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Functional traits influence the assembly of microbial communities, but identifying these traits in the environment has remained challenging. We studied ectomycorrhizal fungal (EMF) communities inhabiting Populus trichocarpa roots distributed across a precipitation gradient in the Pacific Northwest, USA. We profiled these communities using taxonomic (meta-barcoding) and functional (metagenomic) approaches. We hypothesized that genes involved in fungal drought-stress tolerance and fungal mediated plant water uptake would be most abundant in drier soils. We were unable to detect support for this hypothesis; instead, the abundance of genes involved in melanin synthesis, hydrophobins, aquaporins, trehalose-synthases, and other gene families exhibited no significant shifts across the gradient. Finally, we studied variation in sequence homology for certain genes, finding that fungal communities in dry soils are composed of distinct aquaporin and hydrophobin gene sequences. Altogether, our results suggest that while EMF communities exhibit significant compositional shifts across this gradient, coupled functional turnover, at least as inferred using community metagenomics is limited. Accordingly, the consequences of these distinct EMF communities on plant water uptake remain critically unknown, and future studies targeting the expression of genes involved in drought stress tolerance are required.

Dimensionality reduction (DR) is a popular technique that shows great results to analyze high-dimensional data. Generally, DR is used to produce visualizations in 2 or 3 dimensions. While it can help understanding correlations between data, embeddings generated by DR are hard to grasp. The position of instances in low-dimension may be difficult to interpret, especially for non-linear, non-parametric DR techniques. Because most of the techniques are said to be neighborhood preserving (which means that explaining long distances is not relevant), some approaches try explaining them locally. These methods use simpler interpretable models to approximate the decision frontier locally. This can lead to misleading explanations. In this paper a novel approach to locally explain non-linear, non-parametric DR embeddings like t-SNE is introduced. It is the first gradient-based method for explaining these DR algorithms. The technique presented in this paper is applied on t-SNE, but is theoretically suitable for any DR method that is a minimization or maximization problem. The approach uses the analytical derivative of a t-SNE embedding to explain the position of an instance in the visualization. [ABSTRACT FROM AUTHOR]

Background: Early detection of Alzheimer's disease (AD) is essential for timely management and consideration of therapeutic options; therefore, detecting the risk of conversion from mild cognitive impairment (MCI) to AD is crucial during neurodegenerative progression. Existing neuroimaging studies have mostly focused on group differences between individuals with MCI (or AD) and cognitively normal (CN), discarding the temporal information of conversion time. Here, we aimed to develop a prognostic model for AD conversion using functional connectivity (FC) and Cox regression suitable for conversion event modeling. Methods: We developed a prognostic model using a large-scale Alzheimer's Disease Neuroimaging Initiative dataset, and it was validated using external data obtained from the Open Access Series of Imaging Studies. We considered individuals who were initially CN or had MCI but progressed to AD and those with MCI with no progression to AD during the five-year follow-up period. As the exact conversion time to AD is unknown, we inferred this information using imputation approaches. We generated cortex-wide principal FC gradients using manifold learning techniques and computed subcortical-weighted manifold degrees from baseline functional magnetic resonance imaging data. A penalized Cox regression model with an elastic net penalty was adopted to define a risk score predicting the risk of conversion to AD, using FC gradients and clinical factors as regressors. Results: Our prognostic model predicted the conversion risk and confirmed the role of imaging-derived manifolds in the conversion risk. The brain regions that largely contributed to predicting AD conversion were the heteromodal association and visual cortices, as well as the caudate and hippocampus. Our risk score based on Cox regression was consistent with the expected disease trajectories and correlated with positron emission tomography tracer uptake and symptom severity, reinforcing its clinical usefulness. Our findings were validated using an independent dataset. The cross-sectional application of our model showed a higher risk for AD than that for MCI, which correlated with symptom severity scores in the validation dataset. Conclusion: We proposed a prognostic model predicting the risk of conversion to AD. The associated risk score may provide insights for early intervention in individuals at risk of AD conversion. [ABSTRACT FROM AUTHOR]

Earlier studies acknowledged that the design speed does not principally assure consistency in the design of highway geometric elements. Methodologies for estimating operating speeds are limited to specific or local traffic conditions and design standards, as in various studies conducted on two-lane and multi-lane highways. The present study develops operating speed models of the vehicle types observed on horizontal curves and tangent sections on two-lane highways in southern parts of India. Geometric features of the curve section and adjacent tangent sections, such as the radius of the curve, curve length, deflection angle, degree of curvature, gradient, carriageway width, and shoulder width, are obtained from the field. The speed data collected at 24 locations on the highway, including curved and tangent gradient sections, are used to analyze and model operating speed. The results indicate that the inverse of the square root of the radius appears to be an influencing parameter for modeling the operating speed of vehicles. The operating speed is sensitive for a curve radius of up to 600 m; thereafter, the operating speed appears insignificant. On tangent sections, the gradient has a larger influence on the operating speeds of all vehicle types. The operating speed models are validated and compared with models available in the literature. The proposed models developed in the present study are helpful to traffic engineers for predicting the operating speed on two-lane highways. [ABSTRACT FROM AUTHOR]

We show that the gradient of a strongly differentiable function at a point is the limit of a single coordinate‐free Clifford quotient between a multidifference pseudo‐vector and a pseudo‐scalar, or of a sum of Clifford quotients between scalars (as numerators) and vectors (as denominators), both evaluated at the vertices of a same non‐degenerate simplex contracting to that point. Such result allows to fix an issue with a defective definition of pseudo‐scalar field in Sobczyck's simplicial calculus. Then, we provide some consequences and conjectures implied by the foregoing results. [ABSTRACT FROM AUTHOR]

