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TiO2 has been hampered by drawbacks such as rapid photoelectron and hole recombination and a wide energy band gap of 3.2 eV. In this study, MIL-101(Cr)@TiO2 was synthesised without any mineraliser (HF) as part of material modification approach to overcome those pitfalls. The composite was well characterized by XRD, FT-IR, TEM, XPS, BET, TGA, and Raman spectroscopy. Under optimal synthesis conditions, the 9.17% MIL-101(Cr)@TiO2 composite exhibited 99.9% CBZ degradation after 60 min under UV-A irradiation. This can be attributed to the delayed recombination of photo-generated h+ and e− and a reduced band gap energy of 2.9 eV. A Type II heterojunction structure was proposed for the composite using the Mulligan function of electronegativity with the calculated Ecb and Evb. Besides, trapping experiments and ESR spectroscopy confirmed O2•− as the main ROS for CBZ degradation. The effects of the operating parameters such as pH, UV intensity, composite dosage, and initial pollutant concentration were also evaluated. The scavenging effects of inorganic and organic constituents of pharmaceutical wastewater on the process were also evaluated, with HCO3−, CO32−, and THF having more significant inhibition on the overall CBZ degradation. The degradation pathways of CBZ were also proposed based on detected intermediates with the aid of LC/MS/MS. The composite illustrated reusability and stability without considerable loss in the degradation performance after repeated runs. This work builds on the development of more effective photocatalysts and provides a glimpse into applications for similar MOF heterojunction photocatalysts. [ABSTRACT FROM AUTHOR]

Very-high-resolution (VHR) optical imaging satellites can offer precise, accurate, and direct measurements of snow-covered areas (SCA) with sub-meter to meter-scale resolution in regions of complex land cover and terrain. We explore the potential of Maxar WorldView-2 and WorldView-3 in-track stereo images (WV) for land and snow cover mapping at two sites in the Western U.S. with different snow regimes, topographies, vegetation, and underlying geology. We trained random forest models using combinations of multispectral bands and normalized difference indices (i.e., NDVI) to produce land cover maps for priority feature classes (snow, shaded snow, vegetation, water, and exposed ground). We then created snow-covered area products from these maps and compared them with coarser resolution satellite fractional snow-covered area (fSCA) products from Landsat (~30 m) and MODIS (~500 m). Our models generated accurate classifications, even with limited combinations of available multispectral bands. Models trained on a single image demonstrated limited model transfer, with best results found for in-region transfers. Coarser-resolution Landsat and MODSCAG fSCA products identified many more pixels as completely snow-covered (100% fSCA) than WV fSCA. However, while MODSCAG fSCA products also identified many more completely snow-free pixels (0% fSCA) than WV fSCA, Landsat fSCA products only slightly underestimated the number of completely snow-free pixels. Overall, our results demonstrate that strategic image observations with VHR satellites such as WorldView-2 and WorldView-3 can complement the existing operational snow data products to map the evolution of seasonal snow cover. [ABSTRACT FROM AUTHOR]

The effects of Cobalt (II) chloride (CoCl2) in the context of Brucella abortus (B. abortus) infection have not been evaluated so far. Firstly, we found that CoCl2 treatment inhibited the phagocytosis of B. abortus into RAW 264.7 cells. The inhibition of bacterial invasion was regulated by F-actin formation and associated with a reduction in the phosphorylation of ERK1/2 and HIF-1α expression. Secondly, the activation of trafficking regulators LAMP1, LAMP2, and lysosomal enzyme GLA at the transcriptional level activated immune responses, weakening the B. abortus growth at 4 h post-infection (pi). The silencing of HIF-1α increased bacterial survival at 24 h pi. At the same time, CoCl2 treatment showed a significant increase in the transcripts of lysosomal enzyme HEXB and cytokine TNF-α and an attenuation of the bacterial survival. Moreover, the enhancement at the protein level of HIF-1α was induced in the CoCl2 treatment at both 4 and 24 h pi. Finally, our results demonstrated that CoCl2 administration induced the production of serum cytokines IFN-γ and IL-6, which is accompanied by dampened Brucella proliferation in the spleen and liver of treated mice, and reduced the splenomegaly and hepatomegaly. Altogether, CoCl2 treatment contributed to host resistance against B. abortus infection with immunomodulatory effects. [ABSTRACT FROM AUTHOR]

Introduction: Since just after the year 2000 in Quebec, the management of metastatic castration-resistant prostate cancer (mcrpc) has evolved considerably, with the inclusion of docetaxel-based chemotherapy, bone-targeted therapies (zoledronic acid and denosumab), and more recently, abiraterone, enzalutamide, and cabazitaxel for docetaxel-refractory patients. In the present study, we aimed to analyze contemporary mcrpc management patterns and therapy utilization trends in Quebec. Methods: The study cohort consisted of patients dying of prostate cancer (PCA) between January 2001 and December 2013, selected from Quebec public health care insurance databases. Patient selection was based on death from a pca-related cause or therapy used according to the Canadian Urological Association guidelines on mcrpc management. Treatments included chemotherapy (mitoxantrone before 2005 and docetaxel after 2005), abiraterone, bone-targeted therapy (zoledronic acid or denosumab, or both), and palliative radiation therapy (RT). During the study period, neither enzalutamide nor cabazitaxel was publicly reimbursed in Quebec, and as a result, no capture of their use was possible for this study. Multivariate logistic regression was used to identify factors associated with the probability of receiving chemotherapy, bone-targeted therapies, and palliative rt before death from pca. Results: Overall, the database search identified 3106 patients who died of pca between January 2001 and December 2013. Median age of death was 78 years. Of those 3106 patients, just 2568 (83%) received mcrpc-specific treatments: chemotherapy, abiraterone, palliative RT, or bone-targeted therapy; the other 17% of the patients were managed solely with maximum androgen blockade (androgen deprivation therapy plus anti-androgens) despite a record of pca-related death. Logistic regression analyses indicate that patients dying after 2005 were more likely to have received chemotherapy [odds ratio (OR): 1.51; 95% CI: 1.22 to 1.85] and bone-targeted therapy (OR: 1.97; 95% CI: 1.64 to 2.37). Age was a significant predictor for the use of chemotherapy, bone-targeted therapy, and palliative RT (ORs in the range 0.96-0.98, p < 0.05). Conclusions: Patient age seems to be a strong determinant in the of selection mcrpc therapy, affecting the probability of the use of chemotherapy, bone-targeted therapy, or palliative rt. Although chemotherapy is still used only in a small percentage of patients, the introduction of new therapies--such as bone-targeted therapy, docetaxel, and abiraterone--affected treatment selection over time. The availability of enzalutamide since February 2014 will likely produce additional changes in mcrpc management. [ABSTRACT FROM AUTHOR]

