Micropollutant rejection by nanofiltration membranes: a mini review dedicated to the critical factors and modelling prediction

Nanofiltration (NF) membranes, extensively used in advanced wastewater treatment, have broad application prospects for the removal of emerging trace organic micropollutants (MPs). The treatment performance is affected by several factors, such as the properties of NF membranes, characteristics of target MPs, and operating conditions of the NF system concerning MP rejection. However, quantitative studies on different contributors in this context are limited. To fill the knowledge gap, this study aims to assess critical impact factors controlling MP rejection and develop a feasible model for MP removal prediction. The mini-review firstly summarized membrane pore size, membrane zeta potential, and the normalized molecular size (λ = rs/rp), showeing better individual relationships with MP rejection by NF membranes. The Lindeman-Merenda-Gold model was used to quantitatively assess the relative importance of all summarized impact factors. The results showed that membrane pore size and operating pressure were the high impact factors with the highest relative contribution rates to MP rejection of 32.11% and 25.57%, respectively. Moderate impact factors included membrane zeta potential, solution pH, and molecular radius with relative contribution rates of 10.15%, 8.17%, and 7.83%, respectively. The remaining low impact factors, including MP charge, molecular weight, logKow, pKa and crossflow rate, comprised all the remaining contribution rates of 16.19% through the model calculation. Furthermore, based on the results and data availabilities from references, the machine learning-based random forest regression model was trained with a relatively low root mean squared error and mean absolute error of 12.22% and 6.92%, respectively. The developed model was then successfully applied to predict MPs’ rejections by NF membranes. These findings provide valuable insights that can be applied in the future to optimize NF membrane designs, operation, and prediction in terms of removing micropollutants

PromptTTS 2: Describing and Generating Voices with Text Prompt

Speech conveys more information than just text, as the same word can be uttered in various voices to convey diverse information. Compared to traditional text-to-speech (TTS) methods relying on speech prompts (reference speech) for voice variability, using text prompts (descriptions) is more user-friendly since speech prompts can be hard to find or may not exist at all. TTS approaches based on the text prompt face two challenges: 1) the one-to-many problem, where not all details about voice variability can be described in the text prompt, and 2) the limited availability of text prompt datasets, where vendors and large cost of data labeling are required to write text prompt for speech. In this work, we introduce PromptTTS 2 to address these challenges with a variation network to provide variability information of voice not captured by text prompts, and a prompt generation pipeline to utilize the large language models (LLM) to compose high quality text prompts. Specifically, the variation network predicts the representation extracted from the reference speech (which contains full information about voice) based on the text prompt representation. For the prompt generation pipeline, it generates text prompts for speech with a speech understanding model to recognize voice attributes (e.g., gender, speed) from speech and a large language model to formulate text prompt based on the recognition results. Experiments on a large-scale (44K hours) speech dataset demonstrate that compared to the previous works, PromptTTS 2 generates voices more consistent with text prompts and supports the sampling of diverse voice variability, thereby offering users more choices on voice generation. Additionally, the prompt generation pipeline produces high-quality prompts, eliminating the large labeling cost. The demo page of PromptTTS 2 is available online\footnote{https://speechresearch.github.io/prompttts2}.Comment: Demo page: https://speechresearch.github.io/prompttts

Effects of Arsenic Trioxide-Loaded PLGA Nanoparticles on Proliferation and Migration of Human Vascular Smooth Muscle Cells

Backgroud. To evaluate improvement of arsenic trioxide-loaded PLGA nanoparticles (As2O3-PLGA-NPs) to Human Vascular Smooth Muscle Cells (HUVSMCs) in vitro. Methods. As2O3-PLGA-NPs were synthesized and characterized by transmission electron microscopy (TEM), scanning electron microscope (SEM), and energy dispersive spectrometry (EDS), and the cumulative release rates of As2O3-PLGA-NPs were measured in vitro; HUVSMCs were treated with As2O3-PLGA-NPs in vitro. MTT assay and flow cytometry assay (FCM) were performed to examine the inhibitory effect of As2O3-PLGA-NPs on HUVSMCs and compared with As2O3 solution at various concentrations. Optical microscope was used to observe the morphological change of HUVSMCs treated with As2O3-PLGA-NPs. The expression of Bcl-2, Bax, and MMP-9 in HUVSMCs was detected by RT-PCR and Western blot (WB). Results. EDS confirmed that prepared nanoparticles contained elements of arsenic. The surface coating of the eluting stent of As2O3-PLGA-NPs has the same characteristics with our self-prepared As2O3-PLGA-NPs, and it also has a drug sustained-release character. Compared with the control group, cell proliferation and migration cell were significantly suppressed with concentration-dependent (P<0.05, respectively). Meanwhile, in concentration-dependent, As2O3-PLGA-NPs depressed mRNA and protein expression of Bcl-2 and MMP-9 and increased mRNA and protein expression of Bax. Conclusion. As2O3-PLGA-NPs had an inhibitory effect on HUVSMCs’ proliferation and migration, and it may work via regulating Bax, Bcl-2, and MMP-9 expression in vitro

