Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Pathogenic Avipoxvirus Infecting Vulnerable Cook’s Petrel (Pterodroma cookii) in Australia Demonstrates a High Genomic and Evolutionary Proximity with South African Avipoxviruses

Emerging viral disease is a significant concern with potential consequences for human, animal, and environmental health. Over the past several decades, multiple novel viruses have been found in wildlife species, including birds, and they can pose a threat to vulnerable and endangered species. ABSTRACT Avipoxviruses are assumed to be restricted to avian hosts and are considered to be important viral pathogens that may impact the conservation of many vulnerable or endangered birds. Recent reports of avipoxvirus-like viruses from reptiles suggest that cross-species transmission may be possible within birds and other species. Most of the avipoxviruses in wild and sea birds remain uncharacterized, and their genetic variability is unclear. Here, cutaneous pox lesions were used to recover a novel, full-length Cook’s petrelpox virus (CPPV) genome from a vulnerable Cook’s petrel (Pterodroma cookii), and this was followed by the detection of immature virions using transmission electron microscopy (TEM). The CPPV genome was 314,065 bp in length and contained 357 predicted open-reading frames (ORFs). While 323 of the ORFs of the CPPV genome had the greatest similarity with the gene products of other avipoxviruses, a further 34 ORFs were novel. Subsequent phylogenetic analyses showed that the CPPV was most closely related to other avipoxviruses that were isolated mostly from South African bird species and demonstrated the highest sequence similarity with a recently isolated flamingopox virus (88.9%) in South Africa. Considering the sequence similarity observed between CPPV and other avipoxviruses, TEM evidence of poxvirus particles, and phylogenetic position, this study concluded that CPPV is a distinct candidate of avipoxviruses. IMPORTANCE Emerging viral disease is a significant concern with potential consequences for human, animal, and environmental health. Over the past several decades, multiple novel viruses have been found in wildlife species, including birds, and they can pose a threat to vulnerable and endangered species. Cook’s petrel is currently listed as vulnerable. The threats to the species vary, but are, to a large degree, due to anthropogenic impacts, such as climate change, habitat loss, pollution, and other disturbances by humans. Knowledge of viral pathogens, including poxvirus of Cook’s petrel is currently virtually nonexistent.
Four-Year Visual Outcomes in the Protocol W Randomized Trial of Intravitreous Aflibercept for Prevention of Vision-Threatening Complications of Diabetic Retinopathy.

Importance Anti-vascular endothelial growth factor (VEGF) injections in eyes with nonproliferative diabetic retinopathy (NPDR) without center-involved diabetic macular edema (CI-DME) reduce development of vision-threatening complications from diabetes over at least 2 years, but whether this treatment has a longer-term benefit on visual acuity is unknown. Objective To compare the primary 4-year outcomes of visual acuity and rates of vision-threatening complications in eyes with moderate to severe NPDR treated with intravitreal aflibercept compared with sham. The primary 2-year analysis of this study has been reported. Design, Setting, and Participants Randomized clinical trial conducted at 64 clinical sites in the US and Canada from January 2016 to March 2018, enrolling 328 adults (399 eyes) with moderate to severe NPDR (Early Treatment Diabetic Retinopathy Study [ETDRS] severity level 43-53; range, 0 [worst] to 100 [best]) without CI-DME. Interventions Eyes were randomly assigned to 2.0 mg aflibercept (n = 200) or sham (n = 199). Eight injections were administered at defined intervals through 2 years, continuing quarterly through 4 years unless the eye improved to mild NPDR or better. Aflibercept was given in both groups to treat development of high-risk proliferative diabetic retinopathy (PDR) or CI-DME with vision loss. Main Outcomes and Measures Development of PDR or CI-DME with vision loss (≥10 letters at 1 visit or ≥5 letters at 2 consecutive visits) and change in visual acuity (best corrected ETDRS letter score) from baseline to 4 years. Results Among participants (mean age 56 years; 42.4% female; 5% Asian, 15% Black, 32% Hispanic, 45% White), the 4-year cumulative probability of developing PDR or CI-DME with vision loss was 33.9% with aflibercept vs 56.9% with sham (adjusted hazard ratio, 0.40 [97.5% CI, 0.28 to 0.57]; P < .001). The mean (SD) change in visual acuity from baseline to 4 years was -2.7 (6.5) letters with aflibercept and -2.4 (5.8) letters with sham (adjusted mean difference, -0.5 letters [97.5% CI, -2.3 to 1.3]; P = .52). Antiplatelet Trialists' Collaboration cardiovascular/cerebrovascular event rates were 9.9% (7 of 71) in bilateral participants, 10.9% (14 of 129) in unilateral aflibercept participants, and 7.8% (10 of 128) in unilateral sham participants. Conclusions and Relevance Among patients with NPDR but without CI-DME at 4 years treatment with aflibercept vs sham, initiating aflibercept treatment only if vision-threatening complications developed, resulted in statistically significant anatomic improvement but no improvement in visual acuity. Aflibercept as a preventive strategy, as used in this trial, may not be generally warranted for patients with NPDR without CI-DME. Trial Registration ClinicalTrials.gov Identifier: NCT02634333.
Rotational stability of a new toric intraocular lens with an advanced optical profile

