Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Assessment of the Level of Patient Safety Culture between Surgical and Nonsurgical Units in Bulgarian Hospitals

Patient safety culture is a key component of the organizational culture and a critical measure of the quality of healthcare. The aim of this study was to gain an insight into the problems concerning patient safety culture, based on the analysis of data, collected after interviewing healthcare specialists working in surgical and nonsurgical units in selected Bulgarian hospitals. This was a cross-sectional online study using a web-platform and the Bulgarian Version of Hospital Survey on Patient Safety Culture. It was conducted among healthcare workers (n = 620) in 2021. The B-HSOPSC incudes 42 scales grouped in 12 different domains. We compared the percentage of positive ratings and outcome dimensions between surgical and other hospital departments with the nonparametric Mann–Whitney U test, χ2 tests, Fisher’s Exact Test, and OR. The results showed that there are no statistically significant differences between the ratings on Patient Safety Culture given by the surgical and the nonsurgical staff except for the dimension “Hospital management support for patient safety”. Results from the study highlighted that the most important aspect of hospital patient safety is the shortage of medical staff in both surgical and nonsurgical hospital units. Communication, work shift organization, handoffs and transitions between shifts and among different hospital units, as well as communication with line managers were rated as satisfactory in Bulgarian hospitals.
Development of Correction Models for Three-Electrode NO2 Electrochemical Sensor

Ambient conditions, especially temperature and humidity, have a huge impact on the performance of an air quality sensor. In this paper, four correction models were built to compensate the impact of ambient conditions. Linear regression and machine learning algorithms were used for building the models. Correction models were trained by using three types of measurement data. Raw measurement data was used in the first case. Secondly, measurement data was corrected and a significant improvement was shown. Lastly, measurements of various ambient conditions were used as well. Using corrected and extended measurement data brought a great improvement in accuracy of the models. A neural network correction model proved to be the most efficient in all cases. Compensating the impact of ambient conditions on the performance of an air quality sensor by using correction models was efficient and this method could be used in the air quality monitoring applications. This is of particular importance for usage of low-cost sensors in the air quality monitoring.
Sexism in the Judiciary: The Importance of Bias Definition in NLP and In Our Courts

We analyze 6.7 million case law documents to determine the presence of gender bias within our judicial system. We find that current bias detection methods in NLP are insufficient to determine gender bias in our case law database and propose an alternative approach. We show that existing algorithms’ inconsistent results are consequences of prior research’s inconsistent definitions of biases themselves. Bias detection algorithms rely on groups of words to represent bias (e.g., ‘salary,’ ‘job,’ and ‘boss’ to represent employment as a potentially biased theme against women in text). However, the methods to build these groups of words have several weaknesses, primarily that the word lists are based on the researchers’ own intuitions. We suggest two new methods of automating the creation of word lists to represent biases. We find that our methods outperform current NLP bias detection methods. Our research improves the capabilities of NLP technology to detect bias and highlights gender biases present in influential case law. In order to test our NLP bias detection method’s performance, we regress our results of bias in case law against U.S census data of women’s participation in the workforce in the last 100 years.
Sustainable Manufacturing and Environmental Pollution Programme (SMEP): A Circular Economy Experiment in the Global South

The circular economy (CE) is a topic of growing interest, spurred by climate change and increasing recognition of the considerable costs of energy and materials waste, that reflect increasing stress on global environmental systems. Those costs range from physical landfill expenses to effects on human and natural world health. While there are a growing number of articles about the CE, there remains a great deal of ambiguity around pathways to implement it, and even fewer practical examples. Lieder and Rashid (2016) conclude in their overarching examination of CE research that while it is broad and multidisciplinary it is also fragmented, highly granular, and “rarely touching implementation. ” In this article, we review recent efforts to identify models for scaling up circular economy practices in specific sectors of Sub-Saharan Africa and South Asia economies, based on information produced by the Sustainable Manufacturing and Environmental Pollution (SMEP) program. The SMEP program has been established by the United Kingdom’s Foreign, Commonwealth & Development Office (FCDO) and is being implemented in partnership with the United Nations Conference on Trade and Development (UNCTAD). SMEP seeks to reduce pollution in manufacturing in the Global South. After a brief discussion of the CE concept, this article focuses on the innovative features of the SMEP program, its preliminary findings and lessons for the transition to circularity.
Sliding-Priors for Bayesian Information Fusion in SCADA+PMU-based State Estimation

