Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and Design of a Tandem Axial-flow Left Ventricular Assist System

Over the years, the number of deaths caused by cardiovascular diseases has been increasing. As a type of cardiovas-cular disease, heart failure also shows a rapid growth trend worldwide. China has a huge population of heart failure patients, and the number of new heart failure patients is also increasing year by year. At present, heart transplantation is the best treatment for end-stage heart failure when drug control is ineffective. However, due to many intractable problems, this surgical treatment has been difficult to carry out widely. Ventricular assist device (VAD), as the second-best alternative therapy for heart failure patients, has been identified as an important tool in the management of end-stage heart failure. Parallel ventricular assist devices have been becoming the main devices on the market, which increases the survival rate of patients to a certain degree. However, after the installation of this parallel ventricular assist device, the patient's quality of life has not been significantly improved. The patients are prone to many complications after receiving treatment, and the function of the heart is difficult to recover. Therefore, we propose a tandem left ventricular assist device (LVAD), which minimizes surgical trauma and postoperative complications. The life expectancy of patients with end-stage heart failure can be extended and the quality of life can be greatly improved. We model and simulate this device using a lumped parameter model of the cardiovascular system. According to the simulation results, the combination of LVAD and left heart is successful in this model, which enables the blood pressure and cardiac output of patients with end-stage heart failure to be increased to normal levels.
Koopman Operator Spectrum and Data Analysis

We examine spectral operator-theoretic properties of linear and nonlinear dynamical systems with globally stable attractors. Using the Kato Decomposition we develop a spectral expansion for general linear autonomous dynamical systems with analytic observables, and define the notion of generalized eigenfunctions of the associated Koopman operator. We interpret stable, unstable and center subspaces in terms of zero level sets of generalized eigenfunctions. We then utilize conjugacy properties of Koopman eigenfunctions and the new notion of open eigenfunctions - defined on subsets of state space - to extend these results to nonlinear dynamical systems with an equilibrium. We provide a characterization of (global) center manifolds, center-stable and center-unstable manifolds in terms of joint zero level sets of families of Koopman operator eigenfunctions associated with the nonlinear system.After defining a new class of Hilbert spaces, that capture the on and off attractor properties of dissipative dynamics, and introduce the concept of Modulated Fock Spaces}, we develop spectral expansions for a class of dynamical systems possessing globally stable limit cycles and limit tori, with observables that are square-integrable in on-attractor variables and analytic in off-attractor variables. We discuss definitions of stable, unstable and global center manifolds in such nonlinear systems with (quasi)-periodic attractors in terms of zero level sets of Koopman operator eigenfunctions. We define the notion of isostables for a general class of nonlinear systems. We provide a simple example of a measure-preserving system that is not chaotic but has continuous spectrum, and discuss experimental observations of spectrum on such systems. We define the coherent principal dimension for a class of datasets based on the lattice-type principal spectrum of the associated Koopman operator.
Automatic discovery of latent variable models

Much of our understanding of Nature comes from theories about unobservable entities. Identifying which hidden variables exist given measurements in the observable world is therefore an important step in the process of discovery. Such an enterprise is only possible if the existence of latent factors constrains how the observable world can behave. We do not speak of atoms, genes and antibodies because we see them, but because they indirectly explain observable phenomena in a unique way under generally accepted assumptions. How to formalize the process of discovering latent variables and models associated with them is the goal of this thesis. More than finding a good probabilistic model that fits the data well, we describe how, in some situations, we can identify causal features common to all models that equally explain the data. Such common features describe causal relations among observed and hidden variables. Although this goal might seem ambitious, it is a natural extension of several years of work in discovering causal models from observational data through the use of graphical models. Learning causal relations without experiments basically amounts to discovering an unobservable fact (does A cause B? ) from observable measurements (the joint distribution of a set of variables that include A and B). We take this idea one step further by discovering which hidden variables exist to begin with. More specifically, we describe algorithms for learning causal latent variable models when observed variables are noisy linear measurements of unobservable entities, without postulating a priori which latents might exist. Most of the thesis concerns how to identify latents by describing which observed variables are their respective measurements. In some situations, we will also assume that latents are linearly dependent, and in this case causal relations among latents can be partially identified. While continuous variables are the main focus of the thesis, we also describe how to adapt this idea to the case where observed variables are ordinal or binary. Finally, we examine density estimation, where knowing causal relations or the true model behind a data generating process is not necessary. However, we illustrate how ideas developed in causal discovery can help the design of algorithms for multivariate density estimation.
Causality-based Counterfactual Explanation for Classification Models

