Miracle-dz/UniFAR-FTUs huggingface dataset:
Feasibility of spectra-based quantification algorithm for non-linear photoacoustic contrast agents

Photoacoustic (PA) imaging is a technique that visualizes the optical absorption characteristics with ultrasound-like spatial resolution. It has been demonstrated that molecular targeted contrast agents (CAs) have great potential in applying to the early detection of tumor. These CAs attach to the tissues of the subject of interest, i.e., the cancerous cells, and emit PA signals based on the absorbed light. Precise quantification of the CA expression is desired to identify the degree of the malignancies. The current quantification of the CA expression is based on the strength of the PA intensity with the assumption of its linearity between them. However, the estimation accuracy of such a method is limited because the PA intensity is affected by many factors including the light, sound, and tissue interactions and the use of CAs that do not present linearity. Here, we investigate a robust quantification method by using the spectroscopic relationship between the dye concentration and its corresponding PA variation. We introduce a spectroscopic decomposition algorithm considering multiple reference spectra to accommodate the non-linear behavior of sample concentrations. The in vitro validation of the concept was performed using the synthesized PA CA possessing the non-linear property. The concentration of the samples was successfully estimated with the algorithm. The introduced method improved the quantification accuracy by reducing the averaging estimation error from 15.89 𝜇M to 1.80 𝜇M, compared with the conventional estimation.
Shame, self-disgust, and envy: An experimental study on negative emotional response in borderline personality disorder during the confrontation with the own face

Background A markedly negative self-image and pervasive shame proneness have consistently been associated with borderline personality disorder (BPD). The present experimental study investigated the intensity of negative emotional responses with a focus on shame in BPD compared to healthy control persons (HCs) during an experimental paradigm promoting self-awareness, self-reflection, and self-evaluation. Furthermore, the relationship between levels of state shame during the experiment and shame proneness in BPD compared to HCs was examined. Methods A sample of 62 individuals with BPD and 47 HCs participated in the study. During the experimental paradigm, participants were presented with photos of (i) the own face, (ii) the face of a well-known person, and (iii) of an unknown person. They were asked to describe positive facets of these faces. Participants rated the intensity of negative emotions induced by the experimental task as well the pleasantness of the presented faces. Shame-proneness was assessed using the Test of the Self-Conscious Affect (TOSCA-3). Results Individuals with BPD experienced significantly higher levels of negative emotions than HCs both before and during the experimental task. While HC participants responded to their own face particularly with an increase in shame compared to the other-referential condition, the BPD patients responded above all with a strong increase of disgust. Furthermore, the confrontation with an unknown or well-known face resulted in a strong increase of envy in BPD compared to HC. Individuals with BPD reported higher levels of shame-proneness than HCs. Higher levels of shame-proneness were related to higher levels of state shame during the experiment across all participants. Conclusion Our study is the first experimental study on negative emotional responses and its relationship to shame proneness in BPD compared to HC using the own face as a cue promoting self-awareness, self-reflection, and self-evaluation. Our data confirm a prominent role of shame when describing positive features of the own face, but they emphasize also disgust and envy as distinct emotional experience characterizing individuals with BPD when being confronted with the self.
A Case Study of the Sensitivity of Numerical Simulation of Mesoscale Convective Systems to Varying Initial Conditions

Abstract A 12 h nested-grid numerical simulation of a warm-season mesoscale convective weather system (Zhang and Fritsch, 1986) is utilized as a control run in order to 1) test the sensitivity of the numerical simulation to different types of initial conditions; 2) examine the need for an observing system that would resolve mesoscale features; and 3) determine which meteorological variables need to be most carefully considered in observing system design and preprocessing analysis. It is found that improved observational capabilities are likely to have an important impact on the successful prediction of the timing and location of summertime mesoscale convective weather systems if mesoscale features can be resolved. In particular, the resolution of the moisture field significantly affects the prediction of the evolution of the convective weather systems. Correspondingly, the mesoscale distribution of precipitation is substantially affected, especially the location of the areas of heavy rain. It is also foun.
Complexing Governance Styles: Connecting Politics and Policy in Governance Theories

Governance theories consider policy steering as modes sustained in hierarchies, markets, and networks. If governance depoliticizes public management structures, then populism and technocratic forms’ emergence in politics is a threat to public governance. This article analyzes governance styles, showing how a reconciliation between the dimensions of policy and politics is necessary to think about policy steering’s complexity and its ensuing paths. We develop a typology of governance styles to address policy and political dynamics. This typology shows how different governance styles combine pluralist, populist, and technocratic elements, along with hierarchies, markets, and networks. We illustrate our typology with different policies conceived in distinct political regimes in Brazil. We argue that governance theories must incorporate a perspective of political conflict, path dependence, and contingency. This perspective on political conflict is essential for understanding governance reforms and how they shape public management practices.
Adjuvant transarterial chemoembolization timing after radical resection is an independent prognostic factor for patients with hepatocellular carcinoma

