Historical transmission and other controversies related to Sengzhao’s Things Do Not Shift have long been a subject of scholarly attention. However, his essay Emptiness of the Nonabsolute has been insufficiently studied, despite being traditionally deemed emblematic of the Chinese understanding of Mādhyamaka philosophy. The present study shows that this essay has also historically generated divisions and debates in the Chinese context. It finds that Emptiness of the Nonabsolute expresses the Mādhyamaka philosophy of emptiness in a distinctly Chinese manner by grounding itself in the principle of dependent origination, and by transforming issues of being and nonbeing and the name and the “thing-in-itself” into conditional emergence. Nevertheless, Sengzhao’s essay evoked the two markedly distinct construals of Buzhengukong 不真故空 and Bushizhenkong 不是真空 as Tathāgatagarbha and Buddha-nature philosophy within Chinese Buddhism. Bushizhenkong directly aligned Sengzhao’s ostensibly representative theory of Mādhyamaka emptiness in China with the doctrinal framework of Tathāgatagarbha and Buddha-nature, triggering almost a millennium-long period of discussions and controversies. Full article

Silk and silk derivatives have emerged as a possible alternative in surgical device development, offering mechanical strength, biocompatibility, and environmental sustainability. Through a systematic review following PRISMA guidelines, this study evaluated silk fibroin’s application across pre-clinical and clinical settings, focusing on its role as screws and plates for osteofixation. A comprehensive search yielded 245 studies, with 33 subjected to full-text review and 15 ultimately included for qualitative analysis. The findings underscore silk fibroin’s superior properties, including its tunable degradation rates and ability to be functionalized with therapeutic agents. In vivo and in vitro studies demonstrated its efficacy in enhancing bone healing, offering improved outcomes in osteofixation, particularly for craniofacial defects. Silk fibroin’s remarkable attributes in biodegradation and drug release capabilities underscore its potential to enhance patient care. Ultimately, silk fibroin’s integration into surgical practices promises a revolution in patient outcomes and environmental sustainability. Its versatility, coupled with the continuous progress in fabrication techniques, signals a promising horizon for its widespread acceptance in the medical field, potentially establishing a new benchmark in surgical treatment. Further research is expected to solidify the transition of silk products from basic science to patient care, paving the way for widespread use in various surgical applications. Full article

Acinetobacter baumannii has developed multiple drug resistances, posing a significant threat to antibiotic efficacy. LysECD7, an endolysin derived from phages, could be a promising therapeutic agent against multi-drug resistance A. baumannii. In this study, in order to further enhance the antibacterial efficiency of the engineered LysECD7, a few lipopolysaccharide-interacting peptides (Li5, MSI594 and Li5-MSI) were genetically fused with LysECD7. Based on in vitro antibacterial activity, the fusion protein Lys-Li5-MSI was selected for further modifications aimed at extending its half-life. A cysteine residue was introduced into Lys-Li5-MSI through mutation (Lys-Li5-MSI^V12C), followed by conjugation with a C16 fatty acid chain via a protonation substitution reaction(V12C-C16). The pharmacokinetic profile of V12C-C16 exhibited a more favorable characteristic in comparison to Lys-Li5-MSI, thereby resulting in enhanced therapeutic efficacy against lethal A. baumannii infection in mice. The study provides valuable insights for the development of novel endolysin therapeutics and proposes an alternative therapeutic strategy for combating A. baumannii infections. Full article

Additive manufacturing (AM) or 3D printing of metals is gaining popularity due to its flexibility when fabricating parts with highly complex designs, as well as when simplifying manufacturing steps and optimizing process times. In this investigation, 17-4 PH stainless steel was additively manufactured using Laser Powder Bed Fusion (L-PBF), followed by functionalization through a DUPLEX treatment. This treatment involved a plasma-assisted nitriding process, followed by the deposition of an arc-PVD c-Al_0.7Cr_0.3N hard coating. The microstructural modifications resulting from plasma nitriding (such as the formation of Fe_2,3N and Fe₄N and the αN or expanded martensite phases) and the surface improvements with the c-Al_0.7Cr_0.3N coating on the 3D-printed 17-4 PH steel are evaluated in comparison to conventionally manufactured 17-4 PH steel. These microstructural characteristics are correlated with the mechanical response of the treated surfaces. As a result of the plasma nitriding process, the hardness of the 3D-printed 17-4 PH SS increased by approximately 260%. The wear, measured through dynamic and static scratch testing, was reduced by approximately 31%. This improvement was attributed to the modification of adhesive failure mechanisms, leading to a reduction in wear volume, improved coating adhesion, and enhanced scratch resistance. Full article

