Miracle-dz/UniFAR-FTUs huggingface dataset:
A Precision Drone Landing System using Visual and IR Fiducial Markers and a Multi-Payload Camera

We propose a method for autonomous precision drone landing with fiducial markers and a gimbal-mounted, multi-payload camera with wide-angle, zoom, and IR sensors. The method has minimal data requirements; it depends primarily on the direction from the drone to the landing pad, enabling it to switch dynamically between the camera's different sensors and zoom factors, and minimizing auxiliary sensor requirements. It eliminates the need for data such as altitude above ground level, straight-line distance to the landing pad, fiducial marker size, and 6 DoF marker pose (of which the orientation is problematic). We leverage the zoom and wide-angle cameras, as well as visual April Tag fiducial markers to conduct successful precision landings from much longer distances than in previous work (168m horizontal distance, 102m altitude). We use two types of April Tags in the IR spectrum - active and passive - for precision landing both at daytime and nighttime, instead of simple IR beacons used in most previous work. The active IR landing pad is heated; the novel, passive one is unpowered, at ambient temperature, and depends on its high reflectivity and an IR differential between the ground and the sky. Finally, we propose a high-level control policy to manage initial search for the landing pad and subsequent searches if it is lost - not addressed in previous work. The method demonstrates successful landings with the landing skids at least touching the landing pad, achieving an average error of 0.19m. It also demonstrates successful recovery and landing when the landing pad is temporarily obscured.
Johnson-noise-limited cancellation-free microwave impedance microscopy with monolithic silicon cantilever probes

Microwave impedance microscopy (MIM) is an emerging scanning probe technique for nanoscale complex permittivity mapping and has made significant impacts in diverse fields from semiconductors to quantum materials. To date, the most significant hurdles that limit its widespread use are the requirements of specialized microwave probes and high-precision cancellation circuits. Here we show that forgoing both elements not only is feasible but actually enhances MIM performance. Using monolithic silicon cantilever probes and a cancellation-free architecture, we demonstrate thermal Johnson-noise-limited, drift-free MIM operation with 15 nm spatial resolution, minimal topography crosstalk, and an unprecedented sensitivity of 0.26 zF/$\sqrt{\text{Hz}}$. We accomplish this by taking advantage of the high mechanical resonant frequency and spatial resolution of silicon probes, the inherent common-mode phase noise rejection of self-referenced homodyne detection, and the exceptional stability of the streamlined architecture. Our approach makes MIM drastically more accessible and paves the way for more advanced operation modes and integration with complementary techniques.
Gadolinium dose reduction for brain MRI using conditional deep learning

Recently, deep learning (DL)-based methods have been proposed for the computational reduction of gadolinium-based contrast agents (GBCAs) to mitigate adverse side effects while preserving diagnostic value. Currently, the two main challenges for these approaches are the accurate prediction of contrast enhancement and the synthesis of realistic images. In this work, we address both challenges by utilizing the contrast signal encoded in the subtraction images of pre-contrast and post-contrast image pairs. To avoid the synthesis of any noise or artifacts and solely focus on contrast signal extraction and enhancement from low-dose subtraction images, we train our DL model using noise-free standard-dose subtraction images as targets. As a result, our model predicts the contrast enhancement signal only; thereby enabling synthesization of images beyond the standard dose. Furthermore, we adapt the embedding idea of recent diffusion-based models to condition our model on physical parameters affecting the contrast enhancement behavior. We demonstrate the effectiveness of our approach on synthetic and real datasets using various scanners, field strengths, and contrast agents.
Characterization of the low electric field and zero-temperature two-level-system loss in hydrogenated amorphous silicon

