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We present Orbit, a unified and modular framework for robot learning powered by Nvidia Isaac Sim. It offers a modular design to easily and efficiently create robotic environments with photo-realistic scenes and high-fidelity rigid and deformable body simulation. With Orbit, we provide a suite of benchmark tasks of varying difficulty- from single-stage cabinet opening and cloth folding to multi-stage tasks such as room reorganization. To support working with diverse observations and action spaces, we include fixed-arm and mobile manipulators with different physically-based sensors and motion generators. Orbit allows training reinforcement learning policies and collecting large demonstration datasets from hand-crafted or expert solutions in a matter of minutes by leveraging GPU-based parallelization. In summary, we offer an open-sourced framework that readily comes with 16 robotic platforms, 4 sensor modalities, 10 motion generators, more than 20 benchmark tasks, and wrappers to 4 learning libraries. With this framework, we aim to support various research areas, including representation learning, reinforcement learning, imitation learning, and task and motion planning. We hope it helps establish interdisciplinary collaborations in these communities, and its modularity makes it easily extensible for more tasks and applications in the future. ISSN:2377-3766

Crises-such as the COVID-19 pandemic-bring about myriad problems in magnitude (severity), dynamism (quality), and urgency (timing). Collaborative models that bring together actors from both the public and private sector have thus emerged for institutionalized and community-based crisis response. Such models aim particularly to reach vulnerable, hard-to-reach communities, such as racialized immigrant communities that are among those disproportionately impacted at times of crisis. This paper presents a case study of a community-based, cross-sectoral collaborative formed to respond to the COVID-19 pandemic and specifically targeting immigrant communities. Findings inform a conceptual framework that illustrates the integration of two spheres of service: crisis supports, characterized by a short-term approach, broad-based reach and general objectives; and settlement supports, characterized by their long-term approach, trust relations and targeted objectives, such as language supports and culturally appropriate outreach.

Inside a spacecraft, the temperature and humidity, suitable for the human crew onboard, also creates an ideal breeding environment for the proliferation of bacteria and fungi; this can present a hazard to human health and create issues for the safe running of equipment. To address this issue, wear-resistant antimicrobial thin films prepared by magnetron sputtering were developed, with the aim to coat key internal components within spacecrafts. Silver and copper are among the most studied active bactericidal materials, thus this work investigated the antibacterial properties of amorphous carbon coatings, doped with either silver, silver and copper, or with silver clusters. The longevity of these antimicrobial coatings, which is heavily influenced by metal diffusion within the coating, was also investigated. With a conventional approach, amorphous carbon coatings were prepared by cosputtering, to generate coatings that contained a range of silver and copper concentrations. In addition, coatings containing silver clusters were prepared using a separate cluster source to better control the metal particle size distribution in the amorphous carbon matrix. The particle size distributions were characterized by grazing-incidence small-angle X-ray scattering (GISAXS). Antibacterial tests were performed under both terrestrial gravity and microgravity conditions, to simulate the condition in space. Results show that although silver-doped coatings possess extremely high levels of antimicrobial activity, silver cluster-doped coatings are equally effective, while being more long-lived, despite containing a lower absolute silver concentration.

Introduction: A group of substituted benzothiazoles from a research project was found to have low microsomal clearance. However, these compounds had very high clearance in vivo. Methods: In the present study, the clearance mechanism of two of the structural analogs, was investigated in vitro and in vivo. Results: In vitro studies showed the formation of corresponding non-P450 dependent oxidative metabolites in S9, cytosol, and hepatocytes. The in vitro formation of these metabolites was observed in mice, rats, non-human primates, and humans. The dog did not form the corresponding metabolites in any of the matrices. Inhibition studies with S9 fraction and incubation with human recombinant aldehyde oxidase (AO) showed that the formation of the corresponding metabolites was AO dependent. To investigate the role of this pathway in vivo, mice were dosed with compound A and bile and plasma were analyzed. Most of the metabolites in bile contained the AO-dependent oxidized benzothiazole moiety, indicating that metabolism involving AO was probably the main pathway for clearance. The same metabolites were also observed circulating in plasma. Mass spectrometric analysis of the metabolite showed that the oxidation was on the benzothiazole moiety, but the exact position could not be identified. Isolation of the metabolite of compound A and analysis by NMR confirmed the structure of the metabolite as C2 carbon oxidation of the thiazole ring resulting in carboxamide moiety. Further comparison of both metabolites with corresponding authentic standards confirmed the structures. Conclusion: To our knowledge, such an observation of in vitro and in vivo oxidation of substituted benzothiazole by AO has not been reported before. The results helped the medicinal chemists design compounds that avoid AO-mediated metabolism and with better ADME property.

