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With the ongoing advancements and innovations of electronic device, the demand for low-melting-point solder is rising, especially for flexible printed electronics. The service environments of electronic device are complex and diverse, which have raised concerns regarding long-term service reliability in solder materials. In this work, a novel type of 30In33Sn25Bi4AgxZn low-melting-point alloy solder was proposed. The effects of Zn content on the corrosion resistance and electrochemical migration (ECM) resistance of the alloy system were investigated through electrochemical test and water drop test (WDT). The passivation film on the surface and the amorphous region of InSnBiAg8Zn alloys effectively inhibits the anodic dissolution of Zn atoms, improves the corrosion resistance of the alloy and delays the occurrence of electrochemical migration failure. The microscopic mechanism of ECM was revealed by conducting in-situ observations of the migration process of the alloy solder and analyzing the composition and morphology of the anode alloy and the migration products.

Abstract Objectives Parkinson disease (PD) is the third leading cause of mortality among middle‐aged and older individuals in China. This study aimed to explore the trends and distribution features of PD mortality in China from 2013 to 2021 and make predictions for the next few decades. Methods Relevant data were obtained from the Chinese Center for Disease Control and Prevention Disease Surveillance Point system. The joinpoint regression model was used to evaluate trends. The R software was used to predict future trends. Results Age‐standardized mortality rate (ASMR) of PD increased from 0.59 per 100,000 individuals to 1.22 per 100,000 individuals from 2013 to 2021, with an average annual percent change (AAPC) of 9.50 (95% CI: 8.24–10.78). The all‐age ASMR of PD were higher in male individuals than in female individuals, and ASMR increased with age. The number of deaths and ASMR increased gradually from west to east and from rural to urban areas. Furthermore, ASMR is expected to increase to 2.66 per 100,000 individuals by 2040. Conclusions The heightened focus on the ASMR of PD among male individuals, urban areas, eastern China, and individuals aged ≥85 years has become a key determinant in further decreasing mortality, thereby exhibiting novel challenges to effective strategies for disease prevention and control.

Abstract Two-thirds of signaling hormones and one-third of approved drugs exert their effects by binding and modulating the G protein-coupled receptors (GPCRs) activation. While the activation mechanism for monomeric GPCRs has been well-established, little is known about GPCRs in dimeric form. Here, by combining transition pathway generation, extensive atomistic simulation-based Markov state models, and experimental signaling assays, we reveal an asymmetric, stepwise millisecond allosteric activation mechanism for the metabotropic glutamate receptor subtype 5 receptor (mGlu5), an obligate dimeric class C GPCR. The dynamic picture is presented that agonist binding induces dimeric ectodomains compaction, amplified by the precise association of the cysteine-rich domains, ultimately loosely bringing the intracellular 7-transmembrane (7TM) domains into proximity and establishing an asymmetric TM6-TM6 interface. The active inter-domain interface enhances their intra-domain flexibility, triggering the activation of micro-switches crucial for downstream signal transduction. Furthermore, we show that the positive allosteric modulator stabilizes both the active inter-domain 7TM interface and an open, extended intra-domain ICL2 conformation. This stabilization leads to the formation of a pseudo-cavity composed of the ICL2, ICL3, TM3, and C-terminus, which facilitates G protein coordination. Our strategy may be generalizable for characterizing millisecond events in other allosteric systems.

Abstract Maltotetraose amylase (Mta) catalyzes the hydrolysis of amylaceous polysaccharides into maltotetraose, which is an important functional sugar used in the food industry. However, the lack of efficient expression systems for recombinant Mta has hindered its scale-up production and application. In this study, a codon-optimized mta gene from Pseudomonas saccharophila was efficiently produced in Bacillus subtilis by optimizing the regulatory elements. First, a plasmid library containing 173 different signal peptide sequences placed upstream of mta gene was constructed, and transformed into B. subtilis strain WB800N(amyEΔ1) for high-throughput screening. The signal peptide yhcR was found to significantly enhance the secretion of Mta, reaching an activity of 75.4 U/mL in the culture medium. After optimization of the promoters, the Mta activity was further increased to 100.3 U/mL using a dual-promoter PHpaIIPamyE. Finally, the carbon sources and nitrogen sources for recombinant Mta production were optimized, yielding a highest Mta activity of 288.9 U/mL under the optimal culture conditions. The crude enzyme solution containing recombinant Mta produced a highest maltotetraose yield of 70.3% with 200 g/L of maltodextrin as the substrate. Therefore, the present study have demonstrated a high yield of Mta produced in B. subtilis, laying the foundation for large-scale Mta production and application.

Abstract Infections caused by pathogenic Escherichia coli are a serious threat to human health, while conventional antibiotic susceptibility tests (AST) have a long turn-around time, and rapid antibiotic susceptibility methods are urgently needed to save lives in the clinic, reduce antibiotic misuse and prevent emergence of antibiotic-resistant bacteria. We optimized and validated the feasibility of a novel rapid AST based on SYBR Green I and Propidium Iodide (SGPI-AST) for E. coli drug susceptibility test. A total of 112 clinical isolates of E. coli were collected and four antibiotics (ceftriaxone, cefoxitin, imipenem, meropenem) were selected for testing. Bacterial survival rate of E. coli was remarkably linearly correlated with S value at different OD600 values. After optimizing the antibiotic concentrations, the sensitivity and specificity of SGPI-AST reached 100%/100%, 97.8%/100%, 100%/100% and 98.4%/99% for ceftriaxone, cefoxitin, imipenem and meropenem, respectively, and the corresponding concordances of the SGPI-AST with conventional AST were 1.000, 0.980, 1.000 and 0.979, respectively. The SGPI-AST can rapidly and accurately determine the susceptibility of E. coli clinical isolates to multiple antibiotics in 60 min, and has the potential to be applied to guide the precise selection of antibiotics for clinical management of infections caused by pathogenic E. coli.

Walking is the primary travel mode for daily errands, leisure, and accessing local services, particularly for most seniors. Sufficient and diverse facilities within walking distance help improve seniors’ well-being. Countries today face the challenge of providing enough facilities for more seniors and adopt some possible solutions, such as China’s 15-minute community life circle. Focused on Jiande, a medium-sized city in southeast China, we propose an assessment framework with three dimensions: availability, diversity, and balance among medical, living, and leisure facilities. Using GIS network analysis, this study reveals disparities in facility provision at the household-level between earlier and newer developed urban areas, which are closely related to geographical factors and gated communities. This is common in Chinese cities, suggesting the cumulative effects of urban development sequences. To alleviate and prevent serious service inequity, we propose the following two strategies to achieve an equally walkable city: increasing landscape services to overcome geographical obstacles and implementing open-gated community strategies. Furthermore, the limitations of relying solely on big data to calculate walking routes were noted. This diagnostic framework for assessing city environments for seniors is straightforward yet comprehensive and potentially promotes cooperation between planning professionals, policymakers, and the public.

