Miracle-dz/UniFAR-FTUs huggingface dataset:
Vocal modulation in human mating and competition

The human voice is dynamic, and people modulate their voices across different social interactions. This article presents a review of the literature examining natural vocal modulation in social contexts relevant to human mating and intrasexual competition. Altering acoustic parameters during speech, particularly pitch, in response to mating and competitive contexts can influence social perception and indicate certain qualities of the speaker. For instance, a lowered voice pitch is often used to exert dominance, display status and compete with rivals. Changes in voice can also serve as a salient medium for signalling a person's attraction to another, and there is evidence to support the notion that attraction and/or romantic interest can be distinguished through vocal tones alone. Individuals can purposely change their vocal behaviour in attempt to sound more attractive and to facilitate courtship success. Several findings also point to the effectiveness of vocal change as a mechanism for communicating relationship status. As future studies continue to explore vocal modulation in the arena of human mating, we will gain a better understanding of how and why vocal modulation varies across social contexts and its impact on receiver psychology. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’.
GloSAT Historical Measurement Table Dataset: Enhanced Table Structure Recognition Annotation for Downstream Historical Data Rescue

Understanding and extracting tables from documents is a research problem that has been studied for decades. Table structure recognition is the labelling of components within a detected table, which can be detected automatically or manually provided. This paper presents the GloSAT historical measurement table dataset designed to train table structure recognition models for use in downstream historical data rescue applications. The dataset contains 500 scanned and manually annotated images of pages from meteorological measurement logbooks. We enhance standard full table and individual cell annotations by adding additional annotations for headings, headers, and table bodies. We also provide annotations for coarse segmentation cells consisting of multiple data cells logically grouped by ruling lines of ink or whitespace in the table, which often represent data cells that are semantically grouped. Our dataset annotations are provided in VOC2007 and ICDAR-2019 Competition on Table Detection and Recognition (cTDaR-19) XML formats, and our dataset can easily be aggregated with the cTDaR-19 dataset. We report results running a series of benchmark algorithms on our new dataset, concluding that post-processing is very important for performance, and that page style is not as significant a feature as table type on model performance.
OXIDATIVE CHANGES AND COGNITIVE FUNCTION DECLINE IN AGING RATS

Objective: This study aims to show that impairment of cognitive function occurred during aging is related to increased oxidative stress. Methods: A total of 36 Sprague Dawley rats were divided into four groups: Young (3 months), middle (14 months), and old age groups (18 and 23 months). Rats were killed and blood was collected for the measurement of oxidative stress which includes deoxyribonucleic acid (DNA) damage and lipid peroxidation (malondialdehyde [MDA] levels). Cognitive function of rats was measured through open-field experiments, Morris water maze (MWM), and object identification. Results: Increased DNA damage and MDA levels were found in middle age and old rats compared to young rats (3 months old, p<0.05). There was an increase in anxiety with age as indicated by the increased production of fecal boli and decreased activity of grooming and rearing. For the navigation test, older rats took a long time to search for the hidden platform compared to young rats. In the probe test (spatial memory test 24 h after the last training), the middle- and old-age groups spent less time at the quadrant compared to the young age group. Conclusion: There is a decline in cognitive function with increased oxidative stress in aging rats.
20/20 in 2020?: Refractive vision, 45, and white supremacy

ABSTRACT To examine events leading up to and occurring in 2020, we adopt vision, along with refractive diseases and disorders, as a metaphorical framework. Heuristically, a vision metaphor enables us to make sense of and assess acute events that marked the election season through obstructions that impinge on vision. We identify competing visions of America/Amerikkka, which facilitate explicating the nation’s vision and national vision.
Sustainable early literacy outcomes for young children of poverty: Influences of attendance, social competence, and problem behaviour

This study examined the role of children’s early school attendance and social competency skills in their early literacy development. Participants were 286 African American pre-schoolers from low-income homes enrolled in Head Start classrooms in the Unites States of America (mean age = 44.4 months, SD = 6.92 months; boys = 156). We gathered data on their program attendance, social competence, and early literacy skills. Hierarchical multiple regression analyses indicated children’s attendance predicted the pre-schoolers’ early code-related reading measures, while the children’s positive social competence predicted both code-related learning and story comprehension. Positive social competence was a more prominent predictor of early literacy outcomes than children’s challenging behaviour. Findings highlight attendance, literacy, and social-emotional factors important to evidence-based practices aimed at improving and sustaining school readiness among young children of poverty.
Do comment letters from the stock exchanges have governance effect on R&D manipulation?

