Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconstruction d’ensembles compacts 3D

: Reconstructing a 3D shape from sample points is a central problem faced in medical applications, reverse engineering, natural sciences, cultural heritage projects, etc. While these applications motivated intense research on 3D surface reconstruction, the problem of reconstructing more general shapes hardly received any attention. This paper develops a reconstruction algorithm changing the 3D reconstruction paradigm as follows. First, the algorithm handles general shapes i.e. compact sets as opposed to surfaces. Under mild assumptions on the sampling of the compact set, the reconstruction is proved to be correct in terms of homotopy type. Second, the algorithm does not output a single reconstruction but a nested sequence of plausible reconstructions. Third, the algorithm accommodates topological persistence so as to select the most stable features only. Finally, in case of reconstruction failure, it allows the identiﬁcation of under-sampled areas, so as to possibly ﬁx the sampling. These key features are illustrated by experimental results on challenging datasets, and should prove instrumental in enhancing the processing of such datasets in the aforementioned applications.
Electron Beam Effects in Ge–Se Thin Films and Resistance Electron Beam Effects in Ge–Se Thin Films and Resistance Change Memory Devices Change Memory Devices

Chalcogenide glasses are the advanced materials of choice for the emerging nanoionic memory devices – conductive bridge random access memory (CBRAM). To understand the nature of the effects occurring in these devices under in ﬂ uence of electron-beam radiation, the interaction of blanked chalcogenide ﬁ lms and nanostructured ﬁ lms containing chalcogenide glass and silver (Ag) source are studied. Raman spectroscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction are used for establishing the structural and compositional effects occurring under radiation. They have strong compositional dependence with the stoichiometric compositions being most stable showing less structural changes after radiation. These effects are associated with the availability of lone-pair electrons, their participation in the bonding con ﬁ gurations and the coupling of electron states in the bandgap. They are further enhanced in the bilayers by silver diffusion in the chalcogenide matrix, as a result of interaction with electrons. These effects are used to interpret the electrical performance of CBRAM devices after radiation. The devices are characterized by their resistance states, threshold voltage and endurance. Those based on selenium-rich and stoichiometric composition undergo continuous parameters changes with increase in the radiation dose while in the devices based on germanium-rich composition a counter play of the structural changes and expulsion of silver occur.
DataHalo A Customizable Notification Visualization System for Personalized and Longitudinal Interactions

People struggle with the overflow of smartphone notifications but often face two challenges: (1) prioritizing the informative notifications as they wish and (2) retaining the delivered information as long as they want to utilize it. In this paper, we present DataHalo, a customizable notification visualization system that represents no-tifications as prolonged ambient visualizations on the home screen. DataHalo supports keyword-based filtering and categorization, and draws graphical marks based on time-varying importance model to enable longitudinal interaction with the notifications. We evaluated DataHalo through a usability study ( 𝑁 = 17), from which we improved the interface. We then conducted a three-week deployment study ( 𝑁 = 12) to assess how people use DataHalo in their domestic contexts. Our study revealed that people generated various visualization settings for different kinds of apps. Drawing
Modeling naturalistic affective states via facial and vocal expressions recognition

Affective and human-centered computing are two areas related to HCI which have attracted attention during the past years. One of the reasons that this may be attributed to, is the plethora of devices able to record and process multimodal input from the part of the users and adapt their functionality to their preferences or individual habits, thus enhancing usability and becoming attractive to users less accustomed with conventional interfaces. In the quest to receive feedback from the users in an unobtrusive manner, the visual and auditory modalities allow us to infer the users' emotional state, combining information both from facial expression recognition and speech prosody feature extraction. In this paper, we describe a multi-cue, dynamic approach in naturalistic video sequences. Contrary to strictly controlled recording conditions of audiovisual material, the current research focuses on sequences taken from nearly real world situations. Recognition is performed via a 'Simple Recurrent Network' which lends itself well to modeling dynamic events in both user's facial expressions and speech. Moreover this approach differs from existing work in that it models user expressivity using a dimensional representation of activation and valence, instead of detecting the usual 'universal emotions' which are scarce in everyday human-machine interaction. The algorithm is deployed on an audiovisual database which was recorded simulating human-human discourse and, therefore, contains less extreme expressivity and subtle variations of a number of emotion labels.
Overview of the NTCIR-17 FairWeb-1 Task

