Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting stock price and spread movements from news

—We explore several ways of using news articles and ﬁnancial data to train neural network machine learning models to predict shock events in high-frequency market data, and aggregated shock episodes. We investigate the use of price movements in this context, and separately at a daily interval as well. We describe in detail how training sets are created from our data sources and how our machine learning models are trained. We ﬁnd that pairing company-related news text with events or movements in ﬁnancial time series proves less straight-forward than the literature would indicate. We discuss possible reasons for negative results, especially relating to the combination of minute-level news and millisecond-level market data.
A Tale of Two Virtual Communities: A comparative analysis of culture and discourse in two online programming communities

Software programming is increasingly becoming a collaborative and community driven effort, with online discussions becoming vital resources for learning and knowledge sharing. This study explores the differences in the discourse patterns of two popular online programming communities and provides insights into the type of community practices and learning outcomes these collectives support and scaffold. A three step content analysis framework is presented that employs a mixture of automated text processing techniques and qualitative methods on a representative sample of 8639 and 6126 contributions from Stack Overﬂow and r/Askprogramming respectively. Results indicate differences between communities emerge in the scope of topics and the nature of responses the community provides. While r/Askprogramming has a more community centric, interpersonal approach and provides a space for sharing and supporting needs beyond knowledge sharing and factual learning, Stack Overﬂow takes a more task focused, knowledge centric approach. These ﬁndings suggest key normative structures that regulate patterns of collaboration and deliberation, which may have long term design implications for structuring and sustaining informal learning initiatives that nurture and promote technical skill development and enhancement.
High-Performance Detection of Corneal Ulceration Using Image Classification with Convolutional Neural Networks

Corneal Ulcer, also known as keratitis, represents the most frequently appearing symptom among corneal diseases, the second leading cause of ocular morbidity worldwide. Consequences such as irreversible eyesight damage or blindness require an innovative approach that enables a distinction to be made between patterns of different ulcer stages to lower the global burden of visual disability. This paper describes a Convolutional Neural Network-based image classification approach that allows the identification of different types of Corneal Ulcers based on fluorescein staining images. With a balanced accuracy of 92.73 percent, our results set a benchmark in distinguishing between general ulcer patterns. Our proposed method is robust against light reflections and allows automated extraction of meaningful features, manifesting a strong practical and theoretical relevance. By identifying Corneal Ulcers at an early stage, we aid reduction of aggravation by preventively applying and consequently tracking the efficacy of adapted medical treatment, which contributes to IT-based healthcare.
Immersive Storytelling for Information Security Awareness Training in Virtual Reality

Due to the central role of the human factor in information security, the need for information security awareness (ISA) is constantly increasing. In order to maintain a high level of ISA, trainings have to be carried out frequently to ensure sustainability. Since education via virtual reality (VR) has led to a sustainable learning effect in other fields, we evaluated the use of VR for ISA trainings. Moreover, we combined our VR training with immersive storytelling. For the evaluation we used two sets of participants. The first used a traditional e-Learning method to answer the questionnaire. The second used our VR training. After one week we repeated the questionnaires. The results showed that the VR group could achieve higher scores than the noVR group. Moreover, the VR group achieved even higher scores after one week which might be due to the sustained learning effect from the VR training.
Human-AI Collaboration in Healthcare: A Review and Research Agenda

Advances in Artificial Intelligence (AI) have led to the rise of human-AI collaboration. In healthcare, such collaboration could mitigate the shortage of qualified healthcare workers, assist overworked medical professionals, and improve the quality of healthcare. However, many challenges remain, such as investigating biases in clinical decision-making, the lack of trust in AI and adoption issues. While there is a growing number of studies on the topic, they are in disparate fields, and we lack a summary understanding of this research. To address this issue, this study conducts a literature review to examine prior research, identify gaps, and propose future research directions. Our findings indicate that there are limited studies about the evolving and interactive collaboration process in healthcare, the complementarity of humans and AI, the adoption and perception of AI, and the longterm impact on individuals and healthcare organizations. Additionally, more theory-driven research is needed to inform the design, implementation, and use of collaborative AI for healthcare and to realize its benefits.
The effects of random bond breaking on diffusion limited cluster–cluster aggregation