Background It has been reported that postoperative adjuvant TACE (PA-TACE) treatment decreases recurrence and significantly improves the survival of patients who undergo radical resection of hepatocellular carcinoma (HCC) with high-risk recurrence factors. However, when to perform PA-TACE has not been fully studied. Methods We retrospectively collected the clinicopathologic characteristics of the patients with HCC between October 2013 and June 2020. The optimal cutoff value for PA-TACE time was determined based on the R package “maxstat”. Logistic regression and Cox regression analysis were used to determine the effect of the choice of PA-TACE timing on prognosis. Results The analysis was performed on 789 patients with HCC, and 484 patients were finally involved and were divided into training cohort (378) and validation cohort (106). The PA-TACE timing was found to be associated with survival outcomes. Multivariate logistic analysis found independent predictors of the PA-TACE timing, including gender and history of HBV. Multivariate Cox analysis showed that Ki-67, tumor size, MVI and the PA-TACE timing were independent prognostic factors for RFS in HCC patients. Conclusions Based on this study, HCC patients with high-risk recurrence factors can receive personalized assistance in undergoing PA-TACE treatment and improve their survival outcomes.
Real-time neural-network-based denoising for intraoperative 4D-OCT

Noise decreases image quality in optical coherence tomography (OCT) and can obscure important features in real-time visualizations. In this work, we show that a neural network can be applied to denoise volumetric OCT data for intra-surgical visualization in real-time. We adapt a self-supervised training approach, not requiring any paired data for training. Several optimizations and trade-offs in deployment are required, with which we achieved processing times of only few milliseconds. While still being limited by the real-time requirements, denoising in this scenario can enhance surface visibility, and therefore allow guidance for more precise intra-surgical maneuvers.
NUMERICAL STUDY OF TURBULENT FLOW AND HEAT TRANSFER IN A CONVEX CHANNEL OF A CALORIMETRIC ROCKET CHAMBER

Turbulent flows and related heat transfer in a convex channel of a calorimetric rocket chamber are investigated by the nonlinear k–ϵ–fμ model of Park et al. [6] and large-eddy simulation (LES). In order to analyze the geometric effects on heat transfer, several radii of surface curvature 0.067 ≤ D/R ≤ 0.4 and nozzle-to-surface distances 0.5 ≤ H/D ≤ 1.5 are selected for five Reynolds numbers (5,000 ≤ ReD ≤ 75,000). Comparing with the LES results for an impinging jet flow along the convex surface, the nonlinear k–ϵ–fμ model shows some discrepancies. However, the model performance is sufficient to utilize for the investigation of parametric effects. The LES results showed the detailed description of vortical structures responsible for the production of turbulent kinetic energy. In addition, the characteristics of turbulent heat transfer under various conditions of convex channels are investigated by using the nonlinear k–ϵ–fμ model. Finally, the geometric effects on the local heat transfer and the Reynolds number dependence are scrutinized.
Observer-based control of discrete-time Lipschitzian non-linear systems: application to one-link flexible joint robot

The problem of designing asymptotic observers along with observer-based feedbacks for a class of discrete-time non-linear systems is considered. We assume that the system non-linearity is globally Lipschitz and the system is supposed to be stabilizable by a linear controller. Sufficient linear matrix inequality condition is derived to ensure the stability of the considered system under the action of feedback control based on the reconstructed states. A numerical example of a single-link flexible joint robot is presented to illustrate the efficacy of the theoretical developments.
Electrophoretically deposited zinc oxide thick film gas sensor

Fabrication of a ZnO gas sensor by electrophoretic deposition (EPD) is reported. EPD of submicron sized ZnO powder on an aluminium-chromium-iron alloy substrate was carried out in pure acetone. The porous thick film obtained was sintered at 1000/spl deg/C in air. A native aluminium oxide layer grown on the alloy substrate insulated the sintered ZnO layer from the metal substrate. Operated at 250/spl deg/C, the device showed a 20% conductance change in the presence of 10 ppm wood smoke.
Structure-control design of a mechatronic system with parallelogram mechanism using an estimation of distribution algorithm

ABSTRACT In this paper, a structure-control design methodology for simultaneously optimizing both mechanical structure and control of a parallelogram linkage robot is proposed. It takes into count the dynamical model and the mechanical parameters for the optimization process along with the controller. Thus, proportional-integral-derivative (PID) control and geometric variables are optimized in a simultaneously way. Through the concurrent procedure an optimal combination of the robot structure and controller gains is obtained. The global optimization problem is tackled by using an estimation of distribution algorithm (EDA) based on the Boltzmann distribution. The EDA seeks for the global optimum by estimating and sampling a probability distribution. The proposed methodology is verified through simulation experiments and applied to the design process of a parallelogram linkage system. The results obtained in experiments show the effectiveness of the proposal. This approach is generic and could be applied to other mechanisms in similar way when for concurrent process both kinematic and dynamic models are available along with the controller. In particular, the results are promising when the optimization parameters are uncorrelated, namely control and mechanical parameters.
Research Progress of Green Solvent in CsPbBr3 Perovskite Solar Cells