Abstract Drawing from (Dörnyei’s, The Psychology of the language learner: Individual differences in second language acquisition, 2005) L2 Motivational Self System, this case study delved into the L2 learning motivations of liberal arts and science English majors at a transnational university in China, where English Medium Instruction (EMI) is prevalent. The study aimed to uncover how the EMI educational setting, alongside disciplinary backgrounds, shapes students' motivational landscapes. Utilising a mixed-methods approach, a 4-point Likert scale questionnaire was first administered to 182 students, followed by semi-structured interviews with six purposively selected participants to ensure a representation of diverse perspectives. Quantitative data were analysed using descriptive statistics and an independent samples t-test to pinpoint motivational differences between the two groups, with Cohen’s d effect size test further elucidating the significance of these differences. Thematic analysis of qualitative data provided a deeper layer of insight, which, when cross-examined with quantitative results, revealed a nuanced understanding of motivational dynamics. Key findings highlighted that both student groups were driven by factors such as ideal L2 self, ought-to L2 self, international posture, and instrumentality. However, within the EMI context, liberal arts students exhibited heightened sensitivity to their ought-to L2 selves, language anxiety, and teacher influence compared to their science counterparts (p 0.8). These distinctions underscore the EMI context's role in modulating motivational profiles, particularly accentuating certain motivational factors among liberal arts students. In light of these EMI-mediated motivational nuances, the study proposes several educational implications, including enhancing teachers’ professional development training, integrating English learning in EMI programmes with students’ aspirations, and fostering intercultural interactions to enrich students’ language and cultural experiences.

Based on experiments and first-principles calculations, the microstructures and mechanical properties of as-cast and solution treated Mg-10Gd-4Y-xZn-0.6Zr (x = 0, 1, 2, wt.%) alloys are investigated. The transformation process of long-period stacking ordered (LPSO) structure during solidification and heat treatment and its effect on the mechanical properties of experimental alloys are discussed. Results reveal that the stacking faults and 18R LPSO phases appear in the as-cast Mg-10Gd-4Y-1Zn-0.6Zr and Mg-10Gd-4Y-2Zn-0.6Zr alloys, respectively. After solution treatment, the stacking faults and 18R LPSO phase transform into 14H LPSO phase. The Enthalpies of formation and reaction energy of 14H and 18R LPSO are calculated based on first-principles. Results show that the alloying ability of 18R is stronger than that of 14H. The reaction energies show that the 14H LPSO phase is more stable than the 18R LPSO. The elastic properties of the 14H and 18R LPSO phases are also evaluated by first-principles calculations, and the results are in good agreement with the experimental results. The precipitation of LPSO phase improves the tensile strength, yield strength and elongation of the alloy. After solution treatment, the Mg-10Gd-4Y-2Zn-0.6Zr alloy has the best mechanical properties, and its ultimate tensile strength and yield strength are 278.7 MPa and 196.4 MPa, respectively. The elongation of Mg-10Gd-4Y-2Zn-0.6Zr reaches 15.1, which is higher than that of Mg-10Gd-4Y0.6Zr alloy. The improving mechanism of elastic modulus by the LPSO phases and the influence on the alloy mechanical properties are also analyzed.

To address the demand for multilevel package, a low-melting-point high entropy alloy (HEA) solder was developed. It consists of 43In28Sn14Bi9Zn6Ag micro- and nano-particles with a melting point of about 62.80 °C. We obtained 43In28Sn14Bi9Zn6Ag nanoparticles by combining ultrasonic heating interaction with a ''hot shock'' process. Upon reflowing at 115 °C for 5 min, a Cu/Zn/Ag ternary intermetallic compound (IMC) formed at the interface between the solder and the copper substrate, leading to a shear strength of 40 MPa. The microstructure of this joint exhibits a complex composition with at least three phases, including Bi3In5 phase, Ag5Zn8 phase, and In0.2Sn0.8 solid solution. The stable Ag5Zn8 phase not only enhances the overall strength of the alloy matrix but also impedes the diffusion of In and Bi atoms, thereby preventing the segregation of the Bi3In5 phase. The high mixing entropy and pronounced lattice distortion in this high entropy alloy hinder the diffusion of elements within the solder matrix, mitigating the issue of excessive interfacial IMC growth. Consequently, the solder joints exhibit little degradation even after a high-temperature aging test. This high-entropy alloy solder has promising potential for multi-level chip stacking in 3D packaging.

Heat treatment of Mg10Gd-4Y-xZn-0.6Zr (x = 0, 1, 2 wt%) alloys has been optimized based on thermodynamic calculations and experiments. The phase transformations during the heat treatment and their effect on the mechanical properties of the alloys were discussed. Using thermodynamic calculations, three solution treatment temperatures of 475 °C, 500 °C, and 525 °C were determined, and the phase transformation under these temperatures were calculated and characterized, the results aligned well with experimental results. The optimal solution treatment technology was determined to be 500 °C for 18 h. After solution treatment, experimental alloys were subject to isothermal aging at 225 °C, the peak aging time for the experimental alloys was established. The microstructure under peak-aged state of the alloy was characterized, revealing a co-existed β’ and β1 phases. The GWZ1041K alloy, after peak aging treatment, exhibited optimal mechanical properties, with a tensile strength, yield strength, and elongation of 392.3 MPa, 249.3 MPa, and 5.7%, respectively. The study further analyzed the reasons for the microstructure transformation during the heat treatment and their influence on mechanical properties.

Tailoring the phase constitutions of the interfacial reaction layers under the assistance of ultrasonic vibration is a convenient method to fabricate high-strength Al/Cu brazing joints. In this study, 1060-Al and T2-Cu dissimilar metals were ultrasonically brazed with Zn-3Al (wt. %) filler metals. Effects of ultrasonic brazing time on the microstructure and mechanical properties of joints were investigated. Results showed that the CuZn5 intermetallic compound (IMC) layer and Cu-based diffusion layer were created on the Cu substrate surface in the joint ultrasonically brazed at 400 ℃ for 2 s. However, the CuZn5 IMC layer was gradually transformed into a thin Al4.2Cu3.2Zn0.7 IMC layer by increasing the ultrasonic vibration time to 15 s. A well-matched coherent interface was formed between the Al4.2Cu3.2Zn0.7 ternary phase and the Cu-based diffusion layer. The phase transition of the Cu-side interfacial layer correlated closely with the acoustic cavitations induced super-saturation regions near the Cu substrate surface. The measured tensile strength of the Al/Zn-3Al/Cu joint ultrasonically brazed for 15 s was 89.3 MPa, which was approximately 2.5 times higher than that brazed for 2 s, and the tensile failure mainly occurred at the interface between the Al4.2Cu3.2Zn0.7 layer and the Cu-based diffusion layer.

Hydrogen energy, due to its clean and efficient nature, has shown great potential during the current transition period in the shipbuilding industry. However, the application of hydrogen energy in ship energy systems is influenced by variations in operational load and the integration of new energy sources during actual navigation. To address these issues, this paper focuses on optimizing and scheduling the operation of ships under various navigation conditions, considering the distributed nature of hydrogen energy. System simulations were conducted to model the photovoltaic (PV), proton exchange membrane fuel cells (PEMFCs), lithium batteries (LIBs), electrolytic cells (ECs), and energy storage modules of yacht energy systems. Component boundaries and objective functions were set, and two cases (excess photovoltaic state and constant power state) were designed to optimize and regulate the energy balance of hydrogen-powered yachts, enhancing their comprehensive utilization of renewable energy. By comparing the changes in ship energy under the two cases, it was concluded that case 1 ensures the maximum utilization of renewable energy. When photovoltaic power generation is insufficient, the PEMFC and LIB in the system provide the required power to achieve a supply-demand balance. Moreover, when PV power generation is sufficient, hydrogen energy is used to store renewable energy. The optimization method designed in this study can, to some extent, maximize the application of renewable energy in new energy yachts, ensuring the efficiency of the comprehensive energy system of new energy yachts, reducing emissions, and improving the sustainability and economic efficiency of the ships.