The effects of random bond breaking on cluster–cluster aggregation have been investigated using both 2d and 3d simulations. A combination of random bond breaking with the normal cluster–cluster aggregation process produces structures which are more compact on short length scales and contain many loops. However, the fractal dimensionality of the aggregates is increased only slightly, if at all, by random bond breaking. Fast bond breaking rates have the largest effect on short length scale structure, but the effect on the structure at larger length scales is quite small. Fast bond breaking leads to the formation of many small loops but intermediate and slow bond breaking rates lead to the formation of larger loops.
Vulnerable Populations in Prosocial Crowdfunding: Does the Framing Matter for Female and Rural Entrepreneurs?

Prosocial crowdfunding was originally conceived as a financial mechanism to assist vulnerable unbanked populations, typically excluded from formal financial markets. It subsequently grew into a billiondollar scheme in a multi-billion-dollar crowdfunding industry. However, recent evidence claims prosocial crowdfunding may be shifting away from its goal to support the poor and underserved. Drawing on a composite social responsibility and framing theory framework, we examine the role that vulnerability plays in successfully raising funds in a prosocial crowdfunding context. We conduct multilevel logistic regressions on a sample of microloans allocated to 105,727 ventures in 64 countries. Our results indicate that applying for funds through a field partner which caters to vulnerable populations may in fact have a negative effect on the entrepreneur’s request to be fully funded. Notwithstanding, framing the entrepreneur as being female or rural as key characteristics of individual vulnerability increases the project’s likelihood to be fully funded.
Modeling aggregate human mobility patterns in cities based on the spatial distribution of local infrastructure

Understanding human mobility patterns in urban areas is key to solving a wide range of socio-technical problems at the human-infrastructure interface. Extending the intervening opportunities concept, we showcase a data-driven, network-based model that reproduces aggregate mobility patterns in cities. Using this model, we create a digital replication of daily travel across different trip purposes in 5 U.S. metropolitan areas and compare results against publicly available reference data. We ﬁnd that our proposed model explains a large fraction of the variation in mean and median travel distance across the 5 cities. In particular, it accurately captures the effect of density on aggregate travel patterns. These ﬁndings add to evidence that human mobility patterns are strongly governed by the structure of the built environment. We discuss implications for the ongoing transformation of cities and for developing more sophisticated models that replicate human behavior based on crowd-sourced, spatio-temporal data streams.
Upgrading Products based on Existing Dominant Competitors

In the Industry 4.0 era, manufacturers compete to produce better products that are expected to satisfy a larger number of customers. We propose a recommendation system for upgrading products considering user preferences. This approach is based on the dominating regions of dominant competitors. The dominating region represents the estimation of the number of potential customers. However, examining overlapped dominating regions for a high dimensional space is NP-hard. We propose a novel method named TDRDFS which constructs a Dominant Graph of Intersection skyline points (DGI) for modeling the dominating regions. Our experiments show that TDRDFS significantly reduces computation. Based on our approach, product vendors are able to determine the strategy of upgrading products easily.
Performance Measurement in Scaled Agile Organizations

Performance metrics are a key tool for organizations to direct and motivate their members toward desired outcomes. Despite their central role also in Agile development, little is known about how Agile organizations set performance objectives and metrics in practice and balance between business and software engineering goals. In particular, there is a knowledge gap regarding performance measurement and its challenges in scaled Agile organizations. This paper applies an exploratory case study method to examine performance objectives and metrics in two business units of a scaled Agile organization and suggests a framework for selecting and structuring performance objectives within them. We offer five performance measurement dimensions that can be applied to provide guidance for scaled Agile organizations in selecting and prioritizing performance objectives.
WAVELENGTH IDENTIFICATION AND DIFFUSE REFLECTANCE ESTIMATION FOR SURFACE AND PROFILE SOIL PROPERTIES

