Miracle-dz/UniFAR-FTUs huggingface dataset:
User Models, Metrics and Measures of Search: A Tutorial on the C/W/L Evaluation Framework

Evaluation is central to Information Retrieval, and is how we compare the quality of systems. One important principle of evaluation is that the measured score should reflect the user's experience with the system. Hence, there should be direct connection between how users interact with the system and the characteristics of the metric. In this tutorial we introduce the C/W/L approach to user modeling and show how different user models lead to different metrics. We then describe the recent innovations and approaches to evaluation that it has facilitated. The tutorial is presented as a mix of on-line synchronous lecture, pre-recorded in-depth videos, and hands-on activities using the C/W/L toolkit for participants' own evaluation tasks. A followup consultation session is also provided, to allow extended questions and individual discussion with the four presenters.
Polymer Based Lanthanide Luminescent Sensors for the Detection of Nerve Agents

Several devices are being constructed to measure and detect the nerve agents Sarin and Soman. The devices function by selectively binding the phosphonate hydrolysis products to a luminescent functionality-imprinted copolymer. The copolymers possess a securely bound luminescent lanthanide ion, such as Eu 3 + , in a coordination complex that has been templated for the chemical functionality resulting from the hydrolysis of Sarin and Soman but has had a weakly bound anion substituted by mass action. The instrumental support for the device is being designed to monitor the change that occurs in the luminescence spectrum of the lanthanide when the analyte is coordinated. The ligand field shifted luminescence of the lanthanide is excited by a compact laser and monitored via optical fiber by either a filter photometer or a monochromator. Miniaturization will be applied to each of the lab bench components to produce a field portable device that will potentially be comparable in size to a pH meter. Initial results using an Ar ion laser excitation source providing 0.3 mW at 465.7 nm yield a limit of detection of 125 ppt. The chemical and spectroscopic selectivity of this device are being combined to reduce the likelihood of false positive analyses.
BIRDS 2021: Bridging the Gap between Information Science, Information Retrieval and Data Science

2 BACKGROUND AND RELATIONSHIPS TO CHIIR Recent years saw an emergence of formal retrieval models that were informed by theories coming from Information Science (IS) as reported in [7], [1], [4], [5], [2], and [6], for example. These IS-informed formal retrieval models try to put the focus on users and their interaction with the retrieval system. However, work in building formal approaches and models that are expressive enough to incorporate user behaviour in the retrieval systems are still in their infancy. One approach to de ne IS-informed formal retrieval models can be suggested by the increasing availability of di erent data sources either commercially or openly that led to the emergence of Data Science (DS). Interestingly, DS is not only about batch processing of the large datasets. Whereas Machine Learning (ML) provides predictions for the data sources with very little user input, Exploratory Data Analysis (EDA) allows the users to interact with the system for nding data and patterns of the data which cannot easily be found through traditional database querying. Similarly, some research areas of Information Retrieval (IR) have extensively and deeply been in uenced and characterized by Statistics and Probability Theory. As a consequence, IR is more and more regarded as part of DS, as evidenced by the recent challenges and activities when it comes to COVID-19 testbeds containing scienti c
Ethical Issues When Considering Liver Donor Versus Deceased Donor Liver Transplantation

Deceased donors remain the primary source of organs for patients waitlisted for liver transplantation (LT). In 2019, 8372 deceased donor liver transplants (DDLTs) were performed, compared with 524 living donor liver transplants (LDLTs) (Fig. 1). The number of LDLTs has not significantly increased over time in the United States because of local surgical expertise, programmatic decisions, and risks to healthy living donors. Given the organ shortage, the patient and the transplant team may opt to pursue LDLT over DDLT. This practice raises several concerns regarding the ethical soundness of LDLT. Our group’s review in LT discusses various ethical concerns based on actual cases, as well as potential approaches to optimize the informed consent process.
Cognitive Biases in Search: A Review and Reflection of Cognitive Biases in Information Retrieval

