Simulations of Femtosecond-Laser Near-Field Ablation Using Nanosphere under Dynamic Excitation.

Femtosecond lasers have garnered widespread attention owing to their subdiffraction processing capabilities. However, their intricate natures, involving intrapulse feedbacks between transient material excitation and laser propagation, often present significant challenges for near-field ablation predictions and simulations. To address these challenges, the current study introduces an improved finite-difference time-domain method (FDTD)-plasma model (plasma)-two-temperature model (TTM) framework for simulating the ablation processes of various nanospheres on diverse substrates, particularly in scenarios wherein dynamic and heterogeneous excitations significantly influence optical-field distributions. Initially, FDTD simulations of a single Au nanosphere on a Si substrate reveal that, with transitions in the excitation states of the substrate, the field-intensity distribution transforms from a profile with a single central peak to a bimodal structure, consistent with experimental reports. Subsequently, simulations of a polystyrene nanosphere array on a SiO2 substrate reveal that different excitation states of the nanospheres yield two distinct modes, namely near-field enhancement and masking. These modes cannot be adequately modeled in the FDTD simulations. Our combined model also considers the intrapulse feedback between the electromagnetic-field distribution resulting from near-field effects and material excitations. Furthermore, the model can quantitatively analyze subsequent electron-phonon coupling and material removal processes resulting from thermal-phase transitions. Consequently, our model facilitates predictions of the femtosecond-laser ablation of single nanospheres or nanosphere arrays with varying sizes and materials placed on substrates subjected to near-field effects.

Metagenomics reveals unique gut mycobiome biomarkers in psoriasis.

PURPOSE: In present, the diagnosis of psoriasis is mainly based on the patient's typical clinical manifestations, dermoscopy and skin biopsy, and unlike other immune diseases, psoriasis lacks specific indicators in the blood. Therefore, we are required to search novel biomarkers for the diagnosis of psoriasis. METHODS: In this study, we analyzed the composition and the differences of intestinal fungal communities composition between psoriasis patients and healthy individuals in order to find the intestinal fungal communities associated with the diagnosis of psoriasis. We built a machine learning model and identified potential microbial markers for the diagnosis of psoriasis. RESULTS: The results of AUROC (area under ROC) showed that Aspergillus puulaauensis (AUROC = 0.779), Kazachstania africana (AUROC = 0.750) and Torulaspora delbrueckii (AUROC = 0.745) had high predictive ability (AUROC > 0.7) for predicting psoriasis, While Fusarium keratoplasticum (AUROC = 0.670) was relatively lower (AUROC < 0.7). CONCLUSION: The strategy based on the prediction of intestinal fungal communities provides a new idea for the diagnosis of psoriasis and is expected to become an auxiliary diagnostic method for psoriasis.

A study of latent profile analysis of empathic competence and factors influencing it in nursing interns: a multicenter cross-sectional study.

Background: Empathy, as one of the fundamental principles of nursing professionalism, plays a pivotal role in the formation and advancement of the nursing team. Nursing interns, as a reserve force within the nursing team, are of significant importance in terms of their ability to empathize. This quality is not only directly related to the degree of harmony in the nurse-patient relationship and the enhancement of patient satisfaction, but also plays a pivotal role in the promotion of the quality of nursing services to a new level. Aim: The objective of this study was to gain a deeper understanding of the current state of nursing interns' empathic abilities. To this end, we sought to examine empathic performance under different profile models and to identify the key factors influencing these profile models. Methods: The study utilized 444 nursing interns from 11 tertiary general hospitals in Inner Mongolia as research subjects. The study employed a number of research tools, including demographic characteristics, the Jefferson Scale of Empathy, and the Professional Quality of Life Scale. A latent profile model of nursing interns' empathy ability was analyzed using Mplus 8.3. The test of variability of intergroup variables was performed using the chi-square test. Finally, the influencing factors of each profile model were analyzed by unordered multi-categorical logistic regression analysis. Results: The overall level of empathy among nursing interns was found to be low, with 45% belonging to the humanistic care group, 43% exhibiting low empathy, and 12% demonstrating high empathy. The internship duration, empathy satisfaction, secondary traumatic stress, only child, place of birth, and satisfaction with nursing were identified as factors influencing the latent profiles of empathy in nursing interns (p < 0.05). Conclusion: There is considerable heterogeneity in nursing interns' ability to empathize. Consequently, nursing educators and administrators should direct greater attention to interns with lower empathy and develop targeted intervention strategies based on the influences of the different underlying profiles.

