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Electrons and holes, fundamental charge carriers in semiconductors, dominate optical transitions and detection processes. Twisted van der Waals (vdW) heterostructures offer an effective approach to manipulate radiation, separation, and collection processes of electron-hole pairs by creating an atomically sharp interface. Here, we demonstrate that twisted interfaces in vdW layered black phosphorus (BP), an infrared semiconductor with highly anisotropic crystalline structure and properties, can significantly alter both recombination and separation processes of electron-hole pairs. On the one hand, the twisted interface breaks the symmetry of optical transition states resulting in infrared light emission of originally symmetry-forbidden optical states along the zigzag direction. On the other hand, spontaneous electronic polarization/bulk photovoltaic effect is generated at the twisted interface enabling effective separation of electron-hole pairs without external voltage bias. This is supported by first-principles calculations and repeated experiments at various twisted angles from 0 to 90°. Importantly, these phenomena can be observed in twisted heterostructures with thickness beyond two-dimensional. Our results suggest that the engineering of vdW twisted interfaces is an effective strategy for manipulating the optoelectronic properties of materials and constructing functional devices. Here, the authors report a study of the infrared optoelectronic properties of twisted 2D black phosphorus (BP), showing photoluminescence emission from optical transitions that are symmetry-forbidden in BP and spontaneous electronic polarization generating interfacial bulk photovoltaic effect. [ABSTRACT FROM AUTHOR]

Alzheimer's Disease (AD) is a neurodegenerative disorder, and various molecules associated with PANoptosis are involved in neuroinflammation and neurodegenerative diseases. This work aims to identify key genes, and characterize PANoptosis-related molecular subtypes in AD. Moreover, we establish a scoring system for distinguishing PANoptosis molecular subtypes and constructing diagnostic models for AD differentiation. A total of 5 hippocampal datasets were obtained from the Gene Expression Omnibus (GEO) database. In total, 1324 protein-encoding genes associated with PANoptosis (1313 apoptosis genes, 11 necroptosis genes, and 31 pyroptosis genes) were extracted from the GeneCards database. The Limma package was used to identify differentially expressed genes. Weighted Gene Co-Expression Network Analysis (WGCNA) was conducted to identify gene modules significantly associated with AD. The ConsensusClusterPlus algorithm was used to identify AD subtypes. Gene Set Variation Analysis (GSVA) was used to assess functional and pathway differences among the subtypes. The Boruta, Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithms were used to select the three PANoptosis-related Key AD genes (PKADg). A scoring model was constructed based on the Boruta algorithm. PANoptosis diagnostic models were developed using the RF, SVM-RFE, and Logistic Regression (LR) algorithms. The ROC curves were used to assess the model performance. A total of 48 important genes were identified by intersecting 725 differentially expressed genes and 2127 highly correlated module genes from WGCNA with 1324 protein-encoding genes related to PANoptosis. Machine learning algorithms identified 3 key AD genes related to PANoptosis, including ANGPT1, STEAP3, and TNFRSF11B. These genes had strong discriminatory capacities among samples, with Receiver Operating Characteristic Curve (ROC) analysis indicating Area Under the Curve (AUC) values of 0.839, 0.8, and 0.868, respectively. Using the 48 important genes, the ConsensusClusterPlus algorithm identified 2 PANoptosis subtypes among AD patients, i.e., apoptosis subtype and mild subtype. Apoptosis subtype patients displayed evident cellular apoptosis and severe functionality damage in the hippocampal tissue. Meanwhile, mild subtype patients showed milder functionality damage. These two subtypes had significant differences in apoptosis and necroptosis; however, there was no apparent variation in pyroptosis functionality. The scoring model achieved an AUC of 100% for sample differentiation. The RF PANoptosis diagnostic model demonstrated an AUC of 100% in the training set and 85.85% in the validation set for distinguishing AD. This study identified two PANoptosis-related hippocampal molecular subtypes of AD, identified key genes, and established machine learning models for subtype differentiation and discrimination of AD. We found that in the context of AD, PANoptosis may influence disease progression through the modulation of apoptosis and necrotic apoptosis. [ABSTRACT FROM AUTHOR]

Farmers' crop yields and prices are strongly affected by the market, and inadequate yields or poor product management will affect national food crop reserves and rural revitalization. Improving farmers' management capacity can reduce the market's influence on crop yields and prices, stabilize the market food supply and promote rural revitalization. This research is necessary for analyzing the mechanism through which relationship embeddedness affects farmers' management ability. To analyze farmers' management ability in depth, this study first introduces relational embeddedness to analyze the influencing mechanism of farmers' management ability. The second objective is to fill the gap in the literature on how relational embeddedness affects farmers' management ability and to study the role of social cognitive theory in farmers' learning behavior. Seven hypotheses are developed, and data from a questionnaire survey of 418 rural household members in three provinces of China are used. Structural equation modeling was used to test the relationship between variables using Amos 24.0. The research results show the following: (1) Relational embeddedness has a positive and significant impact on knowledge learning and resource acquisition. (2) Knowledge learning (β = 0.552, p < 0.001) and resource acquisition (β = 0.484, p < 0.001) have a positive and significant impact on the improvement of management capabilities. (3) The positive mediating effect of knowledge learning is greater than the positive mediating effect of resource acquisition. In the village where the farmer is located, local governments can carry out more technical training to improve farmers' knowledge and technology to more effectively improve farmers' management capabilities. In addition, farmers communicate with towns and cities through social relations; obtain more market information and product and equipment information; and learn market or product knowledge, thus improving their management ability. [ABSTRACT FROM AUTHOR]

Aquilaria sinensis is a significant resin-producing plant worldwide that is crucial for agarwood production. Agarwood has different qualities depending on the method with which it is formed, and the microbial community structures that are present during these methods are also diverse. Furthermore, the microbial communities of plants play crucial roles in determining their health and productivity. While previous studies have investigated the impact of microorganisms on agarwood formation, they lack comprehensiveness, particularly regarding the properties of the microbial community throughout the entire process from seedling to adult to incense formation. We collected roots, stems, leaves, flowers, fruits and other tissues from seedlings, healthy plants and agarwood-producing plants to address this gap and assess the dominant bacterial species in the microbial community structures of A. sinensis at different growth stages and their impacts on growth and agarwood formation. The bacteria and fungi in these tissues were classified and counted from different perspectives. The samples were sequenced using the Illumina sequencing platform, and sequence analyses and species annotations were performed using a range of bioinformatics tools to assess the plant community compositions. An additional comparison of the samples was conducted using diversity analyses to assess their differences. This research revealed that Listeria, Kurtzmanomyces, Ascotaiwania, Acinetobacter, Sphingobium, Fonsecaea, Acrocalymma, Allorhizobium, Bacillus, Pseudomonas, Peethambara, and Debaryomyces are potentially associated with the formation of agarwood. Overall, the data provided in this article help us understand the important roles played by bacteria and fungi in the growth and agarwood formation process of A. sinensis, will support the theoretical basis for the large-scale cultivation of A. sinensis, and provide a basis for further research on microbial community applications in agarwood production and beyond. [ABSTRACT FROM AUTHOR]

