RWNeRF:Robust Watermarking Scheme for Neural Radiance Fields Based on Invertible Neural Networks

As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network watermarking.Leveraging 2D image watermarking technology for 3D scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3D scenes.However,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s robustness.This module restores distorted images through neural network processing before watermark extraction.Additionally,embedding watermarks in each training image enables watermark information extraction from multiple viewpoints.Our proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,respectively.These results demonstrate the efficacy of our scheme in enhancing copyright protection.

MarkINeRV: A Robust Watermarking Scheme for Neural Representation for Videos Based on Invertible Neural Networks

Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue comprehensively.In response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of watermarks.It is just that the information flow is in the opposite direction.Additionally,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse process.This paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video datasets.The results demonstrate its efficacy in extracting watermarking information for copyright protection of NeRV.MarkINeRV represents a pioneering investigation into copyright issues surrounding NeRV.

Inverse Molecule Design with Invertible Neural Networks as Generative Models

Using neural networks for supervised learning means learning a function that maps input x to output y. However, in many applications, the inverse learning is also wanted, i.e., inferring y from x, which requires invertibility of the learning. Since the dimension of input is usually much higher than that of the output, there is information loss in the forward learning from input to output. Thus, creating invertible neural networks is a difficult task. However, recent development of invertible learning techniques such as normalizing flows has made invertible neural networks a reality. In this work, we applied flow-based invertible neural networks as generative models to inverse molecule design. In this context, the forward learning is to predict chemical properties given a molecule, and the inverse learning is to infer the molecules given the chemical properties. Trained on 100 and 1000 molecules, respectively, from a benchmark dataset QM9, our model identified novel molecules that had chemical property values well exceeding the limits of the training molecules as well as the limits of the whole QM9 of 133,885 molecules, moreover our generative model could easily sample many molecules (x values) from any one chemical property value (y value). Compared with the previous method in the literature that could only optimize one molecule for one chemical property value at a time, our model could be trained once and then be sampled any multiple times and for any chemical property values without the need of retraining. This advantage comes from treating inverse molecule design as an inverse regression problem. In summary, our main contributions were two: 1) our model could generalize well from the training data and was very data efficient, 2) our model could learn bidirectional correspondence between molecules and their chemical properties, thereby offering the ability to sample any number of molecules from any y values. In conclusion, our findings revealed the efficiency and effectiveness of using invertible neural networks as generative models in inverse molecule design.

A Note on the Connectedness of the Invertible Group of a Nest Algebra

The connectedness of the invertibles question for arbitrary nest has been reduced to the case of the lower triangular operators with respect to a fixed orthonormal basis en for n 1. For each f ∈ H∞, let Tf be the Toeplitz operator. In this paper we prove that Tf can be connected to the identity through a path in the invertible group of the lower triangular operators if f satisfies certain conditions.

THE STRUCTURE OF INVERTIBLE SUBSTITUTIONS ON A THREE-LETTER ALPHABET

We study the structure of invertible substitutions on three-letter alphabet. We show that there exists a finite set S of invertible substitutions such that any invertible substitution can be written as I wσ 1σ 2…σ k,where I w is the inner automorphism associated with w, and σ j∈ S for 1≤j≤k. As a consequence,M is the matrix of an invertible substitution if and only if it is a finite product of non-negative elementary matrices.

Alternative Infinitesimal Generator of Invertible Evolution Families

A logarithm representation of evolution operators is defined. Generators of invertible evolution families are characterized by the logarithm representation. In this article, using the logarithm representation, a concept of evolution operators without satisfying the semigroup property is introduced. In conclusion the existence of alternative infinitesimal generator is clarified.

A Determinant Criterion of Invertible Elements in Group Algebras

An embedding from a group algebra to a matrix algebra is given in this paper. By using it, a criterion for an invertible element in a group algebra is proven.

Decomposing a Kind of Weakly Invertible Finite Automata with Delay 2

Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly invertible finite automaton M with delay 2 satisfying the properties mentioned in this paper, two weakly invertible finite automata with delay 1 are constructed such that M is equivalent to a sub-finite-automaton of the composition of those two. So a method to decompose this a kind of weakly invertible finite automata with delay 2 is presented.

Some remarks on invertible substitutions on three letter alphabet

By introducing the notion of 'prime substitution' it is shown that the set of invertible substitutions over an alphabet of more than three letters is not finitely generated. Some examples are given.

