Miracle-dz/UniFAR-FTUs huggingface dataset:
Noncommutative negative order AKNS equation and its soliton solutions

A noncommutative negative order AKNS (NC-AKNS(-1)) equation is studied. To show the integrability of the system, we present explicitly the underlying integrable structure such as Lax pair, zero-curvature condition, an infinite sequence of conserved densities, Darboux transformation (DT) and quasideterminant soliton solutions. Moreover, the NC-AKNS(-1) equation is compared with its commutative counterpart not only on the level of nonlinear evolution equation but also for the explicit solutions.
COMP4801 – FYP Detailed Project Plan

Along with decades of AI application development, Federated Learning (FL), firstly proposed by Google [1] in 2016 for their Gboard text suggestion application, is recently becoming a popular AI technique due to the increasing concerns about data privacy. By definition, FL is an encrypted distributed machine learning. The high-level idea of FL [2] is that rather than centralizing all the data in a central server to train the Machine Learning (ML) or Deep Learning (DL) model, each data owner trains their local model on their local nodes and sends the aggregated local gradients in an encrypted manner to the central node for training the global model. The updated global model will then distribute to all the local nodes. The communication round repeats to improve the model iteratively. Thus, the contradiction between data privacy and data sharing can be resolved. For the case of B2C (business-toconsumer), FL is useful when clients' data is very sensitive or under legal protection, such as in financial and medical applications. For the case of B2B (business-to-business), FL allows industrial entities to bridge their data silo without disclosing their own datasets such that more training data are available to improve the training performance. This is useful when valid data is scarce or mining and labeling new data are costly. It is attractive to startup companies that don't have enough historical data for their AI applications.
Investors’ Behavior and Equity Investment Decision: An Evidence from Nepal

Behavior is the psychological phenomenon/aspect of the individuals, and investors’ behavior influences investment decisions. The research examined the influence of investors’ behavior on equity investment decisions based on quantitative research philosophy and utilized descriptive cum analytical research design. The sample was 400 individual investors from the top ten brokerage firms, with 40 investors who made equity investment decisions in the Nepalese stock market using a first-come-first-basis with readiness to respond to the survey questionnaire. Data were collected from a 5-point Likert type with a self-administered closed-end structured questionnaire from 293 respondents. Descriptive and inferential statistics were applied in analyzing data, including correlation coefficient and multiple regression analysis. The results indicate that investors’ behavior is a significant factor in equity investment decisions. However, gender is not an influencing factor. Hence, the financial market may not always be guided by fundamental principles of standard finance but is largely influenced by investors’ irrationality and behavior. Then, it leads to excessive trading of securities, selling to gain portfolios, and overreaction and underreaction in the marketplace. Therefore, investors’ irrationality can be abated through training, professional advice, investment goal, and implementation of behavioral finance courses at professional and academic institutions.
Cord Blood Lipid Parameters and its Correlation with Birth Weight of Neonates

: Introduction: Cardiovascular diseases are the leading cause of mortality in India. The important factor associated is dyslipidemia. A strong relationship has been seen in epidemiological studies between cholesterol and cardiovascular disease. The present study was planned to analyse cord blood lipid profile, apolipoproteins and atherogenic index and to see their relationship with birth weight. Method: Our study group consisted of 300 healthy fullterm newborn. The cord blood was collected immediately after a normal delivery. The blood was tested to determine lipid parameters and was correlated with birth weight. Result: The results showed that the levels of (TC), triglyceride, (HDL) and atherogenic index was higher whereas LDL was lower in high birth weight babies as compared to low birth weight and normal birth weight newborns. The correlation was positive with TC, LDL-Cholesterol, ApoB and atherogenic index but negative with TG, HDL-C and ApoA-1.
Testing for constant correlation of filtered series under structural change

SummaryThe paper proposes a test for constant correlations that allow for breaks at unknown times in the marginal means and variances. Theoretically and in an application to US and German stock returns, we find that not accounting for changes in the marginal moments has severe consequences. This is because incorrect standardization of the series transfers to the sample correlations onto which the tests are built. Correcting for variance breaks at unknown time will have an asymptotic effect. To discuss adjustments, we tackle the issue more generally by considering partial-sums-based inference on moment properties of unobserved processes that is conducted on the basis of estimated counterparts obtained in a preliminary step. The paper gives a characterization of the conditions under which the effect of filtering does not vanish asymptotically. The analysis extends to models with breaks in parameters at estimated time.
Relativistic Thermodynamics Laws According to Inverse Relativity

