Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximal Multipolarized Cliques Search in Signed Networks

The increasing of group polarization on social media seriously impacts on the health of public discourse and information dissemination. At present, detecting polarized structures in signed networks is well-motivated for studying the group polarization on social media. However, most studies restricted the number of polarized structures to only two, while neglecting the real-world scenario where signed networks consist of multiple polarized structures, that is an unreasonable assumption. To conquer the limitations of the existing work, in this paper, we present a novel cohesive subgraph model based on structural clusterable theory, named maximal multipolarized clique (MMC), which can be partitioned into k polarized subcliques such that the edges in subcliques are positive and the edges between subcliques are negative. This paper formulates the problem of Maximal Multipolarized Cliques Search (MMCS) in signed networks which is proved to be NP-hard. To address this problem, we first devise powerful pruning rules to reduce the signed network significantly and further develop an efficient algorithm to search all maximal multipolarized cliques in the reduced signed network. The experimental results on real-world signed networks demonstrate the efficiency and effectiveness of our algorithm.
Exploratory Design of a Hands-free Video Game Controller for a Quadriplegic Individual

From colored pixels to hyper-realistic 3D landscapes of virtual reality, video games have evolved immensely over the last few decades. However, video game input still requires two-handed dexterous finger manipulations for simultaneous joystick and trigger or mouse and keyboard presses. In this work, we explore the design of a hands-free game control method using realtime facial expression recognition for individuals with neurological and neuromuscular diseases who are unable to use traditional game controllers. Similar to other Assistive Technologies (AT), our facial input technique is also designed and tested in collaboration with a graduate student who has Spinal Muscular Atrophy. Our preliminary evaluation shows the potential of facial expression recognition for augmenting the lives of quadriplegic individuals by enabling them to accomplish things like walking, running, flying or other adventures that may not be so attainable otherwise.
Communication Efficient Distributed Hypergraph Clustering

Hypergraphs can capture higher-order relations between subsets of objects instead of only pairwise relations as in graphs. Hypergraph clustering is an important task in information retrieval and machine learning. We study the problem of distributed hypergraph clustering in the message passing communication model using small communication cost. We propose an algorithm framework for distributed hypergraph clustering based on spectral hypergraph sparsification. For an n-vertex hypergraph G with hyperedges of maximum size r distributed at s sites arbitrarily and a parameter ε∈ (0,1), our algorithm can produce a vertex set with conductance O(√1+ε/1-ε √φG), where φG is the conductance of G, using communication cost ~O(nr2s/εO(1)) (~O hides a polylogarithmic factor). The theoretical results are complemented with extensive experiments to demonstrate the efficiency and effectiveness of the proposed algorithm under different real-world datasets. Our source code is publicly available at github.com/chunjiangzhu/dhgc.
PECAN: A Platform for Searching Chat Conversations

Often, existing chat services that organisations and individuals use today provide a way to search through previously sent messages. However, many of these chat services provide far-limited search functionalities, typically exact matching on individual messages. In this paper, we introduce a new task for addressing this problem, called searching for conversations, whereby the aim is to retrieve and rank groups of related messages given a search query. We promote this task by providing a platform for research and development called PECAN. Our platform provides all the necessary functionality researchers need to conduct experiments on searching for conversations. Our system is also generic so as to support organisations and individuals who wish to search through their chat message archives. We release PECAN to the wider community as an Open Source project available for download at https://github.com/ielab/pecan.
The Winner Takes it All: Geographic Imbalance and Provider (Un)fairness in Educational Recommender Systems

Educational recommender systems channel most of the research efforts on the effectiveness of the recommended items. While teachers have a central role in online platforms, the impact of recommender systems for teachers in terms of the exposure such systems give to the courses is an under-explored area. In this paper, we consider data coming from a real-world platform and analyze the distribution of the recommendations w.r. t. the geographical provenience of the teachers. We observe that data is highly imbalanced towards the United States, in terms of offered courses and of interactions. These imbalances are exacerbated by recommender systems, which overexpose the country w.r. t. its representation in the data, thus generating unfairness for teachers outside that country. To introduce equity, we propose an approach that regulates the share of recommendations given to the items produced in a country (visibility) and the position of the items in the recommended list (exposure).
Evaluating the Predictivity of IR Experiments

