Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation of Injectable Sodium Alginate/Platelet Rich Plasma Porous Microcarriers

Abstract Porous sodium alginate/platelet rich plasma (SA/PRP) microcarriers were fabricated using an emulsion method combined with a freeze-drying method. The effects of the composition, concentration and freeze temperature on the properties of the porous microcarriers were studied. The optimum conditions for fabrication of the SA/PRP microcarriers were determined as −20 °C, SA concentration of 2.0 wt% and mass ratio of 2:1 (SA to PRP) for carrying cells. The SA/PRP microcarriers, with an average diameter of 100–350 μm, showed an interconnective porous structure and the pore size was about 30–70 μm. Such porous SA/PRP may be considered as a promising candidate for injectable carriers supporting attachment and proliferation of cells.
Stressor Classification of Filipino Political Tweets Using LDA, SVM, XGBoost, Logistic Regression

With the advancement of technology, Filipinos have a means of connecting to social media mainly to share what they are doing or what they feel now. This could lead to people venting out their stress on platforms such as Twitter. One of the topics that cause people a lot of stress is Politics and many social media users share their opinions in a stressful manner on Twitter. This paper will focus on detecting the reason for stress called stressors from the tweet. This will be done by collecting tweets based on their hashtags and NLP technique called topic modeling specifically LDA to form the topic of stress for stress detection. Then Machine learning algorithms of SVM, XGBoost, and Logistic Regression will be used on the tweets and topics created by the Topic modeling to create and train a model that can predict stressors based on the tweets and topics.
Antioxidant and toxicological activities of Pyrossia lanceolata (L.) Farw. extracts

Background: Pyrrosia lanceolata (L.) farw. is one of the Polypodiaceae species that is commonly used as a traditional medicinal plant. Objective: The purpose of this study was to determine the antioxidant and toxic levels in the extracts of the species. Method: The aerial portion of the specie was extracted with methanol, followed by a liquid-liquid extraction with n-hexane, dichloromethane, and ethyl acetate. DPPH radicals and the brine shrimp lethality test, , were used to assess its antioxidant activity and toxicity. Result: The n-hexane extract exhibited no activity with IC50 values exceeding 500 μg/mL, whereas the ethyl acetate extract exhibited a high level of antioxidant activity with an IC50 value of 12.08±0.27 μg/mL. Moreover, when tested against Artemia salina leach, the toxicological level of the extracts was greater than 1000 μg/mL. Conclusion: These findings lay the groundwork for further investigation into the process of isolating and evaluating the biological activity of secondary metabolites that were discovered in the extract.
Self-Calibrating Gaze Estimation With Optical Axes Projection for Head-Mounted Eye Tracking

Gaze estimation suffers from burdensome personal calibration or complex all-device calibration. Self-calibrating methods can meet this challenge but depend on scenes and sacrifice accuracy. We propose a flexible and accurate gaze estimation approach calibrated implicitly with potential gaze patterns. By constructing an optical axis projection (OAP) plane and a visual axis projection (VAP) plane simultaneously, the optical axis and the visual axis can be represented as 2-D points, i.e., the OAP and VAP, which have a similarity transformation, indicating the linear consistency of OAP patterns with gaze patterns. Hence, a 3-D gaze estimation model using the OAP as an eye feature to predict the VAP is built. The unknown parameters are calculated separately by linearly aligning OAP patterns to natural and easily detectable gaze patterns. Experimental results show that the proposed gaze estimation approach is more accurate than state-of-the-art head-mounted gaze estimation methods, which require explicit calibration or multiscene saliency.
Distributed Finite-Time and Fixed-Time Nash Equilibrium Seeking for Non-Cooperative Game with Input Saturation

In this paper, a modified distributed Nash equilibrium seeking problem with input saturation has been investigated. The payoff function of each player is related to the communication topology, which is closer to the actual scenes. The sigmoid function is utilized to limit the range of the input. Through the network communication between players and the gradient of the players’ payoff functions, the finite-time and fixed-time distributed Nash equilibrium seeking protocols with input saturation are given. Using the Lyapunov stability analysis, it is determined that the action of each player converges to the Nash equilibrium if all the players update their action according to the proposed algorithms. The numerical simulations are also provided to testify the algorithms.
The applicability of decentralized ventilation equipment in radon mitigation from existing homes