: The three laws of relativistic thermodynamics according to the inverse theory of relativity, the relativistic formula of the first law, we find that time dilation reduces all energy forms of the thermodynamic system from positive space without violating the principle of energy conservation. Where the loss in internal energy besides the work done on the mass of the system appears in the negative space, in the relativistic formula of the second law we get a stability value for the entropy of the system in the positive space and we also get an entropy similar to it in the negative space as a result of a modified copy of the microscopic information of the system, As for the relativistic formula of the third law, the value of entropy in positive space reaches zero when the temperature of the system reaches absolute zero, and in negative space the entropy also reaches zero when the speed of the reference frame theoretically reaches the speed of light.
Linguistic Cognitive Load Analysis on Dialogues with an Intelligent Virtual Assistant

Virtual assistants have become fixtures in everyday settings, but most research focuses on their development rather than their use following deployment. To facilitate study of their use in office settings, we introduce OfficeDial , a multimodal dataset containing audio recordings, transcriptions, eye tracking data, and screen recordings from conversations between humans and virtual assistants in office environments. Conversations are paired with physical and behavioral measures of cognitive load. We study the associations between verbal behavior and noise level and reveal key relationships between verbal redundancy, disfluency, and noise level. We make our new dataset available to interested researchers to inspire further exploration.
New Observations on the Constructive Content of First-Order Completeness Theorems

We report on some new observations regarding the constructive reverse mathematics of ﬁrst-order completeness theorems. When conducted in a constructive type theory such as the calculus of inductive constructions (CIC), many diﬀerent formulations of completeness can be distinguished and analysed regarding their suﬃcient and necessary non-constructive assumptions. As the main new result, we identify a principle we dub WLEMS at the intersection of double-negation shift and weak excluded middle, exactly capturing the non-constructivity needed for object-level disjunctions. The observations reported here are part of an ongoing general attempt at a systematic classiﬁcation of the independent ingredients contributing to the non-constructivity of completeness theorems
Cold Diffusion for Speech Enhancement /Author=Yen, Hao; Germain, Francois; Wichern, Gordon; Le Roux, Jonathan /CreationDate=April 14, 2023 /Subject=Artificial Intelligence, Speech

Diffusion models have recently shown promising results for difficult enhancement tasks such as the conditional and unconditional restoration of natural images and audio signals. In this work, we explore the possibility of leveraging a recently proposed advanced iterative diffusion model, namely cold diffusion, to recover clean speech signals from noisy signals. The unique mathematical properties of the sampling process from cold diffusion could be utilized to restore high-quality samples from arbitrary degradations. Based on these properties, we propose an improved training algorithm and objective to help the model generalize better during the sampling process. We verify our proposed framework by investigating two model architectures. Experimental results on benchmark speech enhancement dataset VoiceBankDEMAND demonstrate the strong performance of the proposed approach compared to representative discriminative models and diffusion-based enhancement models. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023 c © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Mitsubishi Electric Research Laboratories, Inc. 201 Broadway, Cambridge, Massachusetts 02139 COLD DIFFUSION FOR SPEECH ENHANCEMENT Hao Yen, François G. Germain, Gordon Wichern, Jonathan Le Roux Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA School of Electrical and Computer Engineering, Georgia Institute of Technology, GA, USA
Revealing the hillslope response to earthquake legacy effect using time series InSAR

31 Strong earthquakes are not only able to change the earth's surface processes by triggering a 32 large population of coseismic landslides but also by influencing hillslope deformation rates in 33 post-seismic periods. An increase in post-seismic hillslope deformation rates could also be 34 linked to a change in post-seismic landslide hazard level and, thus, could be exploited to better 35 assess post-seismic landslide risk in a given area. However, variations in hillslope 36 deformations from pre- to post-seismic phases have rarely been examined for strong 37 earthquakes. This paper examines pre- and post-seismic hillslope deformations, from 2014 to 38 2018, for a large area (~2,300 km 2 ) affected by the 2016 Mw7.8 Kaikōura earthquake using 39 time series Interferometric Synthetic Aperture Radar (InSAR) techniques. To consistently 40 analyze the entirety of the area from pre- to post-seismic phases, we aggregate InSAR-derived 41 deformations for geomorphologically meaningful landscape partitions called Slope Units. We 42 further examine the aggregated data through the hillslope deformation scheme, which we 43 propose as a method to systematically identify the variations in post-seismic hillslope 44 deformation trends. In this context, we label newly activated, uninterruptedly deforming, and 45 stabilized hillslopes in the post-seismic phase. Our results show an ~130% increase in mean 46 annual line-of-sight velocity after the earthquake. Overall, the areas affected by larger ground 47 shaking show higher post-seismic deformations, which highlights the importance of the 48 earthquake legacy effect as a factor controlling post-seismic hillslope deformations. 49 50 51 52 53 54 55 56 57 58 59 60 61 62
Numerical analysis of the effects of riblets on drag reduction of a flat plate

