Miracle-dz/UniFAR-FTUs huggingface dataset:
Benchmark Dataset Based on Category Maps with Indoor-Outdoor Mixed Features for Positional Scene Recognition by a Mobile Robot

This study was conducted to develop original benchmark datasets that simultaneously include indoor–outdoor visual features. Indoor visual information related to images includes outdoor features to a degree that varies extremely by time, weather, and season. We obtained time-series scene images using a wide field of view (FOV) camera mounted on a mobile robot moving along a 392-m route in an indoor environment surrounded by transparent glass walls and windows for two directions in three seasons. For this study, we propose a unified method for extracting, characterizing, and recognizing visual landmarks that are robust to human occlusion in a real environment in which robots coexist with people. Using our method, we conducted an evaluation experiment to recognize scenes divided up to 64 zones with fixed intervals. The experimentally obtained results using the datasets revealed the performance and characteristics of meta-parameter optimization, mapping characteristics to category maps, and recognition accuracy. Moreover, we visualized similarities between scene images using category maps. We also identified cluster boundaries obtained from mapping weights.
Composite clustering normal distribution transform algorithm

Scan registration is a fundamental step for the simultaneous localization and mapping of mobile robot. The accuracy of scan registration is critical for the quality of mapping and the accuracy of robot navigation. During all of the scan registration methods, normal distribution transform is an efficient and wild-using one. But normal distribution transform will lead to the unreasonable interruption when splitting the grid and can’t express the points’ local geometric feature by prefixed grid. In this article, we propose a novel method, composite clustering normal distribution transform, which comprises the density-based clustering and k-means clustering to aggregate the points with similar local distributing feature. It takes singular value decomposition to judge the suitable degree of one cluster for further division. Meanwhile, to avoid the radiating phenomenon of LIDAR in measuring the points’ distance, we propose a method based on trigonometric to measure the internal distance. The clustering method in composite clustering normal distribution transform could ensure the expression of LIDAR’s local distribution and matching accuracy. The experimental result demonstrates that our method is more accurate and more stable than the normal distribution transform and iterative closest point methods.
Performance assessment of distributed LQG control subject to communication delays

This paper deals with the control performance assessment of distributed networked control systems in the presence of communication delays. The best achievable steady-state performance of distributed networked control systems in the framework of distributed linear quadratic Gaussian (LQG) control is presented where communication delays serve as the most fundamental performance limitation. In the proposed distributed LQG control design, distributed controllers and distributed observers are designed simultaneously without using separation principle. And the non-applicability of separation principle is investigated and demonstrated in distributed networked control with communication delays. In order to handle time-varying communication delays, we propose to use lower and upper bounds to characterize the range of the best achievable control performance with respect to the range of the communication delays. The obtained results can be used to evaluate the potential performance improvement of an existing distributed networked control system. The proposed approach is illustrated through a numerical example.
A COMPLEX ORDER MODEL OF ATRIAL ELECTRICAL PROPAGATION FROM FRACTAL POROUS CELL MEMBRANE

Cardiac tissue is characterized by structural and cellular heterogeneities that play an important role in the cardiac conduction system. Under persistent atrial fibrillation (persAF), electrical and structural remodeling occur simultaneously. The classical mathematical models of cardiac electrophysiological showed remarkable progress during recent years. Among those models, it is of relevance the standard diffusion mathematical equation, that considers the myocardium as a continuum. However, the modeling of structural properties and their influence on electrical propagation still reveal several limitations. In this paper, a model of cardiac electrical propagation is proposed based on complex order derivatives. By assuming that the myocardium has an underlying fractal process, the complex order dynamics emerges as an important modeling option. In this perspective, the real part of the order corresponds to the fractal dimension, while the imaginary part represents the log-periodic corrections of the fractal dimension. Indeed, the imaginary part in the derivative implies characteristic scales within the cardiac tissue. The analytical and numerical procedures for solving the related equation are presented. The sinus rhythm and persAF conditions are implemented using the Courtemanche formalism. The electrophysiological properties are measured and analyzed on different scales of observation. The results indicate that the complex order modulates the electrophysiology of the atrial system, through the variation of its real and imaginary parts. The combined effect of the two components yields a broad range of electrophysiological conditions. Therefore, the proposed model can be a useful tool for modeling electrical and structural properties during cardiac conduction.
Partial results on dp-finite fields

