Miracle-dz/UniFAR-FTUs huggingface dataset:
Building an Enhanced Autoregressive Document Retriever Leveraging Supervised Contrastive Learning

The goal of an information retrieval system is to retrieve documents that are most relevant to a given user query from a huge collection of documents, which usually requires time-consuming multiple comparisons between the query and candidate documents so as to find the most relevant ones. Recently, a novel retrieval modeling approach, dubbed Differentiable Search Index (DSI), has been proposed. DSI dramatically simplifies the whole retrieval process by encoding all information about the document collection into the parameter space of a single Transformer model, on top of which DSI can in turn generate the relevant document identities (IDs) in an autoregressive manner in response to a user query. Although DSI addresses the shortcomings of traditional retrieval systems, previous studies have pointed out that DSI might fail to retrieve relevant documents because DSI uses the document IDs as the pivotal mechanism to establish the relationship between queries and documents, whereas not every document in the document collection has its corresponding relevant and irrelevant queries for the training purpose. In view of this, we put forward to leveraging supervised contrastive learning to better render the relationship between queries and documents in the latent semantic space. Furthermore, an approximate nearest neighbor search strategy is employed at retrieval time to further assist the Transformer model in generating document IDs relevant to a posed query more efficiently. A series of experiments conducted on the Nature Question benchmark dataset confirm the effectiveness and practical feasibility of our approach in relation to some strong baseline systems.
Stance Trees: A Novel Approach for Assessing Politically Polarized Issues in Twitter

Social and political polarization, which sometimes is the result of misinformation, is a common obstacle that can be harmful at the moment of communicating government policies. Intelligent tools that aid critical thinking in the light of different opinions and standpoints available in social media can help ameliorate this obstacle. This paper presents preliminary research work toward developing such tools by proposing a methodology for building stance trees based on tweets collected from social media. Stance trees are hierarchical structures where nodes represent arguments pro, anti, or uncertain about a target issue and edges stand for attack relations between those arguments. The proposed methodology includes retrieving tweets relevant to the target issue, manually labeling a sample set of the collected tweets, developing and applying a model for stance detection, and finally building a stance tree. We illustrate the expected results through a case study on the politically polarized “COVID-19 vaccine” issue. Our preliminary results demonstrate the feasibility of the proposal and highlight the utility of stance trees as a tool for aiding critical thinking.
Seeing is Feeling: A Novel Haptic Display for Wearer-Observer Mutual Haptic Understanding

We propose a new haptic display that enables mutual understanding of haptic sensation between the wearer and an observer. In addition to presenting haptic sensations by inducing skin deformation, we have achieved creating a mutual understanding of the sensations with the observer by making the haptic stimulus evident. People have the ability to predict the sensations of others by observing their sensory states. The system is composed of a part that provides haptic stimulus while creating visible skin deformation, and a mechanical structure that visually exaggerates the deformation. The proposed system realizes richer interactions by extending the entertainment experiences of the observers during live content, increase understanding of internal states through biofeedback, and be used in remote haptic communication.
Efficient Crash Consistency for NVMe over PCIe and RDMA

This article presents crash-consistent Non-Volatile Memory Express (ccNVMe), a novel extension of the NVMe that defines how host software communicates with the non-volatile memory (e.g., solid-state drive) across a PCI Express bus and RDMA-capable networks with both crash consistency and performance efficiency. Existing storage systems pay a huge tax on crash consistency, and thus cannot fully exploit the multi-queue parallelism and low latency of the NVMe and RDMA interfaces. ccNVMe alleviates this major bottleneck by coupling the crash consistency to the data dissemination. This new idea allows the storage system to achieve crash consistency by taking the free rides of the data dissemination mechanism of NVMe, using only two lightweight memory-mapped I/Os (MMIOs), unlike traditional systems that use complex update protocol and synchronized block I/Os. ccNVMe introduces a series of techniques including transaction-aware MMIO/doorbell and I/O command coalescing to reduce the PCIe traffic as well as to provide atomicity. We present how to build a high-performance and crash-consistent file system named MQFS atop ccNVMe. We experimentally show that MQFS increases the IOPS of RocksDB by 36% and 28% compared to a state-of-the-art file system and Ext4 without journaling, respectively.
Empirical framework to determine maturity of digital transformation of a service to citizens through enhancements on existing assessment methods – Case Study India