This article exposes the results of radon mitigation in existing homes using decentralized ventilation equipment with heat recovery. The experimental measurement has been conducted in a large study about radon mitigation from existing homes in Romania. Various methods were treated separately to clearly expose the advantages and disadvantages for each method applied. This article focusses on the use of decentralized mechanical ventilation equipment with heat recovery. The analyzed dwelling is located in Cluj County, a radon prone area located in the west part of Romania. The preliminary measurements shown a high radon level inside the analyzed house. To prevent the high radon accumulation in the analyzed dwelling, a decentralized ventilation equipment was installed. The mean radon level inside the house decreases from 510 Bq/m3 (value recorded one year before mitigation), to approximately 361 Bq/m3 after the mitigation methods were applied, showing an reduction efficiency of approximately 30%.
Towards testing a dark matter candidate that emerges from the scalar ether theory

According to a scalar theory of gravity with a preferred frame, electromagnetism in the presence of a gravitational field implies that there is an additional energy tensor, which might contribute to dark matter. The expression of this tensor is determined by a mere scalar p, that depends on the EM field and (for a weak field) on the Newtonian gravitational field. We briefly recall why this tensor arises and how the EM field in a galaxy can be calculated. The data fields that enter the PDE for the scalar field p oscillate very quickly in space and time, as does the EM field. This prevents integration of that PDE at the relevant galactic scale. Therefore, a homogenization of that PDE has to be operated. We discuss in some detail three possible ways of applying the homogenization theory to that PDE: time, space, or spacetime homogenization. The second and third ways may lead to feasible, albeit heavy calculations.
X-Ray Polarization of BL Lacertae in Outburst

We report the first >99% confidence detection of X-ray polarization in BL Lacertae. During a recent X-ray/γ-ray outburst, a 287 ks observation (2022 November 27–30) was taken using the Imaging X-ray Polarimetry Explorer (IXPE), together with contemporaneous multiwavelength observations from the Neil Gehrels Swift observatory and XMM-Newton in soft X-rays (0.3–10 keV), NuSTAR in hard X-rays (3–70 keV), and optical polarization from the Calar Alto and Perkins Telescope observatories. Our contemporaneous X-ray data suggest that the IXPE energy band is at the crossover between the low- and high-frequency blazar emission humps. The source displays significant variability during the observation, and we measure polarization in three separate time bins. Contemporaneous X-ray spectra allow us to determine the relative contribution from each emission hump. We find >99% confidence X-ray polarization Π2–4keV=21.7−7.9+5.6% and electric vector polarization angle ψ 2–4keV = −28. °7 ± 8. °7 in the time bin with highest estimated synchrotron flux contribution. We discuss possible implications of our observations, including previous IXPE BL Lacertae pointings, tentatively concluding that synchrotron self-Compton emission dominates over hadronic emission processes during the observed epochs.
Social-media based Health Education plus Exercise Programme (SHEEP) to improve muscle function among community-dwelling young-old adults with possible sarcopenia in China: A study protocol for intervention development

Introduction Prevalence of possible sarcopenia is estimated to be significantly higher in community-dwelling older adults than that of confirmed or severe sarcopenia. However, there are currently far fewer non-pharmacological intervention strategies for possible sarcopenia than for sarcopenia in the community. Meanwhile, one type of non-pharmacological intervention in sarcopenic area, health education, is under-researched, and older people's awareness about sarcopenia is extremely low, necessitating an immediate dissemination tool for prevention. Social media may be a potential, scalable, low-cost tool for this. This study protocol outlines how a social media-based multicomponent intervention will be co-designed with stakeholders to address this evidence gap. Methods and analysis Guided by the Medical Research Council's framework, the proposed research covers two phases that employ a co-design approach to develop a theory-based multicomponent intervention to increase sarcopenia prevention in the community. The participants will be recruited from young-old adults (60~69) with possible sarcopenia in the community of Changsha, China. Maximum sample size will be 45 participants in total, with 18~25 participants in the development phase and 15~20 participants in the pre-testing phase. During two rounds of focus groups with older adults, a social-media based intervention strategy will be developed from a theory-based conceptual model and an initial intervention plan formulated by the research group. After this, there will be a three-week pre-testing phase, followed by a semi-structured interview to further modify the theory-based conceptual model and the social-media based intervention strategy. The focus of the data analysis will be on thematic analysis of qualitative data primarily derived from the group interview and the semi-structured interview with key stakeholders. Ethics and dissemination This study has been approved by the University of Manchester Research Ethics Committee (Project ID: 15664), and permissions have already been granted by collaborators in relevant Chinese organisations. We will collaborate with stakeholders to inform our dissemination strategy and co-present our findings (e.g., at community events or through social media). Furthermore, we will disseminate our findings to academics and healthcare professionals via webinars, academic conferences, and peer-reviewed publications.
The universal equivariance properties of exotic aromatic B-series

