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Abstract Host defense peptide (HDP)-mimicking polymers are promising therapeutic alternatives to antibiotics and have large-scale untapped potential. Artificial intelligence (AI) exhibits promising performance on large-scale chemical-content design, however, existing AI methods face difficulties on scarcity data in each family of HDP-mimicking polymers (105), and multi-constraints on properties and structures when exploring high-dimensional polymer space. Herein, we develop a universal AI-guided few-shot inverse design framework by designing multi-modal representations to enrich polymer information for predictions and creating a graph grammar distillation for chemical space restriction to improve the efficiency of multi-constrained polymer generation with reinforcement learning. Exampled with HDP-mimicking β-amino acid polymers, we successfully simulate predictions of over 105 polymers and identify 83 optimal polymers. Furthermore, we synthesize an optimal polymer DM0.8 iPen0.2 and find that this polymer exhibits broad-spectrum and potent antibacterial activity against multiple clinically isolated antibiotic-resistant pathogens, validating the effectiveness of AI-guided design strategy.

Abstract Earthworm cultivation can effectively promote the resource utilization of agricultural waste. The efficient utilization of agricultural waste by earthworms mainly depends on the microbial communities in the guts. This study used silkworm excrement and cow manure as substrates for earthworm cultivation and investigated the associated bacterial communities during earthworms’ growth. The survival rate of earthworms remained above 89% after 21 days of feeding with the two substrates. Proteobacteria, Actinobacteria, and Firmicutes constituted the predominant bacterial communities in earthworm growth, accounting for over 81% of the relative abundance in both guts and vermicompost. The bacteria richness and diversity in the foregut and midgut of earthworm were lower than those in the hindgut. The prediction function of intestinal bacterial communities of earthworms cultured with two substrates mainly involved biosynthesis, decomposition and energy production.

Abstract Unmanned aerial vehicles (UAVs) play a crucial role in various domains such as military, civil, industrial, and so on. However, the coordination and task allocation of multiple UAVs in engineering practices face numerous challenges. As the scale of battlefields expands, and the diversity of UAV missions and constraints increases, the existing task allocation methods suffer from issues such as a mismatch between theoretical models and real‐world applications, low task execution efficiency, and poor responsiveness in dynamic environments. To address these challenges, this paper proposes an improved genetic algorithm (GA)‐based approach for multi‐UAV cooperative task allocation. By collecting battlefield information, decomposing tasks, and considering UAV resource types, an optimization model for multi‐UAV cooperative task allocation is constructed. The proposed method, using an improved GA, generates a set of Pareto‐optimal task solutions for decision‐makers. Case studies demonstrate that this approach effectively enhances task execution efficiency and reduces the total flight distance cost of UAVs.

Abstract X-ray diffraction (XRD) is used for characterizing the crystal structure of molecular sieves after synthetic experiments. However, for a high-throughput molecular sieve synthetic system, the huge amount of data derived from large throughput capacity makes it difficult to analyze timely. While the kernel step of XRD analysis is to search peaks, an automatic way for peak search is needed. Thus, we proposed a novel semantic mask-based two-step framework for peak search in XRD patterns: (1) mask generation, we proposed a multi-resolution net (MRN) to classify the data points of XRD patterns into binary masks (peak/background). (2) Peak search, based on the generated masks, the background points are used to fit an n-order polynomial background curve and estimate the random noises in XRD patterns. Then we proposed three rules named mask, shape, and intensity to screening peaks from initial peak candidates generated by maximum search. Besides, a voting strategy is proposed in peak screening to obtain a precise peak search result. Experiments show that the proposed MRN achieves the state-of-the-art performance compared with other semantic segmentation methods and the proposed peak search method performs better than Jade when using f1 score as the evaluation index.

Accurate prediction of the structurally diverse complementarity determining region heavy chain 3 (CDR-H3) loop structure remains a primary and long-standing challenge for antibody modeling. Here, we present the H3-OPT toolkit for predicting the 3D structures of monoclonal antibodies and nanobodies. H3-OPT combines the strengths of AlphaFold2 with a pre-trained protein language model and provides a 2.24 Å average RMSDCα between predicted and experimentally determined CDR-H3 loops, thus outperforming other current computational methods in our non-redundant high-quality dataset. The model was validated by experimentally solving three structures of anti-VEGF nanobodies predicted by H3-OPT. We examined the potential applications of H3-OPT through analyzing antibody surface properties and antibody–antigen interactions. This structural prediction tool can be used to optimize antibody–antigen binding and engineer therapeutic antibodies with biophysical properties for specialized drug administration route.

