Asymptotic analysis for an elastic layer under light fluid loading was developed. The ratio of fluid and solid densities was chosen as the main small parameter determining a novel scaling. The leading- and next-order approximations were derived from the full dispersion relation corresponding to long-wave, low-frequency, antisymmetric motions. The asymptotic plate models, including the equations of motion and the impenetrability condition, motivated by the aforementioned shortened dispersion equations, were derived for a plane-strain setup. The key findings included, in particular, the necessity of taking into account transverse plate inertia at the leading order, which is not the case for heavy fluid loading. In addition, the transverse shear deformation, rotation inertia, and a number of other corrections appeared at the next order, contrary to the previous asymptotic developments for fluid-loaded plates not assuming a light fluid loading scenario. Full article

This paper investigates the interfacial bonding behavior between high toughness resin concrete with steel wire mesh (HTRCS) and concrete. A total of five sets of fifteen double shear specimens were tested for parameters including concrete strength and material properties of HTRCS composites. The test results showed that the failure mode of DS1 specimens was partial debonding and fracture, and the rest of the specimens were the fracture of HTRCS. The concrete strength and reinforcement ratios of HTRCS composites were positively correlated with interfacial adhesion properties. When the concrete strength was increased from C30 to C40 and C50, the ultimate load increased by 43.4% and 43.2%, respectively. The ultimate load capacity increased by 32.1%, with the reinforcement ratio of HTRCS composites increasing from 1.05% to 1.83%. Moreover, the bonding slip model and the bearing capacity formula for the interface between HTRCS composites and concrete were proposed, and the calculation values were in good agreement with the test values, with an average value of 0.978. Full article

Cnidium monnieri fructus is widely used in traditional Oriental medicine for treating female genital disorders, male impotence, frigidity, and skin-related conditions in East Asia. However, the role of C. monnieri fructus extract (CMFE) in melanin synthesis is not well elucidated. This study aimed to investigate the anti-melanogenesis effect and mechanism of action of CMFE in α-MSH-stimulated B16F10 cells. Intracellular melanin content and tyrosinase activity were measured in α-MSH-stimulated B16F10 cells treated with various concentrations of CMFE (0.5–5 μg/mL). mRNA and protein levels of tyrosinase and MITF were evaluated using qRT-PCR and ting. CMFE’s effect on the proteasomal degradation of tyrosinase was confirmed using a proteasomal degradation inhibitor, MG132. CMFE treatment activated p38, a protein associated with proteasomal degradation. Treatment with CMFE at up to 5 μg/mL showed no significant cytotoxicity. CMFE significantly reduced α-MSH-stimulated melanin production (43.29 ± 3.55% decrease, p < 0.05) and cellular tyrosinase activity (31.14 ± 3.15% decrease, p < 0.05). Although mRNA levels of MITF and tyrosinase increased, CMFE suppressed tyrosinase protein levels. The suppressive effect of CMFE on tyrosinase protein was blocked by MG132. CMFE inhibited melanogenesis by promoting the proteasome degradation of tyrosinase through p38 activation. These findings suggest that CMFE has the potential to be a natural whitening agent for inhibiting melanogenesis. Full article

Polarimetric features extracted from polarimetric synthetic aperture radar (PolSAR) images contain abundant back-scattering information about objects. Utilizing this information for PolSAR image classification can improve accuracy and enhance object monitoring. In this paper, a deep learning classification method based on polarimetric channel power features for PolSAR is proposed. The distinctive characteristic of this method is that the polarimetric features input into the deep learning network are the power values of polarimetric channels and contain complete polarimetric information. The other two input data schemes are designed to compare the proposed method. The neural network can utilize the extracted polarimetric features to classify images, and the classification accuracy analysis is employed to compare the strengths and weaknesses of the power-based scheme. It is worth mentioning that the polarized characteristics of the data input scheme mentioned in this article have been derived through rigorous mathematical deduction, and each polarimetric feature has a clear physical meaning. By testing different data input schemes on the Gaofen-3 (GF-3) PolSAR image, the experimental results show that the method proposed in this article outperforms existing methods and can improve the accuracy of classification to a certain extent, validating the effectiveness of this method in large-scale area classification. Full article

Collaborative multicenter research has significantly increased our understanding of fetal Ebstein anomaly, delineating risk factors for adverse outcomes as well as predictors of postnatal management. These data are incorporated into prenatal care and therapeutic strategies and inform family counseling and delivery planning to optimize care. This report details the translation of findings from multicenter studies into multidisciplinary prenatal care for a fetus with Ebstein anomaly, supraventricular tachycardia, and a circular shunt, including transplacental therapy to control arrhythmias and achieve ductal constriction, informed and coordinated delivery room management, and planned univentricular surgical palliation. Full article