A novel single-stage process integrating simultaneous COD oxidation, partial nitritation-denitritation and anammox (SCONDA) for treating ammonia-rich organic wastewater

In this study, simultaneous carbon oxidation, partial nitritation, denitritation and anammox (SCONDA) was successfully integrated into a one-stage sequencing biofilm batch reactor for treating ammonia-rich organic wastewater with carbon to nitrogen (C/N) ratio of 3. The results showed that 94.3% of COD removal together with 92.6% NH4+-N and 88% TN removal were achieved via SCONDA. High-throughout sequencing analysis further revealed that the microbial community developed in the proposed system was primarily dominated by heterotrophic bacteria (e.g. Thauera, Azovibrio, Ohtaekwangia, Azospira), autotrophic bacteria (e.g. Nitrosomona) and unclassified genus of anammox bacterium, which were all essential for COD and N removal via SCONDA. The observed spatial distributions of the functional species in stratified biofilms were found to be crucial for successful SCONDA at the low dissolved oxygen of 1.3 mg/L. The integrated SCONDA system is expected to offer a promising alternative for advanced nitrogen and organic removal from high-ammonia organic wastewater

Wetland Park Planning and Management Based on the Valuation of Ecosystem Services: A Case Study of the Tieling Lotus Lake National Wetland Park (LLNWP), China

The valuation of wetland ecosystem services and the construction of environmental landscapes are generally recognized as contributing to the sustainable development of human wellbeing. The valuation of ecosystem services plays an important role in planning for the recovery of degraded wetlands and in urban wetland park management; however, the role of the valuation of ecosystem services is always ignored. To bring more intuitive awareness to the importance of the ecological functions of wetlands and to rationally plan wetland parks, the Lotus Lake National Wetland Park (LLNWP), an urban wetland park in Northeast China, was selected as the study area. We referred to the millennium ecosystem assessment (MA) method and calculated the valuation of this park using the market value, benefit transfer, shadow engineering, carbon tax, and travel cost. ArcGIS was used for remote sensing interpretation. The research results were as follows. LLNWP was classified under seven types of land-use. The functions of the ecosystem services included provisioning, regulating, supporting, and cultural services, and their total value in LLNWP was 11.68×108 CNY. Regarding the per-unit area value of the ecological service functions of different land types, it was found that forest swamp > herbaceous swamp > artificial wetland > permanent river > floodplain wetland. Combined with the characteristics of the functions of its ecosystem’s services, LLNWP was divided into ecological and socio-cultural functions. Then, according to the main service functions of the different land types, we propose that the space in LLNWP can be reused, and proposal planning and management suggestions can be made with the aim of preserving the basic functions

Temporal Analysis Reveals the Transient Differential Expression of Transcription Factors That Underlie the Trans-Differentiation of Human Monocytes to Macrophages

The activation of monocytes and their trans-differentiation into macrophages are critical processes of the immune response. Prior work has characterized the differences in the expression between monocytes and macrophages, but the transitional process between these cells is poorly detailed. Here, we analyzed the temporal changes of the transcriptome during trans-differentiation of primary human monocytes into M0 macrophages. We find changes with many transcription factors throughout the process, the vast majority of which exhibit a maximally different expression at the intermediate stages. A few factors, including AP-1, were previously known to play a role in immunological transitions, but most were not. Thus, these findings indicate that this trans-differentiation requires the dynamic expression of many transcription factors not previously discussed in immunology, and provide a foundation for the delineation of the molecular mechanisms associated with healthy or pathological responses that involve this transition

