Miracle-dz/UniFAR-FTUs huggingface dataset:
Persistent Inflammation and Nitric Oxide Dysregulation Are Transcriptomic Blueprints of Subglottic Stenosis

Subglottic stenosis (SGS) is a recurrent, obstructive, fibroinflammatory disease of the upper airway resulting in severe dyspnea, dysphonia, as well as other potentially fatal complications. Although aberrant inflammation and wound-healing are commonly associated with pathogenesis, the mechanism through which such processes occur and recur in affected patients remains poorly studied. Here we report that transcriptomic profiling of laryngotracheal regions from minimally-invasive mucosal swabs of SGS patients reveals a distinctively pro-inflammatory gene signature. Surprisingly, comparative genomics between SGS patients and mice with direct laryngotracheal injury suggest that SGS patients bear more resemblance to the acute than chronic phase of injury. Furthermore, functional and regulatory network analyses identify neutrophilic involvement through hyper-activation of NF-κB and its downstream inflammasome as a potential master regulator. Interestingly, nitric oxide synthesis was found to be downregulated in SGS patients compared to healthy controls. Thus, SGS represents a state of immunodeficiency whereby defective immune clearance triggers recurrent, long-lasting production of pro-inflammatory cytokines.
Different Effects of Biologics on Systemic Bone Loss Protection in Rheumatoid Arthritis: An Interim Analysis of a Three-Year Longitudinal Cohort Study

Objective To compare changes in bone mineral density (BMD) in rheumatoid arthritis (RA) patients receiving three-year conventional synthetic disease-modifying anti-rheumatic drugs (csDMARD), tumor necrosis factor-α inhibitors (TNFi), and abatacept. Methods Patients with RA were recruited from September 2014 to February 2021. Dual-energy X-ray absorptiometry was used to measure BMD at the femoral neck (FN), total hip (TH), and lumbar spine (L1-4) at enrollment and three years later. Changes in the BMD of each regimen group were analyzed. Multiple ordinary least squares regression was used with the dependent variables to develop a model to predict the change in BMD. Results A total of 752 participants were enrolled and 485 completed the three-year follow-up period. Of these, 375 (Group I), 84 (Group II), and 26 (Group III) participants received csDMARDs, TNFi, and abatacept therapy, respectively. Considering both type of therapy and completion of the follow-up period, participants were divided into groups A (csDMARDs, n = 104), B (TNFi, n = 52), and C (abatacept, n = 26). Compared to baseline, BMD decreased significantly at FN (p = 0.003) and L1-4 (p = 0.002) in Group A and at L1-4 (p = 0.005) in Group B, but remained stable at all sites in Group C. In terms of regression-adjusted percent change in BMD, there was a significant difference seen at all measured sites between group C compared to both groups A and B (+0.8%, -2.7%, -1.8% at FN; +0.5%, -1.1%, -1.0% at TH; +0.8%, -2.0%, -3.5% at L1-4, respectively; all p < 0.05). Anti-osteoporosis therapy had a BMD-preserving effect in RA. Conclusion Compared with csDMARDs and TNFi, abatacept may have a better BMD-preserving effect in RA. Anti-osteoporosis therapy can prevent systemic bone loss irrespective of RA therapy.
Aftershock: CEO Great Famine Experience and Stock Price Crash Risk

This study examines the effect of CEOs’ early-life traumatic experience on firm-specific stock price crash risk. Drawing on the idea of natural experiments, we take the Great Famine in China as an external traumatic event which cannot be selected or controlled by human. The analysis points out that compensation psychology and irrational defense psychology after the trauma of Great Famine are important factors that cause CEOs to hoard bad news. Based on a large sample of Chinese companies from 2007 to 2017, we find evidence that CEOs who experienced the Great Famine during early-life tend to hoard bad news, which result in higher stock price crash risk. The more severe and prolonged the Great Famine that the CEOs experienced, the greater the effect of this traumatic experience. CEOs decision-making power enhances the adverse effect of CEOs’ early-life traumatic experiences on crash risk. Findings of this study contributes to the literature by providing a new explanation for the stock price crash risk, which is of great significance for the sustained and healthy development of capital markets.
Exploring a Masked Language Model for Creative Text Transformation

We explore a masked-language model based on BERT for shifting the meaning of text towards a target theme. Content words in the original text are masked and the model provides a list of ﬁlling candidates, out of which one is selected based on its similarity to the theme and constraints regarding morphology and metre. Experimentation is performed with Portuguese song lyrics and trade-offs between grammaticality, semantics, form, and novelty are analysed. We conﬁrm that BERT is a useful tool for creative text transformation.
Syllable Neural Language Models for English Poem Generation