Experimental evaluation is regarded as a critical element of any research activity in Information Retrieval, and is typically used to support assertions of the form "Technique A provides better retrieval effectiveness than does Technique B". Implicit in such claims are the characteristics of the data to which the results apply, in terms of both the queries used and the documents they were applied to. Here we explore the role of evaluation on a collection as a prediction of relative performance on collections that have different characteristics. In particular, by synthesizing new collections that vary from each other in a controlled way, we show that it is possible to explore the reliability of an IR evaluation pipeline, and to better understand the complex interrelationship between documents, queries, and metrics that is an important part of any experimental validation. Our results show that predictivity declines as the collection is varied, even in simple ways such as shifting in focus from one document source to another similar source.
PAN: Prototype-based Adaptive Network for Robust Cross-modal Retrieval

In practical applications of cross-modal retrieval, test queries of the retrieval system may vary greatly and come from unknown category. Meanwhile, due to the cost and difficulty of data collection as well as other issues, the available data for cross-modal retrieval are often imbalanced over different modalities. In this paper, we address two important issues to increase the robustness of cross-modal retrieval system for real-world applications: handling test queries from unknown category and modality-imbalanced training data. The first issue has not been addressed by existing methods and the second issue was not well addressed in the related research. To tackle the above issues, we take the advantage of prototype learning, and propose a prototype-based adaptive network (PAN) for robust cross-modal retrieval. Our method leverages a unified prototype to represent each semantic category across modalities, which provides discriminative information of different categories and takes unified prototypes as anchors to learn cross-modal representations adaptively. Moreover, we propose a novel prototype propagation strategy to reconstruct balanced representations which preserves the semantic consistency and modality heterogeneity. Experimental results on the benchmark datasets demonstrate the effectiveness of our method compared to the SOTA methods, and further robustness tests show the superiority of our method in solving the above issues.
A Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers

Named entity processing over historical texts is more and more being used due to the massive documents and archives being stored in digital libraries. However, due to the poor annotated resources of historical nature, information extraction performances fall behind those on contemporary texts. In this paper, we introduce the development of the NewsEye resource, a multilingual dataset for named entity recognition and linking enriched with stances towards named entities. The dataset is comprised of diachronic historical newspaper material published between 1850 and 1950 in French, German, Finnish, and Swedish. Such historical resource is essential in the context of developing and evaluating named entity processing systems. It evenly allows enhancing the performances of existing approaches on historical documents which enables adequate and efficient semantic indexing of historical documents on digital cultural heritage collections.
Efficient Exciton Relaxation and Charge Generation in Nearly Monochiral (7,5) Carbon Nanotube/C60 Thin-Film Photovoltaics

We report on photovoltaic diodes based on bilayer heterojunctions between nearly monochiral, polymer wrapped (7,5) semiconducting carbon nanotube photoabsorbing films and C60. The internal quantum efficiencies (IQEs) for exciton dissociation and subsequent charge collection at the nanotubes’ visible E22 and near-infrared E11 and E11 + X resonances are 84% ± 7%, 85% ± 5%, and 84% ± 14%, respectively. The high IQE at each transition shows that recombination losses during relaxation and/or direct dissociation of “hot” E11 + X and E22 excitons are negligible. A peak external quantum efficiency (EQE) of 34% is achieved at the E11 transition. Zero-bias photoresponsivity is invariant up to short-circuit current densities of at least 23 mA cm–2, indicating negligible losses via trion, charge-exciton, and charge–charge recombination relaxation pathways. An open circuit voltage of 0.49 V and power conversion efficiency of 7.1% are achieved in response to monochromatic excitation of the diodes at the E11 transition.
Case Report: Uroenteric Fistula in a Pediatric-en-bloc Kidney Transplant Manifests as Deceptive Watery Diarrhea and Normal Anion Gap Acidosis

