Miracle-dz/UniFAR-FTUs huggingface dataset:
Point Cloud Registration Leveraging Structural Regularity in Manhattan World

Point cloud registration is an essential technique for many tasks including autonomous navigation, augmented/virtual reality and scene reconstruction. In man-made environments, abundant plane features with structural regularities are commonly seen, which is actually beneficial for point cloud registration. This paper presents an accurate and robust registration method that formulates the registration problem as a maximum likelihood estimation (MLE) problem where the useful structure information is also leveraged. To align two point sets efficiently, one point set is first represented as a Gaussian mixture models (GMM) tree, and then the Manhattan frame (MF) with dominant planes are estimated and the degenerated nodes corresponding to the dominant planes in the GMM tree are clustered to embody the structure information. The proposed MLE problem is solved by an Expectation Maximization (EM) framework. In the E step, the probabilistic data association between the GMM and another point set is first estimated and then refined by aligning the MF and planes. In the M step, an optimization problem using Mahalanobis distance is solved. Experimental results on both indoor room and hybrid man-made environments show that the proposed method not only achieves a good balance between accuracy and speed, but also provides robust and accurate performance in sequence registration process. The source code is available on our Github.11https://github.com/liu-jc18/StructRegistration.git
Textured Image Segmentation Using Markov Random Fields: Returning Multiple Solutions

Traditionally, the goal of image segmentation is to produce a single partition of an image. This partition is then compared to some \ground truth," or human approved partition, to evaluate the performance of the algorithm. This thesis utilizes a framework for considering a range of possible partitions of the image to compute a distribution of possible partitions of the image. This is an important distinction from the traditional model of segmentation, and has many implications in the integration of segmentation and recognition research. The probabilistic framework that enables us to return a con dence measure on each result also allows us to discard from consideration entire classes of results due to their low cumulative probability. Several experimental results are presented using Markov random elds as texture models to generate distributions of segments and segmentations on textured images. Both simple, homogeneous images and natural scenes are presented. iii Dedicated to my parents, Jack L. and Marian K. Nickels iv ACKNOWLEDGMENTS I would like to thank my parents, to whom this thesis is dedicated, for bringing me up with the inquisitive and adaptive mindset needed to do this research. I would like to thank my advisor, Professor Seth Hutchinson, for providing a rich, creative environment in which to work. His ideas and guidance have been invaluable. I would like to thank my anc ee, Betsy Furlong, for her loving and understanding while this work was going on. Between being a sounding-board for my ideas and a wonderful proofreader, she knows more about computer vision than most other biophysical chemists. I would like to thank my peers in the Computer Vision and Robotics research group for their many helpful discussions. I am especially grateful to Steve LaValle and Becky Casta~ no, whose work in segmentation paved the way for this research. v TABLE OF CONTENTS Chapter Page
Australia's 2019–20 mega‐fires are associated with lower occupancy of a rainforest‐dependent bat

Mega‐fires in the Australian summer of 2019–20 resulted in the largest ever documented forest fire extent. These fires impacted many species, but individual responses remain poorly known, making assessments of their conservation status and ongoing threats uncertain. We assessed the influence of the 2019–20 mega‐fires on habitat occupancy in the golden‐tipped bat Phoniscus papuensis, a specialist which roosts in suspended birds' nests and occurs in relictual Gondwanan rainforest not typically exposed to fire. We used trapping and accounted for nightly detection probability (lower detection with increasing rainfall) to estimate site occupancy. Occupancy increased with the local (1 km buffer surrounding each site) extent of rainforest, gullies and unburnt forest. The model predicted a strong negative effect of fire in the surrounding buffer, with occupancy reduced from >90% at sites with suitable habitat (extensive rainforest and gully systems) surrounded by unburnt forest to 20% when the entire surrounding area was burnt (regardless of severity). Gully rainforest sites surrounded by a mixture of burnt and unburnt forest were modelled to have intermediate occupancy values. On average, fire severity mapping revealed that 22% of rainforest in the 1 km buffer surrounding our burnt sites was unburnt, 61% had a low severity burn, while 17% experienced a high severity burn. The lower occupancy of P. papuensis in burnt rainforest was associated with a reduction in the abundance of suspended bird nests, a critical resource used for day‐roosting. Our results quantify the effects of extreme fire events on animal populations in rainforest that is normally unaffected by fire. The large extent of rainforest burnt during the 2019–20 Australian season of ‘mega‐fires’ and its strong negative effect on occupancy highlights the vulnerability of animal species reliant on fire‐sensitive habitat to a climate‐change driven increase in such extreme fire events.
A perturbative approach to study information communication in brain networks