This paper introduces a unique finite element analysis (FEA) technique designed to predict spring-back behaviour in polymer matrix composites (PMCs). Extensive research has been conducted to model the manufacturing process of multiple ‘L’-shaped components, fabricated from SPRINT^TM materials (GLP 43 and GLP 96) at two thicknesses (15 mm and 25 mm). Three distinct FEA methodologies were utilised to determine the impact of thermal loads and rigid fixtures. An error deviation of 3.23% was recorded when comparing simulation results to experimental data, thereby validating the effectiveness of the FEA methodology. Full article

Recently, due to physical aging, diseases, accidents, and other factors, the population with lower limb disabilities has been increasing, and there is consequently a growing demand for wheelchair products. Modern product design tends to be more intelligent and multi-functional than in the past, with the popularization of intelligent concepts. This supports the design of a new, fully functional, intelligent wheelchair that can assist people with lower limb disabilities in their day-to-day life. Based on the UCD (user-centered design) concept, this study focused on the needs of people with lower limb disabilities. Accordingly, the demand for different functions of intelligent wheelchair products was studied through a questionnaire survey, interview survey, literature review, expert consultation, etc., and the function and appearance of the intelligent wheelchair were then defined. A brain–machine interface system was developed for controlling the motion of the intelligent wheelchair, catering to the needs of disabled individuals. Furthermore, ergonomics theory was used as a guide to determine the size of the intelligent wheelchair seat, and eventually, a new intelligent wheelchair with the features of climbing stairs, posture adjustment, seat elevation, easy interaction, etc., was developed. This paper provides a reference for the design upgrade of the subsequently developed intelligent wheelchair products. Full article

As ESG (environmental, social, and corporate governance) is consistent with the spirit of sustainable development, it is useful to elevate ESG performance to realize the sustainable development of enterprise and society. Using the data of Chinese A-share listed firms in the period of 2011 to 2019, this paper takes the National Big Data Comprehensive Pilot Zone policy as a quasi-natural experiment and uses the difference-in-differences method to assess the effect of digital economy development on ESG performance. This paper reveals the following: (1) the digital economy can facilitate ESG performance; (2) digitalization of the economy helps enterprises to propel digital transformation, which in turn lifts ESG performance; (3) digital economy development has a deeper impact on private enterprises, especially for those in China’s capital cities; and (4) digital economy development moderates the inhibiting effect of ESG performance on corporate financial constraints. The findings of this paper indicate that digitalization of the economy can help to achieve sustainable development. Full article

Background: This investigation assesses the prognostic value of lactate levels and their clearance in septic shock patients, particularly emphasizing the comparative analysis between COVID-19 and non-COVID-19 patients in the emergency department. This study aims to elucidate the unique prognostic implications of lactate dynamics in these distinct patient groups, thereby enhancing the management of septic shock. Methods: An observational prospective study was conducted, enrolling 114 septic shock patients from the Emergency County Hospital Resita, Romania, categorizing them into COVID-19 and non-COVID-19 groups to examine their initial lactate levels, clearance rates, and their correlation with patient outcomes. Results: This study identified significant differences in the initial lactate levels and clearance rates between the two groups, indicating higher initial lactate levels and slower clearance rates in COVID-19 patients. Survivors demonstrated significantly lower initial lactate levels (1.5 ± 0.4 mmol/L) and higher lactate clearance rates (33 ± 15%) compared to non-survivors (2.5 ± 0.5 mmol/L and 24 ± 9%, respectively; lactate levels p = 0.001, clearance rates p = 0.002). Conclusions: Lactate monitoring, particularly clearance rates, is crucial in the prognostic assessment of septic shock patients. These findings highlight the need for targeted interventions in COVID-19 patients to improve outcomes, underscoring lactate dynamics as a vital component of septic shock management in differing patient populations. Full article

