Miracle-dz/UniFAR-FTUs huggingface dataset:
"COVID-19 was a FIFA conspiracy #curropt": An Investigation into the Viral Spread of COVID-19 Misinformation

The outbreak of the infectious and fatal disease COVID-19 has revealed that pandemics assail public health in two waves: ﬁrst, from the contagion itself and second, from plagues of suspicion and stigma. Now, we have in our hands and on our phones an outbreak of moral controversy. Modern dependency on social media has not only facilitated access to the locations of vaccine clinics and testing sites but also—and more frequently—to the convoluted explanations of how “COVID-19 was a FIFA conspiracy” [1]. The MIT Media Lab ﬁnds that false news “diffuses signiﬁcantly farther, faster, deeper, and more broadly than truth, in all categories of information, and by an order of magnitude” [2]. The question is, how does the spread of misinformation interact with a physical epidemic disease? In this paper, we estimate the extent to which misinformation has inﬂuenced the course of the COVID-19 pandemic using natural language processing models and provide a strategy to combat social media posts that are likely to cause widespread harm. the utmost importance to limit the reach of false authoritative content regarding the COVID-19 pandemic, especially when their main victims are regular civilians. Our research has culminated in a misinformation detection pipeline that is comprised of three components: a claim detector, a misinformation classiﬁer, and a virality measurement. Through this pipeline, we aim to derive further insights into the behavior of these types of information spread and their impact on society.
SENSOR NETWORKS FOR MONITORING WATER SUPPLY AND SEWER SYSTEMS: LESSONS FROM BOSTON

In recent years, research in wireless sensor networks (WSN) has been undergoing a quiet revolution, promising to have significant impact on a broad range of applications relating to environmental monitoring, structural health monitoring, security and water safety. The convergence of the Internet, telecommunications, and novel information technologies with techniques for miniaturisation now provides vast opportunities for the development and application of low-cost monitoring solutions which could drastically increase the spatial and temporal resolution of environmental data. The paper describes the development of a prototype monitoring system which bridges advances in wireless sensor networks with advances in hydraulic and water quality modeling. The prototype monitoring system was deployed at Boston Water and Sewer Commission (BWSC) in December 2004, and it has been successfully collecting and charting near-real time hydraulic and water quality data as well as data from combined sewer outflows (CSO). The remote monitoring system has unique functionalities in terms of sampling rates (up to 1000 S/s), time synchronization (up to 1 ms) and in-network processing. These features create novel opportunities for wirelessly collecting data for applications such as hydraulic pressure transients, remote acoustic leak detection together with low-duty cycle applications such as monitoring water quality parameters and water levels in CSOs. The trial with BWSC has been tremendously useful to prototype hardware and software tools, and to identify deployment and operational challenges in using sensor networks for monitoring and management of large scale water supply systems.
Improving component reuse in software development

Forsell, Marko Improving Component Reuse in Software Development / Marko Forsell Jyväskylä: University of Jyväskylä, 2002, 167 pages (Jyväskylä Studies in Computing ISSN 1456-5390;16) ISBN 951-39-1217-5 Finnish summary Diss. This study concerns reuse in the software development process. The focus is in the reuse of components when creating new software. The aim is to improve current software processes to adapt them to the purposes of reuse. The specific research questions are: 1) What are the specific limitations for reuse in the current component-based software development methods? 2) How should reusable components be created and used in software development? 3) How should the components that are created be documented in order to make them reusable in other development projects? The study follows the reflective systems development approach. First, current component-based software development methods are evaluated and examined in the light of reuse process. Also, the software process currently used in organizations is examined. This improves our understanding of the current situation. Here it is claimed that successful and systematic reuse-orientation requires use of the domain analysis method and a systematic way of documenting components. Next, some improvements are designed to address the problems identified. Here the hierarchical domain analysis method and a model to document reusable components are presented. Finally, presented solutions are tried out in practice.
A Phase I Study Investigating AZD8186, a Potent and Selective Inhibitor of PI3Kβ/δ, in Patients with Advanced Solid Tumors