We prove that NIP valued fields of positive characteristic are henselian. Furthermore, we partially generalize the known results on dp-minimal fields to dp-finite fields. We prove a dichotomy: if K is a sufficiently saturated dp-finite expansion of a field, then either K has finite Morley rank or K has a non-trivial Aut(K/A)-invariant valuation ring for a small set A. In the positive characteristic case, we can even demand that the valuation ring is henselian. Using this, we classify the positive characteristic dp-finite pure fields.
The origin of Galactic cosmic rays: Challenges to the standard paradigm

A critical review of the standard paradigm for the origin of Galactic cosmic rays (CRs) is presented. Recent measurements of local and far-away CRs reveal unexpected behaviors, which challenge the commonly accepted scenario. These recent findings are discussed, together with long-standing open issues. Despite the progress made thanks to ever-improving observational techniques and theoretical investigations, at present our understanding of the origin and of the behavior of CRs remains incomplete. We believe it is still unclear whether a modification of the standard paradigm, or rather a radical change of the paradigm itself is needed in order to interpret all the available data on CRs within a self-consistent scenario.
Poverty, Toxic Stress, and Education in Children Born Preterm.

BACKGROUND Preterm birth, defined as birth before the completion of 37 weeks of gestation, is a multifactorial global epidemic with psychosocial, economic, and physical ramifications affecting the child, family, and community at large. Toxic stress-the results of exposure to adverse childhood experiences-results in changes to brain structure and function that negatively affects future health. OBJECTIVES The aim of this study was to apply the Eco-Bio Developmental (EBD) Model of Poverty and Preterm Birth to the cross-sectional data of the 2016 National Survey of Children's Health (NSCH) to evaluate the associations between poverty, toxic stress, and prematurity on neurodevelopmental and educational outcomes. METHODS A subset of data representing children 6 to 11 years old (N = 15,010) from the 2016 NSCH was used for multivariate analysis of demographic variables, and neurodevelopmental and educational outcome variables. Pearson's chi-square, logistic regression and interaction effects explored the relationships between prematurity, toxic stress and poverty. RESULTS Children in this sample born preterm had a higher incidence of toxic stress, poverty, developmental delay, learning disability, intellectual disability, speech/language disorders, ADD/ADHD, autism, and special education/early intervention plans. The combination of poverty toxic stress and preterm birth significantly increased the risk of these conditions. After accounting for gender, insurance coverage, race, and parental education, children in the sample born preterm were more likely to experience developmental delay, intellectual disability, speech/language disorder, learning disability, and ADD/ADHD. Toxic stress increased the incidence of ADD/ADHD and autism in both the preterm and full-term samples.The negative effect of poverty and toxic stress on children born preterm as depicted by the EBD model is supported by this analysis. Healthcare providers are encouraged to address the tripartite vulnerability resulting from prematurity, poverty, and toxic stress.
A hybrid econometric-machine learning approach for relative importance analysis: Food inflation

A measure of relative importance of variables is often desired by researchers when the explanatory aspects of econometric methods are of interest. To this end, the author briefly reviews the limitations of conventional econometrics in constructing a reliable measure of variable importance. The author highlights the relative stature of explanatory and predictive analysis in economics and the emergence of fruitful collaborations between econometrics and computer science. Learning lessons from both, the author proposes a hybrid approach based on conventional econometrics and advanced machine learning (ML) algorithms, which are otherwise, used in predictive analytics. The purpose of this article is two-fold, to propose a hybrid approach to assess relative importance and demonstrate its applicability in addressing policy priority issues with an example of food inflation in India, followed by a broader aim to introduce the possibility of conflation of ML and conventional econometrics to an audience of researchers in economics and social sciences, in general.
Translocator Protein Localises To CD11b+ Macrophages In Atherosclerosis