Chromium poisoning has become one of the most common heavy metal poisoning occupational diseases with high morbidity and mortality. However, most antidotes detoxify the whole body and are highly toxic. To achieve hepato-targeted chromium poisoning detoxification, a novel hepato-targeted strategy was developed using aging erythrocyte membranes (AEMs) as biomimetic material coated with a dimercaptosuccinic acid (DMSA) nanostructured lipid carrier to construct a biomimetic nano-drug delivery system. The particle size, potential, drug loading, encapsulation rate, in vitro release, and stability of the nanoparticles (NPs) were characterized. Confocal microscopy and flow cytometry showed that the prepared NPs could be phagocytized by RAW264.7 macrophage cells. The efficacy of AEM-DMSA-NPs for targeted liver detoxification was evaluated by in vitro MTT analysis and an in vivo model of chromium poisoning. The results showed that the NPs could safely and efficiently achieve targeted liver chromium poisoning detoxification. All the results indicated that the biomimetic nano-drug delivery system mediated by aging erythrocyte membranes and containing DMSA nanoparticles could be used as a novel therapeutic drug delivery system potentially targeting liver detoxification.

Aim/Purpose: This paper reflects on participation in an International Doctoral Research Seminar, held in Beijing, China, to consider what it means to locate difference and make meaning in a globalized world in relation to teaching and learning. Background: The impetus for our inquiry stems from our shared experience at the seminar, which brought together 12 graduate students and six faculty members from three universities. We came with diverse life stories, educational and professional experiences, and research interests. Alongside presentations and school visits, some students questioned how teaching and learning practices differ in China compared to their experiences in Canada. Methodology: We employ an interpretive approach which allows us to revisit our individual stories and to explore different views of meaning-making in a globalized context. Specifically, two authors, positioned by different backgrounds (Chinese and Canadian), share their life histories and experiences for wider dialogue with other delegation members. We consider their experiences at various levels of education (K-12, leading up to graduate school, and at the doctoral seminar) as a mode of generating dialogue around the different contexts in relation to teaching and learning. Contribution: Our article contributes to the area of globalizing teaching and learning. We invite students and educators to revisit their lived experiences and advocate for daily practices that might defy sameness caused by the forces of globalization to instead contribute to epistemological diversity and tolerance. Findings: Through the process of unpacking the lived experiences of the two authors, we encounter the complexities of already being products of a globalized world. We reveal how a singular normative mode of knowing is perpetuated in many educational institutions. Difference, however, was located in the nuances of our stories. Thus, cultivating a practice of paying attention to the dynamic forms of knowing as they emerge can be a process of unlearning sameness toward rich meaning-making. Recommendations for Practitioners: We challenge educational practitioners to reflect on the ways in which meaning is, and can be, generated to resist uniformity and honor the lived experiences of students. We offer an opening to engage in narrative opportunities to promote dialogue and facilitate collaboration. Recommendation for Researchers: We open possibilities to consider a different ethic for generating meaning that resists overpowering global powers and honor local knowledge. Impact on Society: Our article provides an interpretive lens of global meaning-making to discuss critical social, cultural, and ecological dilemmas facing humanity through individuals’ narratives and life histories. Future Research: Future research will inquire into practical and ethical considerations that might play out in local settings (lectures, seminars, assessments, research proposals) and global collaborations, such as future doctoral seminars, to confront western exclusivity.

As a part of the multi-source cooperative navigation scheme, data fusion has a significant impact on the quality of state estimation. Particle filtering has gradually become the focus of many fusion methods due to its unique theoretical advantages in nonlinear non-Gaussian systems. However, the particle degradation and the resulting sample impoverishment restrict its application in complex engineering scenarios. In this paper, a robust cubature fission particle filter (RCFPF) is proposed to deal with these problems. First, in the framework of cubature rule, Huber function is used to combine the L2 norm and L1 norm to improve the importance density function(IDF), suppress the observation noise. Meanwhile, the proposed distribution(PD) is further optimized by combining the Gaussian distribution with Laplace distribution to alleviate particle degradation. Second, the particle swarm is fissioned before resampling, and the particle weight is reconstructed by fission of high weight particles and covering low weight particles to inhibit sample impoverishment. The vehicle experiments of multi-source cooperative navigation show that the proposed algorithm achieves better test results in accuracy and robustness than extended Kalman filter (EKF), strong tracking particle filter (STPF), and cubature particle filter (CPF).