Two-level systems (TLS) are an important, if not dominant, source of loss and noise for superconducting resonators such as those used in kinetic inductance detectors and some quantum information science platforms. They are similarly important for loss in photolithographically fabricated superconducting mm-wave/THz transmission lines. For both lumped-element and transmission-line structures, native amorphous surface oxide films are typically the sites of such TLS in non-microstripline geometries, while loss in the (usually amorphous) dielectric film itself usually dominates in microstriplines. We report here on the demonstration of low TLS loss at GHz frequencies in hydrogenated amorphous silicon (a-Si:H) films deposited by plasma-enhanced chemical vapor deposition in superconducting lumped-element resonators using parallel-plate capacitors (PPCs). The values we obtain from two recipes in different deposition machines, 7$\,\times\,10^{-6}$ and 12$\,\times\,10^{-6}$, improve on the best achieved in the literature by a factor of 2--4 for a-Si:H and are comparable to recent measurements of amorphous germanium. Moreover, we have taken care to extract the true zero-temperature, low-field loss tangent of these films, accounting for temperature and field saturation effects that can yield misleading results. Such robustly fabricated and characterized films render the use of PPCs with deposited amorphous films a viable architecture for superconducting resonators, and they also promise extremely low loss and high quality factor for photolithographically fabricated superconducting mm-wave/THz transmission lines used in planar antennas and resonant filters.
Denoising Gradient Descent in Variational Quantum Algorithms

In this article we introduce an algorithm for mitigating the adverse effects of noise on gradient descent in variational quantum algorithms. This is accomplished by computing a {\emph{regularized}} local classical approximation to the objective function at every gradient descent step. The computational overhead of our algorithm is entirely classical, i.e., the number of circuit evaluations is exactly the same as when carrying out gradient descent using the parameter-shift rules. We empirically demonstrate the advantages offered by our algorithm on randomized parametrized quantum circuits.
VLSP 2023 -- LTER: A Summary of the Challenge on Legal Textual Entailment Recognition

In this new era of rapid AI development, especially in language processing, the demand for AI in the legal domain is increasingly critical. In the context where research in other languages such as English, Japanese, and Chinese has been well-established, we introduce the first fundamental research for the Vietnamese language in the legal domain: legal textual entailment recognition through the Vietnamese Language and Speech Processing workshop. In analyzing participants' results, we discuss certain linguistic aspects critical in the legal domain that pose challenges that need to be addressed.
CAMASim: A Comprehensive Simulation Framework for Content-Addressable Memory based Accelerators

Content addressable memory (CAM) stands out as an efficient hardware solution for memory-intensive search operations by supporting parallel computation in memory. However, developing a CAM-based accelerator architecture that achieves acceptable accuracy, while minimizing hardware cost and catering to both exact and approximate search, still presents a significant challenge especially when considering a broader spectrum of applications. This complexity stems from CAM's rapid evolution across multiple levels--algorithms, architectures, circuits, and underlying devices. This paper introduces CAMASim, a first comprehensive CAM accelerator simulation framework, emphasizing modularity, flexibility, and generality. CAMASim establishes the detailed design space for CAM-based accelerators, incorporates automated functional simulation for accuracy, and enables hardware performance prediction, by leveraging a circuit-level CAM modeling tool. This work streamlines the design space exploration for CAM-based accelerator, aiding researchers in developing effective CAM-based accelerators for various search-intensive applications.
Nonassociative cyclic algebras and the semiassociative Brauer monoid

We look at classes of semiassociative algebras, with an emphasis on those that canonically generalize associative (generalized) cyclic algebras, and at their behaviour in the semiassociative Brauer monoid defined by Blachar, Haile, Matri, Rein, and Vishne. A possible way to generalize this monoid in characteristic $p$ that includes nonassociative differential algebras is briefly considered.
CWTM: Leveraging Contextualized Word Embeddings from BERT for Neural Topic Modeling