Large landslides can involve the multiple failures of regional slopes. To understand the effect of lateral thrust caused by the failure of one slope on its surroundings, the failures of two adjacent highway slopes in Guangdong Province, China, were investigated in detail. The interactive failure processes and landslide morphological characteristics of the two slopes were first analyzed based on the on-site investigation. Then, a plane mechanical model of a large-scale slope was established to evaluate the significant influence of the lateral thrust generated by the west slope acting on the east excavated slope. Furthermore, the extrusion effect of the west slope was modelled under the alternate excavation disturbance and rainfall by transferring the thrust forces onto the interface elements, and the induced failure mechanism and instability mode of the east slope under lateral thrust were reproduced numerically. The results show that the compression-shear failure occurred at the middle and rear slope bodies because of the lateral thrust, which led to the formation of a thrust landslide and the final instability of the east slope. [ABSTRACT FROM AUTHOR]

In practical engineering, noise and impact hazards are pervasive, indicating the pressing demand for materials that can absorb both sound and stress wave energy simultaneously. However, the rational design of such multifunctional materials remains a challenge. Herein, inspired by cuttlebone, we present bioinspired architected metamaterials with unprecedented sound-absorbing and mechanical properties engineered via a weakly-coupled design. The acoustic elements feature heterogeneous multilayered resonators, whereas the mechanical responses are based on asymmetric cambered cell walls. These metamaterials experimentally demonstrated an average absorption coefficient of 0.80 from 1.0 to 6.0 kHz, with 77% of the data points exceeding the desired 0.75 threshold, all with a compact 21 mm thickness. An absorptance-thickness map is devised for assessing the sound-absorption efficiency. The high-fidelity microstructure-based model reveals the air friction damping mechanism, with broadband behavior attributed to multimodal hybrid resonance. Empowered by the cambered design of cell walls, metamaterials shift catastrophic failure toward a progressive deformation mode characterized by stable stress plateaus and ultrahigh specific energy absorption of 50.7 J/g—a 558.4% increase over the straight-wall design. After the deformation mechanisms are elucidated, a comprehensive research framework for burgeoning acousto-mechanical metamaterials is proposed. Overall, our study broadens the horizon for multifunctional material design. Noise and impact hazards are pervasive in engineering, necessitating materials capable of absorbing both sound and stress wave energy. Here, we present bioinspired metamaterials with exceptional sound-absorbing and mechanical properties using a weakly-coupled design strategy. These materials incorporate multi-layered resonators for superior acoustic performance and cambered cell walls for enhanced structural strength. They achieve an average absorption coefficient of 0.80 across the 1.0 to 6.0 kHz range, all within a sleek 21 mm thickness. Furthermore, the design transitions failure modes from catastrophic to progressive, resulting in a remarkable 558.4% increase in energy absorption compared to conventional designs. [ABSTRACT FROM AUTHOR]

Reproductive toxicity is one of the important issues in chemical safety. Traditional laboratory testing methods are costly and time-consuming with raised ethical issues. Only a few in silico models have been reported to predict human reproductive toxicity, but none of them make full use of the topological information of compounds. In addition, most existing atom-based graph neural network methods focus on attributing model predictions to individual nodes or edges rather than chemically meaningful fragments or substructures. In current studies, we develop a novel fragment-based graph transformer network (FGTN) approach to generate the QSAR model of human reproductive toxicity by considering internal topological structure information of compounds. In the FGTN model, the compound is represented by a graph architecture using fragments to be nodes and bonds linking two fragments to be edges. A super molecule-level node is further proposed to connect all fragment nodes by undirected edges, obtaining global molecular features from fragment embeddings. The FGTN model achieved an accuracy (ACC) of 0.861 and an area under the receiver operating characteristic curve (AUC) value of 0.914 on nonredundant blind tests, outperforming traditional fingerprint-based machine learning models and atom-based GCN model. The FGTN model can attribute toxic predictions to fragments, generating specific structural alerts for the positive compound. Moreover, FGTN may also have the capability to distinguish various chemical isomers. We believe that FGTN can be used as a reliable and effective tool for human reproductive toxicity prediction in contribution to the advancement of chemical safety assessment. [ABSTRACT FROM AUTHOR]

The embryo of Volvox globator, a monolayer spheroidal cell sheet, undergoes an inversion to release its flagella during the late stage of its development. This inversion, known as the type-B inversion, initiates from the equator. Other types of inversions also exist, such as the inversion from the anterior pole of Volvox carteri and the bowl-shaped inversion of Pleodorina. These inversions can be regarded as axisymmetric processes, during which complex fold patterns are generated. The invagination of the cell sheet plays a crucial role in embryonic development, and our aim is to understand this process from an interdisciplinary point of view, with a particular focus on the mechanical aspects. In this work, we first develop a morphoelastic shell theory for general deformations of biological shells, incorporating both active and passive biomechanical effects, as well as membrane and bending effects. By means of asymptotic analysis, we establish an analytical framework to study axisymmetric deformations of morphoelastic shells focusing mainly on the membrane effects. For illustrative purposes, we apply this framework to investigate the invagination of Volvox globator embryo. The underlying active stretches driving this process are derived analytically by inverse analysis of experimental data through the morphoelastic shell model. We highlight a two-order remodeling strategy that generates the observed invagination pattern: the Gaussian morphing of the cell sheet creates the first fundamental form of the stress-free folded patterns, while a secondary remodeling generates the membrane tension necessary to balance the external pressure and the second fundamental form of the invaginated pattern. This remodeling strategy unveils the complex interplay between geometry, mechanics, and biological processes during Volvox globator embryogenesis. [ABSTRACT FROM AUTHOR]

Collecting data such vibration signal or others from elevators is crucial for a regular maintenance or emergency repair in industry. However, traditional methods for data transmission through compression and decompression process usually require large input data arrays to be assigned. Therefore, a long computational time is unavoidable so that it may affect system performance efficiency significantly. Therefore, an elevator vibration and loading data collection system was developed using simple compression encoding mechanism. First, in Data Acquisition Unit, the signal-acquiring microprocessor is used for data acquisition through Inter-Integrated Circuit (I2C) bus. Second, in Data Storage Unit, the collected data from the signal-acquiring microprocessor is compressed and transmitted to the signal-processing microprocessor. Third, in Monitor Unit, the elevator analysis tool is developed to analyze the vibration data, which can be viewed directly from APP. Experimental results demonstrated that the restored data are consistent with the results measured from the standard instrument. The proposed hexadecimal compression process can make the data transmission mechanism simple, but two times faster than that using traditional way without compression. Consequently, the demanded memory capacity for signal transmission can be therefore reduced considerably. [ABSTRACT FROM AUTHOR]

Inferior vena cava filter (IVCF) implantation is a common method of thrombus capture. By implanting a filter in the inferior vena cava (IVC), microemboli can be effectively blocked from entering the pulmonary circulation, thereby avoiding acute pulmonary embolism (PE). Inspired by the helical flow effect in the human arterial system, we propose a helical retrievable IVCF, which, due to the presence of a helical structure inducing a helical flow pattern of blood in the region near the IVCF, can effectively avoid the deposition of microemboli in the vicinity of the IVCF while promoting the cleavage of the captured thrombus clot. It also reduces the risk of IVCF dislodging and slipping in the vessel because its shape expands in the radial direction, allowing its distal end to fit closely to the IVC wall, and because its contact structure with the inner IVC wall is curved, increasing the contact area and reducing the risk of the vessel wall being punctured by the IVCF support structure. We used ANSYS 2023 software to conduct unidirectional fluid–structure coupling simulation of four different forms of IVCF, combined with microthrombus capture experiments in vitro, to explore the impact of these four forms of IVCF on blood flow patterns and to evaluate the risk of IVCF perforation and IVCF dislocation. It can be seen from the numerical simulation results that the helical structure does have the function of inducing blood flow to undergo helical flow dynamics, and the increase in wall shear stress (WSS) brought about by this function can improve the situation of thrombosis accumulation to a certain extent. Meanwhile, the placement of IVCF will change the flow state of blood flow and lead to the deformation of blood vessels. In in vitro experiments, we found that the density of the helical support rod is a key factor affecting the thrombus trapping efficiency, and in addition, the contact area between the IVCF and the vessel wall has a major influence on the risk of IVCF displacement. [ABSTRACT FROM AUTHOR]