Abstract How communication among neuronal ensembles shapes functional brain dynamics is a question of fundamental importance to neuroscience. Communication in the brain can be viewed as a product of the interaction of node activities with the structural network over which these activities flow. The study of these interactions is, however, restricted by the difficulties in describing the complex dynamics of the brain. There is thus a need to develop methods to study these network-dynamical interactions and how they impact information flow, without having to ascertain dynamics a priori or resort to restrictive analytical approaches. Here, we adapt a recently established network analysis method based on perturbations, it to a neuroscientific setting to study how information flow in the brain can raise from properties of underlying structure. For proof-of-concept, we apply the approach on in silico whole-brain models. We expound on the functional implications of the distributions of metrics that capture network-dynamical interactions, termed net influence and flow. We also study the network-dynamical interactions at the level of resting-state networks. An attractive feature of this method is its simplicity, which allows a direct translation to an experimental or clinical setting, such as for identifying targets for stimulation studies or therapeutic interventions.
Meiotic recombinaison analyses of individual chromosomes in male domestic pigs (sus scrofa domestica)

For the first time in the domestic pig, meiotic recombination along the 18 porcine autosomes was directly studied by immunolocalization of MLH1 protein. In total, 7,848 synaptonemal complexes from 436 spermatocytes were analyzed, and 13,969 recombination sites were mapped. Individual chromosomes for 113 of the 436 cells (representing 2,034 synaptonemal complexes) were identified by immunostaining and fluorescence in situ hybridization (FISH). The average total length of autosomal synaptonemal complexes per cell was 190.3 m m, with 32.0 recombination sites (crossovers), on average, per cell. The number of crossovers and the lengths of the autosomal synaptonemal complexes showed significant intra- (i.e. between cells) and inter-individual variations. The distributions of recombination sites within each chromosomal category were similar: crossovers in metacentric and submetacentric chromosomes were concentrated in the telomeric regions of the p- and q-arms, whereas two hotspots were located near the centromere and in the telomeric region of acrocentrics. Lack of MLH1 foci was mainly observed in the smaller chromosomes, particularly chromosome 18 (SSC18) and the sex chromosomes. All autosomes displayed positive interference, with a large variability between the chromosomes.
Safety from Fast, In-the-Loop Reachability with Application to UAVs

We present a runtime assurance (RTA) mechanism for ensuring safety of a controlled dynamical system and an application to collision avoidance of two unmanned aerial vehicles (UAVs). We consider a dynamical system controlled by an unverified and potentially unsafe primary controller that might, e.g., lead to collision. The proposed RTA mechanism computes at each time the reachable set of the system under a backup control law. We then develop a novel optimization problem based on control barrier functions that filters the primary controller when necessary in order to keep the system's reachable set within reach of a known, but conservative, safe region. The theory of mixed monotone systems is leveraged for efficient reachable set computation and to achieve a tractable optimization formulation. We demonstrate the proposed RTA mechanism on a dual multirotor UAV case study which requires a fast controller update rate as a result of the small time-scale rotational dynamics. In implementation, the algorithm computes the reachable set of an eight dimensional dynamical system in less than five milliseconds and solves the optimization problem in under one millisecond, yielding a controller update rate of 100Hz.
Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control