This paper describes a new development within the conceptual framework BAYSE (Bayesian State Estimation), which enables the full integration of the SCADA (Supervisory Control and Data Acquisition) data with PMU (phasor measurement units) data. It is based on Bayesian inference principles and extends the concept of the prior distributions to accommodate a broad set of past state conditions, under a sliding window approach. By choosing an appropriate window length, the method enhances accuracy under stationary conditions, with a reduced impact under system changes. The work also submits a rectangular coordinates transformation procedure, based on the Jacobian method, to consistently integrate polar coordinates estimations with the PMU linear model (in rectangular coordinates). The paper presents the new approach in proof-of concept mode over a didactic test-bed, using real PMU time series, to emphasize the enhanced accuracy and good asymptotic properties.
The Impact of Psychological Distress Due to COVID-19 on College Student Career Development

The COVID-19 pandemic has been an ongoing public health crisis and continues to create a variety of challenges (Centers for Disease Control and Prevention, 2020). Since the challenges of COVID-19 seem to be particularly salient for traditional college-age students (Kujawa et al., 2020) and career development is a corner stone of development at this stage, the current study investigated what impact the COVID-19 pandemicrelated stress has on the psychological distress, career-development self-efficacy, and career decidedness of a sample of college students. Three hundred one students from a southeastern United States university participated in the study. We hypothesize 1) Impacts from pandemic stress will negatively impact the career development (i.e., self-efficacy and decidedness) of college students and 2) psychological distress will mediate the relationship between pandemic stress and the career development of college students. The analysis revealed that pandemic stress does not directly impact the career development of college students. However, mediation analyses revealed a positive indirect relationship between pandemic stress and career decidedness when accounting for psychological distress as well as a negative indirect relationship between pandemic stress and career decision making self-efficacy when accounting for psychological distress. While impacts from COVID-19-related stress did not directly account for changes in career decision making self-efficacy and decidedness on its own, when in the presence of psychological distress the relationship between pandemic stress and career development exist. Moreover, the positive relationship between pandemic stress and career decidedness suggests that higher pandemic stress is associated with more career undecidedness when accounting for psychological distress. Likewise, the negative relationship between pandemic stress and career decision making self-efficacy suggests that higher pandemic stress is associated with lower levels of self-efficacy when making career decisions. Practical implications for these findings are discussed. CORRESPONDING AUTHOR:
HoD-Net: High-Order Differentiable Deep Neural Networks and Applications

We introduce a deep architecture named HoD-Net to enable high-order differentiability for deep learning. HoD-Net is based on and generalizes the complex-step finite difference (CSFD) method. While similar to classic finite difference, CSFD approaches the derivative of a function from a higher-dimension complex domain, leading to highly accurate and robust differentiation computation without numerical stability issues. This method can be coupled with backpropagation and adjoint perturbation methods for an efficient calculation of high-order derivatives. We show how this numerical scheme can be leveraged in challenging deep learning problems, such as high-order network training, deep learning-based physics simulation, and neural differential equations.
Coming off fossil fuels: Visual recollection of fossil fuel dependency

As participants of the global capitalist system, we have rich and lifelong experiences of living with fossil fuels. However, these experiences are often implicit in our everyday lives, and rarely formulated explicitly. Coming off Fossil Fuels is a project that visualises and collects personal experiences of fossil fuel dependencies. Experiences can include memories, current attachments and future dreams connected to fossil fuels. This article is a methodological account of collecting fossil fuel experiences through two modes of visual recollection: (1) an autobiographical video piece visualising the author’s own dependencies on fossil fuels and (2) gallery visitors’ fossil fuel experiences. The article utilises a participatory arts-based approach in which gallery visitors were able to react to the video in recorded responses. The video was presented as part of the 2022 LOOK Climate Lab thinking space in Open Eye Gallery, Liverpool, where video responses were collected. The article also discusses possibilities for developing a method of visual recollection by considering temporal and spatial dimensions of fossil fuel dependency.
Frozen by threat or motivated to move? Emotionally charged horizons of opportunities in development work of universities

How do emotions function in the development work and change attempts of universities? This article investigates the emotional dimensions of development of higher education and how emotions relate to the conditions of academic work, and the university as a forum for those initiatives. Building theories from affective cultural studies, the article drafts and explores the concept of ‘emotionally charged horizon of opportunity’. This concept defines emotions as relational, culturally situated social forces connected with relationships, collective mentalities and belief systems, which the article explores by example of two cases: a national attempt to renew a degree structure on a disciplinary level, and a departmental initiative of development of the academic unit. Taking a discourse analytic approach with the focus on emotions, the analysis comprises two major findings. First, affectivity was present in the practices of development work, in the hierarchies of power, group relations and identities of the academic culture. Second, the actors’ expectations about the future, the emotional judgments attached to these expectations, and the position of the actors were crucial for the development process.
Phylogenomics Resolves the Phylogeny of Theaceae by Using Low-Copy and Multi-Copy Nuclear Gene Makers and Uncovers a Fast Radiation Event Contributing to Tea Plants Diversity