Most existing topic models rely on bag-of-words (BOW) representation, which limits their ability to capture word order information and leads to challenges with out-of-vocabulary (OOV) words in new documents. Contextualized word embeddings, however, show superiority in word sense disambiguation and effectively address the OOV issue. In this work, we introduce a novel neural topic model called the Contextlized Word Topic Model (CWTM), which integrates contextualized word embeddings from BERT. The model is capable of learning the topic vector of a document without BOW information. In addition, it can also derive the topic vectors for individual words within a document based on their contextualized word embeddings. Experiments across various datasets show that CWTM generates more coherent and meaningful topics compared to existing topic models, while also accommodating unseen words in newly encountered documents.
IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators

Code understanding and generation have fast become some of the most popular applications of language models (LMs). Nonetheless, research on multilingual aspects of Code-LMs (i.e., LMs for code generation) such as cross-lingual transfer between different programming languages, language-specific data augmentation, and post-hoc LM adaptation, alongside exploitation of data sources other than the original textual content, has been much sparser than for their natural language counterparts. In particular, most mainstream Code-LMs have been pre-trained on source code files alone. In this work, we investigate the prospect of leveraging readily available compiler intermediate representations - shared across programming languages - to improve the multilingual capabilities of Code-LMs and facilitate cross-lingual transfer. To this end, we first compile SLTrans, a parallel dataset consisting of nearly 4M self-contained source code files coupled with respective intermediate representations. Next, starting from various base Code-LMs (ranging in size from 1.1B to 7.3B parameters), we carry out continued causal language modelling training on SLTrans, forcing the Code-LMs to (1) learn the IR language and (2) align the IR constructs with respective constructs of various programming languages. Our resulting models, dubbed IRCoder, display sizeable and consistent gains across a wide variety of code generation tasks and metrics, including prompt robustness, multilingual code completion, code understanding, and instruction following.
A protocol for systematic review and meta-analysis

Background: Rotator cuff tendinitis is a highly prevalent cause of shoulder pain and leads to decreased patient quality of life. Extracorporeal shock wave therapy (ESWT) and ultrasound-guided needling are considered beneficial for rotator cuff tendinitis. A systematic review and meta-analysis comparing ESWT with sham-ESWT or ultrasound-guided needling in the management of pain and calcification is lacking. Methods: We will search the following up database from its inception to August 2020 without language restriction: PubMed, Cochrane Library, Web of Science, EMBASE, China National Knowledge Infrastructure, China Biomedical Literature Database, Chinese Science Journal Database, and WangFang database. All randomized controlled trials compared the effect of ESWT and sham-ESWT or ultrasound-guided needling of rotator cuff tendinitis will be included in pain and calcification. Two researchers will operate literature retrieval, screening, information extraction, quality assessment, and data analysis independently. The analysis will be conducted using Review Manager 5.3 Software. Results: The findings will be submitted to a peer-reviewed publication. Conclusion: This systematic review and meta-analysis will provide high-quality evidence for the treatment of patients with rotator cuff tendinitis. INPLASY registration number: INPLASY202080028 Abbreviations: ESWT = extracorporeal shock wave therapy, RCTs = randomized controlled trails.
A protocol for systematic review and meta analysis

Background: This study will aim to assess the effectiveness and safety of electrical stimulation (ES) for the treatment of patients with benign prostatic hyperplasia (BPH). Methods: PubMed, EMBASE, Web of science, Springer, Cochrane Library, PsycINFO, Allied and Complementary Medicine Database, CBM, and China National Knowledge Infrastructure will be retrieved from inception to the September 1, 2019. No language limitation will be applied to this study. Randomized controlled trials (RCTs) that assessed the effectiveness and safety of ES for the treatment of patients with BPH will be considered for inclusion. Literature selection, data collection, and risk of bias assessment will be conducted by 2 investigators independently. Statistical analysis will be carried out using RevMan 5.3 Software. Results: This study will summarize high quality RCTs based on the present evidence of ES for the treatment of BPH in several aspects, including changes in urological symptoms, changes in prostate size, urodynamic parameters, quality of life, and number and severity of adverse events. Conclusion: The findings of this study will provide latest evidence to appraise whether ES is an effective and safety intervention for patients with BPH. PROSPERO registration number: PROSPERO CRD42019157241. Abbreviations: BPH = benign prostatic hyperplasia, CIs = confidence intervals, ES = electrical stimulation, RCTs = randomized controlled trials.
The Mediating Effect of Tourists’ Feedback Information on the Relationship between Interaction and Service Innovation in Tanzania