Despite notable achievements in the development and application of the remediation of metal-contaminated soils, the search for and study of promising immobilizing agents continues. This article presents a new approach to using brown coal and activated carbon and their application for metal stabilization. An experiment was conducted to test Medicago falcata L. on soils from industrial areas contaminated with varying levels of lead (Pb), cadmium (Cd), chromium (Cr), zinc (Zn), copper (Cu), and nickel (Ni) with the addition of carbons. This plant is a stress-tolerant leguminous species. In this study, the total content of metals in soil and the available forms to plants (single extractions with 0.02 M ethylenediaminetetraacetic acid, EDTA) were determined, along with metal contents in the plant. The use of carbons lowered the phytoavailable forms of metals for plants and thus, resulted in a reduction in the phytotoxicity of the soils. The contents of the tested metals in the roots and shoots were lower than in the combinations of soils with no carbon added. The activated carbon had a stronger effect on limiting the availability of metals than brown coal in relation to plants growing on soils without added carbon; the percentage of reduction for the shoots was Cr (18.2%) > Zn (11.5%) > Ni (10.7%) > Cu (10.3%) > Cd (8.9%) > Pb (2.4%) and Cu (13.3%) > Cr (12.5%) > Zn (10.5%) > Pb (9.0%) > Ni (5.7%) > Cd (4.6%) for roots. Metals reduced the growth of Medicago falcata L. roots from 44 to 21%, while the growth of shoots was reduced from 25 to 2%. Adding carbons to soils in all combinations resulted in a decrease in the following pollution indices: pollution index (PI), pollution load index (PLI), and non-carcinogenic (HQ) and carcinogenic risk factors (ILCR). Full article

Agroecology integrates science, social movements, and agricultural practices, playing a central role in the sustainability of food systems. It addresses agroecosystems and food systems holistically; however, defining whether a farm is agroecological remains a challenge. This article proposes a methodology to measure farms’ agroecological performance, adapted to the family farming context in Portugal. The aim of the developed methodology is to compare the agroecological performance of family farms (conventional and non-conventional), providing information about anchors for agroecological transition and supporting public policies. A literature review identified existing farm evaluation methodologies, with Tool for Agroecological Performance Evaluation (TAPE) and Agroecology Criteria Tool (ACT) scoring highest in an assessment process. Questions from both were integrated into a questionnaire for family farmers. This field work provided critical insights towards the methodologies: (1) territorial adaptability; (2) transition constraints’ origin; and (3) use of non-academic language. The results were incorporated into the developed methodology, which combines the TAPE indicator matrix and Gliessman’s five levels of food system change, the latter of which provides the framework for the ACT. This study made it possible to identify the most relevant aspects for characterizing family farmers/farms and the importance of how the evaluation criteria/indicators are ordered by element/theme, as it alters the values of each farm’s agroecological performance. Full article

This study explores an approach to design and prepare a multilayer scaffold mimicking interstratified natural tissue. This multilayer construct, composed of chitosan matrices with graded nanohydroxyapatite concentrations, was achieved through an in situ biomineralization process applied to individual layers. Three distinct precursor concentrations were considered, resulting in 10, 20, and 30 wt% nanohydroxyapatite content in each layer. The resulting chitosan/nanohydroxyapatite (Cs/n-HAp) scaffolds, created via freeze-drying, exhibited nanohydroxyapatite nucleation, homogeneous distribution, improved mechanical properties, and good cytocompatibility. The cytocompatibility analysis revealed that the Cs/n-HAp layers presented cell proliferation similar to the control in pure Cs for the samples with 10% n-HAp, indicating good cytocompatibility at this concentration, while no induction of apoptotic death pathways was demonstrated up to a 20 wt% n-Hap concentration. Successful multilayer assembly of Cs and Cs/n-HAp layers highlighted that the proposed approach represents a promising strategy for mimicking multifaceted tissues, such as osteochondral onse. Full article

We reveal the continuous change of information dynamics patterns in anyonic-PT symmetric systems that originates from the continuity of anyonic-PT symmetry. We find there are three information dynamics patterns for anyonic-PT symmetric systems: damped oscillations with an overall decrease (increase) and asymptotically stable damped oscillations, which are three-fold degenerate and are distorted using the Hermitian quantum Rényi entropy or distinguishability. It is the normalization of the non-unitary evolved density matrix that causes the degeneracy and distortion. We give a justification for non-Hermitian quantum Rényi entropy being negative. By exploring the mathematics and physical meaning of the negative entropy in open quantum systems, we connect negative non-Hermitian quantum Rényi entropy and negative quantum conditional entropy, paving the way to rigorously investigate negative entropy in open quantum systems. Full article