Some Conditions for Matrices over an Incline To Be Invertible and General Linear Group on an Incline

Inclines are the additively idempotent semirings in which products are less than or equal to either factor. In this paper, some necessary and sufficient conditions for a matrix over L to be invertible are given, where L is an incline with 0 and 1. Also it is proved that L is an integral incline if and only if GLn（L） = PLn （L） for any n （n 〉 2）, in which GLn（L） is the group of all n × n invertible matrices over L and PLn（L） is the group of all n × n permutation matrices over L. These results should be regarded as the generalizations and developments of the previous results on the invertible matrices over a distributive lattice.

Analysis of Progressively Type-Ⅱ Inverted Generalized Gamma Censored Data and Its Engineering Application

A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is considered.In many real-world practical situations,when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing,censoring strategies are frequently used.From this point of view,in the presence of censored data compiled from the most well-known progressively Type-Ⅱ censoring technique,this study examines different parameters of the IGG distribution.From a classical point of view,the likelihood and product of spacing estimation methods are considered.Observed Fisher information and the deltamethod are used to obtain the approximate confidence intervals for any unknown parametric function of the suggestedmodel.In the Bayesian paradigm,the same traditional inferential approaches are used to estimate all unknown subjects.Markov-Chain with Monte-Carlo steps are considered to approximate all Bayes’findings.Extensive numerical comparisons are presented to examine the performance of the proposed methodologies using various criteria of accuracy.Further,using several optimality criteria,the optimumprogressive censoring design is suggested.To highlight how the proposed estimators can be used in practice and to verify the flexibility of the proposed model,we analyze the failure times of twenty mechanical components of a diesel engine.

Comparative analyses of mitogenomes in the social bees with insights into evolution of long inverted repeats in the Meliponini

The insect mitogenome is typically a compact circular molecule with highly conserved gene contents.Nonetheless,mitogenome structural variations have been reported in specific taxa,and gene rearrangements,usually the tRNAs,occur in different lineages.Because synapomorphies of mitogenome organizations can provide information for phylogenetic inferences,comparative analyses of mitogenomes have been given increasing attention.However,most studies use a very few species to represent the whole genus,tribe,family,or even order,overlooking potential variations at lower taxonomic levels,which might lead to some incorrect inferences.To provide new insights into mitogenome organizations and their implications for phylogenetic inference,this study conducted comparative analyses for mitogenomes of three social bee tribes(Meliponini,Bombini,and Apini)based on the phylogenetic framework with denser taxonomic sampling at the species and population levels.Comparative analyses revealed that mitogenomes of Apini and Bombini are the typical type,while those of Meliponini show diverse variations in mitogenome sizes and organizations.Large inverted repeats(IRs)cause significant gene rearrangements of protein coding genes(PCGs)and rRNAs in Indo-Malay/Australian stingless bee species.Molecular evolution analyses showed that the lineage with IRs have lower dN/dS ratios for PCGs than lineages without IRs,indicating potential effects of IRs on the evolution of mitochondrial genes.The finding of IRs and different patterns of gene rearrangements suggested that Meliponini is a hotspot in mitogenome evolution.Unlike conserved PCGs and rRNAs whose rearrangements were found only in the mentioned lineages within Meliponini,tRNA rearrangements are common across all three tribes of social bees,and are significant even at the species level,indicating that comprehensive sampling is needed to fully understand the patterns of tRNA rearrangements,and their implications for phylogenetic inference.

Polymer Fiber Rigid Network with High Glass Transition Temperature Reinforces Stability of Organic Photovoltaics

Organic photovoltaics(OPVs)need to overcome limitations such as insufficient thermal stability to be commercialized.The reported approaches to improve stability either rely on the development of new materials or on tailoring the donor/acceptor morphology,however,exhibiting limited applicability.Therefore,it is timely to develop an easy method to enhance thermal stability without having to develop new donor/acceptor materials or donor–acceptor compatibilizers,or by introducing another third component.Herein,a unique approach is presented,based on constructing a polymer fiber rigid network with a high glass transition temperature(T_(g))to impede the movement of acceptor and donor molecules,to immobilize the active layer morphology,and thereby to improve thermal stability.A high-T_(g) one-dimensional aramid nanofiber(ANF)is utilized for network construction.Inverted OPVs with ANF network yield superior thermal stability compared to the ANF-free counterpart.The ANF network-incorporated active layer demonstrates significantly more stable morphology than the ANF-free counterpart,thereby leaving fundamental processes such as charge separation,transport,and collection,determining the device efficiency,largely unaltered.This strategy is also successfully applied to other photovoltaic systems.The strategy of incorporating a polymer fiber rigid network with high T_(g) offers a distinct perspective addressing the challenge of thermal instability with simplicity and universality.