AbstractIn this article we present an algorithm for faster computation of HMM likelihood gradients when the observation space is discrete. Many parameter estimation algorithms for HMM require repeated computation of gradient to optimize the likelihood function. Gradient computation is costly therefore its faster computation can improve their performance greatly. We develop an algorithm for faster computation of gradient using ideas from data compression. Our algorithm decreased computation cost of gradients by a factor of three to five. We apply our methods to speed up the Baum-Welch algorithm by similar factors. [ABSTRACT FROM AUTHOR]

Incorporating arc‐curved configuration into auxetic honeycomb can evenly distribute pressure, reduce stress concentration, and avoid fracture. In this work, a novel arc‐curved chiral star‐shaped honeycomb (ACSH) has been proposed by combining the chiral honeycomb (CH), the star‐shaped honeycomb (SSH), and arc‐curved configurations. The crushing response of the ACSH is studied experimentally and numerically. In order to verify the accuracy of simulation, quasi‐static compression experiment is carried out on the ACSH sample fabricated by 3D printing. Subsequently, the crashworthiness of the ACSH is compared with other honeycombs. Particularly, under the crushing velocity of 2 m s−1, the ACSH exhibits exceptional specific energy absorption, which is 179% higher than that of the conventional SSH. Additionally, it is also found that introducing arc‐curved configuration can effectively reduce initial peak stress. Moreover, the effect of functionally graded design on crashworthiness is systematically analyzed. The findings indicate that the initial peak stress decreases with the decrease of gradient rate. When crushing velocity increases to 80 m s−1, the SEA of the ACSH increases with the increase of gradient rate. This work investigates the crushing response of a novel honeycomb, which can provide a reference for designing and optimizing novel lightweight honeycombs with better crashworthiness. [ABSTRACT FROM AUTHOR]

The role of stress-induced diffusion (SID) in influencing the mechanical response and diffusion of Li in viscoelastic electrode particles of Lithium-ion batteries is studied. A two-way coupled chemo-viscoelastic model is developed for this purpose, and the governing equations are solved via the finite element method using deal. ii, an open source C++ library. Comparative studies between one-way and two-way coupled chemo-viscoelastic models reveal that concentration and stress are initially larger for the two-way coupled model, but later they reduce in magnitude compared to the one-way coupled model. The level of filling at which the switch is observed decreases with increase in particle size. The switch occurs due to change in the sign of gradient of hydrostatic stress for a viscoelastic material from negative to positive and its concurrent effect on diffusive flux as a result of two-way coupling between stress and diffusion. Further, from comparative studies between two-way coupled elastic and viscoelastic models, it is observed that speed of filling is greater for an elastic particle in comparison to a viscoelastic particle, and the gap increases when the particle size is smaller. In addition, lower values of stresses are observed for viscoelastic electrode particles, and the difference between maximum stress generated increases with increase in particle size. Thus, the time scales associated with viscoelastic constitutive response and diffusion process alters the SID effects and could be tuned while designing electrodes to mitigate slowing down of diffusion and fracture. [ABSTRACT FROM AUTHOR]

Within this article, the maximal function method is used to establish the Calderón-Zygmund estimates for the weak solutions of a class of non-uniformly elliptic equations - div A (x , D u) = - div F (x , f) i n R n , where A (x , D u) ≈ | D u | p 1 - 2 + μ (x) | D u | p 2 - 2 , F (x , f) ≈ | f | p 1 - 2 + μ (x) | f | p 2 - 2 and 1 < p 1 < p 2 , 0 ≤ μ (·) ∈ C 0 , α (R n) , α ∈ (0 , 1 ] . The aforementioned problems arise as Euler-Lagrange equations for variational functionals that were originally presented and studied within the context of Homogenization and the Lavrentiev phenomenon by Marcellini (Arch Ration Mech Anal 105:267–284, 1989. ) and Zhikov (Izv Akad Nauk SSSR Ser Mat 29:33–66, 1987. ). They are distinctive in that they exhibit that the growth and ellipticity change between two distinct types of polynomial depending on the position. This feature is characteristic of strongly anisotropic materials. The contribution of this paper is closely tied to the significant advancements made by Colombo and Mingione (J Funct Anal 270:1416–1478, 2016. ) in the qualitative analysis of double phase problems, as well as the related techniques used by Zhang et al. (Ann Polon Math, 114:45–65, 2015. ). [ABSTRACT FROM AUTHOR]

The aluminum alloy block is a component of aircraft piston engine, and it is prone to fatigue cracks when working in a thermal mechanical coupling state for a long time. Establish a GT-POWER simulation model for a certain type of engine, verify the accuracy of the model, obtain boundary parameters such as temperature and pressure of the engine block under harsh operating conditions through the model, and divide the cylinder wall into gradients based on the engine operating conditions to obtain the surface heat transfer coefficient of the block, and then obtain the temperature field distribution of the engine body. The coupling analysis of the cylinder burst pressure and temperature field of the engine block under harsh working conditions showed that the maximum stress of the engine block was 292.55 MPa and the maximum deformation was 0.39 mm, with thermal load being the main factor causing deformation. Conduct a complete engine bench test, and under the 1000 h bench durability test, there are no cracks on the engine block, indicating that the design and analysis meet the requirements. [ABSTRACT FROM AUTHOR]