Background Atherosclerosis is characterized by lipid deposition, monocyte infiltration and foam cell formation in the artery wall. Translocator protein (TSPO) is abundantly expressed in lipid rich tissues. Recently, TSPO has been identified as a potential diagnostic tool in cardiovascular disease. The purpose of this study was to determine if the TSPO ligand, 18F-PBR111, can identify early atherosclerotic lesions and if TSPO expression can be used to identify distinct macrophage populations during lesion progression. Methods and Results ApoE−/− mice were maintained on a high-fat diet for 3 or 12 weeks. C57BL/6J mice maintained on chow diet served as controls. Mice were administered 18F-PBR111 intravenously and PET/CT imaged. After euthanasia, aortas were isolated, fixed and optically cleared. Cleared aortas were immunostained with DAPI, and fluorescently labelled with antibodies to-TSPO, the tissue resident macrophage marker F4/80 and the monocyte-derived macrophage marker CD11b. TSPO expression and the macrophage markers were visualised in fatty streaks and mature lesions by light sheet microscopy. While tissue resident F4/80+ macrophages were evident in the arteries of animals without atherosclerosis, no CD11b+ macrophages were observed in these animals. In contrast, mature plaques had high CD11b and low F4/80 expression. A ~3-fold increase in the uptake of 18F-PBR111 was observed in the aortas of atherosclerotic mice relative to controls. Conclusions Imaging of TSPO expression is a new approach for studying atherosclerotic lesion progression and inflammatory cell infiltration. The TSPO ligand, 18F-PBR111, is a potential clinical diagnostic tool for the detection and quantification of atherosclerotic lesion progression in humans.
Testing a Goodwin Model with General Capital Accumulation Rate

We perform econometric tests on a modified Goodwin model where the capital accumulation rate is constant but not necessarily equal to one as in the original model (Goodwin, 1967). In addition to this modification, we find that addressing the methodological and reporting issues in Harvie (2000) leads to remarkably better results, with near perfect agreement between the estimates of equilibrium employment rates and the corresponding empirical averages, as well as significantly improved estimates of equilibrium wage shares. Despite its simplicity and obvious limitations, the performance of the modified Goodwin model implied by our results show that it can be used as a starting point for more sophisticated models for endogenous growth cycles.
Serum Cortisol as an Early Biomarker of Cardiopulmonary Parameters Within the First 24 Hours After Aneurysmal Subarachnoid Hemorrhage in Intensive Care Unit Patients

Objective: Cardiopulmonary complications/stress are well-known phenomena in patients after aneurysmal subarachnoid hemorrhage (aSAH) and might be associated with an elevated serum troponin I (TNI) level. Since the glucocorticoid hormone cortisol is released during stress situations, the present study was conducted to investigate the influence of serum cortisol (SC) on cardiac and pulmonary parameters in patients after aSAH within the first 24 hours of intensive care unit (ICU) treatment. Patients and Methods: We retrospectively analyzed a cohort of 104 patients with aSAH admitted to our emergency department between January 2008 and April 2017. Blood samples were taken to determine SC and TNI. Demographics, initial Glasgow Coma Scale (GCS) score, World Federation of Neurosurgical Societies (WFNS) score, and Fisher grade were evaluated retrospectively. Mean norepinephrine application rate (NAR) in µg/kg/min and mean inspiratory oxygen fraction (OF) within the first 24 hours were defined as cardiopulmonary parameters. Results: An elevated SC value was found in 44 (42%) patients, and 27 (26%) patients showed an increased TNI value. In patients with initially increased SC value, a significant higher NAR (P = .04) was needed. Furthermore, patients with initially elevated TNI value had a lower GCS score (P = .0013) and a higher WFNS score (P = .003) on admission and required a higher NAR (P = .02) as well as OF (P = .0008) within the first 24 hours of ICU treatment. Conclusions: In the current study, initially elevated SC values were associated with a higher need of NAR within the first 24 hours of ICU treatment after aSAH. Moreover, patients with initially elevated TNI values required an increased NAR and a higher OF so that these biomarkers could be useful to improve ICU treatment.
Decolonizing Pathways to Sustainability: Lessons Learned from Three Inuit Communities in NunatuKavut, Canada

