Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Graphene Oxide on Properties and Structure of Thin-Film Composite Forward Osmosis Membranes

Forward osmosis (FO) membranes have the advantages of low energy consumption, high water recovery rate, and low membrane pollution trend, and they have been widely studied in many fields. However, the internal concentration polarization (ICP) caused by the accumulation of solutes in the porous support layer will reduce permeation efficiency, which is currently unavoidable. In this paper, we doped Graphene oxide (GO) nanoparticles (50~150 nm) to a polyamide (PA) active layer and/or polysulfone (PSF) support layer, investigating the influence of GO on the morphology and properties of thin-film composite forward osmosis (TFC-FO) membranes. The results show that under the optimal doping amount, doping GO to the PA active layer and PSF support layer, respectively, is conducive to the formation of dense and uniform nano-scale water channels perpendicular to the membrane surface possessing a high salt rejection rate and low reverse solute flux without sacrificing high water flux. Moreover, the water channels formed by doping GO to the active layer possess preferable properties, which significantly improves the salt rejection and water permeability of the membrane, with a salt rejection rate higher than 99% and a water flux of 54.85 L·m−2·h−1 while the pure PSF-PA membrane water flux is 12.94 L·m−2·h−1. GO-doping modification is promising for improving the performance and structure of TFC-FO membranes.
Differentially Private Set Intersection for Asymmetrical ID Alignment

Private Set Intersection (PSI) is typically used to achieve ID alignment with protection of IDs in the preparation phase of Vertical Federated Learning (VFL). However, existing PSI approaches are limited to protecting IDs that are outside the intersection of participants, and most ignore the sensitivity of intersection for a weak party in an asymmetrical ID alignment. Since the set size of the strong party is much greater than the weak party’s in an asymmetrical federation, and the intersection usually accounts for a substantial part of the weak party set, the weak party’s sensitive sample IDs would be severely compromised through sharing the intersection. To address this issue, we propose Differentially private PSI Cardinality and PSI (DPSI-CA, DPSI) protocols, which protect the intersection cardinality and sensitive IDs inside the intersection for the weak party, respectively. First, DPSI-CA encodes IDs in binary notation, and combines them with the GM encryption, to perform the ID-matchmaking by executing bitwise plaintext XOR. Then, the encrypted matching results are independently perturbed using randomized responses to produce differentially private outputs for PSI-CA, and its unbiased estimate is added to remove the deviation brought by the randomization. Furthermore, DPSI fuses Pseudo-Random Function (PRF)-based zero sharing, garbled Bloom filter, and Oblivious PRF (OPRF)-based shares reconstruction, to successfully reconstruct the shares corresponding to sampled IDs in the intersection. Meanwhile, a randomized response is used to sample the inputs and perturb the outputs of the OPRF-based shares reconstruction, producing a randomly sampled intersection for the weak party and differentially private intersection for the strong party. Finally, the privacy analysis shows that our protocols provide differential privacy for the weak party’s sensitive sample IDs, and extensive experiment results illustrate the feasibility of the asymmetrical ID alignment involving millions of IDs.
Lyapunov Optimization Based Mobile Edge Computing for Internet of Vehicles Systems

Mobile-Edge Computing (MEC) is an emerging paradigm in the Internet of Vehicles (IoV) to meet the ever-increasing computation demands of smart applications. To provide satisfactory computation performance, it is of significant importance to conduct computation offloading in IoV. In this paper, we investigate a multi-vehicle IoV system assisted by MECs with limited computation resources, where vehicles with complex applications can offload their subtasks to MEC servers. Applications are modeled as interdependent subtasks with general random task graphs, different from existing works with independent ones. To maximize the average logarithmic data processing rate (LDPR), the computation offloading problem is formulated as a time-average optimization with long-term constraints, which results from variable vehicle number, various applications and time-varying communication channels. To reduce the cooperation overhead, we propose a multi-agent Proximal Policy Optimization algorithm (Ly-MAPPO) which requires local observation only to solve the subproblems achieved by Lyapunov optimization technique in real time. In addition, to improve the performance of the Ly-MAPPO algorithm, Graph Convolutional Neural Network (GCN) is introduced to extract inter-dependencies between subtasks. Extensive simulations show that the GCN embedded Ly-MAPPO outperforms other baseline algorithms, e.g., greedy algorithm and gene algorithm, etc., for different traffic loads and computation resources in MEC servers.
Linear Algebra with Maple