The low survival rate of hepatocellular carcinoma (HCC) remains a major challenge for clinicians and patients, and its progression may be related to hypoxia-inducible factor (HIF) and PD-L1. LW6 is a drug that inhibits hypoxia by reducing HIF-1α accumulation and gene transcriptional activity. However, its effect and regulatory mechanism in HCC remain to be revealed, especially under hypoxic conditions. The HIF-1α and PD-L1 expression in HCC specimens and paracarcinoma tissues was evaluated by a tissue microarray (TMA). The effects of LW6 were evaluated by cell viability, colony formation, and Transwell assays and xenografted nude mice. Cell cycle and apoptosis of HCC cells were detected by flow cytometry. The effects of LW6 on HIF-1α signaling and its targets PD-L1 and VEGF were evaluated through qRT-PCR, Western blots, Cell transfection, Transwell migration and invasion assays, immunohistochemistry, immunofluorescence and luciferase assays. In this study, we found that LW6 had antiproliferative effects on HCC and promoted HCC cell apoptosis, inhibited their migration and invasion, and affected their cell cycle. LW6 dramatically decreased HIF-1α expression through the VHL-dependent proteasome system pathway, inhibited HIF-1α transcriptional activation, and reduced PD-L1 expression by inhibiting EGFR pathway activation. These results suggest that LW6 can promote apoptosis of HCC cells by inhibiting HIF-1α, inhibit tumor angiogenesis, and downregulate the expression of PD-L1, which is an effective choice for the treatment of HCC. Moreover, inhibiting the hypoxic microenvironment combined with immunotherapy is expected to be a potentially effective strategy.

Traumatic brain injury (TBI) is known to activate poly (ADP-ribose) polymerase (PARP-1), which leads to pronounced negative effects on mitochondrial DNA (mt-DNA) repair and function. Notably, PARP inhibitors are reported to be beneficial in experimental models of TBI. A targeting strategy for the delivery of neuronal mitochondria-specific PARP inhibitors could result in a greater neuroprotective effect and be a safer approach for TBI treatment. In the present study, we developed the PARP inhibitor olaparib (Ola) as a model drug and devised red blood cell (RBC)-coated nanostructured lipid carriers (RBCNLCs) co-modified with C3 and SS31 peptide (C3/SS31-RBCNLCs) for brain neuronal mitochondria-targeting. Our results indicated that biomimetic nanosystems have the physical and chemical properties of the NLCs, as well as the biological properties of RBC. A high concentration of Ola delivered into brain mitochondria by C3/SS31-RBCNLCs-Ola effectively improved mitochondrial function and prevented neuronal cell death caused by excessive activation of injury-induced mitochondrial PARP (mt-PARP) in vitro and in vivo. Taken together, the results of this study support the preclinical feasibility of developing highly effective nano-drugs as part of precision medicine for TBI. STATEMENT OF SIGNIFICANCE: TBI-induced neuronal mitochondria DNA damage activates Poly(ADP-ribose) Polymerase (PARP1) which leads to a pronounced negative effect on mitochondrial DNA repair and mitochondrial function. In recent years, PARP inhibitors showed strong benefits in experimental models of TBI, more importantly PARP inhibitors specially target neuronal mitochondria may play a greater neuroprotective role and may be a safer approach for TBI treatment. Herein, we designed red blood cell (RBC) membrane-coated nanostructure lipid carriers dual-modified with C3 and SS31 (C3/SS31-RBCNLCs) to accomplish these objectives. After encapsulating Olaparib (Ola) as the model PARP inhibitor, the data demonstrated that C3/SS31-RBCNLCs, with brain neuronal mitochondria targeting, can reduce neuronal cell death and improve mitochondrial dysfunction triggered by mitochondrial PARP activation in vitro and in vivo.