A moving ground-target recognition system can monitor suspicious activities of pedestrians and vehicles in key areas. Currently, most target recognition systems are based on devices such as fiber optics, radar, and vibration sensors. A system based on vibration sensors has the advantages of small size, low power consumption, strong concealment, easy installation, and low power consumption. However, existing recognition algorithms generally suffer from problems such as the inability to recognize long-distance moving targets and adapt to new environments, as well as low recognition accuracy. Here, we demonstrate that applying transfer learning to recognition algorithms can adapt to new environments and improve accuracy. We proposed a new moving ground-target recognition algorithm based on CNN and domain adaptation. We used convolutional neural networks (CNNS) to extract depth features from target vibration signals to identify target types. We used transfer learning to make the algorithm more adaptable to environmental changes. Our results show that the proposed moving ground-target recognition algorithm can identify target types, improve accuracy, and adapt to a new environment with good performance. We anticipate that our algorithm will be the starting point for more complex recognition algorithms. For example, target recognition algorithms based on multi-modal fusion and transfer learning can better meet actual needs.

Background: Historically, the standard of care for advanced biliary tract cancers (aBTCs) was gemcitabine plus cisplatin (GemCis). Immunotherapy plus GemCis is now recommended as a first-line treatment for aBTCs. Whether patients can tolerate eight cycles of GemCis in clinical practice, as per the Advanced Biliary Cancer (ABC)-02 study, remains to be assessed. We performed a retrospective observational cohort study to assess real-world treatment patterns and overall survival (OS) in patients with de novo or recurrent aBTCs treated with first-line gemcitabine-based chemotherapy in the United States. Methods: This retrospective observational cohort study used Optum's de-identified Market Clarity Data (Market Clarity). Adults diagnosed with de novo or recurrent aBTCs in the United States who began first-line gemcitabine-based chemotherapy from January 2016-March 2022 were identified and followed from index until death, the end of continuous enrolment, or the end of study period. Treatment patterns and OS were assessed. Results: Overall, 559 patients were included (de novo, n = 462; recurrent, n = 97). GemCis was the most common first-line therapy received (de novo: 73.8%; recurrent: 57.7%). Most patients received approximately five cycles of GemCis; median (95% CI) time to discontinuation was 4.6 (4.3-5.1) months. Most patients died over the follow-up period (de novo: 70.3%; recurrent: 62.9%). Median OS (95% CI) was 14.2 (12.1-16.1) months (de novo) and 18.5 (15.6-26.9) months (recurrent). Conclusions: GemCis was the most common first-line therapy received during the study period; most patients were unable to receive eight cycles of GemCis. Survival was limited over the follow-up period, highlighting the need for new treatments for aBTCs. Future studies are warranted to understand the real-world impact of first-line immunotherapy plus GemCis for patients with aBTCs.

Coronavirus epidemics have posed a serious threat to both human and animal health. To combat emerging infectious diseases caused by coronaviruses, various animal infection models have been developed and applied in research, including non-human primate models, ferret models, hamster models, mouse models, and others. Moreover, new approaches have been utilized to develop animal models that are more susceptible to infection. These approaches include using viral delivery methods to induce the expression of viral receptors in mouse tissues and employing gene-editing techniques to create genetically modified mice. This has led to the successful establishment of infection models for multiple coronaviruses, significantly advancing related research. In contrast, livestock and pets that can be infected by animal coronaviruses provide valuable insights when used as infection models, enabling the collection of accurate clinical data through the analysis of post-infection pathological features. However, despite the potential insights, there is a paucity of research data pertaining to these infection models. In this review, we provide a detailed overview of recent progress in the development of animal models for coronaviruses that cause diseases in both humans and animals and suggest ways in which animal models can be adapted to further enhance their value in research.

Flexible, wearable, piezoresistive sensors have significant potential for applications in wearable electronics and electronic skin fields due to their simple structure and durability. Highly sensitive, flexible, piezoresistive sensors with the ability to monitor laryngeal articulatory vibration supply a new, more comfortable and versatile way to aid communication for people with speech disorders. Here, we present a piezoresistive sensor with a novel microstructure that combines insulating and conductive properties. The microstructure has insulating polystyrene (PS) microspheres sandwiched between a graphene oxide (GO) film and a metallic nanocopper-graphene oxide (n-Cu/GO) film. The piezoresistive performance of the sensor can be modulated by controlling the size of the PS microspheres and doping degree of the copper nanoparticles. The sensor demonstrates a high sensitivity of 232.5 kPa -1 in a low-pressure range of 0 to 0.2 kPa, with a fast response of 45 ms and a recovery time of 36 ms, while also exhibiting excellent stability. The piezoresistive performance converts subtle laryngeal articulatory vibration into a stable, regular electrical signal; in addition, there is excellent real-time monitoring capability of human joint movements. This work provides a new idea for the development of wearable electronic devices, healthcare, and other fields.

While deep learning techniques have been extensively employed in malware detection, there is a notable challenge in effectively embedding malware features. Current neural network methods primarily capture superficial characteristics, lacking in-depth semantic exploration of functions and failing to preserve structural information at the file level. Motivated by the aforementioned challenges, this paper introduces MalHAPGNN, a novel framework for malware detection that leverages a hierarchical attention pooling graph neural network based on enhanced call graphs. Firstly, to ensure semantic richness, a Bidirectional Encoder Representations from Transformers-based (BERT) attribute-enhanced function embedding method is proposed for the extraction of node attributes in the function call graph. Subsequently, this work designs a hierarchical graph neural network that integrates attention mechanisms and pooling operations, complemented by function node sampling and structural learning strategies. This framework delivers a comprehensive profile of malicious code across semantic, syntactic, and structural dimensions. Extensive experiments conducted on the Kaggle and VirusShare datasets have demonstrated that the proposed framework outperforms other graph neural network (GNN)-based malware detection methods.