Abstract Purpose: To characterize safety and tolerability of the selective PI3Kβ inhibitor AZD8186, identify a recommended phase II dose (RP2D), and assess preliminary efficacy in combination with abiraterone acetate or vistusertib. Patients and Methods: This phase I open-label study included patients with advanced solid tumors, particularly prostate cancer, triple-negative breast cancer, and squamous non–small cell lung cancer. The study comprised four arms: (i) AZD8186 monotherapy dose finding; (ii) monotherapy dose expansion; (iii) AZD8186/abiraterone acetate (with prednisone); and (iv) AZD8186/vistusertib. The primary endpoints were safety, tolerability, and identification of the RP2D of AZD8186 monotherapy and in combination. Secondary endpoints included pharmacokinetics (PK), pharmacodynamics, and tumor and prostate-specific antigen (PSA) responses. Results: In total, 161 patients were enrolled. AZD8186 was well tolerated across all study arms, the most common adverse events being gastrointestinal symptoms. In the monotherapy dose-finding arm, four patients experienced dose-limiting toxicities (mainly rash). AZD8186 doses of 60-mg twice daily [BID; 5 days on, 2 days off (5:2)] and 120-mg BID (continuous and 5:2 dosing) were taken into subsequent arms. The PKs of AZD8186 were dose proportional, without interactions with abiraterone acetate or vistusertib, and target inhibition was observed in plasma and tumor tissue. Monotherapy and combination therapy showed preliminary evidence of limited antitumor activity by imaging and, in prostate cancer, PSA reduction. Conclusions: AZD8186 monotherapy had an acceptable safety and tolerability profile, and combination with abiraterone acetate/prednisone or vistusertib was also tolerated. There was preliminary evidence of antitumor activity, meriting further exploration of AZD8186 in subsequent studies in PI3Kβ pathway–dependent cancers.
ZNF384 fusion oncoproteins drive lineage aberrancy in acute leukemia.

ZNF384-rearranged fusion oncoproteins (FO) define a subset of lineage ambiguous leukemias, but their mechanistic role in leukemogenesis and lineage ambiguity is poorly understood. Using viral expression in mouse and human hematopoietic stem and progenitor cells (HSPCs) and a Ep300::Znf384 knockin mouse model, we show that ZNF384 FO promote hematopoietic expansion, myeloid lineage skewing, and self-renewal. In mouse HSPCs, concomitant lesions, such as NRASG12D, were required for fully penetrant leukemia, whereas in human HSPCs expression of ZNF384 FO drove B/myeloid leukemia, with sensitivity of a ZNF384-rearranged xenograft to FLT3 inhibition in vivo. Mechanistically, ZNF384 FO occupy a subset of predominantly intragenic/enhancer regions with increased histone 3 lysine acetylation and deregulate expression of hematopoietic stem cell transcription factors. These data define a paradigm for FO-driven lineage ambiguous leukemia, in which expression in HSPCs results in deregulation of lineage-specific genes and hematopoietic skewing, progressing to full leukemia in the context of proliferative stress.
Anti-tumor Activity of a Mitochondrial Targeted HSP90 Inhibitor in Gliomas.