Automatic Poem Generation is an ambitious Natural Language Generation (NLG) problem. Models have to replicate a poem’s structure, rhyme and meter, while producing creative and emotional verses. The lack of abundant poetic corpora, especially for archaic poetry, is a serious limitation for the development of strong poem generators. In this paper, we propose a syllable neural language model for the English language, focusing on the generation of verses with the style of a target author: William Wordsworth. To alleviate the problem of limited available data, we exploit transfer learning. Furthermore, we bias the generation of verses according to a combination of different scoring functions based on meter, style and grammar in order to select lines more compliant with the author’s characteristics. The results of both quantitative and human evaluations show the effectiveness of our approach. In particular, human judges struggle to recognize real verses from the generated ones.
Evaluating Natural Language Descriptions Generated in a Workspace-Based Architecture

This paper concerns the evaluation of a workspace architecture for generating natural language descriptions, including methods for evaluating both its output and its own self-evaluation. Herein are details of preliminary results from evaluation of an early iteration of the architecture operating in the domain of weather. The domain is not typically seen as creative, but provides a simple testbed for the architecture and evaluation methodology. The program does not yet match humans in terms of ﬂuency of language, factual correctness, and how completely the input is described, but human judges did ﬁnd the program’s output easier to read than human generated texts. Planned improvements to the program also described in the paper will incorporate self-monitoring and better self-evaluation with the aim of producing descriptions that are more ﬂuently written and more accurate.
Automated System for Determining a Damage Class for Sections of a Wastewater Disposal Network

The purpose of the study is to provide rationale and describe the process of designing an automated system for determining a damage class for sections of a wastewater disposal network using one of the up-to-date algorithms of data mining. The current stage of development of society requires the introduction of mathematical methods and mining models and the latest developments in the field of IT technology, even in such a well-established industry as public utilities. The proposed automated system provides the user with the opportunity to distribute sections of the network by clusters with the determination of their centers with the subsequent prioritization of repair work. The paper proposes a new approach to determining a damage class for sections of a wastewater disposal network using clustering algorithms with the option of choosing one of two metrics (Manhattan distance and Euclidean metric). The software component implemented in the Java programming language with the use and within the operation of the system allows determining by a number of section’s criteria their affiliation with a certain class with the option of further ranking and prioritization of renovation work. The software is a web application which, on condition of good Internet connection, can be useful for professionals engaged in maintaining trouble-free operation of wastewater disposal networks at any time and at any location.
Inspiring Social Creativity in Children with CUBUS

Although creativity is an ability that can be developed if trained, most of the systems developed for creativity stimulation focused on individual interventions. This work presents the design, development, and evaluation of CUBUS, a digital tool developed to inspire social creativity in children through storytelling and emotionally expressive characters. Groups of children collaborate with the autonomous virtual characters of the digital tool to create a story together. Our main goal was to conduct an experimental study (n= 20 ) to investigate if the interaction between children and the autonomous emotionally expressive virtual characters present in CUBUS can stimulate social creativity during a storytelling activity. We measured the impact of the digital tool across several creativity domains: pre-and post-testing (questionnaire assessment), the creative process of children (behavior analysis), and the story created (creative outcome). Results showed that although children generated fewer storytelling ideas us-ing CUBUS, these ideas were deemed more original.
Weighted model counting with conditional weights for Bayesian networks

Weighted model counting (WMC) has emerged as the unifying inference mechanism across many (probabilistic) domains. Encoding an inference problem as an instance of WMC typically necessitates adding extra literals and clauses. This is partly so because the predominant deﬁnition of WMC assigns weights to models based on weights on literals, and this severely restricts what probability distributions can be represented. We develop a measure-theoretic perspective on WMC and pro-pose a way to encode conditional weights on literals analogously to conditional probabilities. This representation can be as succinct as standard WMC with weights on literals but can also expand as needed to represent probability distributions with less structure. To demonstrate the performance be-neﬁts of conditional weights over the addition of extra literals, we develop a new WMC encoding for Bayesian networks and adapt a state-of-the-art WMC algorithm ADDMC to the new format. Our experiments show that the new encoding signiﬁc-antly improves the performance of the algorithm on most benchmark instances.
CREA.blender: A GAN Based Casual Creator for Creativity Assessment

In this technical demonstration paper we document the use of a Generative Adversarial Network (GAN) based casual creator game for systematic assessment of human creativity. We discuss some of the challenges in designing GAN-based casual creators, speciﬁcally focusing on how to identify and select appropriate parts of the latent vector space - images, in our case.
Revision of Army Technical Manual 5-1300/NAVFAC P-397/AFR 88-22,“Structures to Resist the Effects of Accidental Explosions”

