Miracle-dz/UniFAR-FTUs huggingface dataset:
Haha-POD: An Attempt for Laughter-Based Non-Verbal Speaker Verification

It is widely acknowledged that discriminative representation for speaker verification can be extracted from verbal speech. However, how much speaker information that non-verbal vocalization carries is still a puzzle. This paper explores speaker verification based on the most ubiquitous form of non-verbal voice, laughter. First, we use a semi-automatic pipeline to collect a new Haha-Pod dataset from open-source podcast media. The dataset contains over 240 speakers’ laughter clips with corresponding high-quality verbal speech. Second, we propose a Two-Stage Teacher-Student (2S-TS) framework to minimize the within-speaker embedding distance between verbal and non-verbal (laughter) signals. Considering Haha-Pod as a test set, two trial sets (S2L-Eval) are designed to verify the speaker’s identity through laugh sounds. Experimental results demonstrate that our method can significantly improve the performance of the S2L-Eval test set with only a minor degradation on the VoxCeleb1 test set. The resources for the Haha-Pod dataset can be found at https://github.com/nevermoreLin/HahaPod.
SPICED: News Similarity Detection Dataset with Multiple Topics and Complexity Levels

Nowadays, the use of intelligent systems to detect redundant information in news articles has become especially prevalent with the proliferation of news media outlets in order to enhance user experience. However, the heterogeneous nature of news can lead to spurious findings in these systems: Simple heuristics such as whether a pair of news are both about politics can provide strong but deceptive downstream performance. Segmenting news similarity datasets into topics improves the training of these models by forcing them to learn how to distinguish salient characteristics under more narrow domains. However, this requires the existence of topic-specific datasets, which are currently lacking. In this article, we propose a new dataset of similar news, SPICED, which includes seven topics: Crime&Law, Culture&Entertainment, Disasters&Accidents, Economy&Business, Politics&Conflicts, Science&Technology, and Sports. Futhermore, we present four distinct approaches for generating news pairs, which are used in the creation of datasets specifically designed for news similarity detection task. We benchmarked the created datasets using MinHash, BERT, SBERT, and SimCSE models.
Nonparametric estimation of conditional densities by generalized random forests

Considering a continuous random variable Y together with a continuous random vector X, I propose a nonparametric estimator f^(.|x) for the conditional density of Y given X=x. This estimator takes the form of an exponential series whose coefficients T = (T1,.,TJ) are the solution of a system of nonlinear equations that depends on an estimator of the conditional expectation E[p(Y)|X=x], where p(.) is a J-dimensional vector of basis functions. A key feature is that E[p(Y)|X=x] is estimated by generalized random forest (Athey, Tibshirani, and Wager, 2019), targeting the heterogeneity of T across x. I show that f^(.|x) is uniformly consistent and asymptotically normal, while allowing J to grow to infinity. I also provide a standard error formula to construct asymptotically valid confidence intervals. Results from Monte Carlo experiments and an empirical illustration are provided.
Veer: Verifying Equivalence of Workflow Versions in Iterative Data Analytics

Data analytics using GUI-based workflows is an iterative process in which an analyst makes many iterations of changes to refine the workflow, generating a different version at each iteration. In many cases, the result of executing a workflow version is equivalent to a result of a prior executed version. Identifying such equivalence between the execution results of different workflow versions is important for optimizing the performance of a workflow by reusing results from a previous run. The size of the workflows and the complexity of their operators often make existing equivalence verifiers (EVs) not able to solve the problem. In this paper, we present"Veer,"which leverages the fact that two workflow versions can be very similar except for a few changes. The solution divides the workflow version pair into small parts, called windows, and verifies the equivalence within each window by using an existing EV as a black box. We develop solutions to efficiently generate windows and verify the equivalence within each window. Our thorough experiments on real workflows show that Veer is able to not only verify the equivalence of workflows that cannot be supported by existing EVs but also do the verification efficiently.
A Community Capacity Assessment Study in the Minnehaha Creek Watershed, Minnesota

ii The authors would like to acknowledge and thank the Minnehaha Creek Watershed District (MCWD) for their support and especially Leslie Yetka and Mallory Anderson for their invaluable assistance with study design, participant recruitment, and project outreach. We are particularly grateful to the 25 community stakeholders who shared with us their insights on their communities and their perspectives on community engagement in water resource protection and restoration. Its contents are solely the responsibility of the authors and do not necessarily represent the views of the MCWD. The cover photos were created by Amit Pradhananga and MCWD. The University of Minnesota is committed to the policy that all persons shall have equal access to its programs, facilities, and employment without regard to race, color, creed, religion, national origin, sex, age, marital status, disability, public assistance status, veteran status, or sexual orientation.
Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable Environments