Water pipelines in water diversion projects can leak, leading to soil deformation and ground subsidence, necessitating research into soil deformation monitoring technology. This study conducted model tests to monitor soil deformation around leaking buried water pipelines using distributed fiber optic strain sensing (DFOSS) technology based on optical frequency domain reflectometry (OFDR). By arranging strain measurement fibers in a pipe-soil model, we investigated how leak location, leak size, pipe burial depth, and water flow velocity affect soil strain field monitoring results. The results showed that pipeline leakage creates a "saddle-shaped" spatial distribution of soil strain above the pipeline, effectively indicating ground subsidence locations. When only one survey line is arranged, it is preferable to place the optical fiber directly above the pipeline. Surface monitoring fibers primarily detected tensile strain, with more pronounced peak values observed under conditions of larger leak size, higher flow velocity, shallow burial depth, and top-pipe leakage location. Monitoring fibers below the pipeline showed mainly unimodal distribution, with peak strain coinciding with the leak location. The sequential timing of strain changes at different fiber positions enabled the determination of soil seepage direction. This study demonstrates that DFOSS technology can provide important support for the early warning of such geological disasters.

Background: The influence of serum uric acid (SUA) on bone metabolism, as suggested by previous studies, remains a contentious issue. SUA plays a complex role in bone health and hypertension, making it challenging to discern its impact on the skeletal status of middle-aged and elderly hypertensive patients. This study aims to elucidate the effects of SUA on bone health, with a particular focus on its association with osteoporosis and the risk of fractures., Methods: Multiple linear regression analyzed SUA levels against bone mineral density (BMD) and future fracture risk. Additionally, multivariate logistic regression was used to examine the association between SUA and osteoporosis. Dose-response relationship analysis was conducted using generalized smooth curve fitting (GSCF) and restricted cubic spline (RCS) methods., Results: With the exception of the total femur region, SUA and BMD showed a positive connection. GSCF analysis revealed an inverted U-shaped relationship between SUA and BMD, alongside a U-shaped trend with FRAX scores. Moreover, RCS analysis indicated a U-shaped relationship between osteoporosis risk and SUA levels, with higher risks identified in the first and third tertiles compared to the second tertile., Conclusions: In individuals with middle-aged and older hypertension, SUA is substantially linked to bone health. The identification of an inverted U-shaped relationship with BMD and U-shaped relationships with FRAX scores and osteoporosis risk highlights the nuanced influence of SUA. These findings suggest that both low and high SUA levels may adversely affect bone health, emphasizing the need for further research.

Bacillus microorganisms play an important role in the zearalenone (ZEA) biotransformation process in natural environments. The phosphotransferase pathway in Bacillus is both widespread and relatively well conserved. However, the reaction kinetics of these phosphotransferases remain poorly understood, and their catalytic activities are suboptimal. In this study, a ZEA phosphotransferase, ZPH1101, was identified from Bacillus subtilis 1101 using genome sequencing. The product transformed by ZPH1101 was identified as phosphorylated ZEA (ZEA-P) through LC-TOF-MS/MS analysis. The experiments conducted on MCF-7 cells demonstrated that ZEA-P exhibited a lower level of estrogenic toxicity than ZEA. The optimal reaction conditions for ZPH1101 were determined to be 45 °C and pH 8.0. The maximum velocity ( V max ), Michaelis constant ( K m ), and catalytic constant ( k cat ) were calculated through fitting to be 16.40 μM·s -1 ·mg -1 , 18.18 μM, and 54.69 s -1 , respectively. Furthermore, adding 1 mmol/L Fe 2+ or Fe 3+ to the reaction system increased the efficiency of ZPH1101 in converting ZEA by 100% relative to the system containing solely 1 mmol/L ATP and 1 mmol/L Mg 2+ , suggesting that low concentrations of Fe 2+ or Fe 3+ can improve the ZPH1101-mediated transformation of ZEA. This study contributes to the enzymatic removal of ZEA and broadens the spectrum of strain and enzyme options available to researchers for ZEA detoxification efforts.

Since the discovery of the Australia antigen, now known as the hepatitis B surface antigen (HBsAg), significant research has been conducted to elucidate its physical, chemical, structural, and functional properties. Subviral particles (SVPs) containing HBsAg are highly immunogenic, non-infectious entities that have not only revolutionized vaccine development but also provided critical insights into HBV immune evasion and viral assembly. Recent advances in cryo-electron microscopy (cryo-EM) have uncovered the heterogeneity and dynamic nature of spherical HBV SVPs, emphasizing the essential role of lipid-protein interactions in maintaining particle stability. In this review, recent progress in understanding the molecular architecture of HBV SVPs is consolidated, focusing on their symmetry, lipid organization, and disassembly-reassembly dynamics. High-resolution structural models reveal unique lipid arrangements that stabilize hydrophobic residues, preserve antigenicity, and contribute to SVP functionality. These findings highlight the significance of hydrophobic interactions and lipid-protein dynamics in HBV SVP assembly and stability, offering valuable perspectives for optimizing SVP-based vaccine platforms and therapeutic strategies.

In practical engineering applications, the vibration is often generated in various directions and can be harmful to the engineering equipment. Thus, it is necessary to develop vibration isolators that can reduce vibration in multiple directions. In this paper, we propose a planar two-dimensional vibration isolator based on compliant mechanisms. The proposed mechanism consists of two negative stiffness-compliant modules and two positive stiffness-compliant modules, which leads to the quasi-zero stiffness (QZS) property in the mechanism. The dynamic model is established by using the third-order Taylor expansion and the harmonic balance method. Based on the dynamic model, the influence of different parameters on the displacement transmissibility is discussed, including damping ratio, system stiffness, and excitation amplitude. Finally, we conducted the vibration isolation experiments and obtained the displacement transmissibility of the isolator. The results verify that the proposed isolator has good isolation performance for low-frequency vibration., Competing Interests: The authors declare no conflicts of interest.

This review provides a comprehensive overview of the current understanding of rice resistance to the brown planthopper (BPH), a major pest that poses significant threats to rice production through direct feeding damage and by transmitting viruses such as Rice grassy stunt virus (RGSV) and Rice ragged stunt virus (RRSV). We highlight the emergence of various BPH biotypes that have overcome specific resistance genes in rice. Advances in genetic mapping and cloning have identified 17 BPH resistance genes, classified into typical R genes encoding nucleotide-binding leucine-rich repeat (NLR) proteins and atypical R genes such as lectin receptor kinases and proteins affecting cell wall composition. The molecular mechanisms of these genes involve the activation of plant defense pathways mediated by phytohormones like jasmonic acid (JA), salicylic acid (SA), and ethylene, as well as the production of defensive metabolites. We also examine the complex interactions between BPH salivary proteins and rice defense responses, noting how salivary effectors can both suppress and trigger plant immunity. The development and improvement of BPH-resistant rice varieties through conventional breeding and molecular marker-assisted selection are discussed, including strategies like gene pyramiding to enhance resistance durability. Finally, we outline the challenges and future directions in breeding for durable BPH resistance, emphasizing the need for continued research on resistance mechanisms and the development of rice varieties with broad-spectrum and long-lasting resistance.

