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Chatbot research has advanced significantly over the years. Enterprises have been investigating how to improve these tools’ performance, adoption, and implementation to communicate with customers or internal teams through social media. Besides, businesses also want to pay attention to quality reviews from customers via social networks about products available in the market. From there, please select a new method to improve the service quality of their products and then send it to publishing agencies to publish based on the needs and evaluation of society. Although there have been numerous recent studies, not all of them address the issue of opinion evaluation on the chatbot system. The primary goal of this paper’s research is to evaluate human comments in English via the chatbot system. The system’s documents are preprocessed and opinion-matched to provide opinion judgments based on English comments. Based on practical needs and social conditions, this methodology aims to evolve chatbot content based on user inter-actions, allowing for a cyclic and human-supervised process with the following steps to evaluate comments in English. First, we preprocess the input data by collecting social media comments, and then our system parses those comments according to the rating views for each topic covered. Finally, our system will give a rating and comment result for each comment entered into the system. Experiments show that our method can improve accuracy better than the referenced methods by 78.53%.

Coronary artery vasospasm (CVS), an uncommon cause of acute chest pain, can be provoked by vasoconstriction-induced medications. Misoprostol, a prostaglandin analog, is a safe medication to terminate a pregnancy. However, misoprostol can cause coronary artery vasospasm due to vasoconstrictor properties, leading to acute myocardial infarction with nonobstructive coronary arteries (MINOCA), especially in patients with a high risk for cardiovascular disease. We report a case of a 42-year-old female with a past medical history of hypertension who presented with ST-elevation myocardial infarction following the administration of a high-dose Misoprostol. The fact that coronary angiogram and intravascular ultrasound revealed normal coronary arteries suggested transient coronary vasospasm. CVS is a severe but rare cardiac adverse effect associated with high-dose misoprostol. This medication should be prescribed with caution and close monitoring, especially in those with pre-existing heart disease or cardiovascular risk factors. Our case raises awareness of severe cardiovascular complications that can be related to using misoprostol in high-risk patients.

Medulloblastoma (MB) is a malignant tumour of the cerebellum which can be classified into four major subgroups based on gene expression and genomic features. Single cell transcriptome studies have defined the cellular states underlying each MB subgroup, however the spatial organisation of these diverse cell states and how this impacts response to therapy remains to be determined. Here, we used spatially resolved transcriptomics to define the cellular diversity within a sonic hedgehog (SHH) patient-derived model of MB and show that cells specific to a transcriptional state or spatial location are pivotal for CDK4/6 inhibitor, Palbociclib, treatment response. We integrated spatial gene expression with histological annotation and single cell gene expression data from MB, developing an analysis strategy to spatially map cell type responses within the hybrid system of human and mouse cells and their interface within an intact brain tumour section. We distinguish neoplastic and non-neoplastic cells within tumours and from the surrounding cerebellar tissue, further refining pathological annotation. We identify a regional response to Palbociclib, with reduced proliferation and induced neuronal differentiation in both treated tumours. Additionally, we resolve at a cellular resolution adistincttumourinterfacewhere the tumour contacts neighbouring mouse brain tissue consisting of abundant astrocytes and microglia and continues to proliferate despite Palbociclib treatment. Ourdata highlight the power of using spatial transcriptomics to characterise the response of a tumour to a targeted therapy and provide further insights into the molecular and cellular basis underlying the response and resistance to CDK4/6 inhibitors in SHH MB.&nbsp

Severe tetanus is characterized by muscle spasm and cardiovascular system disturbance. The pathophysiology of muscle spasm is relatively well understood and involves inhibition of central inhibitory synapses by tetanus toxin. That of cardiovascular disturbance is less clear, but is believed to relate to disinhibition of the autonomic nervous system. The clinical syndrome of autonomic nervous system dysfunction (ANSD) seen in severe tetanus is characterized principally by changes in heart rate and blood pressure which have been linked to increased circulating catecholamines. Previous studies have described varying relationships between catecholamines and signs of ANSD in tetanus, but are limited by confounders and assays used. In this study, we aimed to perform detailed characterization of the relationship between catecholamines (adrenaline and noradrenaline), cardiovascular parameters (heart rate and blood pressure) and clinical outcomes (ANSD, mechanical ventilation required, and length of intensive care unit stay) in adults with tetanus, as well as examine whether intrathecal antitoxin administration affected subsequent catecholamine excretion. Noradrenaline and adrenaline were measured by ELISA from 24-h urine collections taken on day 5 of hospitalization in 272 patients enrolled in a 2 × 2 factorial-blinded randomized controlled trial in a Vietnamese hospital. Catecholamine results measured from 263 patients were available for analysis. After adjustment for potential confounders (i.e., age, sex, intervention treatment, and medications), there were indications of non-linear relationships between urinary catecholamines and heart rate. Adrenaline and noradrenaline were associated with subsequent development of ANSD, and length of ICU stay.