Community led planning is necessary for Inuit to self-determine on their lands and to ensure the preservation of cultural landscapes and the sustainability of social-ecological systems that they are a part of. The sustainability efforts of three Inuit communities in Labrador during a Community Governance and Sustainability Initiative were guided by a decolonized and strength-based planning framework, including the values of Inuit in this study. This paper demonstrates that Inuit led planning efforts can strengthen community sustainability planning interests and potential. We situate the experiences of NunatuKavut Inuit within, and contribute to, the existing body of scholarly decolonization and sustainability literature. For many Indigenous people, including Inuit, decolonization is connected to inherent rights to self-determination. The findings suggest that decolonizing efforts must be understood and actualized within an Indigenous led research and sustainability planning paradigm that facilitates autonomous decision making and that is place based. Further, this study illustrates five predominant results regarding Inuit in planning for community sustainability that support sustainable self-determination. These include: inter and cross community sharing; identification of community strengths; strengthened community capacity; re-connection to community and culture; and the possibility for identification of sustainability goals to begin implementation through community led governance and planning processes.
Pericytes Favor Oligodendrocyte Fate Choice in Adult Neural Stem Cells

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS). Upon demyelination, oligodendrocyte progenitor cells (OPCs) are activated and they proliferate, migrate and differentiate into myelin-producing oligodendrocytes. Besides OPCs, neural stem cells (NSCs) may respond to demyelination and generate oligodendrocytes. We have recently shown that CNS-resident pericytes (PCs) respond to demyelination, proliferate and secrete Laminin alpha2 (Lama2) that, in turn, enhances OPC differentiation. Here, we aimed to evaluate whether PCs influence the fate choice of NSCs in vitro, towards the production of new myelin-producing cells. Indeed, upon exposure to conditioned medium derived from PCs (PC-CM), the majority of NSCs gave rise to GalC- and myelin basic protein (MBP)-expressing oligodendrocytes at the expense of the generation of GFAP-positive astrocytes. Consistent with these findings, PC-CM induces an increase in the expression of the oligodendrocyte fate determinant Olig2, while the expression level of the astrocyte determinant ID2 is decreased. Finally, pre-incubation of PC-CM with an anti-Lama2 antibody prevented the generation of oligodendrocytes. Our findings indicate that PCs-derived Lama2 instructs NSCs to an oligodendrocyte fate choice favoring the generation of myelin-producing cells at the expense of astrocytes in vitro. Further studies aiming to reveal the role of PCs during remyelination may pave the way for the development of new therapies for the treatment of MS.
Gardenia Decoction Prevent Intestinal Mucosal Injury by Inhibiting Pro-inflammatory Cytokines and NF-κB Signaling