In recent years, marine transportation as well as land and air transportation has become in the centre of attention. There has been an attempt to reduce the drag exerted on vessels by various methods, such as rough surfaces and base bleed. Study of the high-speed seawater animals like sharks and dolphins has triggered the use of riblets on the hull of marine vessels. The use of riblet is easy among various methods of skin friction drag reduction. For this reason, there is an interest for construction and optimization of riblet as an efficient and economical way. In this research, the shark’s skin was modeled for the first time in ANSYS CFX using Computational Fluid Dynamics, through analyzing the effects of riblet on a submerged flat plate. Different types of riblet based on height and space between micro channels were studied, and then a comparison between a riblet-covered plate and a smooth plate in various velocities were performed. It was found that by selecting the most appropriate type of riblet, 11 % drag reduction can be attained. Then, by comparing different types of riblets, the best type for drag reduction was selected. Furthermore, the obtained results were compared with the available experimental data.
The Effect of the Leadership Development Model on High School Students’ Leadership as a Soft Skill

The aim of this work is to describe a model of efficient leadership qualities development among students in the process of soft skills acquisition. The research was implemented in School No. 98 and Lyceum No. 177 (Kazan). It included a total of 144 students in grades 8-10. The study comprised of a diagnostic, experimental and final phase. At the diagnostic phase, the level of leadership among secondary school students was determined according to the method developed by Zharikov and Krushelnitsky. The model was tested and introduced into secondary education during the experimental phase. A comparative analysis of the results obtained at the diagnostic and final phase in all grade revealed an increase in the number of respondents with moderate and high leadership potential. This fact indicates that the implementation of the leadership development model can be considered successful and may be used in other educational institutions. The introduction of the leadership development model will contribute to further improvement of leadership qualities and soft skills among students. The results of this study can be used as a reference for subsequent research in this field.
Knowledge management requirements for information systems in small ventures: A fuzzy-set qualitative comparative analysis (fsQCA)

Knowledge management and information systems have garnered increased attention for their potential to enhance venture performance. However, there is limited research on the specific competences of information systems based on knowledge management within the context of micro and small businesses. This study aims to fill this gap by examining small businesses in the entrepreneurship field to determine whether they recognize the importance of these competences. The research focuses on a sample of 70 small businesses operating in lower-middle-income economies and employs a fuzzy-set qualitative comparative analysis (fsQCA) methodology. The findings reveal that smaller businesses acknowledge the significance of information systems competences in facilitating their organizational development and that these ventures are increasingly exposed to the value of knowledge management in their day-to-day operations. This study contributes to the existing literature by shedding light on the role of smaller businesses in lower-middle-income economies.
Fabrication of absorption gratings with X-ray lithography for X-ray phase contrast imaging

Grating-based X-ray phase contrast imaging is promising especially in the medical area. Two or three gratings are involved in grating-based X-ray phase contrast imaging in which the absorption grating of high-aspect-ratio is the most important device and the fabrication process is a great challenge. The material with large atomic number Z is used to fabricate the absorption grating for excellent absorption of X-ray, and Au is usually used. The fabrication process, which involves X-ray lithography, development and gold electroplating, is described in this paper. The absorption gratings with 4 μm period and about 100 μm height are fabricated and the high-aspect-ratio is 50.
Comparing Colon Capsule Endoscopy To Colonoscopy; A Symptomatic Patient’s Perspective

M Sya q Ismail (  sya qismail2009@gmail.com ) Tallaght University Hospital and Trinity Academic Gastroenterology Group, Trinity College Dublin https://orcid.org/0000-0002-4461-136X Greg Murphy Tallaght University Hospital Serhiy Semenov Tallaght University Hospital and Trinity Academic Gastroenterology Group, Trinity College Dublin, Ireland Deirdre McNamara Tallaght University Hospital and Trinity Academic Gastroenterology Group, Trinity College Dublin, Ireland
Space Partitioning for Distributed Surface Reconstruction

