Recent trends in functional characteristics and degradation methods of alginate

The total area of the Earth's oceans is 360 million square kilometers, accounting for approximately 71% of the Earth's surface area. It is a huge treasure trove of resources, containing abundant mineral resources, oil and gas resources, microbial resources, etc. The production of marine biomass is enormous, and as a third-generation renewable energy source, it has more sustainable development potential than terrestrial biomass. The main source of marine biomass is marine algae, so the development and excavation of marine algae resources is imperative. At present, alginate has become the second largest sustainable development resource in terms of production, second only to cellulose, and has enormous application value. The biological enzyme method for degrading alginate utilizes alginate lyase to β The elimination mechanism breaks the glycosidic bond, which has more degradation advantages than physical and chemical methods

White-box Membership Inference Attacks against Diffusion Models

Diffusion models have begun to overshadow GANs and other generative models in industrial applications due to their superior image generation performance. The complex architecture of these models furnishes an extensive array of attack features. In light of this, we aim to design membership inference attacks (MIAs) catered to diffusion models. We first conduct an exhaustive analysis of existing MIAs on diffusion models, taking into account factors such as black-box/white-box models and the selection of attack features. We found that white-box attacks are highly applicable in real-world scenarios, and the most effective attacks presently are white-box. Departing from earlier research, which employs model loss as the attack feature for white-box MIAs, we employ model gradients in our attack, leveraging the fact that these gradients provide a more profound understanding of model responses to various samples. We subject these models to rigorous testing across a range of parameters, including training steps, sampling frequency, diffusion steps, and data variance. Across all experimental settings, our method consistently demonstrated near-flawless attack performance, with attack success rate approaching $100\%$ and attack AUCROC near $1.0$. We also evaluate our attack against common defense mechanisms, and observe our attacks continue to exhibit commendable performance

Monitoring Dark-State Dynamics of a Single Nitrogen-Vacancy Center in Nanodiamond by Auto-Correlation Spectroscopy: Photonionization and Recharging

In this letter, the photon-induced charge conversion dynamics of a single Nitrogen-Vacancy (NV) center in nanodiamond between two charge states, negative (NV−) and neutral (NV0), is studied by the auto-correlation function. It is observed that the ionization of NV− converts to NV0, which is regarded as the dark state of the NV−, leading to fluorescence intermittency in single NV centers. A new method, based on the auto-correlation calculation of the time-course fluorescence intensity from NV centers, was developed to quantify the transition kinetics and yielded the calculation of transition rates from NV− to NV0 (ionization) and from NV0 to NV− (recharging). Based on our experimental investigation, we found that the NV−-NV0 transition is wavelength-dependent, and more frequent transitions were observed when short-wavelength illumination was used. From the analysis of the auto-correlation curve, it is found that the transition time of NV− to NV0 (ionization) is around 0.1 μs, but the transition time of NV0 to NV− (recharging) is around 20 ms. Power-dependent measurements reveal that the ionization rate increases linearly with the laser power, while the recharging rate has a quadratic increase with the laser power. This difference suggests that the ionization in the NV center is a one-photon process, while the recharging of NV0 to NV− is a two-photon process. This work, which offers theoretical and experimental explanations of the emission property of a single NV center, is expected to help the utilization of the NV center for quantum information science, quantum communication, and quantum bioimaging

Cast2Face: Character identification in movie with actor-character correspondence

10.1145/1873951.1874090MM'10 - Proceedings of the ACM Multimedia 2010 International Conference831-83

Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality

The transition towards carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitters: electricity and transportation. The transition to a carbon-neutral electric grid poses significant challenges to conventional paradigms of modern grid planning and operation. Much of the challenge arises from the scale of the decision making and the uncertainty associated with the energy supply and demand. Artificial Intelligence (AI) could potentially have a transformative impact on accelerating the speed and scale of carbon-neutral transition, as many decision making processes in the power grid can be cast as classic, though challenging, machine learning tasks. We point out that to amplify AI's impact on carbon-neutral transition of the electric energy systems, the AI algorithms originally developed for other applications should be tailored in three layers of technology, markets, and policy.Comment: To be published in Patterns (Cell Press

A Homeodomain-Containing Transcriptional Factor PoHtf1 Regulated the Development and Cellulase Expression in Penicillium oxalicum

Homeodomain-containing transcription factors (Htfs) play important roles in animals, fungi, and plants during some developmental processes. Here, a homeodomain-containing transcription factor PoHtf1 was functionally characterized in the cellulase-producing fungi Penicillium oxalicum 114-2. PoHtf1 was shown to participate in colony growth and conidiation through regulating the expression of its downstream transcription factor BrlA, the key regulator of conidiation in P. oxalicum 114-2. Additionally, PoHtf1 inhibited the expression of the major cellulase genes by coordinated regulation of cellulolytic regulators CreA, AmyR, ClrB, and XlnR. Furthermore, transcriptome analysis showed that PoHtf1 participated in the secondary metabolism including the pathway synthesizing conidial yellow pigment. These data show that PoHtf1 mediates the complex transcriptional-regulatory network cascade between developmental processes and cellulolytic gene expression in P. oxalicum 114-2. Our results should assist the development of strategies for the metabolic engineering of mutants for applications in the enzymatic hydrolysis for biochemical production

Self-organized Voids Revisited: Experimental Verification of the Formation Mechanism*

In this paper, several experiments were conducted to further clarify the formation mechanism of self organized void array induced by a single laser beam, including energy-related experiments, refractive-index-contrast-related experiments, depth-related experiments and effective-numerical-aperture experiment. These experiments indicate that the interface spherical aberration is indeed responsible for the formation of void arrays