In the study of the deep learning classification of medical images, deep learning models are applied to analyze images, aiming to achieve the goals of assisting diagnosis and preoperative assessment. Currently, most research classifies and predicts normal and cancer cells by inputting single-parameter images into trained models. However, for ovarian cancer (OC), identifying its different subtypes is crucial for predicting disease prognosis. In particular, the need to distinguish high-grade serous carcinoma from clear cell carcinoma preoperatively through non-invasive means has not been fully addressed. This study proposes a deep learning (DL) method based on the fusion of multi-parametric magnetic resonance imaging (mpMRI) data, aimed at improving the accuracy of preoperative ovarian cancer subtype classification. By constructing a new deep learning network architecture that integrates various sequence features, this architecture achieves the high-precision prediction of the typing of high-grade serous carcinoma and clear cell carcinoma, achieving an AUC of 91.62% and an AP of 95.13% in the classification of ovarian cancer subtypes. Full article

The production of flue gas desulfurization gypsum poses a serious threat to the environment. Thus, utilizing gypsum-based self-leveling mortar (GSLM) stands out as a promising and effective approach to address the issue. β-hemihydrate gypsum, cement, polycarboxylate superplasticizer, hydroxypropyl methyl cellulose ether (HPMC), retarder, and defoamer were used to prepare GSLM. The impact of mineral admixtures (steel slag (SS), silica fume (SF), and fly ash (FA)) on the physical, mechanical, and microstructural properties of GSLM was examined through hydration heat, X-ray diffractometry (XRD), Raman spectroscopy, and scanning electron microscopy (SEM) analyses. The GSLM benchmark mix ratio was determined as follows: 94% of desulfurization building gypsum, 6% of cement, 0.638% each of water reducer and retarder, 0.085% each of HPMC and defoamer (calculated additive ratio relative to gypsum), and 0.54 water-to-cement ratio. Although the initial fluidity decreased in the GSLM slurry with silica fume, there was minimal change in 30 min fluidity. Notably, at an SS content of 16%, the GSLM exhibited optimal flexural strength (6.6 MPa) and compressive strength (20.4 MPa). Hydration heat, XRD, and Raman analyses revealed that a small portion of SS actively participated in the hydration reaction, while the remaining SS served as a filler. Full article

Although the effect of campus landscape space on stress relief among college students has been confirmed, few existing studies have considered the impact on stress recovery from the perspective of factor combination, and the key visual elements and the most effective combination of visual elements to relieve stress are still unclear. This study attempts to conduct a natural experiment within Chinese campuses, measuring physiological indicators of stress such as heart rate (HR), frequency domain index of heart rate variability (LF/HF), skin conductance level (SCL), skin temperature (SKT), and respiratory rate (RESP) using physiological instruments. It explored the effects of visual elements and their combinations in campus landscape spaces on short-term stress relief among college students through semantic segmentation, multifactorial analysis of variance, and post hoc multiple comparison methods. Research results demonstrate that the presence of water elements in the field of vision can effectively improve the stress relief effects of landscape spaces. Reasonable combinations of natural landscape elements and artificial landscape elements in the design can also effectively promote stress relief among students. Building facade area and sky area, water area and sky area, and plant species and pavement area are three combinations of factors with the strongest interactive effects. “Natural water scenery” and “exquisite artificial” are two campus landscape design patterns most conducive to short-term stress relief. Full article

We studied the effects of vertical vibrations on a water drop that was pinned to the sharp edges of a rectangular post. By varying the frequency and amplitude of the vertical displacement, distinct resonance peaks were observed using a simple optical technique. The vibrational spectra of the first two modes exhibited two closely spaced peaks, which corresponded to standing waves that exist along the major and minor contour lengths of the drops. The values of the resonance frequencies can be explained rather well by a simple model, which was originally proposed for axially symmetric drops. Full article

New oral tablets of nebivolol have been developed aiming to improve, by cyclodextrin (CD) complexation, its low solubility/dissolution properties—the main reason behind its poor/variable oral bioavailability. Phase-solubility studies, performed using βCD and highly-soluble βCD-derivatives, indicated sulfobutylether-βCD (SBEβCD) as the best solubilizing/complexing agent. Solid drug-SBEβCD systems were prepared by different methods and characterized for solid-state and dissolution properties. The coevaporated product was chosen for tablet development since it provided the highest dissolution rate (100% increase in dissolved drug at 10 min) and almost complete drug amorphization/complexation. The developed tablets reached the goal, allowing us to achieve 100% dissolved drug at 60 min, compared to 66% and 64% obtained, respectively, with a reference tablet without CD and a commercial tablet. However, the percentage dissolved after 10 min from such tablets was only 10% higher than the reference. This was ascribed to the potential binding/compacting abilities of SBEβCD, reflected in the greater hardness and longer disintegration times of the new tablets than the reference (7.64 vs. 1.06 min). A capsule formulation with the same composition of nebivolol-SBEβCD tablets showed about a 90% increase in dissolved drug after 5 min compared to the reference tablet, and reached 100% dissolved drug after only 20 min. Full article

