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The comprehensive optimization of thermodynamic and economic performances is significant for the engineering application of ocean thermal energy conversion (OTEC). Motivated by this, this paper develops a thermo-economic OTEC model and conducts a sensitivity analysis of the OTEC system concerning its thermodynamic and economic performances. Specifically, the impact of warm-seawater temperature and cold-seawater pumping depth on the net thermal efficiency and the total investment cost are investigated. The results indicate that, an increase in warm-seawater temperature and cold-seawater pumping depth can improve the net thermal efficiency and a higher installed capacity is beneficial to the system economics. Building on these, a design optimization method with considering the on-design and off-design conditions is proposed in this paper, and the dynamic variation of warm-seawater temperature are considered in this method. In multi-objective optimization procedure, with the objective functions being the average net thermal efficiency and unit power cost within the operational cycle, the non-dominated sorting genetic algorithm II (NSGA-II) is employed to maximize the net thermal efficiency and minimize the unit power investment cost, resulting in the Pareto front. The net thermal efficiencies of OTEC systems using ammonia and R245fa as working fluids are 4.13% and 3.8%, respectively. This represents an improvement of 19.4% and 57.0%, respectively, compared to traditional optimization methods that do not account for off-design conditions.

Municipal solid waste incineration (MSWI) fly ash must be treated properly prior to being disposed in the security landfill due to its serious pollution toxicity. Nowadays, lots of studies have demonstrated that cement-based stabilization/solidification could reduce the toxicity pollution effectively by encapsulating the heavy metals into cement matrix, which leads to greater capacity and weight. This paper compares and discusses the MSWI fly ash treatment with the mostly used matrix materials such as Portland cement, phosphate cement, aluminate cement, and alkaline activated cement. Moreover, immobilization mechanism introduced by the interaction between the MSWI fly ash and hydrated cement matrix materials, such as the physical cementing effect, adsorption, isomorphous replacement, and complex precipitation, was explored in depth. The paper also pointed out some reasonable development directions for cement-based stabilization/solidification technology to improve the effectiveness and application of cement-based stabilization/solidification technology.

In this paper, the exact solutions of generalized nonlinear Schrödinger (GNLS) equation are obtained by using Darboux transformation(DT). We derive some expressions of the 1-solitons, 2-solitons and n -soliton solutions of the GNLS equation via constructing special Lax pairs. And we choose different seed solutions and solve the GNLS equation to obtain the soliton solutions, breather solutions and rational wave solutions. Based on these obtained solutions, we consider the elastic interactions and dynamics between two solitons.

The ATP binding cassette (ABC) transporter of mitochondria (Atm) from Arabidopsis thaliana ( At Atm3) has been implicated in the maturation of cytosolic iron-sulfur proteins and heavy metal detoxification, plausibly by exporting glutathione derivatives. Using single-particle cryo-electron microscopy, we have determined four structures of At Atm3 in three different conformational states: two inward-facing conformations (with and without bound oxidized glutathione [GSSG]), together with closed and outward-facing states stabilized by MgADP-VO 4 . These structures not only provide a structural framework for defining the alternating access transport cycle, but also reveal the paucity of cysteine residues in the glutathione binding site that could potentially form inhibitory mixed disulfides with GSSG. Despite extensive efforts, we were unable to prepare the ternary complex of At Atm3 containing both GSSG and MgATP. A survey of structurally characterized type IV ABC transporters that includes At Atm3 establishes that while nucleotides are found associated with all conformational states, they are effectively required to stabilize occluded, closed, and outward-facing conformations. In contrast, transport substrates have only been observed associated with inward-facing conformations. The absence of structures with dimerized nucleotide binding domains containing both nucleotide and transport substrate suggests that this form of the ternary complex exists only transiently during the transport cycle.

Recently, convolutional neural networks (CNNs) have been widely applied in brain-computer interface (BCI) based on electroencephalogram (EEG) signals. Due to the subject-specific nature of EEG signal patterns and the multi-dimensionality of EEG features, it is necessary to employ appropriate feature representation methods to enhance the decoding accuracy of EEG. In this study, we proposed a method for representing EEG temporal, frequency, and phase features, aiming to preserve the multi-domain information of EEG signals. Specifically, we generated EEG temporal segments using a sliding window strategy. Then, temporal, frequency, and phase features were extracted from different temporal segments and stacked into 3D feature maps, namely temporal-frequency-phase features (TFPF). Furthermore, we designed a compact 3D-CNN model to extract these multi-domain features efficiently. Considering the inter-individual variability in EEG data, we conducted individual testing for each subject. The proposed model achieved an average accuracy of 89.86, 78.85, and 63.55% for 2-class, 3-class, and 4-class motor imagery (MI) classification tasks, respectively, on the PhysioNet dataset. On the GigaDB dataset, the average accuracy for 2-class MI classification was 91.91%. For the comparison between MI and real movement (ME) tasks, the average accuracy for the 2-class were 87.66 and 80.13% on the PhysioNet and GigaDB datasets, respectively. Overall, the method presented in this paper have obtained good results in MI/ME tasks and have a good application prospect in the development of BCI systems based on MI/ME.