Purpose: To critically review data published in the recent past to scrutinize a causal relationship between retinal vascular occlusion and COVID-19. Method: A comprehensive literature search was performed on Pubmed with the key words retinal vascular occlusion, retinal vein occlusion, retinal artery occlusion, and COVID-19. Results: A total of 17 case reports were published during this period, and 10 were on retinal vein occlusion and 7 on retinal artery occlusion. Most of the published reports lacked convincing evidences in one or the other aspects, such as insufficient laboratory workup or presence of multiple confounding risk factors. Conclusion: In this index article, strength of the data is insufficient to establish a definitive cause-and-effect relationship of retinal vascular occlusive disorders with COVID-19. Hence, clinicians can continue to manage these cases according to the standard guidelines until there are more robust evidences to support this association to alter the diagnostic and treatment modalities.

This work presents the preparation of bioactive glasses 70SiO2–(26 − x)CaO–4P2O5–xAg2O (with x = 0, 1, 3, 10 mol%) by a modified sol–gel method with reduced synthesis time based on hydrothermal reaction in a medium without acid or base catalysts.

Identifying tissue-specific molecular signatures of active regulatory elements is critical to understanding gene regulatory mechanisms. In this study, transcription start sites (TSS) and enhancers were identified using Cap analysis of gene expression (CAGE) across endometrial stromal cell (ESC) samples obtained from women with (n = 4) and without endometriosis (n = 4). ESC TSSs and enhancers were compared to those reported in other tissue and cell types in FANTOM5 and were integrated with RNA-seq and ATAC-seq data from the same samples for regulatory activity and network analyses. CAGE tag count differences between women with and without endometriosis were statistically tested and tags within close proximity to genetic variants associated with endometriosis risk were identified. Over 90% of tag clusters mapping to promoters were observed in cells and tissues in FANTOM5. However, some potential cell-type-specific promoters and enhancers were also observed. Regions of open chromatin identified using ATAC-seq provided further evidence of the active transcriptional regions identified by CAGE. Despite the small sample number, there was evidence of differences associated with endometriosis at 210 consensus clusters, including IGFBP5, CALD1 and OXTR. ESC TSSs were also located within loci associated with endometriosis risk from genome-wide association studies. This study provides novel evidence of transcriptional differences in endometrial stromal cells associated with endometriosis and provides a valuable cell-type specific resource of active TSSs and enhancers in endometrial stromal cells.

In this paper, we propose a novel framework for synthesizing a single multimodal control policy capable of generating diverse behaviors (or modes) and emergent inherent transition maneuvers for bipedal locomotion. In our method, we first learn efficient latent encodings for each behavior by training an autoencoder from a dataset of rough reference motions. These latent encodings are used as commands to train a multimodal policy through an adaptive sampling of modes and transitions to ensure consistent performance across different behaviors. We validate the policy performance in simulation for various distinct locomotion modes such as walking, leaping, jumping on a block, standing idle, and all possible combinations of inter-mode transitions. Finally, we integrate a task-based planner to rapidly generate open-loop mode plans for the trained multimodal policy to solve high-level tasks like reaching a goal position on a challenging terrain. Complex parkour-like motions by smoothly combining the discrete locomotion modes were generated in 3 min. to traverse tracks with a gap of width 0.45 m, a plateau of height 0.2 m, and a block of height 0.4 m, which are all significant compared to the dimensions of our mini-biped platform., Comment: 8 pages, 8 figures

Submission note: A thesis submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the La Trobe Business School, Department of Marketing and Tourism and Hospitality, Faculty of Business, Economics and Law, La Trobe University, Bundoora.

Despite the potential benefits of collaborative robots, effective manipulation tasks with quadruped robots remain difficult to realize. In this paper, we propose a hierarchical control system that can handle real-world collaborative manipulation tasks, including uncertainties arising from object properties, shape, and terrain. Our approach consists of three levels of controllers. Firstly, an adaptive controller computes the required force and moment for object manipulation without prior knowledge of the object's properties and terrain. The computed force and moment are then optimally distributed between the team of quadruped robots using a Quadratic Programming (QP)-based controller. This QP-based controller optimizes each robot's contact point location with the object while satisfying constraints associated with robot-object contact. Finally, a decentralized loco-manipulation controller is designed for each robot to apply manipulation force while maintaining the robot's stability. We successfully validated our approach in a high-fidelity simulation environment where a team of quadruped robots manipulated an unknown object weighing up to 18 kg on different terrains while following the desired trajectory.

Agile-legged robots have proven to be highly effective in navigating and performing tasks in complex and challenging environments, including disaster zones and industrial settings. However, these applications normally require the capability of carrying heavy loads while maintaining dynamic motion. Therefore, this paper presents a novel methodology for incorporating adaptive control into a force-based control system. Recent advancements in the control of quadruped robots show that force control can effectively realize dynamic locomotion over rough terrain. By integrating adaptive control into the force-based controller, our proposed approach can maintain the advantages of the baseline framework while adapting to significant model uncertainties and unknown terrain impact models. Experimental validation was successfully conducted on the Unitree A1 robot. With our approach, the robot can carry heavy loads (up to 50% of its weight) while performing dynamic gaits such as fast trotting and bounding across uneven terrains.