As a core component of the X-ray absorption fine structure spectroscopy (XAFS) system, the multi-channel double-crystal monochromator (DCM) can improve the time resolution of the system significantly. In contrast to the conventional single-channel DCM, the multi-channel DCM includes more pairs of crystals that are located separately in the master and slave motor axis with the same driving direction. However, a mismatched parallelism in the pitch direction, which can result from the manual mounting operation between the two separated crystals, directly affects the performance of the flux and the angular stability of the monochromatic beam. This poses a significant challenge to the precision position tracking of this system. In this paper, the mounting errors were translated into repetitive errors in the slave motor when the master motor was rotated at a constant velocity. Therefore, the iterative learning control (ILC) was considered in order to improve the tracking accuracy of the slave motor motion. The zero-magnitude error controller (ZMETC) was used to calculate the learning function to accelerate the convergence of the control inputs, and the convergence conditions of the control signal and error were also given. To validate the effectiveness of the proposed method, comparative experiments were performed on the motor motion platform. Experimental results indicated that the ILC effectively decreased the parallelism errors of the multi-channel DCM under various trajectories by comparing them with feedback controllers and the ZMETC, respectively.
Meta-Analysis of the Association Between Asthma and the Risk of Stroke

Introduction Asthma and stroke share many risk factors. Previous meta-analysis has indicated that asthma is associated with an increased risk of stroke. However, this study were limited by the small number of articles included and the lack of subgroup analyses of different stroke types and different populations. This meta-analysis aimed to synthesize evidence systematically to investigate the impact of asthma on stroke. Methods We searched Medline (via PubMed), Web of Science and EMBASE databases and manually identified eligible studies (inception dates to December 25, 2021) that analyzed the association between asthma and stroke. We conducted quality assessment to evaluate the risk of bias of studies and sensitivity analyses to test the robustness of results. Results We included 8 cohort studies and 10 cross-sectional studies comprised 3,011,016 participants. We found patients with asthma had a higher risk of stroke than patients without asthma [relative risk (RR): 1.34, 95% confidence interval (CI): 1.21–1.47]. Moreover, asthma significantly increased the risk of ischemic stroke (RR: 1.25, 95% CI: 1.06–1.47) without increasing the risk of hemorrhagic stroke (RR: 1.08, 95% CI: 0.87–1.34). Asthma increased the risk of stroke in both men (RR: 1.20, 95% CI: 1.10–1.32) and women (RR: 1.29, 95% CI: 1.12–1.48) with no significant difference between the sexes. We also found that patients with inactive asthma, child-onset asthma, or no smoking history did not have an increased risk of stroke. Conclusions These results supported the finding that asthma could significantly increase the risk of stroke, but this impact was not consistent in different populations. Systematic Review Registration https://www.crd. york.ac. uk/PROSPERO/display_record. php? RecordID=290745, identifier: CRD42021290745.
THE DYNAMICS OF DENSE STELLAR SYSTEMS

The stars may dissolve, and the fountain of light May sink into ne'er ending chaos and night. Shelley, October 1809 This is a review of the main physical processes which occur in dense stellar systems: gravitational relaxation, evaporation of stars, antiequipartition, growth of dense cores, stellar coalescence, stellar disruption, star-gas interactions, and star formation. These processes are combined to sketch theories of the formation, intermediate evolution, and ultimate fate of galactic nuclei. Key words: galactic nuclei - stellar dynamics - stellar collisions
A calculus for Belnap's logic in which each proof consists of two trees

In this paper we introduce a Gentzen calculus for (a functionally complete variant of) Belnap’s logic in which establishing the provability of a sequent in general requires two proof trees, one establishing that whenever all premises are true some conclusion is true and one that guarantees the falsity of at least one premise if all conclusions are false. The calculus can also be put to use in proving that one statement necessarily approximates another, where necessary approximation is a natural dual of entailment. The calculus, and its tableau variant, not only capture the classical connectives, but also the ‘information’ connectives of four-valued Belnap logics. This answers a question by Avron.
Thermoelectric properties and thermal stability of ferromagnetic half metallic CoVTe alloy, first principles study