Navigating complex and dynamic environments requires autonomous vehicles (AVs) to reason about both visible and occluded regions. This involves predicting the future motion of observed agents, inferring occluded ones, and modeling their interactions based on vectorized scene representations of the partially observable environment. However, prior work on occlusion inference and trajectory prediction have developed in isolation, with the former based on simplified rasterized methods and the latter assuming full environment observability. We introduce the Scene Informer, a unified approach for predicting both observed agent trajectories and inferring occlusions in a partially observable setting. It uses a transformer to aggregate various input modalities and facilitate selective queries on occlusions that might intersect with the AV's planned path. The framework estimates occupancy probabilities and likely trajectories for occlusions, as well as forecast motion for observed agents. We explore common observability assumptions in both domains and their performance impact. Our approach outperforms existing methods in both occupancy prediction and trajectory prediction in partially observable setting on the Waymo Open Motion Dataset.
From non-local to local Navier-Stokes equations

Inspired by some experimental (numerical) works on fractional diffusion PDEs, we develop a rigorous framework to prove that solutions to the fractional Navier-Stokes equations, which involve the fractional Laplacian operator $(-\Delta)^{\frac{\alpha}{2}}$ with $\alpha<2$, converge to a solution of the classical case, with $-\Delta$, when $\alpha$ goes to $2$. Precisely, in the setting of mild solutions, we prove uniform convergence in both the time and spatial variables and derive a precise convergence rate, revealing some phenomenological effects. Finally, our results are also generalized to the coupled setting of the Magnetic-hydrodynamic (MHD) system.
Traj-LO: In Defense of LiDAR-Only Odometry Using an Effective Continuous-Time Trajectory

LiDAR Odometry is an essential component in numerous robotic applications. However, current LiDAR-only methods have poor performance in aggressive situations. Unlike the mainstreamed approaches that focus on improving accuracy by the additional inertial sensors, this letter demonstrates that LiDAR is enough to achieve the similar capability through a continuous-time perspective. Firstly, the measurements of LiDAR are regarded as streaming points continuously captured at separate time. Secondly, the LiDAR movement is parameterized by a simple yet effective continuous-time trajectory. Therefore, our proposed method named Traj-LO can recover the spatial-temporal consistent movement of LiDAR by tightly coupling the geometric information from LiDAR points and kinematic constraints from trajectory smoothness. This framework is generalized for different kinds of LiDAR as well as multi-LiDAR systems. Extensive experiments on the public datasets verify the robustness and effectiveness of our proposed LiDAR-only approach, even in scenarios where the kinematic state exceeds the IMU's measuring range.
Psychological consequences of COVID-19 pandemic among persons residing at institutional quarantine centers in India

COVID-19 is global threat both on physical and mental health since its outbreak. On 24 March 2020, the Government of India ordered a nationwide lockdown with potential consequences on day-to-day life, mental and physical health and this study aims to explore the impact of COVID-19 on mental health institutionally quarantined subjects. Methods: A cross-sectional study was conducted between 9th July and 30th September 2020 among 305 subjects in 12 quarantine centers. Data was collected by physical interview after obtaining informed consent. Descriptive analysis and bivariate linear regression were performed to examine the association of variables. Results: 40.3% were found to not have depression, 59.7% were mild to extremely severely depressed. On the anxiety subscale, 37.7% did not have anxiety, while 62.3% had mild to extremely severe anxiety. On the stress subscale, only 22.6% reported in the normal range, while the rest 77.4% reported experiencing some degree of stress. Female participants showed statistically significant higher degrees of depression, anxiety and stress. Additionally, fear of infection, inadequate supply of essential items, financial uncertainty had significant association with stress, anxiety, depression and post-traumatic symptoms. Conclusion: Quarantine can be a necessary preventive measure during an outbreak of Pandemic situation like COVID-19, however quarantine is often associated with a negative psychological effect.
Supervised, semi-supervised, and unsupervised learning of the Domany-Kinzel model

The Domany Kinzel (DK) model encompasses several types of non-equilibrium phase transitions, depending on the selected parameters. We apply supervised, semi-supervised, and unsupervised learning methods to studying the phase transitions and critical behaviors of the (1 + 1)-dimensional DK model. The supervised and the semi-supervised learning methods permit the estimations of the critical points, the spatial and temporal correlation exponents, concerning labelled and unlabelled DK configurations, respectively. Furthermore, we also predict the critical points by employing principal component analysis (PCA) and autoencoder. The PCA and autoencoder can produce results in good agreement with simulated particle number density.
Rectal cancer (C20)