Abstract Background Early detection of Alzheimer’s disease (AD) is essential for timely management and consideration of therapeutic options; therefore, detecting the risk of conversion from mild cognitive impairment (MCI) to AD is crucial during neurodegenerative progression. Existing neuroimaging studies have mostly focused on group differences between individuals with MCI (or AD) and cognitively normal (CN), discarding the temporal information of conversion time. Here, we aimed to develop a prognostic model for AD conversion using functional connectivity (FC) and Cox regression suitable for conversion event modeling. Methods We developed a prognostic model using a large-scale Alzheimer’s Disease Neuroimaging Initiative dataset, and it was validated using external data obtained from the Open Access Series of Imaging Studies. We considered individuals who were initially CN or had MCI but progressed to AD and those with MCI with no progression to AD during the five-year follow-up period. As the exact conversion time to AD is unknown, we inferred this information using imputation approaches. We generated cortex-wide principal FC gradients using manifold learning techniques and computed subcortical-weighted manifold degrees from baseline functional magnetic resonance imaging data. A penalized Cox regression model with an elastic net penalty was adopted to define a risk score predicting the risk of conversion to AD, using FC gradients and clinical factors as regressors. Results Our prognostic model predicted the conversion risk and confirmed the role of imaging-derived manifolds in the conversion risk. The brain regions that largely contributed to predicting AD conversion were the heteromodal association and visual cortices, as well as the caudate and hippocampus. Our risk score based on Cox regression was consistent with the expected disease trajectories and correlated with positron emission tomography tracer uptake and symptom severity, reinforcing its clinical usefulness. Our findings were validated using an independent dataset. The cross-sectional application of our model showed a higher risk for AD than that for MCI, which correlated with symptom severity scores in the validation dataset. Conclusion We proposed a prognostic model predicting the risk of conversion to AD. The associated risk score may provide insights for early intervention in individuals at risk of AD conversion.

The natural bone structure exhibits a radial gradient with dense cortical bone externally and porous cancellous bone internally. However, previous studies proposing scaffold designs have predominantly focused on homogeneous porous structures. Moreover, no consensus exists on the optimal structure for gradient porous scaffolds. Our scaffold closely imitated the natural bone structure by incorporating a gradient of pillar diameters. Additionally, we introduced a inverse gradient structure and three uniform diameter pillar structures (400 μm, 600 μm, and 1000 μm) for comparative analysis. Mechanical testing revealed that the compressive strength and elastic modulus of the Ti6Al4V porous scaffolds gradually increased with an increase in pillar diameter. In vitro experiments demonstrated that both the biomimetic gradient and inverse gradient scaffolds promoted osteogenic differentiation, with higher ALP activity (alkaline phosphatase) and osteogenesis-related gene expression compared to the uniform pillar structure scaffolds. The in vivo experiments confirmed these results, highlighting the superior ability of the biomimetic gradient Ti6Al4V porous scaffold to induce new bone formation. Based on our findings, we suggest that the optimal porous structure should have fine-diameter pillars (approximately 400 μm) internally to enhance cell penetration, while coarse-diameter pillars (approximately 800 μm) should be used externally to increase the cell attachment area and enhance mechanical strength. Overall, our study contributes to the field of bone tissue engineering by providing a biomimetic scaffold design that closely imitates the structure of natural bone and promotes osteogenic activity.

BACKGROUND: Gradient artificial bone repair scaffolds can mimic unique anatomical features in musculoskeletal tissues, showing great potential for repairing injured musculoskeletal tissues. OBJECTIVE: To review the latest research advances in gradient artificial bone repair scaffolds for tissue engineering in the musculoskeletal system and describe their advantages and fabrication strategies. METHODS: The first author of the article searched the Web of Science and PubMed databases for articles published from 2000 to 2023 with search terms "gradient, bone regeneration, scaffold". Finally, 76 papers were analyzed and summarized after the screening. RESULTS AND CONCLUSION: (1) As an important means of efficient and high-quality repair of skeletal system tissues, gradient artificial bone repair scaffolds are currently designed bionically for the natural gradient characteristics of bone tissue, bone-cartilage, and tendon-bone tissue. These scaffolds can mimic the extracellular matrix of native tissues to a certain extent in terms of structure and composition, thus promoting cell adhesion, migration, proliferation, differentiation, and regenerative recovery of damaged tissues to their native state. (2) Advanced manufacturing technology provides more possibilities for gradient artificial bone repair scaffold preparation: Gradient electrospun fiber scaffolds constructed by spatially differentiated fiber arrangement and loading of biologically active substances have been developed; gradient 3D printed scaffolds fabricated by layered stacking, graded porosity, and bio-3D printing technology; gradient hydrogel scaffolds fabricated by in-situ layered injections, simple layer-by-layer stacking, and freeze-drying method; and in addition, there are also scaffolds made by other modalities or multi-method coupling. These scaffolds have demonstrated good biocompatibility in vitro experiments, were able to accelerate tissue regeneration in small animal tests, and were observed to have significantly improved histological structure. (3) The currently developed gradient artificial bone repair scaffolds have problems such as mismatch of gradient scales, unclear material-tissue interactions, and side effects caused by degradation products, which need to be further optimized by combining the strengths of related disciplines and clinical needs in the future. [ABSTRACT FROM AUTHOR]

