Miracle-dz/UniFAR-FTUs huggingface dataset:
Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction

Background The stratification of the general population according to health needs allows to provide better-tailored services. A simple score called Multisource Comorbidity Score (MCS) has been developed and validated for predicting several outcomes. The aim of this study was to evaluate whether the ability of MCS in predicting 1-year mortality improves by incorporating socioeconomic data (as measured by a deprivation index). Methods Beneficiaries of the Italian National Health Service who in the index year (2018) were aged 50–85 years and were resident in the Sicily region for at least 2 years were identified. For each individual, the MCS was calculated according to his/her clinical profile, and the deprivation index of the census unit level of the individual’s residence was collected. Frailty models were fitted to assess the relationship between the indexes (MCS and deprivation index) and 1-year mortality. Akaike information criterion and Bayesian information criterion statistics were used to compare the goodness of fit of the model that included only MCS and the model that also contained the deprivation index. The models were further compared by means of the area under the receiver operating characteristic curve (AUC). Results The final cohort included 1,062,221 individuals, with a mortality rate of 15.6 deaths per 1,000 person-years. Both MCS and deprivation index were positively associated with mortality. The goodness of fit statistics of the two models were very similar. For MCS only and MCS plus deprivation index models, Akaike information criterion were 17,013 and 17,038, respectively, whereas Bayesian information criterion were 16,997 and 17,000, respectively. The AUC values were 0.78 for both models. Conclusion The present study shows that socioeconomic features as measured by the deprivation index did not improve the capability of MCS in predicting 1-year risk of death. Future studies are needed to investigate other sources of data to enhance the risk stratification of populations.
Efficiency of Trans-dimensional Bayesian Inference for Geoacoustic Inversion

This paper considers the efficiency of trans-dimensional (trans-D) Bayesian inference methods applied to seabed geoacoustic inversion. Trans-D inversion is applied to sample the posterior probability density over geoacoustic parameters for a variable number of layers, providing seabed-profile estimates with uncertainties that include the uncertainty in the model parameterization. However, the approach is computationally intensive. Sampling efficiency is largely determined by the proposal schemes which are applied to generate perturbed values for existing parameters and for new parameters assigned to layers added to the model. Perturbations of existing parameters are considered in a principal-component space based on an eigen-decomposition of the unit-lag parameter covariance matrix (computed from the history of sampled models, a diminishing adaptation). The relative efficiency of proposing new parameters from the prior versus a Gaussian distribution focused near existing values is examined. Parallel tempering, which employs a sequence of interacting samplers in which the likelihood function is successively relaxed, is also considered as a means to increase the acceptance rate of new layers. The relative efficiency of various proposal schemes is compared through repeated inversions with a pragmatic convergence criterion. Results are presented for inversions of simulated and measured seabed reflection data.
Optimal design of the laser synthetic wavelength interferometer

Abstract. From the actual implementation of displacement measurement in the laser synthetic wavelength interferometer, a nonlinear error analysis model was proposed by detecting the simultaneous zero-crossing position errors of two interference signals. By using this model, periodic nonlinear errors resulting from the polarizing leakage induced by the imperfection or misalignment of the polarizing beamsplitter in the basic configuration of the interferometer were analyzed. In order to reduce periodic nonlinear errors, two optimized optical configurations of the interferometer were presented. The simulations and experiments for verifying the performance of three configurations of the interferometer were performed. The experimental results demonstrate that the optimized third configuration has good stability, with a standard deviation of about 0.7 nm.
Research on Sensing Compression Method in Image Denoising

This paper mainly studies a kind of different from the traditional signal processing theory, compressed sensing. The theory in the process of data transmission greatly save the space and the cost of storage and transmission is a new breakthrough in the data mining technology. Application of compressed sensing principle, the discrete tracking algorithm combined with matrix learning algorithm, to deal with the noise of original image. Through a large number of experiments show that the fusion algorithm is better than other similar algorithms in terms of denoising, is a better image denoising technique.
Mendelian Randomization and Transcriptome-Wide Association Analysis Identified Genes That Were Pleiotropically Associated with Intraocular Pressure