Exotic aromatic B-series were originally introduced for the calculation of order conditions for the high order numerical integration of ergodic stochastic differential equations in $\mathbb{R}^d$ and on manifolds. We prove in this paper that exotic aromatic B-series satisfy a universal geometric property, namely that they are characterised by locality and orthogonal-equivariance. This characterisation confirms that exotic aromatic B-series are a fundamental geometric object that naturally generalises aromatic B-series and B-series, as they share similar equivariance properties. In addition, we classify with stronger equivariance properties the main subsets of the exotic aromatic B-series, in particular the exotic B-series. Along the analysis, we present a generalised definition of exotic aromatic trees, dual vector fields, and we explore the impact of degeneracies on the classification.
Bring More Attention to Syntactic Symmetry for Automatic Postediting of High-Quality Machine Translations

Automatic postediting (APE) is an automated process to refine a given machine translation (MT). Recent findings present that existing APE systems are not good at handling high-quality MTs even for a language pair with abundant data resources, English–German: the better the given MT is, the harder it is to decide what parts to edit and how to fix these errors.One possible solution to this problem is to instill deeper knowledge about the target language into the model.Thus, we propose a linguistically motivated method of regularization that is expected to enhance APE models’ understanding of the target language: a loss function that encourages symmetric self-attention on the given MT.Our analysis of experimental results demonstrates that the proposed method helps improving the state-of-the-art architecture’s APE quality for high-quality MTs.
On Transmission Zeros of Mass-Dashpot-Spring Systems

For a noncollocated mass-dashpot-spring system with B = C T Γ, a novel approach is proposed to gain a better insight into the fact that none of its transmission zeros lie in the open right-half of the complex plane. In addition, the transmission zeros have physical meanings and will simply be the natural frequencies of a substructure constrained in the equivalently transformed system. Moreover, it is also shown that transmission zeros interlace with poles along the imaginary axis for a mass-spring system with B = C T Γ. They also interlace with poles along the negative real axis for a mass-dashpot system with B = C T Γ. Finally, two examples are used to illustrate the interlacing property.
Analysing Biomedical Knowledge Graphs using Prime Adjacency Matrices

Most phenomena related to biomedical tasks are inherently complex, and in many cases, are expressed as signals on biomedical Knowledge Graphs (KGs). In this work, we introduce the use of a new representation framework, the Prime Adjacency Matrix (PAM) for biomedical KGs, which allows for very efficient network analysis. PAM utilizes prime numbers to enable representing the whole KG with a single adjacency matrix and the fast computation of multiple properties of the network. We illustrate the applicability of the framework in the biomedical domain by working on different biomedical knowledge graphs and by providing two case studies: one on drug-repurposing for COVID-19 and one on important metapath extraction. We show that we achieve better results than the original proposed workflows, using very simple methods that require no training, in considerably less time.
Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization

We consider a non-convex constrained optimization problem, where the objective function is weakly convex and the constraint function is either convex or weakly convex. To solve this problem, we consider the classical switching subgradient method, which is an intuitive and easily implementable first-order method whose oracle complexity was only known for convex problems. This paper provides the first analysis on the oracle complexity of the switching subgradient method for finding a nearly stationary point of non-convex problems. Our results are derived separately for convex and weakly convex constraints. Compared to existing approaches, especially the double-loop methods, the switching gradient method can be applied to non-smooth problems and achieves the same complexity using only a single loop, which saves the effort on tuning the number of inner iterations.
ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning

Noisy partial label learning (noisy PLL) is an important branch of weakly supervised learning. Unlike PLL where the ground-truth label must conceal in the candidate label set, noisy PLL relaxes this constraint and allows the ground-truth label may not be in the candidate label set. To address this challenging problem, most of the existing works attempt to detect noisy samples and estimate the ground-truth label for each noisy sample. However, detection errors are unavoidable. These errors can accumulate during training and continuously affect model optimization. To this end, we propose a novel framework for noisy PLL with theoretical guarantees, called ``Adjusting Label Importance Mechanism (ALIM)''. It aims to reduce the negative impact of detection errors by trading off the initial candidate set and model outputs. ALIM is a plug-in strategy that can be integrated with existing PLL approaches. Experimental results on benchmark datasets demonstrate that our method can achieve state-of-the-art performance on noisy PLL. \textcolor[rgb]{0.93,0.0,0.47}{Our code can be found in Supplementary Material}.
Toward Platform-based Building Design

The electronic design industry has undergone a significant transformation, transitioning from traditional hand-drawn designs to modern automated design processes. While Computer-Aided Design (CAD) tools emerged alongside the electronic industry, the current building design process has little to no automation. There is a need for a unified platform to address the complexity of building design and provide a more systematic approach. Platform-based design (PBD), originally developed in the electronic industry, enables efficient design processes by promoting the reuse of hardware and software systems. It also facilitates design space exploration while optimizing performance. This paper proposes a modular approach that divides the building into various disciplines and introduces a design flow using the PBD framework to streamline the design process. We also present a case study that demonstrates the use of the PBD framework in the Heating, Ventilation, and Air Conditioning (HVAC) systems design.
The Photon Content of the Neutron