Regulation of Fuzheng Huayu capsule on inhibiting the fibrosis-associated hepatocellular carcinogenesis.

In the current study, bioinformatics analysis of the hepatocellular carcinoma (HCC) dataset was conducted with the hepatoprotective effect of the Fuzheng Huayu (FZHY) capsule against the diethylnitrosamine-induced HCC progression analyzed. Eight cell clusters were defined and tanshinone IIA, arachidonic acid, and quercetin, compounds of the FZHY capsule, inhibit HCC progression-related fibrosis by regulating the expression of PLAU and IGFBP3. Combined with the ameliorative effect of the FZHY capsule against liver dysfunctions and expression of PLAU and IGFBP3, our study confirmed the effect of the FZHY capsule on inhibiting the fibrosis-associated HCC progression via regulating the expression of PLAU and IGFBP3.

Moderately reducing N input to mitigate heat stress in maize.

In a warming climate, high temperature stress greatly threatens crop yields. Maize is critical to food security, but frequent extreme heat events coincide temporally and spatially with the period of kernel number determination (e.g., flowering stage), greatly limiting maize yields. In this context, how to increase or at least maintain maize yield has become more important. Nitrogen fertilizer (N) is widely used to improve maize yields, but its effect in heat stress is unclear. For this, we collected 1536 pairs of comparisons from 113 studies concerning N conducted in the past 20 years over China. We classified the data into two groups - without high temperature stress (NHT) and with high temperature stress during the critical period for maize kernel number determination (HT) - based on the national meteorological data. We comprehensively evaluated N effects on grain yield under HT and NHT using meta-analysis. The effect of N on maize yield became significantly smaller in HT than that in NHT. In NHT, soil characteristics, crop management practices, and climatic conditions all significantly affected N effects on maize yield, but in HT, only a few factors such as soil organic matter and mean annual precipitation significantly affected N effects. Hence, it is difficult to improve N effect by improving soil characteristics and crop management when meeting with high temperature stress during flowering. On average, N effect increased with increased N input, but there were respective N input thresholds in NHT and HT, beyond which N effects on maize yield remained stable. According to the thresholds, it is speculated that moderately reducing N input (~20 %) likely increased high temperature tolerance of maize during flowering. These findings have important implications for the optimization of N management under a warming climate.

Treatment of colorectal cancer by traditional Chinese medicine: prevention and treatment mechanisms.

Colorectal cancer (CRC) is a significant global health burden, with high morbidity and mortality rates. It is often diagnosed at middle to advanced stage, affecting approximately 35% of patients at the time of diagnosis. Currently, chemotherapy has been used to improve patient prognosis and increase overall survival. However, chemotherapy can also have cytotoxic effects and lead to adverse reactions, such as inhibiting bone marrow hematopoiesis, causing digestive dysfunction, hand-foot syndrome, and even life-threatening conditions. In response to these adverse effects, researchers have proposed using Traditional Chinese Medicine (TCM) as an option to treat cancer. TCM research focuses on prescriptions, herbs, and components, which form essential components of the current research in Chinese medicine. The study and implementation of TCM prescriptions and herbs demonstrate its distinctive holistic approach to therapy, characterized by applying multi-component and multi-target treatment. TMC components have advantages in developing new drugs as they consist of single ingredients, require smaller medication dosages, have a precise measure of pharmacodynamic effects, and have a clear mechanism of action compared to TCM prescriptions and herbs. However, further research is still needed to determine whether TMC components can fully substitute the therapeutic efficacy of TCM prescriptions. This paper presents a comprehensive analysis of the research advancements made in TCM prescriptions, herbs, and components. The findings of this study can serve as a theoretical basis for researchers who are interested in exploring the potential of TCM for the treatment of colorectal cancer.

Dynamic optimization of battery recycling e-platforms under non-equalizing supply and demand: Recycling price and service commissions.

With the rapid advancement of electric vehicles (EVs), the burgeoning increase in used power batteries necessitates the development of efficient battery recycling e-platforms. A key challenge in this field is the mismatch between supply and demand. In response, a dynamic optimization model is proposed to capture the non-equalizing supply-demand relationship and its linkage over continuous periods to enable dynamic simulations and predictions of transaction volume changes. Meanwhile, pricing and commission-setting strategies are optimized based on the objectives of maximizing social welfare and platform revenue. The result shows that due to the lower recycling volumes that result, increasing the recycling price usually increases platform revenues, exacerbates environmental costs, and leads to lower social welfare. Moreover, platform revenues are more sensitive to commission rates than social welfare, which is more vulnerable to recycling prices. Furthermore, prioritizing social welfare leads to a higher recycling volume compared to prioritizing revenue, but it also creates an imbalance between supply and demand, destabilizing the recycling market. With the dynamic pricing and commission strategies, this study enriches the literature in the third-party recycling mode for power batteries, offering a novel perspective that is more aligned with real-world operational conditions. Our findings help platforms clarify the impact of pricing and commission decisions on platform revenue and social welfare and thereby provide support for their decision optimization.