The main finding of this study was the rotational stability of a new toric IOL, the TECNIS Eyhance Toric II, over a course of 3 months. Purpose: To examine the rotational stability of a new toric intraocular lens (IOL), the TECNIS Eyhance Toric II, over a course of 3 months. Setting: Vienna Institute for Research in Ocular Surgery, Hanusch Hospital, Vienna, Austria. Design: Prospective unmasked single-center study. Methods: 50 eyes of 50 patients with cataract and regular corneal astigmatism ≥0.75 diopters (D) were included. The TECNIS Eyhance Toric II IOL was implanted in 1 eye of each study patient. Images of the alignment axis of the IOL were taken intraoperatively, as well as at 1 hour, 1 week, and 3 months postoperatively. For the measurement of toric IOL rotation, images were superimposed on the basis of ocular landmarks. Uncorrected and corrected distance (4 m) and intermediate (66 cm) visual acuities were assessed at the 3-month visit. Results: There was no significant difference in the rotational position between the intraoperative and 3 month timepoints, with a mean rotation of 1.34 ± 1.46 degrees, in 27 examined eyes. (P = 0.313). No patients had to undergo repositioning of the toric IOL. A significant reduction of refractive cylinder occurred from preoperatively 1.8 ± 1.1 to 0.40 ± 0.42 D at the 3-month visit (P = .001; n = 43). The corrected distance visual acuity improved significantly from 0.28 ± 0.16 logMAR preoperatively to −0.01 ± 0.13 logMAR at 3 months postoperatively (P = .001; n = 43). Conclusions: The TECNIS Eyhance Toric II showed a good visual performance with no significant rotation over a course of 3 months and, therefore, an excellent rotational stability. The intraocular lens showed a good safety profile with no adverse events.
Modeling the formation of defensive gaps in basketball: Cutting on a teammate’s drive

Basketball is a game of simultaneous actions, and inter-player coordination is key for offensive success. One of the most challenging aspects in this regard is basket cutting on a teammate’s drive. The ability to make these cuts is considered to be an artistic skill, mastered by only a handful of players. This skill is also hard to assess, as there is no method to measure the players’ capability with respect to this quality–especially not automatically. Using SportVU data from the NBA, we created a mathematical model that identifies the openings in the defense which allow to perform a cut. Our model succeeds to generalize, as it detects these openings on average 139ms earlier than the actual cuts start and has an overall (balanced) accuracy of 0.818 on the test set. Having a tree-based gradient boosting classifier, we received a clear hierarchy of feature importance and were able to inspect the interactions between these attributes during action. This way, the model gives insights about the kind of defensive movements needed for a player to allow enough space to cut while in practical usage the analysis of the output can also help the coaching staff in designing play options and assessing player abilities. By paying more attention to the possible off ball movements during drives, offensive plays can become more versatile–benefiting the participants and the spectators alike.
An Adaptive Edge Detection Method for Image Polluted by Hybrid Noise in Image Measurement

Edge detection directly affects the accuracy of image measurement. In this paper, focusing on the edge detection of the image of mechanical part polluted by hybrid noise consisting of Gaussian noise and impulse noise, an adaptive edge detection method is proposed. The proposed method combines a new hybrid filter smoothing noise adaptively with Canny operator to avoid the conflict of Canny operator between noise removing and edge locating, and uses Otsu threshold selection method to determine Dual-threshold of Canny operator adaptively. Using the gauge image polluted by hybrid noise as experiment object, the performance of the proposed method is evaluated qualitatively and quantitatively. Experimental results show that the proposed edge detection method has good performance.
The role of ectopic P granules protein 5 homolog (EPG5) in DHPG‐induced pain sensitization in mice