ABSTRACT Metabolism in host cells can be modulated after viral infection, favoring viral survival or clearance. Here, we report that lipid droplet (LD) synthesis in host cells can be modulated by yin yang 1 (YY1) after porcine reproductive and respiratory syndrome virus (PRRSV) infection, resulting in active antiviral activity. As a ubiquitously distributed transcription factor, there was increased expression of YY1 upon PRRSV infection both in vitro and in vivo. YY1 silencing promoted the replication of PRRSV, whereas YY1 overexpression inhibited PRRSV replication. PRRSV infection led to a marked increase in LDs, while YY1 knockout inhibited LD synthesis, and YY1 overexpression enhanced LD accumulation, indicating that YY1 reprograms PRRSV infection-induced intracellular LD synthesis. We also showed that the viral components do not colocalize with LDs during PRRSV infection, and the effect of exogenously induced LD synthesis on PRRSV replication is nearly lethal. Moreover, we demonstrated that YY1 affects the synthesis of LDs by regulating the expression of lipid metabolism genes. YY1 negatively regulates the expression of fatty acid synthase (FASN) to weaken the fatty acid synthesis pathway and positively regulates the expression of peroxisome proliferator-activated receptor gamma (PPARγ) to promote the synthesis of LDs, thus inhibiting PRRSV replication. These novel findings indicate that YY1 plays a crucial role in regulating PRRSV replication by reprogramming LD synthesis. Therefore, our study provides a novel mechanism of host resistance to PRRSV and suggests potential new antiviral strategies against PRRSV infection.IMPORTANCEPorcine reproductive and respiratory virus (PRRSV) has caused incalculable economic damage to the global pig industry since it was first discovered in the 1980s. However, conventional vaccines do not provide satisfactory protection. It is well known that viruses are parasitic pathogens, and the completion of their replication life cycle is highly dependent on host cells. A better understanding of host resistance to PRRSV infection is essential for developing safe and effective strategies to control PRRSV. Here, we report a crucial host antiviral molecule, yin yang 1 (YY1), which is induced to be expressed upon PRRSV infection and subsequently inhibits virus replication by reprogramming lipid droplet (LD) synthesis through transcriptional regulation. Our work provides a novel antiviral mechanism against PRRSV infection and suggests that targeting YY1 could be a new strategy for controlling PRRSV.

Background/Aims: At present, there are relatively few reports on the treatment consisting of transarterial chemoembolization (TACE) combined with lenvatinib, and there is no unified conclusion on the curative effect. The objective of this research was to assess the efficacy and safety of combining TACE with lenvatinib for the treatment of unresectable hepatocellular carcinoma (uHCC). Materials and Methods: This study was a retrospective analysis of the patient’s medical records. In this study, 249 patients (uHCC) in our hospital from 2020 to 2021 were divided into 2 groups, including the TACE-alone group (198 patients received TACE alone) and the TACE-LEN group (51 patients were treated with TACE combined with lenvatinib). According to the propensity score matching method, there were TACE-LEN group (51 patients) and TACE-alone group (51 patients). With the help of surgical experts, the overall survival (OS), progression-free survival (PFS), and tumor response (according to mRECIST) of the 2 groups were sorted and recorded, and then analyzed. Survival curves were established, the prognostic factors of OS and PFS were analyzed by univariate and multivariate analyses, and the independent prognostic factors were recorded. The adverse reactions of patients after treatment were recorded. Results: The 1-year and 2-year OS rates were 50.98% and 19.48% for the TACE-LEN group, 27.45% and 8.55% for the TACE-alone group (P = .042), respectively. The PFS of patients in the TACE-LEN group was also longer (1-year PFS rate: 25.49% vs. 11.76%, 2-year PFS rate: 19.17% vs. 5.88%; P = .0069). The disease control rate (68.63% vs. 49.10%, P = .044) of the TACE-LEN group was significantly higher. In the subgroup analysis, the OS of the TACE-LEN group was better than TACE-alone group in patients with Barcelona Clinic Liver Cancer stage C (1-year OS rate: 44.44% vs. 17.14%, 2-year OS rate: 8.67% vs. 0%; P = .009). Factor analysis concluded that serum alkaline phosphatase and treatment protocol (TACE-LEN vs. TACE) were independent influencing factors of OS. The most common treatment-related AEs included decreased albumin (n = 28, 54.9%), hypertension (n = 23, 45.1%), elevated aspartate transaminase (n = 21, 41.2%) and elevated total bilirubin (n = 18, 35.2%) in TACE-LEN group. Conclusion: Compared with TACE monotherapy, TACE combined with lenvatinib effectively prolonged the OS time with a controllable safety profile for patients with uHCC.

Abstract. Background:. Cerebrovascular disease (CVD) ranks among the foremost factors responsible for mortality on a global scale. The mortality patterns of CVDs and temporal trends in China need to be well-illustrated and updated. Methods:. We collected mortality data on patients with CVD from Chinese Center for Disease Control and Prevention's Disease Surveillance Points (CDC-DSP) system. The mortality of CVD in 2020 was described by age, sex, residence, and region. The temporal trend from 2013 to 2019 was evaluated using joinpoint regression, and estimated rates of decline were extrapolated until 2030 using time series models. Results:. In 2019, the age-standardized mortality in China (ASMRC) per 100,000 individuals was 113.2. The ASMRC for males (137.7/105) and rural areas (123.0/105) were both higher when stratified by gender and urban/rural residence. The central region had the highest mortality (126.5/105), the western region had a slightly lower mortality (123.5/105), and the eastern region had the lowest mortality (97.3/105). The age-specific mortality showed an accelerated upward trend from aged 55–59 years, with maximum mortality observed in individuals over 85 years of age. The age-standardized mortality of CVD decreased by 2.43% (95% confidence interval, 1.02–3.81%) annually from 2013 to 2019. Notably, the age-specific mortality of CVD increased from 2013 to 2019 for the age group of over 85 years. In 2020, both the absolute number of CVD cases and the crude mortality of CVD have increased compared to their values in 2019. The estimated total deaths due to CVD were estimated to reach 2.3 million in 2025 and 2.4 million in 2030. Conclusion:. The heightened focus on the burden of CVD among males, rural areas, the central and western of China, and individuals aged 75 years and above has emerged as a pivotal determinant in further decreasing mortalities, consequently presenting novel challenges to strategies for disease prevention and control.

Copper-based azide (Cu(N3)2 or CuN3, CA) chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years. However, the advantages of in-situ synthesis method, including small size and low dosage, bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips. The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability. In this work, Cu(N3)2 and CuN3 components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N3− concentration through spectrophotometry. The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied, ensuring the accuracy and reproducibility of test results. The optimized method is linear in range from 1.0–25.0 mg/L, with a correlation coefficient R2 = 0.9998, which meets the requirements of CA chips with a milligram-level content test. Compared with the existing ICP method, component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy. Moreover, as its application in miniaturized explosive systems, the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied. This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

Al/Ni reactive multilayer foil (RMF) possesses excellent comprehensive properties as a promising substitute for traditional Cu bridge. A theoretical resistivity model of Al/Ni RMF was developed to guide the optimization of EFIs. Al/Ni RMF with different bilayer thicknesses and bridge dimensions were prepared by MEMS technology and electrical explosion tests were carried out. According to physical and chemical reactions in bridge, the electrical explosion process was divided into 5 stages: heating of condensed bridge, vaporization and diffusion of Al layers, intermetallic combination reaction, intrinsic explosion, ionization of metal gases, which are obviously shown in measured voltage curve. Effects of interface and grain boundary scattering on the resistivity of film metal were considered. Focusing on variations of substance and state, the resistivity was developed as a function of temperature at each stage. Electrical explosion curves were calculated by this model at different bilayer thicknesses, bridge dimensions and capacitor voltages, which showed an excellent agreement with experimental ones.