Introduction: The diagnosis of a post–surgical uroenteric fistula can be challenging and may be delayed for months after symptoms begin. A normal anion gap metabolic acidosis has been reported in up to 100% of patients after ureterosigmoidostomy, and bladder substitution using small bowel and/or colonic segments. Here, we describe a rare case of a pediatric patient who developed a uroenteric fistula from the transplant ureters into the small bowel, after an en-bloc kidney transplantation resulting in profound acidosis and deceptive watery diarrhea. Case Presentation: The patient is an 8-year-old girl with end stage kidney disease (ESKD) secondary to focal segmental glomerulosclerosis. Through a right retroperitoneal approach, she underwent a right native nephrectomy and a pediatric deceased donor en-bloc kidney transplant including two separate ureters. One month later, she had a renal allograft biopsy for suspected rejection. During the week after the biopsy, she experienced abdominal pain followed by watery diarrhea and metabolic acidosis requiring continuous bicarbonate/acetate infusions. An extensive gastro-intestinal evaluation for the cause of the diarrhea including endoscopy was inconclusive. The urine output decreased to <500 ml daily; although, the kidney function remained normal. After 2 weeks of unexplained watery diarrhea a magnetic resonance urogram with contrast was performed which demonstrated extravasation of urine from both ureters with fistulization into the small bowel. She underwent corrective surgery which identified the fistulous tract, which was resected and both ureters were re-implanted. The diarrhea and acidosis resolved, and she has maintained normal renal allograft function for over 1 year. Conclusion: An important aspect in the early diagnosis of a uroenteric fistula is the sudden onset of severe hyperchloremic metabolic acidosis that results when urine is diverted into the intestinal tract. The mechanism is similar to that described in cases of urinary diversions and/or bladder augmentation using the intestine. Important diagnostic tools are the measurements of solute excretion and pH in the urine as compared to the “watery diarrhea” or bowel output. Summary: We describe a case of a uroenteric fistula in a pediatric-en-bloc kidney transplant patient that went undiagnosed for almost 3 weeks due to the deceptive nature of the watery diarrhea which was actually urine. A uroenteric fistula should be considered in the differential diagnosis of diarrhea and hyperchloremic metabolic acidosis as a complication of kidney transplant. The simultaneous comparison of stool and urine pH and solute excretions may lead to the diagnosis, appropriate imaging and surgical intervention.
Cost-Effectiveness Analysis of High-Risk Groups Tuberculosis Screening in Malaysia

Screening of high-risk groups for Tuberculosis (TB) is considered as the cornerstone for TB elimination but the measure of cost-effectiveness is also crucial in deciding the strategy for TB screening. This study aims to measure the cost-effectiveness of TB screening between the various high-risk groups in Malaysia. A decision tree model was developed to assess the cost-effectiveness of TB screening among the high-risk groups from a provider perspective using secondary data from the year 2016 to 2018. The results are presented in terms of an Incremental Cost-Effectiveness Ratio (ICER), expressed as cost per TB case detected. Deterministic and Probabilistic Sensitivity Analysis was also performed to measure the robustness of the model. TB screening among Person Living with Human Immunodeficiency Virus (PL HIV) was the most cost-effective strategy, with MYR 2,597.00 per TB case detected. This was followed by elderly, prisoners and smokers with MYR 2,868.62, MYR 3,065.24, and MYR 4,327.76 per one TB case detected, respectively. There was an incremental cost of MYR 2.49 per screening, and 3.4 TB case detection per 1,000 screening for TB screening among PL HIV in relation to TB screening among prisoners. The probability of symptomatic cases diagnosed as TB was the key driver for increasing cost-effectiveness efficacy among PL HIV. Results of the study suggest prioritization of high-risk group TB screening program by focusing on the most cost-effective strategy such as screening among PL HIV, prisoners and elderly, which has a lower cost per TB case detected.
Shared Pathogenetic Features Between Common Variable Immunodeficiency and Sjögren’s Syndrome: Clues for a Personalized Medicine