The water weakening effect refers to the gradual deterioration of soil mechanical properties under long-term saturation. This paper analyzed the impact of water weakening on slope stability under alternating excavation and rainfall. The field investigation speculated shale hydration as the cause of overall slope instability. The mechanical parameters of hydrated shale were determined by the parameter inversion and empirical estimation methods. The simulations were used to restore the process of parameter weakening and slope failure, and confirmed the fact that hydration causes landslide. Furthermore, the failure mechanism of slope and support structure under hydration were investigated. The results show that the mechanical parameters of the slope decreased linearly, whereas the plastic strain–time and total displacement-maximum shear stress curves of the hydrated shale exhibited three stages: slow initial growth, rapid growth in the middle term, and rapid increase in the later period; the rate of slope deformation and the factor of safety reduction also gradually increase over time; under middle stage of hydration, the middle to rear of shale were extruded, while the front first underwent tensile shear deformation, forming a plastic zone of at rear and front excavated slope; In the late stage, hydrated shale quickly reaches its yield limit (maximum shear stress of 270 kPa), the middle and rear shale is damaged and compresses the front, causing it to transform from tensile shear to compressive shear failure. The plastic zone in the rear extends forward and connects with the front ones, forming an overall landslide. Besides, preventing deep landslides caused by hydration through waterproofing, drainage, protection, and support for excavated slopes has proven difficult. Therefore, it is necessary to redesign treatment schemes based on the characteristics of stress, strain, and seepage. [ABSTRACT FROM AUTHOR]

The optical appearance of the numerically black hole solutions within the higher derivative gravity illuminated by an accretion disk context is discussed. We obtain solutions for non-Schwarzschild black holes with r 0 = 1 , r 0 = 2 , and r 0 = 3 . Further analysis of spacetime trajectories reveals properties similar to Schwarzschild black holes, while the r 0 = 2 black hole exhibits significant differences. The results reveal the presence of a repulsive potential barrier for the black hole, allowing only particles with energies exceeding a certain threshold to approach it, providing a unique gravitational scenario for non-Schwarzschild black holes. Additionally, the optical images are derived through numerical simulations by discussing the trajectories of photons in the black hole spacetime. The distribution of radiation flux and the effects of gravitational redshift and Doppler shift on the observed radiation flux are considered. Interestingly, previous analyses of the optical appearance of black holes were conducted within the framework of analytic solutions, whereas the analysis of numerical black hole solutions first appears in our analysis. [ABSTRACT FROM AUTHOR]

In order to study the influence of various design parameters on the ultimate load of the bias component of the pipe-roof pre-construction (PP) structure, a variable section steel-concrete-steel (VSSCS) bias component, incorporating studs, was designed, and a bias loading test conducted. The impact of component parameters on bearing capacity underwent further analysis using a finite element model, leading to the optimization of the PP structure and a revision of its bearing capacity calculation model. The following conclusions are obtained: 1) The failure mode of VSSCS bias components is mainly characterized by large eccentric tensile failure. 2) For each 1mm increase in steel plate thickness and each 5 Mpa enhancement in concrete strength, the maximum bearing capacity of the component correspondingly rises by 1.6%–10.9% and 6.4%–15.7%, respectively. 3) The strength and stiffness of the components are increased by 9.2%–13.1% and 18.1%–64.9% by adding stud connectors, respectively. [ABSTRACT FROM AUTHOR]

The rapid growth of textile industry and fast-fashion has led to the production of about 92 million ton of textile waste per year. Nearly 85% of textile waste is disposed of by landfill and incineration, causing serious environmental pollution and huge resource waste, calling for alternative textile production. Here we review the green production of textiles with focus on additive manufacturing, 3- and 4-dimension printing, recycling textile waste, and synthetic and natural fibers. Additive manufacturing technologies, particularly 4-dimension printing, is flexible, green, and allows on-demand manufacturing, which is one solution to the textile waste problem. 4-Dimension printing contributes to the development of intelligent materials, and can create structures that deform in response to external stimuli. Textile waste contains high-quality, low-cost materials that can be re-used and recycled. Applications include smart textiles, flexible electronics, soft robotics, human–computer interaction, and wearable devices. [ABSTRACT FROM AUTHOR]

Water conservation has become a global problem as the population increases. In many densely populated cities in China, leaks from century-old pipe works have been widespread. However, entirely eradicating the issues involves replacing all water networks, which is costly and time-consuming. This paper proposed an AI-enabled water-saving control system with three control modes: time division control, flow regulation, and critical point control according to actual flow. Firstly, based on the current leaking situation of water supply networks in China and the capability level of China's water management, a water-saving technology integrating PID control and a series of deep learning algorithms was proposed. Secondly, a multi-jet control valve was designed to control pressure and reduce water distribution network cavitation. This technology has been successfully applied in industrial settings in China and has achieved gratifying water-saving results. [ABSTRACT FROM AUTHOR]

We reported a case of atypical spinal tuberculosis on the posterior elements of lumbar spine in a 52-year-old female. It was easy to be misdiagnosed as spinal tumor due to its imaging characteristics. We performed puncture biopsy to initially consider tuberculosis, and then the patient was accepted surgical treatment. The intraoperative removed specimen was sent to pathological examination, microbial culture, Xpert MTB/RIF and metagenomic next-generation sequencing (mNGS) and then the diagnosis of neural arch tuberculosis was confirmed. After operation, the patient obtained stable effect by anti-tuberculosis drug treatment. In a word, the uncommon case had an important reference significance for the diagnosis of atypical spine tuberculosis and differentiation from spinal tumors. It is critical to make right preliminary diagnosis by appropriate examination as it determined the next diagnosis and treatment in special and rare clinical cases. [ABSTRACT FROM AUTHOR]

In this study, the evolution of grain and ripple structures on the surface of 6061 aluminum alloy (AA6061) parts fabricated by a laser-foil-printing (LFP) additive manufacturing process at different preheated temperatures were characterized and compared. Results indicated that the preheated temperature of the substrate plays a crucial role in the formation of grain structures, the shape of ripples, and the surface quality of aluminum parts fabricated by LFP. As the preheated temperature of the substrate elevated from room temperature to 300 °C, the grain and ripple structures formed coarser and flatter, respectively, due to the reduction in the thermal gradient and cooling rate. The grain structure was coarsened with an increasing average grain size from 74.96 to 150.5 μm measured by the electron backscattered diffraction (EBSD) technique. Meanwhile, the ripple structure was stretched and transformed from short and curved shapes to smoother, which improved the surface roughness significantly and reduced the Sa value from 21.7 to 8.5 μm in three-dimensional (3D) surface morphologies. However, when the preheated temperature reached 500 °C in LFP, the grain structure experienced a recrystallization process, resulting in the formation of finer grains compared to those observed at 300 °C. Furthermore, the surface quality was improved to a Sa value of 5.2 μm because the flowability of the melt pool was enhanced from the extended solidification time by the smallest temperature gradient and cooling rate at the highest preheat temperature, which was estimated using the finite element method (FEM). In the X-ray diffraction (XRD) patterns, the ratio of the main peak (200) to the secondary peak was gradually increased when preheated temperature elevated; however, the ratio decreased at 500 °C due to the recrystallization. [ABSTRACT FROM AUTHOR]