People are susceptible to an array of cognitive biases, which can result in systematic errors and deviations from rational decision making. Over the past decade, an increasing amount of attention has been paid towards investigating how cognitive biases influence information seeking and retrieval behaviours and outcomes. In particular, how such biases may negatively affect decisions because, for example, searchers may seek confirmatory but incorrect information or anchor on an initial search result even if its incorrect. In this perspectives paper, we aim to: (1) bring together and catalogue the emerging work on cognitive biases in the field of Information Retrieval; and (2) provide a critical review and reflection on these studies and subsequent findings. During our analysis we report on over thirty studies, that empirically examined cognitive biases in search, providing over forty key findings related to different domains (e.g. health, web, socio-political) and different parts of the search process (e.g. querying, assessing, judging, etc.). Our reflection highlights the importance of this research area, and critically discusses the limitations, difficulties and challenges when investigating this phenomena along with presenting open questions and future directions in researching the impact --- both positive and negative --- of cognitive biases in Information Retrieval.
Effects of hydroxyethyl starch and gelatin on the risk of acute kidney injury following orthotopic liver transplantation: A multicenter retrospective comparative clinical study

Abstract Objectives This multicenter retrospective study aimed to compare the effects of HES and gelatin (GEL) on the risk of post-OLT AKI. Method A total of 1,672 patients undergoing OLT were enrolled from major transplant centers in China between 2005 and 2013. These patients were divided into three groups: GEL, hydroxyethyl starch (HES), and GEL + HES group. Results There was no significant difference in the incidence of post-OLT AKI among the GEL, HES, and GEL + HES groups. The GEL + HES group had a lower incidence of stage II post-OLT AKI than the other two groups. Compared with patients receiving GEL, patients receiving HES did not harbor an increased risk of AKI. Our results showed that MELD score (adjusted odds ratio [OR], 1.579; 95% confidence interval [CI], 1.123–2.219; P = 0.009) and preoperative anemia (adjusted OR, 1.533; 95% CI, 1.212–1.939; P < 0.001) were independent risk factors for post-OLT AKI, and normal preoperative Scr level (vs abnormal; adjusted OR, 0.402; 95% CI, 0.222–0.729; P = 0.003) was independent protective factors for post-OLT AKI. Conclusion This large-scale multicenter retrospective study found that the intraoperative use of HES did not increase the overall incidence of post-OLT AKI in patients when compared with GEL, and whether to increase the risk of post-OLT AKI needs to be further explored.
Implementing Eco’s Model Reader with Word Embeddings. An Experiment on Facebook Ideological Bots

In semiotics, the concept of model reader is used to describe the felicity conditions of a text, that is, the information and pragmatic competence needed to interpret the text with reference to a hypothesis on its producer’s intention. The model reader permits to formulate inferences about the implicit content of sentences and of the entire text. In this paper we propose to formalize the model reader as a function that takes as inputs a text and a larger context and produces as output what is needed to complete the text’s implicit information, filling up its “blank spaces”. One possible technique to implement this function is word embedding. We performed an experiment in this sense, using the data collected and analyzed by the Tracking Exposed group (TREX) during the Italian 2018 elections. For their study, six blank Facebook profiles were created, each characterized by a political orientation: all profiles followed the same common set of 30 pages, representative of the entire Italian political spectrum at the time, but each profile interacted only with content linked to its distinctive political orientation. TREX’s study of the profiles’ newsfeeds demonstrated that each profile was prompted with an uneven distribution of information sources, biased by its political orientation. For our study, we created six different word spaces, one for each profile. Then we identified a certain number of politically neutral terms and observed the semantic associations of these terms in each word space. To identify the terms, we performed a classification of the entire corpus with the software Iramuteq and selected the most significant terms associated with each cluster. Finally, by performing some operations within each word space, we observed some differences in semantic associations that are coherent with the political orientation of the corresponding profile. These results appear to show that word embedding is a valuable approach for computational text pragmatics, as they can help to model the inferences performed by a certain reader. Also, these results suggest the pertinence of such analyses for the study of filter bubbles resulting from algorithmic personalization.
PFG NMR Study of Diffusion in MFI-Type Zeolites: Evidence of the Existence of Intracrystalline Transport Barriers