Digital Government has now moved into its second phase, in which digital transformation of major proportions has begun to occur. Government will be both a driver and a facilitator of this transformation that requires a multi-disciplinary perspective for a better understanding of the impacts of the digital transformation of government. The focus has now shifted from a single national e-governance initiative to innumerable mission mode projects. Each of these projects aim to transform the delivery of an identified high priority citizen service from its current manual format into an e-delivery one. In such an environment there is need to drill down and accurately measure the maturity of each of the digital services being provided to citizens, in addition to the standard practice of rating the overall digital government performance of a country. This Paper presents a framework that has the proven capacity of determining the level of maturity of the digital transformation of a digital service to citizens. The innovative solution presented here is in alignment with one of themes of this track ‘to include enhancements on existing assessment methods currently used by nations or international organizations for measuring, assessing, and monitoring various aspects of digital governance and transformation development. ’ The Paper goes further to validate that ingenious framework by generating conclusive evidence, through robust empirical analysis, using a case study of digital transformation of a service in a State in India.
E.S.P.: Extra-Sensory Puck in Air Hockey using the Projection-Based Illusion

E.S. P. (Extra-Sensory Puck) provides a new experience by introducing optical illusions to air hockey. The perception of a solid puck randomly hit by a player is altered to show various physics-defying appearances and motions to the player’s naked eye. Such altered perceptions are based on our high-speed projector-camera system generating stimulation patterns onto the moving puck. This paper presents two demonstrations. The first is the invisible puck, where the hit puck is camouflaged to disappear on the table. The second is the altered motion, where the direction and speed are altered.
Integrating Robot Manufacturer Perspectives into Legible Factory Robot Light Communications

In a world with increasing numbers of robots operating in everyday human spaces, the employees at this robotics company are pioneers, with intelligent point-to-point path planning and autonomous transport operations in 150+ factory and warehouse locations in North America. At the time of research, this robotics company consisted of 250 employees. Unlike other industry models, their robots are designed to operate with people in mixed human-machine spaces, yet no HRI style evaluations had previously been run with their robots. As early observers of how factory workers and transport robot interact, across varied job roles ranging from technology design to customer relations, this work sought to leverage employee knowledge and experiences to identify opportunities for improving the communication capabilities of the robots, resulting in the addition of several robot state communications to their initial software set leveraging both employee- and social robotics literature- sourced ideas for communicating with lights. To achieve this a social robotics researcher spent a summer onsite at the robotics company, getting to know their software stack and culture. Her research activities included: (1) a company-wide survey relative to the robot’s light, sound, and motion communications was sent out and analyzed, (2) the development of three new light sets (car-like, sweeping, heartbeat) and five overall states (blocked, at goal, turning, idle), and (3) a user study evaluating the developed light sets relative to the current robot default light patterns, all significantly improving the overall legibility of the targeted robot state communications: at goal, blocked, turning, and idle. Our initial findings advance knowledge in which style of light patterns is best for different communication states, showing that eye-catching lights are best for high urgency states, such as blocked, and subtle lights are best for low urgency states, such as idle. Finally, the latest software release for this robot has deployed a subset of these light patterns to all of their currently operating client sites, i.e., anyone who updates their robots to the latest release will benefit from these research results. This deployment sets the ground for future researchers exploring how end-users at different sites have responded to the new, more communicative light patterns.
A rotating vane electrometer of high sensitivity

An electrometer has been developed which primarily is intended for measurement of electric fields associated with magnetically confined laboratory plasmas. The main features of the design are that sensitivity and time resolution have been significantly increased beyond the limits existing in present instruments of this type so that fields of the order of a few volts per centimetre can be detected, provided that fluctuations in the field have a time constant greater than a few milliseconds.
EGOV strategy formulation taking into account international rankings: Application of a method in an African Country

Abstract: The formulation of the EGOV Strategy of São Tomé e Príncipe has been done using a method to formulate EGOV strategies taking into account international rankings. During the strategy formulation process, government agencies and designated focal points applied the five stages of the method: 1 – Diagnosis and Context Analysis; 2 – Definition of Vision and Principles; 3 – Choice of Thematic Areas and Initiatives; 4 – Identification of Structuring Pillars; and 5 – Definition of Implementation and Evaluation Plans. The method was developed to be flexible and adaptable to the country's context, including selecting international rankings by the team involved. In that case, it was selected the World Bank Worldwide Governance Index (WB/WGI), the United Nations eGovernment Development Index (UN/EGDI), the World Bank Ease of Doing Business Report (WB/DB), and the United Nations World Happiness Report (UN/WHR). The method application resulted in an official document approved by the Council of Ministers for 2020 to 2024.
The Counterintuitive Universe