The purpose of this study is to optimize the critical parameters of the directed energy deposition (DED) process using the response surface methodology (RSM) and central composite design (CCD). The experiments investigate the influence of three key process factors, namely laser power, powder feed rate, and scanning speed, on deposition efficiency, deposition rate (DR), and porosity. Additionally, through analysis of variance (ANOVA), the significant factors and interaction effects are identified, and predictive models are developed for quality prediction. The research successfully optimizes the process parameters, which are validated through the fabrication of geometric components, specifically thin-walled nozzles. The study introduces innovative approaches such as "plunge-cutting toolpath" and "hybrid laser head lift height (Z-offset) method" to address the challenges associated with complex geometries. Additionally, the reliability and practicality of the optimized process parameters are confirmed. [ABSTRACT FROM AUTHOR]

Using a model of an accretion disk around a Schwarzschild black hole, the analytic estimates for image polarization were derived by Narayan et al. (Astrophys J 102:912, 2021). Recently, the EHT team also obtained polarization images of the Sgr A ∗ and measured both linear and circular polarization (Astrophys J Lett 964:L25, 2024). We find that quantum correction effects can also influence polarization information. Considering the quantum corrected Schwarzschild black hole (Kazakov–Solodukhin black hole), we derive the polarization intensity of the target black hole and investigate polarization images under different parameters. It is found that a larger quantum deformation leads to an expansion of the polarization region, while the polarization intensity value decrease. Under different observation angles, magnetic fields, fluid direction angles, and fluid velocity conditions, we also derive polarization images of corrected black holes. These key indicators not only affect the intensity of polarization but also the direction of polarization. We establish the relationship between polarization intensity and quantum correction deformation parameters, revealing a gradual decline in polarization intensity with reduced radius and an anti-polarization behavior induced by the progressive increase in deformation parameters at a constant radius. Our analysis may provide observational evidence for quantum effect of general relativity. [ABSTRACT FROM AUTHOR]

To evaluate the potential toxicity of waterborne silver (Ag), we analyzed the chronic effects of Ag on the physiological and reproductive responses of the Manila clam Ruditapes philippinarum. Clams were exposed to dissolved Ag (AgNO3) at concentrations of 0 (control), 0.03, 0.06, and 0.12 µmol L–1 for 6 weeks. The clearance rate, food absorption efficiency, and respiration rate of clams exposed to Ag were measured to determine their scope for growth (SFG). Histological assays were conducted to investigate gonad development in the clams. Despite considerable Ag accumulation in tissues at all test concentrations, no mortality occurred during the experiment, indicating that even an Ag concentration of 0.12 µmol L–1 did not have lethal effects within 6 weeks. However, the clearance rate and absorption efficiency markedly decreased in clams exposed to 0.12 µmol Ag L–1, resulting in a decline in SFG. Gonadal development was significantly delayed in female clams exposed to 0.06 and 0.12 µmol Ag L–1 for 6 weeks. These data suggest that the SFG and reproductive condition of clams analyzed in this study reflect the physiological status of R. philippinarum exposed to sublethal concentrations of Ag. [ABSTRACT FROM AUTHOR]

The lack of aerial physical interaction capability is one of the choke points limiting the extension of aerial robot applications, such as rescue missions and aerial maintenance. We present a new aerial robotic manipulator (AEROM) for aerial dexterous operations in this work. It contains a robotic manipulator with 6-degree-of-freedom and a compact flight platform. Firstly, we propose a quantitative capability index to evaluate and guide the mechanical design of the AEROM. Based on the proposed quantitative index, we construct a lightweight bird-inspired manipulator to imitate a raptor hindlimb. An additional telescopic joint and an end-effector consisting of three soft fingers allow the AEROM to execute aerial interaction tasks. In addition, the wrist joints enable independent control of the end-effector attitude regardless of the flight platform. After explicitly analyzing the multi-source disturbances during the aerial operation tasks, we develop a refined anti-disturbance controller to compensate for the disturbances with different characteristics. The proposed controller further improves the position accuracy of end-effector to enable dexterous operations during aerial interaction tasks. Finally, the physical experiments verify the effectiveness of the proposed AEROM system. [ABSTRACT FROM AUTHOR]

Background and Objective: Azithromycin is the first azalide antibiotic that is related to the macrolide family of antibiotics. Bioequivalence studies in China are initiated by the National Medical Products Administration (NMPA), which supports a generic consistency evaluation program for ensuring that generic products manufactured in China meet the required standards and provide equivalent therapeutic effects to their reference products. This study aimed to assess the bioequivalence of two azithromycin tablets under both fasting and fed conditions in healthy Chinese volunteers. Methods: This was a single-center, open-label, single-dose, randomized, three-way crossover trial with two independent groups (fasting group and fed group). A total of 72 healthy Chinese subjects (36 subjects in the fasting state and 36 subjects in the fed state) were enrolled and randomized to treatment. Blood samples were collected from 0 to 120 h after a single oral dose of a 250-mg generic azithromycin tablet (test, T) or branded azithromycin tablet (reference, R). The plasma concentrations of azithromycin were determined by high-performance liquid chromatography–tandem mass spectrometry (HPLC‒MS/MS). A non-compartmental analysis method was used to estimate the pharmacokinetic parameters. Adverse events were documented. Results: In a fasting state, the bioequivalence of maximum plasma concentration (Cmax) was evaluated using the reference-scaled average bioequivalence (RSABE) approach (within-subject standard deviation, SWR > 0.294), and the bioequivalence of area under the concentration–time curve from time 0 to the time of the last measurable plasma concentration (AUC0–t) and area under the concentration–time curve from time 0 extrapolated to infinity (AUC0–∞) were evaluated by the average bioequivalence (ABE) method (SWR < 0.294). The geometric mean ratio (GMR) of T/R for Cmax was 106.49%, while the 95% upper confidence bound was < 0. The GMRs of AUC0–t and AUC0–∞ were 103.34% and 101.28%, and the 90% confidence intervals (CIs) of the test/reference were 95.90–111.35%/94.85–108.15%, respectively. In the fed state, the RSABE approach was applied to estimate the bioequivalence of Cmax (SWR >0.294), and the ABE approach was applied to estimate the bioequivalence of AUC0–t and AUC0–∞ (SWR < 0.294). The GMR for Cmax was 99.80%, while the 95% upper confidence bound value was < 0. The GMRs of AUC0–t and AUC0–∞ were 97.07% and 98.15%, and the 90% CIs of the T/R were 90.02–104.68% and 90.66–106.25%, respectively. All adverse events were mild and transient. Conclusions: The trial indicated that the test and the reference azithromycin tablets were bioequivalent and well tolerated in healthy Chinese volunteers under both fasting and fed conditions. Trial Registration: Clinicaltrials, ChiCTR2300071630 (retrospectively registered in 19/05/2023). [ABSTRACT FROM AUTHOR]

