Miracle-dz/UniFAR-FTUs huggingface dataset:
PROJECT TITLE: The Prognostic Value of Cystatin C and Urinary NGAL in Patients With the Cardiorenal Syndrome

Congestive heart failure (CHF) is a common disease and leads to numerous deaths in Canada annually. Part of the reason is due to the high prevalence of renal dysfunction in this patient population, a comorbidity that acts as an independent risk factor for the progression of cardiovascular disease and therefore dramatically increases morbidity and mortality. The phenomenon linking the interaction between these two vital organ systems is called the cardiorenal syndrome. Further understanding of the pathophysiology as well as the ability to predict the development of cardiorenal syndrome in patients with CHF can aid clinicians in guiding therapy towards prevention, and optimizing patient management. To further the understanding of this disease, as well as risk stratify patients with CHF it is important to look at novel biomarkers like serum cystatin C and urinary neutrophil gelatinase-associated lipocalin (NGAL). Cystatin C has been shown to be a robust measure of renal function as it is not subjected to many of the limitations that exist for creatinine. NGAL is a marker of renal tubular injury and levels in both urine and serum are quickly increased when the renal tubules are damaged. By looking at the predictive value and pattern of both of these biomarkers in the development and progression of renal dysfunction in ambulatory CHF patients, we can identify individuals with greater risks of adverse events as well as further our understanding in the development of the cardiorenal syndrome.
I MPACT OF O RGANIZATIONAL C ULTURE ON W ORK E NVIRONMENT AND Q UALITY

The aim of this work is to demonstrate the influence of culture in healthcare organizations on the quality of healthcare services. For the organization of health care, the key factor is to improve the quality of health services. Which consist of the following components: patient care, patient safety and patient satisfaction. The quality of health care delivery consists of two components: a clinical component and a psychoemotional component. These two components can be simultaneously positively influenced by the culture of the organization, while the culture aimed at improving quality can not only positively influence the components of the quality of medical care, safety, satisfaction, but also positively influence the working environment within the organization. Leading to employee satisfaction, reduced stress, burnout, and employee turnover. The review is based on materials from Scopus, Web of Science, CHINAL, PubMed and Sage databases. Several cultural influences such as excellence in care delivery, ethical values, involvement, professionalism, value-for-money, cost of care, commitment to quality and strategic thinking were found to be key cultural determinants in quality care delivery. The study provides evidence for a relationship between culture and performance in hospital settings.
Torn Between Valences: Mixed Emotions Predict Poorer Psychological Well‑Being and Job Burnout

Conflicting perspectives on whether mixed emotions are adaptive states which promote integrative processes or uncomfortable states which are agonizing make divergent predictions on whether mixed emotions in daily life are conducive towards psychological wellbeing. We examined this across three studies. Study 1 ( N = 335, 135 males; M age = 41.31) examined associations between state mixed emotions and psychological well-being. Study 2 ( N = 389; 160 males; M age = 40.86) examined associations between workplace-specific mixed emotions and workplace ill-being assessed based on burnout. Both direct measures and indirect measures were examined in Study 1 and 2, allowing some comparison of methodological issues related to their predictive validity. Study 3 ( N = 3444; 1587 males; M age = 55.34) examined bidirectional relationships between an index of emotional ambivalence and psychological well-being about ten years later, controlling for baselines. Demographic covariates, positive emotions, and negative emotions were controlled for in all studies. Analyses were performed using latent variable structural equation modelling. After adjusting for all covariates, the direct measures of mixed emotions predicted poorer psychological well-being (Study 1) and greater burnout (Study 2). However, indirect measures were found to suffer from relatively greater multicollinearity and poorer predictive validity upon controlling for positive and negative emotions. In Study 3, emotional ambivalence predicted poorer long-term psychological well-being, while psychological well-being also predicted lower emotional ambivalence, supporting bidrectionality. The findings provide preliminary evidence that naturalistically experienced mixed emotions may be conflicting and unpleasant, with potentially negative implications for psychological well-being over and above positive and negative emotions.
WhatsApp and Digital Astroturfing: A Social Network Analysis of Brazilian Political Discussion Groups of Bolsonaro’s Supporters