PURPOSE To investigate the anti-tumor activity of a mitochondrial-localized HSP90 inhibitor, Gamitrinib, in multiple glioma models, and to elucidate the anti-tumor mechanisms of Gamitrinib in gliomas. EXPERIMENTAL DESIGN A broad panel of primary and temozolomide (TMZ)-resistant human glioma cell lines were screened by cell viability assays, flow cytometry and crystal violet assays to investigate the therapeutic efficacy of Gamitrinib. Seahorse assays were used to measure the mitochondrial respiration of glioma cells. Integrated analyses of RNA sequencing (RNAseq) and reverse phase protein array (RPPA) data were performed to reveal the potential anti-tumor mechanisms of Gamitrinib. Neurospheres, patient-derived organoids (PDOs), cell line-derived xenografts (CDX) and patient-derived xenografts (PDX) models were generated to further evaluate the therapeutic efficacy of Gamitrinib. RESULTS Gamitrinib inhibited cell proliferation and induced cell apoptosis and death in 17 primary glioma cells, 6 TMZ-resistant glioma cells, 4 neurospheres and 3 PDOs. Importantly, Gamitrinib significantly delayed the tumor growth and improved survival of mice in both CDX and PDX models in which tumors were either subcutaneously or intracranially implanted. Integrated computational analyses of RNAseq and RPPA data revealed that Gamitrinib exhibited its anti-tumor activity via (1) suppressing mitochondrial biogenesis, OXPHOS and cell cycle progression and (2) activating the energy-sensing AMP-activated kinase, DNA damage and stress response. CONCLUSIONS These preclinical findings established the therapeutic role of Gamitrinib in gliomas and revealed the inhibition of mitochondrial biogenesis and tumor bioenergetics as the primary anti-tumor mechanisms in gliomas.
Accessibility of mathematical resources: the technology gap

The amended Disability Discrimination Act (DDA) places a requirement on higher education establishments to make reasonable adjustments to ensure that disabled students are not placed at a substantial disadvantage. The legislation applies to all teaching and requires that universities should anticipate changes required and be proactive in making them. Disabled students may be in receipt of the Disabled Students’ Allowance (DSA) perhaps allowing the purchase of assistive technologies or paying for limited human assistance.
Hitchhiker: A Quadrotor Aggressively Perching on a Moving Inclined Surface Using Compliant Suction Cup Gripper

Perching on {the surface} of moving objects, like vehicles, could extend the flight {time} and range of quadrotors. Suction cups are usually adopted for {surface attachment} due to their durability and large adhesive force. To seal on {a surfaces}, suction cups {must} be aligned with {the surface} and {possess proper relative tangential velocity}. {However, quadrotors' attitude and relative velocity errors would become significant when the object surface is moving and inclined. To address this problem, we proposed a real-time trajectory planning algorithm. The time-optimal aggressive trajectory is efficiently generated through multimodal search in a dynamic time-domain. The velocity errors relative to the moving surface are alleviated. } To further adapt to the residual errors, we design a compliant gripper using self-sealing cups. Multiple cups in different directions are integrated into a wheel-like mechanism to increase the tolerance to attitude errors. The wheel mechanism also eliminates the requirement of matching the attitude and tangential velocity. {Extensive tests are conducted to perch on static and moving surfaces at various inclinations. } Results demonstrate that our proposed system enables a quadrotor to reliably perch on moving inclined surfaces (up to $1.07m/s$ and $90^\circ$) with a success rate of $70\%$ or higher. {The efficacy of the trajectory planner is also validated. Our gripper has larger adaptability to attitude errors and tangential velocities than conventional suction cup grippers. } The success rate increases by 45\% in dynamic perches.
Autoregressive Image Generation using Residual Quantization

For autoregressive (AR) modeling of high-resolution images, vector quantization (VQ) represents an image as a sequence of discrete codes. A short sequence length is important for an AR model to reduce its computational costs to consider long-range interactions of codes. However, we postulate that previous VQ cannot shorten the code sequence and generate high-fidelity images together in terms of the rate-distortion trade-off. In this study, we propose the two-stage framework, which consists of Residual-Quantized VAE (RQ-VAE) and RQ-Transformer, to effectively generate high-resolution images. Given a fixed codebook size, RQ-VAE can precisely approximate a feature map of an image and represent the image as a stacked map of discrete codes. Then, RQ-Transformer learns to predict the quantized feature vector at the next position by predicting the next stack of codes. Thanks to the precise approximation of RQ-VAE, we can represent a $256\times 256$ image as $8\times 8$ resolution of the feature map, and RQ-Transformer can efficiently reduce the computational costs. Consequently, our framework out-performs the existing AR models on various benchmarks of unconditional and conditional image generation. Our approach also has a significantly faster sampling speed than previous AR models to generate high-quality images.
The Sherali-Adams Hierarchy for Promise CSPs through Tensors