Background: Frailty leads to vulnerability to stress, impaired daily functioning, and an increased need for care. Frailty is considered reversible, and it is crucial to detect the risk of frailty early and investigate factors that may delay its progression. Objectives: To identify tests that can explain frailty risk and compare the situation of local residents with and without frailty support. Methods: Participants were recruited in two ways: through public advertisements in Akita City (open recruitment group) and through invites from frailty supporters in their immediate communities (community-based group). We examined the differences in frailty risk and oral, motor, and social functions between the two groups and identified factors associated with frailty risk in both groups. Results: The community-based group exhibited a lower risk of frailty than the open recruitment group despite having more older members on average. Additionally, the community-based group demonstrated better social functioning than the open-recruitment group. Furthermore, factors such as oral diadochokinesis (ODK), one-leg stand test (OLS), and grip strength (GS) showed significant association with frailty risk. Conclusion: The ODK, OLS, and GS were identified as factors explaining frailty risk, and Frailty Supporters may reduce the risk of frailty. Full article

In response to the limited accuracy of current three-dimensional (3D) object detection algorithms for small objects, this paper presents a multi-sensor 3D small object detection method based on LiDAR and a camera. Firstly, the LiDAR point cloud is projected onto the image plane to obtain a depth image. Subsequently, we propose a cascaded image fusion module comprising multi-level pooling layers and multi-level convolution layers. This module extracts features from both the camera image and the depth image, addressing the issue of insufficient depth information in the image feature. Considering the non-uniform distribution characteristics of the LiDAR point cloud, we introduce a multi-scale voxel fusion module composed of three sets of VFE (voxel feature encoder) layers. This module partitions the point cloud into grids of different sizes to improve detection ability for small objects. Finally, the multi-level fused point features are associated with the corresponding scale’s initial voxel features to obtain the fused multi-scale voxel features, and the final detection results are obtained based on this feature. To evaluate the effectiveness of this method, experiments are conducted on the KITTI dataset, achieving a 3D AP (average precision) of 73.81% for the hard level of cars and 48.03% for the hard level of persons. The experimental results demonstrate that this method can effectively achieve 3D detection of small objects. Full article

Seed dormancy and germination play pivotal roles in the agronomic traits of plants, and the degree of dormancy intuitively affects the yield and quality of crops in agricultural production. Seed priming is a pre-sowing seed treatment that enhances and accelerates germination, leading to improved seedling establishment. Seed priming technologies, which are designed to partially activate germination, while preventing full seed germination, have exerted a profound impact on agricultural production. Conventional seed priming relies on external priming agents, which often yield unstable results. What works for one variety might not be effective for another. Therefore, it is necessary to explore the internal factors within the metabolic pathways that influence seed physiology and germination. This review unveils the underlying mechanisms of seed metabolism and germination, the factors affecting seed dormancy and germination, as well as the current seed priming technologies that can result in stable and better germination. Full article

The environmental impact caused by the intensive exploitation of fossil fuels to generate heat and electricity has already reached a critical level. Also, as the industrial sector is the largest energy consumer, mainly in the form of heat, it has then become compulsive to implement the use of renewable solar heat in industrial processes, such as those found in the food processing and beverages industries, which do not require high temperatures. Consequently, this study examines the viability of supplying heat as hot water at 80 °C and saturated steam at 160 °C to a medium-sized brewery factory through a hybrid solar plant composed of flat plate and parabolic trough collectors and sensible thermal energy storage. The study was conducted numerically using the meteorological conditions of a city different from that where the factory is located because it benefits from higher insolation levels. The mean annual solar fractions achieved were 49.9% for hot water production and 37.3% for steam generation, at a levelized cost of heat of 0.032 USD/kWh, which can be considered competitive if compared against the values reported in other similar solar projects. Also, the decrease in fossil fuel consumption allowed an annual reduction of 252 tons of carbon dioxide emissions. Full article