Real-world image denoising is important in image analysis such as image enhancement, object tracking, and recognition. However, the traditional deep learning-based methods suffer from insufficient ability to perceive global information and long inference time. Aiming at this issue, we construct a Transformer-based U-shaped denoising network (GUFORMER) and implement its deployment and inference acceleration on edge computing platforms. Specifically, the distributional adaptive module is introduced to promote the network’s ability to adapt to the complex distributional characteristics of real image noise. In addition, the improved Swin Transformer is utilized to enhance the perception of global feature information. Meanwhile, the limitation of Transformer in extracting local feature information is compensated by combining with multi-scale attention unit. Furthermore, the skip connection of the U-Net is optimized by the connected domain gradient extraction module to extract fine-grained features passed from the encoder to the decoder, thus reducing the redundancy of feature information and improving the network’s feature extraction capability. The proposed method has been verified on the real-world image datasets such as PolyU, SIDD, DND, and RNI15. Extensive experimental results show that the proposed method can effectively preserve image details while maintaining a higher inference speed. [ABSTRACT FROM AUTHOR]

Land cover is recognized as an important determinant of mosquito community assemblages and pathogen transmission, but few studies have investigated the role of land cover in populations of La Crosse virus (LACV) vectors. La Crosse virus is a zoonotic disease primarily maintained by native Aedes triseriatus, with accessory transmission by invasive vectors Ae. albopictus and Ae. japonicus. The objective of this study was to investigate the association between land cover composition and the egg abundances of LACV vectors in a city with endemic LACV transmission. Oviposition cups were deployed at sites ranging from recreational forests to urban areas. Mixed-effects regression models were used to test the relationships between land cover composition and species abundances. Sites characterized by large percentages of impervious and built surfaces were dominated by Ae. albopictus, but Ae. triseriatus was the most abundant species in forested areas. Aedes japonicus was rare at all sites, but its presence was associated with higher percentages of forested land. These results indicate that forested areas may allow Ae. triseriatus to maintain large populations near urban areas that are dominated by Ae. albopictus. Further research should explore the potential for these land cover-dependent population dynamics to influence LACV transmission cycles. [ABSTRACT FROM AUTHOR]

Abstract Lung images often have the characteristics of strong noise, uneven grayscale distribution, and complex pathological structures, which makes lung image segmentation a challenging task. To solve this problems, this paper proposes an initial lung mask extraction algorithm that combines threshold and gradient. The gradient used in the algorithm is obtained by the time series feature extraction method based on differential memory (TFDM), which is obtained by the grayscale threshold and image grayscale features. At the same time, we also proposed a lung contour repair algorithm based on the improved convex hull method to solve the contour loss caused by solid nodules and other lesions. Experimental results show that on the COVID-19 CT segmentation dataset, the advanced lung segmentation algorithm proposed in this article achieves better segmentation results and greatly improves the consistency and accuracy of lung segmentation. Our method can obtain more lung information, resulting in ideal segmentation effects with improved accuracy and robustness.

Inhomogeneities in the near-surface region of diffusion-doped silicon with manganese atoms were studied using the local photo-EMF method and photovoltage and photoconductivity signals were detected. It has been established that the inhomogeneous region is located at a depth of 3÷35 μm from the surface of the crystal. The magnitude of photo-EMF in these layers does not change monotonically from point to point. It was revealed that the photo-EMF spectra depend on the wavelength of the irradiated light, while the shape of the areas and their shift are related to the penetration depth of laser radiation. The photo-EMF signal increases to a depth of ~25 µm from the surface, then saturates and from ~30 µm smoothly decreases and completely disappears at a depth of ~40 µm. The magnitude of the internal electric field was determined using the Tauc method. A model of the structure of the near-surface region of diffusion-doped silicon with manganese is proposed.

An efficient method for the synthesis of a self‐supporting carbon framework (denoted Gra‐GC‐MoSe2) is proposed with a triple‐gradient structure—in sodiophilic sites, pore volume, and electrical conductivity—which facilitates the highly efficient regulation of Na deposition. In situ and ex situ measurements, together with theoretical calculations, reveal that the gradient distribution of Se heteroatoms in MoSe2, and its derivatives tailor the sodiophilicity, while the gradient distribution of porous nanostructures homogenizes the Na+ diffusion. Therefore, Na deposition occurs from the bottom to the top of the Gra‐GC‐MoSe2 framework without dendrite formation. In addition, the gradient in electrical conductivity ensures the stripping process does not lead to dead Na. As a result, a Gra‐GC‐MoSe2 modified Na anode (Na@Gra‐GC‐MoSe2) shows impressive cycling stability with a high average Coulombic efficiency in an asymmetric cell. In symmetric cells, it also exhibits a long cycling life of 2000 h with a low polarization voltage and works stably even under a large capacity of 10 mAh cm−2. Moreover, a Na@Gra‐GC‐MoSe2|| Na3V2(PO4)3 full cell delivers a high energy density with an excellent cycling performance. [ABSTRACT FROM AUTHOR]