Blockchain technology can be used in the IoT to ensure the data privacy collected by sensors. In blockchain systems, consensus mechanisms are a key technology for maintaining data consistency and correctness. Among the various consensus protocols, asynchronous Byzantine consensus protocols offer strong robustness as they do not rely on any network timing assumptions during design. As a result, these protocols have become a research hotspot in the field of blockchain. Based on different structural design approaches, asynchronous Byzantine consensus protocols can be divided into two categories: protocols based on the DAG structure and protocols based on the ACS structure. The paper describes their principles and summarizes the related research works. The advantages and disadvantages of the protocols are also compared and analyzed. At the end of the paper, future research directions are identified.

The accuracy of the control model is essential for the effectiveness of model-based control methods. However, factors such as model simplification, parameter variations, and environmental noise can introduce inaccuracies in vehicle state descriptions, thereby compromising the precision of path tracking. This study introduces data-driven enhancements for an MPC-based path tracking controller in autonomous vehicles (DD-PTC). The approach consists of two parts: firstly, Kolmogorov-Arnold Networks (KANs) are utilized to estimate tire lateral forces and correct tire cornering stiffness, thereby establishing a dynamic predictive model. Secondly, Gaussian Process Regression (GPR) is deployed to accurately capture the unmodeled dynamics of the vehicle to form a comprehensive control model. This enhanced model allows for precise path tracking through steering control. The superiority of DD-PTC is confirmed through extensive testing on the Simulink-CarSim simulation platform, where it consistently surpasses normal MPC and Linear Quadratic Regulator (LQR) strategies, especially in minimizing lateral distance errors under challenging driving conditions.

Objectives : B7 homolog 3 protein (B7-H3, also known as CD276) is a member of the B7 family that has been found to be associated with the growth and progression of a variety of tumors, but no pan-cancer evaluations of CD276 have been performed so far. In this study, we aimed to perform a pan-cancer analysis of the oncogenic role of CD276 in human tumors; Methods : We used a series of databases to perform a pan-cancer analysis of CD276, including the expression level of CD276 in pan-cancer and its relationship to tumor progression, patient survival duration, the immune cell infiltration within the tumor, and the potential signaling pathways and molecular mechanisms associated with CD276; Results : We found that CD276 was a potential biomarker for the prognosis of most cancers. The high expression of CD276 was associated with tumor progression, leading to poor survival. Notably, the up-regulation of CD276 expression in tumors increased the tumor infiltration of cancer-associated fibroblasts (CAFs) and myeloid-derived suppressor cells (MDSCs) and decreased the CD8+ T cells; Conclusions : Our study demonstrates that CD276 might promote tumor progression via the promotion of an immunosuppressive microenvironment.

The most promising material for uranium extraction from saltwater is generally acknowledged to be fibrous adsorbents. An irradiation-modified anti-biofouling ultra-high-molecular-weight polyethylene (UHMWPE- g -PGAO) fibrous adsorbent with a hyperbranched structure was synthesized. It exhibited adsorption capacities of 314.8 mg-U/g-Ads in aqueous solution and 4.04 mg-U/g-Ads in simulated seawater over a 28-day period. The ultra-high-molecular-weight polyethylene (UHMWPE) fiber was functionalized by covalently linking hyperbranched polyethyleneimine (h-PEI) to facilitate the migration of uranyl ions within the fibers. Additionally, amidoxime and quaternary ammonium groups were immobilized on the fiber surface to enhance uranium affinity and provide defense against marine organisms. This three-dimensional design of amidoxime and h-PEI-modified UHMWPE fiber retained more than 91.0% of its maximum adsorption capacity after undergoing five adsorption-desorption cycles. The UHMWPE- g -PGAO adsorbent exhibits significant antibacterial activity against Escherichia coli and Staphylococcus aureus , achieving an inactivation efficiency of over 99.9%. It is proved to be an innovative fiber adsorbent for uranium extraction from seawater for its biofouling resistance, robustness, and reusability.

In contemporary medical practice, perioperative visual guidance technology has become a critical element in enhancing the precision and safety of surgical procedures. This study provides a comprehensive review of the advancements in the application of Augmented Reality (AR) technology for perioperative visual guidance. This review begins with a retrospective look at the evolution of AR technology, including its initial applications in neurosurgery. It then delves into the technical challenges that AR faces in areas such as image processing, 3D reconstruction, spatial localization, and registration, underscoring the importance of improving the accuracy of AR systems and ensuring their stability and consistency in clinical use. Finally, the review looks forward to how AR technology could be further facilitated in medical applications with the integration of cutting-edge technologies like skin electronic devices and how the incorporation of machine learning could significantly enhance the accuracy of AR visual systems. As technology continues to advance, there is ample reason to believe that AR will be seamlessly integrated into medical practice, ushering the healthcare field into a new "Golden Age".

The search for efficient, environmentally friendly adsorbents is critical for purifying dye wastewater. In this study, we produced a first-of-its-kind effective biomimetic amorphous calcium carbonate (BACC) using bacterial processes and evaluated its capacity to adsorb a hazardous organic cationic dye-methylene blue (MB). BACC can adsorb a maximum of 494.86 mg/g of MB, and this excellent adsorption performance was maintained during different solution temperature (10-55 °C) and broad pH (3-12) conditions. The favorable adsorption characteristics of BACC can be attributable to its hydrophobic property, porosity, electronegativity, and perfect dispersity in aqueous solution. During adsorption, MB can form Cl-Ca, S-O, N-Ca, and H-bonds on the surface of BACC. Since BACC has excellent resistance to adsorption interference in different water bodies and in real dye wastewater, and can also be effectively recycled six times, our study is an important step forward in dye wastewater treatment applications.

The permeation of tritium from secondary neutron source rods in nuclear power plants presents a significant and unavoidable safety concern both for internal equipment and the external environment. This study primarily explores two feasible strategies for tritium permeation barriers: coating stainless steel surfaces with tritium permeation barrier (TPB) materials and utilizing materials with excellent tritium absorption properties. Through external ion irradiation tests, a comparative analysis was conducted on the tritium permeation performance, morphology, and nanohardness changes in two tritium-resistant designs, specifically Cr 2 O 3 /Al 2 O 3 composite coatings and a zirconium-based tritium-absorbing material under varying irradiation doses. The results indicate that both approaches exhibit exceptional radiation resistance, maintaining an effective tritium permeation reduction factor (PRF) even after irradiation., Competing Interests: The authors declare no conflict of interest.