The constant use of alcoholic beverages can deregulate serotonin levels, affecting neurotransmitters and triggering symptoms of anxiety. In this context, the objective of this work was to evaluate the anxiolytic potential and possible action mechanisms of the natural compound amentoflavone against the deleterious effects caused by alcohol withdrawal on the behavior of adult zebrafish (aZF). The experiments showed that amentoflavone did not change locomotion and did not cause toxicity in aZF during up to 96 h of analysis, with a median lethal concentration (LC₅₀) greater than 1.0 mg/mL. The reversal of anxiety by pretreatment with granisetron suggested that the anxiolytic effect of amentoflavone is dependent on serotonergic 5-HT_3A/3B receptors. Furthermore, amentoflavone reversed anxiety due to flumazenil pretreatment, suggesting a dependence on the GABA_A receptor. The three concentrations of amentoflavone tested were effective in treating anxiety resulting from alcohol withdrawal. In silico analysis validated the in vivo results, supporting the idea that the interaction of amentoflavone with the protein occurs in a more stable manner than reference compounds. Amid growing interest in natural alternatives to treat anxiety disorders, amentoflavone is a potential candidate for a new anxiolytic compound that acts specifically on the 5HT_3A/3B and GABAergic serotonergic pathways. Full article

I employ autoethnography to undertake a broader scholarly inquiry on intergenerational relationships and transnational care shaped by global migration and aging. Specifically, I reflect on the dynamics of my relationship with my mother, beginning with my departure from my home and spanning a period of 40 years, 8 in China and 34 outside China. In doing so, I contemplate theoretical models of intergenerational solidarity, ambivalence, and role ambiguity. I also challenge cultural assumptions of filial piety. The geographical distance, passage of time, and acculturation process have profoundly influenced my perception of filial piety, which differs markedly from my mother’s. However, this divergence in consensual solidarity—marked by variations in attitudes, beliefs, and values—does not translate into weakened affectual solidarity, characterized by positive sentiments and emotions. Furthermore, aided by advancements in transportation and social media technology, I have been able to extend crucial emotional and some “instrumental” care to my mother, along with financial support if needed, despite limited hands-on care. Nevertheless, I must negotiate my care for my mother and navigate a delicate balance in coordinating my care efforts with those of my non-migrant siblings. Full article

The visitor economy is responsible for a substantial percentage of the global carbon footprint. The mechanisms used to decarbonize it are insufficient, and the industry is relying on carbon trading with substandard credits that allow businesses to outsource the responsibility to decarbonize. We aim to transform carbon markets, help finance climate investments, and support decarbonization strategies. We identify and define the problem, outline the components and their interactions, and develop a conceptual model to transform carbon markets. The new, blockchain-based Carbon Tokenomics Model rolls out a decentralized database to store, trade, and manage carbon credits, with the goal of enabling sustainable climate finance investment. We outline the criteria needed for an industry-wide carbon calculator. We explain the process needed to increase rigor in climate investments in the visitor economy and introduce a delegated Proof of Commitment consensus mechanism. Our inclusive and transparent model illustrates how to reduce transaction costs and how to build consumer and industry trust, generating much-needed investments for decarbonization. Full article

