Miracle-dz/UniFAR-FTUs huggingface dataset:
OOWL500: Overcoming Dataset Collection Bias in the Wild

The hypothesis that image datasets gathered online"in the wild"can produce biased object recognizers, e.g. preferring professional photography or certain viewing angles, is studied. A new"in the lab"data collection infrastructure is proposed consisting of a drone which captures images as it circles around objects. Crucially, the control provided by this setup and the natural camera shake inherent to flight mitigate many biases. It's inexpensive and easily replicable nature may also potentially lead to a scalable data collection effort by the vision community. The procedure's usefulness is demonstrated by creating a dataset of Objects Obtained With fLight (OOWL). Denoted as OOWL500, it contains 120,000 images of 500 objects and is the largest"in the lab"image dataset available when both number of classes and objects per class are considered. Furthermore, it has enabled several of new insights on object recognition. First, a novel adversarial attack strategy is proposed, where image perturbations are defined in terms of semantic properties such as camera shake and pose. Indeed, experiments have shown that ImageNet has considerable amounts of pose and professional photography bias. Second, it is used to show that the augmentation of in the wild datasets, such as ImageNet, with in the lab data, such as OOWL500, can significantly decrease these biases, leading to object recognizers of improved generalization. Third, the dataset is used to study questions on"best procedures"for dataset collection. It is revealed that data augmentation with synthetic images does not suffice to eliminate in the wild datasets biases, and that camera shake and pose diversity play a more important role in object recognition robustness than previously thought.
Multi-Attributed and Structured Text-to-Face Synthesis

Generative Adversarial Networks (GANs) have revolutionized image synthesis through many applications like face generation, photograph editing, and image super-resolution. Image synthesis using GANs has predominantly been uni-modal, with few approaches that can synthesize images from text or other data modes. Text-to-image synthesis, especially text-to-face synthesis, has promising use cases of robust face-generation from eye witness accounts and augmentation of the reading experience with visual cues. However, only a couple of datasets provide consolidated face data and textual descriptions for text-to-face synthesis. Moreover, these textual annotations are less extensive and descriptive, which reduces the diversity of faces generated from it. This paper empirically proves that increasing the number of facial attributes in each textual description helps GANs generate more diverse and real-looking faces. To prove this, we propose a new methodology that focuses on using structured textual descriptions. We also consolidate a Multi-Attributed and Structured Text-to-face (MAST) dataset consisting of high-quality images with structured textual annotations and make it available to researchers to experiment and build upon. Lastly, we report benchmark Fréchet’s Inception Distance (FID), Facial Semantic Similarity (FSS), and Facial Semantic Distance (FSD) scores for the MAST dataset.
A Trilevel Model for Segmentation of the Power Transmission Grid Cyber Network

Network segmentation of a power grid's communication system can make the grid more resilient to cyberattacks. We develop a novel trilevel programming model to optimally segment a grid communication system, taking into account the actions of an information technology (IT) administrator, attacker, and grid operator. The IT administrator is allowed to segment existing networks, and the attacker is given a budget to inflict damage on the grid by attacking the segmented communication system. Finally, the grid operator can redispatch the grid after the attack to minimize damage. The resulting problem is a trilevel interdiction problem that we solve using a branch and bound algorithm for bilevel problems. We demonstrate the benefits of optimal network segmentation through case studies on the 9-bus Western System Coordinating Council (WSCC) system and the 30-bus IEEE system. These examples illustrate that network segmentation can significantly reduce the threat posed by a cyberattacker.
Adversarially Robust One-Class Novelty Detection

