Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges in Generalization in Open Domain Question Answering

Recent work on Open Domain Question Answering has shown that there is a large discrepancy in model performance between novel test questions and those that largely overlap with training questions. However, it is unclear which aspects of novel questions make them challenging. Drawing upon studies on systematic generalization, we introduce and annotate questions according to three categories that measure different levels and kinds of generalization: training set overlap, compositional generalization (comp-gen), and novel-entity generalization (novel-entity). When evaluating six popular parametric and non-parametric models, we find that for the established Natural Questions and TriviaQA datasets, even the strongest model performance for comp-gen/novel-entity is 13.1/5.4% and 9.6/1.5% lower compared to that for the full test set -- indicating the challenge posed by these types of questions. Furthermore, we show that whilst non-parametric models can handle questions containing novel entities relatively well, they struggle with those requiring compositional generalization. Lastly, we find that key question difficulty factors are: cascading errors from the retrieval component, frequency of question pattern, and frequency of the entity.
Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation

The scarcity of high quality medical image annotations hinders the implementation of accurate clinical applications for detecting and segmenting abnormal lesions. To mitigate this issue, the scientific community is working on the development of unsupervised anomaly detection (UAD) systems that learn from a training set containing only normal (i.e., healthy) images, where abnormal samples (i.e., unhealthy) are detected and segmented based on how much they deviate from the learned distribution of normal samples. One significant challenge faced by UAD methods is how to learn effective low-dimensional image representations that are sensitive enough to detect and segment abnormal lesions of varying size, appearance and shape. To address this challenge, we propose a novel self-supervised UAD pre-training algorithm, named Multi-centred Strong Augmentation via Contrastive Learning (MSACL). MSACL learns representations by separating several types of strong and weak augmentations of normal image samples, where the weak augmentations represent normal images and strong augmentations denote synthetic abnormal images. To produce such strong augmentations, we introduce MedMix, a novel data augmentation strategy that creates new training images with realistic looking lesions (i.e., anomalies) in normal images. The pre-trained representations from MSACL are generic and can be used to improve the efficacy of different types of off-the-shelf state-of-the-art (SOTA) UAD models. Comprehensive experimental results show that the use of MSACL largely improves these SOTA UAD models on four medical imaging datasets from diverse organs, namely colonoscopy, fundus screening and covid-19 chest-ray datasets.
Regularized Tapered Sample Covariance Matrix

Covariance matrix tapers have a long history in signal processing and related fields. Examples of applications include autoregressive models (promoting a banded structure) or beamforming (widening the spectral null width associated with an interferer). In this paper, the focus is on high-dimensional setting where the dimension <inline-formula><tex-math notation="LaTeX">$p$</tex-math></inline-formula> is high, while the data aspect ratio <inline-formula><tex-math notation="LaTeX">$n/p$</tex-math></inline-formula> is low. We propose an estimator called <sc>Tabasco</sc> (TApered or BAnded Shrinkage COvariance matrix) that shrinks the tapered sample covariance matrix towards a scaled identity matrix. We derive optimal and estimated (data adaptive) regularization parameters that are designed to minimize the mean squared error (MSE) between the proposed shrinkage estimator and the true covariance matrix. These parameters are derived under the general assumption that the data is sampled from an unspecified elliptically symmetric distribution with finite 4th order moments (both real- and complex-valued cases are addressed). Simulation studies show that the proposed <sc>Tabasco</sc> outperforms all competing tapering covariance matrix estimators in diverse setups. An application to space-time adaptive processing (STAP) also illustrates the benefit of the proposed estimator in a practical signal processing setup.
Computing Graph Descriptors on Edge Streams