Identifying the potential pollution sources of surface water pollutants is essential for the management and protection of regional water environments in drinking water source areas. In this study, absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models were applied to assess water quality and identify the potential pollution sources affecting the surface water quality of Xin’an River Basin. For this purpose, a 10-year (2011–2020) dataset of eight water quality indicators (including pH, EC, DO, COD, NH₃-N, TN, TP, and FC) covering eight monitoring stations and 7248 monthly observations was used. The results indicated that Pukou section had the worst water quality among the eight monitoring stations, and TN was the most serious water quality index. Both the APCS-MLR and PMF models identified agricultural nonpoint source pollution, urban nonpoint source pollution and rural domestic pollution, and meteorological factors. The sum of these three sources was very close, accounting for 60% and 58%, respectively. The APCS-MLR results demonstrated that for EC, COD, and NH₃-N, the major pollution sources were urban nonpoint sources and rural domestic pollution. The major contamination source of TN was agricultural nonpoint source pollution (30.4%). Meanwhile, the major pollution sources of pH, DO, TP, and FC were unidentified factors. The PMF model identified five potential sources, and pH and DO were affected by meteorological factors. NH₃-N and TP were influenced mainly by agricultural nonpoint source pollution. Atmospheric deposition was the major pollution source (87.9%) of TN. FC was mostly derived from livestock and poultry breeding (88.3%). EC and COD were mostly affected by urban nonpoint sources and rural domestic pollution. Therefore, receptor models can help managers identify the major sources of pollution in watersheds, but the major factors affecting different pollutants need to be supplemented by other methods. Full article

For the convenience of comparison with previous literature, the gravity calculations are revisited for the Asteroid 4769 Castalia, but with extensions on its surface and on intersecting planes and spheres around it, using the polyhedron and harmonic expansion methods with different order and degree for different cases, especially including the gravitational accelerations inside the asteroid, which did not appear at all before. In these evaluations, a few different facts of the these methods and results are revealed, such as the fact that gravity diverges when the position radius is less than the mean radius from harmonic-expansion method, and the maximum gravity is not at the deep valley and mountain top. For a surface that intersects the asteroid, the maximum gravity on it is at the intersection lines between the asteroid surface and the spheres or planes. This means that on the sphere and the plane, the gravities inside and outside the asteroid are smaller than the gravity on the intersection, i.e., on the surface. Some analyses of these conclusions are given with many examples with different radii of the sphere and with different order and degree harmonic expansion models for the above asteroid surface and surrounding spheres. It is interesting to note that very few researchers know that the polyhedral method can also be used to calculate the gravity inside an asteroid with just some modifications of the code. Some special gravity figures on surface and planes inside the asteroid Castalia are computed and made for the first time. The calculations also include tangential gravity, potential, and gravitational slope on surface. Specifically, we find that the overall mean gravitational slope could be one kind of indicator of the density of an asteroid. The minimum overall mean slope happens when the asteroid density is about 2.9 g/cm³, which is much larger than a usually assumed value between 1.7 and 2.5 for asteroid Castalia when its period is 4.07 h, since rotation period should be a more accurate parameter than its estimated density. These conclusions about this typical prolate-like asteroid could be a benchmark for analyzing other similar asteroids. Full article

In the global apiculture industry, reward feeding and supplementary feeding are essential for maintaining bee colonies. Beekeepers provide artificial supplements to their colonies, typically in the form of either a honey–water solution or sugar syrup. Owing to cost considerations associated with beekeeping, most beekeepers opt for sugar syrup. However, the effects of different types of artificial sugar supplements on bee colonies and their subsequent impact on honey composition remain unclear. To address this gap, this study compared the chemical composition, antioxidant capacity, and nutritional potency of three types of honey: honey derived from colonies fed sugar syrup (sugar-based product, SP) or a honey–water solution (honey-sourced honey, HH) and naturally sourced honey (flower-sourced honey, FH), which served as the control. The results revealed that FH outperformed HH and SP in terms of total acidity, sugar content, total protein content, and antioxidant capacity, and HH outperformed SP. Regarding nutritional efficacy, including the lifespan and learning and memory capabilities of worker bees, FH exhibited the best outcomes, with no significant differences observed between HH and SP. This study underscores the importance of sugar source selection in influencing honey quality and emphasizes the potential consequences of substituting honey with sugar syrup in traditional apiculture practices. Full article

The integration of 3D laser scanning and digital photogrammetry in the architecture, engineering, and construction (AEC) industry has facilitated high-quality architectural surveys. However, the processes remains constrained by significant costs, extensive manual labor, and accuracy issues associated with manual data processing. This article addresses these operational challenges by introducing automated Building Information Modeling (BIM) techniques that minimize manual input through the use of Dynamo for Autodesk Revit. We developed algorithms that efficiently convert point cloud data into accurate BIM models, enhancing productivity and reducing the potential for errors. The application of these algorithms is analyzed in a case study of the Old Lifeguard Station of Fuseta, showcasing notable reductions in modeling time and improvements in accuracy. The findings suggest that automated scan-to-BIM methods could provide a viable solution for enhancing BIM workflows across the industry, with the potential for wider adoption given their impact on efficiency and model quality. Full article