Digital astroturfing and computational propaganda have drawn a lot of attention in recent years because of the malicious effects on the political environment, especially in the face of the emerging far right. But most studies on astroturfing are limited to seeking theoretical concepts. The present article suggests that the concept of astroturfing can be conceptually defined and empirically investigated through a social network analysis (SNA) approach. The article is specially focused on understanding the use of mobile instant messaging services (MIMS) like WhatsApp as a stage for astroturfing practices in 2018 Brazilian elections. Its main hypothesis is that SNA methods can help in understanding how a Bolsonarist influence operation and misinformation network was structured. Results show different thematic groups and several functional clusters and lead to the identification of practices that match with those of agents from the professional field of politics.
Incorporating Dried Distillers Grains with Solubles in Sheep Supplementation Programs

In the U.S., dried distillers grains with solubles (DDGS) is a highly available coproduct of ethanol and brewery industries utilized in ruminant diets that, due to the comparable nutritional quality, is capable of substituting (partially or totally) traditional sources of protein and energy with a possibility of reducing feed costs. With the use of this product, there is the potential to increase reproductive efficiency, survivability, growth performance, and meat production and quality when a well-designed supplementation program is implemented and monitored. However, the literature has scarce papers evaluating the effects of DDGS in sheep nutrition, notably in supplementation programs. The lack of DDGS utilization in sheep diets may be related to some challenges, such as nutritional composition variability, handling, storage, and feeding issues. In addition to addressing these challenges, an overview of the statistics and concepts applied to the ethanol and sheep industry will be presented here, as well as the criteria involved in the incorpo-ration of DDGS into sheep supplementation programs. These latter factors include the interaction between pasture and supplement type, along with feeding and herd characteristics.
Sex of Littermate Twin Affects Lifetime Ewe Productivity3

Ewe productivity is synonymous with annual litter-weight weaned (LWW) per ewe exposed to rams for breeding, and LWW is largely a function of number of lambs born (NLB) and weaned (NLW). Selecting for LWW should increase litter size and numbers of ewe-ram co-twins. Thus, we used historical records to determine whether sex of co-twin affected lifetime productivity of twinborn ewes. United States Sheep Experiment Station (USSES) lambing records (n = 8,650) from 1991 through 1997 were queried to identify twinborn ewes that were reared with their biological dams and retained in the breeding flock (n = 1,628; Columbia, 383; Polypay, 536; Rambouillet, 383; and Targhee, 326). Corresponding records for lifetime-cumulative counts of lambs born (stillborn and live-born) with recorded birth weights and weaned with recordedweaning weights, cumulative weight of lambs weaned, lifetime count of lambing events, and age at first lambing (1 yr, 2 yr, or 3 yr) were evaluated using PROC GLM and PROC MIXED methods. Alpha was set at 0.10. Only the main effects of sex of co-twin, ewe-weaning weight, ewe breed, and ewe-birth year were significant. Per-ewe exposed to rams, but not per-ewe lambing, cumulative-lifetime weaning weight (P = 0.03) and numbers of lambs born (P = 0.07) and weaned (P = 0.04) were greater for ewes with a ram co-twin than for ewes with a ewe co-twin. Sex of co-twin did not affect number of lifetime-lambing events or age at first lambing for ewes exposed (P = 0.14 and P = 0.59, respectively) or ewes lambing (P = 0.67 and P = 0.27, respectively). Ewe-weaning weight affected cumulative-lifetime weaning weights (P = 0.0003), lifetime numbers of lambs born (P = 0.001) and weaned (P = 0.02), and lifetime-lambing events (P = 0.001), but not age at first lambing (P = 0.44) per-ewe exposed. Productivity of Polypay and Rambouillet ewes generally exceeded that of Columbia and Targhee ewes, although breed ranking was not constant among productivity traits of twinborn ewes. Based on the data, we concluded that ewes born co-twin to a ram had an advantage over ewes born co-twin to a ewe. This advantage amounted to 15.55 kg in lifetime litter-weight weaned per-ewe exposed. We believe that sex of co-twin should be evaluated further to determine whether it is a useful environmental adjustment, beyond lamb sex and type of birth and rearing, for lamb weights and traits related to ewe productivity.
RIII g Through Fc IgE-Mediated Activation of NK Cells