Feature extraction is an essential task in graph analytics. These feature vectors, called graph descriptors, are used in downstream vector-space-based graph analysis models. This idea has proved fruitful in the past, with spectral-based graph descriptors providing state-of-the-art classification accuracy. However, known algorithms to compute meaningful descriptors do not scale to large graphs since: (1) they require storing the entire graph in memory, and (2) the end-user has no control over the algorithm’s runtime. In this article, we present streaming algorithms to approximately compute three different graph descriptors capturing the essential structure of graphs. Operating on edge streams allows us to avoid storing the entire graph in memory, and controlling the sample size enables us to keep the runtime of our algorithms within desired bounds. We demonstrate the efficacy of the proposed descriptors by analyzing the approximation error and classification accuracy. Our scalable algorithms compute descriptors of graphs with millions of edges within minutes. Moreover, these descriptors yield predictive accuracy comparable to the state-of-the-art methods but can be computed using only 25% as much memory.
Domains of Convergence for Polyhedral Packings

Polyhedral circle packings are generalizations of the Apollonian packing. We develop the theory of the Apollonian group, Descartes quadratic form, and related objects for all polyhedral packings. We use these tools to determine the domain of absolute convergence of a generating function that can be associated to any polyhedral packing. This domain of convergence is the Tits cone for an infinite root system.
Evaluation of the impact of bottom-up and top-down approaches on daily activities in people with neglet – a systematic review

| BACKGROUND: Currently there is no consensus on which are the characteristics of rehabilitation approaches (bottom-up or top-down) most effective in the rehabilitation of ADLs in people with Neglet Syndrome (NS). AIM: To characterize the approaches (bottomup or top-down) with more impact on ADLs in adults and elderly with NS. METHODS: This systematic review was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Metaanalyses (PRISMA) recommendation. A bibliographic search was carried out in PubMed, Web of Science, PEDro and Cochrane databases. Experimental studies were considered in which at least one technique of the bottom-up and top-down approaches was used. The Joanna Briggs Institute Critical Appraisal Checklist for RCTs tool was used to assess the methodological quality of the studies. The following combination of keywords was used: Negligence Syndrome OR Unilateral Syndrome OR Negligence (.) AND Activities OF Daily OR Daily Life (.) AND Treatment OR Intervention OR Technique (.). RESULTS: 16 studies were included, which 9 include techniques from the bottom-up approach, 6 include techniques from the top-down approach and 1 article includes two techniques, each belonging to each approach. The techniques of the bottom-up approach that increased independence in the ADLs were Visuomotor Feedback Training, Smooth Pursuit Eye Movement Training and the combination of Eye Patching with Constraint-induced Therapy. In the top-down approach, the techniques with the same results were Visual Scanning, Mental Practice, Continuous Theta Burst Stimulation and Transcranial Direct Current Stimulation. CONCLUSION: Both bottom-up and top-down approaches increase independence in ADLs. Each approach contains techniques with a significant positive impact on ADLs such as Visuomotor Feedback Training and Continuous Theta Burst Stimulation. The present work also allowed a critical analysis to the classification of the approaches in bottom-up and top-down, since they are not different to the category of rehabilitation mechanisms.
Surface chemical composition and roughness as factors affecting the wettability of thermo-mechanically modified oak (Quercus robur L.)

Abstract European oak wood (W) was thermo-mechanically modified (TM) via densifying at 100 and 150°C and the surface properties of the TMW were investigated. The contact angle (CA) of the wood with the reference liquids water and diiodomethane was determined using the sessile drop method. The surface free energy of the TMW on tangential sections within the first 60 s after applying a drop was analyzed. The roughness parameters Ra and Rz parallel (‖) and perpendicular (⊥) to the grain were investigated. The wettability analysis showed that densified wood had a higher CA and lower work of adhesion and surface free energy than non-densified wood. An X-ray photoelectron spectroscopy [XPS or electron spectroscopy for chemical analysis (ESCA)] analysis showed that the oxygen to carbon atoms ratio (O/C ratio) of densified wood surface was lower than that of non-densified wood. The carbon C1-C2 atoms ratio (C1/C2 ratio) increased with increasing TM temperature. The results were interpreted as being that extractives migrate to the surface and amorphous and glassy polymers, i.e. lignin and hemicelluloses, in wood are rearranged. Increasing densification temperature makes TMW surfaces more hydrophobic.
SBAR (Situation, Background, Assessment, Recomendation) Communication on Attitude And Nursing Behavior in Improving Patient Safety