Optical diffuse reflectance spectroscopy (DRS) has been used to estimate soil physical and chemical properties, but much of the previous work has been limited to surface soils or to samples obtained from a restricted geographic area. Our objectives in this research were: (1) to assess the accuracy of DRS for estimating variation in several important surface and profile soil properties across a wide range of soils from the U.S. Corn Belt, and (2) to determine the wavelength ranges and/or specific wavelengths that should be included in a DRS soil property sensor. Soil cores were obtained to a 120 cm depth from ten fields, two each in Missouri, Illinois, Michigan, South Dakota, and Iowa. Cores were segmented by pedogenic horizon and samples (n = 165 for the surface soil horizon, n = 697 for all soil horizons in the profile) were analyzed for texture fractions, cations (calcium, magnesium, and potassium) and cation exchange capacity (CEC), pH, total and organic carbon, and total nitrogen using standard laboratory procedures. Spectra were obtained on sieved, air-dried soils from 350 to 2500 nm using a commercial three-detector spectrometer. Reflectance data were related to soil properties using partial least squares (PLS) regression and stepwise multiple linear regression (SMLR). Calibration accuracies varied among the different soil properties, but for a given soil property, similar accuracies were generally obtained with PLS and SMLR. The most accurate estimates, with R2 values above 0.8, were obtained for organic carbon, clay, CEC, and calcium. When data from each of the three spectrometer detector ranges were analyzed separately with PLS, the third detector range (1770 to 2500 nm) provided results similar to those obtained using the complete spectral range. Discrete wavelength models that described 90% or more of the variance described by a full model were obtained using eight or fewer wavelengths for the profile dataset and six or fewer wavelengths for the surface dataset. Several wavelengths and wavelength ranges common to models for multiple soil properties were identified: 2070 nm, 1870 to 1915 nm, and 2220 to 2410 nm. Because additional wavelengths important for individual soil properties were dispersed across the 1770 to 2500 nm spectral range, a full-spectrum sensing approach is recommended for simultaneous estimation of multiple soil properties. A discrete-waveband sensor could be practical for estimating one or two individual soil properties.
Between Anthropomorphism, Trust, and the Uncanny Valley: a Dual-Processing Perspective on Perceived Trustworthiness and Its Mediating Effects on Use Intentions of Social Robots

Designing social robots with the aim to increase their acceptance is crucial for the success of their implementation. However, even though increasing anthropomorphism is often seen as a promising way to achieve this goal, the uncanny valley effect proposes that anthropomorphism can be detrimental to acceptance unless robots are almost indistinguishable from humans. Against this background, we use a dual processing theory approach to investigate whether an uncanny valley of perceived trustworthiness (PT) can be observed for social robots and how this effect differs between the intuitive and deliberate reasoning system. The results of an experiment with four conditions and 227 participants provide support for the uncanny valley effect. Furthermore, mediation analyses suggested that use intention decreases through both reduced intuitive and deliberate PT for medium levels of anthropomorphism. However, for high levels of anthropomorphism (indistinguishable from real human), only intuitive PT determined use intention. Consequently, our results indicate both advantages and pitfalls of anthropomorphic design.
Activation of cryptic donor splice sites by non-coding and coding PAX6 variants contributes to congenital aniridia