Direct aging of water-quenched metastable β-titanium alloys usually follows the sequence: rapid growth of ωiso and then slow transformation into α. To inhibit ωiso growth and promote α nucleation, 6% pre-deformation was introduced in Ti-10V-6Cu alloy before 500°C/60s aging. An ultrafast α-formation and a few α-free kink-bands are observed, indicating the alteration of the precipitation sequence. For α-nucleation without ωiso as the sites, it shows that O' nanodomains induced by stress accumulation around slip bands mediate the ultrafast nucleation of hcp-α structure, while dislocation pipe diffusion accelerates the necessary phase separation. This provides new insights into regulating precipitation kinetics of age-hardenable β-titanium alloys.

Abstract Asthma exacerbations caused by respiratory viral infections are a serious global health problem. Impaired antiviral immunity is thought to contribute to the pathogenesis, but the underlying mechanisms remain understudied. Here using mouse models we find that Cullin5 (CUL5), a key component of Cullin-RING E3 ubiquitin ligase 5, is upregulated and associated with increased neutrophil count and influenza-induced exacerbations of house dust mite-induced asthma. By contrast, CUL5 deficiency mitigates neutrophilic lung inflammation and asthma exacerbations by augmenting IFN-β production. Mechanistically, following thymic stromal lymphopoietin stimulation, CUL5 interacts with O-GlcNAc transferase (OGT) and induces Lys48-linked polyubiquitination of OGT, blocking the effect of OGT on mitochondrial antiviral-signaling protein O-GlcNAcylation and RIG-I signaling activation. Our results thus suggest that, in mouse models, pre-existing allergic injury induces CUL5 expression, impairing antiviral immunity and promoting neutrophilic inflammation for asthma exacerbations. Targeting of the CUL5/IFN-β signaling axis may thereby serve as a possible therapy for treating asthma exacerbations.

Common complications following laparoscopic appendectomy include wound infection, bleeding, intra-abdominal abscess, small bowel obstruction, stump leakage, and stump appendicitis. Here, we presented a case reporting detailing a rare complication following laparoscopic appendectomy: the development of a metastatic neck abscess induced by Klebsiella pneumoniae(K. pneumoniae). A 49-year-old male underwent emergency laparoscopic surgery with prophylactic antibiotic administration for acute appendicitis. Subsequently, he experienced persistent neck pain and fever postoperatively, prompting further investigation. Pus and blood cultures revealed K. pneumoniae, with magnetic resonance imaging confirming the presence of a neck abscess. Antibiotic therapy was adjusted, and surgical drainage of the abscess was performed after multidisciplinary consultation. The patient was discharged without complications. While rare, metastatic abscesses following appendectomy warrant consideration, particularly in K. pneumoniae infections. Comprehensive clinical assessment, imaging, and laboratory evaluation are crucial for timely diagnosis and management of such complications.

The MTCH2 protein is located on the mitochondrial outer membrane and regulates mitochondria-related cell death. This study set out to investigate the role of MTCH2 in the underlying pathophysiological mechanisms of breast cancer (BC). MTCH2 expression levels in BC were analyzed using bioinformatics prior to verification by cell lines in vitro. Experiments of over-expression and siRNA-mediated knockdown of MTCH2 were conducted to assess its biological functions, including its effects on cellular proliferation and cycle progression. Xenografts were utilised for in vivo study and signaling pathway alterations were examined to identify the mechanisms driven by MTCH2 in BC proliferation and cell-cycle regulation. MTCH2 was up-regulated in BC and correlated with patients’ overall survival. Over-expression of MTCH2 promoted cellular proliferation and cycle progression, while silencing MTCH2 had the opposite effect. Xenograft experiments were utilised to confirm the in vitro cellular findings and it was identified that the PI3K/Akt signaling pathway was activated by MTCH2 over-expression and suppressed by its silencing. Moreover, the activation of IGF-1R rescued cellular growth and cycle arrest induced by MTCH2-silencing. Overall, this study reveals that expression of MTCH2 in BC is upregulated and potentiates cellular proliferation and cycle progression via the PI3K/Akt pathway.