To address issues with excessive displacement, deformation, and insufficient load bearing capacity in high-fill-reinforced soil-retaining walls, a novel reinforced soil–frame anchor combination system was developed. Despite the limited existing research on its mechanical properties and synergy, a physical model test was conducted to investigate the system’s behavior. The test focused on the horizontal displacement of the frame beam wall, grid strain, wall back earth pressure, and anchor strain. Results indicated that anchor prestress effectively controlled horizontal deformation, limiting it to 65% of the original displacement value. Additionally, as the top load increased, strain in the bottom bars showed minor changes, while strain in the middle and upper bars exhibited significant sensitivity to load variations. The application of anchor prestress reduced strain in each reinforcement layer, enhancing the geogrid’s load bearing capacity. Furthermore, anchor prestress altered the distribution of earth pressure within the system, establishing a synergistic relationship between reinforced soil and frame beam anchors. This stress transfer mechanism improved overall system performance, as demonstrated in the test. Overall, the study confirmed the benefits and superior performance of the combined system. Full article

The presence of mutagenic and carcinogenic N-nitrosamine impurities in medicinal products poses a safety risk. While incorporating antioxidants in formulations is a potential mitigation strategy, concerns arise regarding their interference with drug absorption by inhibiting intestinal drug transporters. Our study screened thirty antioxidants for inhibitory effects on key intestinal transporters—OATP2B1, P-gp, and BCRP in HEK-293 cells (OATP2B1) or membrane vesicles (P-gp, BCRP) using ³H-estrone sulfate, ³H-N-methyl quinidine, and ³H-CCK8 as substrates, respectively. The screen identified that butylated hydroxyanisole (BHA) and carnosic acid inhibited all three transporters (OATP2B1, P-gp, and BCRP), while ascorbyl palmitate (AP) inhibited OATP2B1 by more than 50%. BHA had IC₅₀ values of 71 ± 20 µM, 206 ± 14 µM, and 182 ± 49 µM for OATP2B1, BCRP, and P-gp, respectively. AP exhibited IC₅₀ values of 23 ± 10 µM for OATP2B1. The potency of AP and BHA was tested with valsartan, an OATP2B1 substrate, and revealed IC₅₀ values of 26 ± 17 µM and 19 ± 11 µM, respectively, in HEK-293-OATP2B1 cells. Comparing IC₅₀ values of AP and BHA with estimated intestinal concentrations suggests an unlikely inhibition of intestinal transporters at clinical concentrations of drugs formulated with antioxidants. Full article

Background: High dietary diversity has been found to be associated with frailty. However, the trajectory of dietary diversity intake in relation to frailty is unclear. Methods: Using the latent class trajectory modeling approach, we identified distinctive dietary variety trajectory groups among 2017 participants based on the Chinese Longitudinal Healthy Longevity Survey acquired at four time points within a 10-year period. Frailty status was assessed using a frailty index comprising 37 health deficits. Dietary diversity was quantified using the dietary variety score (DVS), based on food category consumption frequency. Logistic regression analyses were employed to explore the association between DVS change trajectories and frailty. Results: This study identified two distinct DVS trajectories: “Moderate-Slow decline-Slow growth”, encompassing 810 (40.16%) individuals, and “Moderate-Slow growth-Accelerated decline”, including 1207 (59.84%) individuals. After adjusting for covariates, the odds ratio for DVS in the “Moderate-Slow decline-Slow growth” group was 1.326 (95% confidence interval: 1.075–1.636) compared to the “Moderate-Slow growth-Accelerated decline” group. The “Moderate-Slow decline-Slow growth” trajectory continued to decrease and was maintained at a low level in the early stages of aging. Conclusion: Sustaining a high dietary diversity trajectory over time, particularly in the early stages of aging, could potentially decrease the risk of frailty among older Chinese adults. Full article