Control of GaN inverted pyramids growth on c-plane patterned sapphire substrates

Growth of gallium nitride(GaN)inverted pyramids on c-plane sapphire substrates is benefit for fabricating novel devices as it forms the semipolar facets.In this work,GaN inverted pyramids are directly grown on c-plane patterned sapphire substrates(PSS)by metal organic vapor phase epitaxy(MOVPE).The influences of growth conditions on the surface morphol-ogy are experimentally studied and explained by Wulff constructions.The competition of growth rate among{0001},{1011},and{1122}facets results in the various surface morphologies of GaN.A higher growth temperature of 985 ℃ and a lowerⅤ/Ⅲratio of 25 can expand the area of{}facets in GaN inverted pyramids.On the other hand,GaN inverted pyramids with almost pure{}facets are obtained by using a lower growth temperature of 930℃,a higherⅤ/Ⅲratio of 100,and PSS with pattern arrangement perpendicular to the substrate primary flat.

Role of self-assembled molecules’anchoring groups for surface defect passivation and dipole modulation in inverted perovskite solar cells

Inverted perovskite solar cells have gained prominence in industrial advancement due to their easy fabrication,low hysteresis effects,and high stability.Despite these advantages,their efficiency is currently limited by excessive defects and poor carrier transport at the perovskite-electrode interface,particularly at the buried interface between the perovskite and transparent conductive oxide(TCO).Recent efforts in the perovskite community have focused on designing novel self-assembled molecules(SAMs)to improve the quality of the buried interface.However,a notable gap remains in understanding the regulation of atomic-scale interfacial properties of SAMs between the perovskite and TCO interfaces.This understanding is crucial,particularly in terms of identifying chemically active anchoring groups.In this study,we used the star SAM([2-(9H-carbazol-9-yl)ethyl]phosphonic acid)as the base structure to investigate the defect passivation effects of eight common anchoring groups at the perovskite-TCO interface.Our findings indicate that the phosphonic and boric acid groups exhibit notable advantages.These groups fulfill three key criteria:they provide the greatest potential for defect passivation,exhibit stable adsorption with defects,and exert significant regulatory effects on interface dipoles.Ionized anchoring groups exhibit enhanced passivation capabilities for defect energy levels due to their superior Lewis base properties,which effectively neutralize local charges near defects.Among various defect types,iodine vacancies are the easiest to passivate,whereas iodine-substituted lead defects are the most challenging to passivate.Our study provides comprehensive theoretical insights and inspiration for the design of anchoring groups in SAMs,contributing to the ongoing development of more efficient inverted perovskite solar cells.

Efficient and Stable Inverted Perovskite Solar Modules Enabled by Solid-Liquid Two-Step Film Formation

A considerable efficiency gap exists between large-area perovskite solar modules and small-area perovskite solar cells.The control of forming uniform and large-area film and perovskite crystallization is still the main obstacle restricting the efficiency of PSMs.In this work,we adopted a solid-liquid two-step film formation technique,which involved the evaporation of a lead iodide film and blade coating of an organic ammonium halide solution to prepare perovskite films.This method possesses the advantages of integrating vapor deposition and solution methods,which could apply to substrates with different roughness and avoid using toxic solvents to achieve a more uniform,large-area perovskite film.Furthermore,modification of the NiO_(x)/perovskite buried interface and introduction of Urea additives were utilized to reduce interface recombination and regulate perovskite crystallization.As a result,a large-area perovskite film possessing larger grains,fewer pinholes,and reduced defects could be achieved.The inverted PSM with an active area of 61.56 cm^(2)(10×10 cm^(2)substrate)achieved a champion power conversion efficiency of 20.56%and significantly improved stability.This method suggests an innovative approach to resolving the uniformity issue associated with large-area film fabrication.