Simple Summary The Theaceae includes more than 300 species of great morphological diversity and has immense economic, cultural, and ornamental values. However, the evolutionary history of this family remains elusive. We integrated 91 genomes and transcriptome datasets of Theaceae and successfully resolved the phylogeny of Theaceae including relatives of cultivated tea plants from both extensive low-copy and multi-copy nuclear gene markers. Bayes-based molecular dating revealed that the ancestor of the tea family originated slightly earlier than the K-Pg boundary (Mass extinction events including the extinction of dinosaurs) with early diversification of three tribes associated with the Early Eocene Climatic Optimum. Further speciation analysis suggested a sole significant diversification shift rate in the common ancestor of Camellia associated with the Mid-Miocene Climatic Optimum. Collectively, polyploidy events, and key morphological innovation characters, such as pericarp with seed coat hardening, could possibly contribute to the Theaceae species diversity. Abstract Tea is one of the three most popular nonalcoholic beverages globally and has extremely high economic and cultural value. Currently, the classification, taxonomy, and evolutionary history of the tea family are largely elusive, including phylogeny, divergence, speciation, and diversity. For understanding the evolutionary history and dynamics of species diversity in Theaceae, a robust phylogenetic framework based on 1785 low-copy and 79,103 multi-copy nuclear genes from 91 tea plant genomes and transcriptome datasets had been reconstructed. Our results maximumly supported that the tribes Stewartieae and Gordonieae are successive sister groups to the tribe Theeae from both coalescent and super matrix ML tree analyses. Moreover, in the most evolved tribe, Theeae, the monophyletic genera Pyrenaria, Apterosperma, and Polyspora are the successive sister groups of Camellia. We also yield a well-resolved relationship of Camellia, which contains the vast majority of Theaceae species richness. Molecular dating suggests that Theaceae originated in the late L-Cretaceous, with subsequent early radiation under the Early Eocene Climatic Optimal (EECO) for the three tribes. A diversification rate shift was detected in the common ancestors of Camellia with subsequent acceleration in speciation rate under the climate optimum in the early Miocene. These results provide a phylogenetic framework and new insights into factors that likely have contributed to the survival of Theaceae, especially a successful radiation event of genus Camellia members to subtropic/tropic regions. These novel findings will facilitate the efficient conservation and utilization of germplasm resources for breeding cultivated tea and oil-tea. Collectively, these results provide a foundation for further morphological and functional evolutionary analyses across Theaceae.
Critical Investigation of the Usability of Hepatoma Cell Lines HepG2 and Huh7 as Models for the Metabolic Representation of Resectable Hepatocellular Carcinoma

Simple Summary Energy metabolism plays a central role in the liver. Therefore, metabolic alterations in liver cancer are fundamental for the development of diagnostic screening and therapeutic intervention. The aim of our experimental study was to investigate the extent to which commonly used hepatoma cell lines (HCLs) sufficiently represent tumor cells from hepatocellular carcinoma (HCC) from a metabolic point of view. To that end, we successfully established a method for the isolation of primary human hepatoma cells (PHCs). We present the unsurprising finding that cell lines are a poor substitute for primary cells. Surprisingly, our transcript data revealed that malign metabolic adaptions had already occurred in non-tumor-bearing liver tissue of HCC patients. In PHCs, we observed that downregulated metabolic key players showed a correlation with malign transformation and were predominantly pronounced in multilocular HCC. These findings should be taken into account for the future optimization of HCC models for in vitro research. Abstract Metabolic alterations in hepatocellular carcinoma (HCC) are fundamental for the development of diagnostic screening and therapeutic intervention since energy metabolism plays a central role in differentiated hepatocytes. In HCC research, hepatoma cell lines (HCLs) like HepG2 and Huh7 cells are still the gold standard. In this study, we characterized the metabolic profiles of primary human hepatoma cells (PHCs), HCLs and primary human hepatocytes (PHHs) to determine their differentiation states. PHCs and PHHs (HCC-PHHs) were isolated from surgical specimens of HCC patients and their energy metabolism was compared to PHHs from non-HCC patients and the HepG2 and Huh7 cells at different levels (transcript, protein, function). Our analyses showed successful isolation of PHCs with a purity of 50–73% (CK18+). The transcript data revealed that changes in mRNA expression levels had already occurred in HCC-PHHs. While many genes were overexpressed in PHCs and HCC-PHHs, the changes were mostly not translated to the protein level. Downregulated metabolic key players of PHCs revealed a correlation with malign transformation and were predominantly pronounced in multilocular HCC. Therefore, HCLs failed to reflect these expression patterns of PHCs at the transcript and protein levels. The metabolic characteristics of PHCs are closer to those of HCC-PHHs than to HCLs. This should be taken into account for future optimized tumor metabolism research.
Social media marketing system: conceptualization, scale development and validation