We study the Sherali-Adams linear programming hierarchy in the context of promise constraint satisfaction problems (PCSPs). We characterise when a level of the hierarchy accepts an instance in terms of a homomorphism problem for an appropriate multilinear structure obtained through a tensor power of the constraint language. The geometry of this structure, which consists in a space of tensors satisfying certain symmetries, allows then to establish non-solvability of the approximate graph colouring problem via constantly many levels of Sherali-Adams. Besides this primary application, our tensorisation construction introduces a new tool to the study of hierarchies of algorithmic relaxations for computational problems within (and, possibly, beyond) the context of constraint satisfaction. In particular, we see it as a key step towards the algebraic characterisation of the power of Sherali-Adams for PCSPs.
A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

Recent developments in video analysis of sports and computer vision techniques have achieved significant improvements to enable a variety of critical operations. To provide enhanced information, such as detailed complex analysis in sports like soccer, basketball, cricket, badminton, etc., studies have focused mainly on computer vision techniques employed to carry out different tasks. This paper presents a comprehensive review of sports video analysis for various applications: high-level analysis such as detection and classification of players, tracking player or ball in sports and predicting the trajectories of player or ball, recognizing the team‟s strategies, classifying various events in sports. The paper further discusses published works in a variety of application-specific tasks related to sports and the present researcher‟s views regarding them. Since there is a wide research scope in sports for deploying computer vision techniques in various sports, some of the publicly available datasets related to a particular sport have been provided. This work reviews a detailed discussion on some of the artificial intelligence (AI) applications in sports vision, GPU-based work stations, and embedded platforms. Finally, this review identifies the research directions, probable challenges, and future trends in the area of visual recognition in sports.
Low-order preconditioning for the high-order finite element de Rham complex

In this paper we present a unified framework for constructing spectrally equivalent low-order-refined discretizations for the high-order finite element de Rham complex. This theory covers diffusion problems in $H^1$, $H({\rm curl})$, and $H({\rm div})$, and is based on combining a low-order discretization posed on a refined mesh with a high-order basis for N\'ed\'elec and Raviart-Thomas elements that makes use of the concept of polynomial histopolation (polynomial fitting using prescribed mean values over certain regions). This spectral equivalence, coupled with algebraic multigrid methods constructed using the low-order discretization, results in highly scalable matrix-free preconditioners for high-order finite element problems in the full de Rham complex. Additionally, a new lowest-order (piecewise constant) preconditioner is developed for high-order interior penalty discontinuous Galerkin (DG) discretizations, for which spectral equivalence results and convergence proofs for algebraic multigrid methods are provided. In all cases, the spectral equivalence results are independent of polynomial degree and mesh size; for DG methods, they are also independent of the penalty parameter. These new solvers are flexible and easy to use; any"black-box"preconditioner for low-order problems can be used to create an effective and efficient preconditioner for the corresponding high-order problem. A number of numerical experiments are presented, based on an implmentation in the finite element library MFEM. The theoretical properties of these preconditioners are corroborated, and the flexibility and scalability of the method are demonstrated on a range of challenging three-dimensional problems.
Postcertificates for Revocation Transparency