ObjectiveWhite matter hyperintensity (WMH) in patients with cerebral small vessel disease (CSVD) is strongly associated with cognitive impairment. However, the severity of WMH does not coincide fully with cognitive impairment. This study aims to explore the differences in the dynamic functional network connectivity (dFNC) of WMH with cognitively matched and mismatched patients, to better understand the underlying mechanisms from a quantitative perspective.MethodsThe resting-state functional magnetic resonance imaging (rs-fMRI) and cognitive function scale assessment of the patients were acquired. Preprocessing of the rs-fMRI data was performed, and this was followed by dFNC analysis to obtain the dFNC metrics. Compared the dFNC and dFNC metrics within different states between mismatch and match group, we analyzed the correlation between dFNC metrics and cognitive function. Finally, to analyze the reasons for the differences between the mismatch and match groups, the CSVD imaging features of each patient were quantified with the assistance of the uAI Discover system.ResultsThe 149 CSVD patients included 20 cases of “Type I mismatch,” 51 cases of Type I match, 38 cases of “Type II mismatch,” and 40 cases of “Type II match.” Using dFNC analysis, we found that the fraction time (FT) and mean dwell time (MDT) of State 2 differed significantly between “Type I match” and “Type I mismatch”; the FT of States 1 and 4 differed significantly between “Type II match” and “Type II mismatch.” Correlation analysis revealed that dFNC metrics in CSVD patients correlated with executive function and information processing speed among the various cognitive functions. Through quantitative analysis, we found that the number of perivascular spaces and bilateral medial temporal lobe atrophy (MTA) scores differed significantly between “Type I match” and “Type I mismatch,” while the left MTA score differed between “Type II match” and “Type II mismatch.”ConclusionDifferent mechanisms were implicated in these two types of mismatch: Type I affected higher-order networks, and may be related to the number of perivascular spaces and brain atrophy, whereas Type II affected the primary networks, and may be related to brain atrophy and the years of education.

Cities are increasingly vital in global carbon mitigation efforts, yet few have specifically tailored carbon neutrality pathways. Furthermore, out-of-boundary indirect greenhouse gas (GHG) emissions, aside from those related to electricity and heat imports, are often overlooked in existing pathways, despite their significance in comprehensive carbon mitigation strategies. Addressing this gap, here we introduce an integrated analysis framework focusing on both production and consumption-related GHG emissions. Applied to Wuyishan, a service-oriented city in Southern China, this framework provides a holistic view of a city's carbon neutrality pathway, from a full-scope GHG emission perspective. The findings reveal the equal importance of carbon reduction within and outside the city's boundaries, with out-of-boundary emissions accounting for 42% of Wuyishan's present total GHG emissions. This insight highlights the necessity of including these external factors in GHG accounting and mitigation strategy development. This framework serves as a practical tool for cities, particularly in developing countries, to craft effective carbon neutrality roadmaps that encompass the full spectrum of GHG emissions.

Cobalt has emerged as a vital material in 10 nm technology for localized interconnect layers, potentially offering a compelling alternative to Cu-based interconnects. In this study, we subjected the contamination arising from the presence of cobalt atoms in silicon to comprehensive investigation, employing electron transmission electron microscopy (TEM) observations in conjunction with first-principles calculations. The results show that a dense CoSi layer with a thickness of a few nanometers is formed at the interface of cobalt and Si. The CoSi layer blocks the diffusion of Co atoms into Si. This is due to the semiconducting nature of the covalent bond formed between Co and Si, leading to the emergence of a forbidden zone at the Co/CoSi interface. The diffusion of Co into CoSi is governed by the atomic exchange mechanism, however, the local distortion of the periodic atomic potential due to the presence of the forbidden zone at the Co/CoSi interface hinders the diffusion of Co into Si. Therefore, the deposition of a Co metal layer on a Si chip does not require an additional barrier layer.

Background Despite studies confirming that patients with inflammatory bowel disease (IBD) present with dyslipidaemia, the associations between IBD and the serum lipid profile have not been determined. The present study aimed to investigate the causal relationship between the serum lipid profile and IBD risk and elucidate the nature of the interactions between them.Methods Two-sample Mendelian randomisation (MR) analysis was performed to investigate the causal links between total cholesterol (TC), total triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A (Apo A), apolipoprotein B (Apo B) and lipoprotein (a) (Lp(a)) and IBD. The study was carried out using the R TwoSampleMR and Mendelian randomisation packages.Results All MR methods, including the weighted median, weighted mode, inverse-variance weighted model, MR-PRESSO, contamination mixture and MR Egger, supported a null causal relationship between TG, TC, HDL-C, LDL-C, Apo A, Apo B and Lp(a) and between IBD, Crohn’s disease and ulcerative colitis. Null causal effects of lipid indices on IBD were validated through independent genome-wide association studies (GWAS), indicating that the findings are robust.Conclusion Our findings suggest that none of the seven lipid indices may be a potential risk factor for the onset of IBD. However, additional research is needed since our MR analyses cannot assess the potential non-linear causal relationship between serum lipids and IBD.

Abstract Robust anti‐counterfeiting techniques aim for easy identification while remaining difficult to forge, especially for high‐value items such as currency and passports. However, many existing anti‐counterfeiting techniques rely on deterministic processes, resulting in loopholes for duplication and counterfeiting. Therefore, achieving high‐level encryption and easy authentication through conventional anti‐counterfeiting techniques has remained a significant challenge. To address this, this work proposes a solution that combined fluorescence and structural colors, creating a physically unclonable multiplex encryption system (PUMES). In this study, the physicochemical properties of colloidal photonic inks are systematically adjusted to construct a comprehensive printing phase diagram, revealing the printable region. Furthermore, the brightness and color saturation of inkjet‐printed colloidal photonic crystal structural colors are optimized by controlling the substrate's hydrophobicity, printed droplet volume, and the addition of noble metals. Finally, fluorescence is incorporated to build PUMES, including macroscopic fluorescence and structural color patterns, as well as microscopic physically unclonable fluorescence patterns. The PUMES with intrinsic randomness and high encoding capacity are authenticated by a deep learning algorithm, which proved to be reliable and efficient under various observation conditions. This approach can provide easy identification and formidable resistance against counterfeiting, making it highly promising for the next‐generation anti‐counterfeiting of currency and passports.

The rapid development of wireless communication systems demands extremely high reliability in transmission links. However, non-ideal characteristics of RF links, such as carrier frequency offset (CFO) and IQ mismatch (IQM), can lead to RF impairments, severely affecting system performance. Advanced signal processing techniques are indispensable to mitigate the non-ideal characteristics of RF links. Within signal processing, synchronization issues, including CFO estimation schemes for frequency synchronization, should be prioritized. However, the traditional CFO estimation schemes are susceptible to interference from the harmonics caused by IQM, resulting in severe performance degradation. Therefore, based on the least squares (LS) interpolation method, we develop a CFO estimation scheme robust to IQM by using $2l _{0}+1$ ( $l _{0}\geqslant ~3$ ) discrete Fourier transform (DFT) coefficients. The proposed estimator combines a coarse estimation and a fine estimation. In the first stage, the peak position of the signal amplitude spectrum is detected to provide a rough frequency estimation. In the second stage (fine estimation), an LS equation relationship between the observation vector and the observation matrix is established with observed DFT samples and DFT rotation factors. The precise frequency is extracted using the LS principle from the equation, utilizing $2l _{0}+1$ ( $l _{0}\geqslant ~3$ ) DFT sample points. Because the IQM interference structure is considered in the equation, the proposed method can combat IQI. Test results based on the RF verification platform indicate that the proposed method improves accuracy by at least 20 dB at an input power of −45 dBm. Accuracy improves by at least 9 dB at an input power of −65 dBm. Complexity analysis shows that the proposed method increases by at most 10.74% compared to the traditional LS-based methods.