SBAR (Situation, Backgroud, Assessment, Recomendation) communication is an information tool that provides a structured or systematic method that facilitates communication between health workers. SBAR communication is easy because communication has been systematically structured to report the condition of patients to other health workers so as to improve patient safety by reducing errors that occur during the action. The purpose of this study was to determine the effect of SBAR communication on nurses’ attitudes and behavior in improving patient safety. The type of research used was quasi experiment with pre-posttest with control group design, the results of the study were processed by paired sample t test and independent samples t test, SBAR communication instruments using observation, attitude and behavior instruments of nurses using questionnaires. The population in the study of all nurses who served in the inpatient room is ivory 1, ivory 2, flamboyant, dahliah RAA Soewondo Pati Hospital as many as 48 nurses, the sampling technique in the study was a total sampling of 48 nurses. There was a significant difference in nurses’ attitudes after being given SBAR communication training in the intervention group with a p value of 0,000 compared to the control group with a p value of 0.103. There was a significant difference in the nurses’ behavior after being given SBAR communication training in the intervention group with a p value of 0,000 compared to the control group with a p value of 0.198.
Extent of Integration in Agriculture Supply Chain: The Public Sector Stakeholders Perspective

Nadir Munir Hassan, Muhammad Nauman Abbasi Department of Business Administration, Air University, Multan, Pakistan, nadir.magsi@aumc.edu. pk Institute of Management Sciences, Bahauddin Zakariya University, Multan, Pakistan, abbasimna@bzu.edu. pk ARTICLE DETAILS ABSTRACT History Revised format: November 2020 Available Online: December 2020 Purpose: Integrating network factors (i.e. Actors, Activities, and Resources), help organizations in achieving superior supply chain performance. Despite reasonable evidence on positive relationship between SCI and SCP, there exists sufficient contradiction on universal integration of chains. This paper is a qualitative exploratory study, which based on the network perspective intends to explore the current and required levels of supply chain integration among actors, activities, and resources in the agriculture supply chain of Pakistan. Design/Methodology/Approach: The data was collected through in depth semi-structured interviews from public sector stake holders of agriculture sector (i.e. From Thirteen wings of Ministry of Agriculture) across Pakistan. The current and required extent of supply chain integration was measured at three levels, i.e. strategic (long-term), tactical (medium-term) and operational (short-term) as suggested by (Childerhouse & Towill, 2011). Findings: The research results indicate that the relationship between supply chain integration and supply chain performance is a contextual phenomenon and significantly varies among Network factors. This study and its findings are expected to add into the literature of supply chain integration and its impact on supply chain performance.
Environmental Uncertainty as a Moderator of Entrepreneurship Orientation and Innovation Capability during the Pandemic: A Case of Written Batik SMEs in Yogyakarta

Background: Written batik is one of Indonesia's cultural heritages that must be preserved. During the Covid-19 pandemic, written batik producers in Indonesia experienced increasing challenges due to the uncertainty of the business environment. Innovation is a solution to the problems faced by SMEs during a pandemic to survive. This study aims to examine the effect of entrepreneurship orientation on innovation capability. This study also examines the role of moderating environmental uncertainty in strengthening the effect of entrepreneurship orientation on innovation capability. Methods: The research was conducted at the centre of small and medium-sized batik companies Giriloyo, Bantul, Yogyakarta, Indonesia. Respondents of this study were 130 small and medium companies selected by random sampling. The questionnaire is used as a primary data collection tool. WarpPLS has been used to analyze the effect between variables in this study. Results: Entrepreneurship orientation is an important aspect in improving the innovation capabilities of SMEs. Environmental uncertainty during the COVID-19 pandemic has strengthened the effect of entrepreneurship orientation on innovation capabilities. Conclusions: The findings of this study indicate that entrepreneurship orientation has a significant effect on innovation capabilities. Environmental uncertainty significantly strengthens the effect of entrepreneurship orientation on innovation capability.
When Brands Go Dark