One-class novelty detectors are trained with examples of a particular class and are tasked with identifying whether a query example belongs to the same known class. Most recent advances adopt a deep auto-encoder style architecture to compute novelty scores for detecting novel class data. Deep networks have shown to be vulnerable to adversarial attacks, yet little focus is devoted to studying the adversarial robustness of deep novelty detectors. In this article, we first show that existing novelty detectors are susceptible to adversarial examples. We further demonstrate that commonly-used defense approaches for classification tasks have limited effectiveness in one-class novelty detection. Hence, we need a defense specifically designed for novelty detection. To this end, we propose a defense strategy that manipulates the latent space of novelty detectors to improve the robustness against adversarial examples. The proposed method, referred to as Principal Latent Space (PrincipaLS), learns the incrementally-trained cascade principal components in the latent space to robustify novelty detectors. PrincipaLS can purify latent space against adversarial examples and constrain latent space to exclusively model the known class distribution. We conduct extensive experiments on eight attacks, five datasets and seven novelty detectors, showing that PrincipaLS consistently enhances the adversarial robustness of novelty detection models.
YANMTT: Yet Another Neural Machine Translation Toolkit

In this paper, we present our open-source neural machine translation (NMT) toolkit called “Yet Another Neural Machine Translation Toolkit” abbreviated as YANMTT - https://github.com/prajdabre/yanmtt, which is built on top of the HuggingFace Transformers library. YANMTT focuses on transfer learning and enables easy pre-training and fine-tuning of sequence-to-sequence models at scale. It can be used for training parameter-heavy models with minimal parameter sharing and efficient, lightweight models via heavy parameter sharing. Additionally, it supports parameter-efficient fine-tuning (PEFT) through adapters and prompts. Our toolkit also comes with a user interface that can be used to demonstrate these models and visualize various parts of the model. Apart from these core features, our toolkit also provides other advanced functionalities such as but not limited to document/multi-source NMT, simultaneous NMT, mixtures-of-experts, model compression and continual learning.
Profiling Fake News Spreaders on Social Media through Psychological and Motivational Factors

The rise of fake news in the past decade has brought with it a host of consequences, from swaying opinions on elections to generating uncertainty during a pandemic. A majority of methods developed to combat disinformation either focus on fake news content or malicious actors who generate it. However, the virality of fake news is largely dependent upon the users who propagate it. A deeper understanding of these users can contribute to the development of a framework for identifying users who are likely to spread fake news. In this work, we study the characteristics and motivational factors of fake news spreaders on social media with input from psychological theories and behavioral studies. We then perform a series of experiments to determine if fake news spreaders can be found to exhibit different characteristics than other users. Further, we investigate our findings by testing whether the characteristics we observe amongst fake news spreaders in our experiments can be applied to the detection of fake news spreaders in a real social media environment.
3D Face Recognition: A Survey

Face recognition is one of the most studied research topics in the community. In recent years, the research on face recognition has shifted to using 3D facial surfaces, as more discriminating features can be represented by the 3D geometric information. This survey focuses on reviewing the 3D face recognition techniques developed in the past ten years which are generally categorized into conventional methods and deep learning methods. The categorized techniques are evaluated using detailed descriptions of the representative works. The advantages and disadvantages of the techniques are summarized in terms of accuracy, complexity and robustness to face variation (expression, pose and occlusions, etc). The main contribution of this survey is that it comprehensively covers both conventional methods and deep learning methods on 3D face recognition. In addition, a review of available 3D face databases is provided, along with the discussion of future research challenges and directions.
Anosognosia in moderate-to-severe traumatic brain injury: A review of prevalence, clinical correlates, and diversity considerations

Abstract Objective : Anosognosia, or poor self-awareness into current deficits, is a common sequela in both acute and chronic stages of recovery following moderate-to-severe traumatic brain injury (msevTBI). Poor insight into one’s limitations following brain injury can have wide-ranging negative implications on treatment engagement, utilization of compensatory strategies, functional independence, and caregiver burden. Despite its clinical importance, this is the first literature review to document the prevalence and course of anosognosia following msevTBI as well as the demographic, injury-related, neuroanatomical, and neuropsychological correlates of this condition. In addition, this review highlights a range of diversity and cultural considerations for anosognosia assessment and intervention. Method A comprehensive search of peer-reviewed articles was conducted from September to November 2020 using Google Scholar and PubMed databases. Key terms included “anosognosia,” “self-awareness,” “traumatic brain injury,” and variants thereof. Our search was restricted to articles published in English within the last 25 years, although a few historical articles were included due to scientific merit. Articles were chosen based on methodological quality, inclusion of solely or predominantly msevTBI sample, and relevance to the current topic. Conclusions Anosognosia is a multifaceted and domain-specific construct that affects the majority of those with msevTBI. It is related to TBI severity, injuries in right-hemispheric and cortical midline regions, specific aspects of executive function, psychological function, and cultural factors. We offer pragmatic advice for clinicians working with this population and discuss implications for the field regarding “best practices” of anosognosia assessment and intervention.
Analysis of m6A methylation in skin tissues of different sex Liaoning cashmere goats