The major advances in physics have been through counterintuitive breakthroughs– ideas that seemed to go against prevailing convictions. In the twentieth century the Special and General Theory of Relativity and Quantum Mechanics have provided very good examples of this process. However, twentieth century physics has led to an impasse, one of the most important unsolved problems being the uniﬁcation of gravitation with other interactions. This has led to another sacred tenet of physics, viz., spacetime as a smooth manifold, being ques-tioned in latest approaches, be it Quantum Super Strings or other Quantum Gravity and similar theories. In particular spacetime described by an underpinning of Planck scale oscillators is investigated.
ADACOP: A Big Data Platform for Open Government Data

In modern states, transparency in the public sector has become a critical issue in developing a democratic process. Emerging technologies such as Big Data and Open Government Data have become essential for assuring and improving transparency at all public sector dimensions. Particularly, Big Data has a significant impact potential in fields where data with considerable volume, velocity, and variety properties are present, such as monitoring public procurement. In this work, we present an Open Government Big Data tool for monitoring and exploiting the potential of data from Open Government Data portals. The solution automatically generates descriptive statistics about Open Government Data and allows the verification of Open Government Data quality by contrasting different versions of the data across time. To validate the solution, we develop a case focused on monitoring public procurement data, due to its importance in assuring government transparency. The platform provides a set of analytical tools to resolve specific requirements from public procurement fiscal evaluators.
Anonymizing and obfuscating PDF content while preserving document structure

The portable document format (PDF) is both versatile and complex, with a specification exceeding well over a thousand pages. For independent developers writing software that reads, displays, or transforms PDFs, it is difficult to comprehensively account for all of the potential variations that might exist in the wild. Compounding this problem are the usage agreements that often accompany purchased and proprietary PDFs, preventing end users from uploading a troublesome document as part of a bug report and limiting the set of test cases that can be made public for open source development. In this paper, pdf-mangler is presented as a solution to this problem. The goal of pdf-mangler is to remove information in the form of text, images, and vector graphics while retaining as much of the document structure and general visual appearance as possible. The intention is for pdf-mangler to be deployed as part of an automated bug reporting tool for PDF software.
OVERPAINT: Automatic Multi-Layer Stencil Generation without Bridges

Stencil art is a drawing technique for reproducing designs by repeatedly painting pigments through stencil sheets. Each stencil sheet is a connected surface maintained via thin connections called bridges. Existing computer-aided stencil art creation studies focus on choosing a set of bridges that causes the least amount of distortion while fully connecting all islands to the sheet. Unlike previous works, we propose a novel method called OVERPAINT that sidesteps the use of bridges by overpainting pigments. Our method automatically generates an ordered set of bridge-free stencil sheets from an input image. By painting sequentially, one can obtain a result resembling the appearance of the input image. We demonstrate our method on several artworks and a user study. The results show that our method enables the user to create visually precise and delicate stencil arts.
A study of some southern planetary nebulae

Radial velocities and expansions velocities (forbidden line O III, forbidden line O II, and He II) are measured for a sample of 64 southern Galactic planetary nebulae. Also, nebular electronic densities are derived from the forbidden line O II 3727, 3729 A double for 23 of these objects. The distance scale of Dopita et al. (1987) is used to derive distances to 33 Galactic nebulae. 50 references.
Teaching Statistics and Data Science to Business Students

Data and the analyses thereof are more important than ever for driving critical decision-making in different business applications today. Hence, statistics forms an integral part of most business curriculum across colleges and universities at both undergraduate and graduate levels. This article explores the different facets of teaching statistics (and data science, by extension) to non-STEM majors at a minority-serving institution located in the western United States. It starts with a brief overview of their business statistics course curriculum along with assessment outcomes reported in recent years. It then presents some of my own research in understanding factors that impact student performance and success in this course for potential early detection of “at-risk” students, the role of academic support services like Supplemental Instruction (or SI) in potentially improving student outcomes, the differences in student outcomes between traditional face-to-face and online sections of the course, and lastly the challenges faced during the virtual instruction period precipitated by the COVID-19 pandemic since March 2020. The article concludes with some of my own reflections from teaching this course for over 10 years and the future opportunities to further improve student outcomes in this course, particularly for underserved students.
Effect of nematic ordering on the elasticity and yielding in disordered polymeric solids