The PFG NMR technique is applied to investigate the intracrystalline diffusion of methane and n-butane molecules in MFI-type zeolites at several temperatures (from 123 up to 383 K) and over a wide range of diffusion times (from 2 to 35 ms). The intracrystalline self-diffusion coefficients of the guest molecules recorded at low temperatures were observed to decrease with increasing root-mean-square displacements. The comparison of the experimental results with the results of the Monte Carlo simulations of diffusion allowed us to rule out the restriction of diffusion by crystal boundaries as a possible explanation of the observed dependencies of the diffusivities on the root-mean-square displacement. These dependencies are tentatively attributed to the existence of intracrystalline transport barriers in MFI-type crystals. The intersections between the elementary building blocks of the crystals and/or intergrowth sections of MFI crystals are suggested as the possible candidates for the transport barriers.
Bounded Exhaustive Search of Alloy Specification Repairs

The rising popularity of declarative languages and the hard to debug nature thereof have motivated the need for applicable, automated repair techniques for such languages. However, despite significant advances in the program repair of imperative languages, there is a dearth of repair techniques for declarative languages. This paper presents BeAFix, an automated repair technique for faulty models written in Alloy, a declarative language based on first-order relational logic. BeAFix is backed with a novel strategy for bounded exhaustive, yet scalable, exploration of the spaces of fix candidates and a formally rigorous, sound pruning of such spaces. Moreover, different from the state-of-the-art in Alloy automated repair, that relies on the availability of unit tests, BeAFix does not require tests and can work with assertions that are naturally used in formal declarative languages. Our experience with using BeAFix to repair thousands of real-world faulty models, collected by other researchers, corroborates its ability to effectively generate correct repairs and outperform the state-of-the-art.
DEEP LEARNING OBJECT DETECTION FOR MAPPING CAVE CANDIDATES ON MARS: BUILDING UP THE MARS GLOBAL CAVE CANDIDATE CATALOG (MGC^3)

Introduction: The Mars Global Cave Candidate Catalog (MGC3) v1, published by Cushing et al. [1] in 2017 contains the locations and a short description of more than 1000 possible cave-entrances on Mars that have been identified by manually surveying images acquired by Mars Odyssey’s (MO) Thermal Emission Imaging System (THEMIS) and Mars Reconnaissance Orbiter’s (MRO) Context Camera (CTX) and High Resolution Imaging Science Experiment (HiRISE) cameras. Authors analysed all images that covers the area north of Arsia Mons (235° to 243° E, 28° to 2° N). The Arsia Mons is a shield volcano, located in the southern area of the large Tharsis Region, on whose flanks have been identified at least 7 possible cave entrances in a previous work [2] and thus selected by the authors for creating the MGC3. Since cavities are among the most interesting and valuable targets for space exploration [3][4], extending the investigated area to the whole planet could advance the state of the art and provide potential targets for future mission. Since the datasets involved are very large, with approx. products of 115,897 for CTX and 1,775,440 for HiRISE [5] a manual approach is not feasible. In this respect, computer-assisted techniques that rely mainly on Machine Learning and Deep Learning algorithms are extremely valuables, providing robust, standardized and highly customizable pipelines and tools for analysing automatically large datasets. Deep Learning Object Detection algorithms such [6] were used in this study, with proper training, can detect virtually all pit and cave entrance occurrences.
CLARION: Sound and Clear Provenance Tracking for Microservice Deployments