The study of dynamic singularity formation in spacetime, focusing on scalar field collapse models, is analyzed. We revisit key findings regarding open spatial topologies, concentrating on minimal conditions necessary for singularity and apparent horizon formation. Moreover, we examine the stability of initial data in the dynamical system governed by Einstein’s equations, considering variations in parameters that influence naked singularity formation. We illustrate how these results apply to a family of scalar field models, concluding with a discussion on the concept of genericity in singularity studies. Full article

Botulinum toxin (BoNT) injection can safely be done as an office-based procedure, but can be painful itself, especially when injecting pelvic floor muscles to treat chronic pelvic pain (CPP). Mindfulness interventions may reduce procedure-associated acute anxiety and pain. We applied mindfulness techniques to increase the tolerability of office-based pelvic floor BoNT injections in women with CPP. Women enrolled in a clinical trial of BoNT for endometriosis-associated CPP were offered a brief, guided mindfulness session before and/or after transvaginal injection. Anxiety, pain, and dysphoria were rated on a 0–10 numerical rating scale (NRS) before and after each mindfulness session. Eight women underwent mindfulness sessions. Five participants had a session before and two after the transvaginal injection. One participant had two sessions: one before and one after separate injections. All six women completing a session prior to injection had at least moderate anxiety, which lessened after the mindfulness session (median NRS change: −3.3/10). All three women reporting injection-associated pain experienced less intense pain following the post-injection session (median NRS change: −3/10). Three women experiencing dysphoria improved after the session (median NRS change: −3/10). A brief, guided mindfulness session may lessen acute pain, anxiety, and dysphoria associated with office-based transvaginal BoNT injection. Full article

The segmentation and localization of Agaricus bisporus is a precondition for its automatic harvesting. A. bisporus growth clusters can present challenges for precise localization and segmentation because of adhesion and overlapping. A low-cost image stitching system is presented in this research, utilizing a quick stitching method with disparity correction to produce high-precision panoramic dual-modal fusion images. An enhanced technique called Real-Time Models for Object Detection and Instance Segmentation (RTMDet-Ins) is suggested. This approach utilizes SimAM Attention Module’s (SimAM) global attention mechanism and the lightweight feature fusion module Space-to-depth Progressive Asymmetric Feature Pyramid Network (SPD-PAFPN) to improve the detection capabilities for hidden A. bisporus. It efficiently deals with challenges related to intricate segmentation and inaccurate localization in complex obstacles and adhesion scenarios. The technology has been verified by 96 data sets collected on a self-designed fully automatic harvesting robot platform. Statistical analysis shows that the worldwide stitching error is below 2 mm in the area of 1200 mm × 400 mm. The segmentation method demonstrates an overall precision of 98.64%. The planar mean positioning error is merely 0.31%. The method promoted in this research demonstrates improved segmentation and localization accuracy in a challenging harvesting setting, enabling efficient autonomous harvesting of A. bisporus. Full article

Neurofibromatosis type 1 (NF1) is an inherited autosomal dominant disorder primarily affecting children and adolescents characterized by multisystemic clinical manifestations. Mutations in neurofibromin, the protein encoded by the Nf1 tumor suppressor gene, result in dysregulation of the RAS/MAPK pathway leading to uncontrolled cell growth and migration. Neurofibromin is highly expressed in several cell lineages including melanocytes, glial cells, neurons, and Schwann cells. Individuals with NF1 possess a genetic predisposition to central nervous system neoplasms, particularly gliomas affecting the visual pathway, known as optic pathway gliomas (OPGs). While OPGs are typically asymptomatic and benign, they can induce visual impairment in some patients. This review provides insight into the spectrum and visual outcomes of NF1, current diagnostic techniques and therapeutic interventions, and explores the influence of NF1-OPGS on visual abnormalities. We focus on recent advancements in preclinical animal models to elucidate the underlying mechanisms of NF1 pathology and therapies targeting NF1-OPGs. Overall, our review highlights the involvement of retinal ganglion cell dysfunction and degeneration in NF1 disease, and the need for further research to transform scientific laboratory discoveries to improved patient outcomes. Full article