Abstract N6-methyladenosine (m6A) is the most frequent internal modification of mRNA and lncRNA in eukaryotes. We used two high-throughput sequencing method, m6A-seq and RNA-seq to identify pivotal m6A-modified genes in cashmere fineness and fiber growth. 8062 m6A peaks were detected by m6A-seq, including 2157 upregulated and 6445 downregulated. Furthermore, by comparing m6A-modified genes of the male Liaoning Cashmere Goat (M-LCG) and female Liaoning Cashmere Goat (F-LCG) skin tissues, we get 862 differentially expressed m6A-modified genes. To identify differently expressed m6A genes associated with cashmere fineness, 11 genes were selected for validation using real time fluorescent quantitative PCR in M-LCG and F-LCG. This study provides an acadamic basis on the molecular regulation mechanism of m6A modification in cashmere growth process.
Pretransplant Intensive Care Unit Management and Selection of Grade 3 Acute‐on‐Chronic Liver Failure Transplant Candidates

The aim of this study is to report on the liver transplantation (LT) activity and posttransplant outcome, over time, of patients with grade 3 acute‐on‐chronic liver failure (ACLF‐3) in a single transplant center performing a large number of LTs for patients with ACLF‐3. It aims at showing how pre‐LT intensive care unit (ICU) management impacts post‐LT outcomes, in particular through monitoring the transplantation for ACLF‐3 model (TAM) score. A total of 100 patients who had ACLF‐3 at the time of LT between 2007 and 2019 were included retrospectively. The cohort was divided in 2 periods, with 50 patients in each period. There was an increase in the number of patients with ACLF‐3 who received an LT during the course of the study period and significantly higher 1‐year post‐LT survival rates in the second period compared with the first period (86% versus 66%, respectively; P = 0.02). Interestingly, patients during both periods had similar severity profiles and scores apart from a significantly lower number of patients with TAM scores >2 at the time of LT in the second period compared with the first period (1 [2%] versus 11 [22%], respectively; P ≤ 0.01). In addition, patients whose clinical condition improved in the ICU (with a TAM score downstaged between admission and LT) had significantly higher post‐LT survival rates than those whose TAM score stayed the same or increased: 88% versus 70%, respectively (P = 0.04). This study shows a learning curve in LT for patients with ACLF‐3, with optimized ICU management and patient selection leading to increased numbers of LTs for patients with ACLF‐3 and improved post‐LT outcomes. It also delineates how the TAM score can be used to identify the optimal transplantability window for patients with ACLF‐3.
The effect of enhanced bone marrow in conjunction with 3D-printed PLA-HA in the repair of critical-sized bone defects in a rabbit model