Gardenia jasminoides Ellis, which belongs to the Rubiaceae family, is a widely used traditional Chinese medicine. Although effect of Gardenia jasminoides Ellis has been widely reported, its anti-inflammatory role in intestinal mucosal injury induced by LPS remains unclear. In the present study, we investigated the effects of decoction extracted from Gardenia jasminoides on the morphology and intestinal antioxidant capacity of duodenum induced by LPS in mice. Further analysis was carried out in the expression of inflammatory and anti-inflammatory cytokines. Nuclear factor-kappa B (NF-κB) was determined by Western blot. Gardenia jasminoides water extract was qualitative analyzed by high-performance liquid chromatography coupled with electro spray ionization quadrupole time-of-flight mass spectrometry. The results showed that Gardenia decoction markedly inhibited the LPS-induced Tumor necrosis factor (TNF)-α, Interleukin (IL)-6, IL-8, and IL-1 production. It was also observed that Gardenia decoction attenuated duodenum histopathology changes in the mouse models. Furthermore, Gardenia decoction inhibited the expression of NF-κB in LPS stimulated mouse duodenum. These results suggest that Gardenia decoction exerts an anti-inflammatory and antioxidant property by up-regulating the activities of the total antioxidant capacity (T-AOC), the total superoxide dismutase (T-SOD), and glutathione peroxidase (GSH-Px). Gardenia decoction is highly effective in inhibiting intestinal mucosal damage and may be a promising potential therapeutic reagent for intestinal mucosal damage treatment.
On the relation between Sion's minimax theorem and existence of Nash equilibrium in asymmetric multi-players zero-sum game with only one alien

We consider the relation between Sion's minimax theorem for a continuous function and a Nash equilibrium in an asymmetric multi-players zero-sum game in which only one player is different from other players, and the game is symmetric for the other players. Then, 1. The existence of a Nash equilibrium, which is symmetric for players other than one player, implies Sion's minimax theorem for pairs of this player and one of other players with symmetry for the other players. 2. Sion's minimax theorem for pairs of one player and one of other players with symmetry for the other players implies the existence of a Nash equilibrium which is symmetric for the other players. Thus, they are equivalent.
Promoting cooperation by reputation-driven group formation

In previous studies of the spatial public goods game, each player is able to establish a group. However, in real life, some players cannot successfully organize groups for various reasons. In this paper, we propose a mechanism of reputation-driven group formation, in which groups can only be organized by players whose reputation reaches or exceeds a threshold. We define a player’s reputation as the frequency of cooperation in the last T time steps. We find that the highest cooperation level can be obtained when groups are only established by pure cooperators who always cooperate in the last T time steps. Effects of the memory length T on cooperation are also studied.
Rethinking the Evaluation of Video Summaries

Video summarization is a technique to create a short skim of the original video while preserving the main stories/content. There exists a substantial interest in automatizing this process due to the rapid growth of the available material. The recent progress has been facilitated by public benchmark datasets, which enable easy and fair comparison of methods. Currently the established evaluation protocol is to compare the generated summary with respect to a set of reference summaries provided by the dataset. In this paper, we will provide in-depth assessment of this pipeline using two popular benchmark datasets. Surprisingly, we observe that randomly generated summaries achieve comparable or better performance to the state-of-the-art. In some cases, the random summaries outperform even the human generated summaries in leave-one-out experiments. Moreover, it turns out that the video segmentation, which is often considered as a fixed pre-processing method, has the most significant impact on the performance measure. Based on our observations, we propose alternative approaches for assessing the importance scores as well as an intuitive visualization of correlation between the estimated scoring and human annotations.
Nonparametric Tests for Treatment Effect Heterogeneity With Duration Outcomes

Abstract This article proposes different tests for treatment effect heterogeneity when the outcome of interest, typically a duration variable, may be right-censored. The proposed tests study whether a policy (1) has zero distributional (average) effect for all subpopulations defined by covariate values, and (2) has homogeneous average effect across different subpopulations. The proposed tests are based on two-step Kaplan–Meier integrals and do not rely on parametric distributional assumptions, shape restrictions, or on restricting the potential treatment effect heterogeneity across different subpopulations. Our framework is suitable not only to exogenous treatment allocation but can also account for treatment noncompliance—an important feature in many applications. The proposed tests are consistent against fixed alternatives, and can detect nonparametric alternatives converging to the null at the parametric -rate, n being the sample size. Critical values are computed with the assistance of a multiplier bootstrap. The finite sample properties of the proposed tests are examined by means of a Monte Carlo study and an application about the effect of labor market programs on unemployment duration. Open-source software is available for implementing all proposed tests.