Background: Intraocular pressure (IOP) is a major modifiable risk factor for glaucoma. However, the mechanisms underlying the controlling of IOP remain to be elucidated. Objective: To prioritize genes that are pleiotropically associated with IOP. Methods: We adopted a two-sample Mendelian randomization method, named summary-based Mendelian randomization (SMR), to examine the pleiotropic effect of gene expression on IOP. The SMR analyses were based on summarized data from a genome-wide association study (GWAS) on IOP. We conducted separate SMR analyses using Genotype-Tissue Expression (GTEx) and Consortium for the Architecture of Gene Expression (CAGE) expression quantitative trait loci (eQTL) data. Additionally, we performed a transcriptome-wide association study (TWAS) to identify genes whose cis-regulated expression levels were associated with IOP. Results: We identified 19 and 25 genes showing pleiotropic association with IOP using the GTEx and CAGE eQTL data, respectively. RP11-259G18.3 (PSMR = 2.66 × 10−6), KANSL1-AS1 (PSMR = 2.78 × 10−6), and RP11-259G18.2 (PSMR = 2.91 × 10−6) were the top three genes using the GTEx eQTL data. LRRC37A4 (PSMR = 1.19 × 10−5), MGC57346 (PSMR = 1.19 × 10−5), and RNF167 (PSMR = 1.53 × 10−5) were the top three genes using the CAGE eQTL data. Most of the identified genes were found in or near the 17q21.31 genomic region. Additionally, our TWAS analysis identified 18 significant genes whose expression was associated with IOP. Of these, 12 and 4 were also identified by the SMR analysis using the GTEx and CAGE eQTL data, respectively. Conclusions: Our findings suggest that the 17q21.31 genomic region may play a critical role in the regulation of IOP.
Design, Synthesis, and Biomedical Application of Multifunctional Fluorescent Polymer Nanomaterials

Luminescent polymer nanomaterials not only have the characteristics of various types of luminescent functional materials and a wide range of applications, but also have the characteristics of good biocompatibility and easy functionalization of polymer nanomaterials. They are widely used in biomedical fields such as bioimaging, biosensing, and drug delivery. Designing and constructing new controllable synthesis methods for multifunctional fluorescent polymer nanomaterials with good water solubility and excellent biocompatibility is of great significance. Exploring efficient functionalization methods for luminescent materials is still one of the core issues in the design and development of new fluorescent materials. With this in mind, this review first introduces the structures, properties, and synthetic methods regarding fluorescent polymeric nanomaterials. Then, the functionalization strategies of fluorescent polymer nanomaterials are summarized. In addition, the research progress of multifunctional fluorescent polymer nanomaterials for bioimaging is also discussed. Finally, the synthesis, development, and application fields of fluorescent polymeric nanomaterials, as well as the challenges and opportunities of structure–property correlations, are comprehensively summarized and the corresponding perspectives are well illustrated.
Learning Temporal Attention Based Keypoint-Guided Embedding for Gait Recognition

Gait recognition is one of technology for biometrics at a distance that can be used to identify a human through walking postures and body shape. In the field of information forensics and security, gait recognition is exploited for crime prevention, forensic identification, and social security. However, the existing gait recognition methods usually consider the appearance, posture and temporal information separately, thus, we focus on considering a learned temporal attention mechanism to fuse these features in global and local manner. In this article, a novel gait recognition framework Temporal Attention and Keypoint-guided Embedding (GaitTAKE) is proposed, which effectively fuses temporal-attention-based global and local appearance feature and temporal aggregated human pose feature. Experimental results show that our proposed method achieves superior performance in gait recognition with rank-1 accuracy of 98.0% (normal), 97.5% (bag) and 92.2% (coat) on the CASIA-B gait dataset; 90.4% accuracy on the OU-MVLP gait dataset; 51.34% accuracy on the GREW dataset; 53.1% accuracy on the Gait3D gait dataset.
Dual-Channel EtherCAT Control System for 33-DOF Humanoid Robot TOCABI

Multi-axis actuation robotics systems comprising many joints with a floating base require more stability and safety than fixed robots and thus require more considerations. In this paper, we describe the implementation of a real-time EtherCAT control system for the TOCABI humanoid robot with 33 degrees of freedom (DOFs) is described. The focus is on the development of a high-performing EtherCAT MainDevice, which enables control of the robot’s high DOF at fast communication cycles. We also explore the use of a dual-channel EtherCAT MainDevice as a redundancy mechanism to handle communication disruptions and show that this configuration reduces the burden on the communication network and increases the communication cycle, leading to good real-time performance. To demonstrate the advantages of the system, we examine the performance of the EtherCAT communication and evaluate the impact of RTnet on real-time performance, demonstrating that a high-performing EtherCAT MainDevice having hard real-time capabilities can be established using open-source software. The results of this work demonstrate the potential of using dual channels in EtherCAT MainDevice configurations and utilizing open-source software to implement low-cost EtherCAT MainDevice systems. The paper’s contribution to the field is its indication of developing stable robot systems with high DOF, which require hard real-time capability, even with open-source software.
Unlocking Social Innovation in XR for Healthcare in Coastal Communities

This position paper reconsiders the “social” aspect of XR systems for healthcare, often developed following a “problem-solution” approach that neglects sociocultural factors affecting their codesign and successful adoption. Focusing on coastal and rural communities, we review and present key principles to consider when codesigning XR systems with marginalised groups. Our work stems from two projects funded by UK Research & Innovation that aim to promote healthy ageing in coastal communities.
Nonlinear aeroelastic analysis of high aspect-ratio wings using the method of numerical continuation