Modern machine learning increasingly supports paradigms that are multi-institutional (using data from multiple institutions during training) or cross-institutional (using models from multiple institutions for inference), but the empirical effects of these paradigms are not well understood. This study investigates cross-institutional learning via an empirical case study in higher education. We propose a framework and metrics for assessing the utility and fairness of student dropout prediction models that are transferred across institutions. We examine the feasibility of cross-institutional transfer under real-world data- and model-sharing constraints, quantifying model biases for intersectional student identities, characterizing potential disparate impact due to these biases, and investigating the impact of various cross-institutional ensembling approaches on fairness and overall model performance. We perform this analysis on data representing over 200,000 enrolled students annually from four universities without sharing training data between institutions. We find that a simple zero-shot cross-institutional transfer procedure can achieve similar performance to locally-trained models for all institutions in our study, without sacrificing model fairness. We also find that stacked ensembling provides no additional benefits to overall performance or fairness compared to either a local model or the zero-shot transfer procedure we tested. We find no evidence of a fairness-accuracy tradeoff across dozens of models and transfer schemes evaluated. Our auditing procedure also highlights the importance of intersectional fairness analysis, revealing performance disparities at the intersection of sensitive identity groups that are concealed under one-dimensional analysis., Comment: Code to reproduce our experiments is available at https://github.com/educational-technology-collective/cross-institutional-transfer-learning-facct-2023

This paper presents a novel approach for controlling humanoid robots pushing heavy objects using kinodynamics-based pose optimization and loco-manipulation MPC. The proposed pose optimization plans the optimal pushing pose for the robot while accounting for the unified object-robot dynamics model in steady state, robot kinematic constraints, and object parameters. The approach is combined with loco-manipulation MPC to track the optimal pose. Coordinating pushing reaction forces and ground reaction forces, the MPC allows accurate tracking in manipulation while maintaining stable locomotion. In numerical validation, the framework enables the humanoid robot to effectively push objects with a variety of parameter setups. The pose optimization generates different pushing poses for each setup and can be efficiently solved as a nonlinear programming (NLP) problem, averaging 250 ms. The proposed control scheme enables the humanoid robot to push object with a mass of up to 20 kg (118$\%$ of the robot's mass). Additionally, the MPC can recover the system when a 120 N force disturbance is applied to the object., Comment: 8 pages, 9 figure, submitted to IROS 2023, supplementary video: https://youtu.be/iunrSQjQx4M

Bioactive glasses (Bioglasses) are widely synthesized by the conventional sol-gel method consisting of two main steps for sol and gel formation. However, the conversion from sol to gel requires a long time (5–7 days). In this study, the hydrothermal system was used to quickly synthesize the bioactive glass by reducing the conversion time from sol to gel. The hydrothermal assisted conventional sol-gel method was applied for synthesis of the bioactive glass 70SiO2–30CaO (mol%) (noted as 70S30C). The synthetic glass was investigated by the physical-chemical techniques. The ‘‘in vitro’’ experiments in SBF (Simulated Body Fluid) solution was also performed to evaluate the bioactivity of synthetic material. The obtained results show that the bioactive glass 70S30C was successfully elaborated by using the hydrothermal assisted conventional sol-gelmethod. The consuming time was reduced compared to the conventional method. The physical-chemical characterization confirmed that the synthetic glass is amorphous material with mesoporous structure consisting of interconnected particles.The specific surface area, pore volume and average pore diameter of synthetic glass were 142.8 m2/g, 0.52 cm3/g, and 19.1 nm, respectively. Furthermore, synthetic bioactive glass exhibited interesting bioactivity when immersed in simulated body fluid (SBF) solution for 1 days and good biocompatibility when cultured in cellular media.

Spatial transcriptomics (ST) to explore a vast amount of formalin-fixed paraffin-embedded (FFPE) archival cancer tissues has been highly challenging due to severalcritical technical issues. In this work, we optimised ST protocols to generateunprecedented spatial gene expression data for FFPE skin cancer. Skin is among themost challenging tissue types for ST due to its fibrous structure and a high risk ofRNAse contamination. We evaluated tissues collected from ten years to two yearsago, spanning a range of tissue qualities and complexity. Technical replicates andmultiple patient samples were assessed. Further, we integrated gene expressionprofiles with pathological information, revealing a new layer of molecular information.Such integration is powerful in cancer research and clinical applications. The dataallowed us to detect the spatial expression of non-coding RNAs. Together, this workprovides important technical perspectives to enable the applications of ST on archivedcancer tissues.

The three major skin cancer types - squamous cell carcinoma (SCC), basal cell carcinoma (BCC), and melanoma - account for >70% of all cancer. Although these cancers all derive from the outer skin layer (epidermis), variability in cell type composition and interactions causes substantial cross-cancer differences in disease initiation and invasive and metastatic potential. A knowledgebase of cell type composition and cell-to-cell interactions within the three skin cancers is needed to aid the assessment of risks and prognosis upon patient presentation. Here we integrated six distinct yet complementary spatial single-cell technologies to build the largest cell atlas and interactome of SCC, BCC, and melanoma to date. First, we performed single-cell RNA sequencing (scRNAseq) on >50,000 cells from 11 paired healthy and SCC patient biopsies. We found 30 molecularly-distinct cell types/states, 18 of which were significantly enriched in SCC tissues and expressed strong transcriptional signatures of pro-tumour signalling. GeoMx spatial proteomics data independently validated the presence of rare immune cell types defined by scRNAseq. Visium and CosMx transcriptomic analyses were performed for all three skin cancer types to map spatial neighbourhoods and construct a cell-to-cell interaction atlas. We screened all captured ligand-receptor (LR) pairs in 121 possible cell type combinations to reveal signalling between cancer types/states, patients, and tissue regions. With CosMx data, we found between 2-12 LR pairs specific to each cancer type, some of which have been previously implicated in skin cancer progression and metastasis. We independently validated two key LR interactions, PD1_PDL1 and IL34_CSF1R, using Opal Multiplex Polaris and RNAscope data. Downstream analysis of IL34_CSF1R signalling zones suggested enrichment of IL34-related antigen presenting pathways in melanoma. Overall, we present a valuable database and analysis approaches to reveal potential biomarkers of initiation and progression of the most lethal type (melanoma) and the most common types (SCC and BCC) of skin cancer. This resource is available for users to explore interactively at the skInteractive web browser: https://skincspatialatlas.web.app/