This paper provides an overview of the NTCIR-17 FairWeb-1 Task. FairWeb-1 is an English web search task which seeks more than an ad-hoc web search task. Our task considers not only document relevance but also group fairness. We designed three types of search topics for this task: researchers (R), movies (M), and Youtube contents (Y). For each topic type, attribute sets are defined for considering group fairness. We utilise a deduped version of the Chuweb21 corpus as the target corpus. We received 28 runs from six teams, including six runs from the organisers team. In this paper, we describe the task, the test collection construction and the official evalution results of the submitted runs.
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Fanconi anemia (FA) is a rare genetic condition in which the cell’s DNA repair machinery is dysregulated, significantly increasing the chances of tumorigenesis. Further research is being done in order to improve patient outcomes and incidences of cancer. Our group created a computational model of the FA DNA repair gene network, which removes interstrand crosslinks found in damaged DNA and repairs it so DNA synthesis can continue. Computer simulations show the number of DNA damage indicators decreased as the pathway continued. This was expected as the FA pathway repairs DNA damage. The goal of this project was to provide further understanding of the protein interactions so that other biologically significant pathways may be added in the future.
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Breast cancer overdiagnosis risk is difficult to estimate and varies significantly across current research. This research establishes a simulation approach to examine the relationship between breast cancer overdiagnosis and patient outcome and understand the impact that the range of breast cancer overdiagnosis rate estimates in the current literature has on patient outcomes. Overdiagnosis is represented in this study by a set of disease regression probabilities. Using microsimulation, we evaluate patient outcome, measured by number of mammograms and lifetime breast cancer mortality risk, as a function of treatment policy and regression probability. We use numerical experiments to evaluate treatment policies and disease regression probabilities, and we conclude through sensitivity analysis that treatment policy is a statistically significant factor for patient outcome and regression probability, or overdiagnosis rate, is only partially statistically significant for patient outcome.
Judging a Book by its Criticism: A Digital Analysis of the Professional and Community Driven Literary Criticism of the Ingeborg-Bachmann-Preis

You should not judge a book by its cover, but by its content. However, in reality many books are judged based on other criteria even before being read, when potential readers rely on book reviews or ratings to decide whether or not to read a specific book. How a book has been judged before may influence how it is judged by others. This literary criticism may originate from either professional or layperson critics. According to Beth Driscoll, two of the increasingly influential phenomena in modern publishing are “literary prizes and social media, both of which draw together participants from multiple areas of literary culture” (Driscoll, 2013, 103). In this article, we shall therefore examine the Ingeborg-Bachmann-Preis, a literary prize which receives a lot of attention in both the academic field and on social media. This prize is awarded during the Tage der deutschsprachigen Literatur (TDDL), an annual and multi-day literary festival. We manually annotated a corpus of TDDL-related Tweets, Instagram posts and Goodreads reviews, as well as the descriptions of the official jury discussions. We then performed a fine-grained aspect-based sentiment analysis (ABSA), which allows us to gain deeper insight in the content of the literary discourse surrounding the Bachmann-Preis and in the evaluative criteria used by both professional (jury discussions) and layperson critics (social media contributions). We argue that there are noticeable differences between the Twitter, Instagram, Goodreads and jury discourse surrounding the Ingeborg-Bachmann-Preis, as well as between the evaluative criteria used by professional and layperson critics. Our analysis will also demonstrate that, contrary to the common prejudice, layperson literary criticism is not necessarily less critical than professional criticism and does in fact concern itself with aesthetic principles, such as form, style etc., instead of solely assessing a literary text based on the judgement of the professional jury.
Digital Consumerism among Nepalese College Students: A Study of Online Shopping Behavior

Online shopping is a form of electronic commerce that allows consumers to purchase products or services directly from sellers over the Internet using a web browser. The main objective of this study is to explore the relationship between price, convenience, security, and online shopping behavior of students in Kathmandu. The research adopted the analytical research design. Four hundred students from different colleges in Kathmandu Valley were selected for this study. The convenience sampling method was used while selecting the respondents. The questionnaire survey was developed to collect primary data. The study adopted cross tab, independent t-test, and correlation to analyze the data. Convenience is the most preferable factor when selecting a product in online shopping. Price, convenience, and security are positively correlated with online shopping behavior. As per the result, the price highly correlates with online shopping behavior. Hence, online shopping companies must maintain the product's standard price to meet consumers' expectations. Online shopping companies also consider improving websites with solid security mechanisms for the convenience of online shopping to build up the company's image. Likewise, the firm should consider the preferable factors of online shopping for a better budget allocation for promoting their online business. Future researchers can study the online shopping behavior of the general public with a larger sample size.
Zero-shot classification of TNM staging for Japanese radiology report using ChatGPT at RR-TNM subtask of NTCIR-17 MedNLP-SC