The Nigerian Younger Granite (NaYG) province is renowned for its world-class anorogenic alkaline ring granite complexes and has been recognized as a potential host for abundant Nb–Sn–W–Mo mineralization. In this study, a comprehensive investigation was conducted on the southernmost complex of the province, known as the Afu granite complex, encompassing petrography, zircon U–Pb dating and Lu–Hf isotopes, and whole-rock geochemical analyses. The dominant rocks within the Afu complex consist of biotite granite and albite biotite granite. Both rock units exhibit typical characteristics of A1-type granite, including elevated levels of alkali oxides (Na2O + K2O = 8.01–8.52 wt%) and high field strength elements (Zr + Nb + Ce + Y = 495–950 ppm), as well as high FeOT/(FeOT + MgO) and Ga/Al ratios, similar to other younger granites found in Nigeria. Bulk rock Sm–Nd and zircon Lu–Hf isotopic data (εNd(t) = −2.6 to 0.9; εHf(t) = −7.2 to −0.5) indicate a predominantly crustal material-dominated magma source, with some contribution from mantle-derived magma. The linear correlations observed between Rb/Sr and Nb/Ta ratios as well as Sr contents from biotite granite to albite biotite granite suggest the significant role played by magma differentiation. The elevated bulk Nb contents observed in all rocks, along with the presence of Sn–W-bearing quartz veins, contribute to the rare metal mineralization of the Afu complex and indicate a combination of magmatic and hydrothermal processes. Additionally, zircon U–Pb dating results from the Afu granites reveal their relatively young ages (149–148 Ma) compared to other NaYGs (263–151 Ma), suggesting the cessation of anorogenic alkaline magmatism within the NaYG province. [ABSTRACT FROM AUTHOR]

In genome-wide association studies, combinations of single nucleotide polymorphisms are considered to be more effective than individual mutations in linking genes to traits. Clearly, finding the most relevant combinations from tens of thousands of these mutations associated with a trait is a complicated combinatorial problem. To achieve the higher prediction performance, improve computational efficiency and results interpretation, we proposed three algorithms for searching combinations of individual mutations and applied these algorithms to 3178 samples of Mycobacterium tuberculosis strains for predicting their drug resistance to 20 drugs. The single nucleotide polymorphisms associated with drug resistance were identified in the Mycobacterium tuberculosis genome using the single-marker test, and the combinations of individual mutations were searched using the multimarker test. The data were compared with those predicted by the widely recognized Mykrobe and TB-profiler software. Comparative analysis of the results obtained showed that, excepting for ofloxacin, the combinations of individual mutations found by our algorithms for the second-line drugs have some advantages in prediction accuracy. [ABSTRACT FROM AUTHOR]

Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample. Simultaneous profiling of multiple RNA modifications is a promising yet understudied field of research. Here, authors develop a transferable deep learning framework capable of detecting multiple types of RNA modifications in single nanopore sequencing sample. [ABSTRACT FROM AUTHOR]

Domesticated herbivores are an important agricultural resource that play a critical role in global food security, particularly as they can adapt to varied environments, including marginal lands. An understanding of the molecular basis of their biology would contribute to better management and sustainable production. Thus, we conducted transcriptome sequencing of 100 to 105 tissues from two females of each of seven species of herbivore (cattle, sheep, goats, sika deer, horses, donkeys, and rabbits) including two breeds of sheep. The quality of raw and trimmed reads was assessed in terms of base quality, GC content, duplication sequence rate, overrepresented k-mers, and quality score distribution with FastQC. The high-quality filtered RNA-seq raw reads were deposited in a public database which provides approximately 54 billion high-quality paired-end sequencing reads in total, with an average mapping rate of ~93.92%. Transcriptome databases represent valuable resources that can be used to study patterns of gene expression, and pathways that are related to key biological processes, including important economic traits in herbivores. [ABSTRACT FROM AUTHOR]

CircRNAs are covalently closed, single-stranded RNA that form continuous loops and play a crucial role in the initiation and progression of tumors. Cancer stem cells (CSCs) are indispensable for cancer development; however, the regulation of cancer stem cell-like properties in gastric cancer (GC) and its specific mechanism remain poorly understood. We elucidate the specific role of Circ-0075305 in GC stem cell properties. Circ-0075305 associated with chemotherapy resistance was identified by sequencing GC cells. Subsequent confirmation in both GC tissues and cell lines revealed that patients with high expression of Circ-0075305 had significantly better overall survival (OS) rates than those with low expression, particularly when treated with postoperative adjuvant chemotherapy for GC. In vitro and in vivo experiments confirmed that overexpression of Circ-0075305 can effectively reduce stem cell-like properties and enhance the sensitivity of GC cells to Oxaliplatin compared with the control group. Circ-0075305 promotes RPRD1A expression by acting as a sponge for corresponding miRNAs. The addition of LF3 (a β-catenin/TCF4 interaction antagonist) confirmed that RPRD1A inhibited the formation of the TCF4–β-catenin transcription complex through competitive to β-catenin and suppressed the transcriptional activity of stem cell markers such as SOX9 via the Wnt/β-catenin signaling pathway. This leads to the downregulation of stem cell-like property-related markers in GC. This study revealed the underlying mechanisms that regulate Circ-0075305 in GCSCs and suggests that its role in reducing β-catenin signaling may serve as a potential therapeutic candidate. Circular RNA Circ0075305 hinders gastric cancer stem cells by indirectly increasing the expression of RPRD1A. In turn, RPRD1A disrupts TCF4-β-catenin complex formation and promotes downregulation of SOX9 transcription. [ABSTRACT FROM AUTHOR]

This work systematically analyzed the microstructure and physicochemical properties of amylose (AM) and amylopectin (AP) isolated from tigernut starch (TS). The yields of AM and AP were 66.50% and 72.80%, respectively. Scanning electron micrographs showed that AM and AP were, structurally, very different from TS. Granules of AM and AP had rough surfaces and irregular shapes. AM had a V-type crystalline structure, while AP was believed to be amorphous. These structural differences influence their functional properties. AM had superior thermal stability and swelling characteristics, as well as high resistance to digestion. Meanwhile, AM gel had superior springiness and high chewability. While AP had good solubility and its paste was a liquid showing high fluidity. Collectively, these results are expected to provide new information valuable for future developments in the industrial application of AM and AP derived from TS. [ABSTRACT FROM AUTHOR]

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A meshfree orthotropic laminated shell model for geometrically nonlinear static and dynamic analysis based on the reproducing kernel particle method (RKPM) and the Mindlin-Reissner shell theory is proposed for the first time, suitable for dealing with the finite deformation of composite shell structures of arbitrary geometry in engineering. The Mindlin-Reissner shell theory is adopted to describe the geometric configuration of the laminated shells via a single-layer particle. Then, the Galerkin weak form governing equations are established explicitly and discretized using RKPM and linear transformation in the thickness direction. Furthermore, a laminate stacking sequence that can eliminate the coupling terms of linear and angular acceleration is proposed for simplification. For considering the orthotropic materials, the stress–strain transformation between local and material coordinates is introduced. A stiffened laminated shell model is also presented for simulating complex composited structures. The accuracy and convergence of the proposed laminated shell model are verified through several static and dynamic benchmarks, demonstrating the ability of the presented model to solve the nonlinear response of composite structures. [ABSTRACT FROM AUTHOR]