Gas tungsten arc welding (GTAW), also known as tungsten inert gas welding, is now widely used in the manufacturing industry. In GTAW, the weld size, especially the weld depth, is one of the important parameters of the weld. Many studies demonstrated that the weld depth significantly affects the quality of the weld joint and is greatly influenced by the welding current. Thus, estimating the welding current value for the desired weld depth is necessary. This paper presents a method to estimate the welding current in the GTAW process with a specified width penetration for AISI 304 stainless steel with 0.8[Formula: see text]mm thickness. The welding current determination of the GTAW process is performed by using the inverse method. In this work, the inverse method utilized is the Levenberg–Marquardt (LM) method. The advantage of the method is that the algorithm is simple, easy to apply, and has a high convergence rate. Two examples are considered to demonstrate the proposed method. The relative error between the desired width penetration of the weld value and the estimated width penetration of the weld by the LM method is very small (0.2% for case 1 and 0.08% for case 2). The results show that the proposed method efficiently estimates the welding current for a specified width penetration in the GTAW process.

Purpose To clarify the rate of posterior residual ridge resorption (PRRR) in different denture treatments and the factors that can affect PRRR. Study selection A bibliographical electronic search was conducted on MeSH, Web of Science, and Ovid databases. Hand searching was also conducted. Longitudinal studies recording the average rate of PRRR in the mandible were included. The effect size was calculated based on the mean rate of PRRR with standard deviation and group size. The random-effects analysis was used to perform meta-analyses across qualified studies. Results A total of 2245 eligible studies were collected from the MeSH, Web of Science, and Ovid databases and hand searching. In the end, 19 studies met the inclusion criteria and were extracted. The average rate of PRRR in different mandibular denture treatments was assessed in this systematic review. The mean combined effect size was -1.05 ± 0.5 (95% confidence interval [CI]: -3.18-1.08) between four-implant overdentures and two-implant overdentures. The combined effect size was -0.01 ± 0.22 (95% CI: -0.93-0.82) between complete dentures and two-implant overdentures. Body mass index, number of dentures used, denture wearing habit, impression technique, artificial tooth material, and peri-implant bone resorption showed no significant effect on the rate of PRRR. Gender, denture material, and relining frequency showed a significant effect on the rate of PRRR. Conclusions This review summarized different average rates of PRRR in mandibular denture treatments. Meta-analyses have reported that four-implant overdenture treatments can lower the rate of PRRR compared to two-implant overdenture treatments. However, there was no significant difference in the treatment effect between the complete denture and two-implant ov erdenture treatments.

The use of analytical methods from learning analytics (LA) research combined with visualizations of learning activities using learning design (LD) tools and frameworks has provided important insight into how instructors design for learning. Nonetheless, there are many subtle nuances in instructors’ design decisions that might not easily be captured using LA tools. Therefore, this study sets out to explore how and why instructors design for learning in an online and distance higher education setting by employing a mixed-method approach, which combined semi-structured interviews of 12 instructors with network analyses of their LDs. Our findings uncovered several underlying factors that influenced how instructors designed their modules and highlighted some discrepancies between instructors’ pedagogical beliefs and their actual LD as captured by the Open University Learning Design Initiative (OULDI). This study showcases the potential of combining LA with qualitative insights for a better understanding of the complex design process in online distance higher education.

Active search is a setting in adaptive experimental design where we aim to uncover members of rare, valuable class(es) subject to a budget constraint. An important consideration in this problem is diversity among the discovered targets -- in many applications, diverse discoveries offer more insight and may be preferable in downstream tasks. However, most existing active search policies either assume that all targets belong to a common positive class or encourage diversity via simple heuristics. We present a novel formulation of active search with multiple target classes, characterized by a utility function chosen from a flexible family whose members encourage diversity via a diminishing returns mechanism. We then study this problem under the Bayesian lens and prove a hardness result for approximating the optimal policy for arbitrary positive, increasing, and concave utility functions. Finally, we design an efficient, nonmyopic approximation to the optimal policy for this class of utilities and demonstrate its superior empirical performance in a variety of settings, including drug discovery.

Additional file 1.