In optoelectronic applications, all-Brominated inorganic perovskite CsPbBr3 solar cells have received a great deal of attention because of their remarkable stability and simplicity of production. Most of the solvents used in CsPbBr3 perovskite solar cells are toxic, which primarily hinders the commercialization of the products. In this review, we introduce the crystal structure and fundamental properties of CsPbBr3 materials and the device structure of perovskite cells, summarize the research progress of green solvents for CsPbBr3 PSCs in recent years from mono-green solvent systems to all-green solvent systems, and discuss the approaches to improving the PCE of CsPbBr3 PSCs, intending to facilitate the sustainable development of CsPbBr3 perovskite solar cells. Finally, we survey the future of green solvents in the area of CsPbBr3 perovskite solar cells.
The factorization method for scatterers with different physical properties

The scattering of time-harmonic acoustic plane waves by a mixed type scatterer is considered. Such a scatterer is given as the union of several components with different physical properties. Some of them are impenetrable obstacles with Dirichlet or impedance boundary conditions, while the others are penetrable inhomogeneous media with compact support. This paper is concerned with modifications of the factorization method for the following two basic cases, one is the scattering by a priori separated sound-soft and sound-hard obstacles, the other one is the scattering by a scatterer with impenetrable (Dirichlet) and penetrable components. The other cases can be dealt with similarly. Finally, some numerical experiments are presented to demonstrate the feasibility and effectiveness of the modified factorization methods.
Sarcopenia and COVID-19 Outcomes

Abstract Coronavirus disease 2019 (COVID-19) spread rapidly and became a severe global public health threat. Older adults have a high risk of COVID-19 and its associated mortality. Sarcopenia has emerged as a predictor of poor outcomes in COVID-19 patients, including lengthy hospital stays, mortality, intensive care unit admission, need for invasive mechanical ventilation, and poor rehabilitation outcomes. Chronic inflammation, immune dysfunction, respiratory muscle dysfunction, and swallowing dysfunction may underlie the association between sarcopenia and the poor outcomes of COVID-19 patients. Interleukin 6 receptor blockers (tocilizumab or sarilumab) are recommended for treating patients with severe COVID-19, and their therapeutic effects on sarcopenia are of great interest. This review aimed to analyze the current reports on the association between sarcopenia and COVID-19 and provide an update on the contribution of sarcopenia to the severity and adverse outcomes of COVID-19 and its underlying mechanisms. We also aimed to explore the different screening tools for sarcopenia concurrent with COVID-19, and advocate for early diagnosis and treatment of sarcopenia. Given that the fight against the COVID-19 pandemic may be long-term, further research into understanding the effects of sarcopenia in patients infected with the Omicron variant is necessary.
Theory and practice on the self-calibration of a rotating and zooming camera from two views

The paper deals with first the uniqueness of the self-calibration of a rotating and zooming camera, mathematically, given two views. It is assumed that the principal point and the aspect ratio are fixed but the focal length changes as the camera rotates. In this case, theoretically at least one inter-image homography is enough to compute the internal calibration parameters as well as the rotation, and the self-calibration is unique up to a rotation. Secondly, it is shown that the calibration parameters can be obtained through a linear computation, even though the original problem is highly nonlinear, when the principal point is given a priori. Finally, the authors analyse the effects of the deviation of the principal point on the linear computation of the focal lengths and the rotation. From the mathematical analysis, it is found that the more the camera changes its zoom the larger the effects are, and the larger the rotation angle the smaller the effects are. Thus, the image centre may be taken as the principal point in practical applications. Experimental results using real images are also given.
Regulation of Paracellular Fluxes of Amino Acids by Claudin-8 in Normal Mouse Intestinal MCE301 Cells

The ingested proteins are catabolized to di/tri-peptides and amino acids (AAs), which are absorbed through various transporters in the small intestinal and colonic epithelial cells. Tight junctions (TJs) are formed between neighboring cells and restrict paracellular fluxes to mineral ions and aqueous molecules. However, it is unknown whether the TJs are implicated in the control of paracellular fluxes to AAs. The paracellular permeability is controlled by claudins (CLDNs), which comprise a family of over 20 members. Here, we found that CLDN8 expression is decreased by AAs deprivation in normal mouse colon-derived MCE301 cells. The reporter activity of CLDN8 was not significantly changed by AAs deprivation, whereas the stability of CLDN8 protein was decreased. MicroRNA analysis showed that AAs deprivation increases the expression of miR-153-5p which targets CLDN8. The AAs deprivation-induced decline of CLDN8 expression was reversed by a miR-153-5p inhibitor. The CLDN8 silencing enhanced the paracellular fluxes to AAs, especially middle molecular size AAs. The expression levels of colonic CLDN8 and miR-153-5p in aged mice were lower and higher than those in young mice, respectively. We suggest that AAs deprivation downregulates CLDN8-dependent barrier function, mediated by the elevation of miR-153-5p expression in the colon, in order to enhance the AAs absorption.
Biometric person authentication method using features extracted from pen holding style