High‐performance flexible pressure sensors have garnered widespread applications across numerous vital fields, encompassing flexible robotics, artificial intelligence, and brain‐computer interfaces. However, the small compressibility range of flexible materials and the easy saturation characteristics of microstructures greatly limit their practical applications. Therefore, achieving high sensitivity over an extensive pressure range remains a challenge. Here, inspired by the skin, a raised structure with graded features is designed as the sensitive layer. A flexible pressure sensor with high performance is manufactured by combining iontronic interfaces. The results indicate that this sensor can stably maintain a high sensitivity of 161.26 kPa−1 even at a pressure of 320 kPa. Moreover, this sensor also has a fast response time and recovery time of 26 and 85 ms, respectively. As a demonstration, these sensors are applied to materials stiffness recognition, human motion monitoring, and control of long‐distance four‐wheel vehicles. This work will offer valuable insights and serve as a useful reference for achieving high sensitivity and a broadened sensing range in sensors. [ABSTRACT FROM AUTHOR]

This paper presents a first implementation of gradient, divergence, and particle tracing schemes for the EMC3 code, a stochastic 3D plasma fluid code widely employed for edge plasma and impurity transport modeling in tokamaks and stellarators. These schemes are essential to accommodate plasma drift computations, which are currently absent in the code. Plasma drifts have been recognized to significantly influence transport of particles and energy, and their inclusion in future code upgrades will substantially enhance the code's predictive capabilities. For gradient and divergence calculations, we introduce a second‐order least‐squares gradient scheme. We confirm the second‐order convergence properties and assess the accuracy of several analytical test cases in the presence of synthetic noise. In the second part of this paper, we employ the validated gradient scheme in a fourth‐order Runge–Kutta particle tracing scheme to trace a particle through a generic drift velocity field. The impact of synthetic noise on the scheme's performance is investigated by evaluating various error metrics. We find that the implemented schemes function as intended and exhibit sufficient accuracy to enable drift computations. [ABSTRACT FROM AUTHOR]

Data regarding the impact of reduced left ventricular ejection fraction (LVEF) and/or reduced mean aortic valve gradient (AVG) on outcomes following transcatheter aortic valve intervention (TAVI) have been conflicting. We sought to assess the relationship between LVEF, AVG, and 1-year mortality in patients undergoing TAVI. We prospectively evaluated 298 consecutive adults undergoing TAVI from 2015 to 2018 at an academic tertiary medical center. Patients were categorized according to LVEF and mean AVG. The primary outcome of interest was all-cause mortality at 1 year. Of 298 adults undergoing TAVI, 66 (22.1%) had baseline LVEF ≤45% while 232 (77.9%) had baseline LVEF >45%; 173 (58.1%) had baseline AVG < 40mmHg while 125 (41.9%) had baseline AVG ≥ 40mmHg. Rates of 1-year all-cause mortality were significantly higher in patients with LVEF ≤45% (28.8% vs 12.1%, p = 0.001) and those with AVG < 40mmHg (19.7% vs 10.4%, p = 0.031) compared to those with LVEF >45% and AVG ≥ 40mmHg respectively. In multivariable analysis, higher AVG (per mmHg) (OR 0.97, 95% CI 0.94–0.99, p = 0.026) was noted to be independently associated with lower rates of 1-year mortality, while LVEF was not (OR 0.98, 95% CI 0.96–1.01). In this prospective, contemporary registry of adults undergoing TAVI, while 1-year unadjusted mortality rates are significantly higher in patients with reduced LVEF and reduced AVG, risk-adjusted mortality at 1 year is only higher in those with reduced AVG – not in those with reduced LVEF. • Low ejection fraction (EF) and aortic valve gradient (AVG) are common pre- transcatheter aortic valve intervention (TAVI). • Crude 1-year mortality rates following TAVI are significantly higher in patients with reduced EF and AVG at baseline. • Reduced AVG is independently associated with higher mortality at 1 year post TAVI. [ABSTRACT FROM AUTHOR]

This study presents the flexural analysis of Ti-6A1-4V/ZrO2 functionally graded (FG) sandwich plates under combined thermal and mechanical loading via exponential-cubic-sinusoidal integral shear deformation theory. The current formulation used in the modeling provides a parabolic distribution of transverse shear stresses without requiring additional factors in the formulation. Various sandwich plate models with different layer thicknesses and material types are considered. The FG layers vary continuously and smoothly according to exponential and power-law functions. The governing differential equations of the system are derived and solved analytically using the virtual work principle and Navier's approach. Benchmark comparisons are performed to validate and show the accuracy of the proposed model. Various parametric examples are presented to illustrate the effect of the geometry, dimensions, FG sandwich type and material gradient on the static flexural response of the studied structure. [ABSTRACT FROM AUTHOR]

Lung images often have the characteristics of strong noise, uneven grayscale distribution, and complex pathological structures, which makes lung image segmentation a challenging task. To solve this problems, this paper proposes an initial lung mask extraction algorithm that combines threshold and gradient. The gradient used in the algorithm is obtained by the time series feature extraction method based on differential memory (TFDM), which is obtained by the grayscale threshold and image grayscale features. At the same time, we also proposed a lung contour repair algorithm based on the improved convex hull method to solve the contour loss caused by solid nodules and other lesions. Experimental results show that on the COVID-19 CT segmentation dataset, the advanced lung segmentation algorithm proposed in this article achieves better segmentation results and greatly improves the consistency and accuracy of lung segmentation. Our method can obtain more lung information, resulting in ideal segmentation effects with improved accuracy and robustness. [ABSTRACT FROM AUTHOR]