Legged robots have shown remarkable advantages in navigating uneven terrain. However, realizing effective locomotion and manipulation tasks on quadruped robots is still challenging. In addition, object and terrain parameters are generally unknown to the robot in these problems. Therefore, this paper proposes a hierarchical adaptive control framework that enables legged robots to perform loco-manipulation tasks without any given assumption on the object's mass, the friction coefficient, or the slope of the terrain. In our approach, we first present an adaptive manipulation control to regulate the contact force to manipulate an unknown object on unknown terrain. We then introduce a unified model predictive control (MPC) for loco-manipulation that takes into account the manipulation force in our robot dynamics. The proposed MPC framework thus can effectively regulate the interaction force between the robot and the object while keeping the robot balance. Experimental validation of our proposed approach is successfully conducted on a Unitree A1 robot, allowing it to manipulate an unknown time-varying load up to $7$ $kg$ ($60\%$ of the robot's weight). Moreover, our framework enables fast adaptation to unknown slopes (up to $20^\circ$) or different surfaces with different friction coefficients., Comment: Accepted to appear at IEEE International Conference on Robotics and Automation (ICRA), 2023

Local optimization presents a promising approach to expensive, high-dimensional black-box optimization by sidestepping the need to globally explore the search space. For objective functions whose gradient cannot be evaluated directly, Bayesian optimization offers one solution -- we construct a probabilistic model of the objective, design a policy to learn about the gradient at the current location, and use the resulting information to navigate the objective landscape. Previous work has realized this scheme by minimizing the variance in the estimate of the gradient, then moving in the direction of the expected gradient. In this paper, we re-examine and refine this approach. We demonstrate that, surprisingly, the expected value of the gradient is not always the direction maximizing the probability of descent, and in fact, these directions may be nearly orthogonal. This observation then inspires an elegant optimization scheme seeking to maximize the probability of descent while moving in the direction of most-probable descent. Experiments on both synthetic and real-world objectives show that our method outperforms previous realizations of this optimization scheme and is competitive against other, significantly more complicated baselines., Comment: NeurIPS 2022

Alveolar cleft bone graft in the second stage of surgery was a crucial part of the cleft palate treatment protocol with many advantages: reconstructing bone for tooth eruption, supporting the periodontal structure for the teeth adjacent to the cleft, supporting and lifting the arch and preventing from collapsing of maxillary arch. Grafting technique and material are selected based on the treatment purpose that for orthodontic moving tooth into the arch or for dental implant rehabilitation. Cancellous material provides rapid vascularization and healing facilitating for tooth moving into the cleft site but easy to resorb that unsuitable for dental implant placement. While dense material is difficult to move teeth into the cleft but increase initial stability. Therefore, we offered a method that limit bone resorption, easily obtain the implant initial stability, quick osseointegration called two iliac cortical bone blocks sandwich technique for a purposes of dental implant rehabilitation. Treatment protocol started with orthodontic treatment prior alveolar bone grafting to create proper space for implant restoration. Our clinical experience with 32 cleft sites using two iliac cortical bone blocks sandwich had shown potential clinical application in follow-up time up to 96 months. Evaluation criteria of bone grafting for alveolar cleft included soft tissue condition of graft area, nasal fistula closure, bone grafting outcome, success in osseointegration and implant prosthesis. This chapter described in detail treatment procedure and outcomes of a new technique of two iliac cortical bone blocks sandwich for alveolar cleft in patients with unilateral cleft palate.

Accurate and timely measurement of learning engagement is crucial for the application of precision education. At the same time, it is still a central research theme, both in the learning analytics community as in the broader area of educational research. 'Engagement is one of the hottest research topics in the field of educational psychology' is for a good reason the opening sentence of a recent special issue. In our contribution, we propose a holistic approach to the measurement of engagement by integrating data of behavioral type through traces of learning processes captured from log files into affective, behavioral, and cognitive measures of engagement collected with surveys and cognitive measures from assessments for and as learning. We apply this holistic approach in an empirical analysis of dispositional learning analytics. Starting from four different engagement profiles created by two-step clustering, we find that these profiles primarily differ in their timing of engagement with learning. Next, we develop regression-based prediction models that make clear that trace, survey, and assessment data have complementary roles in signaling students at risk for failure and are all three crucial constituents of prediction equations that differ in the timing of learning feedback.

BackgroundImmunomodulatory therapy (IMT) is often considered for systemic treatment of non-infectious uveitis (NIU). During the evolving coronavirus disease-2019 (COVID-19) pandemic, given the concerns related to IMT and the increased risk of infections, an urgent need for guidance on the management of IMT in patients with uveitis has emerged.MethodsA cross-sectional survey of international uveitis experts was conducted. An expert steering committee identified clinical questions on the use of IMT in patients with NIU during the COVID-19 pandemic. Using an interactive online questionnaire, guided by background experience and knowledge, 139 global uveitis experts generated consensus statements for IMT. In total, 216 statements were developed around when to initiate, continue, decrease and stop systemic and local corticosteroids, conventional immunosuppressive agents and biologics in patients with NIU. Thirty-one additional questions were added, related to general recommendations, including the use of non-steroidal anti-inflammatory drugs (NSAIDs) and hydroxychloroquine.ResultsHighest consensus was achieved for not initiating IMT in patients who have suspected or confirmed COVID-19, and for using local over systemic corticosteroid therapy in patients who are at high-risk and very high-risk for severe or fatal COVID-19. While there was a consensus in starting or initiating NSAIDs for the treatment of scleritis in healthy patients, there was no consensus in starting hydroxychloroquine in any risk groups.ConclusionConsensus guidelines were proposed based on global expert opinion and practical experience to bridge the gap between clinical needs and the absence of medical evidence, to guide the treatment of patients with NIU during the COVID-19 pandemic.