Linux container-based microservices have emerged as an attractive alternative to virtualization as they reduce application footprints and facilitate more efﬁcient resource utilization. Their popularity has also led to increased scrutiny of the underlying security properties and attack surface of container technology. Provenance-based analysis techniques have been proposed as an effective means toward comprehensive and high-assurance security control as they provide ﬁne-grained mechanisms to track data ﬂows across the system and detect unwanted or unexpected changes to data objects. However, existing provenance tracking techniques are limited in their ability to build sound and clear provenance in container network environments due to complexities introduced by namespace virtualization . We describe a namespace-and container-aware provenance tracking solution, called CLARION, that addresses the unique soundness and clarity challenges introduced by traditional provenance tracking solutions. Speciﬁcally, we ﬁrst describe fragmentation and ambiguities introduced in provenance analysis tools by each of the Linux namespaces and propose solutions to address analysis soundness. Then we discuss the design of specialized semantics-summarization techniques that improve the clarity of provenance analysis. We have developed a prototype implementation of CLARION and evaluate its performance against a spectrum of container-speciﬁc attacks. The results demonstrate the utility of our sys-tem and how it outperforms the state-of-the-art provenance tracking systems by providing an accurate and concise view of data provenance in container environments.
A mixture of Topic Modeling and Network Analysis. The case-study of climate change on Twitter

The paper proposes a semi-automatic labeling of topics extracted with a Topic Model using the tools of Social Network Analysis. The aim is to attach a label to every topic studying the terms-topics network structure. This method performs a semi-automatic topics labelling by using Latent Dirichlet Allocation model, integrating the network approach with topic generative model. LDA allows to extract latent topics and Social Network Analysis’ tools permit to delineate the neighborhood of each topic, fostering a stronger interpretation of the meanings of the topics through the analysis of the extracted topics and documents’ terms. To better show the joint use of Topic Model and Network Analysis, we present a case-study of how young people feel the climate change through the messages of user @Fridays4future extracted by International Fridays For Future Twitter account.
CURARE ALKALOIDS FROM CHONDODENDRON TOMENTOSUM

Crystalline d-tubocurarine has been isolated in good yield from curare prepared from a single plant species, namely, Chondodendron tomentosum. This result establishes with certainty the botanical origin of this compound and substantiates the supposition that it is this species which furnishes the active constituent in certain types of curare. The extract from this plant furthermore yielded two new tertiary alkaloids which could be converted into physiologically active quaternary bases. Methylation of the phenolic hydroxyl groups in the quaternary bases resulted in a 3-9-fold increase in physiological potency.
CrowdSolve

Investigators in fields such as journalism and law enforcement have long sought the public's help with investigations. New technologies have also allowed amateur sleuths to lead their own crowdsourced investigations - that have traditionally only been the purview of expert investigators - with mixed results. Through an ethnographic study of a four-day, co-located event with over 250 attendees, we examine the human infrastructure responsible for enabling the success of an expert-led crowdsourced investigation. We find that the experts enabled attendees to generate useful leads; the attendees formed a community around the event; and the victims' families felt supported. Additionally, the co-located setting, legal structures, and emergent social norms impacted collaborative work practice. We also surface three important tensions to consider in future investigations and provide design recommendations to manage these tensions.
THE CHALLENGE OF IMPLEMENTING THE NATIONAL GENDER EQUALITY NORM IN IT ORGANIZATIONS