Common variable immunodeficiency disorders (CVID) are a group of rare diseases of the immune system and the most common symptomatic primary antibody deficiency in adults. The “variable” aspect of CVID refers to the approximately half of the patients who develop non-infective complications, mainly autoimmune features, in particular organ specific autoimmune diseases including thyroiditis, and cytopenias. Among these associated conditions, the incidence of lymphoma, including mucosal associated lymphoid tissue (MALT) type, is increased. Although these associated autoimmune disorders in CVID are generally attributed to Systemic Lupus Erythematosus (SLE), we propose that Sjogren’s syndrome (SS) is perhaps a better candidate for the associated disease. SS is an autoimmune disorder characterized by the lymphocytic infiltrates of lacrimal and salivary glands, leading to dryness of the eyes and mouth. Thus, it is a lymphocyte aggressive disorder, in contrast to SLE where pathology is generally attributed to auto-antibody and complement activation. Although systemic lupus erythematosus (SLE) shares these features with SS, a much higher frequency of MALT lymphoma distinguishes SS from SLE. Also, the higher frequency of germ line encoded paraproteins such as the monoclonal rheumatoid factor found in SS patients would be more consistent with the failure of B-cell VDJ switching found in CVID; and in contrast to the hypermutation that characterizes SLE autoantibodies. Thus, we suggest that SS may fit as a better “autoimmune” association with CVID. Examining the common underlying biologic mechanisms that promote lymphoid infiltration by dysregulated lymphocytes and lymphoma in CVID may provide new avenues for treatment in both the diseases. Since the diagnosis of SLE or rheumatoid arthritis is usually based on specific autoantibodies, the associated autoimmune features of CVID patients may not be recognized in the absence of autoantibodies.
Online Noise as Illustrated by Pitfalls and Biogeography Associated With Common Names for Puma concolor

Noise is the non-target search results that people encounter when searching for a particular topic of interest; it is also the cloud of distracting data that can obscure or deflect conservation communication. Online noise associated with large carnivores is particularly dense because their defining characteristics make them salient. Mountain lions (Puma concolor) exemplify noise associated with multiple vernaculars for a species in the crosshairs of conservation conundrums. We compared internet search results, Google Trends reflecting topic interest, use in science publications and sentiment in print and online media for P. concolor's most frequent vernacular names, “mountain lion,” “cougar,” “puma” and “Florida panther. ” Puma and panther exhibited greater noise and salience than cougar or mountain lion, but, results for mountain lion, followed by cougar, yielded the highest biological relevance. Online sentiment negatively correlated with biological relevance, with positive sentiment highest for the noisiest vernaculars, puma and panther. As conservation practitioners, we must recognize that public outreach is part of our scientific agenda and be conscious of crafting communication that reaches and resonates with our intended audiences.
Developing Bioprospecting Strategies for Bioplastics Through the Large-Scale Mining of Microbial Genomes

The accumulation of petroleum-based plastic waste has become a major issue for the environment. A sustainable and biodegradable solution can be found in Polyhydroxyalkanoates (PHAs), a microbially produced biopolymer. An analysis of the global phylogenetic and ecological distribution of potential PHA producing bacteria and archaea was carried out by mining a global genome repository for PHA synthase (PhaC), a key enzyme involved in PHA biosynthesis. Bacteria from the phylum Actinobacteria were found to contain the PhaC Class II genotype which produces medium-chain length PHAs, a physiology until now only found within a few Pseudomonas species. Further, several PhaC genotypes were discovered within Thaumarchaeota, an archaeal phylum with poly-extremophiles and the ability to efficiently use CO2 as a carbon source, a significant ecological group which have thus far been little studied for PHA production. Bacterial and archaeal PhaC genotypes were also observed in high salinity and alkalinity conditions, as well as high-temperature geothermal ecosystems. These genome mining efforts uncovered previously unknown candidate taxa for biopolymer production, as well as microbes from environmental niches with properties that could potentially improve PHA production. This in silico study provides valuable insights into unique PHA producing candidates, supporting future bioprospecting efforts toward better targeted and relevant taxa to further enhance the diversity of exploitable PHA production systems.
Mechanical Overloading Induced-Activation of mTOR Signaling in Tendon Stem/Progenitor Cells Contributes to Tendinopathy Development