Delaunay triangulation, as one of the fundamental problems in computational geometry, has been vastly explored in scientific research as it often constitutes the bottleneck in composite algorithms if no acceleration structures are used. In recent years however, data sets grew successively larger due to technological advancements such as in photogrammetry, 3D laser scanning or scientific simulation methods. Thus, distributed algorithms gained increasing attention as the main method to deal with data quantities in the terra-or petabyte range in a reasonable amount of time. This work investigates prospects of speeding up a state-of-the-art surface reconstruction algorithm (not yet published) by splitting up the underlying required Delaunay tetrahedralization using efficient uniform space partitioning. In a distributed execution environment, the constraints that a valid Delaunay graph must satisfy typically lead to the expensive exchange of points among the distributed compute nodes. By exploiting traits of the surface reconstruction algorithm, the implementation can relax the constraints for the distributed Delaunay tetrahedralization to gain performance and trade formal correctness with a minor and visually acceptable error bound. Moreover, the implementation deals with the technical challenges of incorporating the complete storage hierarchy to support data sets that exceed main memory capacities, as well as being usable in both local and distributed execution environments. The evaluation focuses on an analysis of the runtime performance of the space partitioned implementation for large planetary surface reconstruction with respect to la-*
Measuring Fraud in Banking and its Impact on the Economy: A Quasi-Natural Experiment

This paper suggests a novel approach to measuring fraud in banking and to evaluating its crosssectional and aggregate implications. I explore unique evidence of declining regulatory forbearance from the Russian banking system in the 2010s, when the central bank forcibly closed roughly twothirds of all operating banks for fraudulent activities. I first introduce an empirical model of the regulatory decision rule that determines whether a regulator is likely to run an unscheduled onsite inspection of a suspicious bank in the near future. I estimate the model using unique data on asset losses hidden by commercial banks and discovered by the Central Bank of Russia during unscheduled on-site inspections in the last two decades. I find that the average size of hidden asset losses detected by the rule equals 38% of the total assets of not-yet-closed fraudulent banks, and that the likelihood of fraud detection soared by a factor of 5 after 2013. With quarter-by-quarter predictions from the estimated rule, I form a “treatment” group of likely-to-be-inspected banks and then run a “fuzzy” difference-in-differences (FDID) regression to estimate the effects of the tightened regulation. FDID estimates show that likely-to-be-inspected banks substantially reduced credit to households and firms after the policy started in 2013, compared to similar untreated banks. Interpreting the FDID estimates of credit contraction as a credit supply shock and evaluating the macroeconomic implications of this shock using a VAR model of the Russian economy, I find that Russia’s GDP could have been larger by 7.3% cumulatively by the end of 2016 in the absence of the policy. This is the price the economy pays for reducing fraud in the banking system. JEL classifications: D22, G21, G28, G33, H11.
From Scene Representation to Robust Autonomy: A seamless Integration

The objective of this study is to examine the interdependence between scene representation and robust autonomy of mobile robots such as quadrotors and cars. It addresses crucial issues with the motion planning and SLAM components in the navigation system. Voxel Grids built from range sensors have been a popular choice of world representation for motion planning. The planners query the map for distance to collision and gradients, the planner uses these measurements to generate a smooth and safe trajectory through trajectory optimization. However, these methods assume the presence of zero sensor noise, such an assumption is severely violated when the maps are built through RGBD cameras, the noise in the point clouds are transferred to the occupancy maps through a non-linear transform and is further propagated to the distance and gradient field which results in a non-parametric noise. The performance of the deterministic planners that rely on such inaccurate gradients was found to decrease. As an antidote we propose CCO-VOXEL the very first chance-constrained optimization (CCO) algorithm that can compute trajectory plans with probabilistic safety guarantees in real-time directly on the voxel-grid representation of the world. We leverage the notion of Hilbert Space embedding of distributions and Maximum Mean Discrepancy (MMD) and gradient free Cross-Entropy Method for obtaining its minimum. We also show how a combination of low-dimensional feature embedding and pre-caching of Kernel Matrices of MMD allows us to achieve real-time performance in simulations as well as in implementations on on-board commodity hardware that controls the quadrotor flight. Voxel maps are not robust to outliers and fail to capture the world geometry when built from a highly noisy and sparse point cloud, such as those generated from triangulation through monocular visualinertial SLAM (VI-SLAM ). Inaccurate maps like these can significantly decrease the performance of the motion planner. We propose UrbanFly , a quadrotor planning framework for navigation in a planar urban high-rise environment. The core importance of UrbanFly is its ability to handle sparse and noisy point clouds built from VI-SLAM. Based on the insight that the sky-scrappers are planar, we derived an Uncertainty-Integrated Cuboidal (UIC) representation of the world and developed an uncertaintyaware planner that can interpret and leverage the benefits of UIC to generate safe trajectories in real time. UrbanFly demonstrates a 3.5 times improvement in safety metrics compared to state-ofthe-art algorithms. Points clouds generated from LiDAR need a lot of memory to store and transfer and lack structure, making it hard to extract spatial features. This makes it challenging to deploy lidar based Loop Detection and Closure (LDC) for distributed collaborative SLAM. To address this, we present FinderNet, a 6-DOF