In March 2003, the Department of Defense Explosives Safety Board (DDESB) established a technical working group to update the tri-service blast design manual, Structures to Resist the Effects of Accidental Explosions , Army Technical Manual 5-1300/Navy Publication NAVFAC P-397/Air Force Manual (AFM) 88-22 (TM 5-1300) (Department of the Air Force, 1990). The revision will be written to retain its open distribution, thereby providing an invaluable source of information to both government and private sector engineers. When first published in 1969, TM 5-1300 (Department of the Air Force, 1969) represented the state-of-the-art in the analysis and design of blast resistant structures. Based primarily on explosive tests of reinforced concrete walls, the manual provided a comprehensive introduction to the blast design process including load calculation, dynamic analysis, structural design, and detailing. Revision 1, published in 1990, updated and expanded the manual to include structural steel, masonry, and other materials. Since 1990, the increased computational capacity of mainframe and personal computers has revolutionized both conventional and blast resistant design. Armed with this powerful research tool, knowledge has advanced rapidly, necessitating not only update of TM 5-1300's present content but also added coverage. New sections are planned on innovative, cost effective materials; applicability and limitations of blast design software; and retrofit of existing structures. Constructability guidance will be expanded to aid engineers in reducing the cost of often complex, blast resistant structures. This paper summarizes the working group's activities to date and future plans. Emphasis is given to anticipated revisions and additions to the manual.
A Deep Learning Pipeline for the Synthesis of Graphic Novels

In this paper, we present what is to the best of our knowledge, the ﬁrst deep learning pipeline to produce a synthetic graphic novel. Our method can synthe-size from scratch engaging sequences of graphic novel pages, focusing on the Manga genre. To achieve this, we extract images and text from around 670 thousand Manga pages, which we use separately in order to train state-of-the-art generative architectures, such as GPT-2 for text generation and StyleGAN2 for image synthesis. Using these as sources of synthetic content, we develop a set of algorithmic aesthetic rules in order to bring together complete and continuous Manga pages.
Performance analysis of mixed communication architectures: bus and network-on-chip

System on Chip performances in terms of speed and power dissipation are becoming dominated by communication between the cores. The communication architectures are usually based on bus or Network on Chip. Bus-based on chip communication architectures are simple and flexible. Network on Chip is a distributed communication architecture allowing to overcome the bus bottleneck occurring when the number of cores connected is high. In this work we present the integration in a SystemC NoC library of a new library for creating and simulating master and slave devices of the AMBA AHB bus. The simulation environment has been used to evaluate the performance in terms of communication throughput and delay in different communication architectures: AMBA AHB bus, NoC and mixed.
A Systematic Approach for the definition of countermeasures in industrial IoT: An Automotive Case

Inter-dependencies in critical industrial systems pose huge security challenges, which are tightly linked to the problems of interoperability and trustworthiness within and among those systems. In this paper, we try to establish the interconnection between these system properties in a way that allows the establishment of one property to positively affect and facilitate the establishment of the other. For that purpose, we design a methodology based on standardized and well-known models and frameworks, which are upgraded as needed and integrated into a single generic framework. Although this approach is meant to primarily help the security experts and the architects in their design practices, it also aims to facilitate the dialogue on important (cyber and physical) security issues among all relevant levels in an industrial IoT organization. The formal value and the practical applicability of the methodology are also demonstrated through a use case in the domain of road transportation and automotive industry.
Composition, Performance and Evaluation: A Dance Education Framework for AI Systems

Most AI-based dance generation methods consider dance as a selection of movements. While these methods aim for realistic outputs and synchronization with music, domain-speciﬁc knowledge related to dance is often not incorporated in these models. This results in outputs that are far from what the dance community considers as high quality dances. Therefore we present CoPE, a dance education framework for AI systems with three key components: Composition, Performance, and Evaluation. By analyzing nowadays dance education, we suggest how to incorporate principles from the dance community into AI-based dance generation systems by aiming for more realistic pieces of art.
Software Design Patterns of Computational Creativity: A Systematic Mapping Study

Software design patterns can be helpful in describing the architecture of a system. Our objective is to obtain a broad overview of the current state-of-the-art of software design patterns used in Computational Creative (CC) systems. We conducted a systematic mapping study using manual and snowballing search techniques. Only 7 primary studies are identiﬁed in the CC community that explicitly mention the use of design patterns. Within these primary studies, 14 de-sign patterns are mentioned, 12 of which are user-interaction design patterns rather than software design patterns describing the architecture of the system. The small number of primary studies indicates a gap in CC literature regarding the use of software design patterns in CC systems and motivates the need for research to identify software design patterns speciﬁc to CC systems.
Mobile Technology in Higher Education: An Extended Technology Mobile Technology in Higher Education: An Extended Technology Acceptance Perspective Acceptance Perspective