Counterfactual explanation is one branch of interpretable machine learning that produces a perturbation sample to change the model's original decision. The generated samples can act as a recommendation for end-users to achieve their desired outputs. Most of the current counterfactual explanation approaches are the gradient-based method, which can only optimize the differentiable loss functions with continuous variables. Accordingly, the gradient-free methods are proposed to handle the categorical variables, which however have several major limitations: 1) causal relationships among features are typically ignored when generating the counterfactuals, possibly resulting in impractical guidelines for decision-makers; 2) the counterfactual explanation algorithm requires a great deal of effort into parameter tuning for dertermining the optimal weight for each loss functions which must be conducted repeatedly for different datasets and settings. In this work, to address the above limitations, we propose a prototype-based counterfactual explanation framework (ProCE). ProCE is capable of preserving the causal relationship underlying the features of the counterfactual data. In addition, we design a novel gradient-free optimization based on the multi-objective genetic algorithm that generates the counterfactual explanations for the mixed-type of continuous and categorical features. Numerical experiments demonstrate that our method compares favorably with state-of-the-art methods and therefore is applicable to existing prediction models. All the source codes and data are available at \url{https://github.com/tridungduong16/multiobj-scm-cf}.
Spatio‐Temporal Coarse‐Graining Decomposition of the Global Ocean Geostrophic Kinetic Energy

We expand on a recent determination of the first global energy spectrum of the ocean's surface geostrophic circulation (Storer et al., 2022, https://doi.org/10.1038/s41467-022-33031-3) using a coarse‐graining (CG) method. We compare spectra from CG to those from spherical harmonics by treating land in a manner consistent with the boundary conditions. While the two methods yield qualitatively consistent domain‐averaged results, spherical harmonics spectra are too noisy at gyre‐scales (>1,000 km). More importantly, spherical harmonics are inherently global and cannot provide local information connecting scales with currents geographically. CG shows that the extra‐tropics mesoscales (100–500 km) have a root‐mean‐square (rms) velocity of ∼15 cm/s, which increases to ∼30–40 cm/s locally in the Gulf Stream and Kuroshio and to ∼16–28 cm/s in the ACC. There is notable hemispheric asymmetry in mesoscale energy‐per‐area, which is higher in the north due to continental boundaries. We estimate that ≈25%–50% of total geostrophic energy is at scales smaller than 100 km, and is un(der)‐resolved by pre‐SWOT satellite products. Spectra of the time‐mean circulation show that most of its energy (up to 70%) resides in stationary eddies with characteristic scales smaller than (<500 km). This highlights the preponderance of “standing” small‐scale structures in the global ocean due to the temporally coherent forcing by boundaries. By coarse‐graining in space and time, we compute the first spatio‐temporal global spectrum of geostrophic circulation from AVISO and NEMO. These spectra show that every length‐scale evolves over a wide range of time‐scales with a consistent peak at ≈200 km and ≈2–3 weeks.
Research on Photoinduction-Based Technology for Trapping Asian Longhorned Beetle (Anoplophora glabripennis (Motschulsky, 1853) (Coleoptera: Cerambycidae)

Simple Summary The Asian longhorned beetle (Anoplophora glabripennis) is an invasive species that attacks at least 209 species (or cultivars) of healthy trees. Several sex pheromones and host kairomones have been used as bites to monitor A. glabripennis in the field, but two beetles were captured by the dozens of traps at Cornuda, Italy, while no beetles were captured at Paddock wood, UK. Semiochemical-based traps have still not reached operational efficacy in the field. Therefore, an effective tool is needed for monitoring this beetle. Light traps were widely used in the monitoring and management of pest populations. However, the phototactic behavior of adults remains enigmatic. To provide a theoretical foundation to select the suitable light emitting diode (LED)-based light sources used for monitoring A. glabripennis, we first investigated the influence of exposure time and diel rhythm on the phototactic behavior of females and males to provide test conditions, and then tested effect of 14 different wavelength lights and intensity of the most preferred wavelength. Our findings show that 420 nm and 435 nm are the most suitable wavelengths for attracting adult A. glabripennis at night. This study can provide a theoretical basis for developing monitoring technologies for A. glabripennis based on LED light traps. Abstract Light traps play a crucial role in monitoring pest populations. However, the phototactic behavior of adult Asian longhorned beetle (ALB) remains enigmatic. To provide a theoretical foundation to select the suitable light emitting diode (LED)-based light sources used for monitoring ALB, we compared the effect of exposure time on the phototactic response rates of adults at wavelengths of 365 nm, 420 nm, 435 nm, and 515 nm, and found that the phototactic rate increased gradually when the exposure time was prolonged, but there was no significant difference between different exposure times. We evaluated the effect of diel rhythm and found the highest phototactic rate at night (0:00–2:00) under 420 nm and 435 nm illumination (74–82%). Finally, we determined the phototactic behavioral response of adults to 14 different wavelengths and found both females and males showed a preference for violet wavelengths (420 nm and 435 nm). Furthermore, the effect of the light intensity experiments showed that there were no significant differences in the trapping rate between different light intensities at 120 min exposure time. Our findings demonstrate that ALB is a positively phototactic insect, showing that 420 nm and 435 nm are the most suitable wavelengths for attracting adults.
AMELIORATING ACCESS TO PRIMARY HEALTH CARE SERVICES IN CAMEROON.