Preface 1. Systems of Equations Solutions of systems of equations 2. Augmented Matrices and Elementary Row Operations Augmented matrix Elementary row operation Echelon form Reduced echelon form Gauss-Jordan elimination Transpose Rank 3. The Algebra of Matrices Matrix addition Scalar multiplication Matrix multiplication 4. Inverses of Matrices Matrix inversion 5. Determinants, Adjoints, and Cramer's Rule Determinant Adjoint Cramer's rule 6. Application: Matrix Algebra and Modular Arithmetic Modular arithmetic Matrix operations Hill codes 7. Vector Products, Lines, and Planes Dot product Cross product Projection Unit vector Vectors in R? n Orthogonal vectors 8. Vector Spaces and Subspaces Vector space Subspace Spaces of functions and matrices Linear combination Spanning Set Null Space Rank of a matrix 9. Independence, Basis and Dimension Linearly independent set Basis Dimension Coordinate vector 10. Row Space, Column Space, and Null Space Row space Column space Null space Rank Nullity 11. Inner Product Spaces General inner products 12. Orthonormal Bases and the Gram-Schmidt Process Orthonormal basis Gram-Schmidt process 13. Change of Basis and Orthogonal Matrices Transition (or change of basis) matrix Orthogonal matrices 14. Eigenvalues and Eigenvectors Characteristic polynomial Eigenvalue Eigenvector Eigenspace 15. Diagonalization and Orthogonal Diagonalization Similarity Diagonalization Symmetric matrix Orthogonal diagonalization 16. Matrices and Linear Transformations from R? m to R? n Linear transformation Matrix of a linear transformation Kernel of a linear transformation Image of a linear transformation Inverse of a linear transformation Composition of linear transformations 17. Matrices of General Linear Transformations Similarity Matrix of a linear transformation Similar matrices 18. Applications and Numerical Methods Systems of differential equations Gauss-Seidel method Generalized inverse and curve fitting Rotation of axes LU and QR factorizations Appendix A. Maple V Mini-Reference Appendix B. User-Defined Functions
Parental Psychological Control and Children’s Prosocial Behavior: The Mediating Role of Social Anxiety and the Moderating Role of Socioeconomic Status

Complementing internalizing and externalizing developmental outcomes of parental psychological control, in this study, we shift the focus to children’s prosocial behaviors. Drawing on self-determination theory and problem-behavior theory, this study addresses the relationship between parental psychological control, social anxiety, socioeconomic status (SES), and children’s prosocial behavior. The parental psychological control scale, social anxiety scale for children, and prosocial behavior were applied in the study. Participants were 1202 elementary school-age children in China. The present study showed that parental psychological control was negatively associated with prosocial behavior and social anxiety played a partial mediating role between parental psychological control and prosocial behavior. Meanwhile, SES moderated the relationship between parental psychological control and prosocial behavior. The effect of parental psychological control on prosocial behavior was more significant among students with low levels of SES than the higher ones. The findings showed that parenting plays an essential role in the development of children’s prosociality.
CODE: Blockchain-based Travel Rule Compliance System