ABSTRACT As an important reform of supervision, the comment letter mechanism adopted by the Shanghai Stock Exchange and the Shenzhen Stock Exchange has been paid much attention by regulators and academics. Taking Chinese A-share listed firms from 2015 to 2018 as our samples, this paper investigates the impact of comment letters on companies’ R&D manipulation. Our empirical results show that R&D-related comment letters can effectively reduce companies’ R&D manipulation. Further tests show that the more timely the comment letters and responses letters, or the stronger the intensity of comment letters, the higher the governance effect of comment letters on R&D manipulations. Specifically, when R&D-related comment letters involve the questions of R&D manipulation directly, the governance effect is pronounced. The governance effect of R&D-related comment letters is stronger for firms which are punished following the receipt of comment letters or firms which are paid more market attention. Finally, from the perspective of motivations of R&D manipulation, the governance effect of R&D-related comment letters is more pronounced in samples with strong tax-reducing incentives. After employing PSM-DID to control endogeneity, the main results are still held. To sum up, our findings enrich the growing body of research on the effectiveness of the comment letter mechanism and provide important implications for improving the resources allocation in R&D.
Ontology-based Validation of Enterprise Architecture Principles in Enterprise Models

Enterprises use Enterprise Architecture Principles as a guiding set of rules to provide a basis for decision making. These principles are described using natural language and are not machine-interpretable. The validation of these principles in models is a complex and time-consuming task. The goal of this research is to help humans in this review. Annotating enterprise architecture models with an enterprise ontology and representing architecture principles as rules, it is possible to automatically check architecture principles. The proposed approach is to combine both the domain knowledge and the modeling language knowledge to reason about models, allowing the automatic check of architecture principles.
Identifying Top-k Players in Cooperative Games via Shapley Bandits

The usefulness of cooperative game theory and key concepts like the Shapley value, which measures the contribution of individual players to the overall performance of a coalition, has been demonstrated in various applications. Due to the computational effort growing exponentially with the number of participants in a game, several methods have been proposed to approximate Shapley values. Yet, in many applications, only the order of players according to their Shapley values is important, or maybe the set of the 𝑘 best players, but not the values themselves. In this paper, we consider the problem of identifying the 𝑘 players in a cooperative game with the highest Shapley values and denote it as the Top-𝑘 Shapley problem. By viewing the marginal contributions of a player as a random variable, we establish a connection between cooperative games and multi-armed bandits, which in turn allows us to reduce Top-𝑘 Shapley to the multiple arms identification problem. We call the resulting bandits problem Shapley bandits . Besides adopting existing algorithms for multiple arms identifications, we propose the Border Uncertainty Sampling algorithm (BUS) and provide empirical evidence for its superiority over state-of-the-art algorithms.
Predicting Canonization: Comparing Canonization Scores Based on Text-Extrinsic and -Intrinsic Features

The majority of literary texts ever written are hardly known, read, or studied today, and belong to the so-called “Great Unread”. Theories of canonization predominantly focus on sociocultural processes of selection which culminate in the formation of a canon, but say little about how the texts themselves contribute to canonization. In this paper, we propose an operationalization for canonization, which is then used to build a classifier that predicts a canonization score for a text by considering text-intrinsic features only. Working on a historical corpus of English and German texts, which includes both canonical and “unread” works, the results show that a canonization score based on text-inherent features has weak correlations with a canonization score based on text-extrinsic features.
Consent Withdrawal Processes in Information Systems

In May 2018 ‘ consent ‘ to the processing of Personal Identifiable Information (PII) was enshrined in legislation in Europe through the enactment of the General Data Protection Regulation (GDPR) [15] placing new demands on Information Systems (IS) for the management of consent withdrawal. This research proposes to identify the relationships between the underlying technology, organization and environment variables for Consent Withdrawal Management (CWM) in IS. This will be achieved through several case studies with consent management practitioners, using qualitative methods, process model analyses, and evaluation. The resulting research output will be a reference process model artefact and methodology that can be utilized in approaches to designing, deploying or improving information systems for the consent withdrawal requirements of GDPR.
An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm and RWT