Samuel Nambile Cumber 2,3 , * Jackson Jr N. Ndenkeh 1,2,4 , Joyce Mahlako Tsoka-Gwegweni 3 and Thomas A. Vukugah 1 . 1. Department of Biomedical Sciences, University of Dschang, Cameroon. 2. Under Privileged Children and Women Assistance (UPCAWA), Cameroon. 3. Discipline of Public Health Medicine, Department of Nursing & Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa. 4. District Health Service of Abong Mbang, Cameroon. Manuscript Info Abstract . Manuscript History
SERUM IMMUNOGLOBULIN G ( IgG ) AS A PREDICTIVE MARKER OF EARLY RENAL AFFECTION IN TYPE 2 DIABETIC PATIENTS.

Fawzy A Elmessallamy 1 ,Abdallah Nawara 1 , Mohammad M. Sallam 1 and Hanaa H Elsaid 2 . 1. Internal Medicine Department, Faculty of Medicine, Zagazig University, Egypt. 2. Clinical Pathology Department , Faculty of Medicine, Zagazig University, Egypt. Manuscript Info Abstract . Manuscript History
Soil Moisture Controls on Spatial and Temporal Patterns of Carbon Dioxide Fluxes in Drylands

Dryland ecosystems provide a unique opportunity to study the effects of water limitation on ecosystem activity. The sensitivity of these systems to small inputs of moisture is well-documented, but the expression of water limitation in terms of carbon dioxide flux between the ecosystem and atmosphere remains unclear. Applying a simple conceptual approach to soil moisture dynamics, patterns in carbon flux become clear. Release of carbon dioxide via respiration is primarily driven by moisture in the shallow soil, and differences in respiration rates among plant functional types are only evident after controlling for soil moisture. Alternatively, carbon uptake by a semiarid shrubs ecosystem is largely driven by the availability of deep soil moisture. This link to deep soil moisture improves spatial scaling of gross and net carbon uptake using remote sensing data. Lateral redistribution of moisture on the landscape connects readily observed physical features, namely topography, to ecosystem function, but redistribution is generally not considered in carbon models. A simple runoff scheme coupled to a conceptual model for carbon flux demonstrates the high degree of spatial heterogeneity in carbon dioxide flux resulting from moisture redistribution. The importance of redistribution in carbon modeling is highlighted by interannual variability in modeled carbon fluxes under different rainfall characteristics (event size, event duration, interstorm duration). The links between hydrology and ecology across spatial scales become clearer when topographically-based moisture distribution is used as an organizing variable. In all, this research identifies new avenues for research where moisture dynamics are of central interest in dryland ecohydrology.
Chromite in Komatiites, II. Modification during Greenschist to Mid-Amphibolite Facies Metamorphism