Financial Action Task Force (FATF) guidelines specifies a ‘travel rule’ to prevent illegal usages of virtual assets such as money laundering. Following the travel rule, Virtual Asset Service Providers (VASPs) should exchange personal identity information of originator and beneficiary when transferring virtual assets. In this paper, we propose CODE, a novel decentralized blockchain-based travel rule compliance system. Since blockchain does not need any third party, it can eliminate the possibility of massive data leakage due to centralization. It also ensures secure management of travel rule data. We developed a system that uses Corda as a blockchain platform. According to the characteristics of Corda, data are only shared between related parties. Our system also provides an address-search method to verify the beneficiary's identity in real-time. An originator requests virtual asset transfer using only the beneficiary's virtual asset address. By joining the Corda network and installing the proposed system developed in the form of a CorDapp, any VASP can easily use this system to exchange travel rule data.
On stylized facts of cryptocurrencies returns and their relationship with other assets, with a focus on the impact of COVID-19

ABSTRACT This study provides an empirical analysis on the main univariate and multivariate stylized facts iin return series of the two of the largest cryptocurrencies, namely Ethereum and Bitcoin. A Markov-Switching Vector AutoRegression model is considered to further explore the dynamic relationships between cryptocurrencies and other financial assets. We estimate the presence of volatility clustering, a rapid decay of the autocorrelation function, an excess of kurtosis and multivariate little cross-correlation across the series, except for contemporaneous returns. The analysis covers the pandemic period and sheds lights on the behaviour of cryptocurrencies under unexpected extreme events.
YAP Activates STAT3 Signalling to Promote Colonic Epithelial Cell Proliferation in DSS-Induced Colitis and Colitis Associated Cancer

Background and Aims Yes-associated protein (YAP) is a key transcriptional coactivator of cell proliferation and differentiation. In this study, we sought to identify the roles of YAP in colonic epithelial regeneration and tumourigenesis. Methods Murine DSS-induced colitis and YAP overexpression models were constructed via lentiviral intraperitoneal injection. Stable YAP-overexpressing cells, protein immunoprecipitation, and ChIP were used to deeply explore the molecular mechanism. Results We found that the expression of YAP was dramatically diminished in the colonic crypts during the acute colitis phase, while YAP was strikingly enhanced to initiate tissue repair after DSS withdrawal. Overexpressing YAP in mice drastically accelerated epithelial regeneration, presenting with more intact structural integrity and reduced inflammatory cell infiltration in the mucosa. Further mechanistic studies showed that the expression of YAP in the nucleus was significantly increased by 2 h post-DSS removal, accompanied by upregulated protein levels of activated STAT3. Overexpression of YAP (YAPWT) elevated the expression of activated STAT3 and its transcriptional targets and strengthened the proliferation and “wound healing” ability of colonic cells. However, these effects were reversed when STAT3 was silenced in YAPWT cells. Moreover, YAP could directly interact with STAT3 in the nucleus, and c-Myc and CyclinD1 were the transcriptional targets. Finally, during colitis-associated cancer (CAC), YAPWT promoted the progression of CAC, while the phosphomimetic YAP downregulated the expression of STAT3 and inhibited the development and progression of CAC. Conclusion YAP activates STAT3 signalling to facilitate mucosal regeneration after DSS-induced colitis. However, excessive YAP activation in the colonic epithelium promotes CAC development.
Decentralized Authorization using Hyperledger Fabric

Access control in multi-user web service applications is an important problem. Access control methods ensure that only authorised users have access to data and resources by deciding whether to give access to a resource or not by verifying credentials of the entity requesting access. In several real-world situations, these credentials may not be available within a single authority and it may require verification through multiple authorities. In this paper, we propose a decentralized framework using Hyperledger Fabric and Attribute Based Access Control (ABAC) to verify access requests through multiple authorities in a decentralized manner. Hyperledger Fabric enables transparent authorization and immutability of credentials and ensures a secure operation between authorities. Each authority can safely store the credentials in their own Hyperleger Fabric network and our framework performs access requests by automating the end-to-end process of authorization across multiple authorities. The framework can be extended to perform access requests across any number of authorities and is applicable to any attribute based access control use case. We implemented a prototype of the framework using Hyperledger Fabric and the results validate the performance of the proposed approach.
Exploring Ethical Requirements Elicitation for Applications in the Context of AI