Coal seam water injection technology enables seam permeability enhancement and facilitates outburst risk reduction. This study investigated the microscale effects of water infiltration on coal and the evolution mechanisms of its mechanical properties. To this end, we systematically analyzed dynamic changes (such as mineral composition, pore structure, and mechanical performance) in coal soaked for various durations using X-ray diffraction, low-field nuclear magnetic resonance (NMR), and uniaxial compression testing. The results indicate: (1) the coal NMR T 2 spectrum displays three characteristic peaks, corresponding to rapid water absorption, uniform transition, and stabilization stages of soaking traditionally divided according to peak area variation trends. (2) The coal strength decreases with progressive soaking, influenced by water content, pore volume, mineral composition, etc. Its compressive strength and elastic modulus drop by 22.4% and 19.5%, respectively, compared to the initial values. (3) The expansion of clay minerals during immersion reduces average pore size. In contrast, quartz particle displacement, pore water movement, and soluble mineral dissolution increase pore volume, reducing the overall structure strength. (4) The dominant factors driving the degradation of mechanical properties vary across immersion stages, including water content and specific mineral concentration. This work offers new insights into how hydraulic technology alters coal seams, providing theoretical support for optimizing water injection strategies in the seam.

Newcastle disease virus (NDV), known as avian paramyxovirus-1, poses a significant threat to poultry production worldwide. Vaccination currently stands as the most effective strategy for Newcastle disease control. However, the mesogenic vaccine strain Mukteswar has been observed to evolve into a velogenic variant JS/7/05/Ch during poultry immunization. Here, we aimed to explore the mechanisms underlying virulence enhancement of the two viruses. Pathogenically, JS/7/05/Ch mediated stronger virulence and pathogenicity in vivo compared to Mukteswar. Comparative transcriptome analysis revealed 834 differentially expressed genes (DEGs), comprising 339 up-regulated and 495 down-regulated genes, in the spleen, and 716 DEGs, with 313 up-regulated and 403 down-regulated genes, in the thymus. Gene Ontology (GO) analysis indicated that these candidate targets primarily participated in cell and biological development, extracellular part and membrane composition, as well as receptor and binding activity. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis unveiled a substantial portion of candidate genes predominantly involved in cellular processes, environmental information processing, metabolism, and organismal systems. Additionally, five DEGs (TRAT1, JUP, LPAR4, CYB561A3, and CXCR5) were randomly identified through RNA-seq analysis and subsequently confirmed via quantitative real-time polymerase chain reaction (qRT-PCR). The findings revealed a marked up-regulation in the expression levels of these DEGs induced by JS/7/05/Ch compared to Mukteswar, with CYB561A3 and CXCR5 exhibiting significant increases. The findings corroborated the sequencing accuracy, offering promising research directions. Taken together, we comprehensively evaluated transcriptomic alterations in chicken immune organs infected by NDV strains of diverse virulence. This study establishes a basis and direction for NDV virulence research.

SiC particle reinforced aluminum matrix composites (SiCp/Al) are widely used in aviation, weaponry, and automobiles because of their excellent service performance. Wire electrical discharge machining (WEDM) regardless of workpiece hardness has become an alternative method for processing SiCp/Al composites. In this paper, the temperature distribution and the discharge crater size of the SiCp/Al composite are simulated by a thermophysical model during a single-pulse discharge process (SPDP) based on the random distribution of SiC particles. The material removal mechanism of the SiCp/Al composite during the multi-pulse discharge process (MPDP) is revealed, and the surface roughness ( Ra ) of the SiCp/Al composite is predicted during the MPDP. The thermophysical model simulation results during the MPDP and experimental characterization data indicate that the removal mechanism of SiCp/Al composite material consists of the melting and vaporization of the aluminum matrix, as well as the heat decomposition and shedding of silicon carbide particles. Pulse-on time ( T on ), pulse-off time ( T off ), and servo voltage ( SV ) have a great influence on surface roughness. The Ra increases with an increase in T on and SV , but decreases slightly with an increase in T off . Moreover, compared with experimental data, the relative error of Ra calculated from the thermophysical model is 0.47-7.54%. This means that the developed thermophysical model has a good application and promotion value for the WEDM of metal matrix composite material.

Service life of traditional steel bridge deck pavement is significantly shortened due to the failure of waterproof adhesion. To improve the interlayer bonding performance and extend its service life, polyurethane is proposed as a waterproof adhesion layer (WAL) for a steel bridge deck. This study aims to synthesize polyurethane WAL by free radical solution polymerization under different types and dosages of crosslinking agents as well as the mixing ratio of an acrylic co-blend. Tensile properties, water resistance, glass transition temperatures, thermal stability, and adhesive strength of the polyurethane binder are evaluated. The results demonstrate that polyurethane WAL yields desirable performance by using a hydroxyl molar ratio of 1/3 and an acrylic co-blend of 65%. Specifically, the tensile strength and breaking elongation of polyurethane WAL reach the maximum values of 6.466 MPa and 268.4%, respectively. The water absorption rate of polyurethane WAL is less than 4%. Glass transition temperatures of polyurethane WAL are between -80 °C and 60 °C, respectively. Polyurethane WAL features remarkable high- and low-temperature performance and thermal stability. Finally, adhesion strength between polyurethane WAL and the steel plate reaches up to 5.21 MPa. The outcome of this study facilitates the design and application of polyurethane waterproofing adhesion layers for steel bridge decks.

Neonicotinoid resistance is increasingly prevalent in the agricultural pest Myzus persicae . Lipids play a critical role in insect defense systems, but their contribution to insect neonicotinoid resistance is disregarded. We conducted metabolomics and transcriptomics studies on M. persicae thiacloprid-resistant (THG-R) and -susceptible (FFJ-S) populations. A total of 149 lipid metabolites were identified, with 90 upregulated and 59 downregulated in THG-R compared to in FFJ-S. Metabolites in the arachidonic acid (AA) pathway substantially varied between THG-R and FFJ-S. For example, arachidonic acid, (±)11-HETE, and prostaglandin B1 were significantly upregulated, while prostaglandin A1, tetranor-PGDM, 8,15-diHETE, and (±)11(12)-EET were significantly decreased in THG-R. Transcriptomics profiles and qPCR indicated that lipid metabolic enzymes, including fatty acid synthase (FAS), the elongase of very-long-chain fatty acids (ELO), fatty acid desaturase (FAD), and phospholipase (PL) genes, were not overexpressed in THG-R. Among the twelve thioesterase genes, only MpTHEM6a was significantly upregulated in THG-R. Knocking down the expression of MpTHEM6a in THG-R significantly increased the toxicity of the three neonicotinoids, reduced the lifespan of adults, and decreased the number of nonviable nymphs produced by female adults. The metabolites AA, (±)11-HETE, and prostaglandin B1 are potential biomarkers in neonicotinoid-resistant M. persicae . MpTHEM6a may become a potential target for combating neonicotinoid-resistant M. persicae .