In this paper, we study the n-player game and the mean field game under the constant relative risk aversion relative performance on terminal wealth, in which the interaction occurs by peer competition. In the model with n agents, the price dynamics of underlying risky assets depend on a common noise and contagious jump risk modeled by a multi-dimensional nonlinear Hawkes process. With a continuum of agents, we formulate the mean field game problem and characterize a deterministic mean field equilibrium in an analytical form under some conditions, allowing us to investigate some impacts of model parameters in the limiting model and discuss some financial implications. Moreover, based on the mean field equilibrium, we construct an approximate Nash equilibrium for the n-player game when n is sufficiently large. The explicit order of the approximation error is also derived. [ABSTRACT FROM AUTHOR]

There has been increasing interest in the role of epigenetic modification in cancers recently. Among the various modifications, sialylation has emerged as a dominant subtype implicated in tumor progression, metastasis, immune evasion, and chemoresistance. The prognostic significance of sialylation-related molecules has been demonstrated in colorectal cancer. However, the potential roles and regulatory mechanisms of sialylation in lung adenocarcinoma (LUAD) have not been thoroughly investigated. Through Pearson correlation, univariate Cox hazards proportional regression, and random survival forest model analyses, we identified several prognostic long non-coding RNAs (lncRNAs) associated with aberrant sialylation and tumor progression, including LINC00857, LINC00968, LINC00663, and ITGA9-AS1. Based on the signatures of four lncRNAs, we classified patients into two clusters with different landscapes using a non-negative matrix factorization approach. Collectively, patients in Cluster 1 (C1) exhibited worse prognoses than those in Cluster 2 (C2), as well as heavier tumor mutation burden. Functional enrichment analysis showed the enrichment of several pro-tumor pathways in C1, differing from the upregulated Longevity and programmed cell death pathways in C2. Moreover, we profiled immune infiltration levels of important immune cell lineages in two subgroups using MCPcounter scores and single sample gene set enrichment analysis scores, revealing a relatively immunosuppressive microenvironment in C1. Risk analysis indicated that LINC00857 may serve as a pro-tumor regulator, while the other three lncRNAs may be protective contributors. Consistently, we observed upregulated LINC00857 in C1, whereas increased expressive levels of LINC00968, LINC00663, and ITGA9-AS1 were observed in C2. Finally, drug sensitivity analysis suggested that patients in the two groups may benefit from different therapeutic strategies, contributing to precise treatment in LUAD. By integrating multi-omics data, we identified four core sialylation-related lncRNAs and successfully established a prognostic model to distinguish patients with different characterizations. These findings may provide some insights into the underlying mechanism of sialylation, and offer a new stratification way as well as clinical guidance in LUAD. [ABSTRACT FROM AUTHOR]

In the context of global warming and intensified human activities, glacier instability in plateau regions has increased, and glacier debris flows have become active, which poses a significant threat to the lives and property of people and socioeconomic development. The mass movement process of glacier debris flows is extremely complex, so this paper uses the 2018 Sedongpu glacier debris flow event on the Qinghai-Tibet Plateau as an example and applies a numerical simulation method to invert the whole process of mass movement. In view of the interaction between phases in the process of motion, we use the fluid-solid coupling method to describe the mass movement. The granular-flow model and drift-flux model are employed in FLOW3D software to study the mass movement process of glacier debris flows and explore their dynamic characteristics. The results indicate that the glacier debris flow lasted for 700 s, and the movement process was roughly divided into four stages, including initiation, scraping, surging and deposition; the depositional characteristics calculated by the fluid-solid coupling model are consistent with the actual survey results and have good reliability; strong erosion occurs during the mass movement, the clear volume amplification effect, and the first wave climbs 17.8 m across the slope. The fluid-solid coupling method can better simulate glacier debris flows in plateau regions, which is helpful for the study of the mechanism and dynamic characteristics of such disasters. [ABSTRACT FROM AUTHOR]

Partial label learning deals with the problem where each training instance is associated with a set of candidate labels, among which only one is valid. Existing approaches on partial label learning assume that the scale of label space is fixed, however, this assumption may not be satisfied in open and dynamic environment. In this paper, the first attempt towards the problem of partial label learning with emerging new labels is presented. There are mainly three challenges in this task, namely new label detection, effective classification, and efficient model updating. Specifically, a new method is proposed to address these challenges which consists of three parts: (1) An ensemble-based detector that identifies instances from new labels while also assigns candidate labels to instances which may belong to known labels. (2) An effective classification mechanism that involves data pool construction and label disambiguation process. (3) An efficient updating procedure that adapts both the detector and classifier to new labels without training from scratch. Our experiments on artificial and real-world partial label data sets validate the effectiveness of the proposed method in dealing with emerging labels for partial label learning. [ABSTRACT FROM AUTHOR]

Convolutional Neural Network (CNN) or Recurrent Neural Network (RNN) based text classification algorithms currently in use can successfully extract local textual features but disregard global data. Due to its ability to understand complex text structures and maintain global information, Graph Neural Network (GNN) has demonstrated considerable promise in text classification. However, most of the GNN text classification models in use presently are typically shallow, unable to capture long-distance node information and reflect the various scale features of the text (such as words, phrases, etc.). All of which will negatively impact the performance of the final classification. A novel Graph Convolutional Neural Network (GCN) with dense connections and an attention mechanism for text classification is proposed to address these constraints. By increasing the depth of GCN, the densely connected graph convolutional network (DC-GCN) gathers information about distant nodes. The DC-GCN multiplexes the small-scale features of shallow layers and produces different scale features through dense connections. To combine features and determine their relative importance, an attention mechanism is finally added. Experiment results on four benchmark datasets demonstrate that our model’s classification accuracy greatly outpaces that of the conventional deep learning text classification model. Our model performs exceptionally well when compared to other text categorization GCN algorithms. [ABSTRACT FROM AUTHOR]

Recently, the neural networks with convolution computation is widely used for image classification and recognition. For real-time implementation, the video buffer is required to store the image temperately. However, traditional buffers like CLSB (content line shift buffer) may experience delays during the read process, particularly when encountering line breaks or image changes. As for N × N convolution, the delay time is N−1 clocks for every row changing. As the image width is W, the delay time is 2W + N clocks for every frame changing. These delays can impact the efficiency and performance of the neural network. To overcome this challenge, this paper presented novel buffer design to avoid the delay at the line ends and frame change. By proactively fetching data ahead of time, the buffer can dynamically schedule the read operation and ensure that the subsequent data are correctly placed for efficient processing. This improvement in read latency contributes to enhanced performance and better utilization of computational resources within the hardware system. Then the full convolutional network accelerator is implemented with the fast buffer design and common computational kernel to save the hardware cost based on LeNet model. The results show that the accuracy can achieve 99.1% with MNIST dataset verification. By eliminating the waiting time, the modified buffer allows for more efficient processing in the image, and the fame rate for a computer vision can achieve 46 per second, to meet the real-time requirement. [ABSTRACT FROM AUTHOR]