Supervised summarization has made significant improvements in recent years by leveraging cutting-edge deep learning technologies. However, the true success of supervised methods relies on the availability of large quantity of human-generated summaries of documents, which is highly costly and difficult to obtain in general. This paper proposes an unsupervised approach to extractive text summarization, which uses an automatically constructed sentence graph from each document to select salient sentences for summarization based on both the similarities and relative distances in the neighborhood of each sentences. We further generalize our approach from single-document summarization to a multi-document setting, by aggregating document-level graphs via proximity-based cross-document edges. In our experiments on benchmark datasets, the proposed approach achieved competitive or better results than previous state-of-the-art unsupervised extractive summarization methods in both single-document and multi-document settings, and the performance is competitive to strong supervised baselines.

The recent success of abstractive summarization is partly due to the availability of large-volume and high-quality human-produced summaries for training, which are extremely expensive to obtain. In this paper, we aim to improve state-of-the-art summarization models by utilizing less expensive text classification data. Specifically, we use an eXtreme Multi-label Text Classification (XMTC) classifier to predict relevant category labels for each input document, and impose topic consistency in the system-produced summary or in the document encoder shared by both the classifier and the summarization model. In other words, we use the classifier to distill the training of the summarization model with respect to topical consistency between the input document and the system-generated summary. Technically, we propose two novel formulations for this objective, namely a multi-task approach, and a policy gradient approach. Our experiments show that both approaches significantly improve a state-of-the-art BART summarization model on the CNNDM and XSum datasets. In addition, we propose a new evaluation metric, CON, that measures the topic consistency between the input document and the summary. We show that CON has high correlation with human judgements and is a good complementary metric to the commonly used ROUGE scores.

Recent studies have demonstrated that ivermectin (IVM) exhibits antiviral activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus of coronavirus disease 2019 (COVID-19). However, the repurposing of IVM for the treatment of COVID-19 has presented challenges primarily due to the low IVM plasma concentration after oral administration, which was well below IC

We introduce a new task, Video-and-Language Inference, for joint multimodal understanding of video and text. Given a video clip with aligned subtitles as premise, paired with a natural language hypothesis based on the video content, a model needs to infer whether the hypothesis is entailed or contradicted by the given video clip. A new large-scale dataset, named Violin (VIdeO-and-Language INference), is introduced for this task, which consists of 95,322 video-hypothesis pairs from 15,887 video clips, spanning over 582 hours of video. These video clips contain rich content with diverse temporal dynamics, event shifts, and people interactions, collected from two sources: (i) popular TV shows, and (ii) movie clips from YouTube channels. In order to address our new multimodal inference task, a model is required to possess sophisticated reasoning skills, from surface-level grounding (e.g., identifying objects and characters in the video) to in-depth commonsense reasoning (e.g., inferring causal relations of events in the video). We present a detailed analysis of the dataset and an extensive evaluation over many strong baselines, providing valuable insights on the challenges of this new task., Comment: Accepted to CVPR2020

To explore the degree of embolization and embolization endpoints in patients with large hepatocellular carcinoma (HCC) treated via transarterial chemoembolization (TACE).Thirty-two HCC patients treated with TACE from 2015 to 2016 who met the enrollment criteria for this study were retrospectively analyzed. The experimental group was treated via complete embolization, with complete occlusion of the tumor blood supplying artery, while the control group underwent incomplete embolization of any blood supplying arteries, with limited residual visible blood flow detectable via angiography. Postoperative liver and kidney function, complications, prognosis, and survival for patients in these two groups were analyzed.There was no significant difference at baseline patient condition between the two treatment groups before treatment. After treatment, the alanine aminotransferase (ALT), aspartic aminotransferase (AST), and white blood cell (WBC) values in the experimental group were significantly higher than those in the control group (p=0.031, 0.038, and 0.034, respectively). There was also a significant increase in hepatic aseptic necrosis and acute liver function damage in the experimental group relative to the control group (p=0.015 and 0.023, respectively). Compared with the control group, the prognosis and survival of the experimental group was significantly decreased. Univariate and multivariate Cox regression analyses of overall survival revealed that the different treatment group and hepatitis B infection status were the main factors affecting patient prognosis and survival.For patients with large HCC tumors with a limited number of supporting arteries, careful attention should be paid to the use of embolic agents during the TACE procedure. Rather than proceeding to complete embolization of the artery root, embolization can be terminated when the main tumor feeding artery is still faintly visible on an angiogram in a structure reminiscent of a tree with dry branches, thereby reducing adverse outcomes in patients.