Background The paired-domain transcription factor paired box gene 6 (PAX6) causes a wide spectrum of ocular developmental anomalies, including congenital aniridia, Peters anomaly and microphthalmia. Here, we aimed to functionally assess the involvement of seven potentially non-canonical splicing variants on missplicing of exon 6, which represents the main hotspot region for loss-of-function PAX6 variants. Methods By locus-specific analysis of PAX6 using Sanger and/or targeted next-generation sequencing, we screened a Spanish cohort of 106 patients with PAX6-related diseases. Functional splicing assays were performed by in vitro minigene approaches or directly in RNA from patient-derived lymphocytes cell line, when available. Results Five out seven variants, including three synonymous changes, one small exonic deletion and one non-canonical splice variant, showed anomalous splicing patterns yielding partial exon skipping and/or elongation. Conclusion We describe new spliceogenic mechanisms for PAX6 variants mediated by creating or strengthening five different cryptic donor sites at exon 6. Our work revealed that the activation of cryptic PAX6 splicing sites seems to be a recurrent and underestimated cause of aniridia. Our findings pointed out the importance of functional assessment of apparently silent PAX6 variants to uncover hidden genetic alterations and to improve variant interpretation for genetic counselling in aniridia.
BAME community hesitancy in the UK for COVID-19 vaccine: suggested solutions

COVID- 19 vaccination drive has been launched throughout the world in the past months with the aim to initially cover healthcare professionals and elderly population who are at high risk of COVID-19 infection due to occupational exposure and comorbidities, respectively. The vaccination drive was launched in the UK on 8 December 2020. The UK has ordered 100 million doses of the Oxford-AstraZeneca adenovirus vaccine and 40 million of the Pfizer-BioNTech messenger RNA (mRNA) vaccine—both are currently being rolled out in the UK. Another 17 million doses of the Moderna vaccine, an mRNA vaccine that has been approved by the Medicines and Healthcare products Regulatory Agency in early January, are expected in the spring.1 Vaccination for COVID-19 has multiple advantages as it helps to prevent COVID-19 infection, decreases the severity and transmission of the disease. It will provide a cost-effective intervention to achieve herd immunity.2 Thus, it is the right and duty of everyone to support the vaccination drive for COVID-19 as per guidelines laid down by each country depending on logistics and availability. Vaccine hesitancy - Vaccine hesitancy is a known term and implies a delay in acceptance or refusal to take the vaccine, despite its availability.3 It is not restricted to any specific country or religion but is found across the population in the world. The Black, Asian and Minority Ethnic (BAME) communities in the UK have shown hesitancy4 for this vaccination drive, particularly the black community followed by members of the Asian lineage. This hesitancy has led to slow …
Impact of COVID-19 national lockdown on asthma exacerbations: interrupted time-series analysis of English primary care data

Background The impact of COVID-19 and ensuing national lockdown on asthma exacerbations is unclear. Methods We conducted an interrupted time-series (lockdown on 23 March 2020 as point of interruption) analysis in asthma cohort identified using a validated algorithm from a national-level primary care database, the Optimum Patient Care Database. We derived asthma exacerbation rates for every week and compared exacerbation rates in the period: January to August 2020 with a pre-COVID-19 period and January to August 2016–2019. Exacerbations were defined as asthma-related hospital attendance/admission (including accident and emergency visit), or an acute course of oral corticosteroids with evidence of respiratory review, as recorded in primary care. We used a generalised least squares modelling approach and stratified the analyses by age, sex, English region and healthcare setting. Results From a database of 9 949 387 patients, there were 100 165 patients with asthma who experienced at least one exacerbation during 2016–2020. Of 278 996 exacerbation episodes, 49 938 (17.9%) required hospital visit. Comparing pre-lockdown to post-lockdown period, we observed a statistically significant reduction in the level (−0.196 episodes per person-year; p<0.001; almost 20 episodes for every 100 patients with asthma per year) of exacerbation rates across all patients. The reductions in level in stratified analyses were: 0.005–0.244 (healthcare setting, only those without hospital attendance/admission were significant), 0.210–0.277 (sex), 0.159–0.367 (age), 0.068–0.590 (region). Conclusions There has been a significant reduction in attendance to primary care for asthma exacerbations during the pandemic. This reduction was observed in all age groups, both sexes and across most regions in England.
Preconception, Antepartum, and Peripartum Care for the Woman With a Spinal Cord Injury: A Review of the Literature