Improving the green space arrangement in residential areas from the perspective of tree leaf temperature utilizing scenario simulation in ENVI-met.

Studying the differences in leaf temperature and their mechanisms can help us accurately understand the microenvironment in which plants are located. In this paper, typical residential areas in Jianye District, Nanjing, Jiangsu Province, China, are selected as the research area, we investigated the suitability of green space configurations from the perspective of tree leaf temperature of residential areas based on the scenario simulation in ENVI-met. Firstly, twenty abstract models were constructed, including four kinds of aspect ratio of trees (ARTs) which can be used to indicate the different green space arrangement and two typical tree species, camphora tree and platanus tree. And then three aspects were discussed including impacts of different Aspect Ratio of Trees (ART), different house-side configurations on tree leaf temperature and the relationship between temperature of tree leaves and land surface temperature (ΔSurfT) and the thermal comfort index of physiological equivalent temperature (ΔPET). The results showed that B-1 (camphor tree, ART = 2) demonstrates the most effective cooling effect in summer, with ΔPET of 3.09 °C and ΔSurfT of 3.34 °C. In winter, A-1 (platanus tree, ART = 2) proves to be the most effective in enhancing thermal comfort (ΔPET = -0.15 °C), while B-1 excels in improving surface temperature (ΔSurfT = 0.55 °C). In all, for residential area, especially in summer, planting dense camphora trees is better than platanus trees and house-side green space was very necessary. This research can help to determine appropriate tree species and green space configuration strategies for future residential areas to enhance thermal comfort.

Full-day profiling of a beam attenuation coefficient using a single-photon underwater lidar with a large dynamic measurement range.

A compact underwater lidar system, utilizing a single-photon detection technology, is proposed to effectively eliminate interference from the sea-air interface and enhance the accuracy of water optical property measurements. However, the high sensitivity of the single-photon detector poses challenges, including daytime operation difficulties due to strong solar radiation noise and detector saturation from near-field lidar signals. To address these issues, the laser and optical receiver of the lidar are optimized to suppress solar radiation noise, and a dual-telescope structure is introduced to improve the dynamic measurement range beyond 70 dB. In addition, a Monte Carlo simulation establishes the relationship between beam attenuation coefficients (c) and lidar attenuation coefficients (Klidar), enabling the retrieval of c profiles from Klidar. A field experiment conducted in the South China Sea, spanning from inshore to offshore waters, demonstrates the effectiveness of the lidar. The results highlight its potential applications, including the assessment of subsurface particulate organic carbon (POC).

Day and night continuous high-resolution shallow-water depth detection with single-photon underwater lidar.

Single-photon lidar has emerged as a strong technology for bathymetric measurements. However, its heightened sensitivity additionally makes it susceptible to solar radiation noise, particularly in the green light wavelength where solar radiation is strong, posing challenges for its daytime operation. To address this issue, a single-photon underwater lidar system is proposed and demonstrated. This scheme has these features. 1) Underwater applications not only mitigate the impact of the air-water interface on laser transmission but also significantly attenuate solar radiation reaching the lidar due to the absorption and scattering properties of water. 2) The telescope is designed with a small aperture and narrow field of view to significantly suppress solar radiation. 3) A combination of a narrowband laser and narrowband filter technique is effectively employed to minimize residual solar radiation, thus enabling continuous bathymetric observation capabilities during both day and night. 4) After acquiring the backscattered signal from the bottom, a water depth extraction algorithm utilizing bi-Gaussian fitting is proposed. To demonstrate the robustness of the lidar and the effectiveness of the algorithm, the underwater single-photon lidar system is deployed on a ship to conduct cruise surveys of two bays in the nearshore area, as well as a full-day stationary observation experiment. The lidar measurements are highly consistent with the synchronized sonar observations. The full-day stationary observation experiment showcased its capability to deliver continuous measurements throughout the day and night. These results demonstrate the potential of the system in various applications, including high-precision underwater terrain mapping, obstacle avoidance for underwater platforms, and underwater target imaging.