PurposeUnderstanding what organizational factors enable a successful social media presence is a relevant issue for academics and practicing managers. The purpose of this investigation is to thus develop and validate a scale to measure a social media marketing system (SMMS). Design/methodology/approachThis paper follows a rigorous scale development process based on three stages: item generation, measurement development and instrument testing. The validity and reliability tests were conducted using data provided by social media managers and the managers' supervisors.FindingsThe results validate a 25-item multidimensional SMMS scale that exhibits adequate internal consistency, reliability, construct validity and nomological validity. The results also show that the SMMS scale positively correlates with outcomes that are key to firm success (social media strategy success and marketing performance). Originality/valueThis paper conceptualizes SMMS through four dimensions, namely formalization, human resource management, co-creation and marketing planning, and the paper associates SMMS to important firm outcomes. The newly developed measurement instrument adds to the small repository of research scales relevant to social media and can serve as a springboard from which future work can understand social media from both an internal management perspective and an integrated outlook.
IIIT Hyderabad Submission To WAT 2021: Efficient Multilingual NMT systems for Indian languages

This paper describes the work and the systems submitted by the IIIT-Hyderbad team in the WAT 2021 MultiIndicMT shared task. The task covers 10 major languages of the Indian subcontinent. For the scope of this task, we have built multilingual systems for 20 translation directions namely English-Indic (one-to- many) and Indic-English (many-to-one). Individually, Indian languages are resource poor which hampers translation quality but by leveraging multilingualism and abundant monolingual corpora, the translation quality can be substantially boosted. But the multilingual systems are highly complex in terms of time as well as computational resources. Therefore, we are training our systems by efficiently se- lecting data that will actually contribute to most of the learning process. Furthermore, we are also exploiting the language related- ness found in between Indian languages. All the comparisons were made using BLEU score and we found that our final multilingual sys- tem significantly outperforms the baselines by an average of 11.3 and 19.6 BLEU points for English-Indic (en-xx) and Indic-English (xx- en) directions, respectively.
NukCP: An Improved Local Search Algorithm for Maximum k-Club Problem

The maximum k-club problem (MkCP) is an important clique relaxation problem with wide applications. Previous MkCP algorithms only work on small-scale instances and are not applicable for large-scale instances. For solving instances with different scales, this paper develops an efficient local search algorithm named NukCP for the MkCP which mainly includes two novel ideas. First, we propose a dynamic reduction strategy, which makes a good balance between the time efficiency and the precision effectiveness of the upper bound calculation. Second, a stratified threshold configuration checking strategy is designed by giving different priorities for the neighborhood in the different levels. Experiments on a broad range of different scale instances show that NukCP significantly outperforms the state-of-the-art MkCP algorithms on most instances.
An Empirical Investigation on the Perceptual Similarity of Prosodic Language Types

This study explores whether prosodic similarities of typological prosodic language types can be perceived by German native speakers. For this purpose, two online perception experiments were conducted containing twelve typologically and geographically diverse languages. Participants were asked to judge their prosodic similarity. Results showed that languages with mainly word-level prosodic properties were judged as similar to one another, while languages employing sentence-level prosodic properties were not clearly perceived as similar to their specific language type. Frequent confusions of Intonation and Phrase languages indicate a high perceptional similarity of languages belonging to these prosodic types. This leads to the assumption that the adopted distinction of prosodic properties is not completely represented in perception. Rather, additional prosodic factors influence the perception of the sentence prosody of languages.
A Novel Differentially-Fed Dual-Polarized Filtering Antenna for Base Station

The theory, design and experiments of a wideband dual-polarized filtering antenna are presented. A novel technique, which combines the use of open loops, parasitic loop, and extended ground plane, is proposed to realize two upper band radiation nulls and a lower band radiation null. Thanks to these radiation nulls, the proposed antenna obtains a sharp cut-off at the edges of the operating band. To achieve wideband performance, another novel technique of exciting multiple resonant modes of the crossed dipoles and parasitic loop is proposed. The measured results demonstrate that this antenna achieves a wide impedance bandwidth from 1.7 to 3.01 GHz (56%), high isolation of 38dB, low cross-polarization within the working frequency band and also filtering performance. At 3.17 GHz, the gain of the antenna will drop rapidly to -18.1 dBi, which is 26.4 dB lower than the average in-band gain. These advantages make the proposed antenna a good candidate for base station applications.