Ethical concerns arises from the proliferation of Artificial Intelligence (AI) based systems in use. AI ethics has been approached mainly in guidelines and principles, not providing enough practical guidance for developers. Hence, we aim to present RE4AI Ethical Guide and its evaluation. We used the Design Science Research methodology to understand the problem, present the guide and evaluate it through a focus group. The Guide is composed of 26 cards across 11 principles. We evaluated it with 5 AI professionals and our preliminary results reveal that it has the potential to facilitate the elicitation of ethical requirements. Thus, we contribute to bridge the gap between principles and practice by assisting developers to elicit ethical requirements and operationalise ethics in AI.
Astrophysical Jets and Beams

1. Introduction 2. Detection and measurement 3. The dynamical toolbox 4. Observations of extragalactic jets 5. Jets in galactic nuclei 6. Jets from young stars and protostars 7. Jets associated with evolved stars 8. Jets within the solar system 9. Jet launching 10. Jet propagation 11. New questions Index.
Taking Care of Elderly Parents or Children: How Are They Related to the Decision to Hire Foreign Domestic Helpers?

Hiring foreign domestic helpers has been seen as a policy to release females from household responsibilities so they can join the labor market. Surprisingly, few studies explore the relative importance of needs to taking care children and elderly. Employing the 2016 Hong Kong census, we found that the number of elderly persons and the number of young children in the household are positively associated with the decision to hire foreign domestic helpers. Our analysis also demonstrates that members are more likely to choose to work and outsource the care of young children to foreign domestic helpers. However, the findings show that households are more likely to take care of elderly without helpers even when household members are employed. Household members may co-ordinate and allocate time to take care of their elderly instead of outsourcing the care to a foreign domestic helper.
Functional Study of Lipoxygenase-Mediated Resistance against Fusarium verticillioides and Aspergillus flavus Infection in Maize

Mycotoxin contamination of maize kernels by fungal pathogens like Fusarium verticillioides and Aspergillus flavus is a chronic global challenge impacting food and feed security, health, and trade. Maize lipoxygenase genes (ZmLOXs) synthetize oxylipins that play defense roles and govern host-fungal interactions. The current study investigated the involvement of ZmLOXs in maize resistance against these two fungi. A considerable intraspecific genetic and transcript variability of the ZmLOX family was highlighted by in silico analysis comparing publicly available maize pan-genomes and pan-transcriptomes, respectively. Then, phenotyping and expression analysis of ZmLOX genes along with key genes involved in oxylipin biosynthesis were carried out in a maize mutant carrying a Mu transposon insertion in the ZmLOX4 gene (named UFMulox4) together with Tzi18, Mo17, and W22 inbred lines at 3- and 7-days post-inoculation with F. verticillioides and A. flavus. Tzi18 showed the highest resistance to the pathogens coupled with the lowest mycotoxin accumulation, while UFMulox4 was highly susceptible to both pathogens with the most elevated mycotoxin content. F. verticillioides inoculation determined a stronger induction of ZmLOXs and maize allene oxide synthase genes as compared to A. flavus. Additionally, oxylipin analysis revealed prevalent linoleic (18:2) peroxidation by 9-LOXs, the accumulation of 10-oxo-11-phytoenoic acid (10-OPEA), and triglyceride peroxidation only in F. verticillioides inoculated kernels of resistant genotypes.
Parametric study of a vertical axis tidal turbine blade using the CFD method to achieve high turbine performance