Nonlinear Aeroelastic Analysis of High Aspect-Ratio Wings Using the Method of Numerical Continuation. (May 2006) Chetan Nichkawde, B.Tech., Indian Institute of Technology Bombay; M.Tech., Indian Institute of Technology Bombay Chair of Advisory Committee: Dr. Thomas W. Strganac This research explores the impact of kinematic structural nonlinearities on the dynamics of a highly deformable cantilevered wing. Two different theoretical formulations are presented and analysed for nonlinear behavior. The first formulation, which is more conventional, assumes zero equilibrias and structural nonlinearities occur as terms up to third order in the Taylor series expansion of structural nonlinearities. In the second approach, no prior assumption about equilibria states of the wing is made. Kinematic nonlinearities due to curvature and inertia were retained in their exact form. Thus, the former becomes a special case of the latter. This nonlinear formulation permits the analysis of dynamics about nonzero trims. Nonzero trim states are computed as a system parameter is varied using a continuation software tool. The stability characteristics of these trim states are also ascertained. Various bifurcation points of the system are determined. Limit-cycle oscillations are also investigated for and are characterized in terms of amplitude of vibration. The research in particular examines the impact of in-plane degree of freedom on the stability of nonzero trim states. The effect of variation of system parameters such as stiffness ratio, aspect ratio and root angle of attack is also studied. The method of direct eigenanalysis of nonzero equilibria is novel and new for an aeroelastic system.
Overlapping and order-independent patterns in type theory

Pattern matching is a mechanism to write programs by case distinction and recursion in functional programming languages. In a language based on type theory with dependent types, pattern matching allows us to write not just programs, but also proofs. In order to check whether these proofs are correct, certain restrictions are put on definitions by pattern matching [Coq92]. These restrictions allow us to write definitions by pattern matching in function of the theoretically simpler eliminators [GMM06]. This ensures that definitions by pattern matching are correct, but also limits the expressiveness of the language. One of these restrictions is that patterns must form a covering, i.e. are created by repeatedly splitting on a pattern variable. Some dependently typed languages with pattern matching like Agda [Nor07] allow more general pattern sets, but translate them to a covering internally. In this translation, overlapping patterns are treated on a first-match basis. However, the result of the translation depends on the order of the clauses, even when the patterns do not overlap. This can lead to unexpected results for a user who doesn’t know the internal workings of this translation. This is a sign of bad abstraction. This thesis is concerned with making dependent pattern matching more intuitive for the user. We do this by interpreting each clause directly as a definitional equality, even when the patterns overlap. In particular, our interpretation doesn’t depend on the order of the patterns. This allows us to give definitions with overlapping patterns, which can be used to extend a function with extra evaluation rules. To interpret pattern matching in this way, we lift the restriction that the patterns must form a covering. Instead of this restriction, we give a more general criterion for completeness. In order to ensure correctness in the presence of overlapping patterns, we also give a criterion for confluence. By making all clauses hold as definitional equalities, definitions by pattern matching feel more like mathematical definitions, rather than program instructions. However, we lose the ability to translate pattern matching to the use of eliminators, making it more complex to understand theoretically. In order to reduce this loss, we will prove a theoretical result that gives an equivalence with non-overlapping definitions.
Social, Geographical and Income Inequality as Demonstrated by the Coronary Calcium Score: An Ecological Study in Sydney, Australia

Background: The coronary calcium score is a non-invasive biomarker of coronary artery disease. The concept of “arterial age” transforms the coronary calcium score to an expected age based on the degree of coronary atherosclerosis. This study aimed to investigate the relationship of socioeconomic status with the burden of coronary artery disease within Sydney, Australia. Methods: This was an ecological study at the postcode level of patients aged 45 and above who had completed a CT coronary calcium scan within New South Wales (NSW), Australia from January 2012 to December 2020. Arterial age difference was calculated as arterial age minus chronological age. Socioeconomic data was obtained for median income, Index of Relative Socio-economic Advantage and Disadvantage (IRSAD) score and median property price. Linear regression was used for analysis. Results: There were 17,102 patients across 325 postcodes within NSW, comprising 9129 males with a median arterial age difference of 7 years and 7972 females with -9 years. Income, IRSAD score and property price each had an inverse relationship with arterial age difference (p-values < 0.05). Conclusions: Income, socioeconomic status and local property prices are significantly correlated with premature coronary aging. Healthcare resource allocation and prevention should target the inequalities identified to reduce the burden of coronary artery disease.
IL-17A and Th17 Cells Contribute to Endometrial Cell Survival by Inhibiting Apoptosis and NK Cell Mediated Cytotoxicity of Endometrial Cells via ERK1/2 Pathway