ABSTRACT Thermoelectric properties and the thermal stability of ternary half-Heusler compound CoVTe are investigated for the first time, using the first principles computations. It is found that CoVTe alloy is an indirect half metallic ferromagnetic alloy. The integral value of the total magnetic moment obeys the Slater-Pauling rule which is in accordance with the half-metallic nature of this compound. The negative value of the formation energy EF and the positive value of the cohesive energy Ec show that this alloy can be easily produced experimentally with exothermic formation processes. The thermoelectric properties are computed at different temperatures from 0 to 900 K by step of 50 K and at different chemical potential values from −2 to 2 eV. Moreover, the lattice dynamical results regarding the phonon dispersion curves and phonon density of states are obtained and discussed. The investigated thermodynamic properties are in line with the results obtained by the Debye theory applied to several materials. The attractive magnetic half metallicity as well as the interesting thermoelectric properties make this alloy a good candidate for spintronic and thermoelectric applications.
How urban wellbeing is influenced by spatial urban parameters (density, morphology, vegetation & commerce), as examined in a VR framework

Urban environments face the serious challenge of complying with relatively tight constraints regarding land and tenant density. In fact, this has become a key constraint in both current and future urban designs. Moreover, wellbeing is strongly influenced by urban planning and design decisions. The objective of this study was to examine the effect of spatial parameters on the wellbeing of potential dwellers through VR experiments. The research incorporated two experiments that were conducted in a VR laboratory, by manipulating virtual twins of an existing urban environment. The first experiment focused on increased density levels combined with commerce and vegetation, while the second one focused on variant morphologies within a fixed density level. The results indicate that morphology, density, vegetation, and commercial activity have a significant impact on people’s wellbeing. The findings of this research emphasize certain design principles that could improve urban designs that are part of densification processes.
Multiple-Network Alterations in Major Depressive Disorder With Gastrointestinal Symptoms at Rest Revealed by Global Functional Connectivity Analysis

Objective Gastrointestinal (GI) symptoms are prominent in major depressive disorder (MDD) and bring patients lots of complaints and troubles. We aimed to explore whether there were some distinctive brain image alterations in MDD with GI symptoms, which could be used to distinguish MDD with GI symptoms from those without GI symptoms and healthy controls (HCs). Methods A total of 35 outpatients with GI symptoms, 17 outpatients without GI symptoms, and 28 HCs were recruited. All the participants were scanned by a resting-state functional magnetic resonance imaging. Imaging data were analyzed with the global functional connectivity (GFC) and support vector machine methods. Results MDD with GI symptoms showed decreased GFC in the left superior medial prefrontal cortex (MPFC) compared with MDD without GI symptoms. Compared with HCs, MDD with GI symptoms showed decreased GFC in the bilateral middle temporal pole (MTP) and left posterior cingulate cortex/precuneus (PCC/Pcu), and increased GFC in the right insula and bilateral thalamus. SVM analysis showed that an accuracy was 78.85% in differentiating MDD with GI symptoms from MDD without GI symptoms by using the GFC of the left superior MPFC. A combination of GFC of the left PCC/Pcu and bilateral MTP exhibited the highest accuracy (87.30%) in differentiating patients with MDD with GI symptoms from HCs. Conclusion MDD with GI symptoms showed abnormal GFC in multiple networks, including the default mode network and cortico-limbic mood-regulating circuit. Using abnormal GFC might work well to discriminate MDD with GI symptoms from MDD without GI symptoms and HCs.
Knowledge, Attitudes, and Preparedness for Managing Pregnant and Postpartum Women with COVID-19 Among Nurse-Midwives in Kenya