Nociplastic pain is a severe health problem, while its mechanisms are still unclear. (R, S)‐3,5‐Dihydroxyphenylglycine (DHPG) is a group I metabotropic glutamate receptor (mGluR) agonist that can cause central sensitization, which plays a role in nociplastic pain. In this study, after intrathecal injection of 25 nmol DHPG for three consecutive days, whole proteins were extracted from the L4~6 lumbar spinal cord of mice 2 h after intrathecal administration on the third day for proteomics analysis. Based on the results, 15 down‐regulated and 20 up‐regulated proteins were identified in mice. Real‐time quantitative PCR (RT‐qPCR) and western blotting (WB) revealed that the expression of ectopic P granules protein 5 homolog (EPG5) mRNA and protein were significantly up‐regulated compared with the control group, which was consistent with the proteomics results. Originally identified in the genetic screening of Caenorhabditis elegans, EPG5 is mainly involved in regulating autophagy in the body, and in our study, it was mainly expressed in spinal neurons, as revealed by immunohistochemistry staining. After the intrathecal injection of 8 μL adeno‐associated virus (AAV)‐EPG5 short hairpin RNA (shRNA) to knock down spinal EPG5, the hyperalgesia caused by DHPG was relieved. Altogether, these results suggest that EPG5 plays an important role in DHPG‐induced pain sensitization in mice.
Cells as the first data scientists

The concepts that we generally associate with the field of data science are strikingly descriptive of the way that life, in general, processes information about its environment. The ‘information life cycle’, which enumerates the stages of information treatment in data science endeavours, also captures the steps of data collection and handling in biological systems. Similarly, the ‘data–information–knowledge ecosystem’, developed to illuminate the role of informatics in translating raw data into knowledge, can be a framework for understanding how information is constantly being transferred between life and the environment. By placing the principles of data science in a broader biological context, we see the activities of data scientists as the latest development in life's ongoing journey to better understand and predict its environment. Finally, we propose that informatics frameworks can be used to understand the similarities and differences between abiotic complex evolving systems and life.
Mechanics and optimization of undulatory locomotion in different environments, tuning geometry, stiffness, damping and frictional anisotropy

One of the oldest yet most common modalities of locomotion known among limbless animals is undulatory, also recognized for its stability compared to legged locomotion. Multiple forms of active mechanisms, e.g. active gait control, and passive mechanisms, e.g. body morphology and material properties, have adapted to different environments. The current research explores the passive role of body stiffness and internal losses in meeting terrain requirements. Furthermore, it addresses the influence of the environment on the resultant gait and how the interplay between various environments and body properties can lead to different speeds. We modelled undulatory locomotion in a dry friction environment where frictional anisotropy determines propulsion. We found that the body stiffness, the moment of inertia, the dry frictional coefficient ratio between normal and tangential frictional constants, and the internal damping of the body play an essential role in optimizing speed and animal adaptability to external conditions. Furthermore, we demonstrate that various known gaits like swimming, crawling and polychaete-like locomotion are achieved as a result of the interaction between body and environment parameters. Moreover, we validated the model by retrieving a corn snake's speed using data from the literature. This study demonstrates that the dependence between morphology, body material properties and environment can be exploited to design long-segmented robots to perform in specialized situations.
Calibration techniques and datatype extraction for time-resolved optical tomography

This article describes the preprocessing and calibration methods currently applied to data acquired with the University College London multichannel time-resolved optical tomography system. We briefly outline the imaging system and describe the features of our experimentally collected data, sources of stochastic noise, and systematic errors. We examine two methods of calibrating data: “difference imaging” using two image data sets with and without the features of interest to produce an image, and “absolute imaging” using an independent calibration measurement. We describe the methods developed to apply each calibration to raw data. Although the difference imaging performed is found to produce images with fewer artifacts, analysis indicates that it will not be directly applicable for clinical applications. Also examined are the effects of using a two dimensional (2D) reconstruction scheme to produce images from measured data. For absolute imaging, artifacts are shown to dominate such images even in the case.
An Application Research on the MIS-Based Workflow Tools Integrated in a Large Hospital System

Based on the current hospital information system integration, point-to-point integration, agent-based information integration, component-based integration, the integration of middleware-based integration programs, such as the inadequacy of traditional, this article analysis the characteristics of an integrated hospital system, discussing the hospital system integration design, workflow mechanism based on the MIS integrated platform for development tools to customize and control processes to achieve strong to connect the main line to the node to work independently as a business system interface to enhance the scalability of loosely coupled integrated system framework and integrated programs, and give the integrated system framework and integrated programs included a integration platform based on workflow mechanism of MIS development tools, a strong connection customized and controlled by the main line, and the node to work independently as a business system interface to enhance the scalability of loosely. Keyword: WF-MIS; hospital information system; integration platform; process control; integrated program
Performance Implication of Tensor Irregularity and Optimization for Distributed Tensor Decomposition