Abstract Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular property prediction, their applications, such as drug discovery and molecular dynamics (MD) simulation, have been hindered by insufficient utilization of geometric information and high computational costs. Here we propose an equivariant geometry-enhanced graph neural network called ViSNet, which elegantly extracts geometric features and efficiently models molecular structures with low computational costs. Our proposed ViSNet outperforms state-of-the-art approaches on multiple MD benchmarks, including MD17, revised MD17 and MD22, and achieves excellent chemical property prediction on QM9 and Molecule3D datasets. Furthermore, through a series of simulations and case studies, ViSNet can efficiently explore the conformational space and provide reasonable interpretability to map geometric representations to molecular structures.

Recently, deep learning has yielded transformative success across optics and photonics, especially in optical metrology. Deep neural networks (DNNs) with a fully convolutional architecture (e.g., U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks, such as fringe denoising, phase unwrapping, and fringe analysis. However, the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naïve, as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning practice. To this end, we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (LeFTP) module. By parameterizing conventional phase retrieval methods, the LeFTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples, while circumventing the requirement of collecting a large amount of high-quality data in supervised learning methods. Guided by the initial phase from LeFTP, the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end networks. Experimental results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval, exhibiting its excellent generalization to various unseen objects during training. The proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches, opening new avenues to achieve fast and accurate single-shot 3D imaging.

The high-order microring filter has been proposed for a larger free spectral range (FSR) compared with the single microring filter; therefore, it has great potential to be used in wavelength division multiplexing (WDM) systems. In this article, we have designed and fabricated a second-order microring filter made up of two rings connected in series with two Ti thermal heaters deposited above them. The large FSR of 56.8 nm is obtained by decreasing the difference of the radii between the two series rings, achieving similar FSRs to that of higher-order filters but with a simpler and more compact design. The average electrical tuning efficiencies of the two heaters are 0.186 nm/mW and 0.207 nm/mW, and the center wavelength of the filter can be tuned over the entire FSR with an applied electrical power of less than 40 mW.

Bacterial outer membrane vesicles (OMVs) contain a variety of chemical compounds and play significant roles in maintaining symbiotic relationships in a changing ocean, but little is known about their function, particularly in sponge larval development. During the growth of sponge Tedania sp., OMVs from Bacteroidetes species significantly promoted larval settlement, and Tenacibaculum mesophilum SP-7-OMVs were selected as a representative strain for further investigation. According to OMVs metabolomics, larval settlement might be connected to organic acids and derivatives. The multiomics analysis of the T. mesophilum genome, SP-7-OMVs metabolome, and larval transcriptome revealed 47 shared KEGG pathways. Among the number of candidate metabolites, arginine was chosen for its greater ability to increase the settlement rate and its role as the principal substrate for nitric oxide (NO) synthesis of sponge larvae. In summary, these results demonstrated that sponge-associated bacteria might utilize OMVs and their cargo to support host development and make up for host metabolic pathway deficiencies. This study enhances our fundamental knowledge of OMVs in interactions between metazoan hosts and microorganisms that are crucial in the coevolution of marine ecosystems and the complex marine environment.

In animal husbandry applications, segmenting live pigs in complex farming environments faces many challenges, such as when pigs lick railings and defecate within the acquisition environment. The pig’s behavior makes point cloud segmentation more complex because dynamic animal behaviors and environmental changes must be considered. This further requires point cloud segmentation algorithms to improve the feature capture capability. In order to tackle the challenges associated with accurately segmenting point cloud data collected in complex real-world scenarios, such as pig occlusion and posture changes, this study utilizes PointNet++. The SoftPool pooling method is employed to implement a PointNet++ model that can achieve accurate point cloud segmentation for live pigs in complex environments. Firstly, the PointNet++ model is modified to make it more suitable for pigs by adjusting its parameters related to feature extraction and sensory fields. Then, the model’s ability to capture the details of point cloud features is further improved by using SoftPool as the point cloud feature pooling method. Finally, registration, filtering, and extraction are used to preprocess the point clouds before integrating them into a dataset for manual annotation. The improved PointNet++ model’s segmentation ability was validated and redefined with the pig point cloud dataset. Through experiments, it was shown that the improved model has better learning ability across 529 pig point cloud data sets. The optimal mean Intersection over Union (mIoU) was recorded at 96.52% and the accuracy at 98.33%. This study has achieved the automatic segmentation of highly overlapping pigs and pen point clouds. This advancement enables future animal husbandry applications, such as estimating body weight and size based on 3D point clouds.

Flexible electronics have attracted increasing attention and are extensively used in medical care and health monitoring applications. However, research on their applications in low-temperature environments is limited, mainly owing to material intrinsic limitation. In this work, a cryogenic pressure sensor using low-melting (−71 °C) ionic liquid 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM]BF4) is fabricated via the template removal method. The sensor unit can function at temperatures ranging from −50 to 30 °C, with improved sensing performance at lower temperatures. At −50 °C, it demonstrates an ultralow detection limit of 0.5 Pa and a high sensitivity of 2.0 × 105 Ω/kPa, thereby enabling the detection of dynamic pressure loads with different frequencies (0.2 to 2 Hz) and waveforms (sine and triangle). Subsequently, these units are integrated into a 3 × 3 array and embedded into a bionic thumb. The sensor can accurately identify up to 9 independent touch points and recognize dynamic sliding with velocities in the range of 0.31 to 4.42 cm/s at an extremely low temperature (−50 °C), thus demonstrating remarkable multitouch and sliding trajectory recognition capabilities. Furthermore, the proposed sensor unit is expected to contribute to the research on the human–machine interface of space suits.

We study a sample of 14 spectroscopically confirmed Ly α emitters (LAEs) in the late era of reionization (at redshift z ≈ 6) based on the JWST/NIRCam imaging data set. These LAEs with high Ly α luminosity of L (Ly α ) ∼10 ^42.4 –10 ^43.4 erg s ^−1 have been covered by the (ongoing) COSMOS-Web survey over 0.28 deg ^2 in four NIRCam bands (F115W, F150W, F277W, and F444W). With JWST/NIRCam imaging, we determine the UV continua with M _UV ranging from −20.5 to −18.5 mag. The UV slopes have a median value of β ≈ −2.35, and the steepest slopes can reach β < −3. Under the excellent spatial resolution of JWST, we identify three objects in the sample as potential merging/interacting systems. The 14 LAEs (and their components) are compact in morphology, residing substantially below the mass–size relation of high- z galaxies. We further investigate their physical properties, including the stellar mass ( M _* ) and star formation rates (SFRs). Most of the LAEs lie on the SFR– M _* main-sequence relation, while two of them, featured as “little red dots,” likely host active galactic nuclei (AGNs), implying a ∼10% AGN fraction. Moreover, we reveal that a new correlation may exist between Ly α equivalent width and the offset between Ly α and UV emission (Δ d _Ly _α ), with a median Δ d _Ly _α ∼ 1 kpc. This could be explained by the Ly α radiative transfer process in both the interstellar medium and circumgalactic medium. The results usher in a new era of detailed analysis on high- z LAEs with the JWST capability.