NK cells express Fc (cid:1) RIII (CD16), which is responsible for IgG-dependent cell cytotoxicity and for production of several cytokines and chemokines. Whereas Fc (cid:1) RIII on NK cells is composed of both Fc (cid:1) RIII (cid:2) and FcR (cid:1) chains, that on mast cells is distinct from NK cells and made of Fc (cid:1) RIII (cid:2) , FcR (cid:3) , and FcR (cid:1) . Mast cells show degranulation and release several mediators, which cause anaphylactic responses upon cross-linking of Fc (cid:1) RIII as well as Fc (cid:4) RI with aggregated IgE. In this paper, we examined whether IgE activates NK cells through Fc (cid:1) RIII on their cell surface. We found that NK cells produce several cytokines and chemokines related to an allergic reaction upon IgE stimulation. Furthermore, NK cells exhibited cytotoxicity against IgE-coated target cells in an Fc (cid:1) RIII-dependent manner. These effects of IgE through Fc (cid:1) RIII were not observed in NK cells from FcR (cid:1) -deﬁcient mice lacking Fc (cid:1) RIII expression. Collectively, these results demonstrate that NK cells can be activated with IgE through Fc (cid:1) RIII and exhibit both cytokine/chemokine production and Ab-dependent cell cytotoxicity. These data imply that not only mast cells but also NK cells may contribute to IgE-mediated allergic responses. The Journal of Immunology, 2003, 170: 3054–3058. various mediators and results in an anaphylactic reaction. Fc (cid:1) RI-deﬁcient FcR (cid:3) , 5 (cid:5) -AAGAATTCCAGCGCCG CAGCCCCCAGCG and 3 (cid:5) -GGAATTCGCTGCCTTTCGGACCTGGAT; and (cid:5) -actin, 5 (cid:5) -ACCCACACTGTGCCCATCTA and 3 (cid:5) -TCATGGATGCC ACAGGATTC. To detect several cytokines and chemokines, the following primers were used: IFN- (cid:3) , 5 (cid:5) -CCTCAGACTCTTTGAAGTCT and 3 (cid:5) -CAGCGACTCCTTTTCCGCTT; TNF- (cid:2) , 5 (cid:5) -ATGAGCACAGAAAGCAT GATCCGCGAC and 3 (cid:5) -TCACAGAGCAATGACTCCAAAGTAGACCTG; GM-CSF, 5 (cid:5) -CCGCTCACCCATCACTGTCAC and 3 (cid:5) -AGGCTGTCTATG AAATCCGCA; and macrophage-inﬂammatory protein (MIP)-1 (cid:2) , 5 (cid:5) -CAA GTCTTCTCAGCGCCATA and 3 (cid:5) -TCTTTGGAGTCAGCGCAGAT.
Pre-Processing to Leverage Temporal Information with Transfer Learning on Convolutional Neural Networks for End-to-End DeepFake Video Detection