Because of various financial reasons, or a change in strategic focus, sometimes brands stop broad-reach media advertising for a year or longer. These long dark periods have not been subject to much study, so little is known about the likely consequences. This exploratory study addresses this omission by documenting the sales performance of 41 beer, cider, and spirit brands that advertised intermittently over almost two decades. Changes in aggregate brand sales are reported for the years when brands stopped advertising relative to the last advertised year. On average, brand sales declined immediately in the first year and every subsequent year of advertising cessation. Decline generally was faster for smaller brands and for brands that already were declining in sales before advertising cessation.
Proximal analysis of chihua pumpkins accessions in the Yucatán Peninsula

Technological Institute of Chiná. Street s/n between 22 and 28, Campeche, México. CP. 24520. Tel. 981 8272082, ext. 103. (betymonic@hotmail.com; jlruiz15@hotmail.com, rolito22@hotmail.com). Edzná Experimental Field-INIFAP. Campeche-Pocyaxum Highway km 15.5, Campeche, México. CP. 24520. Tel. 55 38718700, ext. 100 y 310. Mococha Experimental Field-INIFAP. Mérida-Motul Highway km 25, Mococha, Yucatán, México. CP. 97454. Tel. 55 38718700, ext. 88216 y 88213. (rangel.alma@inifap.gob.mx). Chetumal Experimental Field-INIFAP. Chetumal-Bacalar Highway km 25, Othón Blanco, Quintana Roo, México. CP. 77000. Tel. 55 38718700, ext. 88411. (garcia.angel@inifap.gob.mx).
O-Glycosylation Landscapes of SARS-CoV-2 Spike Proteins

The densely glycosylated spike (S) proteins that are highly exposed on the surface of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) facilitate viral attachment, entry, and membrane fusion. We have previously reported all the 22 N-glycosites and site-specific N-glycans in the S protein protomer. Herein, we report the O-glycosylation landscapes of SARS-CoV-2 S proteins, which were characterized through high-resolution mass spectrometry. Following digestion with trypsin and trypsin/Glu-C, and de-N-glycosylation using PNGase F, we determined the GalNAc-type O-glycosylation pattern of S proteins, including O-glycosites and the six most common O-glycans occupying them, via Byonic identification and manual validation. Finally, 255 intact O-glycopeptides composed of 50 peptides sequences and 43 O-glycosites were discovered by higher energy collision-induced dissociation (HCD), and three O-glycosites were confidently identified by electron transfer/higher energy collision-induced dissociation (EThcD) in the insect cell-expressed S protein. Most glycosites were modified by non-sialylated O-glycans such as HexNAc(1) and HexNAc(1)Hex (1). In contrast, in the human cell-expressed S protein S1 subunit, 407 intact O-glycopeptides composed of 34 peptides sequences and 30 O-glycosites were discovered by HCD, and 11 O-glycosites were unambiguously assigned by EThcD. However, the measurement of O-glycosylation occupancy hasn’t been made. Most glycosites were modified by sialylated O-glycans such as HexNAc(1)Hex (1)NeuAc (1) and HexNAc(1)Hex (1)NeuAc (2). Our results reveal that the SARS-CoV-2 S protein is an O-glycoprotein; the O-glycosites and O-glycan compositions vary with the host cell type. These comprehensive O-glycosylation landscapes of the S protein are expected to provide novel insights into the viral binding mechanism and present a strategy for the development of vaccines and targeted drugs.
Properdin Deficiency Impairs Phagocytosis and Enhances Injury at Kidney Repair Phase Post Ischemia–Reperfusion