1Department of Radiotherapy I, Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland 2Department of Chemotherapy, Medical University of Łódź, Copernicus Memorial Hospital, Łódź, Poland 3Department of Colorectal Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland 4Department of Gastroenterology, Hepatology and Clinical Oncology, Medical Center for Postgraduate Education, Warsaw, Poland 5Department of Pathomorphology, Medical Centre for Postgraduate Education, Warsaw, Poland 6Department of Pathology and Laboratory Medicine, Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland 7Department of Radiology, Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland 8Department of Radiotherapy, Military Institute of Medicine, Warsaw, Poland 9Department of Radiotherapy, Regional Oncology Centre, Czestochowa, Poland 10Department of Lung Cancer and Chest Tumours, Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland
Willingness-to-pay value of cultural heritage and its management for sustainable conservation of George Town, world heritage site / Noor Fazamimah Mohd Ariffin

This research explores the issue of the local management system governing the heritage conservation in Malaysia which has not clearly defined the value of the cultural heritage in order to justify any benefits of preserving the cultural heritage as a tourism product for the sustainable heritage site conservation. There are conflicts between stakeholders relating to the benefits of the UNESCO World Heritage Site (WHS) designation. Stakeholders such as the local community are often neglected or ignored and have derived very few benefits from tourism development of WHS in Malaysia. Thus, there is a dire need to evaluate the value of a cultural heritage in formulating heritage development plans making it physically, economically and socially acceptable as well as equally beneficial amongst the local stakeholders in order to preserve their cultural heritage sites, thus contributing towards the overall sustainable development of the WHS in Malaysia. The research adopts various approaches of study and triangulates the findings. The case study, Contingent Valuation questionnaire survey and interviews are the main strategies used for data collection. The single case study approach was carried out in search of empirical data on one of the historic cities in Malaysia i.e. George Town, Penang which has been recently inscribed as a UNESCO WHS. Three separate sets of questionnaires were designed and administered among the three key stakeholders in the field: local community, tourists and management personnel in the tourism and heritage site management. The Contingent Valuation is a direct Stated Preferences technique where respondents were asked their willingness-to-pay (WTP) value for the benefits received. The WTP value is one of the best techniques for estimating the total economic value of the cultural heritage resources that were not traded in the market. The public preferences, as measured by their WTP for the cultural heritage iv conservation, should be given due consideration in the decision-making process in order to promote the sustainability of a heritage site. This research has found that the George Town households were willing to pay RM57.46 per year and the tourist respondents were willing to pay RM42.54 per visit in the form of the conservation zone entry ticket or heritage building admission fee as a contribution for the George Town Heritage Conservation Fund. Both categories of respondents have shown their strong support for the George Town WHS conservation with the WTP value of the George Town WHS conservation. The managers also have shown their positive support for the proposed management of the WTP value of the cultural heritage for the sustainable George Town WHS conservation. Finally, this research has established a framework for the management of the WTP value of the cultural heritage for the sustainable George Town WHS conservation in Malaysia.
Tracer Test Data Assimilation for the Assessment of Local Hydraulic Properties in Heterogeneous Aquifers

The hydraulic conductivity distribution in a natural porous media is characterized by a great heterogeneity that makes its spatial assessment problematic and expensive. At the same time, a detailed knowledge of the hydraulic properties, as porosity, storativity, transmissivity and hydraulic conductivity K, is fundamental for the prediction of groundwater flow and solute transport in natural formations. Among the hydraulic properties, being the subsurface transport phenomena in natural formations mainly controlled by the Darcy's law, the proper definition of the K spatial distribution at different scales plays a fundamental role to evaluate the evolution of a contaminant plume, to define the well-catchment areas or to monitor a landfill site. To estimate aquifer hydraulic properties, inverse models have long been studied and, beyond the traditional hydraulic conductivity and head measurements, tracer test analyses have been widely adopted in the past and their use have increased in the recent years thanks to a great improvement of geophysical techniques. Among others, the Electrical Resistivity Tomography (ERT) allows to monitor a tracer test injection, providing time-lapse informations about the plume evolution with limited cost. Assuming that time-lapse spatially distributed data deduced from a tracer test are available, the present work investigates different approaches aimed to the estimation of the local K distribution. At this purpose, Kalman filter based data assimilation techniques are coupled with the Lagrangian transport model and applied in different synthetic contexts
School of Citizenship and Public Affairs 3-1-2010 Alternative Technical Efficiency Measures : Skew , Bias , and Scale