Many state-of-the-art DeepFake video detectors use Long Short-Term Memory-based networks (LSTM) as they can easily capture temporal information and take video as direct input. We opt not to use LSTM-based approaches and instead utilise Convolutional Neural Networks which cannot infer temporal information and instead take images as input. We consider a series of pre-processing methods. Frame differencing (FD) is where we take the difference of frames over subsections of video in hopes to highlight idiosyncratic movements often present in DeepFake videos. We also consider averaging over subsections of video (FA) and compare against a baseline dataset of randomly selecting single frames over the same subsections (RF). We do this in hopes to leverage temporal information in an image: FA uses averaging and blurs to indicate movement, FD uses highlighted colours to do the same, and RF does not capture any temporal data. The aim is to make our model time-aware in some rudimentary sense. We hypothesise that these pre-processing methods, FA and FD, which transform video into a series of images encapsulating movement, will increase performance compared to still, randomly selected frames, RF. We use Transfer Learning on both our MesoInception4 baselines and custom Xception for DeepFake detection. We ﬁnd that this hypothesis is correct, with the frame averaging dataset yielding consistently higher performance compared to randomly selected frames. However, we did not see this trend with our novel frame differencing approach.
Pre-Training Language Models for Identifying Patronizing and Condescending Language: An Analysis

Patronizing and Condescending Language (PCL) is a subtle but harmful type of discourse, yet the task of recognizing PCL remains under-studied by the NLP community. Recognizing PCL is challenging because of its subtle nature, because available datasets are limited in size, and because this task often relies on some form of commonsense knowledge. In this paper, we study to what extent PCL detection models can be improved by pre-training them on other, more established NLP tasks. We find that performance gains are indeed possible in this way, in particular when pre-training on tasks focusing on sentiment, harmful language and commonsense morality. In contrast, for tasks focusing on political speech and social justice, no or only very small improvements were witnessed. These findings improve our understanding of the nature of PCL.
Undecidability of Dyadic First-Order Logic in Coq

We develop and mechanize compact proofs of the undecidability of various problems for dyadic first-order logic over a small logical fragment. In this fragment, formulas are restricted to only a single binary relation, and a minimal set of logical connectives. We show that validity, satisfiability, and provability, along with finite satisfiability and finite validity are undecidable, by directly reducing from a suitable binary variant of Diophantine constraints satisfiability. Our results improve upon existing work in two ways: First, the reductions are direct and significantly more compact than existing ones. Secondly, the undecidability of the small logic fragment of dyadic first-order logic was not mechanized before. We contribute our mechanization to the Coq Library of Undecidability Proofs, utilizing its synthetic approach to computability theory.
Coﬀee Bean (and other) Models about the Metric Structure of Music

This article discusses the question of how to evaluate computational models for metric structures in music. The great amount of computational models developed in this ﬁeld in recent years has provoked the request to compare the results of these models. Starting from a suggestion to count the number of correct results produced by the model, the article points to some of the diﬃculties associated with this criterion for a model in music. We give some examples of how the comparison to other models or theories nevertheless can contribute to new insights into the phenomenon of meter in music.
Why “backﬁre effects” do not explain the durability of political misperceptions

Previous research indicated that corrective information can provoke a so-called “backﬁre effect” in which respondents more strongly endorsed a misperception about a controversial political or scientiﬁc issue when their beliefs or predispositions were chal-lenged. I show how subsequent research and media coverage seized on this ﬁnding, distorting its generality and exaggerating its role relative to other factors in explain-ing the durability of political misperceptions. To the contrary, an emerging research consensus ﬁnds that corrective information is typically at least somewhat effective at increasing belief accuracy when received by respondents. However, the research I review suggests that the accuracy-increasing effects of corrective information like fact-checks often do not last or accumulate; instead, they frequently appear to decay or be overwhelmed by cues from elites and the media promoting more congenial but less accurate claims. As a result, misperceptions typically persist in public opinion for years after they have been debunked. Given these realities, the primary challenge for scientiﬁc communication is not to prevent backﬁre effects but instead to understand how to target corrective information better and to make it more effective. Ultimately, however, the best approach is to disrupt the formation of linkages between group identities and false claims and to reduce the ﬂow of cues reinforcing those claims from elites and the media. Doing so will require a shift from a strategy focused on providing information to the public to one that considers the roles of intermediaries in forming and maintaining belief systems.
To Sell or Not to Sell: Knowledge Risks in Data-Driven Business To Sell or Not to Sell: Knowledge Risks in Data-Driven Business Models Models