Background Traditionally, the iliac crest has been the most common harvesting site for autologous bone grafts; however, it has some limitations, including poor bone availability and donor-site morbidity. This study sought to explore the effect of enhanced bone marrow (eBM) in conjunction with three-dimensional (3D)-printed polylactide–hydroxyapatite (PLA-HA) scaffolds in the repair of critical-sized bone defects in a rabbit model. Methods First, 3D-printed PLA-HA scaffolds were fabricated and evaluated using micro-computed tomography (µCT) and scanning electron microscopy (SEM). Twenty-seven New Zealand white rabbits were randomly divided into 3 groups (n=9 per group), and the defects were treated using 3D-printed PLA-HA scaffolds (the PLA-HA group) or eBM in conjunction with 3D-printed PLA-HA scaffolds (the PLA-HA/eBM group), or were left untreated (the control group). Radiographic, µCT, and histological analyses were performed to evaluate bone regeneration in the different groups. Results The 3D-printed PLA-HA scaffolds were cylindrical, and had a mean pore size of 500±47.1 µm and 60%±3.5% porosity. At 4 and 8 weeks, the lane-sandhu X-ray score in the PLA-HA/eBM group was significantly higher than that in the PLA-HA group and the control group (P<0.01). At 8 weeks, the µCT analysis showed that the bone volume (BV) and bone volume/tissue volume (BV/TV) in the PLA-HA/eBM group were significantly higher than those in the PLA-HA group and the control group (P<0.01). Hematoxylin and eosin staining indicated that the new bone area in the PLA-HA/eBM group was significantly higher than that in the PLA-HA group and the control group (P<0.01). Conclusions The group that was treated with eBM in conjunction with 3D-printed PLA-HA showed enhanced bone repair compared to the other 2 groups. PLA-HA/eBM scaffolds represent a promising way to treat critical-sized bone defects.
CCAT1/FABP5 promotes tumour progression through mediating fatty acid metabolism and stabilizing PI3K/AKT/mTOR signalling in lung adenocarcinoma

Long non‐coding RNA (lncRNA) colon cancer associated transcript 1 (CCAT1) has been identified as an oncogene in many cancers, but its role in lung adenocarcinoma (LUAD) remains to be further investigated. We identified the upregulation of CCAT1 in LUAD tissues and LUAD cells. Through RNA pull‐down and mass spectrometry analysis, we obtained the interacting proteins with CCAT1 and discovered their functional relation with ‘signal transduction’, ‘energy pathways’ and ‘metabolism’ and revealed the potential of CCAT1 on fatty acid (FA) metabolism. For mechanism exploration, we uncovered the mediation of CCAT1 on the translocation of fatty acid binding protein 5 (FABP5) into nucleus by confirming their interaction and localization. Also, CCAT1 was discovered to promote the formation of the transcription complex by RXR and PPARγ so as to activate the transcription of CD36, PDK1 and VEGFA. Moreover, we found that CCAT1 regulated the activity of AKT by promoting the ubiquitination of FKBP51 through binding with USP49. Subsequently, cell function assays revealed the enhancement of CCAT1 on LUAD cell proliferation and angiogenesis in vitro and in vivo. Collectively, CCAT1 regulated cell proliferation and angiogenesis through regulating FA metabolism in LUAD, providing a novel target for LUAD treatment.
Identification and Characterization of Human Norovirus NTPase Regions Required for Lipid Droplet Localization, Cellular Apoptosis, and Interaction with the Viral P22 Protein