Abstract Intravitreal (IVT) injection of anti‐vascular endothelial growth factor (anti‐VEGF) has greatly improved the treatment of many retinal disorders, including wet age‐related macular degeneration (wAMD), which is the third leading cause of blindness. However, frequent injections can be difficult for patients and may lead to various risks such as elevated intraocular pressure, infection, and retinal detachment. To address this issue, researchers have found that IVT injection of anti‐VEGF proteins at their maximally viable concentration and dose can be an effective strategy. However, the intrinsic protein structure can limit the maximum concentration due to stability and solution viscosity. To overcome this challenge, we developed a novel anti‐VEGF protein called nanoFc by fusing anti‐VEGF nanobodies with a crystallizable fragment (Fc). NanoFc has demonstrated high binding affinity to VEGF165 through multivalency and potent bioactivity in various bioassays. Furthermore, nanoFc maintains satisfactory chemical and physical stability at 4°C over 1 month and is easily injectable at concentrations up to 200 mg/mL due to its unique architecture that yields a smaller shape factor. The design of nanoFc offers a bioengineering strategy to ensure both strong anti‐VEGF binding affinity and high protein concentration, with the goal of reducing the frequency of IV injections.

In order to better understand the role of coral reefs around an isolated island in mitigating tsunami hazards, this study performed a horizontally two-dimensional (2DH) numerical study of tsunami-like solitary wave propagation and run-up around an idealized reef-fringed island. The shock-capturing Boussinesq wave model, the FUNWAVE-TVD is used in the present study and well-validated with existing experimental data for its robustness in predicting 2DH solitary wave processes around an island. Based on the validated model, the typical solitary propagation process around the reef-fringed island and the effects of morphological and hydrodynamic parameters on the maximum run-up heights were systematically investigated. It is found that coral reefs can effectively reduce maximum run-up heights around an isolated island. The reef flat’s water depth, reef flat width, and reef surface roughness are the main factors affecting maximum run-up heights around an island, while the fore-reef slope has little impact. For the idealized reef-fringed island in this study, sea-level rise will cause coral reefs to lose their protective capability on the lee side, and the presence of coral reefs may even enhance tsunami hazards around an island when the reef flat width is very narrow or coral bleaching happens.

Growing environmental concerns have prompted the shipping industry to adopt stringent measures to address greenhouse gas emissions, with fuel-powered ships being the primary source of such emissions. Additionally, alternative forms of ship propulsion, such as internal combustion engine hybridization, low-carbon fuels, and zero-carbon fuels, face significant challenges either in terms of cost or emission-reduction capability at present. In order to decarbonize navigation, countries are focusing the maritime industry’s transition towards low-carbon alternatives on transforming energy consumption, with widespread attention on the electrification of ships. Therefore, this paper provides a comprehensive review of the feasibility of fully electrifying ships, covering aspects such as technological prospects, economic viability, and emission-reduction capabilities. Firstly, the current state of research on ship electrification technology is summarized; the applicability of different battery types to electric ship technology is compared. Subsequently, the economic viability and emission-reduction capabilities of five different electric ship lifecycles are discussed separately. The results indicate that ship electrification is a key pathway to achieving zero-emission shipping, with lithium-ion batteries being the most suitable battery technology for maritime use currently. Short-to-medium-range electric ship types have demonstrated economic advantages over traditional diesel ships. As battery costs continue to decline and energy density keeps improving, the economic feasibility of ship electrification is expected to expand.