Importance Spinal cord injury (SCI) may result in temporary or permanent loss of sensory, motor, and autonomic function, presenting unique medical and psychosocial challenges in women during their childbearing years. Objective The aim of this study was to review the literature and describe the spectrum of pregnancy considerations, complications, and evidence-based obstetric practices in women with SCI. Evidence Acquisition A literature search was undertaken using the search engines of PubMed and Web of Science using the terms “spinal cord injury” or “spinal cord complications” and “pregnancy outcomes” or “pregnancy complications. ” The search was limited to the English language, and there was no restriction on the years searched. Results The search identified 174 abstracts, 50 of which are the basis for this review. Pregnancy in women who have experienced an SCI requires a multidisciplinary approach. Common complications during pregnancy include recurrent urinary tract infection, upper respiratory tract infection, hypertension, venous thromboembolism, and autonomic dysreflexia (AD), which is a potentially life-threatening complication. Obstetricians should avoid potential triggers and be familiar with acute management of AD. Postpartum complications include difficulty initiating and maintaining breastfeeding and increased risk of postpartum depression and other mental health issues. Conclusions and Relevance Obstetricians caring for women with an SCI must be familiar with the unique challenges and complications that may occur during pregnancy and puerperium. Relevance Statement An evidence-based literature review of the care of pregnant women with spinal cord injury. Target Audience Obstetricians, Obstetric Anesthesiologists Learning Objectives After completing this activity, the learner should be better able to evaluate published literature regarding SCI in pregnant patients; explain the unique complications that can occur in these patients; identify potential risk factors and management strategies of AD; and devise treatment and recommendations for optimal patient outcomes.
Influence of Acidity on the Electrostatic Stability of Alumina Suspensions in Ethanol

Alumina (Al 2 O 3 ) powders have been dispersed in ethanol (EtOH) solutions of different acidity. In aqueous media, acidity is defined by pH. This definition can be extended to nonaqueous media using ion-transfer functions. The electrical charge on the particle surfaces has been found to be acidity dependent. The electrostatic stability of Al 2 O 3 -EtOH suspensions has been evaluated via electrophoresis and turbidity. An electrostatic stabilization mechanism is proposed and analyzed via Derjaguin-Landau-Verwey-Overbeek (DLVO) theory.
THE INFLUENCE OF BUPIVACAINE ON THE CORD BLOOD CHEMILUMINESCENCE IN FULL TERM INFANTS - A PRELIMINARY REPORT WPèYW BUPIWAKAINY NA CHEMILUMINESCENCJKRWI PPOWINOWEJ NOWORODKÓW DONOSZONYCH - DONIESIENIE WSTPNE

Summary Introduction. It has been shown that neutrophil function in the neonate may by modified according to mode of delivery and analgesia or anaes- thesia technique applied to the mother. Aim. The purpose of this study was to assess the influence of bupivacaine on the reactive oxygen species (ROS) production by neutrophils in the umbilical cord blood. Methods. Luminol-dependent opsonized zymosan stimulated whole blood chemiluminescence (CL) was measured in umbilical vein blood samples drawn from six full term healthy neonates incubated with 0.1, 10, 1000 μM of bupivacaine. Simultaneously, peripheral blood CL of six healthy volunteers who served as the control group was also assessed. In the cord blood no significant changes were noted at all concentrations measured. A significant CL decrease at the concentration of 1000 μM could be observed in the control group. Conclusion. Bupivacaine does not significantly influence opsonized zymosan stimulated luminol dependent whole cord blood CL in vitro at all concentrations measured. The question of possible implications of different reactivity of foetus and neonate to local anaesthetics for alternative effects of these compounds under physiological and pathological conditions warrants further studies.