Memristive Synapse Based on Single‐Crystalline LiNbO3 Thin Film with Bioinspired Microstructure for Experience‐Based Dynamic Image Mask Generation

Abstract One of the key steps toward constructing neuromorphic systems is to develop reliable bio‐realistic synaptic devices. Here, memristors based on single‐crystalline LiNbO3 (SC‐LNO) thin film are fabricated as artificial synapses. A reservoir of oxygen vacancies is induced by Ar+ irradiation to resemble synaptic vesicles containing neurotransmitters. Phenomena of saturation and adaptivity, short‐term plasticity, paired‐pulse facilitation, paired‐pulse depression, and long‐term potentiation are successfully mimicked. The dynamic transition from sensory memory to short‐term memory, and further to long‐term memory, is also successfully emulated for multipattern memorization. In addition, first, taking advantage of short‐ and long‐term synaptic plasticity is proposed, to realize experience‐based image mask generation with different stimuli schemes. During the experience‐based generation process, memristive multi‐value masks (MMVMs) are generated with different numbers of stimuli applied to the memristor at each pixel, which corresponds to the times the region occurred in the history image set. The experience‐based memristive multi‐value mask successfully extracts multiple regions of interest with different priorities. This work demonstrates that the memristor based on Ar+‐irradiated SC‐LNO thin film with bioinspired microstructure shows great potential in future neuromorphic systems for experience‐based intelligent image processing

Excitonic Insulator Enabled Ultrasensitive Terahertz Photodetection with Efficient Low‐Energy Photon Harvesting

Abstract Despite the interest toward the terahertz (THz) rapidly increasing, the high‐efficient detection of THz photon is not widely available due to the low photoelectric conversion efficiency at this low‐energy photon regime. Excitonic insulator (EI) states in emerging materials with anomalous optical transitions and renormalized valence band dispersions render their nontrivial photoresponse, which offers the prospect of harnessing the novel EI properties for the THz detection. Here, an EI‐based photodetector is developed for efficient photoelectric conversion in the THz band. High‐quality EI material Ta2NiSe5 is synthesized and the existence of the EI state at room temperature is confirmed. The THz scanning near‐field optical microscopy experimentally reveals the strong light–matter interaction in the THz band of EI state in the Ta2NiSe5. Benefiting from the strong light–matter interaction, the Ta2NiSe5‐based photodetectors exhibit superior THz detection performances with a detection sensitivity of ≈42 pW Hz−1/2 and a response time of ≈1.1 µs at 0.1 THz at room temperature. This study provides a new avenue for realizing novel high‐performance THz photodetectors by exploiting the emerging EI materials

Application and Development of Noncontact Detection Method of &alpha;-Particles Based on Radioluminescence

The detection of &alpha; particles is of great significance in military and civil nuclear facility management. At present, the contact method is mainly used to detect &alpha; particles, but its shortcomings limit the broad application of this method. In recent years, preliminary research on noncontact &alpha;-particle detection methods has been carried out. In this paper, the theory of noncontact &alpha;-particles detection methods is introduced and studied. We also review the direct detection and imaging methods of &alpha; particles based on the different wavelengths of fluorescence photons, and analyze the application and development of this method, providing an important reference for researchers to carry out related work

Magnetic-Field-Induced Deformation Analysis of Magnetoactive Elastomer Film by Means of DIC, LDV, and FEM

This work studied a flexible and stretchable magnetoactive elastomer (MAE) film consisting of carbonyl iron (CI) particles and polydimethylsiloxane (PDMS) elastomer matrix. The deformation of the MAE film was investigated using digital image correlation (DIC) and laser Doppler velocimetry (LDV) methods. The MAE film with free boundary is highly wrinkled under a magnetic field generated by an electromagnet with the current of 0.65 A. While in fixed boundary condition, the maximum deformation appears at the center point, and the maximum displacement reaches 0.63 mm when the current is 3 A. The finite element method (FEM) results demonstrate that the maximum internal stress and strain are 33 kPa and 2.3%, respectively. The FEM results are in good agreement with the DIC and LDV tests. With the exceptional magnetic controllability, the MAE film can find extensive applications in intelligent control systems, acoustic absorption devices, and haptics