We describe our submission to the RR-TNM subtask of the NTCIR-17 MedNLP-SC shared task. In the RR-TNM subtask, we developed our system for automatic extraction and classification of the TNM staging from Japanese radiology reports of lung cancers. In our system, zero-shot classification and prompt engineering were performed using ChatGPT and LangChain, respectively. According to the accuracies calculated by the organizers of the RR-TNM subtask, the accuracies of N and M factors in the TNM staging were higher in our submission than in the other submissions. These results indicate that our system with ChatGPT and LangChain may be promising.
Preparing students to meet their data: an evaluation of K-12 data science tools

Data science education has gained momentum in recent years. Along with the development of curricula to teach data science, the number and diversity of tools for introducing data science to learners are also multiplying. The tools used to teach data science play a central role in shaping the learning experience. Therefore, it is important to carefully choose which tools to use to introduce learners to data science. This article presents a systematic analysis of 30 data science tools that are, or designed to be, used in introductory data science education for K-12 students. The identi ﬁ ed tools list includes spreadsheets, visual analysis tools, and scripting environments. For each tool, we examine facets of its capabilities, interactions, educational support, and accessibility. For block-based programming tools, we also examine the data science functionalities available in that tool ’ s blocks. This paper advances our understanding of the current state of introductory data science environments and highlights opportunities for creating new tools to better prepare learners to navigate the data-rich world surrounding them.
Microgravity Decoupling in Torsion Pendulum for Enhanced Micro-Newton Thrust Measurement

To enhance the accuracy of micro-Newton thrust measurements via a torsion pendulum, addressing microgravity coupling effects caused by platform tilt and pendulum mass eccentricity is crucial. This study focuses on analyzing and minimizing these effects by alleviating reference surface tilt and calibrating the center of mass during thrust measurements. The study introduced analysis techniques and compensation measures. It first examined the impact of reference tilt and center of mass eccentricity on the stiffness and compliance of the torsion pendulum by reconstructing its dynamic model. Simscape Multibody was initially employed for numerical analysis to assess the dynamic coupling effects of the tilted pendulum. The results showed the influence of reference tilt on the stiffness and compliance of the torsion pendulum through simulation. An inverted pendulum was developed to amplify the platform’s tilt angle for microgravity drag-free control. Center of mass calibration can identify the gravity coupling caused by the center of mass position. Based on the displacement signal from the capacitive sensor located at the end of the inverted pendulum, which represents the platform’s tilt angle, the pendulum’s vibration at 0.1 mHz was reduced from 5.7 μm/Hz1/2 to 0.28 μm/Hz1/2 by adjusting the voltage of piezoelectric actuator. Finally, a new two-stage torsion pendulum structure was proposed to decouple the tilt coupling buried in both pitch and roll angle. The study utilized theoretical models, numerical analysis, and experimental testing to validate the analysis methods and compensation measures for microgravity coupling effects in torsion pendulums. This led to a reduction in low-frequency noise caused by ground vibrations and thermal strains, ultimately improving the micro-Newton thrust measurement accuracy of the torsion pendulum through the platform’s drag-free control.
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Thermal management of electronic devices has become an increasingly vital field of study with the rapid miniaturization of many key electrical components. With the significant improvement of semiconductor manufacturing and intensified focus on interconnects, electronic devices have decreased in size at an incredible rate. Decreasing spatial requirements is essential to improving device capabilities as the electronic system is able to incorporate more components. Currently, electronic systems are drastically limited by the capabilities of their cooling mechanisms. Smaller devices lead to large increases in the energy density of the system and require more powerful cooling systems to maintain proper component operating temperatures. The cooling systems, heat pipes, fans or vapor/liquid cooling, capable of high performance requirements are often bulky and rely on large energy inputs to remove extra thermal energy, leading to significant reduction in overall system efficiencies. Phase change materials, PCMs, offer an alternative approach to aid in thermal management. PCMs can absorb large amounts of energy, in the form of latent heat, when undergoing a phase transition. This passive cooling mechanism can be combined with conventional cooling systems to protect the system against temperature spikes, allowing the conventional components to be designed for average thermal load rather than peak load. This study focuses on the enhancement of Sorbitol, a sugar alcohol with a large latent heat (W/g). Many organic PCMs have poor thermal conductivity, an essential component to optimizing a passive cooling system. Previous research shows thermal conductivity and other thermal properties such as melting temperature and latent heat can be changed by altering the materials’ crystalline structure through nanoparticle inclusion. Sorbitol naturally has a polycrystalline structure, but it can be shown that dispersed nanoparticles can induce crystalline ordering within the host material’s structure. Particle size, type, concentration, and interaction chemistry will be altered in attempt to understand their effect on the thermal properties of Sorbitol. Changes in the composite’s structure will be evaluated using a variety of thermal, crystallographic, and mechanical characterization methods. This work covers the trends observed across the thermal and mechanical properties of significance with respect to the alterations in nanoparticle properties. Understanding the effects of nanoparticle inclusion on Sorbitol could lead to the development of property enhancement trends, crucial to optimizing Sorbitol as a PCM for electronic cooling system integration.
CHARACTERISATION AND ANALYSIS OF SUPERSONIC GAS JETS USING INTERFEROMETRIC MEASUREMENT METHODS ∗