As an indigenous species on the Tibetan Plateau, the yak is well adapted to the plateau hypoxic environment. The high-altitude hypoxia adaptation of the yak requires the adaptive reshaping of multiple tissues and organs, especially the lungs. To reveal the adaptive development of yak lungs under hypoxic stress at the tissue and molecular levels, we conducted histomorphological observations as well as transcriptomic and metabolomic studies of yak lungs at three ages (0.5, 2.5, and 4.5 years). The results showed that the lung tissue developed significantly with age. The mean alveolar area was higher ( p < 0.01) in 4.5 and 2.5-year-old yaks than in 0.5-year-old yaks. The percentage of elastic fibers, micro-arterial wall thickness, and micro-arterial area showed an increasing trend ( p < 0.01) from 0.5-year-old yaks to 2.5-year-old yaks and then to 4.5-year-old yaks. In addition, some critical differentially expressed genes related to angiogenesis ( MYC , EPHA2 , TNF ), fiber formation ( EREG ), smooth muscle proliferation ( HBEGF ), erythropoiesis ( SOCS3 ), and hypoxia response ( ZFP36 ) were identified. Some metabolites associated with these genes were also found simultaneously. These findings provide a deeper understanding of the molecular strategies underlying this species' extraordinary ability to survive normally in low-oxygen environments. In conclusion, the lungs of yaks undergo continuous adaptive development under hypoxic stress, and these findings are crucial for understanding the molecular mechanisms by which native species of the Tibetan Plateau survive in harsh environments.

Newcastle disease virus (NDV) poses a significant threat to the poultry industry, with the emergence of genotype VII NDV leading to extensive outbreaks and economic losses. Vaccination is the primary means of controlling NDV, but the presence of maternal antibodies (MDAs) can interfere with the immunological effect of live virus vaccines. Thus, we constructed a chimeric NDV live virus vaccine, LX-OAI4S, by replacing the extracellular regions of the F and HN genes of the NDV LX strain with the corresponding regions of the A-VII vaccine strain. The chimeric vaccine LX-OAI4S demonstrated high genetic stability, good safety, and strong reproductive capacity in chicken embryos. The LX-OAI4S vaccine induced rapid antibody production in specific pathogen-free (SPF) and commercial chickens via the intranasal and intraocular (IN/IO) routes, with hemagglutination inhibition (HI) antibody titers reaching 4.71 ± 1.03 log 2 at 7 days post-vaccination (dpv), significantly higher than those of the two classical vaccine strains La Sota and VG/GA. The LX-OAI4S vaccine group provided effective protection against the challenge of genotype VII NDV virulent strain JS2/06 and inhibited viral shedding. When administered via spray, the LX-OAI4S vaccine elicited high systemic immunity against NDV in both SPF and commercial chickens, effectively protecting against clinical disease and reducing viral shedding. The chickens were exposed to high-dose vaccine for spray vaccination, and no adverse reactions were observed after vaccination. Despite the presence of anti-NDV MDAs in chickens, the NDV-specific antibody titers were significantly greater in the vaccinated groups than in the unvaccinated group. The vaccine exhibited high immunogenicity and the potential to overcome maternal antibody interference. The LX-OAI4S vaccine is a promising candidate for an ND vaccine. Its administration via spray can effectively prevent the occurrence of ND, making it a valuable tool for the poultry industry.

An accurate panorama depth estimation result is crucial to risk perception in autonomous driving practice. In this paper, an innovative framework is presented to address the challenges of imperfect observation and projection fusion in panorama depth estimation, enabling the accurate capture of distances from surrounding images in driving scenarios. First, the Patch Filling method is proposed to alleviate the imperfect observation of panoramic depth in autonomous driving scenarios, which constructs a panoramic depth map based on the sparse distance data provided by the 3D point cloud. Then, in order to tackle the distortion challenge faced by outdoor panoramic images, a method for image context learning, ViT-Fuse, is proposed and specifically designed for equirectangular panoramic views. The experimental results show that the proposed ViT-Fuse reduces the estimation error by 9.15% on average in driving scenarios compared with the basic method and exhibits more robust and smoother results on the edge details of the depth estimation maps.

This study used hyperspectral remote sensing to rapidly, economically, and non-destructively determine the soil iron oxide content of the Dinosaur Valley annular tectonic region of Lufeng, Yunnan Province. The laboratory determined the iron oxide content and original spectral reflectance (OR) in 138 surface soil samples. We first subjected the OR data to Savizky-Golay smoothing, followed by four spectral transformations-continuum removal reflectance, reciprocal logarithm reflectance, standard normal variate reflectance, and first-order differential reflectance-which improved the signal-to-noise ratio of the spectral curves and highlighted the spectral features. Then, we combined the correlation coefficient method (CC), competitive adaptive reweighting algorithm, and Boruta algorithm to screen out the characteristic wavelength. From this, we constructed the linear partial least squares regression model, nonlinear random forest, and XGBoost machine learning algorithms. The results show that the CC-Boruta method can effectively remove any noise and irrelevant information to improve the model's accuracy and stability. The XGBoost nonlinear machine learning algorithm model better captures the complex nonlinear relationship between the spectra and iron oxide content, thus improving its accuracy. This provides a relevant reference for the rapid and accurate inversion of iron oxide content in soil using hyperspectral data.

Objective: Pedestrian detection is very important for the environment perception and safety action of intelligent robots and autonomous driving, and is the key to ensuring the safe action of intelligent robots and auto assisted driving., Methods: In response to the characteristics of pedestrian objects occupying a small image area, diverse poses, complex scenes and severe occlusion, this paper proposes an improved pedestrian object detection method based on the YOLOv7 model, which adopts the Convolutional Block Attention Module (CBAM) attention mechanism and Deformable ConvNets v2 (DCNv2) in the two Efficient Layer Aggregation Network (ELAN) modules of the backbone feature extraction network. In addition, the detection head is replaced with a Dynamic Head (DyHead) detector head with an attention mechanism; unnecessary background information around the pedestrian object is also effectively excluded, making the model learn more concentrated feature representations., Results: Compared with the original model, the log-average miss rate of the improved YOLOv7 model is significantly reduced in both the Citypersons dataset and the INRIA dataset., Conclusions: The improved YOLOv7 model proposed in this paper achieved good performance improvement in different pedestrian detection problems. The research in this paper has important reference significance for pedestrian detection in complex scenes such as small, occluded and overlapping objects.