Non-destructive buffer enabling near-infrared-transparent inverted inorganic perovskite solar cells toward 1400 h light-soaking stable perovskite/Cu(In,Ga)Se_(2) tandem solar cells

Near-infrared(NIR)transparent inverted all-inorganic perovskite solar cells(PSCs)are excellent top cell candidates in tandem applications.An essential challenge is the replacement of metal contacts with transparent conductive oxide(TCO)electrodes,which requires the introduction of a buffer layer to prevent sputtering damage.In this study,we show that the conventional buffers(i.e.,small organic molecules and atomic layer deposited metal oxides)used for organic-inorganic hybrid perovskites are not applicable to all-inorganic perovskites,due to non-uniform coverage of the vulnerable layers underneath,deterioration upon ion bombardment and moisture induced perovskite phase transition,A thin film of metal oxide nanoparticles by the spin-coating method serves as a non-destructive buffer layer for inorganic PSCs.All-inorganic inverted near-infrared-transparent PSCs deliver a PCE of 17.46%and an average transmittance of 73.7%between 780 and 1200 nm.In combination with an 18.56%Cu(In,Ga)Se_(2) bottom cell,we further demonstrate the first all-inorganic perovskite/CIGS 4-T tandem solar cell with a PCE of 24.75%,which exhibits excellent illumination stability by maintaining 86.7%of its initial efficiency after 1400 h.The non-destructive buffer lays the foundation for efficient and stable NIR-transparent inverted inorganic perovskite solar cells and perovskite-based tandems.

A novel cascaded H-bridge photovoltaic inverter with flexible arc suppression function

This paper presents a novel approach that simultaneously enables photovoltaic(PV)inversion and flexible arc suppression during single-phase grounding faults.Inverters compensate for ground currents through an arc-elimination function,while outputting a PV direct current(DC)power supply.This method effectively reduces the residual grounding current.To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models,an adaptive fuzzy neural network imitating a sliding mode controller was designed.An online adaptive adjustment law for network parameters was developed,based on the Lyapunov stability theorem,to improve the robustness of the inverter to fault and connection locations.Furthermore,a new arc-suppression control exit strategy is proposed to allow a zerosequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time.Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults.Compared to other methods,the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations.

Significance of including lid thickness and particle shape factor in numerical modeling for prediction of particle trap efficiency of invert trap

Sediment accumulation on the bed of open sewers and drains reduces hydraulic efficiency and can cause localized flooding.Slotted invert traps installed underneath the bed of open sewers and drains can eliminate sediment build-up by catching sediment load.Previous three-dimensional(3D)computational studies have examined the particle trapping performance of invert traps of different shapes and depths under varied sediment and flow conditions,considering particles as spheres.For two-dimensional and 3D numerical modeling,researchers assumed the lid geometry to be a thin line and a plane,respectively.In this 3D numerical study,the particle trapping efficiency of a slotted irregular hexagonal invert trap fitted at the flume bottom was examined by incorporating the particle shape factor of non-spherical sewage solid particles and the thicknesses of upstream and downstream lids over the trap in the discrete phase model of the ANSYS Fluent 2020 R1 software.The volume of fluid(VOF)and the realizable k-turbulence models were used to predict the velocity field.The two-dimensional particle image velocimetry(PIV)was used to measure the velocity field inside the invert trap.The results showed that the thicknesses of upstream and downstream lids affected the velocity field and turbulent kinetic energy at all flow depths.The joint impact of the particle shape factor and lid thickness on the trap efficiency was significant.When both the lid thickness and particle shape factor were considered in the numerical modeling,trap efficiencies were underestimated,with relative errors of-8.66%to-0.65%in comparison to the experimental values of Mohsin and Kaushal(2017).They were also lower than the values predicted by Mohsin and Kaushal(2017),which showed an overall overestimation with errors of-2.3%to 17.4%.

Review of Fault-tolerant Control for Motor Inverter Failure with Operational Quality Considered

In recent years,motor drive systems have garnered increasing attention due to their high efficiency and superior control performance.This is especially apparent in aerospace,marine propulsion,and electric vehicles,where high performance,efficiency,and reliability are crucial.The ability of the drive system to maintain long-term fault-tolerant control(FTC)operation after a failure is essential.The likelihood of inverter failures surpasses that of other components in the drive system,highlighting its critical importance.Long-term FTC operation ensures the system retains its fundamental functions until safe repairs or replacements can be made.The focus of developing a FTC strategy has shifted from basic FTC operations to enhancing the post-fault quality to accommodate the realities of prolonged operation post-failure.This paper primarily investigates FTC strategies for inverter failures in various motor drive systems over the past decade.These strategies are categorized into three types based on post-fault operational quality:rescue,remedy,and reestablishment.The paper discusses each typical control strategy and its research focus,the strengths and weaknesses of various algorithms,and recent advancements in FTC.Finally,this review summarizes effective FTC techniques for inverter failures in motor drive systems and suggests directions for future research.