nudge. These behavioral changes result in lasting learning gains concentrated among richer households, reflecting that the relevant behavior change—increased tutoring investment—is easier for them to implement. In contrast, when interventions do increase take-up, they have the potential to narrow the socioeconomic achievement gap. We observe that increases in usage of the targeted educational service limit parental behavioral responses. This implies that learning gains in these cases are directly caused by the potential effectiveness of the services adopted. In our setting, remote one-to-one teacher support improves learning among students from poorer households, whereas receiving the free data package jointly with the app information has no impact on learning. JEL Classification: C93, I21, I24, J13, O15
Effects of Climate Change on Northern Bobwhite Nesting Chronology and Clutch Size

Widespread changes to breeding bird phenology in response to climate change have been apparent in North America for several decades. While the impact of an earlier breeding season may be minimal by itself, changes in community-level interactions can be greatly influenced because of varying responses to climate change in different trophic levels. Climate change has been shown to alter the onset of breeding season and chick survival, and lead to population declines for game birds in high latitudes, at high elevations, and on the periphery of their range. The topic of climate change in relation to northern bobwhite (Colinus virginianus; hereafter, bobwhite) populations has attracted interest in the past 2 decades. Some researchers have hypothesized that climate change has the potential to cause the breeding season to initiate sooner and have a shorter duration. Using a 29year dataset (1992–2020) with 1,171 individual bobwhites, we analyzed how temperatures prior to the breeding season affected the timing of nest initiation and clutch size, and how the length of the breeding season varied over time. We determined that the average minimum daily temperatures 30 days prior to the breeding season warmed by 0.07° C/year from 1992–2020. For any given year, we found that nest initiation could occur 1.12 days earlier for every 1° C increase in temperature. Overall, we determined that the timing of the nesting season had not changed from 1992–2020. The overall average breeding season length (135 days) or last average initiation date (27 Aug) did not change over the course of our study. We did not find that clutch sizes have changed over time and they were not correlated to pre-laying temperature. We attribute the lack of significant change in nesting chronology to plasticity of populations within the core of the range and the intensity of bobwhite management on the landscape. Citation: Rectenwald, J. A. , D. C. Sisson, and J. A. Martin. 2022. Effects of climate change on northern bobwhite nesting chronology and clutch size. National Quail Symposium Proceedings 9:341–347. https://doi.org/10.7290/nqsp09KPkE
Photonic quantum-corral ring laser: A fermionic phase transition

Extensive Bose-Einstein condensation research activities have recently led to studies of fermionic atoms and optical confinements. Here we present a case of micro-optical fermionic electron phase transition. Optically confined ordering and phase transitions of a fermionic cloud in dynamic steady state are associated with Rayleigh emissions from photonic quantum ring manifold which are generated by nature without any ring lithography. The whispering gallery modes, produced in a semiconductor Rayleigh-Fabry-Perot toroidal cavity at room temperature, exhibit novel properties of ultralow thresholds open to nano-ampere regime, thermal stabilities from square-root-T-dependent spectral shift, and angularly varying intermode spacings. The photonic quantum ring phenomena are associated with a photonic field-driven phase transition of quantum-well-to-quantum-wire and hence the photonic (non-de Broglie) quantum corral effect on the Rayleigh cavity-confined carriers in dynamic steady state. Based upon the intra-cavity fermionic condensation we also offer a prospect for an electrically driven few-quantum dot single photon source from the photonic quantum ring laser for quantum information processors.
Kayaking and wagging of rigid rod-like colloids in shear flow

In this thesis we report on Brownian dynamics simulations of colloidal suspensions of rigid spherocylinders in shear flow. A widely investigated topic, rod-like liquid crystalline polymers (LCPs) in the nematic phase arouse much scientific interest, both theoretically and experimentally, not only due to the spectacular collective orientational motions that these systems perform under shear but also due to the peculiar rheological properties compared to those of the isotropic phase. The goal of our study is to simulate and to understand the dynamical and rheological behavior exhibited in shear flow. Our simulated systems are based on the fd virus, because this slightly flexible nearly monodisperse biopolymer is considered a convenient experimental representative for a rigid rod-like particle.