The manner of holding a pen is distinctive among people. Therefore, pen holding style is useful for person authentication. In this paper, we propose a biometric person authentication method using features extracted from images of pen holding style. Images of the pen holding style are captured by a camera, and several features are extracted from the captured images. These features are compared with a reference dataset to calculate dissimilarity scores, and these scores are combined for verification using a three-layer perceptron. Preliminary experiments were performed by using a private database. The proposed system yielded an equal error rate (EER) of 2.6%.
Distributed adaptive controller for the cooperative control of networked parametric strict feedback systems

In this article, we investigate the cooperative control of networked parametric strict feedback systems in the presence of uncertainties and nonlinearities. A distributed controller is constructed recursively such that the synchronization error of agents’ outputs can be bounded, that is, practical output synchronization is achieved. By command-filtered backstepping approach, the derivation of the virtual control is avoided, which significantly reduces the computational burden of each agent. Moreover, the neighborhood information which is needed for agent i to construct its controller is minimized. Therefore, information transfer burden is eased as well. It is proved that practical output synchronization is achieved when the digraph has a spanning tree. Finally, the effectiveness of the proposed controller is illustrated by a numerical example.
Bimetallic oxide Cu2O@MnO2 with exposed phase interfaces for dual-effect purification of indoor formaldehyde and pathogenic bacteria

The combination of materials with different functions is an optimal strategy for synchronously removing various indoor pollutants. For multiphase composites, exposing all components and their phase interfaces fully to the reaction atmosphere is a critical problem that needs to be solved urgently. Here, a bimetallic oxide Cu2O@MnO2 with exposed phase interfaces was prepared by a surfactant-assisted two-step electrochemical method, which shows a composite structure of non-continuously dispersed Cu2O particles anchored on flower-like MnO2. Compared with the pure catalyst MnO2 and bacteriostatic agent Cu2O, Cu2O@MnO2 respectively shows superior dynamic formaldehyde (HCHO) removal efficiency (97.2% with a weight hourly space velocity of 120 000 mL g−1 h−1) and pathogen inactivation ability (the minimum inhibitory concentration for 104 CFU mL−1Staphylococcus aureus is 10 μg mL−1). According to material characterization and theoretical calculation, its excellent catalytic-oxidative activity is attributable to the electron-rich region at the phase interface which is fully exposed to the reaction atmosphere, inducing the capture and activation of O2 on the material surface, and then promoting the generation of reactive oxygen species that can be used for the oxidative-removal of HCHO and bacteria. Additionally, as a photocatalytic semiconductor, Cu2O further enhances the catalytic ability of Cu2O@MnO2 under the assistance of visible light. This work will provide efficient theoretical guidance and a practical basis for the ingenious construction of multiphase coexisting composites in the field of multi-functional indoor pollutant purification strategies.
A new forecasting model GDM(2,2,1) of dynamic systems

Usually, a linear differential equation is used to represent continuous dynamic systems, but a linear difference equation is used to represent discrete dynamic systems; AGO is one of the most important characteristics of grey theory and its main purpose is to reduce the randomness of data. Improvements upon the existing grey prediction model are made, for example, using a linear differential equation, instead of a linear difference equation, to replace the grey differential equation to analyse discrete systems in this article; approximating i–order derivatives by operating after cubic spline curve fitting of 1–AGO data; estimating the model parameters by means of the deterministic convergence scheme; using ARIMA models to analyse the leading indicator and using Fourier series with appropriately chosen values of parameters in the fitting of the input series. This new model presented in this article is called the grey dynamic model GDM(2,2,1).
The heuristic approach in finding initial values for minimum density power divergence estimators

It is well known that in the presence of outliers the maximum likelihood estimates are very unstable. In these situations, an alternative is resorting to the estimators based on the minimum density power divergence criterion for which feasible, computationally closed-form expressions can be derived, so that solutions can be achieved by any standard nonlinear optimization code. But since the function to be minimized is often ill-behaved, the convergence of the algorithm to optimal solutions strongly depends on the choice of the configuration of the initial values. A new procedure based on a heuristic local search approach is introduced in order to survey the parameters space and hence obtaining an accurate set of starting guesses for the gradient-method minimization routine.