Road extraction techniques based on remote sensing image have significantly advanced. Currently, fully supervised road segmentation neural networks based on remote sensing images require a significant number of densely labeled road samples, limiting their applicability in large-scale scenarios. Consequently, semi-supervised methods that utilize fewer labeled data have gained increasing attention. However, the imbalance between a small quantity of labeled data and a large volume of unlabeled data leads to local detail errors and overall cognitive mistakes in semi-supervised road extraction. To address this challenge, this paper proposes a novel consistency self-training semi-supervised method (CSSnet), which effectively learns from a limited number of labeled data samples and a large amount of unlabeled data. This method integrates self-training semi-supervised segmentation with semi-supervised classification. The semi-supervised segmentation component relies on an enhanced generative adversarial network for semantic segmentation, which significantly reduces local detail errors. The semi-supervised classification component relies on an upgraded mean-teacher network to handle overall cognitive errors. Our method exhibits excellent performance with a modest amount of labeled data. This study was validated on three separate road datasets comprising high-resolution remote sensing satellite images and UAV photographs. Experimental findings showed that our method consistently outperformed state-of-the-art semi-supervised methods and several classic fully supervised methods.

The merbecovirus subgenus of coronaviruses includes Middle East Respiratory Syndrome Coronavirus (MERS-CoV), a zoonotic pathogen transmitted from dromedary camels to humans that causes severe respiratory disease. Viral discovery efforts uncover hundreds of merbecoviruses in different species across multiple continents, but few are studied under laboratory conditions, leaving basic questions regarding their human threat potential unresolved. Viral entry into host cells is a critical step for transmission between hosts. Here, we develop and apply a scalable approach to assesses novel merbecovirus cell entry across the entire merbecovirus subgenus. Merbecoviruses are sorted into clades based on the receptor-binding domain of the spike glycoprotein. Receptor tropism is clade-specific, with the clade including MERS-CoV using DPP4 and multiple clades using ACE2, including HKU5 bat coronaviruses. Mutational analysis identifies possible structural limitations to HKU5 adaptability and a cryo-EM structure of the HKU5-20s spike trimer reveals only ‘down’ RBDs. This work shows that receptor use in merbecovirus is clade-specific by clustering them into clades based on the receptor-binding domain (RBD) of their spike proteins. While MERS-CoV and its close relatives use the DPP4 receptor, several other clades—including all HKU5 bat coronaviruses—rely on ACE2, the same receptor used by SARS-CoV and SARS-CoV-2.

Purpose Sustainable manufacturing is practiced globally as a comprehensive strategy for improving the sustainability performance of the manufacturing industry. While sustainability is characterized into such three dimensions as economic, environmental, and social, currently, there is no quantitative method yet to measure the so-called “sustainability” in the manufacturing industry. The objective of this research is to develop a comprehensive and effective quantitative method to measure the overall sustainability performance of manufacturing companies. Methods In this paper, an integrated methodology is presented for the development of composite sustainability indicators based on principal component analysis (PCA). In developing this integrated approach, both industry and academia surveys are conducted to identify what sustainability indicators are favored by the sustainable manufacturing community. A unique index is then generated to measure the overall sustainability performance of industrial practices. The methodology can be used for benchmarking the overall sustainability performance of various manufacturing companies. Results A case study is conducted on a total of 11 global electronic manufacturing companies. The overall sustainability performance of these companies are measured, benchmarked, and ranked. The results showed that PCA is an effective approach for constructing composite sustainability indicators across environmental, economic, and social dimensions. Conclusions From this research, it is found that industry and academia have different views on the sustainability measurement, evidenced by different weights put on the same indicator in industry and academia. The case study demonstrated that the methodology presented in this paper is an effective tool for comprehensive measurement of sustainability performance of manufacturing companies. Strengths and weaknesses of each company can be identified. Then, the recommended improvements can be suggested based on the study of each of the individual indicators.

It is of particular interest to use eco-friendly working fluids in ocean thermal energy conversion (OTEC) systems. In response, this study develops a thermo-economic model to evaluate the feasibility of fourth-generation refrigerants, including R1234yf, R1234ze(Z), and R1336mzz(Z), as potential alternatives to ammonia. The analysis examines the effects of system scale and cold seawater pumping depth on capital investment distribution and key economic indicators, such as the levelized cost of energy (LCOE) and net present value (NPV). The findings highlight the viability of R1234ze(Z) as a substitute for ammonia, demonstrating a slightly lower LCOE and requiring 8.6% less installed capacity to achieve financial breakeven. Additionally, the economic impact of pumping depth varies with system scale: in small-scale OTEC systems, LCOE initially decreases with depth before rising beyond an optimal point, while in large-scale systems, it continuously declines and eventually stabilizes. Moreover, capital investment allocation shifts with system size, making pipeline optimization crucial for small-scale systems, whereas minimizing heat exchanger costs is key to enhancing the economic feasibility of large-scale OTEC plants. The results offer guidance for cost-effective OTEC deployment and refrigerant selection, supporting a sustainable energy supply for tropical islands.

The role of definitive radiotherapy (dRT) and debulking surgery (DS) for patients with locally advanced, unresectable, Masaoka-Koga stage III thymomas was not well studied. Unresectable tumor refers to tumor that could not be completely resected because of invasion of surrounding organs. Consecutive patients with unresectable stage III thymomas between 2000 and 2017 were reviewed. According to the treatment intent and radiation dose, patients were categorized into a dRT group and a non-dRT group. The former group included patients who received radiotherapy at doses ≥ 54 Gy after DS or biopsy. The latter group included patients who did not receive radiotherapy and those who received a radiation dose < 54 Gy. A total of 82 patients were included. Compared with non-dRT, dRT significantly improved 5-year overall survival (OS, P = 0.003), progression-free survival (PFS, P = 0.008), and freedom from locoregional failure (FFLF, P < 0.001). Compared with biopsy alone, DS did not improve OS, PFS, FFLF. On multivariate analysis, dRT was an independent prognostic factor for OS (hazard ratio [HR]: 2.37, P = 0.024), PFS (HR: 2.40, P = 0.004), and FFLF (HR: 3.83, P = 0.001). In conclusion, dRT was an effective and beneficial treatment for patients with unresectable Masaoka-Koga stage III thymoma.