Human noroviruses (HuNVs) are the major agent of global gastroenteritis outbreaks. However, due to the lack of an efficient cell culture system for HuNV propagation, functions of the viral-encoded proteins in host cells are still poorly understood. ABSTRACT The human norovirus (HuNV)-encoded nucleoside-triphosphatase (NTPase) is a multifunctional protein critically involved in viral replication and pathogenesis. Previously, we have shown that the viral NTPase is capable of forming vesicle clusters in cells, interacting with other viral proteins such as P22, and promoting cellular apoptosis. Herein, we demonstrate that NTPase-associated vesicle clusters correspond to lipid droplets (LDs) wrapped by the viral protein and show that NTPase-induced apoptosis is mediated through both caspase-8- and caspase-9-dependent pathways. Deletion analysis revealed that the N-terminal 179-amino-acid (aa) region of NTPase encompasses two LD-targeting motifs (designated LTM-1 and LTM-2), two apoptosis-inducing motifs, and multiple regulatory regions. Interestingly, the identified LTM-1 and LTM-2, which are located from aa 1 to 50 and from aa 51 to 90, respectively, overlap with the two apoptosis-inducing motifs. Although there was no positive correlation between the extent of LD localization and the degree of cellular apoptosis for NTPase mutants, we noticed that mutant proteins defective in LD-targeting ability could not induce cellular apoptosis. In addition to LD targeting, the amphipathic LTM-1 and LTM-2 motifs could have the potential to direct fusion proteins to the endoplasmic reticulum (ER). Furthermore, we found that the LTM-1 motif is a P22-interacting motif. However, P22 functionally augmented the proapoptotic activity of the LTM-2 fusion protein but not the LTM-1 fusion protein. Overall, our findings propose that NTPase may participate in multiple cellular processes through binding to LDs or to the ER via its N-terminal amphipathic helix motifs. IMPORTANCE Human noroviruses (HuNVs) are the major agent of global gastroenteritis outbreaks. However, due to the lack of an efficient cell culture system for HuNV propagation, functions of the viral-encoded proteins in host cells are still poorly understood. In the current study, we present that the viral NTPase is a lipid droplet (LD)-associated protein, and we identify two LD-targeting motifs, LTM-1 and LTM-2, in its N-terminal domain. In particular, the identified LTM-1 and LTM-2 motifs, which contain a hydrophobic region and an amphipathic helix, are also capable of delivering the fusion protein to the endoplasmic reticulum (ER), promoting cellular apoptosis, and physically or functionally associating with another viral protein P22. Since LDs and the ER have been linked to several biological functions in cells, our study therefore proposes that the norovirus NTPase may utilize LDs or the ER as replication platforms to benefit viral replication and pathogenesis.
A multilevel analysis of the impact of transitioning to grandparenthood on individuals’ depression in England, Europe and China

Abstract Objectives The impact of grandparenting on depression is mediated by both macro- and micro-level factors, however, their combined examination between different country contexts is relatively rare. This study examined whether country level income and grandparents’ gender influenced the relationship between the transition to grandparenthood and individuals’ depression across England, Europe and China. Methods Multi-level linear regression analyses with restricted maximum likelihood estimation were performed covering 15 countries from the ELSA, the SHARE and the CHARLS 2010-15 in order to understand cross-country differences in this area. Results This study found significant cross-national variations in the effects of transitioning to grandparenthood on individuals’ depression. Transitioning to grandparenthood reduced the depression score among both men and women in lower income countries, but increased it in higher income countries. Moreover, the gender gap in the effects of becoming a grandparent on one’s depression was wider in lower income countries than higher income countries. Conclusions Policymakers should pay attention to the support grandparents need, and systematically integrate childcare provided by grandparents into family policies. Policies supporting older people should take into account the way in which macro-level and micro-level factors combine to affect grandparents’ well-being.
Rate of device-related infections using an antibacterial envelope in patients undergoing cardiac resynchronization therapy reoperations.

AIMS Cardiac resynchronization therapy (CRT) reoperations are associated with a particularly high risk of device-related infection (DRI). An antibacterial envelope reduces the occurrence of DRIs in a broad population of moderate-tohigh-risk patients. To investigate the efficacy of an antibacterial envelope in a very high-risk population of patients undergoing CRT reoperation. METHODS AND RESULTS In this Danish two-centre, observational cohort study, we included consecutive patients who underwent a CRT pacemaker- or defibrillator reoperation procedure between January 2008 and November 2019. We obtained data from the Danish Pacemaker and ICD Register and through systematic medical chart review. Follow-up was restricted to 2 years. A total of 1943 patients were included in the study of which 736 (38%) received an envelope. Envelope patients had more independent risk factors for infection than non-envelope patients. Sixty-seven (3.4%) patients met the primary endpoint of DRI requiring device system extraction; 50 in the non-envelope group and 17 in the envelope group [4.1% vs. 2.3%, adjusted hazard ratio (HR) 0.52, 95% confidence interval (CI) 0.30-0.90; P = 0.021]. This difference persisted in propensity score analysis (HR 0.51, 95% CI 0.29-0.90; P = 0.019). CONCLUSION Use of an antibacterial envelope was associated with a clinically and statistically significant reduction in DRIs in patients undergoing CRT reoperations. Our results were comparable to those recently reported from a large randomized controlled trial, which is suggestive of a proportional effect of the envelope even in very high-risk patients.