Properdin, a positive regulator of complement alternative pathway, participates in renal ischemia–reperfusion (IR) injury and also acts as a pattern-recognition molecule affecting apoptotic T-cell clearance. However, the role of properdin in tubular epithelial cells (TECs) at the repair phase post IR injury is not well defined. This study revealed that properdin knockout (PKO) mice exhibited greater injury in renal function and histology than wild-type (WT) mice post 72-h IR, with more apoptotic cells and macrophages in tubular lumina, increased active caspase-3 and HMGB1, but better histological structure at 24 h. Raised erythropoietin receptor by IR was furthered by PKO and positively correlated with injury and repair markers. Properdin in WT kidneys was also upregulated by IR, while H2O2-increased properdin in TECs was reduced by its small-interfering RNA (siRNA), with raised HMGB1 and apoptosis. Moreover, the phagocytic ability of WT TECs, analyzed by pHrodo Escherichia coli bioparticles, was promoted by H2O2 but inhibited by PKO. These results were confirmed by counting phagocytosed H2O2-induced apoptotic TECs by in situ end labeling fragmented DNAs but not affected by additional serum with/without properdin. Taken together, PKO results in impaired phagocytosis at the repair phase post renal IR injury. Properdin locally produced by TECs plays crucial roles in optimizing damaged cells and regulating phagocytic ability of TECs to effectively clear apoptotic cells and reduce inflammation.
Persuasive Features of Scientific Explanations: Explanatory Schemata of Physical and Psychosocial Phenomena

Explanations are central to understanding the causal relationships between entities within the environment. Instead of examining basic heuristics and schemata that inform the acceptance or rejection of scientific explanations, recent studies have predominantly examined complex explanatory models. In the present study, we examined which essential features of explanatory schemata can account for phenomena that are attributed to domain-specific knowledge. In two experiments, participants judged the validity of logical syllogisms and reported confidence in their response. In addition to validity of the explanations, we manipulated whether scientists or people explained an animate or inanimate phenomenon using mechanistic (e.g., force, cause) or intentional explanatory terms (e.g., believes, wants). Results indicate that intentional explanations were generally considered to be less valid than mechanistic explanations and that ‘scientists’ were relatively more reliable sources of information of inanimate phenomena whereas ‘people’ were relatively more reliable sources of information of animate phenomena. Moreover, after controlling for participants’ performance, we found that they expressed greater overconfidence for valid intentional and invalid mechanistic explanations suggesting that the effect of belief-bias is greater in these conditions.
The Ability of Zika virus Intravenous Immunoglobulin to Protect From or Enhance Zika Virus Disease

The closely related flaviviruses, dengue and Zika, cause significant human disease throughout the world. While cross-reactive antibodies have been demonstrated to have the capacity to potentiate disease or mediate protection during flavivirus infection, the mechanisms responsible for this dichotomy are still poorly understood. To understand how the human polyclonal antibody response can protect against, and potentiate the disease in the context of dengue and Zika virus infection we used intravenous hyperimmunoglobulin (IVIG) preparations in a mouse model of the disease. Three IVIGs (ZIKV-IG, Control-Ig and Gamunex®) were evaluated for their ability to neutralize and/or enhance Zika, dengue 2 and 3 viruses in vitro. The balance between virus neutralization and enhancement provided by the in vitro neutralization data was used to predict the IVIG concentrations which could protect or enhance Zika, and dengue 2 disease in vivo. Using this approach, we were able to define the unique in vivo dynamics of complex polyclonal antibodies, allowing for both enhancement and protection from flavivirus infection. Our results provide a novel understanding of how polyclonal antibodies interact with viruses with implications for the use of polyclonal antibody therapeutics and the development and evaluation of the next generation flavivirus vaccines.