The aim of this paper is to identify numerically the influence of some vertical axis tidal turbine blade design parameters to the turbine performance. The parameters are inlet fluid velocity, initial angle of attack, number of response motions, blade material stiffness constant. The blade is initially (before variations) exposed in a set of environmental condition which is executed by high Reynolds number (3,07x10-6) flow. The turbine blade performance is evaluated from the time history lift, drag, and moment coefficients. A 2D CFD model of a single vertical axis tidal turbine blade is developed using OpenFOAM. The blade utilizes NACA 0012 profile. The performance of parametric models is compared to the performance of initial condition model. The results show that velocity and angle of attack variations significantly affect to the blade performance. It is also found that the number of response and stiffness constant variations generate unsteadiness in the turbine blade coefficients. This indicates that tidal velocity and blade orientation is more favourable to improve turbine’s performance.
S-wave sector of type IIB supergravity on S^1 \times T^4

We consider the type IIB supergravity in ten dimensions compactified on S^1 \times T^4, with intersecting one and five D-branes in the compact dimensions. By imposing the spherical symmetry in the resulting five dimensional theory, we further reduce the s-wave sector of the theory to a two dimensional dilaton gravity. Via this construction, the techniques developed for the general two dimensional dilaton gravities are applicable in this context. Specifically, we obtain the bosonic sector general static solutions. In addition to the well-known asymptotically flat black hole solutions, they include solutions with naked singularities and non-asymptotically flat black holes.
Research on Detection Method of Truck Face Based on Deformable Parts Model

The video monitoring system is susceptible to illumination and other factors. To effectively solve the problem of high-precision detection of truck face in complex highway scenes, a truck face detection method based on deformable parts model is proposed and compared with four other truck face detection methods based on machine learning in this paper. Based on the vehicle image database of Southeast University, comparative experiments are carried out and the theoretical analysis and experimental results show that the performance of the truck face detection method based on deformable parts model is better than the other four truck face detection methods based on machine learning, and its verification accuracy is better than 98%.
Development of the quantum state evolution model based on the "amplitude quanta" method

Nowadays the task of molecular modeling plays the important role in many branches of science and engineering. But the existing models do not take quantum effects into account because of known calculating issues. The main difficulty in modeling of the evolution of multi particle quantum states by solving the Schroedinger equation consists iii exponential growth of required time and memory with the corresponding increase of entangled particles. The approach to this problem considered in works [3 4] consists in applying Feynman path integrals instead of solving Schroedinger equation. In terms of the "amplitude quanta" method based on this approach the wave function of a particle is calculated as a sum of the large amount of a.q. that probably will allow the linear growth of required memory with the corresponding increase of entangled particles. This approach also allows to the easy transition from the classical description of a particle to the quantum and back. The given work is devoted to the development of the quantum state evolution model based on the a. q. method in one and two-dimensional cases.
Weakly-Supervised Crack Segmentation via Scribble Annotations

For precise pixel-level crack extraction, a large amount of densely labeled data is usually required to train a deep neural network, which is time-consuming and laborious. Scribble annotations are easier to label crack images, especially for tiny cracks. Due to the topology complexity, irregular edges, and sparse annotations, crack segmentation with scribbles is a challenging task. In this paper, we first relabel a crack dataset with scribbles. Inspired by the long-range dependencies of Vision Transformer, we propose a novel feature encoder with hybrid convolutional neural network and Vision Transformer to extract low-level features, high-level features and global context features. Moreover, a skip feature aggregation module is adopted to fuse the three types of features. Additionally, in order to alleviate the poor boundary localization caused by sparse annotations, we adopt the deep supervision strategy with two auxiliary losses to train the network. Extensive experiments on the crack dataset demonstrate that our method outperforms existing weakly-supervised methods and is on par with fully-supervised methods.
Craniosynostosis: A Pediatric Neurologist’s Perspective

Craniosynostosis is premature fusion of sutures of the cranium, resulting in an abnormal skull shape and restriction of brain growth. It may affect either a single suture or multiple sutures. In most cases, craniosynostosis is secondary to an underlying abnormality of the growing brain; however, syndromic craniosynostosis is not uncommon. It might lead to several complications such as raised intracranial pressure, neurological deficits, and neurodevelopmental disabilities. Pediatric neurologists do play a significant role in early identification and treatment, and thereby ensure a better clinical and neurodevelopmental outcome in such children.