Although digitalization across sectors drives an increasing demand for IT specialists, women still make up a small part of computing communities, IT education and work – in the US and across Europe. Our project aims to build knowledge about how this situation can be improved in the context of Nordic gender equality regimes. The "gender equality paradox" is a label for women's underrepresentation in STEM disciplines, particularly in IT, that seems to be more extreme in highly gender egalitarian cultures. It has been suggested that the paradox is a result of women's choices in wealthy countries with a high degree of individual freedom. Our project highlights another side to this paradox, as we explore attitudes towards women's underrepresentation among IT employers and organizations. The analysis reveals mixed signals from the organizations: while they recognize the low proportion of women in IT, they simultaneously negotiate the meaning of women's underrepresentation in IT in ways that do not make gender equality in IT a goal, thus it leaves little space for gender equality actions. While this can have major consequences for women's careers in computing and IT work, it also illustrates a central mechanism of the "gender equality paradox" characterized by a widely accepted norm of gender equality existing alongside employers' skepticism to the goal of gender balance in computing. Here we analyze the organizations' approaches towards gender equality ideals through the notion of "discursive resources", which points to how individuals translate these ideals in light of their own organizational context. Furthermore, this highlights the importance of taking the organizations' "discursive resources" into account when suggesting solutions to increased awareness of and engagement for gender equality in the IT sector.
Interleukin (IL)-33 is dispensable for Schistosoma mansoni worm maturation, egg excretion, and the maintenance of egg-induced pathology in intestines of mice

Background: Schistosomes are trematode worms that dwell in their definitive host’s blood vessels, where females lay eggs that need to be eliminated in the environment with host excreta to maintain their life cycle. Both worms and eggs require type 2 immunity for their maturation and excretion, respectively. However, immune molecules that orchestrate such immunity remain unclear. IL-33 is one of the epithelium-derived cytokines that induce type 2 immunity in tissues. This study aimed at determining its role in the maturation, reproduction, and excretion of S. mansoni eggs, and in the maintenance of egg-induced pathology in the intestines of mice.Methods: Using S. mansoni-infected IL-33-deficient (IL-33-/-) and wild-type (WT) mice, worm morphology, reproduction, and egg excretion were studied at different time points of infection. IL-5 and IL-13 production in spleens and mesenteric lymph nodes were measured. Tissue histology was performed on the terminal ilea of non- and infected mice.Results: Morphology-wise, worms from IL-33-/- and WT mice at the fourth and sixth weeks of infection did not differ. The worms' reproduction, expressed as eggs per worm pair, as well as the excretion of eggs, expressed as the number of eggs in intestinal tissues, did not differ between IL-33-/- and WT mice. In the sixth week of infection, IL-33-/- mice presented impaired type 2 immunity in intestines, characterized by decreased production of IL-5 and IL-13 in mesenteric lymph nodes and fewer inflammatory infiltrates with fewer eosinophils in the ilea. Besides, there was no difference between IL-33-/- and WT mice in the levels of IL-25 and TSLP in intestinal tissues.Conclusions: Despite its ability to initiate type 2 immunity in tissues, IL-33 alone seems dispensable for S. mansoni maturation, reproduction, and egg excretion. The transient impairment of type 2 immunity observed in the intestines, but not spleens, highlights the importance of IL-33 over IL-25 and TSLP in initiating, but not maintaining, locally induced type 2 immunity in intestinal tissues in schistosome infection. Further studies are needed to decipher the role of each of them in schistosomiasis and clarify the possible interactions that might exist between them.
Comparison of Two Approaches to Recommender Systems with Anonymous Purchase Data (short paper)

The paper discusses problem of assessing customer preferences proﬁles for goods oﬀered by retail store. A proﬁle is assessed on the condition that a certain set of goods was previously purchased by the buyer. It is supposed that information about previously purchased products is contained in sales receipt. The trivial technique where preference rating is calculated as common frequency of occurrence of products in sales receipts is compared with a technique using combinations of association rules and a new method involving product clustering at initial stage. Preference rating is at that evaluated by combined feature description that includes the description of the evaluated product and the description of the set of goods present in sales receipt. Feature description of evaluated product is a vector of proximity measures to clusters received by agglomerative hierarchical clustering. Feature description of a set of goods is vector of mean proximity measures between clusters and goods from this set. Gradient boosting method was used to distinguish goods which were and were not actually purchased by combined feature description. At that purchasing probabilities estimates that are returned by recognition algorithm are considered as preference ratings. ROC analysis is used to compare eﬃciency of three techniques.