Meniscal implants with biomimetic 3D architecture, gradient mechanical properties, and excellent biocompatibility are urgently required due to the increasing incidence of meniscus injuries. Inspired by the microstructure of the meniscus, which consists of a meshwork interwoven with collagen fibers and a hydrophilic matrix filled with glycosaminoglycans and chondrocytes, here a type of structurally and functionally optimized meniscal scaffolds is prepared. Direct‐ink‐writing 3D printing technology is utilized to construct an elastomeric skeleton with a biomimetic 3D and gradient microstructure, and then hydrogel resin is infiltrated into the skeleton, resulting in an elastomer‐reinforced hydrogel composite meniscal scaffold through co‐curing of the elastomer and hydrogel resins. The composite meniscal scaffolds exhibit a highly porous structure and biomimetic gradient mechanical properties by controlling the ratio of elastomer and hydrogel materials. The co‐curing of the two materials creates robust interfaces through strong covalent bonding, ensuring their reliable long‐term mechanical performance. Furthermore, the coexistence of aqueous and oily phases of the emulsion‐type hydrogel resin allows the loading of both water‐soluble and lipid‐soluble drugs, endowing the composite scaffolds with a diphasic drug‐release capacity. The composite scaffolds are then implanted in the knee joints of beagle canines, successfully promoting the repair of meniscal injury and tissue regeneration. [ABSTRACT FROM AUTHOR]

Socio-economic differences in mortality are among the most pervasive characteristics of Western societies. While the mortality gradient by income is well established for the period after 1970, knowledge about the origins of this gradient is still rudimentary. We analyse the association between income and cause-specific adult mortality during the period 1905–2014 in an area of southern Sweden, using competing-risk hazard models with individual-level longitudinal data for over 2.2 million person-years and over 35,000 deaths. We find that the present-day income gradient in adult mortality emerged only in the period after the Second World War and did so for the leading causes of death and for men and women largely simultaneously. [ABSTRACT FROM AUTHOR]

Aims: Spinocerebellar Ataxia Type 3 (SCA3) is a rare genetic ataxia that impacts the entire brain and is characterized as a neurodegenerative disorder affecting the neural network. This study explores how alterations in the functional hierarchy, connectivity, and structural changes within specific brain regions significantly contribute to the heterogeneity of symptom manifestations in patients with SCA3. Methods: We prospectively recruited 51 patients with SCA3 and 59 age‐and sex‐matched healthy controls. All participants underwent comprehensive multimodal neuroimaging and clinical assessments. In SCA3 patients, an innovative approach utilizing gradients in resting‐state functional connectivity (FC) was employed to examine atypical patterns of hierarchical processing topology from sensorimotor to supramodal regions in the cerebellum and cerebrum. Coupling analyses of abnormal FC and structural connectivity among regions of interest (ROIs) in the brain were also performed to characterize connectivity alterations. Additionally, relationships between quantitative ROI values and clinical variables were explored. Results: Patients with SCA3 exhibited either compression or expansion within the primary sensorimotor‐to‐supramodal gradient through four distinct calculation methods, along with disruptions in FC and structural connectivity coupling. A comprehensive correlation was identified between the altered gradients and the clinical manifestations observed in patients. Notably, altered fractional anisotropy values were not significantly correlated with clinical variables. Conclusion: Abnormal gradients and connectivity in the cerebellar and cerebral cortices in SCA3 patients may contribute to disrupted motor‐to‐supramodal functions. Moreover, these findings support the potential utility of FCG analysis as a biomarker for diagnosing SCA3 and assessing treatment efficacy. [ABSTRACT FROM AUTHOR]

Arc grounding faults occur frequently in the power grid with small resistance grounding neutral points. The existing arc fault identification technology only uses the fault line signal characteristics to set the identification index, which leads to detection failure when the arc zero-off characteristic is short. To solve this problem, this paper presents an arc fault identification method by utilizing integrated signal characteristics of both the fault line and sound lines. Firstly, the waveform characteristics of the fault line and sound lines under an arc grounding fault are studied. After that, the convex hull, gradient product, and correlation coefficient index are used as the basic characteristic parameters to establish fault identification criteria. Then, the logistic regression algorithm is employed to deal with the reference samples, establish the machine discrimination model, and realize the discrimination of fault types. Finally, simulation test results and experimental results verify the accuracy of the proposed method. The comparison analysis shows that the proposed method has higher recognition accuracy, especially when the arc dissipation power is smaller than 2 x 10³ W, the zero-off period is not obvious. In conclusion, the proposed method expands the arc fault identification theory. [ABSTRACT FROM AUTHOR]

In this paper, a convolutional recurrent neural network (ConvRNN) wavelet-based kernel is proposed to improve the time–frequency localization of non-stationary signals. Time–frequency distributions (TFDs) are used to localize the power spectral density components of a signal simultaneously over the time–frequency plane. For various non-stationary signals (NSS) with different features, poor time–frequency resolution is always an inherent problem in all developed TFDs. This is mainly due to inefficient segmentation methods and improper kernel adaptation. In the current work, the fraction Bezier–Bernstein polynomial function is applied to model the NSS, and points of inflection are used for signal segmentation. From the obtained segments, statistical time–frequency features are extracted and fed to a ConvRNN for better time–frequency localization. The ConvRNN employs a convolution computation between input signal features and the proposed Newton–Raphson gradient algorithm (NRGA)-based wavelet function. The optimization of the ConvRNN network is achieved by incorporating a hybrid method that combines the principles of normalized adaptive gradient descent and momentum-based optimization, with an additional normalization step to enhance convergence and stability. The ConvRNN weights are updated in both forward and backward directions (resilient propagation) until a better correlation is achieved between signal segments and the wavelet kernel. It is observed that the proposed ConvRNN NRGA wavelet improves the time–frequency localization when compared with standard TFDs and state-of-the-art methodologies. Furthermore, the proposed ConvRNN model is compared with other CNN and RNN architectures for better practical interpretations. [ABSTRACT FROM AUTHOR]