Introduction Globally, maternal morbidity and mortality have increased during the COVID-19 pandemic. Given the high burden of maternal and neonatal mortality in Kenya prior to COVID-19, front line health workers, including nurse-midwives, must be competent to ensure continued quality maternal services. Knowledge and awareness of COVID-19 transmission influence nurse-midwives risk perception and ability to implement prevention strategies. Objective We examined nurse-midwives’ knowledge, attitudes, and preparedness in managing pregnant and postpartum women with COVID-19 in Kenya. Methods A cross-sectional online survey was conducted among 118 nurse-midwives between July 2020 and November 2020. A 31-item survey comprising 15 knowledge, 11 attitude, and five preparedness questions was administered using SurveyMonkey. A link to the survey was distributed among nurse-midwives via email. Multiple logistic regression analysis was used to assess associations between the variables. A p-value <. 05 was considered statistically significant. Results Eighty-five participants were included in the final analysis (response rate 72%). Most participants were female (n = 69, 81.2%), 52.9% (n = 45) worked in labor wards, and 57.6% (n = 49) worked in rural hospitals. Overall, 71% (n = 57) of participants had sufficient knowledge about managing COVID-19 in pregnant and postpartum women. However, only 63% were willing to receive COVID-19 vaccination. Nurse-midwives working in urban areas were 3.7 times more likely to have positive attitudes than those in rural areas (odds ratio 3.724, 95% confidence interval 1.042–13.31; p = .043). Conclusion Nurse-midwives’ responses to the Kenyan government's COVID-19 guidelines for managing and caring for pregnant women were inconsistent. Continued professional development for nurse-midwives is important to ensure they stay abreast of evolving COVID-19 guidelines for maternal health. Our findings also suggest vaccine hesitancy may be a hurdle for ongoing COVID-19 vaccination.
Identification of Hub Genes and Immune-Related Pathways for Membranous Nephropathy by Bioinformatics Analysis

OBJECTIVE: We aim to explore the detailed molecular mechanisms of membrane nephropathy (MN) related genes by bioinformatics analysis. METHODS: Two microarray datasets (GSE108109 and GSE104948) with glomerular gene expression data from 65 MN patients and 9 healthy donors were obtained from the Gene Expression Omnibus (GEO) database. After processing the raw data, DEGs screening was conducted using the LIMMA (linear model for microarray data) package and Gene set enrichment analysis (GSEA) was performed with GSEA software (v. 3.0), followed by gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The protein-protein interaction (PPI) network analysis was carried out to determine the hub genes, by applying the maximal clique centrality (MCC) method, which was visualized by Cytoscape. Finally, utilizing the Nephroseq v5 online platform, we analyzed subgroups associated with hub genes. The findings were further validated by immunohistochemistry (IHC) staining in renal tissues from MN or control patients. RESULTS: A sum of 370 DEGs (188 up-regulated genes, 182 down-regulated genes) and 20 hub genes were ascertained. GO and KEGG enrichment analysis demonstrated that DEGs of MN were preponderantly associated with cell damage and complement cascade-related immune responses. Combined with literature data and hub gene-related MN subset analysis, CTSS, ITGB2, and HCK may play important roles in the pathological process of MN. CONCLUSION: This study identified novel hub genes in MN using bioinformatics. We found that some hub genes such as CTSS, ITGB2, and HCK might contribute to MN immunopathological process, providing new insights for further study of the molecular mechanisms underlying glomerular injury of MN.
Synchronous Retreat of Southeast Greenland's Peripheral Glaciers

Recently, scientific attention has focused on estimating Greenland's dynamic mass loss through changes to flow speeds, thickness, and length on its marine outlet glaciers. For the ice sheet outlet glaciers, dynamic mass loss has been found to be highly sensitive to changes in climate and individual glacier geometry. For the ice‐sheet‐independent marine glaciers around Greenland's periphery, dynamic mass loss is presently overlooked. Here, we apply an open‐source, automated method of measuring glacier length changes using satellite imagery, to produce highly detailed records of length changes for 135 peripheral marine glaciers in southeast Greenland. We find evidence for anomalous retreat across 56 glaciers coincident with elevated surface melt in 2016, with melt 22% above the 2013–2019 average. Our detailed observations resolve the widespread, rapid, and synchronous response of these independent marine glaciers to increased meltwater input in 2016, indicating that their dynamics may be more sensitive to atmospheric warming than currently thought.