Depositing a tritium permeation barrier on the surface of materials is a key method for reducing tritium permeability. During actual operational processes, the surface of the tritium permeation barrier may experience mechanical damage, such as spalling and scratches. The hydrogen permeability resistance of the coating will degrade due to such forms of mechanical damage. It is a significant engineering challenge to evaluate the impact of these damages on the coating's tritium resistance. In this experiment, the mechanical damage to the FeAl/Al 2 O 3 tritium permeation barrier on 316L stainless steel was simulated through scratching, debonding, and thermal shock. Subsequently, a hydrogen isotope gas drive permeation (GDP) test was conducted. The influence of the degree of mechanical damage on the coating's tritium permeation behavior was assessed and discussed. The results indicate that, under the same damage mechanism, the coating's tritium permeability resistance is positively correlated with the integrity of the coating. Additionally, the impact of scratches on the coating surface is more severe than that of other damage mechanisms.

The sensitivity of Tunnel Magnetoresistance (TMR) sensors is characterized by significant temperature drift and poor sensitivity drift repeatability, which severely impairs measurement accuracy. Conventional temperature compensation techniques are often hindered by low compensation precision, inadequate real-time performance, and an inability to effectively address the issue of poor repeatability in temperature drift characteristics. To overcome these challenges, this paper introduces a novel method for suppressing temperature drift in TMR sensors. In this method, an alternating reference magnetic field is applied to TMR sensors, and the output amplitude at the frequency of the reference magnetic field is calculated to compensate the sensitivity temperature drift in real time. Temperature characteristic tests were conducted in a non-magnetic temperature test chamber, and the results revealed that the proposed method significantly reduced the TMR sensitivity drift coefficient from 985.39 ppm/°C to 59.08 ppm/°C. Additionally, the repeatability of sensitivity temperature characteristic curves was enhanced, with a reduction in root mean square error from 0.84 to 0.21. This approach effectively mitigates temperature-induced sensitivity drift without necessitating the use of a temperature sensor, and has the advantages of real-time performance and repeatability, providing a new approach for the high-precision temperature drift suppression of TMR.

Background: Goat milk has gained global attention for its unique nutritional properties and potential health benefits. Advancements in functional genomic technologies have significantly progressed genetic research on milk composition traits in dairy goats., Results: This review summarizes various research methodologies applied in this field. Genome-wide association studies (GWAS) have identified genomic regions associated with major milk components, with the diacylglycerol acyltransferase 1 ( DGAT1 ) gene and casein gene cluster consistently linked to milk composition traits. Transcriptomics has revealed gene expression patterns in mammary tissue across lactation stages, while the role of non-coding RNAs (such as miRNAs and circRNAs) in regulating milk composition has been confirmed. Proteomic and metabolomic studies have not only helped us gain a more comprehensive understanding of goat milk composition characteristics but have also provided crucial support for the functional validation of genes related to milk components. The integration of multi-omics data has emerged as an effective strategy for elucidating complex regulatory networks from a systems biology perspective., Conclusions: Despite progress, challenges remain, including refining reference genomes, collecting large-scale phenotypic data, and conducting functional validations. Future research should focus on improving reference genomes, expanding study populations, investigating functional milk components, exploring epigenetic regulation and non-coding RNAs, and studying microbiome-host genome interactions. These efforts will inform more precise genomic and marker-assisted selection strategies, advancing genetic improvements in milk composition traits in dairy goats.

Recently, there has been a growing interest in the biocontrol activity of volatile organic compounds (VOCs) produced by microorganisms. This study specifically focuses on the effects of VOCs produced by the co-culture of Burkholderia vietnamiensis B418 and Trichoderma harzianum T11-W for the control of two phytopathogenic fungi, Botrytis cinerea and Fusarium oxysporum f. sp. cucumerium Owen. The antagonistic activity of VOCs released in mono- and co-culture modes was evaluated by inhibition assays on a Petri dish and in detached fruit experiments, with the co-culture demonstrating significantly higher inhibitory effects on the phytopathogens on both the plates and fruits compared with the mono-cultures. Metabolomic profiles of VOCs were conducted using the solid-liquid microextraction technique, revealing 341 compounds with significant changes in their production during the co-culture. Among these compounds, linalool, dimethyl trisulfide, dimethyl disulfide, geranylacetone, 2-phenylethanol, and acetophenone were identified as having strong antagonistic activity through a standard inhibition assay. These key compounds were found to be related to the improved inhibitory effect of the B418 and T11-W co-culture. Overall, the results suggest that VOCs produced by the co-culture of B. vietnamiensis B418 and T. harzianum T11-W possess great potential in biological control.

Contrast-induced acute kidney injury (CIAKI) is a common complication with limited treatments. Intermedin (IMD), a peptide belonging to the calcitonin gene-related peptide family, promotes vasodilation and endothelial stability, but its role in mitigating CIAKI remains unexplored. This study investigates the protective effects of IMD in CIAKI, focusing on its mechanisms, particularly the cAMP/Rac1 signaling pathway. Human umbilical vein endothelial cells (HUVECs) were treated with iohexol to simulate kidney injury in vitro. The protective effects of IMD were assessed using CCK8 assay, flow cytometry, ELISA, and Western blotting. A CIAKI rat model was utilized to evaluate renal peritubular capillary endothelial cell injury and renal function through histopathology, immunohistochemistry, immunofluorescence, Western blotting, and transmission electron microscopy. In vitro, IMD significantly enhanced HUVEC viability and mitigated iohexol-induced toxicity by preserving intercellular adhesion junctions and activating the cAMP/Rac1 pathway, with Rac1 inhibition attenuating these protective effects. In vivo, CIAKI caused severe damage to peritubular capillary endothelial cell junctions, impairing renal function. IMD treatment markedly improved renal function, an effect negated by Rac1 inhibition. IMD protects against renal injury in CIAKI by activating the cAMP/Rac1 pathway, preserving peritubular capillary endothelial integrity and alleviating acute renal injury from contrast media. These findings suggest that IMD has therapeutic potential in CIAKI and highlight the cAMP/Rac1 pathway as a promising target for preventing contrast-induced acute kidney injury in at-risk patients, ultimately improving clinical outcomes.