There is a lack of research that provides institutions with information on educators’ acceptance of mobile technology in higher education within the United States. This study utilized the Chen et al. (2013) extended technology acceptance model, that extended the original Davis (1989) TAM. In this research study, Chen et al. (2013) survey instrument provided the necessary tool to collect data from educators in higher education within the United States before COVID-19. The results showed statistical significance exists in relationships across the assessed factors of perceived usefulness, perceived ease of use, perceived attitude toward use, and behavioral intention, which contribute to the acceptance of mobile technology in higher education. The study implies that institutions face a challenging task to understand the technology acceptance of educators as they incorporate the use of mobile technology to support their work and improve instructional practices.
Grid Connected Power Supplies for Particle Accelerator Magnets

Power supplies play a large role in particle accelerators, for creating, accelerating, steering and shaping the beam. This thesis covers the power supplies for steering and shaping the beam, namely the magnet power supplies. These power supplies have a special set of requirements regarding output current stability and accuracy, typically allowed drift over 8 hours is down to 10 parts per million of the maximum output current. After an introduction to the topic several topologies are discussed and compared for different power ranges. Hereafter a topology is proposed. A converter based on this topology is constructed using a single power module on the grid side of the transformer, consisting of a boost rectifier and a dual half-bridge isolated DC/DC converter. It is shown that it is possible to create a power supply using a single module and that this approach can lead to improved layout and smaller converter size. A high efficiency converter based on Silicon Carbide switching devices is also presented exhibiting above 96 % efficiency for the entire power range. Finally reliability issues are considered as the reliability of a particle accelerator supply is of utmost importance. Particle accelerators requires large up time and many power supplies, magnets etc. must function in parallel for the particle accelerator to operate. A method for increasing the reliability of the proposed converter is shown. This is done by creating a lifetime model for the power module converter together with a mission profile.
Spot Weld Property Testing and Simulation Modeling with Failure Criteria

Spot welds have been widely used in vehicle body assembly, and can affect the performance of a vehicle. This paper studies the mechanical properties of spot weld and utilizes those properties in the numerical simulation to predict the failure behavior of a spot-welded component. The mechanical properties of a spot weld are not easy to obtain due to the size of spot weld, and the non-uniformity around the weld zone. The study utilized the hardness measured on and around the spot weld, heat treated samples with the same hardness, and then performed the tensile tests on those heat treated specimens to obtain the corresponding mechanical properties. With those testing data, the numerical simulation model was then created based on the properties obtained. A single-spot-welded part was used to correlate the results of hardware tests and numerical simulation. The study compared the results of three different modeling schemes with those of the hardware test. The results showed that the simulation model with material properties assigned to their corresponding region provided better correlation with the hardware testing results.
Overview of hydrogenerator stator winding monitoring

Stator winding failure due to insulation system deterioration is an important cause of hydrogenerator forced outages. Furthermore, if the deterioration is not found at an early stage, premature stator rewinding may be required, at a cost that far exceeds the cost of many maintenance procedures, such as rewedging and cleaning. Several online monitors are now available which detect stator winding deterioration. This paper reviews the need for online monitoring and describes ozone, temperature and partial discharge monitoring systems.
Which Service Attributes Sway Internet Service Providers? Analysis Through Triangulation Approach

Internet service providing industry is considered a mainstay for all types of organizations all over the world. In order to be competitive, internet service providers (ISPs) need to realize that all service quality attributes do not carry the same value in customers’ eyes. Therefore, the present study proposes a rationally appealing methodological framework for prioritizing attributes of the SERVQUAL model without restricting them to their dimensions. The responses on 22 attributes of service quality collected from 401 internet users were processed through a triangulation approach comprising three ranking methods: Relative to an Identified Distribution Integral Transformation (RIDIT), Grey Relational Analysis (GRA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). A correlational study of these results was also computed using Spearman’s rank-order correlation coefficient, which proved positive. The consistent outcomes reveal a definite set of users’ priorities for the quality attributes of internet services, and it denies the general thought that the rate of internet service providers is the primary concern of customers. The findings uniquely contribute by highlighting important facets of service quality from customers’ viewpoint. The study would benefit ISPs to empathize customers’ needs corresponding to essential attributes. In this way, they would be able to rationalize the budget for top-ranked features, and redesign operational strategies accordingly.