The relation between elasticity and yielding is investigated in a model polymer solid by Molecular-Dynamics simulations. By changing the bending stiffness of the chain and the bond length, semicrystalline and disordered glassy polymers - both with bond disorder - as well as nematic glassy polymers with bond ordering are obtained. It is found that in systems with bond disorder the ratio Ty/G between the shear yield strength Ty and the shear modulus G is close to the universal value of the atomic metallic glasses. The increase of the local nematic order in glasses leads to the increase of the shear modulus and the decrease of the shear yield strength, as observed in experiments on nematic thermosets. A tentative explanation of the subsequent reduction of the ratio Ty/G in terms of the distributions of the per-monomer stress is offered.
The problem with water footprints outside of irrigated drylands

ABSTRACT Virtual water – embedded in an agricultural commodity by virtue of evapotranspiration during crop growth – is effectively consumed by the purchaser. In water-poor economies, it breaks their dependence on local water-for-food and acts as a political stabilizer. Tony Allan’s concept remains highly relevant in the irrigated drylands for which it was developed, but calculating water footprints for agriculture elsewhere should take account of the non-agricultural counterfactual – which may consume more water than the agriculture that replaces it. Otherwise, use of water footprinting, for example, in trade policy, will be misleading and counterproductive.
Heavy quark expansion and universal form-factors in the quark model

Meson transition amplitudes of the vector, axial-vector, and tensor quark currents are analyzed within the dispersion formulation of the constituent quark model. The form factors in the decay region are given by relativistic double spectral representations through the wave functions of the initial and final mesons. We perform a heavy quark expansion of the quark-model mesonic matrix elements with a next-to-leading-order accuracy and demonstrate that matching this expansion to the heavy quark expansion in QCD requires subtractions in the double spectral representations for the form factors and allows fixing the subtraction terms. The Isgur-Wise function and next-to-leading-order universal form factors are calculated. {copyright} {ital 1997} {ital The American Physical Society}
Qualitative dynamics of piecewise-linear differential equations: a discrete mapping approach

We propose a discrete mapping to study the qualitative properties of the dynamics of biological or other complex networks, involving switchlike interactions between the various elements. The stable steady states and the limit cycles of the piecewise-linear equations which model such networks are derived from the dynamical behaviour of the proposed discrete mapping. Furthermore, this mapping takes into account not only the logical structure of the network but also the parameters used in the description.
Rapid and signal crowdedness-robust in situ sequencing through hybrid block coding

Spatial transcriptomics technology has revolutionized our understanding of cell types and tissue organization, opening new possibilities for researchers to explore transcript distributions at subcellular levels. However, existing methods have limitations in resolution, sensitivity, or speed. To overcome these challenges, we introduce SPRINTseq (Spatially Resolved and signal-diluted Next-generation Targeted sequencing), an innovative in situ sequencing strategy that combines hybrid block coding and molecular dilution strategies. Our method enables fast and sensitive high-resolution data acquisition, as demonstrated by recovering over 142 million transcripts using a 108 gene panel from 453,843 cells from four mouse brain coronal slices in less than two days. Using this advanced technology, we uncover the cellular and subcellular molecular architecture of Alzheimer’s disease, providing additional information into abnormal cellular behaviors and their subcellular mRNA distribution. This improved spatial transcriptomics technology holds great promise for exploring complex biological processes and disease mechanisms.
Selecting Chromosomes for Polygenic Traits

We define and study the problem of chromosomal selection for multiple complex traits. In this problem, it is assumed that one can construct a genome by selecting different genomic parts (e.g. chromosomes) from different cells. The constructed genome is associated with a vector of polygenic scores, obtained by summing the polygenic scores of the different genomic parts, and the goal is to minimize a loss function of this vector. While out of reach today, the problem may become relevant in the future with emerging future technologies, and may yield far greater gains in the loss compared to the present day technology of as embryo selection, provided that technological and ethical barriers are overcome. We suggest and study several natural loss functions relevant for both quantitative traits and disease. We propose two algorithms, a Branch-and-Bound technique, to solve the problem for multiple traits and any monotone loss function, and a convex relaxation algorithm applicable for any differentiable loss. Finally, we use the infinitesimal model for genetic architecture to approximate the potential gain achieved by chromosomal selection for multiple traits.