We characterize the multiphase circumgalactic medium (CGM) and galaxy properties at z = 6.0–6.5 in four quasar fields from the James Webb Space Telescope A SPectroscopic survey of biased halos In the Reionization Era (ASPIRE) program. We use the Very Large Telescope/X-shooter spectra of quasar J0305–3150 to identify one new metal absorber at z = 6.2713 with multiple transitions (O i , Mg ii , Fe ii, and C ii ). They are combined with the published absorbing systems in Davies et al. at the same redshift range to form a sample of nine metal absorbers at z = 6.03–6.49. We identify eight galaxies within 1000 km s ^−1 and 350 kpc around the absorbing gas from the ASPIRE spectroscopic data, with their redshifts secured by [O iii ] ( λ λ 4959, 5007) doublets and H β emission lines. Our spectral energy distribution fitting indicates that the absorbing galaxies have stellar masses ranging from 10 ^7.2 to 10 ^8.8 M _⊙ and metallicity between 0.02 and 0.4 solar. Notably, the z = 6.2713 system in the J0305–3150 field resides in a galaxy overdensity region, which contains two (tentatively) merging galaxies within 350 kpc and seven galaxies within 1 Mpc. We measure the relative abundances of α elements to iron ([ α /Fe]) and find that the CGM gas in the most overdense region exhibits a lower [ α /Fe] ratio. Our modeling of the galaxy’s chemical abundance favors a top-heavy stellar initial mass function and hints that we may be witnessing the contribution of the first generation of Population III stars to the CGM at the end of the reionization epoch.

When locating multiple magnetic targets, the interference between each magnetic dipole is often ignored, we propose a method to detect and locate multiple weak magnetic target signals under the interference of strong magnetic sources. First, under different burial depths, the influence of shallow magnetic sources and deep magnetic sources on each other was studied and the conclusion was drawn that shallow targets are less affected by deep targets, while deep targets have the opposite effect; and the normalized source strength (NSS) is introduced into the concept of magnetic inclination in the terrain field, this simultaneously utilizes the insensitivity of magnetic inclination to burial depth and the isotropy of NSS to amplify the signal characteristics of submerged deep targets, and initially obtains the horizontal position of the measured target; the idea of locating shallow targets first, removing the interference of shallow targets, and then locating deep targets is proposed, The results of positioning were fitted and optimized by moth Moth-Flame Optimization (MFO), and the accuracy of positioning was improved. In the simulation, compared with the total magnetic field intensity (TMI), the root mean square error (RMSE) of the positioning results of the three measured targets after using the proposed method is reduced from 0.2820, 0.1831 and 0.3972 to 0.0112, 0.0145 and 0.0326, the positioning error of deep target is greatly reduced, which proves the feasibility of the proposed method, in the actual experiment, the positioning accuracy of the deep measured magnetic source is also improved.

3D magnetic inversion is an important method for detecting underwater or underground magnetic objects, which can obtain the physical parameters and geometric features of the target. In order to solve the problem of smooth inversion results of L2 norm regularization, this paper proposes a three-dimensional inversion method of magnetic gradient data based on equivalent source weighting. First, the center position of the magnetic object is estimated using the correlation imaging method, and then the equivalent source weighting function is constructed based on the acquired center position. The weights are calculated according to the distance from the grid to the center of the magnetic object. The further away the grid is, the higher weight will be given. The Euclidean distance and Chebyshev distance are used for calculating the weights of grids. Finally, the equivalent source weighting function is added to the total objective function and solved by conjugate gradient method. Simulation experiments show that the equivalent source weighting function can reduce the root-mean-square error of the inversion results and improve the structural similarity. Compared with the Euclidean distance, the inversion result of the edges and corners of cubic magnetic body model is better when weighted with the Chebyshev distance. The proposed method does not require iterative solving and can avoid generating too smooth results, which improves the inversion accuracy.

With the progress of integrated optoelectronic devices over recent decades, the semiconductor research has increasingly focused on tunable semiconductor lasers featuring a compact structure and simplified fabrication. In this manuscript, we present a proposal for a V-Cavity tunable semiconductor Laser (VCL) at a center wavelength of 940 nm. The theoretical analysis encompasses the threshold conditions of the laser, considering various cavity length differences within the waveguide layer structure. Moreover, we showcase a VCL with a waveguide width of 3 μm and a channel interval of 0.6 nm. Through the optimization of polynomial parameters associated with the curved waveguide, the VCL attains a transmittance exceeding 99.4 %. Additionally, we address the determination of optimal parameter ranges and solve the optical field distribution within the half-wave coupler. The simulation results exhibit that the half-wave coupler, employing optimized parameters, achieves remarkable single-mode selectivity when operating at a central wavelength of 940 nm. Notably, a maximum side mode suppression ratio (SMSR) of 47.9 dB is attainable with a half-wave coupler length of 45 μm and a waveguide gap of 1.7 μm.

Amid growing emphasis on achieving carbon neutrality, this study conducts a thorough assessment of different fuel cell technologies for their suitability as primary ship power sources. The primary goal is to evaluate the energy efficiency and carbon footprint impacts associated with adopting fuel cells for ship propulsion. The analysis employs simulation modeling and comparative evaluation to establish key indices: energy efficiency design index (EEDI), energy efficiency operational index (EEOI), and carbon footprint design index (CFDI). These indices consider factors like system weight, maintenance cycle, and fuel economy, ensuring a comprehensive comparison under consistent ship design parameters. Results reveal that liquefied natural gas fuel cells, direct methanol fuel cells, and low-temperature proton exchange membrane fuel cells (LT-PEMFC) outperform other fuel cell systems in terms of energy efficiency and carbon emissions reduction. Their respective EEDI values stand at 11.62, 12.72, and 10.05 g CO2/ton·km, accompanied by corresponding EEOI values of 0.10, 0.13, and 0.11 g CO2/ton·km. Additionally, CFDI values are calculated as 39.10 %, 19.45 %, and 11.64 %, respectively. Notably, the comprehensive assessment underscores LT-PEMFC as the most viable option for ship propulsion, offering improved energy utilization, reduced carbon impact, and decreased operational expenses. These findings contribute valuable insights into the appropriateness of diverse fuel cell technologies for ship power applications, considering both their energy efficiency and environmental implications.

An exploding foil initiator system (EFIs) is essential in modern weaponry for its safety and reliability. As the main component of EFIs, the performance of the switch is critical to EFIs. In this study, a planar three-electrode trigger switch was designed and fabricated using the Flexible Printed Circuits (FPC) process. Subsequently, the performance of the FPC switch was tested. The results show that the self-breakdown voltage of the FPC switch is stable. In addition, an FPF switch with a 0.6 mm main electrode gap demonstrated consistency, with delay times below 31.75 ns, and a jitter ranging from 1.7 ns to 10.94 ns at 900 V to 1200 V, evidencing the FPC switches’ reliability and uniform performance across various voltages. Compared to the Micro-Electro-Mechanical Systems (MEMS) switches of similar dimensions, the FPC switches achieved a faster high-current attainment with less inductance, showing a 5% reduction in loop inductance. The repetitive testing results demonstrate that the FPC switch maintains consistent output performance, with stable peak currents, peak current time, and delay time over 50 action cycles, highlighting its repeatability. The FPC switch was assembled with an EFI chip and capacitor into an integrated system, which was subsequently able to successfully detonate HNS-IV at 1000 V/0.22 μF, proving the FPC switch’s potential in low inductance applications.