This paper presents a method that employs an evolutionary normal distributions transform (NDT) for simultaneous localization and mapping (SLAM) using light detection and ranging (LiDAR) for autonomous mobile robots. An adaptive inertia weight and two genetic operators were employed in the Taguchi-based whale optimization algorithm (WOA) to improve the search diversity and avoid local optima. NDT was used to model the environment of differential-drive mobile robots and WOA was applied to optimize the scan matching for the robotic SLAM problem. The NDT-WOA determines the SLAM pose estimation using sensed data from the physical world. A nonholonomic mobile robot was steered to achieve the NDT-WOA SLAM task with the derived robot kinematics and actuator dynamics. The proposed method was implemented in a TurtleBot3 Burger robotic development kit, which includes a single-board computer and an OpenCR control board. The Robot Operating System (ROS) was utilized to implement the evolutionary NDT-WOA SLAM system due to its flexibility, open source, and client library. Simulation and comparisons were conducted to illustrate the efficiency of the proposed NDT-WOA SLAM method compared to other SLAM paradigms. The experimental results show the effectiveness of the proposed evolutionary NDT-WOA SLAM for autonomous mobile robots. The results could have theoretical and practical significance for robotics research. [ABSTRACT FROM AUTHOR]

Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy. Here, we constructed the first prospective multi-omics atlas of the largest osteoporosis cohort to date (longitudinal data from 366 participants at three time points), and also implemented an explainable data-intensive analysis framework (DLSF: Deep Latent Space Fusion) for an omnigenic model based on a multi-modal approach that can capture the multi-modal molecular signatures (M3S) as explicit functional representations of hidden genotypes. Accordingly, through DLSF, we identified two subtypes of the osteoporosis population in Chinese individuals with corresponding molecular phenotypes, i.e., clinical intervention relevant subtypes (CISs), in which bone mineral density benefits response to calcium supplements in 2-year follow-up samples. Many snpGenes associated with these molecular phenotypes reveal diverse candidate biological mechanisms underlying osteoporosis, with xQTL preferences of osteoporosis and its subtypes indicating an omnigenic effect on different biological domains. Finally, these two subtypes were found to have different relevance to prior fracture and different fracture risk according to 4-year follow-up data. Thus, in clinical application, M3S could help us further develop improved diagnostic and treatment strategies for osteoporosis and identify a new composite index for fracture prediction, which were remarkably validated in an independent cohort (166 participants). [ABSTRACT FROM AUTHOR]

The mix proportion of multi-source coal-based solid waste (CSW) for underground backfilling affects transportation and support performance of backfill materials, and even the backfilling cost. In this study, the optimal mix proportion of desulfurization gypsum (DG), furnace bottom slag (FBS) and gasification fine slag (GFS) is determined by the Response Surface Methodology–Box Behnken Design (RSM-BBD). Then the fluidity, bleeding rate, 3-day strength, 7-day strength and preparation cost are evaluation indicators, the optimal mix proportion of backfill materials is determined by the multi-objective decision-making method (MDM). Finally, the microstructure of the backfill material with optimal mix proportion was studied by TGA, MIP, SEM–EDS and XRD. The results show that the mix proportion of CSW with the optimal comprehensive index is coal gangue (CG): coal fly ash (CFA): DG: FBS: GFS = 1:1.5:0.2:0.1:0.1, the mass concentration is 78%, and ordinary Portland cement (OPC)/CSW = 7.5%. The weight loss phenomenon of the backfill material with the optimal mix proportion occurs continuously during the heating process, mainly due to the evaporation of crystal water, structural water and hydroxyl water. There are dense narrow-necked pores in the backfill material, and the pore connectivity is poor. There is no hydration reaction occurs between CSW particles, and the strength increase of the backfill material mainly depends on the hydration reaction of cement. In ettringite, part of Al2O3 is replaced by SiO2, and part of CaSO4 is replaced by CaCO3. This study provides a reference for the engineering application of underground backfilling with multi-source CSW. [ABSTRACT FROM AUTHOR]

A less prominent N-S oriented continental-scale strike-slip shear zone occurs within the Babouri-Figuil Magmatic Complex (BFMC). Studies have shown that such shallow to middle crustal levels shear zones often display long-lasting deformation, physical expression of strain localization, and mineralization. However, until dates, deformation evolution and structural mineralization of this ~ 8 km long shear zone in Babouri-Figuil remain enigmatic, which prompted its investigation. A combined structural study supported by U-Pb zircon dating on the sheared granitoids is reported. Biotite granite sampled near Sorawel village yielded zircon U-Pb concordia age of 606 ± 6 Ma, whereas hornblende-biotite granite sampled at the western corner of the Ribao massif yielded zircon U-Pb concordia age of 601 ± 2 Ma. These granites were emplaced in a transpressive tectonic regime shortly after a regional thickening event < 620 Ma. The studied microstructures demonstrate a typical transition from protomylonite to extremely deformed mylonite marked with decreased mineral sizes. On thin sections, two main zones are identified: "zone A" (low-strain zone) and "zone B" (high-strain zone). Core-mantle K-feldspar porphyroclasts within the mylonite show dislocation creep deformation, whereas recrystallized to neocrystallized aggregates indicate plastic flow by viscous grain boundary sliding. Shear sense indicators revealed both early dextral and late sinistral shearing. In all, the results revealed that the Guider-Sorawel shear zone (GSSZ) experienced ductile deformation probably under medium to high temperature conditions. The double shearing is possible during the switch of the regional maximum principal stress from N-S (~ 585 Ma) to NW-SE (< 580 Ma). The obtained dates are syn-collisional and are consistent with D2 deformation phase in other parts of Cameroon. Also, the dates marked the final tectonic college between the north Cameroon domain and the southwest Chad domain, which probably might have induced the SZ. The construction of these adjacent domains probably resulted to a sort of increased temperature and strain localization that led to the initiation of a rheologically weaken mechanical zone via which the magma generated flows to near surface crustal level. [ABSTRACT FROM AUTHOR]

Amongst all types of cancer, breast cancer has become one of the most common cancers in the UK threatening millions of people's health. Early detection of breast cancer plays a key role in timely treatment for morbidity reduction. Compared to biopsy, which takes tissues from the lesion for further analysis, image-based methods are less time-consuming and pain-free though they are hampered by lower accuracy due to high false positivity rates. Nevertheless, mammography has become a standard screening method due to its high efficiency and low cost with promising performance. Breast mass, as the most palpable symptom of breast cancer, has received wide attention from the community. As a result, the past decades have witnessed the speeding development of computer-aided systems that are aimed at providing radiologists with useful tools for breast mass analysis based on mammograms. However, the main issues of these systems include low accuracy and require enough computational power on a large scale of datasets. To solve these issues, we developed a novel breast mass classification system called DF-dRVFL. On the public dataset DDSM with more than 3500 images, our best model based on deep random vector functional link network showed promising results through five-cross validation with an averaged AUC of 0.93 and an average accuracy of 81.71 % . Compared to sole deep learning based methods, average accuracy has increased by 0.38. Compared with the state-of-the-art methods, our method showed better performance considering the number of images for evaluation and the overall accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a nonlocal energy-informed neural network is proposed to deal with elastic solids containing discontinuities by considering the long-range interactions of material points. First, the solution to peridynamic equilibrium equation is converted to an variational energy minimization problem based on principle of virtual work, which automatically satisfies the zero-traction boundary conditions and avoids the introduction of artificial damping. Furthermore, the energetic representation of behavior of physical system can be tractable as the loss function for deep learning neural network. This allows to approximate the solution of the system by the active machine learning community. As the basic technique in deep learning, automatic differentiation is capable to evaluate derivatives for smooth functions, but it is prone to singularity due to the presence of discontinuities. To address this limitation, spatial integration is employed in the proposed neural network to evaluate the strain energy of the system rather than the spatial derivatives of displacement fields calculated by automatic differentiation. Moreover, the initial cracks can be directly introduced in the constitutive model without the explicit definition of crack surfaces. The accuracy and efficiency of the proposed neural network is validated by conducting several mechanical problems with or without discontinuities. More importantly, the proposed neural network is capable to capture the jump discontinuities at the crack surfaces, where the neural network with automatic differentiation is hard to address. Additionally, the convergence of the proposed neural network and the comparison of two widely used activation functions are investigated. [ABSTRACT FROM AUTHOR]