In this paper a new approach for enhancement of satellite image, which is based on AHE-RWT with SVD and PSO-CS algorithm for quality improvement of the low brightness satellite images. The satellite image is corrupted due to noise, so removing of noise is necessary from the images for better visualization. The input image is first applied for enhancement by using Adaptive Histogram Equalization (AHE) and the image is decomposed into the four sub band through the redundant wavelet transform (RWT). Optimization of each sub band of RWT is done by using cuckoo search algorithm and LL threshold sub band of the image is obtained by using singular value decomposition, finally enhanced image is reconstructed by applying inverse redundant wavelet transform (IRWT). The Particular gray scale information of the satellite image is employed by singular value decomposition (SVD). The result of proposed method is shown in terms resolution, and mean deviation over state of the art and conventional techniques.
Modelling the Alignment Between Agile Application Development and Business Strategies

Enterprise application software (EAS) needs to be aligned with the long-term goals of the organization to fully support business operations. Agile software development management tools like Atlassian “Jira” do not ensure required integrity between the strategic business objectives and lower-level items (themes, initiatives, epics, user stories, tasks, etc.). The aim of the paper is to describe a model-driven approach of Agile software tools enhancement with integrity checking functionality. The complexity of the problem lies in transforming the declared business strategies into well-defined structures suitable for model-driven development methods. The first task is mapping required business strategies to well-defined application design models using MODAF concepts and products. The content of Agile concepts is defined using the concept of capability and related MODAF models. In the next step, the interactions between the concepts in the dynamic Agile hierarchy are formalized using management transaction (MT) concept. The advantage of our approach is the usage of well-defined frameworks to identify the content of Agile concepts and their interactions in the application development to ensure alignment. This is proved by providing an example of improved usability of “Jira” concepts and Agile software management hierarchy.
Leveraging Context-Aware Recommender Systems for Improving Personal Knowledge Assistants by Introducing Contextual States

During the last decades, recommender systems have played a remarkable role in putting one step further toward making content platforms more intelligent in a wide variety of domains ranging from music and movies to books and documents. Notwithstanding the various applications of recommender systems, not many contributions have been made regarding their potential capabilities in the domain of personal knowledge management. Hence, it has been tried in this study to shed new light on an innovative application of recommender systems to improve personal knowledge assistants by making them capable of providing knowledge workers with useful information through every single situation during their daily work. This paper provides a comprehensive research tree involving the key information about state of the art approaches with a focus on the three most relevant categories to this research including knowledge-based, sequential, and session-based recommender systems. Furthermore, the idea of the contextual states is introduced as the first step of a promising direction toward collecting the required multi-dimensional information for making such helpful recommendations.
Enterprise Engineering for Business Opportunity Recognition - A Design Science Approach

: Recognizing business opportunities in a timely and accurate way is crucial for business operation today. Due to steadily improving technologies in almost all areas relevant for organizations, organizational actors need multifaceted support when digital transformation processes are instantiated, targeting technology utilization for business opportunities. Although initial triggers enable a quick start of transformation processes, requirements evolve over time whenever stakeholders adopt novel organizational practices and technologies to achieve business objectives according to recognized opportunities. Consequently, requirements need to be refined by the time of emergence, and handled step-by-step to implement respective digital transformation steps. For structuring this socio-technical, and thus, complex endeavor, we suggest and introduce a de-sign science approach for methodology development. The initial development step has its focus on relevant knowledge items and relations guiding organizational actors when elaborating on digital transformation processes. Streamlining technology, technical and organizational issues when recognizing transformation potential facilitates the exploration of corresponding business practices.
Autistic Traits and Attention-Deficit Hyperactivity Disorder Symptoms Associated With Greater Pain Interference and Depression, and Reduced Health-Related Quality of Life in Children With Chronic Pain

Previous research indicates elevated levels of clinically significant traits and symptoms of autism spectrum disorder and attention-deficit hyperactivity disorder (ADHD) in children with chronic pain, but associations with functioning and depression are yet unclear. The current study examined the relationships of autistic traits and ADHD symptoms with pain interference, depression, and health-related quality of life, as well as the mediating roles of insomnia and psychological inflexibility, in children with chronic pain (n = 146, 8–17 years, 102 girls) presenting at a tertiary pain clinic. Children completed measures of pain intensity, depression, pain interference, health-related quality of life, insomnia, and psychological inflexibility. Parents (n = 146, 111 mothers) completed measures to assess autistic traits and ADHD symptoms in their children. Children with clinically significant autistic traits and ADHD symptoms presented with significantly higher levels of depressive symptoms and pain interference, and significantly lower health-related quality of life, than did the other children. Autistic traits and ADHD symptoms contributed significantly to the prediction of pain interference and depressive symptoms, as well as health-related quality of life. Psychological inflexibility mediated the relationships between ADHD symptoms and autistic traits on the one hand and depression, pain interference, and health-related quality of life on the other, while insomnia mediated the relationships between ADHD symptoms and depression, pain interference, and health-related quality of life. All analyses were adjusted for demographics and pain intensity. Results suggest the utility of screening for neurodevelopmental disorders in children with chronic pain. Furthermore, the findings may indicate insomnia and skills related to psychological flexibility as potential treatment targets in interventions aiming at improving functioning and health-related quality of life in children with chronic pain and co-occurring symptoms of neurodevelopmental disorders.
A Call to Expand Avian Vocal Development Research