The effect of Al content on phase structure and mechanical properties of vacuum annealed Cr-Al-C coatings was investigated. Cr-Al-C coatings were deposited by co-sputtering of Cr2Al and Al targets in optimized CH4/Ar atmosphere. The atomic content of Al was adjusted through the control of Al target current from 0.5 A to 3.0 A, thus Cr-Al-C coatings with different stoichiometric ratios were obtained. After 1.5 h thermal annealing at 750 °C in vacuum, Cr2AlC MAX phase was observed from the XRD measurements. The Rietveld refinement of XRD spectra results indicated that the annealed coatings were composed of Cr2AlC, Al8Cr5 and Cr7C3 phases with different amounts. With the increase of Al content, the hardness and modulus of the Cr2AlC MAX phase coatings varied from 10.17 to 19.00 GPa and 198.43 to 267.62 GPa, respectively, while the toughness suffered an obvious decline. HRTEM analysis demonstrated that the excess of Al content resulted in the formation of Al8Cr5 and Al segregation at grain boundaries, which led to the deterioration of mechanical properties.

Chinese international students are vital to internationalization development in Canadian higher education, providing immediate and significant social and economic benefits to Canadian society. The existing scholarly studies have primarily adopted a cultural approach, with a focus on intercultural adaptation or related cross-cultural perspectives. This study goes beyond the cultural approach and examines how race, gender, and class intersect in producing social inequality among Chinese international students in Canada. Through the narratives of five students attending higher education institutions in British Columbia, the study reveals that Chinese international students have experienced discrimination in relation to developing friendship, integrating to the learning environment, and accessing supports and resources on campus based on the color of skin, their gender, and misperception of their class. The color line divides them into the “dominant white” and “people of color.” Color blindness negates their racial identities and ignores the ways in which these affect their learning experiences. The findings of this research call for an intersectional approach to examine international students and their lived experiences by addressing students’ multiple identities and differences to enrich their lived experience in Canada.

Ti2AlN belongs to a family of ternary nano-laminate alloys known as the MAX phases, which exhibit a unique combination of metallic and ceramic properties. In the present work, the dense and high-stability Ti2AlN coating has been successfully prepared through the combined cathodic arc/sputter deposition, followed by heat post-treatment. It was found that the as-deposited Ti-Al-N coating behaved a multilayer structure, where (Ti, N)-rich layer and Al-rich layer grew alternately, with a mixed phase constitution of TiN and TiAlx. After annealing at 800 °C under vacuum condition for 1.5 h, although the multilayer structure still was found, part of multilayer interfaces became indistinct and disappeared. In particular, the thickness of the Al-rich layer decreased in contrast to that of as-deposited coating due to the inner diffusion of the Al element. Moreover, the Ti2AlN MAX phase emerged as the major phase in the annealed coatings and its formation mechanism was also discussed in this study. The vacuum thermal analysis indicated that the formed Ti2AlN MAX phase exhibited a high-stability, which was mainly benefited from the large thickness and the dense structure. This advanced technique based on the combined cathodic arc/sputter method could be extended to deposit other MAX phase coatings with tailored high performance like good thermal stability, high corrosion and oxidation resistance etc. for the next protective coating materials.

Large-scale pre-trained language model such as BERT has achieved great success in language understanding tasks. However, it remains an open question how to utilize BERT for language generation. In this paper, we present a novel approach, Conditional Masked Language Modeling (C-MLM), to enable the finetuning of BERT on target generation tasks. The finetuned BERT (teacher) is exploited as extra supervision to improve conventional Seq2Seq models (student) for better text generation performance. By leveraging BERT's idiosyncratic bidirectional nature, distilling knowledge learned in BERT can encourage auto-regressive Seq2Seq models to plan ahead, imposing global sequence-level supervision for coherent text generation. Experiments show that the proposed approach significantly outperforms strong Transformer baselines on multiple language generation tasks such as machine translation and text summarization. Our proposed model also achieves new state of the art on IWSLT German-English and English-Vietnamese MT datasets. Code is available at https://github.com/ChenRocks/Distill-BERT-Textgen., ACL 2020