Tensors are used by a wide variety of applications to represent multi-dimensional data; tensor decompositions are a class of methods for latent data analytics, data compression, and so on. Many of these applications generate large tensors with irregular dimension sizes and nonzero distribution. CANDECOMP/PARAFAC decomposition (Cpd) is a popular low-rank tensor decomposition for discovering latent features. The increasing overhead on memory and execution time of Cpd for large tensors requires distributed memory implementations as the only feasible solution. The sparsity and irregularity of tensors hinder the improvement of performance and scalability of distributed memory implementations. While previous works have been proved successful in Cpd for tensors with relatively regular dimension sizes and nonzero distribution, they either deliver unsatisfactory performance and scalability for irregular tensors or require significant time overhead in preprocessing. In this work, we focus on medium-grained tensor distribution to address their limitation for irregular tensors. We first thoroughly investigate through theoretical and experimental analysis. We disclose that the main cause of poor Cpd performance and scalability is the imbalance of multiple types of computations and communications and their tradeoffs; and sparsity and irregularity make it challenging to achieve their balances and tradeoffs. Irregularity of a sparse tensor is categorized based on two aspects: very different dimension sizes and a non-uniform nonzero distribution. Typically, focusing on optimizing one type of load imbalance causes other ones more severe for irregular tensors. To address such challenges, we propose irregularity-aware distributed Cpd that leverages the sparsity and irregularity information to identify the best tradeoff between different imbalances with low time overhead. We materialize the idea with two optimization methods: the prediction-based grid configuration and matrix-oriented distribution policy, where the former forms the global balance among computations and communications, and the latter further adjusts the balances among computations. The experimental results show that our proposed irregularity-aware distributed Cpd is more scalable and outperforms the medium- and fine-grained distributed implementations by up to 4.4 × and 11.4 × on 1,536 processors, respectively. Our optimizations support different sparse tensor formats, such as compressed sparse fiber (CSF), coordinate (COO), and Hierarchical Coordinate (HiCOO), and gain good scalability for all of them.
Recent Trends in Task and Motion Planning for Robotics: A Survey

Autonomous robots are increasingly served in real-world unstructured human environments with complex long-horizon tasks, such as restaurant serving and office delivery. Task and motion planning (TAMP) is a recent research method in Artificial Intelligence Planning for these applications. TAMP integrates high-level abstract reasoning with the low-level geometric feasibility check and thus is more comprehensive than traditional task planning methods. While regular TAMP approaches are challenged by different types of uncertainties and the generalization of various applications when implemented in real-world scenarios. This article systematically reviews the most relevant approaches to TAMP and classifies them according to their features and emphasis; it categorizes the challenges and presents online TAMP and machine learning-based TAMP approaches for addressing them.
Examining the Low- Resolution Electromagnetic Tomography Technique for EEG Brain Mapping

NeuroIS presents a new opportunity for information systems research. Often used neuroscience techniques include brain mapping with the functional magnetic resonance imaging (fMRI) device or eventrelated potential time-domain studies with the electroencephalogram (EEG). The critics of EEG consider the poor spatial resolution as justification for EEG's inadequacy to brain mapping studies. However, the low-resolution electromagnetic tomography (LORETA) technique provides strong estimation parameters allowing EEG to perform brain mapping. This paper presents EEG (with lower number of channels) and LORETA techniques as an effective approach for exploratory investigation specially when researchers are constrained with lack of resources (specially at significantly lower costs). We demonstrate the effectiveness of EEG using sLORETA with respect to fMRI as proof-of-concept approach to study IS phenomenon. The results of such studies can serve as a preliminary step for further analysis with the use of more sophisticated neuroscience devices. This can enhance IS research by taking advantage of both high temporal and spatial resolution leading to reduced estimation errors of neural activity and stronger basis for correlating neural activity and specific tasks. We also present a set of guidelines for using the LORETA family of techniques in IS research.
Patterns of Agile Coach roles

Agile software development, and other applications of agile working, continue to grow both in terms of usage and in terms of knowledge and lore. As a result the Agile Coach role has become an established role; yet the role is mired in confusion. This paper aims to reduce this confusion by differentiating the agile coach role. Agile coaches are not homogenous: some are directive, some non-directive, some deal with specific technologies while others address management and organisational form. Skills, experience, specialisation and motivations differ widely. Strictly speaking, other coaching roles, such as Product Coach, are distinct to agile. However, these roles are frequently used in conjunction with agile and managed in a similar fashion. Therefore, it makes sense to take a board view of coaching roles.
Patterns for the Advanced Design of Programming Exercises supported by Technology-Enhanced Assessment Systems

Students typically must work on complex exercises if they are about to learn advanced concepts of programming. Technology-enhanced assessment systems can not only be used to grade submissions to such exercises, but also as a support tool for students. In particular, they can support them in the learning process with automated, formative feedback. However, they cannot automatically reduce the complexity of the problems and thus reduce the cognitive load for the students. Instead, that can be achieved by careful exercise design in conjunction with specific features of technology-enhanced assessment systems. This paper introduces five patterns on how to split complex exercises into several parts so that additional benefits can arise from a close interaction between students and a technology-enhanced assessment systems with appropriate additional features beyond direct feedback generation.