Birds are our best models to understand vocal learning – a vocal production ability guided by auditory feedback, which includes human language. Among all vocal learners, songbirds have the most diverse life histories, and some aspects of their vocal learning ability are well-known, such as the neural substrates and vocal control centers, through vocal development studies. Currently, species are classified as either vocal learners or non-learners, and a key difference between the two is the development period, extended in learners, but short in non-learners. But this clear dichotomy has been challenged by the vocal learning continuum hypothesis. One way to address this challenge is to examine both learners and canonical non-learners and determine whether their vocal development is dichotomous or falls along a continuum. However, when we examined the existing empirical data we found that surprisingly few species have their vocal development periods documented. Furthermore, we identified multiple biases within previous vocal development studies in birds, including an extremely narrow focus on (1) a few model species, (2) oscines, (3) males, and (4) songs. Consequently, these biases may have led to an incomplete and possibly erroneous conclusions regarding the nature of the relationships between vocal development patterns and vocal learning ability. Diversifying vocal development studies to include a broader range of taxa is urgently needed to advance the field of vocal learning and examine how vocal development patterns might inform our understanding of vocal learning.
Mycobacterium tuberculosis and Paracoccidioides brasiliensis Formation and Treatment of Mixed Biofilm In Vitro

Co-infection of Mycobacterium tuberculosis and Paracoccidioides brasiliensis, present in 20% in Latin America, is a public health problem due to a lack of adequate diagnosis. These microorganisms are capable of forming biofilms, mainly in immunocompromised patients, which can lead to death due to the lack of effective treatment for both diseases. The present research aims to show for the first time the formation of mixed biofilms of M. tuberculosis and P. brasiliensis (Pb18) in vitro, as well as to evaluate the action of 3’hydroxychalcone (3’chalc) -loaded nanoemulsion (NE) (NE3’chalc) against monospecies and mixed biofilms, the formation of mixed biofilms of M. tuberculosis H37Rv (ATCC 27294), 40Rv (clinical strains) and P. brasiliensis (Pb18) (ATCC 32069), and the first condition of formation (H37Rv +Pb18) and (40Rv + Pb18) and second condition of formation (Pb18 + H37Rv) with 45 days of total formation time under both conditions. The results of mixed biofilms (H37Rv + Pb18) and (40Rv + Pb18), showed an organized network of M. tuberculosis bacilli in which P. brasiliensis yeasts are connected with a highly extracellular polysaccharide matrix. The (Pb18 + H37Rv) showed a dense biofilm with an apparent predominance of P. brasiliensis and fragments of M. tuberculosis. PCR assays confirmed the presence of the microorganisms involved in this formation. The characterization of NE and NE3’chalc displayed sizes from 145.00 ± 1.05 and 151.25 ± 0.60, a polydispersity index (PDI) from 0.20± 0.01 to 0.16± 0.01, and zeta potential -58.20 ± 0.92 mV and -56.10 ± 0.71 mV, respectively. The atomic force microscopy (AFM) results showed lamellar structures characteristic of NE. The minimum inhibitory concentration (MIC) values of 3’hidroxychalcone (3’chalc) range from 0.97- 7.8 µg/mL and NE3’chalc from 0.24 - 3.9 µg/mL improved the antibacterial activity when compared with 3’chalc-free, no cytotoxicity. Antibiofilm assays proved the efficacy of 3’chalc-free incorporation in NE. These findings contribute to a greater understanding of the formation of M. tuberculosis and P. brasiliensis in the mixed biofilm. In addition, the findings present a new possible NE3’chalc treatment alternative for the mixed biofilms of these microorganisms, with a high degree of relevance due to the lack of other treatments for these comorbidities.