Flexible sensors are prone to the problems of slow recovery rate and large residual strain in practical use. In this paper, a polyurethane functional composite with a gradient change in elastic modulus is proposed as a flexible sensor to meet the recovery rate and residual strain without affecting the motion. Different hard and soft segment ratios are used to synthesize a gradient polyurethane structure. The conductive percolation threshold was obtained between 45 wt% and 50 wt% of flake silver powder. Both gradient polyurethane and gradient polyurethane composites demonstrated that gradient materials can increase the recovery rate and reduce residual strain. The gradient polyurethane composites had a tensile strength of 3.26 MPa, an elastic modulus of 2.58 MPa, an elongation at break of 245%, a sensitivity coefficient of 1.20 at 0–25% deformation, a sensitivity coefficient of 11.38 at 25–75% deformation, a rate of recovery of 1.95 s at a time, and a resistance to fatigue (over 1000 cycles at a fixed strain of 20% showed a stable electrical response). The sensing performance under different cyclic strain frequencies was also investigated. The process has practical applications in the field of wearable skin motion and health monitoring. [ABSTRACT FROM AUTHOR]

Ultrathin flexible organic solar cells (OSCs) have garnered widespread attention in wearable electronic devices for their lightweight and excellent conformability. Silver nanowires (AgNWs) are one of the most widely used bottom electrodes because of their high conductivity and transmittance. However, the high roughness of AgNWs on the flexible substrate exerts adverse effects on device performance. To address this critical issue, a bilayer electron‐transport‐materials (ETMs) strategy consisting of an indium‐doped zinc oxide (IZO) and a pristine ZnO is developed. The IZO is utilized as the first layer of ETM, which can effectively fill voids in AgNWs to form a high‐conductive composite electrode. The ZnO is used as the second layer of ETM, facilitating charge extraction. The ultrathin flexible OSCs prepared based on the gradient bilayer ETMs can achieve a power conversion efficiency (PCE) of 16.1%, associated with improved mechanical stability, showing a PCE retention of 93% after 10 000 bending cycles (R = 1 mm) and 82% under 1000 compression (30%)‐release cycling test. To the best of knowledge, it's one of the highest efficiency for ultrathin (less than 10 μm) flexible OSCs based on the solution‐processed electrodes. This work will provide a new avenue for fabricating high‐performance and mechanically robust ultraflexible ITO‐free OSCs. [ABSTRACT FROM AUTHOR]

The problem of controllability for problems of optimal control and optimization of distributed parameter systems governed by partial differential equations is considered. The concept of controllability understood as Tikhonov correctness for solving optimization problems is introduced. A theorem formulating controllability conditions for directly solving optimization problems (direct minimization of the objective functional) is presented. A test example of the numerical solution of the optimization problem for a nonlinear hyperbolic system describing the unsteady flow of water in an open channel is considered. The analysis of controllability is demonstrated that ensures the correctness of the problem solution and high accuracy of optimization of the distributed friction coefficient in the flow equations. [ABSTRACT FROM AUTHOR]

Copyright of Rudarsko-Geolosko-Naftni Zbornik is the property of Faculty of Mining, Geology & Petroleum Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of New Building Materials / Xinxing Jianzhu Cailiao is the property of New Building Materials Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The repair of bone defects necessitates the establishment of sophisticated gradients. However, most strategies for gradient casting require specialized apparatus and have high equipment requirements. Therefore, there is a strong desire to develop a simple method for constructing gradient scaffolds that mimic the hierarchical structure of native bone. In this study, we prepared poly (vinyl alcohol)/bacterial cellulose (PVA/BC) scaffolds with gradient hydroxyapatite (HAp) content using the buoyancy-driven gradient (BG) method. Scanning electron microscopy characterization revealed that HAp gradient scaffold exhibited the gradient microstructure and HAp content. Furthermore, HAp gradient scaffold demonstrated enhanced adhesion, spreading, and proliferation of MC3T3-E1 cells and displayed excellent osteogenic ability. Additionally, when applied in subcutaneous implantation models in mice, HAp gradient scaffold showed superior biocompatibility compared to other scaffolds tested in vitro. These results present a straightforward approach for fabricating gradient HAp bone scaffolds that hold great potential as candidate materials for bone regeneration. [ABSTRACT FROM AUTHOR]

Habitat-specific thermal responses are well documented in various organisms and likely determine the vulnerability of populations to climate change. However, the underlying roles of genetics and plasticity that shape such habitat-specific patterns are rarely investigated together. Here we examined the thermal plasticity of the butterfly Bicyclus dorothea originating from rainforest and ecotone habitats in Cameroon under common garden conditions. We also sampled wild-caught butterflies from forest and ecotone sites and used RADseq to explore genome-wide population differentiation. We found differences in the level of phenotypic plasticity across habitats. Specifically, ecotone populations exhibited greater sensitivity in wing eyespot features with variable development temperatures relative to rainforest populations. Known adaptive roles of wing eyespots in Bicyclus species suggest that this morphological plasticity is likely under divergent selection across environmental gradients. However, we found no distinct population structure of genome-wide variation between habitats, suggesting high level of ongoing gene flow between habitats is homogenizing most parts of the genome.

Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning. These calculations are readily available for arbitrary models via "automatic differentiation" implemented in general-purpose machine-learning libraries such as TensorFlow and PyTorch. Although these libraries are highly optimized, it is not clear if their general-purpose nature will limit their algorithmic complexity or implementation speed for the phylogenetic case compared to phylogenetics-specific code. In this paper, we compare six gradient implementations of the phylogenetic likelihood functions, in isolation and also as part of a variational inference procedure. We find that although automatic differentiation can scale approximately linearly in tree size, it is much slower than the carefully implemented gradient calculation for tree likelihood and ratio transformation operations. We conclude that a mixed approach combining phylogenetic libraries with machine learning libraries will provide the optimal combination of speed and model flexibility moving forward.

Earlier studies acknowledged that the design speed does not principally assure consistency in the design of highway geometric elements. Methodologies for estimating operating speeds are limited to specific or local traffic conditions and design standards, as in various studies conducted on two-lane and multi-lane highways. The present study develops operating speed models of the vehicle types observed on horizontal curves and tangent sections on two-lane highways in southern parts of India. Geometric features of the curve section and adjacent tangent sections, such as the radius of the curve, curve length, deflection angle, degree of curvature, gradient, carriageway width, and shoulder width, are obtained from the field. The speed data collected at 24 locations on the highway, including curved and tangent gradient sections, are used to analyze and model operating speed. The results indicate that the inverse of the square root of the radius appears to be an influencing parameter for modeling the operating speed of vehicles. The operating speed is sensitive for a curve radius of up to 600 m; thereafter, the operating speed appears insignificant. On tangent sections, the gradient has a larger influence on the operating speeds of all vehicle types. The operating speed models are validated and compared with models available in the literature. The proposed models developed in the present study are helpful to traffic engineers for predicting the operating speed on two-lane highways.

The bone-cartilage interface is defined by a unique arrangement of cells and tissue matrix. Injury to the interface can contribute to the development of arthritic joint disease. Attempts to repair osteochondral damage through clinical trials have generated mixed outcomes. Tissue engineering offers the potential of integrated scaffold design with multiregional architecture to assist in tissue regeneration, such as the bone-cartilage interface. Challenges remain in joining distinct materials in a single scaffold mass while maintaining integrity and avoiding delamination. The aim of the current work is to examine the possibility of joining two closely related acrylamide derivatives such as, poly n-isopropyl acrylamide (pNIPAM) and poly n‑tert‑butyl acrylamide (pNTBAM). The target is to produce a single scaffold unit with distinct architectural regions in the favour of regenerating the osteochondral interface. Longitudinal phosphate glass fibres (PGFs) with the formula 50P2O5.30CaO.20Na2O were incorporated to provide additional bioactivity by degradation to release ions such as calcium and phosphate which are considered valuable to assist the mineralization process. Polymers were prepared via atom transfer radical polymerization (ATRP) and solutions cast to ensure the integration of polymers chains. Scaffold was characterized using scanning electron microscope (SEM) and Fourier transform infra-red (FTIR) techniques. The PGF mass degradation pattern was inspected using micro computed tomography (µCT). Biological assessment of primary human osteoblasts (hOBs) and primary human chondrocytes (hCHs) upon scaffolds was performed using alizarin red and colorimetric calcium assay for mineralization assessment; alcian blue staining and dimethyl-methylene blue (DMMB) assay for glycosaminoglycans (GAGs); immunostaining and enzyme-linked immunosorbent assay (ELISA) to detect functional proteins expression by cells such as collagen I, II, and annexin A2. FTIR analysis revealed an intact unit with gradual transformation from pNIPAM to pNTBAM. SEM images showed three distinct architectural regions with mean pore diameter of 54.5 µm (pNIPAM), 16.5 µm (pNTBAM) and 118 µm at the mixed interface. Osteogenic and mineralization potential by cells was observed upon the entire scaffold's regions. Chondrogenic activity was relevant on the pNTBAM side of the scaffold only with minimal evidence in the pNIPAM region. PGFs increased mineralization potential of both hOBs and hCHs, evidenced by elevated collagens I, X, and annexin A2 with reduction of collagen II in PGFs scaffolds. In conclusion, pNIPAM and pNTBAM integration created a multiregional scaffold with distinct architectural regions. Differential chondrogenic, osteogenic, and mineralized cell performance, in addition to the impact of PGF, suggests a potential role for phosphate glass-incorporated, acrylamide-derivative scaffolds in osteochondral interface regeneration.

Extracellular vesicles (EVs) influence a host of normal and pathophysiological processes in vivo. Compared to soluble mediators, EVs can traffic a wide range of proteins on their surface including extracellular matrix (ECM) binding proteins, and their large size (∼30-150 nm) limits diffusion. We isolated EVs from the MCF10 series-a model human cell line of breast cancer progression-and demonstrated increasing presence of laminin-binding integrins α3β1 and α6β1 on the EVs as the malignant potential of the MCF10 cells increased. Transport of the EVs within a microfluidic device under controlled physiological interstitial flow (0.15-0.75 μm/s) demonstrated that convection was the dominant mechanism of transport. Binding of the EVs to the ECM enhanced the spatial concentration and gradient, which was mitigated by blocking integrins α3β1 and α6β1. Our studies demonstrate that convection and ECM binding are the dominant mechanisms controlling EV interstitial transport and should be leveraged in nanotherapeutic design.