There has been a growing interest in how teaching might be informed by learning design (LD), with a promising method for investigating LD being offered by the emerging field of learning analytics (LA). In this study, we used a novel LA for LD methodology to investigate the implementation of LD in an online distance learning context. A key innovation is the focus on patterns of LD. Using data from the virtual learning environment, outcomes data, and self-reports, for 47,784 students, we investigated the impact of those patterns on student behaviour, pass rates and satisfaction. A second innovation involves social network analysis. Our study revealed that different patterns of LD were associated with statistically significant differences in behaviour, but not in pass rates or satisfaction. Nonetheless, the study highlights that applying LA to LD might, in a virtuous circle, contribute to the validity and effectiveness of both, and to the enhancement of online distance learning.

Purpose: To examine the effect of the attachment features (abutment height, retention, and freedom of rotation) of implant overdentures on the bending strain around implants under an overdenture. Materials and Methods: Mandibular and maxillary edentulous models were fabricated and covered with silicone rubber. Strain gauges were attached to the four sides of each implant. Two implants (tissue-level implant, 4.1-mm diameter, 10-mm length) were placed bilaterally in the area between the mandibular canines and lateral incisors. A maxillary conventional denture and a mandibular overdenture were made to fit the edentulous models. Three levels of peri-implant bone resorption were created sequentially: no bone resorption, 0.8 mm, and 1.5 mm. Three kinds of attachments (magnetic, stud, and ball attachments) were used. Bending strains generated from a 98-N occlusal load through the maxillary denture were measured using a sensor interface, and the data were analyzed using the Kruskal-Wallis and Bonferroni tests. Multiple regression analysis was used to find the relationship between independent variables (peri-implant bone resorption level, abutment height, retention, and freedom of rotation) and the dependent variable (bending strain). Results: For all attachment types, the bending strains were smallest with no bone resorption and largest with 1.5-mm bone resorption (P < .05). Multiple regression analysis showed that abutment height had the greatest impact on the reduction of bending strain (beta = .413), followed by freedom of rotation (beta = −.349), and retention (beta = .107). Conclusion: Low abutment height, large freedom of rotation, and low retention can minimize bending strain around implants.

Ternary bioactive glass 58SiO2-33CaO-9P2O5 (wt.%) was elaborated by the acid-free hydrothermal method. Thermal behavior, textural property, phase composition, morphology, and ionic exchange were investigated by thermal analysis, N2 adsorption/desorption, XRD, FTIR, SEM, and ICP-OES analysis. The bioactivity and biocompatibility of synthetic bioactive glass were evaluated by in vitro experiments with SBF solution and cell culture medium. The obtained results confirmed that the acid-free hydrothermal process is one of the standard methods for preparing bioactive glass.

Performing highly agile acrobatic motions with a long flight phase requires perfect timing, high accuracy, and coordination of the full-body motion. To address these challenges, we present a novel approach on timings and trajectory optimization framework for legged robots performing aggressive 3D jumping. In our method, we firstly utilize an effective optimization framework using simplified rigid body dynamics to solve for contact timings and a reference trajectory of the robot body. The solution of this module is then used to formulate a full-body trajectory optimization based on the full nonlinear dynamics of the robot. This combination allows us to effectively optimize for contact timings while ensuring that the jumping trajectory can be effectively realized in the robot hardware. We first validate the efficiency of the proposed framework on the A1 robot model for various 3D jumping tasks such as double-backflips off the high altitude of 2m. Experimental validation was then successfully conducted for various aggressive 3D jumping motions such as diagonal jumps, barrel roll, and double barrel roll from a box of heights 0.4m and 0.9m, respectively., Comment: Accepted to the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)

Additional file 3. STROBE_checklist_cohort.

Additional file 4. Ethical Review Board Approval.

Additional file 1. Data collection form.

TOPIC The Collaborative Ocular Tuberculosis Study (COTS), supported by the International Ocular Inflammation Society, International Uveitis Study Group, and Foster Ocular Immunological Society, set up an international, expert-led consensus project to develop evidence- and experience-based guidelines for the management of tubercular uveitis (TBU). CLINICAL RELEVANCE The absence of international agreement on the use of antitubercular therapy (ATT) in patients with TBU contributes to a significant heterogeneity in the approach to the management of this condition. METHODS Consensus statements for the initiation of ATT in TBU were generated using a 2-step modified Delphi technique. In Delphi step 1, a smart web-based survey based on background evidence from published literature was prepared to collect the opinion of 81 international experts on the use of ATT in different clinical scenarios. The survey included 324 questions related to tubercular anterior uveitis (TAU), tubercular intermediate uveitis (TIU), tubercular panuveitis (TPU), and tubercular retinal vasculitis (TRV) administered by the experts, after which the COTS group met in November 2019 for a systematic and critical discussion of the statements in accordance with the second round of the modified Delphi process. RESULTS Forty-four consensus statements on the initiation of ATT in TAU, TIU, TPU, and TRV were obtained, based on ocular phenotypes suggestive of TBU and corroborative evidence of tuberculosis, provided by several combinations of immunologic and radiologic test results. Experts agreed on initiating ATT in recurrent TAU, TIU, TPU, and active TRV depending on the TB endemicity. In the presence of positive results for any 1 of the immunologic tests along with radiologic features suggestive of past evidence of tuberculosis infection. In patients with a first episode of TAU, consensus to initiate ATT was reached only if both immunologic and radiologic test results were positive. DISCUSSION The COTS consensus guidelines were generated based on the evidence from published literature, specialists' opinions, and logic construction to address the initiation of ATT in TBU. The guidelines also should inform public policy by adding specific types of TBU to the list of conditions that should be treated as tuberculosis.