Motivated by recent developments in risk management based on the U.S. bankruptcy code, we revisit the De Finetti’s optimal dividend problem by incorporating the reorganization process and regulator’s intervention documented in Chapter 11 bankruptcy. The resulting surplus process, bearing financial stress towards the more subtle concept of bankruptcy, corresponds to a non-standard spectrally negative Lévy process with endogenous regime switching. Some explicit expressions of the expected present values under a barrier strategy, new to the literature, are established in terms of scale functions. With the help of these expressions, when the tail of the Lévy measure is log-convex, the optimal dividend control is shown to be of the barrier type and the associated optimal barrier can be identified using scale functions of spectrally negative Lévy processes. Some financial implications are also discussed in an illustrative example. [ABSTRACT FROM AUTHOR]

Background: Stroke is a major medical problem, and novel therapeutic targets are urgently needed. This study investigates the protective role and potential mechanisms of the N6-methyladenosine (m6A) RNA methyltransferase METTL3 against cerebral injury resulting from insufficient cerebral blood flow. Methods: In this study, we constructed mouse MCAO models and HT-22 cell OGD/R models to mimic ischemic stroke-induced brain injury and neuronal damage. We generated NEDD4L knockout and METTL3 overexpression models and validated therapeutic effects using infarct volume, brain edema, and neurologic scoring. We performed qRT-PCR, western blotting, and co-immunoprecipitation to assess the influence of NEDD4L on ferroptosis markers and TFRC expression. We verified the effect of NEDD4L on TFRC ubiquitination by detecting half-life and ubiquitination. Finally, we validated the impact of METTL3 on NEDD4L mRNA stability and MCAO outcomes in both in vitro and in vivo experimental models. Result: We find NEDD4L expression is downregulated in MCAO models. Overexpressing METTL3 inhibits the iron carrier protein TFRC by upregulating the E3 ubiquitin ligase NEDD4L, thereby alleviating oxidative damage and ferroptosis to protect the brain from ischemic injury. Mechanistic studies show METTL3 can methylate and stabilize NEDD4L mRNA, enhancing NEDD4L expression. As a downstream effector, NEDD4L ubiquitinates and degrades TFRC, reducing iron accumulation and neuronal ferroptosis. Conclusion: In summary, we uncover the METTL3-NEDD4L-TFRC axis is critical for inhibiting post-ischemic brain injury. Enhancing this pathway may serve as an effective strategy for stroke therapy. This study lays the theoretical foundation for developing m6A-related therapies against ischemic brain damage. [ABSTRACT FROM AUTHOR]

The photovoltaic effect lies at the heart of eco-friendly energy harvesting. However, the conversion efficiency of traditional photovoltaic effect utilizing the built-in electric effect in p-n junctions is restricted by the Shockley-Queisser limit. Alternatively, intrinsic/bulk photovoltaic effect (IPVE/BPVE), a second-order nonlinear optoelectronic effect arising from the broken inversion symmetry of crystalline structure, can overcome this theoretical limit. Here, we uncover giant and robust IPVE in one-dimensional (1D) van der Waals (vdW) grain boundaries (GBs) in a layered semiconductor, ReS2. The IPVE-induced photocurrent densities in vdW GBs are among the highest reported values compared with all kinds of material platforms. Furthermore, the IPVE-induced photocurrent is gate-tunable with a polarization-independent component along the GBs, which is preferred for energy harvesting. The observed IPVE in vdW GBs demonstrates a promising mechanism for emerging optoelectronics applications. The intrinsic photovoltaic effect (IPVE) in noncentrosymmetric materials has the potential to overcome the limitations of traditional photovoltaic devices. Here, the authors report the observation of a strong and gate-tunable IPVE in 1D grain boundaries of a van der Waals semiconductor, ReS2. [ABSTRACT FROM AUTHOR]

Visible light-driven bimetallic photocatalyst FcC2Cu was prepared by one-step aqueous phase method. The FcC2Cu sample was characterized using X-ray powder diffraction, UV–Visible diffuse reflectance spectroscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy and Mott–Schottky analysis. The photocatalytic activity of the as-prepared FcC2Cu sample was tested through the photocatalytic degradation of glyphosate. The catalyst exhibited good photocatalytic activity toward glyphosate degradation under natural solar light irradiation. The enhancement of photocatalytic activity is ascribed to its strong visible light absorption and the synergistic effect of π-conjugated system and Fe2+ in FcC2Cu. [ABSTRACT FROM AUTHOR]

How to effectively and economically estimate the occurrence of sandstone-type uranium deposits in deep metallogenic environments considering the high costs of drilling methods has troubled the uranium geologists for a long time. To address this, we developed a novel workflow using a combination of clustering and neural networks in seismic attributes (SA) analysis to characterize uranium-bearing environments in directly predicting uranium zones. In the workflow, PCA and a clustering method for SA analysis in the target layer were first used to predict favorable zones for uranium; second, supervised neural networks were utilized for quantitative estimation of gamma volume, with subsequent delineation of the zones with high gamma anomalies; finally, results from the two processes were examined for mutual intersection, and intersection results with ordinal ranking of A and B were then extracted. In practical application, several A-level and B-level regions were predicted, which represent very high U-mineralization potential and significant potential, respectively. The prediction results were then essentially verified by logging data of the study area. We consider our developed approach to be a reasonably cost-effective technique for uranium-bearing environment prediction as it can yield useful suggestions for drilling programs with significantly reduced cost and prospecting risk. [ABSTRACT FROM AUTHOR]

Landslides induced by rainfall pose a notable threat to post-earthquake reconstruction in mountainous areas. Taking Qingliu landslide as an example, this paper reveals the potential failure mechanism and range of the landslide mass through field investigation and monitoring data, and further uses the improved computational fluid dynamics method to simulate and predict the disaster range after landslide destabilization. The results show that the landslide was initially deformed and cracked under the influence of strong earthquakes and formed seepage channels for water infiltration. The circulation of surface recharge of groundwater in rainy season and long-distance recharge of groundwater from melting ice and snow in winter season leads to the continuous softening and reduction of sliding resistance in the sliding zone. Under the action of this change chain, the cracks along the back edge and boundary of the landslide continue to develop and expand and finally will lead to landslide collapse failure. The equivalent fluid method can better simulate the movement process and accumulation process of landslide, since the Qingliu landslide is a soil landslide with fluid characteristics in the process of landslide movement. The results indicate that the maximum speed of the mass flow could reach 49 m/s, which could destroy the infrastructures along the sliding path, besides, both of the two landslides could bury Xiameng town below and block the Mengtun River to form a landslide-dammed lake. The research results could provide a reference for further comprehensive treatment of landslides and the formulation of emergency plans. [ABSTRACT FROM AUTHOR]