In the fixed-effects stochastic frontier model an efficiency measure relative to the best firm in the sample is universally employed. This paper considers a new measure relative to the worst firm in the sample. We find that estimates of this measure have smaller bias than those of the traditional measure when the sample consists of many firms near the efficient frontier. Moreover, a two-sided measure relative to both the best and the worst firms is proposed. Simulations suggest that the new measures may be preferred depending on the skewness of the inefficiency distribution and the scale of efficiency differences. Email: qfeng@ntu.edu. sg, Tel: +65 6592 1543. Division of Economics, School of Humanities and Social Sciences, HSS-04-48, 14 Nanyang Drive, Singapore 637332 †Corresponding Author. Email: whorrace@maxwell.syr. edu, Tel: 315-443-9061. Fax: 315-4431081. Center for Policy Research, 426 Eggers Hall, Syracuse, NY 13244-1020
Flow Selection Techniques

The Intermediate Flow Selection Process is the process of selecting a subset of Flows from all observed Flows. The Intermediate Flow Selection Process may be located at an IP Flow Information Export (IPFIX) Exporter or Collector, or within an IPFIX Mediator. It reduces the effort of post-processing Flow data and transferring Flow Records. This document describes motivations for using the Intermediate Flow Selection process and presents Intermediate Flow Selection techniques. It provides an information model for configuring Intermediate Flow Selection Process techniques and discusses what information about an Intermediate Flow Selection Process should be exported.
Diversity ranking of weed-communities on crop fields cultivated by variants of soil conservation tillage.

The objectives of this paper are (1) to describe weed communities of variants of tillage examined by statistics of diversity and (2) to answer that they can be ordered by diversity or can not. It can be stated that one diversity measure or one diversity function is not enough to describe communities. For actualities, more methods should be used in parallel. To understand diversity properly, scale-dependent description of diversity is necessary, which provides us with new information that are not revealed by traditional methods. Diversity ranking of variants of tillage based on data collected spring time can be executed, since diversity profiles do not cross. The ranking is as follows: 1. direct drilling 2. shallow ploughed field 3. traditional tillage 4. tillage by disk-ripper. In summer time, diversity profile for direct drilling, however, crosses the profile for shallow tillage. Therefore, they can not be ranked, which means that they can not be ranked by diversity. Despite of not being ranked, that situation can be interpreted from ecological aspect.
Recent developments in acacia planting: proceedings of an international workshop held in Hanoi, Vietnam, 27-30 October 1997

The 1300 species of the genus Acacia extend around the globe, from Australia through Asia to Africa and the Americas. These nitrogen-fixing trees and shrubs grow in a range of environments and fill an important niche in natural ecosystems. They have also been planted as exotics in over 70 countries for land rehabilitation, shade and shelter, and to produce a range of wood and non-wood products including firewood, charcoal, building poles, tannins and fodder. In recent years extensive plantations have been established in Asia to provide wood pulp for paper and textile manufacture. This book contains 52 papers and 7 short communications on recent developments in planting tropical and subtropical acacias presented at a workshop held in Hanoi, Vietnam, 27-30 October 1997. It brings together the research results and experiences of scientists involved in developing new technologies for acacia planting in Asia and Australia and forest managers facing practical problems growing acacias in the region. Many papers refer to well-known species, such as Acacia auriculiformis, A. mangium and A. mearnsii, but others report the results of testing lesser-known species in a range of environments. The 57 participants at the workshop reviewed the major issues arising from the meeting, identified gaps in knowledge and made recommendations for future research. The key areas were: genetic resources and tree improvement, silviculture and site management, pests and diseases, physiology (including soil symbionts), social, economic and utilisation issues, and mechanisms to foster future collaboration.
A Model Checking Procedure for Interval Temporal Logics based on Track Representatives

Model checking is commonly recognized as one of the most effective tool in system verification. While it has been systematically investigated in the context of classical, point-based temporal logics, it is still largely unexplored in the interval logic setting. Recently, a non-elementary model checking algorithm for Halpern and Shoham's modal logic of time intervals HS, interpreted over finite Kripke structures, has been proposed, together with a proof of the EXPSPACE-hardness of the problem. In this paper, we devise an EXPSPACE model checking procedure for two meaningful HS fragments. It exploits a suitable contraction technique, that allows one to replace long enough tracks of a Kripke structure by equivalent shorter ones.
The laws of the web

From the Publisher: Despite its haphazard growth, the Web hides powerful underlying regularities--from the organization of its links to the patterns found in its use by millions of users. Many of these regularities have been predicted on the basis of theoretical models based on a field of physics--statistical mechanics--that few would have thought applicable to the social domain. In this book Bernardo Huberman explains in accessible language the laws of the Web. One of the foremost researchers in the field, Huberman has established, for example, that the surfing patterns of individuals are describable by a precise law. Such findings can lead to more efficient Web design and use. They also shed light on social mechanisms whose significance goes beyond the Web. In this sense, the Web is a gigantic informational ecosystem that can be used to quantify and test explanations of human behavior and social interaction.