Additional file 2. Supplementary results.

Additional file 1: Figure S1-S20.

Additional file 12:. Review history.

Bioactive glasses 70SiO2–(30-x)CaO–xZnO (x = 1, 3, 5 mol.%) were prepared by the acid-free hydrothermal method in keeping with green chemical technology. The synthetic glasses were investigated by TG-DSC, BET, XRD, and SEM–EDX methods. All synthetic glasses present mesoporous structures consisting of aggregates of nanoparticles. The bioactivity of synthetic glasses was confirmed through the formation of the hydroxyapatite phase after an in vitro experiment in simulated body fluid (SBF) solution. The effect of Zn addition is shown through the decrease in the bioactivity of synthetic glasses. Additionally, the inductively coupled plasma optical emission spectrometry (ICP-OES) analysis indicates that the Zn ions were released from the glassy networks during in vitro experiments, and they act as Zn(OH)2 suspended precipitation to inhibit the apatite deposition. The in vitro experiment in cell culture matter was performed for SaOS2 and Eahy929 cells. The results confirm the biocompatibility of synthetic glasses and the role of Zn addition in the proliferation of living cells.

Background Diabetic macular edema (DME) is the leading cause of visual loss in patients with diabetic retinopathy. There has been a paradigm shift in the treatment of DME since the advent of anti-vascular endothelial growth factor (anti-VEGF) therapy. The safety and efficacy of anti-VEGF therapy has been well established. Although efficacious, currently approved anti-VEGF agents are associated with certain limitations, which include, among others: frequent need for injections, high treatment cost and variable response to treatment. These challenges have led to an active search for more novel agents that may be able to overcome these limitations. Areas covered The index review focuses on novel treatment agents that target various pathways in patients with DME. These agents are used either as monotherapy or in combination with other agents in the management of DME. Drugs discussed include novel anti-VEGF inhibitors, TIE-2 receptor modulators, integrin peptide inhibitors, rho kinase inhibitors, and future therapies such as neuroprotection and gene therapy. Conclusions The future of investigational pharmacological therapy appears promising for patients with DME. Results from early clinical trials indicate that newer agents highlighted in the study may be safe and efficacious treatment options for patients with DME. However, data from large multicenter clinical trials need to be analyzed before these agents can be incorporated into clinical practice.

This article discusses a fixed critical security bug in Google Tink's Ed25519 Java implementation. The bug allows remote attackers to extract the private key with only two Ed25519 signatures. The vulnerability comes from the misunderstanding of what "final" in Java programming language means. The bug was discovered during security review before Google Tink was officially released. It reinforces the challenge in writing safe cryptographic code and the importance of the security review process even for the code written by professional cryptographers.

In this paper we consider a general task of jumping varying distances and heights for a quadrupedal robot in noisy environments, such as off of uneven terrain and with variable robot dynamics parameters. To accurately jump in such conditions, we propose a framework using deep reinforcement learning to leverage the complex solution of nonlinear trajectory optimization for quadrupedal jumping. While the standalone optimization limits jumping to take-off from flat ground and requires accurate assumption of robot dynamics, our proposed approach improves the robustness to allow jumping off of significantly uneven terrain with variable robot dynamical parameters. Through our method, the quadruped is able to jump distances of up to 1 m and heights of up to 0.4 m, while being robust to environment noise of foot disturbances of up to 0.1 m in height as well as with 5% variability of its body mass and inertia. This behavior is learned through just a few thousand simulated jumps in PyBullet, and we perform a sim-to-sim transfer to Gazebo. Video results can be found at https://youtu.be/jkzvL2o3g-s.