Mastitis is a common disease worldwide that affects the development of the dairy industry due to its high incidence and complex etiology. Precise regulation of cell death and survival plays a critical role in maintaining internal homeostasis, organ development, and immune function in organisms, and regulatory abnormalities are a common mechanism of various pathological changes. Recent research has shown that regulated cell death (RCD) plays a crucial role in mastitis. The development of drugs to treat cell death and survival abnormalities that can be widely used in mastitis treatment has important clinical significance. This paper will review the molecular mechanisms of apoptosis, autophagy, pyroptosis, ferroptosis, and necroptosis and their regulatory roles in mastitis to provide a new perspective for the targeted treatment of mastitis.

In the process of construction, pouring and vibrating concrete on existing reinforced structures is a necessary process. This paper presents an automatic vibration position detecting method based on the feature extraction of 3D lidar point clouds. Compared with the image-based method, this method has better anti-interference performance to light with reduced computational consumption. First, lidar scans are used to capture multiple frames of local steel bar point clouds. Then, the clouds are stitched by Normal Distribution Transform (NDT) for preliminary matching and Iterative Closest Point (ICP) for fine-matching. The Graph-Based Optimization (g2o) method further refines the precision of the 3D registration. Afterwards, the 3D point clouds are projected into a 2D image. Finally, the locations of concrete vibration points and concrete casting points are discerned through point cloud and image processing technologies. Experiments demonstrate that the proposed automatic method outperforms ICP and NDT algorithms, reducing the mean square error (MSE) by 11.5% and 11.37%, respectively. The maximum discrepancies in identifying concrete vibration points and concrete casting points are 0.059 ± 0.031 m and 0.089 ± 0.0493 m, respectively, fulfilling the requirement for concrete vibration detection.

To enhance the application of alkali-activated materials in mine filling, cemented tailings backfill was prepared using slag, fly ash, sodium silicate, and NaOH as primary constituents. The effects of the raw material type and dosage on the backfill were examined through a single-factor experiment. Additionally, response surface methodology (RSM) was utilized to optimize the mixing ratios of the backfill, with a focus on fluidity and compressive strength as key objectives. The evolution of backfill quality and compressive strength under the combined effects of dry-wet and freeze-thaw (DW-FT) cycles was analyzed. The hydration products, microstructure, and pore characteristics of the specimens were analyzed using X-ray diffraction (XRD), scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS), and nitrogen adsorption tests (NATs) across varying cycles. The results demonstrate that the optimal backfill composition includes 47.8% fly ash, 6.10% alkali equivalent, and a 1.44 sodium silicate modulus. The macroscopic behavior of the backfill under DW-FT coupling followed this progression: pore initiation → pore expansion → crack formation → crack propagation → structural damage. After a minor initial increase, the backfill strength steadily decreased. Microscopic analysis revealed that the decline in internal cementation products and the deterioration of pore structure were the primary causes of this strength reduction. Thus, the DW-FT coupling can cause significant erosion of the backfill. The technical solutions presented in this paper offer a reference for solid waste utilization and provide valuable insights into the durability of backfill under DW-FT coupling.

Cationic porous organic polymers have a unique advantage in removing radioactive iodine from the aqueous phase because iodine molecules exist mainly in the form of iodine-containing anions. However, halogen anions will inevitably be released into water during the ion-exchange process. Herein, we reported a novel and easy-to-construct zwitterionic hypercrosslinked polymer (7AIn-PiP)-containing cationic pyridinium-type group, uncharged pyridine-type group, pyrrole-type group, and even an electron-rich phenyl group, which in synergy effectively removed 94.2% (456 nm) of I 2 from saturated I 2 aqueous solution within 30 min, surpassing many reported iodine adsorbents. Moreover, an I 2 adsorption efficiency of ~95% can still be achieved after three cyclic evaluations, indicating a good recycling performance. More importantly, a unique dual 1,3-dipole was obtained and characterized by 1 H/ 13 C NMR, HRMS, and FTIR, correlating with the structure of 7AIn-PiP. In addition, the analysis of adsorption kinetics and the characterization of I 2 @7AIn-PiP indicate that the multiple binding sites simultaneously contribute to the high affinity towards iodine species by both physisorption and chemisorption. Furthermore, an interesting phenomenon of inducing the formation of HIO 2 in unsaturated I 2 aqueous solution was discovered and explained. Overall, this work is of great significance for both material and radiation protection science.

To explore the bending process and theory of the free-boundary aerodynamic film forming method for curved detectors, this study integrates practical forming structures with theoretical analysis and establishes a simulation model to investigate stress, strain, and morphological changes during bending. The analysis indicates that the shift from "projection" to "wrapping" in forming theory is due to the release of boundary degrees of freedom. The forming process can be summarized as the mold's arc characteristics, originating from the chip's corners, gradually replacing the chip's rectangular characteristics along the diagonal, resulting in corresponding stress and strain changes. The "wrapping" bending theory of this method has significant advantages over traditional methods and represents a crucial direction for achieving higher curvature in the future. However, this study found that the use of film pressure can only inhibit out-of-plane deformation to a certain extent, and the buckling phenomenon will still occur when the thinner chip is bent. It prevents the use of thinner chips in the thinning-bending method, so avoiding out-of-plane deformation during the molding process is the direction that needs to be broken in the future.

Background: As large language models continue to expand in size and diversity, their substantial potential and the relevance of their applications are increasingly being acknowledged. The rapid advancement of these models also holds profound implications for the long-term design of stimulus-responsive materials used in drug delivery. Methods: The large model used Hugging Face's Transformers package with BigBird, Gemma, and GPT NeoX architectures. Pre-training used the PubChem dataset, and fine-tuning used QM7b. Chemist instruction training was based on Direct Preference Optimization. Drug Likeness, Synthetic Accessibility, and PageRank Scores were used to filter molecules. All computational chemistry simulations were performed using ORCA and Time-Dependent Density-Functional Theory. Results: To optimize large models for extensive dataset processing and comprehensive learning akin to a chemist's intuition, the integration of deeper chemical insights is imperative. Our study initially compared the performance of BigBird, Gemma, GPT NeoX, and others, specifically focusing on the design of photoresponsive drug delivery molecules. We gathered excitation energy data through computational chemistry tools and further investigated light-driven isomerization reactions as a critical mechanism in drug delivery. Additionally, we explored the effectiveness of incorporating human feedback into reinforcement learning to imbue large models with chemical intuition, enhancing their understanding of relationships involving -N=N- groups in the photoisomerization transitions of photoresponsive molecules. Conclusions: We implemented an efficient design process based on structural knowledge and data, driven by large language model technology, to obtain a candidate dataset of specific photoswitchable molecules. However, the lack of specialized domain datasets remains a challenge for maximizing model performance.