Supersonic gas jets are useful tools in particle accelerators used in both scientific and medical applications. They can provide real-time, longitudinal and transverse beam profile measurements for charged particle beams in accelerators and are also being used as a plasma source in wakefield accelerators. For gas jets to be used effectively as beam profile monitors, the density profile of the jet must also be well-known. This can be calculated by measuring the phase shift produced by the gas jet inside a laser beam due to the difference in density between the gas and the surrounding vacuum environment from the Lorentz-Lorenz relation. Using a 532 nm laser with a gas jet backing pressure of 7 bar, multiple techniques for measuring gas jet profile and density will be compared and analysed; Mach-Zehnder and Nomarski interferometry. Multi-pass interferometry will also be discussed as a method of increasing the measurable phase shift making the technique suitable for lower density gas jets.
Abstract Argumentation and Answer Set Programming: Two Faces of Nelson’s Logic

Argumentation and Answer Set Programming: Two Faces of Nelson’s Logic Jorge Fandinno University of Nebraska at Omaha, jfandinno@unomaha.edu LUIS FARIÑAS DEL CERRO Follow this and additional works at: https://digitalcommons.unomaha.edu/compscifacpub Part of the Computer Sciences Commons Please take our feedback survey at: https://unomaha.az1. qualtrics.com/jfe/form/ SV_8cchtFmpDyGfBLE Recommended Citation Fandinno, Jorge and FARIÑAS DEL CERRO, LUIS, "Abstract Argumentation and Answer Set Programming: Two Faces of Nelson’s Logic" (2022). Computer Science Faculty Publications. 82. https://digitalcommons.unomaha.edu/compscifacpub/82 This Article is brought to you for free and open access by the Department of Computer Science at DigitalCommons@UNO. It has been accepted for inclusion in Computer Science Faculty Publications by an authorized administrator of DigitalCommons@UNO. For more information, please contact unodigitalcommons@unomaha.edu. TPLP : Page 1–24. c © The Author(s), 2022. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. doi:10.1017/S1471068422000114 1 Abstract Argumentation and Answer Set Programming: Two Faces of Nelson’s Logic∗Argumentation and Answer Set Programming: Two Faces of Nelson’s Logic∗ JORGE FANDINNO University of Nebraska Omaha, Omaha, NE, USA (e-mail: jfandinno@unomaha.edu) LUIS FARIÑAS DEL CERRO IRIT, Université de Toulouse, CNRS, Toulouse, France (e-mail: luis@irit.fr) submitted 18 December 2020; revised 21 December 2022; accepted 7 April 2022
Salt Weathering Hazards

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Design of a system for bioinformatics processing of metagenomic data

Advancements in acquiring, storing and processing information have led to a significant accumulation of large databases in the field of metagenomics—a branch of biology that deals with the study of genetic material directly recovered from environmental or clinical samples. The data collected from metagenomic experiments are massive and noisy, often containing fragmented information representing over 10,000 species. Processing and analyzing this data require software installed on supercomputers. In this paper, the authors present the design, development, and creation of a computational server system aimed at processing and analyzing bioinformatics data in metagenomics and 16S rRNA gene studies. They utilized the specialized software product Galaxy Europe for this purpose. The analysis was performed using the metagenomics-based method Targeted Amplicon Sequencing. The data was divided into three test collections in a special fasta file format. These collections were processed using the web-based Galaxy platform and two configuration variants on a high-performance cluster equipped with NVIDIA Tesla V100 32 GB GPU cards. The analysis process was optimized to reduce information processing time, and the parallel performance of the three different system configurations was investigated for the data used.
Logistic probability function: an analysis and modification from the perspective of reaction network theory

In this work we study some characteristics of growth functions of the logistic type. The standard logistic function and the 2-logistic growth function are solutions of ordinary differential equations derived from the perspective of reaction network theory. These solutions are compared in terms of their shape. We are interested in the new 2-logistic probability distribution and its characteristics. Using the tools of reaction network theory and numerical methods we derive some properties of this distribution.