Chromite compositions in komatiites are influenced by metamorphic chromite is highly susceptible to modification during processes, particularly above 500°C. Metamorphosed chromite is early hydrous alteration and subsequent prograde metasubstantially more iron rich than igneous precursors, as a result of morphism of host rocks. This modification is the subject Mg–Fe exchange with silicates and carbonates. Chromite metaof this paper. morphosed to amphibolite facies is enriched in Zn and Fe, and Metamorphic modification of chromite has been disdepleted in Ni, relative to lower metamorphic grades. Relative cussed extensively in the literature in the context mainly of proportions of the trivalent ions Cr, Al and Fe are not ophiolitic or ‘alpine ultramafic’ complexes (Onyeagocha, greatly modified by metamorphism up to lower amphibolite facies, 1974; Ulmer, 1974; Evans & Frost, 1975; Hoffman & although minor Fe depletion occurs during talc–carbonate alWalker, 1978; Loferski & Lipin, 1983; Kimball, 1990; teration at low temperature. Significant Al is lost from chromite Burkhard, 1993) and in a few studies of komatiitic rocks cores above 550°C, as a result of equilibration with fluids in (Bliss & MacLean, 1975; Donaldson, 1983; Gole & Hill, equilibrium with chlorite. Elevated Zn content in chromite is 1990), and in a detailed study of the Pechenga intrusions restricted to rocks with low (metamorphic) Mg/Fe ratios, and is (Abzalov, 1998). These studies have highlighted two the result of introduction of Zn during low-temperature alteration, important effects. First, chromites become rimmed and with further concentration and homogenization during prograde progressively replaced by chromian magnetite or ‘fermetamorphism. Cobalt and Mn also behave similarly, except where ritchromit’. Second, chromite core compositions become carbonate minerals are predominant in the metamorphic assemblage. progressively modified during prograde metamorphism Chromite at amphibolite facies is typically extensively replaced by as a result of exchange of components with surrounding magnetite. This is the result of incomplete metamorphic reaction silicate minerals (Evans & Frost, 1975; Abzalov, 1998). between chromite and chlorite-bearing silicate assemblages. MagThis paper examines the nature and magnitude of these netite compositions at the inner chromite–magnetite boundary are effects in komatiites from a variety of localities in the indicators of metamorphic grade. Eastern Goldfields Province of the Archaean Yilgarn Block in Western Australia (Fig. 1). Brief locality descriptions are given in Appendix B.
Regulation of the innate immune response and gut microbiome by p53

Abstract p53 is a key tumor suppressor mutated in half of human cancers. In recent years, p53 was shown to regulate a wide variety of functions. From the transcriptome analysis of 24 tissues of irradiated mice, we identified 553 genes markedly induced by p53. Gene Ontology (GO) enrichment analysis found that the most associated biological process was innate immunity. 16S rRNA‐seq analysis revealed that Akkermansia, which has anti‐inflammatory properties and is involved in the regulation of intestinal barrier integrity, was decreased in p53‐knockout (p53 −/− ) mice after radiation. p53 −/− mice were susceptible to radiation‐induced GI toxicity and had a significantly shorter survival time than p53‐wild‐type (p53 +/+ ) mice following radiation. However, administration of antibiotics resulted in a significant improvement in survival and protection against GI toxicity. Mbl2 and Lcn2, which have antimicrobial activity, were identified to be directly transactivated by p53 and secreted by liver into the circulatory system. We also found the expression of MBL2 and LCN2 was decreased in liver cancer tissues with p53 mutations compared with those without p53 mutations. These results indicate that p53 is involved in shaping the gut microbiome through its downstream targets related to the innate immune system, thus protecting the intestinal barrier.
Offloading in P4 Switch Integrated with Multiple Virtual Network Function Servers

—Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two transformative technologies that offer distinct benefits. SDN virtualizes the control plane by separating it from the data plane, while NFV virtualizes the data plane by moving network functions from hardware and implementing them in software. Therefore, combining SDN and NFV can fully exploit the benefits of both technologies. As Programming Protocol-independent Packet Processors (P4) become popular due to its flexibility, traditional SDN switches are being replaced by P4 switches. In the P4+NFV architecture, network functions can be provided in both P4 switches (PNF) and NFV servers (VNF). However, to minimize packet delay, the offloading problem between P4 switches and NFV needs to be addressed. The novelty of our paper lies in investigating the offloading problem and evaluating the impact of employing multiple VNFs with varying computing capacities within the P4+NFV architecture. We also use M/M/1 queuing theory to derive the average packet delay and propose an optimization solution based on gradient descent to find out the optimal offloading probabilities of various VNF servers. Results show that optimal offloading from P4 switch to multiple VNFs can reduce the average packet delay from 4.76% to 40.02%.
Boosting Lidar 3D Object Detection with Point Cloud Semantic Segmentation

The integration of semantic information can effectively enhance the performance of 3D object detection based on lidar point cloud. Most of previous researches utilize camera-lidar fusion to improve detection accuracy for distant or small objects. However, this approach is typically unsuitable for real-time applications due to the large amount of input data. Recently, a multi-task framework using only Iidar has emerged as an alternative that employs the same feature extraction backbone with different heads to simultaneously output detection and semantic segmentation results for lidar point clouds. Nonetheless, some previous works have failed to achieve an optimal balance between accuracy and speed. To address this issue, we propose a multi-task framework which leverages the Cartesian pillar and a multi-scale semantic segmentation head to overcome the shortcomings of existing works and improve the detection accuracy. We evaluate the proposed method using typical pillar-based and voxel-based detection models on the nuScenes dataset. The experimental results demonstrate that the proposed design achieves better performance especially on small objects, compared to single-task models. Moreover, the proposed network increases mAP and NDS by 3.1 % and 2.5 % respectively on the nuScenes test set, compared to the representative multi-task network.