To enhance the energy efficiency of exploding foil initiator systems (EFIs) and mitigate energy loss due to ablation in the bridge-wing regions, a low-energy bridge-wing-thickened EFI chip was designed and fabricated. Computational analysis revealed that increasing the thickness of the bridge flanks significantly reduces ablation within the bridge region during the electrical explosion. The refinement of the design led to the adoption of a bridge flank thickness of 19 μm, with the bridge area dimensions specified as 0.25 mm × 0.25 mm × 4 μm. This bridge-wing-thickened EFI chip was produced by employing micro-electro-mechanical systems (MEMS) technology and underwent rigorous performance evaluations. The empirical results closely matched the computational predictions, thereby corroborating the precision of the proposed model in simulating the temperature distribution seen during the explosion process. Notably, this enhanced EFI design achieves a flyer velocity of 3800 m/s at a condition of 900 V/0.22 μF, signifying a significant advancement in EFI system efficiency and performance.

Preparing copper-based azide by in situ reaction is well-suited for MEMS processing technology and holds promising prospects in the field of MEMS micro-initiators. This study involved the preparation of porous copper with particle sizes of approximately 30 nm, 60 nm and 100 nm through powder sintering. These were used as precursors for a gas–solid in situ azide reaction to produce copper-based azide with varying morphologies and compositions. Copper-based azide micro-initiators were designed, and their output performance was evaluated using CL-20 and HNS-IV explosives. Analytical results revealed that the product from the reaction of the 100 nm precursor exhibited a lumpy and uneven structure with a conversion rate of 90.36%. The product from the 60 nm precursor reaction had a dense surface with a conversion rate of 94.56%, while the 30 nm precursor resulted in a needle-like form with a conversion rate of 92.82%. Detonation experiments demonstrated that the copper-based azide micro-initiators prepared with 100 nm of a porous copper precursor exhibited unstable output performance, requiring a 1.6 mg charge to successfully detonate CL-20 explosives. On the other hand, copper-based azide micro-initiators prepared from 60 nm and 30 nm of porous copper precursors exhibited stable output performance. A charge of 0.8 mg was adequate for reliably and consistently detonating CL-20 and HNS-IV explosives. The reduced particle size of the precursor enhanced the output performance of the copper-based azide micro-initiators, providing increased energy redundancy during detonation and improving overall usage reliability.

The accurate online detection of laser welding penetration depth has been a critical problem to which the industry has paid the most attention. Aiming at the laser welding process of TC4 titanium alloy, a multi-sensor monitoring system that obtained the keyhole/molten pool images and laser-induced plasma spectrum was built. The influences of laser power on the keyhole/molten pool morphologies and plasma thermo-mechanical characteristics were investigated. The results showed that there were significant correlations among the variations of the keyhole–molten pool, plasma spectrum, and penetration depth. The image features and spectral features were extracted by image processing and dimension-reduction methods, respectively. Moreover, several penetration depth prediction models based on single-sensor features and multi-sensor features were established. The mean square error of the neural network model built by multi-sensor features was 0.0162, which was smaller than that of the model built by single-sensor features. The established high-precision model provided a theoretical basis for real-time feedback control of the penetration depth in the laser welding process.

(1) Background: Particulate methane monooxygenase (pMMO) has a strong dependence on the natural electron transfer path and is prone to denaturation, which results in its redox activity centers being unable to transfer electrons with bare electrodes directly and making it challenging to observe an electrochemical response; (2) Methods: Using methanobactin (Mb) as the electron transporter between gold electrodes and pMMO, a bionic interface with high biocompatibility and stability was created. The Mb-AuNPs-modified functionalized gold net electrode as a working electrode, the kinetic behaviors of pMMO bioelectrocatalysis, and the effect of Mb on pMMO were analyzed. The CV tests were performed at different scanning rates to obtain electrochemical kinetics parameters. (3) Results: The values of the electron transfer coefficient (α) and electron transfer rate constant (ks) are relatively large in test environments containing only CH4 or O2. In contrast, in the test environment containing both CH4 and O2, the bioelectrocatalysis of pMMO is a two-electron transfer process with a relatively small α and ks; (4) Conclusions: It was inferred that Mb formed the complex with pMMO. More importantly, Mb not only played a role in electron transfer but also in stabilizing the enzyme structure of pMMO and maintaining a specific redox state. Furthermore, the continuous catalytic oxidation of natural substrate methane was realized.

Nanoporous Cu foam is widely applied in many fields such as the packaging of electronic power devices. In this study, a sandwich-structured Cu-Zn eutectic alloy precursor composed of Cu0.53Zn0.47/Cu5Zn8/Cu0.53Zn0.47 is prepared through electroplating. The surface layer of the precursor, Cu0.53Zn0.47, has a flat surface with numerous grain boundaries, which effectively promotes its dealloying behavior. By contrast, Cu5Zn8 has a porous structure, which promotes the dealloying behavior at the center of the precursor. The dealloying of Cu0.53Zn0.47 is dominated by the coherent surface diffusion of Cu atoms, and the crystal lattice and orientation show no changes before and after dealloying. By contrast, the dealloying behavior of Cu5Zn8 requires the renucleation of Cu crystals; in this process, Cu atoms are transported to the surface of the layer by capillary forces to form clusters, which nucleate and grow.

Livestock’s live body dimensions are a pivotal indicator of economic output. Manual measurement is labor-intensive and time-consuming, often eliciting stress responses in the livestock. With the advancement of computer technology, the techniques for livestock live body dimension measurement have progressed rapidly, yielding significant research achievements. This paper presents a comprehensive review of the recent advancements in livestock live body dimension measurement, emphasizing the crucial role of computer-vision-based sensors. The discussion covers three main aspects: sensing data acquisition, sensing data processing, and sensing data analysis. The common techniques and measurement procedures in, and the current research status of, live body dimension measurement are introduced, along with a comparative analysis of their respective merits and drawbacks. Livestock data acquisition is the initial phase of live body dimension measurement, where sensors are employed as data collection equipment to obtain information conducive to precise measurements. Subsequently, the acquired data undergo processing, leveraging techniques such as 3D vision technology, computer graphics, image processing, and deep learning to calculate the measurements accurately. Lastly, this paper addresses the existing challenges within the domain of livestock live body dimension measurement in the livestock industry, highlighting the potential contributions of computer-vision-based sensors. Moreover, it predicts the potential development trends in the realm of high-throughput live body dimension measurement techniques for livestock.

Acquiring phenotypic data from livestock constitutes a crucial yet cumbersome phase in the breeding process. Traditionally, obtaining livestock phenotypic data primarily involves manual, on-body measurement methods. This approach not only requires extensive labor but also induces stress on animals, which leads to potential economic losses. Presently, the integration of next-generation Artificial Intelligence (AI), visual processing, intelligent sensing, multimodal fusion processing, and robotic technology is increasingly prevalent in livestock farming. The advantages of these technologies lie in their rapidity and efficiency, coupled with their capability to acquire livestock data in a non-contact manner. Based on this, we provide a comprehensive summary and analysis of the primary advanced technologies employed in the non-contact acquisition of livestock phenotypic data. This review focuses on visual and AI-related techniques, including 3D reconstruction technology, body dimension acquisition techniques, and live animal weight estimation. We introduce the development of livestock 3D reconstruction technology and compare the methods of obtaining 3D point cloud data of livestock through RGB cameras, laser scanning, and 3D cameras. Subsequently, we explore body size calculation methods and compare the advantages and disadvantages of RGB image calculation methods and 3D point cloud body size calculation methods. Furthermore, we also compare and analyze weight estimation methods of linear regression and neural networks. Finally, we discuss the challenges and future trends of non-contact livestock phenotypic data acquisition. Through emerging technologies like next-generation AI and computer vision, the acquisition, analysis, and management of livestock phenotypic data are poised for rapid advancement.