Immune status including the immune cells and cytokine profiles has been implicated in the development of endometriosis. In this study, we analyzed Th17 cells and IL-17A in peritoneal fluid (PF) and endometrial tissues of patients with (n=10) and without (n=26) endometriosis. Our study has shown increased Th17 cell population and IL-17A level in PF with endometriosis patients. To determine the roles of IL-17A and Th17 cells in the development of endometriosis, the effect of IL-17A, major cytokine of Th17, on endometrial cells isolated from endometriotic tissues was examined. Recombinant IL-17A promoted survival of endometrial cells accompanied by increased expression of anti-apoptotic genes, including Bcl-2 and MCL1, and the activation of ERK1/2 signaling. In addition, treatment of IL-17A to endometrial cells inhibited NK cell mediated cytotoxicity and induced HLA-G expression on endometrial cells. IL-17A also promoted migration of endometrial cells. Our data suggest that Th17 cells and IL-17A play critical roles in the development of endometriosis by promoting endometrial cell survival and conferring a resistance to NK cell cytotoxicity through the activation of ERK1/2 signaling. Targeting IL-17A has potential as a new strategy for the treatment of endometriosis.
SCP-SLAM: Accelerating DynaSLAM With Static Confidence Propagation

DynaSLAM is the state-of-the-art visual simultaneous localization and mapping (SLAM) in dynamic environments. It adopts a convolutional neural network (CNN) for moving object detection, but usually incurs a very high computational cost because it performs semantic segmentation using the CNN model on every frame. This paper proposes SCP-SLAM, which accelerates DynaSLAM by running the CNN only on keyframes and propagating static confidence through other frames in parallel. The proposed static confidence characterizes the moving object features by the residual defined by inter-frame geometry transformation, which can be computed quickly. Our method combines the effectiveness of a CNN with the efficiency of static confidence in a tightly coupled manner. Extensive experiments on the publicly available TUM and Bonn RGB-D dynamic benchmark datasets demonstrate the efficacy of the method. Compared with DynaSLAM, it enables acceleration by a factor of ten on average, but retains comparable localization accuracy.
Investigation of Genes and Their Interactions in Liver Diseases Using Bioinformatics Algorithms

In this study, we considered progression of liver diseases. Particularly we considered Hepatocellular Carcinoma Cancer, HCC, whose patients have low survival rates. For this purpose, we researched molecular structures and protein interactions involved in the initiation and progression of HCC. We exploited microarray data samples and their gene expression profiles from literature. During analysis, we implemented statistical data analysis techniques and looked for Differentially Expressed Genes during the initiation and progression of HCC. As a result of this analysis we found 12 hub genes, where 3 of them (ANLN, TOP2A and ASPM) were upregulated and the others (CXCL14, LINC01093, OIT3, CLEC4G, THRSP, APOF, CLTRN and FCN3) were downregulated. By performing Gene Ontology Analysis, we classified genes with increased or decreased expressions in terms of cellular component, biological process, and molecular function. Subsequently, we executed protein-protein interaction network analysis and found important interactions between the hub genes. Results of data analysis concluded that these 12 genes and their interactions play a key role in the initiation and progression of significant liver diseases and can be used as a potential biomarker for disease progression. Furthermore, gene feature analysis showed that it is becoming more difficult to compensate functional deficiencies of the proteins encoded by these genes during biological processes. In particular, Gene Ontology Analysis denoted that TOP2A gene associates with many of the biological pathways and a change in the expression of this gene can cause decent problems in many cellular functions.
Physical Human–Robot Interaction Using a Macro–Mini Robotic System

In this article, we investigate the characteristics of a collaborative hybrid parallel robot. A comparison between this robot and other collaborative robots regarding the Cartesian inertia is presented to highlight the very low inertia of the hybrid parallel robot. A task space stiffness-damping control is also proposed. In order to improve the performance of macro--mini systems in the interaction context, an active macro-active mini system consisting of the hybrid parallel robot mounted on a three degrees of freedom (3-DOF) gantry translational robot is introduced. A control strategy for physical human–robot interaction is applied to the macro--mini arrangement. The stability of this method is analyzed and it is shown that the macro–mini combination is more stable than the mini alone. An experimental validation is then carried out. The results obtained with the hybrid parallel robot show that the desired interaction force can be tracked at high speed and that prescribed impedance parameters can be precisely rendered to the human operator without using any additional sensor. Also, it is pointed out that the bandwidth of interaction of the hybrid parallel robot, as well as of the macro--mini system is much higher than that of other commercial collaborative robots. In addition, other tests are realized on the macro–mini system in order to verify the performance and to demonstrate potential applications. The macro–mini robot introduced in this work yields a very intuitive human–robot interaction, which makes it ideal for many applications in which direct physical teaching or assistance is needed.