Designing a curriculum in online and distance education can be challenging because the processes of what, when, and how students study are not always visible to teachers due to the limited opportunities for face-to-face interactions. The aim of this thesis is to explore how teachers design for learning, together with how the learning design impacts upon the students’ actual engagement with the learning materials, with the subsequent effect on their academic performance. One way forward, is to build on the intersection between the most recent work in learning analytics and learning design research. I have therefore argued for and investigated the potential of incorporating the design of learning activities into the analysis of student learning behaviour. On the one hand, the visualisation of learning activities designed by teachers provides the pedagogical context to improve the interpreta-tion of the observed learning behaviour and its effect on academic performance. On the oth-er hand, the analysis of online digital traces of learning activities offers a dynamic account of how students learn in practice in a distance learning environment. As a result, this thesis sheds new light on the implicit process of how learning design influences student engagement in distance education\ud \ud By employing a mixed-method research design, I first examined how teachers design for learning using visualisations and network analysis of 37 modules over 30 weeks at The Open University. In the next step, I conducted an in-depth qualitative investigation with 12 teachers into the underlying factors that influenced their design decisions, as well as the perceived barriers and affordances of adopting approaches from the Open University Learning Design Initiative. The findings revealed common patterns as well as variations in learning design across modules and their disciplines of study. Analysis of the interviews revealed underlying tensions between teachers’ autonomy and the influence of management and institutional policies in the design process and the adoption of learning design tools. \ud \ud After laying out the foundation for understanding the learning design processes, I carried out a large-scale analysis of 37 modules and 45,190 students to examine how learning design influences student engagement, satisfaction, and performance. The findings indicated that learning design explained up to 69% of the variance in student engagement, which was strongly driven by assimilative, assessment, and communication activities. Finally, I conducted a fine-grained analysis exploring the (in)consistencies between learning design and student behaviour and how different engagement patterns impact academic performance. The analysis found misalignments between how teachers designed for learning and how students actually studied. In most weeks, students spent less time studying the assigned materials compared to the number of hours recommended by instructors. High-performing students not only studied ‘harder’ by spending more time, but also ‘smarter’ by engaging in a timely manner. \ud \ud Altogether, this thesis has contributed new scientific insights into the dynamic temporal aspects of how teachers design for learning and the relations between learning design, engagement, and academic performance in distance education. As an implication, the findings reported here demonstrated how learning design could improve the accuracy and interpretability of learning analytics models, and how learning analytics could help teachers identify potential inconsistencies between learning design and student behaviour.

In contemporary technology-enhanced, learning platforms that combine the learning of new concepts with the practicing of newly learned skills, students are offered multiple feedback options. Typically, a problem-solving exercise allows the option to check the correctness of the answer, for calling hints that provide a partial help in the sequence of problem-solving steps, or calling a fully worked-out example. This opens new opportunities for research into student learning tactics and strategies, leaving the traditional context of lab-based research following experimental design principles behind, going into the research of revealed learning choices of students learning in authentic settings. In this empirical study, we apply multi-modal data consisting of logged trace data, self-report surveys and learning performance data, to investigate antecedents and consequences of learning tactics and strategies applied by students learning introductory mathematics and statistics. We do so by distinguishing different learning profiles, determined by the intensity of using the platform and the relative amounts of examples and hints called. These learning profiles are related to prior knowledge and learning dispositions, as antecedents, and course performance, as a consequence. One of our findings is that of ‘help abuse’: students who bypass the option to call for hints as concrete feedback in their problem-solving journey and instead opt for calling generic solutions of the problem: the worked examples. This help abuse is associated with prior knowledge and learning dispositions, but much less with course performance.

Byzantine fault tolerance (BFT) has been extensively studied in distributed trustless systems to guarantee system's functioning when up to 1/3 Byzantine processes exist. Despite a plethora of previous work in BFT systems, they are mainly concerned about common knowledge deducible from the states of all participant processes. In BFT systems, it is crucial to know about which knowledge a process knows about the states of other processes and the global state of the system. However, there is a lack of studies about common knowledge of Byzantine faults, such as, whether existence of a Byzantine node is known by all honest nodes. In a dynamic setting, processes may fail or get compromised unexpectedly and unpredictably. It is critical to reason about which processes know about the faulty processes of the network. In this paper, we are interested in studying BFT systems in which Byzantine processes may misbehave randomly, possibly at some random periods of time. The problem of \emph{probabilistic Byzantine} (PB) processes studied in this paper is more general than the problems previously studied in existing work. We propose an approach that allows us to formulate and reason about the concurrent knowledge of the PB processes by all processes. We present our study of the proposed approach in both synchronous and asynchronous systems.

Smart contract (SC) platforms form blocks of transactions into a chain and execute them via user-defined smart contracts. In conventional platforms like Bitcoin and Ethereum, the transactions within a block are executed \emph{sequentially} by the miner and are then validated \emph{sequentially} by the validators to reach consensus about the final state of the block. In order to leverage the advances of multicores, this paper explores the next generation of smart contract platforms that enables concurrent execution of such contracts. Reasoning about the validity of the object states is challenging in concurrent smart contracts. We examine a programming model to support \emph{optimistic} execution of SCTs. We introduce a novel programming language, so-called OV, and a Solidity API to ease programing of optimistic smart contracts. OV language together with static checking will help reasoning about a crucial property of optimistically executed smart contracts -- the validity of object states in trustless systems.

Post-quantum cryptography is inevitable. National Institute of Standards and Technology (NIST) starts standardizing quantum-resistant public-key cryptography (aka post-quantum cryptography). The reason is that investment in quantum computing is blooming which poses significant threats to our currently deployed cryptographic algorithms. As a security engineer, to prepare for the apocalypse in advance, I've been watching the development of quantum computers and post-quantum cryptography closely. Never mind, I simply made up an excuse to study these fascinating scientific fields. However, they are extremely hard to understand, at least to an amateur like me. This article shares with you my notes with the hope that you will have an intuitive understanding of the beautiful and mind-blowing quantum algorithms and post-quantum cryptography. Update: Multivariate signature scheme Rainbow is broken by Ward Beullens. Supersingular Isogeny Diffie-Hellman protocol (SIDH) is broken by Wouter Castryck and Thomas Decru, Comment: Update: Multivariate signature scheme Rainbow is broken by Ward Beullens. Supersingular Isogeny Diffie-Hellman protocol (SIDH) is broken by Wouter Castryck and Thomas Decru