Studies on feedback information and interactions among tourists and tourism services are limited to residents, service providers, and mostly business-to-business. Little remains unknown about the relevance of tourists’ feedback information and interactions to service innovation. This study examined the mediating effect of tourist feedback information in the relationship between tourists’ interactions and service innovation. A survey of 290 Tanzanian tourism firms gathered the scale data that was analysed using Structural Equation Modelling in the Partial Least Square method. Tourist feedback information and tourists’ interactions were found to positively affect service innovation. While tourists’ interactions exhibited a strong positive effect on service innovation, there is a partial mediation of feedback information between the two. These results inform the service industry to capitalize on customer feedback information in enriching new service designs. As a result, practitioners in service firms are at a high point to set strategies to improve interactions as good practices in service innovation. Specifically, the tourism industry actors obtain insights into handling customers and benefiting from their actions and information. Theoretically, the study offers an understanding of interactions as applied in the service dominant logic such that apart from the exchange focus, feedback and interactions can also be considered as information sources for service innovation across firms. These results suggest that tourist interactions and feedback should be treated as key information points for enabling service innovation.
Cardiovascular and Respiratory Benefits From Regular Sauna Bathing and Its Role in Treating Disease

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Most of our population is either directly affected or has a loved one that suffered the burden of cardiovascular disease. Given this, investigating all possible treatment strategies is crucial to alleviating this burden. Finnish sauna bathing is a form of whole-body passive thermotherapy that has shown promise in positively reinforcing our cardiovascular system. The affordable and easily accessible nature of sauna bathing makes it an attractive candidate to be utilized in the treatment of disease. The purpose of this review is to explore how sauna bathing benefits the heart and blood vessels in both physiological and diseased states. The therapeutic value of sauna bathing is evaluated in treating hypertension (HTN), coronary artery disease (CAD), congestive heart failure (CHF), and its usefulness in comorbidities of CVD such as metabolic syndrome and respiratory impairment. This literature review examines primary, peer-reviewed, and systematic review research from EMBASE, PubMed, and MEDLINE that link sauna bathing to improved cardiovascular and respiratory health. The positive effects on pathological states as well as the physiological mechanism responsible for these effects were investigated. Sauna bathing shows reduction in mean arterial pressure (MAP) in short-term as well as long-term studies through decreased arterial compliance and vasodilatory mechanisms. Studies have also shown positive effects of heat therapy in alleviating active CAD along with preventing disease by processes such as altering blood flow mechanics, supporting endothelial cell function, and attenuating metabolic risk factors. It has been deemed safe in the setting of stable CAD but is contraindicated in unstable CAD. In CHF, sauna’s therapeutic properties include reducing heart size, preload, serum BNP as well as increasing left-ventricular ejection fraction (LVEF). Regular heat therapy also mitigated metabolic risk factors and aided concurrent pulmonary function. Whole-body passive thermotherapy shows a clinical benefit in preventing and treating cardiovascular disease. It has been shown to be safe in most patients, but it should be discussed with one’s physician prior to use. Future work will include studying long-term outcomes and its beneficial role in other diseases that have cardiovascular consequences.
Erratum: Evidence for an intermediate-mass black hole in the globular cluster NGC 6624

The paper ‘Evidence for an intermediate-mass black hole in the globular cluster NGC 6624’ was published in MNRAS, 468, 2114 (2017). When estimating the model-dependent minimum mass of the intermediate-mass black hole (IMBH) of 60 000 M⊙ in Section 5, we used the separation of 0.15 pc for PSR J1823−3021C from the globular cluster centre, as given in Peuten et al. (2014, see table 2 therein). Unfortunately, this value is incorrect and the correct separation is 0.34 pc based on the position given in Table 1 (also see Lynch et al. 2012). This correct distance measurement changes the result presented in Fig. 9 in the published version, and the modified figure based on the positions given in Table 1 is appended here. Note that this does not affect any other results presented in the paper, in particular, the IMBH mass estimation obtained through orbital dynamics given in Section 4.
How well do LSTM language models learn ﬁller-gap dependencies?