The modern Internet is highly dependent on trust communicated via certificates. However, in some cases, certificates become untrusted, and it is necessary to revoke them. In practice, the problem of secure revocation is still open. Furthermore, the existing procedures do not leave a transparent and immutable revocation history. We propose and evaluate a new revocation transparency protocol that introduces postcertificates and utilizes the existing Certificate Transparency (CT) logs. The protocol is practical, has a low deployment cost, provides an immutable history of revocations, enables delegation, and helps to detect revocation-related misbehavior by certificate authorities (CAs). With this protocol, a holder of a postcertificate can bypass the issuing CA and autonomously initiate the revocation process via submission of the postcertificate to a CT log. The CAs are required to monitor CT logs and proceed with the revocation upon detection of a postcertificate. Revocation status delivery is performed independently and with an arbitrary status protocol. Postcertificates can increase the accountability of the CAs and empower the certificate owners by giving them additional control over the status of the certificates. We evaluate the protocol, measure log and monitor performance, and conclude that it is possible to provide revocation transparency using existing CT logs.
Microfluidic Amperometric Detection Sensor with Integrated Ag/AgCl Reference Electrode

In this paper, we presented a novel method for fabricating the integrated electrochemical sensor based on a microfluidic device. The device included: printed circuit board (PCB) substrate with vertical embedded electrodes; polymethyl methacrylate (PMMA) with micro structures; PMMA cover with amperometric detection sensor (ADS). The ADS employed three-electrode sensor system which was composed by two Au electrodes and an Ag/AgCl reference electrode. The polyvinyl chloride (PVC) membrane was used as ion-exchange medium of reference electrode and installed between Au electrodes. Then, the potential changes and the standardization oxidation-reduction experiments were executed to characterize the integrated reference electrode performance. Finally, the ADS system was tested by cyclic voltammetry (CV).
Robust Counterexample-guided Optimization for Planning from Differentiable Temporal Logic

Signal temporal logic (STL) provides a powerful, flexible framework for specifying complex autonomy tasks; however, existing methods for planning based on STL specifications have difficulty scaling to long-horizon tasks and are not robust to external disturbances. In this paper, we present an algorithm for finding robust plans that satisfy STL specifications. Our method alternates between local optimization and local falsification, using automatically differentiable temporal logic to iteratively optimize its plan in response to counterexamples found during the falsification process. We benchmark our counterexample-guided planning method against state-of-the-art planning methods on two long-horizon satellite rendezvous missions, showing that our method finds high-quality plans that satisfy STL specifications despite adversarial disturbances. We find that our method consistently finds plans that are robust to adversarial disturbances and requires less than half the time of competing methods. We provide an implementation of our planner at https://github.com/MIT-REALM/architect.
Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Paths

Local explanations of learning-to-rank (LTR) models are thought to extract the most important features that contribute to the ranking predicted by the LTR model for a single data point. Evaluating the accuracy of such explanations is challenging since the ground truth feature importance scores are not available for most modern LTR models. In this work, we propose a systematic evaluation technique for explanations of LTR models. Instead of using black-box models, such as neural networks, we propose to focus on tree-based LTR models, from which we can extract the ground truth feature importance scores using decision paths. Once extracted, we can directly compare the ground truth feature importance scores to the feature importance scores generated with explanation techniques. We compare two recently proposed explanation techniques for LTR models when using decision trees and gradient boosting models on the MQ2008 dataset. We show that the explanation accuracy in these techniques can largely vary depending on the explained model and even which data point is explained.
Comprehension of Subtitles from Re-Translating Simultaneous Speech Translation

In simultaneous speech translation, one can vary the size of the output window, system latency and sometimes the allowed level of rewriting. The effect of these properties on readability and comprehensibility has not been tested with modern neural translation systems. In this work, we propose an evaluation method and investigate the effects on comprehension and user preferences. It is a pilot study with 14 users on 2 hours of German documentaries or speeches with online translations into Czech. We collect continuous feedback and answers on factual questions. Our results show that the subtitling layout or flicker have a little effect on comprehension, in contrast to machine translation itself and individual competence. Other results show that users with a limited knowledge of the source language have different preferences to stability and latency than the users with zero knowledge. The results are statistically insignificant, however, we show that our method works and can be reproduced in larger volume.