Despite the importance of mechanical loading in tendon homeostasis and pathophysiology, the molecular responses involved in the mechanotransduction in tendon cells remain unclear. In this study, we found that in vitro mechanical loading activated the mammalian target of rapamycin (mTOR) in rat patellar tendon stem/progenitor cells (TSCs) in a stretching magnitude-dependent manner. Application of rapamycin, a specific inhibitor of mTOR, attenuated the phosphorylation of S6 and 4E-BP1 and as such, largely inhibited the mechanical activation of mTOR. Moreover, rapamycin significantly decreased the proliferation and non-tenocyte differentiation of PTSCs as indicated by the reduced expression levels of LPL, PPARγ, SOX-9, collagen II, Runx-2, and osteocalcin genes. In the animal studies, mice subjected to intensive treadmill running (ITR) developed tendon degeneration, as evidenced by the formation of round-shaped cells, accumulation of proteoglycans, and expression of SOX-9 and collagen II proteins. However, daily injections of rapamycin in ITR mice reduced all these tendon degenerative changes. Collectively, these findings suggest that mechanical loading activates the mTOR signaling in TSCs, and rapamycin may be used to prevent tendinopathy development by blocking non-tenocyte differentiation due to mechanical over-activation of mTOR in TSCs.
Downregulation of ATXN3 Enhances the Sensitivity to AKT Inhibitors (Perifosine or MK-2206), but Decreases the Sensitivity to Chemotherapeutic Drugs (Etoposide or Cisplatin) in Neuroblastoma Cells

Background Chemotherapy resistance is the major cause of failure in neuroblastoma (NB) treatment. ATXN3 has been linked to various types of cancer and neurodegenerative diseases; however, its roles in NB have not been established. The aim of our study was to explore the role of ATXN3 in the cell death induced by AKT inhibitor (perifosine or MK-2206) or chemotherapy drugs (etoposide or cisplatin) in NB cells. Methods The expressions of ATXN3 and BCL-2 family members were detected by Western blot. Cell survival was evaluated by CCK8, cell confluence was measured by IncuCyte, and apoptosis was detected by flow cytometry. AS and BE2 were treated with AKT inhibitors or chemotherapeutics, respectively. Results Downregulation of ATXN3 did not block, but significantly increased the perifosine/MK-2206-induced cell death. Among the BCL-2 family members, the expression of pro-apoptotic protein BIM and anti-proapoptotic protein Bcl-xl expression increased significantly when ATXN3 was down-regulated. Downregulation of BIM protected NB cells from the combination of perifosine/MK-2206 and ATXN3 downregulation. Downregulation of ATXN3 did not increase, but decrease the sensitivity of NB cells to etoposide/cisplatin, and knockdown of Bcl-xl attenuated this decrease in sensitivity. Conclusion Downregulation of ATXN3 enhanced AKT inhibitors (perifosine or MK-2206) induced cell death by BIM, but decreased the cell death induced by chemotherapeutic drugs (etoposide or cisplatin) via Bcl-xl. The expression of ATXN3 may be an indicator in selecting different treatment regimen.
EOGNET: A Novel Deep Learning Model for Sleep Stage Classification Based on Single-Channel EOG Signal

In recent years, automatic sleep staging methods have achieved competitive performance using electroencephalography (EEG) signals. However, the acquisition of EEG signals is cumbersome and inconvenient. Therefore, we propose a novel sleep staging approach using electrooculogram (EOG) signals, which are more convenient to acquire than the EEG. A two-scale convolutional neural network first extracts epoch-wise temporary-equivalent features from raw EOG signals. A recurrent neural network then captures the long-term sequential information. The proposed method was validated on 101 full-night sleep data from two open-access databases, the montreal archive of sleep studies and Sleep-EDF, achieving an overall accuracy of 81.2 and 76.3%, respectively. The results are comparable to those models trained with EEG signals. In addition, comparisons with six state-of-the-art methods further demonstrate the effectiveness of the proposed approach. Overall, this study provides a new avenue for sleep monitoring.