Data plays a central role in many of today's business models. With the help of advanced analytics, knowledge about real-world phenomena can be discovered from data. This may lead to unintended knowledge spillover through a data-driven offering. To properly consider this risk in the design of data-driven business models, suitable decision support is needed. Prior research on approaches that support such decision-making is scarce. We frame designing business models as a set of decision problems with the lens of Behavioral Decision Theory and describe a Design Science Research project conducted in the context of an automotive company. We develop an artefact that supports identifying knowledge risks, concomitant with design decisions, during the design of data-driven business models and verify knowledge risks as a relevant problem. In further research, we explore the problem in-depth and further design and evaluate the artefact within the same company as well as in other companies
Competition Network: Distress Spillovers and Predictable Industry Returns

We build a competition network of industries — two industries are connected if they share at least one multi-industry firm that competes as a major player in both. Exploiting quasi-experiments induced by the local-natural-disaster occurrences, Lehman failure, and American-Jobs-Creation-Act passage, we find that firms hit by adverse (positive) distress shocks decrease (increase) profit margins, and in response, their “untreated” industry peers, driven by intensified (eased) competition, also cut (raise) profit margins and become more (less) distressed. Further, distress shocks and the resulting changes in competition intensity can propagate to other industries through common major players. Such cross-industry spillovers, with investors’ learning frictions, rationalize industry return predictability through the competition-network links.
SceneSqueezer: Learning to Compress Scene for Camera Relocalization

Standard visual localization methods build a priori 3D model of a scene which is used to establish correspondences against the 2D keypoints in a query image. Storing these pre-built 3D scene models can be prohibitively expensive for large-scale environments, especially on mobile devices with limited storage and communication bandwidth. We design a novel framework that compresses a scene while still maintaining localization accuracy. The scene is compressed in three stages: first, the database frames are clustered using pairwise co-visibility information. Then, a learned point selection module prunes the points in each cluster taking into account the final pose estimation accuracy. In the final stage, the features of the selected points are further compressed using learned quantization. Query image registration is done using only the compressed scene points. To the best of our knowledge, we are the first to propose learned scene compression for visual localization. We also demonstrate the effectiveness and efficiency of our method on various outdoor datasets where it can perform accurate localization with low memory consumption.
HUMAN RESOURCE MANAGEMENT PRACTICES AND FIRM INNOVATION: MEDIATING ROLE OF HUMAN CAPITAL

Firms’ ability to innovate becomes a more significant concern over the hypercompetitive and dynamic business environment. Within this context, how to promote innovation in organisations becomes challenging. Many studies far less focused on the role of human resource management in promoting firm innovation. Since the human resource management practices vary from country to country and firm to firm, the findings of the studies limit its application in a diverse context. Sadly, there is bereft of such studies recorded in many developing countries. Consequently, the study aims at investigating the relationship between human resource management practices and firm innovation and the mediating role of the human capital of such relationship. This study deploys PLS-SEM to test the hypotheses in a sample of 127 firms operating in Sri Lanka. The data were collected through a self-reported questionnaire. The result shows that human resource management practices are significantly, positively, related to human capital, which positively affects firm innovation. The findings support that human capital plays a mediating role between human resource management practices and firm innovation. Finally, this study discusses the implications and highlights the future research directions. That is to say, knowledge, skills and capabili ties and attributes embedded in firm’s human resources is saliant to organisation’s ability to captivate and shape the knowledge needed in the innovation process. The hypothesis (H 4 ) foretold that human capital mediates the relationship between HRM practices and firm innovation was supported. The findings show support for the mediating effect of human capital on the relationship between HRM practices and firm innovation. HRM practices works their valuable effects on firm innovation through the capacity in human capital.