This paper revisits the question of what LSTMs know about the syntax of ﬁller-gap dependencies in English. One contribution of this paper is to adjust the metrics used by Wilcox et al. (2018) and show that their language models (LMs) learn embedded wh -questions – a kind of ﬁller-gap dependencies – better than they originally claimed. Another contribution of this paper is to examine four additional ﬁller-gap dependency constructions to see whether LMs perform equally on all types of ﬁller-gap dependencies. We ﬁnd that different constructions are learned to different extents, and there is a correlation between performance and frequency of constructions in the Penn Treebank Wall Street Journal corpus.
Retirement Pensions and Disability Insurance for the 21st Century

This project estimates the degree of disability risk among the United States and English over-50 populations. Using a disability measure that closely matches the criteria used by English and U.S. disability systems, we find both higher levels of disability in the U.S. and higher levels of disability risk in the U.S. Furthermore, we estimate spillovers between disability insurance and retirement pension program in the context of the increase in the United Kingdom retirement age for women in the years 2010 to 2019. We document that, despite a significant increase in disability benefit take-up among disabled individuals who would have been otherwise retired, these individuals experienced large losses in household income. Healthy individuals, in contrast, experienced much smaller losses in income, as they responded to the increase in the retirement age by increasing their labor-force participation. Finally, we develop a dynamic model of labor supply, social security benefits, and savings to evaluate the U.K. disability benefit system in the context of the U.K. retirement reform. This model uses as its inputs the parameters of the disability process we have estimated, and is estimated to match the responses to the reform. It can then be used to evaluate other joint reforms of disability and retirement program.
Understanding Instrumental Variables in Models with Essential Heterogeneity

This paper examines the properties of instrumental variables (IV) applied to models with essential heterogeneity, that is, models where responses to interventions are heterogeneous and agents adopt treatments (participate in programs) with at least partial knowledge of their idiosyncratic response. We analyze two-outcome and multiple-outcome models, including ordered and unordered choice models. We allow for transition-specific and general instruments. We generalize previous analyses by developing weights for treatment effects for general instruments. We develop a simple test for the presence of essential heterogeneity. We note the asymmetry of the model of essential heterogeneity: outcomes of choices are heterogeneous in a general way; choices are not. When both choices and outcomes are permitted to be symmetrically heterogeneous, the method of IV breaks down for estimating treatment parameters.
NBER WORKING PAPER SERIES UNDERSTANDING THE RISE IN CORPORATE CASH: PRECAUTIONARY SAVINGS OR FOREIGN TAXES

What has driven the dramatic rise in U.S. corporate cash? Using non-public data, we show that the run-up is not uniform across firms and is greatest in the foreign subsidiaries of multinational firms. Standard precautionary motives explain only domestic cash holdings, not the burgeoning foreign cash balances. Falling foreign tax rates, coupled with relaxed restrictions on income shifting, are the root of the changing foreign cash patterns. IP intensive firms have the greatest ability to shift income to low tax jurisdictions, and their foreign subsidiaries are where we observe the largest accumulations of cash. Michael W. Faulkender University of Maryland RH Smith School of Business 4417 Van Munching Hall College Park, MD 20742 mfaulken@rhsmith.umd. edu Kristine W. Hankins University of Kentucky Lexington, KY 40506 kristine.hankins@uky.edu Mitchell A. Petersen Kellogg School of Management Northwestern University 2001 Sheridan Road Evanston, IL 60208 and NBER mpetersen@northwestern.edu