The global rise and spread of antibiotic resistance greatly challenge the treatment bacterial infections. Wastewater plants (WWTPs) harbor discharge genes (ARGs) as environmental contaminants. However, knowledge gap on host identity, activity, functionality ARGs limits transmission health risk assessment WWTP resistome. Hereby, a genome-centric quantitative metatranscriptomic approach was exploited to realize high-resolution qualitative analyses hosts (i.e., multiresistance, pathogenicity,...

The metatranscriptomic recharacterization in the present study captured microbial enzymes at unprecedented scale of 40,000 active genes belonged to 2,269 KEGG functions were identified. novel information obtained herein revealed interesting patterns and provides an initial transcriptional insight into thermophilic cellulose methanization process. Synergistic beta-sugar consumption by Thermotogales is crucial for hydrolysis cellulose-degrading consortium because primary degraders...

The randomness of user behaviors plays a significant role in electric vehicle (EV) scheduling problems, especially when the power supply for EV equipment (EVSE) is limited. Existing methods do not consider this limitation and assume charging session parameters, such as stay duration energy demand values, are perfectly known, which realistic practice. In paper, based on real-world implementations networked EVSEs University California at Los Angeles campus, we developed predictive framework,...

Resilience of a distribution system can be enhanced by efficient restoration critical load following major outage. Existing models include optimization approaches that consider available information without incorporating the inherent asynchrony data arrival during execution plan. Failure to asynchronous nature lead underutilization resources. Moreover, analytical become computationally inefficient for large scale systems. On other hand, artificial intelligence (AI)-based tools have...

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities distributed storage and generation in distribution network. With the introduction Vehicle-to-Home (V2H) Vehicle-to-Grid (V2G), EVs can help stabilize operation grid. This paper proposed implemented a hybrid V2H/V2G system commercialized EVs, which is able to support both islanded AC/DC one single platform. Standard industrial communication protocols are seamless...

Temperature sensors are widely used in industrial production and scientific research, accurate temperature measurement is crucial for ensuring the quality safety of processes. To improve accuracy stability sensors, this paper proposed using an artificial neural network (ANN) model calibration explored feasibility effectiveness ANNs to calibrate sensors. The experiment collected multiple sets data from standard different environments compared results ANN model, linear regression, polynomial...

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities distributed storage and generation. This paper comprehensively models analyzes Vehicle-to-Grid (V2G) automatic sharing driver preference. In a micro-grid limited communications, V2G EVs need to decide based on their own voltage profile. A droop controller taking into account preference is proposed in this address the control EVs. Simulations are designed three...

Deploying text-to-image (T2I) models is challenging due to high computational demands, extensive data needs, and the persistent goal of enhancing generation quality diversity, particularly on resource-constrained devices. We introduce a lightweight T2I framework that uses dual-conditioned Conditional Variational Autoencoder (CVAE), leveraging CLIP embeddings for semantic guidance enabling explicit attribute control, thereby reducing load dependency. Key our approach specialized mapping...

Evaluating the marginal likelihood in Bayesian analysis is essential for model selection. Estimators based on a single Markov chain Monte Carlo sample from posterior distribution include harmonic mean estimator and inflated density ratio estimator. We propose new class of estimators this sample. This can be thought as generalization using partition weighted kernel (likelihood times prior). show that our consistent has better theoretical properties than estimators. In addition, we provide...

Modern distribution systems are confronted by increasing penetration of distributed energy resources, making state estimation a critical application for systems. However, existing schemes often time-consuming and therefore, hard to scale up large In this context, paper has proposed using surrogate model accelerate estimations. Long-short-term memory (LSTM) recurrent neural networks have been applied produce fast yet coarse the system states, which captures temporal correlations between...

Resiliency of distribution systems under extreme operating conditions is critical, especially when the utility not available. With large-scale deployment distributed resources, it becomes possible to restore critical loads with local non-utility resources. Distribution system operators (DSOs) need determine be restored, considering limited resources and facilities. Several studies on resiliency have been conducted for restoration systems. However, inherent asynchronous characteristic...

Uncertainty Quantification for the BGK Model of Boltzmann Equation Using Multilevel Variance Reduced Monte Carlo Methods

We introduce PowerGym, an open-source reinforcement learning environment for Volt-Var control in power distribution systems. Following OpenAI Gym APIs, PowerGym targets minimizing loss and voltage violations under physical networked constraints. provides four systems (13Bus, 34Bus, 123Bus, 8500Node) based on IEEE benchmark design variants various difficulties. To foster generalization, offers a detailed customization guide users working with their As demonstration, we examine...

Using a dynamic method, the experimental solubility of ammonium benzoate (ABE) in supercritical carbon dioxide (SCCO2) with cosolvent ethanol, acetone, or ethylene glycol was measured at temperature 318 K, mole fraction 0.02, and pressure range from 11.0 to 21.0 MPa; under same conditions, ABE SCCO2 ethanol further determined temperatures 308, 318, 328 K molar concentrations 0.01, 0.04. The data were correlated four semi-empirical models (González, Thakur, Sovová, Tang) commonly used for...

Reinforcement learning is well-studied under discrete actions. Integer actions setting popular in the industry yet still challenging due to its high dimensionality. To this end, we study reinforcement integer by incorporating Soft Actor-Critic (SAC) algorithm with an reparameterization. Our key observation for that their structure can be simplified using comparability property. Hence, proposed reparameterization does not need one-hot encoding and of low Experiments show SAC as good...

Cellulose degradation results from the synergistic effect of different enzymes, but which enzyme is involved in initial stage cellulose still not well understood. Cellobiohydrolase 2 (CBH2) attached to conidial surface possibly associated with stage. However, its specific mechanism incompletely known. This study explored potential role CBH2 initiating using a constitutive overexpression strategy. First, CBH2-overexpression

The filamentous fungus Trichoderma reesei is extensively used for the industrial-scale cellulase production. It has been well known that transcription factor Xyr1 plays an important role in regulatory network controlling gene expression. However, of regulation expression not comprehensively elucidated, which hinders further improvement lignocellulolytic enzyme production.Here, dosage xyr1 was tailored T. by differentially overexpressing under control three strong promoters (Pegl2, Pcbh1, and...