Histone deacetylases (HDACs) are crucial in gene transcription, removing acetyl groups from histones. They also influence the deacetylation of non-histone proteins, contributing to the regulation of various biological processes. Thus, HDACs play pivotal roles in various diseases, including cancer, neurodegenerative disorders, and inflammatory conditions, highlighting their potential as therapeutic targets. This paper reviews the structure and function of the four classes of human HDACs. While four HDAC inhibitors are currently available for treating hematological malignancies, numerous others are undergoing clinical trials. However, their non-selective toxicity necessitates ongoing research into safer and more efficient class-selective or isoform-selective inhibitors. Computational methods have aided the discovery of HDAC inhibitors with the desired potency and/or selectivity. These methods include ligand-based approaches, such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure–activity relationships, and structure-based virtual screening (molecular docking). Moreover, recent developments in the field of molecular dynamics simulations, combined with Poisson–Boltzmann/molecular mechanics generalized Born surface area techniques, have improved the prediction of ligand binding affinity. In this review, we delve into the ways in which these methods have contributed to designing and identifying HDAC inhibitors. Full article

Phenylketonuria is an inherited metabolic disorder that leads to neurobehavioral dysfunction. The main treatment is a low-phenylalanine diet and/or the cofactor tetrahydrobiopterin. Regular outpatient follow-up care and measurement of the phenylalanine levels in the blood are required. We aimed to analyze the economic burden of phenylketonuria on families and the state. The patients with phenylketonuria were divided into three groups according to their treatment: a low-phenylalanine diet group (n = 50), a tetrahydrobiopterin group (n = 44), and a group taking tetrahydrobiopterin together with the diet (n = 25). A comparative cost analysis was carried out. The annual economic burden to the state was calculated to average EUR 18,801 ± 15,345 and was lowest in the diet group, then in the tetrahydrobiopterin group, and highest in the tetrahydrobiopterin + diet group (p < 0.001). Out-of-pocket costs amounted to EUR 1531 ± 1173 per year, and indirect losses averaged EUR 2125 ± 1930 per year for all families. The economic loss was significantly lower in the families taking tetrahydrobiopterin than in the other groups (p = 0.001). The combined use of medical nutrition and BH4 treatments has been shown to increase the economic burden on the state. Reimbursing low-protein products and increasing the number of patients eligible for financial allowances may reduce the economic burden on families. Full article

Artificial Intelligence (AI) has revolutionized the management of non-small-cell lung cancer (NSCLC) by enhancing different aspects, including staging, prognosis assessment, treatment prediction, response evaluation, recurrence/prognosis prediction, and personalized prognostic assessment. AI algorithms may accurately classify NSCLC stages using machine learning techniques and deep imaging data analysis. This could potentially improve precision and efficiency in staging, facilitating personalized treatment decisions. Furthermore, there are data suggesting the potential application of AI-based models in predicting prognosis in terms of survival rates and disease progression by integrating clinical, imaging and molecular data. In the present narrative review, we will analyze the preliminary studies reporting on how AI algorithms could predict responses to various treatment modalities, such as surgery, radiotherapy, chemotherapy, targeted therapy, and immunotherapy. There is robust evidence suggesting that AI also plays a crucial role in predicting the likelihood of tumor recurrence after surgery and the pattern of failure, which has significant implications for tailoring adjuvant treatments. The successful implementation of AI in personalized prognostic assessment requires the integration of different data sources, including clinical, molecular, and imaging data. Machine learning (ML) and deep learning (DL) techniques enable AI models to analyze these data and generate personalized prognostic predictions, allowing for a precise and individualized approach to patient care. However, challenges relating to data quality, interpretability, and the ability of AI models to generalize need to be addressed. Collaboration among clinicians, data scientists, and regulators is critical for the responsible implementation of AI and for maximizing its benefits in providing a more personalized prognostic assessment. Continued research, validation, and collaboration are essential to fully exploit the potential of AI in NSCLC management and improve patient outcomes. Herein, we have summarized the state of the art of applications of AI in lung cancer for predicting staging, prognosis, and pattern of recurrence after treatment in order to provide to the readers a large comprehensive overview of this challenging issue. Full article