The precise calculation and effective control of the horizontal displacement of deep foundation pit retaining structures are critical for foundation pit support design and construction. Based on stress–strain linear elastomer theory and considering the deformation coordination between an enclosure wall and its internal support member, a formula for the redundant restraint force acting on the retaining wall was derived through the unit load method and the principle of elastic superposition. Moreover, a method for calculating the horizontal displacement of the retaining structure of a deep foundation pit was formulated, which is convenient for engineering applications. The method can also be used to calculate the horizontal displacement of cantilevered and anchored retaining structures when the loading conditions of the deep foundation pit and the relevant parameters of the enclosure structure are known. A case study was conducted on a standard section with an excavation width H of 19.3 m and an excavation depth h of 17.8 m. The structural parameters of the enclosure wall, along with the elastic support stiffness coefficient and soil layer parameters of the pit, were inputted into a MATLAB calculation code. Then, four internal support constraint forces Fi and the calculated values for the horizontal displacement of the enclosure wall were obtained after running the code. The calculated curve closely matched the curve of values measured in the field. The horizontal displacements of the top of the wall of several cement–soil gravity enclosure structures mentioned in the literature were also calculated. The results of these calculations were then compared with the measured data and corresponding data from the literature. The examples provided clear evidence demonstrating that the proposed method is highly reliable for calculating the horizontal displacement of deep foundation pit enclosure structures.

Converting a camera’s RAW image to an RGB format for human perception involves utilizing an imaging pipeline, and a series of processing modules. Existing modules often result in varying degrees of original information loss, which can render the reverse imaging pipeline unable to recover the original RAW image information. To this end, this paper proposes a new, almost reversible image imaging pipeline. Thus, RGB images and RAW images can be effectively converted between each other. Considering the impact of original information loss, this paper introduces a two-stage tone mapping operation (TMO). In the first stage, the RAW image with a linear response is transformed into an RGB color image. In the second stage, color scale mapping corrects the dynamic range of the image suitable for human perception through linear stretching, and reduces the loss of sensitive information to the human eye during the integer process. effectively preserving the original image’s dynamic information. The DCRAW imaging pipeline addresses the problem of high light overflow by directly highlighting cuts. The proposed imaging pipeline constructs an independent highlight processing module, and preserves the highlighted information of the image. The experimental results demonstrate that the two-stage tone mapping operation embedded in the imaging processing pipeline provided in this article ensures that the image output is suitable for human visual system (HVS) perception and retains more original image information.

Network alignment is an important technique with applications in diverse domains, such as social network analysis, bioinformatics, and knowledge graph construction. Many of the alignment methods rely on predefined anchor nodes, which are often unavailable in real-world scenarios. To overcome this limitation, we propose MANNA (MAtched Neighbor consistency for Network Alignment), an unsupervised approach to network alignment that exploits the concept of Matched Neighborhood Consistency (MNC). The hypothesis of MANNA is that nodes with higher similarity within their local neighborhood structures are more likely to be aligned across different networks. To learn the structural and attribute features of networks, MANNA uses a Graph Neural Network (GNN). It extracts multi-order node embeddings to capture multi-scale neighborhood features, which are then used to construct similarity matrices for the alignment process. MANNA introduces a key innovation by using pseudo-anchor nodes identified by the MNC strategy to provide self-supervised learning signals in the absence of real anchor nodes. This approach enhances the model’s ability to learn accurate network representations and improve alignment accuracy. Alignment results are iteratively refined by applying the MNC strategy, which strengthens the consistency of neighborhood structures between matched nodes. Extensive experiments on three public datasets show that MANNA outperforms existing network alignment methods.

An important challenge in industrial laser ablation is laser-induced damage. In this study, reduced damage was achieved through the transition of the laser distribution from a Gaussian beam to a top-hat beam using diffractive optical elements (DOE), which overcome inhomogeneous irradiation. The higher peak fluence of a Gaussian beam far exceeded the ablation threshold and led to severely melted silicon at a higher depth covering the polished texture. The top-hat beam, with uniform irradiation, had a superior ablation characteristic and created a uniform square opening with the shallow melted silicon in the lift-off process. Thus, its effective minor carrier lifetime was 15.35% less at an ablated area fraction of 2% after re-passivation because of the decreased damage. After optimizing the ablation pattern with a top-hat beam, the local contacts improved the average open-circuit voltage (Voc) and short-circuit current (Isc) values of the cells due to the decreased damage and the uniform openings, but the damage induced by a Gaussian beam was too deep and can be partly restored under back surface field (BSF) formation. The overall increment in Isc and Voc enhanced the average efficiency by 0.05% of the absolute value for the PERC cells and 0.03% of the absolute value for bi-facial PERC cells.