The James Webb Space Telescope provides an unprecedented opportunity for unbiased surveys of H α -emitting galaxies at z > 4 with the NIRCam's wide-field slitless spectroscopy (WFSS). In this work, we present a census of Ly α escape fraction ( f _esc,Ly _α ) of 165 star-forming galaxies at z = 4.9–6.3, utilizing their H α emission directly measured from FRESCO NIRCam/WFSS data. We search for Ly α emission of each H α -emitting galaxy in the Very Large Telescope/MUSE data. The overall f _esc,Ly _α measured by stacking is 0.090 ± 0.006. We find that f _esc,Ly _α displays a strong dependence on the observed UV slope ( β _obs ) and E ( B − V ), such that the bluest galaxies ( β _obs ∼ −2.5) have the largest escape fractions ( f _esc,Ly _α ≈ 0.6), indicative of the crucial role of dust and gas in modulating the escape of Ly α photons. f _esc,Ly _α is less well related to other parameters, including the UV luminosity and stellar mass, and the variation in f _esc,Ly _α with them can be explained by their underlying coupling with E ( B − V ) or β _obs . Our results suggest a tentative decline in f _esc,Ly _α at z ≳ 5, implying increasing intergalactic medium attenuation toward higher redshift. Furthermore, the dependence of f _esc,Ly _α on β _obs is proportional to that of the ionizing photon escape fraction ( f _esc,LyC ), indicating that the escape of Ly α and ionizing photon may be regulated by similar physical processes. With f _esc,Ly _α as a proxy to f _esc,LyC , we infer that UV-faint ( M _UV > −16) galaxies contribute >70% of the total ionizing emissivity at z = 5–6. If these relations hold during the epoch of reionization, UV-faint galaxies can contribute the majority of UV photon budget to reionize the Universe.

We introduced a label-free sensing system based on an array of microring resonators (MRRs) which was successfully employed for human serum albumin (HSA) detection. The sensing-ring surface was functionalized to immobilize anti-HSA, facilitating HSA binding. Our refractive index sensing system demonstrates high sensitivity at 168 nm/RIU and a low limit of detection (LOD) of 63.54 ng/mL, closely comparable to current HSA detection methods. These findings confirm the potential of MRRs as biocompatible sensors for HSA detection. This system holds great promise as an innovative platform for the detection of HSA, carrying significant importance in medical diagnostics.

Cosmic variance introduces significant uncertainties into galaxy number density properties when surveying the high-redshift Universe with a small volume. Such uncertainties produce the field-to-field variance σ _g of galaxy numbers in observational astronomy, which significantly affects the luminosity function (LF) measurement of Ly α emitters (LAEs). For most previous Ly α LF studies, σ _g is often adopted from predictions by cosmological simulations, but barely confirmed by observations. Measuring cosmic variance requires a huge sample over a large volume, exceeding the capabilities of most astronomical instruments. In this study, we demonstrate an observational approach for measuring the cosmic variance contribution for z ≈ 2.2 Ly α LFs. The LAE candidates are observed using the narrow band and broad band of the Subaru/Hyper Suprime-Cam in eight independent fields, making the total survey area ≃11.62 deg ^2 and a comoving volume of ≃8.71 × 10 ^6 Mpc ^3 . We report a best-fit Schechter function with parameters α = −1.75 (fixed), ${L}_{\mathrm{Ly}\alpha }^{* }={5.95}_{-0.96}^{+1.22}\times {10}^{42}$ erg s ^−1 , and ${\phi }_{\mathrm{Ly}\alpha }^{* }={5.26}_{-1.27}^{+1.65}$ × 10 ^−4 Mpc ^−3 for the overall Ly α LFs. After clipping out the regions that may bias the cosmic variance measurements, we calculate σ _g by sampling LAEs within multiple pointings on the field image. We investigate the relation between σ _g and survey volume V , and fit a simple power-law ${\sigma }_{g}=k\times {\left(\tfrac{V}{{10}^{5}\,{\mathrm{Mpc}}^{3}}\right)}^{\beta }$ . We find best-fit values of $-{1.399}_{-0.156}^{+0.160}$ for β and ${1.249}_{-0.193}^{+0.213}$ for k . We compare our measurements with predictions from simulations and find that the cosmic variance of LAEs is likely larger than that of general star-forming galaxies.

In this paper, we present a Ly α halo (LAH) identified by stacking ∼3300 Ly α emitters (LAEs) at z = 2.2–2.3. We carry out imaging observations and data reduction with Subaru/Hyper Suprime-Cam. Our total survey area is ∼12 deg ^2 and the imaging depths are 25.5–27.0 mag. Using the imaging data, we select 1240 and 2101 LAE candidates at z = 2.2 and 2.3, respectively. We carry out spectroscopic observations of our LAE candidates and data reduction with Magellan/IMACS to estimate the contamination rate of our LAE candidates. We find that the contamination rate of our sample is low (8%). We stack our LAE candidates with a median stacking method to identify the LAH at z = 2. We show that our LAH is detected until ∼100 kpc at the 2 σ significance level and likely extended to ∼200 kpc at a surface brightness level of ∼10 ^−20 erg s ^−1 cm ^−2 arcsec ^−2 . Compared to those of previous studies, our LAH is brighter at radii of ∼25–100 kpc, which is not likely caused by the contamination in our sample but by the different redshifts, fields, and selection methods instead. To investigate how central galaxies affect surrounding LAHs, we divide our LAEs into subsamples based on the Ly α luminosity ( L _Ly _α ), rest-frame Ly α equivalent width (EW _0 ), and UV magnitude ( M _uv ). We stack the subsamples and find that higher L _Ly _α , smaller EW _0 , and brighter M _uv cause more extended halos. Our results suggest that more massive LAEs generally have more extended LAHs.

Drawing from (Dörnyei's, The Psychology of the language learner: Individual differences in second language acquisition, 2005) L2 Motivational Self System, this case study delved into the L2 learning motivations of liberal arts and science English majors at a transnational university in China, where English Medium Instruction (EMI) is prevalent. The study aimed to uncover how the EMI educational setting, alongside disciplinary backgrounds, shapes students' motivational landscapes. Utilising a mixed-methods approach, a 4-point Likert scale questionnaire was first administered to 182 students, followed by semi-structured interviews with six purposively selected participants to ensure a representation of diverse perspectives. Quantitative data were analysed using descriptive statistics and an independent samples t-test to pinpoint motivational differences between the two groups, with Cohen's d effect size test further elucidating the significance of these differences. Thematic analysis of qualitative data provided a deeper layer of insight, which, when cross-examined with quantitative results, revealed a nuanced understanding of motivational dynamics. Key findings highlighted that both student groups were driven by factors such as ideal L2 self, ought-to L2 self, international posture, and instrumentality. However, within the EMI context, liberal arts students exhibited heightened sensitivity to their ought-to L2 selves, language anxiety, and teacher influence compared to their science counterparts (p < 0.05, d[subscript Cohen] > 0.8). These distinctions underscore the EMI context's role in modulating motivational profiles, particularly accentuating certain motivational factors among liberal arts students. In light of these EMI-mediated motivational nuances, the study proposes several educational implications, including enhancing teachers' professional development training, integrating English learning in EMI programmes with students' aspirations, and fostering intercultural interactions to enrich students' language and cultural experiences.