In this work, we complete our CT18qed study with the neutron's photon parton distribution function (PDF), which is essential for the nucleus scattering phenomenology. Two methods, CT18lux and CT18qed, based on the LUXqed formalism and the DGLAP evolution, respectively, to determine the neutron's photon PDF have been presented. Various low-$Q^2$ non-perturbative variations have been carefully examined, which are treated as additional uncertainties on top of those induced by quark and gluon PDFs. The impacts of the momentum sum rule as well as isospin symmetry violation have been explored, and turn out to be negligible. A detailed comparison with other neutron's photon PDF sets has been performed, which shows a great improvement in the precision and a reasonable uncertainty estimation in our results. Finally, two phenomenological implications are demonstrated with photon-initiated processes: neutrino-nucleus $W$-boson production, which is important for the near-future TeV--PeV neutrino observations, and the axion-like particle production at a high-energy muon beam-dump experiment.
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs

The prevalence of large-scale graphs poses great challenges in time and storage for training and deploying graph neural networks (GNNs). Several recent works have explored solutions for pruning the large original graph into a small and highly-informative one, such that training and inference on the pruned and large graphs have comparable performance. Although empirically effective, current researches focus on static or non-temporal graphs, which are not directly applicable to dynamic scenarios. In addition, they require labels as ground truth to learn the informative structure, limiting their applicability to new problem domains where labels are hard to obtain. To solve the dilemma, we propose and study the problem of unsupervised graph pruning on dynamic graphs. We approach the problem by our proposed STEP, a self-supervised temporal pruning framework that learns to remove potentially redundant edges from input dynamic graphs. From a technical and industrial viewpoint, our method overcomes the trade-offs between the performance and the time&memory overheads. Our results on three real-world datasets demonstrate the advantages on improving the efficacy, robustness, and efficiency of GNNs on dynamic node classification tasks. Most notably, STEP is able to prune more than 50% of edges on a million-scale industrial graph Alipay (7M nodes, 21M edges) while approximating up to 98% of the original performance. Code is available at https://github.com/EdisonLeeeee/STEP.
Using Symbolic Computation to Analyze Zero-Hopf Bifurcations of Polynomial Differential Systems

This paper is devoted to the study of infinitesimal limit cycles that can bifurcate from zero-Hopf equilibria of differential systems based on the averaging method. We develop an efficient symbolic program using Maple for computing the averaged functions of any order for continuous differential systems in arbitrary dimension. The program allows us to systematically analyze zero-Hopf bifurcations of polynomial differential systems using symbolic computation methods. We show that for the first-order averaging, ℓ ∈ {0, 1, …, 2n − 3} limit cycles can bifurcate from the zero-Hopf equilibrium for the general class of perturbed differential systems and up to the second-order averaging, the maximum number of limit cycles can be determined by computing the mixed volume of a polynomial system obtained from the averaged functions. A number of examples are presented to demonstrate the effectiveness of the proposed algorithmic approach.
Detecting the driver nodes of temporal networks

Detecting the driver nodes of complex networks has garnered significant attention recently to control complex systems to desired behaviors, where nodes represent system components and edges encode their interactions. Driver nodes, which are directly controlled by external inputs, play a crucial role in controlling all network nodes. While many approaches have been proposed to identify driver nodes of static networks, we still lack an effective algorithm to control ubiquitous temporal networks, where network structures evolve over time. Here we propose an effective online time-accelerated heuristic algorithm (OTaHa) to detect driver nodes of temporal networks. Together with theoretical analysis and numerical simulations on synthetic and empirical temporal networks, we show that OTaHa offers multiple sets of driver nodes, and noticeably outperforms existing methods in terms of accuracy and execution time. We further report that most edges are redundant in controlling temporal networks although the complete instantaneous signal-carrying edges cannot be guaranteed. Moreover, removing edges with high edge betweenness (the number of all-pairs shortest paths passing through the edge) significantly impedes the overall controllability. Our work provides an effective algorithm and paves the way for subsequent explorations on achieving the ultimate control of temporal networks.
Automorphisms of K3 surfaces, cyclotomic polynomials and orthogonal groups

Let X be a complex projective K3 surface, and let T(X) be its transcendental lattice; the characteristic polynomials of the isometries of T(X) induced by automorphisms of X are powers of cyclotomic polynomials. Which powers of cyclotomic polynomials occur ? The aim of this note is to answer this question, as well as related ones, and give an alternative approach to some results of Kondo, Machida, Oguiso, Vorontsov, Xiao and Zhang; this leads to questions and results concerning orthogonal groups of lattices.