Nature provides us with a wealth of inspiration for the design of bionic functional surfaces. Numerous types of plant leaves with exceptional wettability, anisotropy, and adhesion are extensively employed in many engineering applications. Inspired by the wettability, anisotropy, and adhesion of indocalamus leaves, bionic upper and lower surfaces (BUSs and BLSs) of the indocalamus leaf were successfully prepared using a facile approach combining laser scanning and chemical modification. The results demonstrated the BUSs and BLSs obtained similar structural features to the upper and lower surfaces of the indocalamus leaf and exhibited enhanced and more-controllable wettability, anisotropy, and adhesion. More importantly, we conducted a detailed comparative analysis of the wettability, anisotropy, and adhesion between BUSs and BLSs. Finally, BUSs and BLSs were also explored for the corresponding potential applications, including self-cleaning, liquid manipulation, and fog collection, thereby broadening their practical utility. We believe that this study can contribute to the enrichment of the research on novel biological models and provide significant insights into the development of multifunctional bionic surfaces.

The yield behavior of aluminum alloy 5754-H111 under different stress conditions for three kinds of plastic work is studied using an anisotropic Drucker model. It is found that when the plastic work is 30 MPa, the anisotropic Drucker model has the most accurate prediction. Comparing the Hill48 and Yld91 models with the Drucker model, the results show that both the anisotropic Drucker and Yld91 models can accurately predict the yield behavior of the alloy. Cylinder drawing finite element analysis is performed under the AFR, but it is not possible to accurately predict the position and height of earing appearance. The anisotropic Drucker model is used to predict the earing behavior under the non-AFR, which can accurately predict the earing phenomenon. Numerical simulation is conducted using three different combinations of yield functions: the anisotropic yield function and the anisotropic plastic potential function (AYAPP), the anisotropic yield function and the isotropic plastic potential function (AYIPP), and the isotropic yield function and the anisotropic plastic potential function (IYAPP). It is concluded that the influence of the plastic potential function on predicting earing behavior is more critical than that of the yield function.

Additive manufacturing (AM) is a technology that builds parts layer by layer. Over the past decade, metal additive manufacturing (AM) technology has developed rapidly to form a complete industry chain. AM metal parts are employed in a multitude of industries, including biomedical, aerospace, automotive, marine, and offshore. The design of components can be improved to a greater extent than is possible with existing manufacturing processes, which can result in a significant enhancement of performance. Studies on the anisotropy of additively manufactured metallic materials have been reported, and they describe the advantages and disadvantages of preparing different metallic materials using additive manufacturing processes; however, there are few in-depth and comprehensive studies that summarize the microstructural and mechanical properties of different types of additively manufactured metallic materials in the same article. This paper begins by outlining the intricate relationship between the additive manufacturing process, microstructure, and metal properties. It then explains the fundamental principles of powder bed fusion (PBF) and directed energy deposition (DED). It goes on to describe the molten pool and heat-affected zone in the additive manufacturing process and analyzes their effects on the microstructure of the formed parts. Subsequently, the mechanical properties and typical microstructures of additively manufactured titanium alloys, stainless steel, magnesium-aluminum alloys, and high-temperature alloys, along with their anisotropy, are summarized and presented. The summary indicates that the factors leading to the anisotropy of the mechanical properties of metallic AM parts are either their unique microstructural features or manufacturing defects. This anisotropy can be improved by post-heat treatment. Finally, the most recent research on the subject of metal AM anisotropy is presented.

Presbycusis, or age-related hearing loss, affects both elderly humans and dogs, significantly impairing their social interactions and cognition. In humans, presbycusis involves changes in peripheral and central auditory systems, with central changes potentially occurring independently. While peripheral presbycusis in dogs is well-documented, research on central changes remains limited. Diffusion tensor imaging (DTI) is a useful tool for detecting and quantifying cerebral white matter abnormalities. This study used DTI to explore the central auditory pathway of senior dogs, aiming to enhance our understanding of canine presbycusis. Dogs beyond 75% of their expected lifespan were recruited and screened with brainstem auditory evoked response testing to select dogs without severe peripheral hearing loss. Sixteen dogs meeting the criteria were scanned using a 3 T magnetic resonance scanner. Tract-based spatial statistics was used to analyze the central auditory pathways. A significant negative correlation between fractional lifespan and fractional anisotropy was found in the acoustic radiation, suggesting age-related white matter changes in the central auditory system. These changes, observed in dogs without severe peripheral hearing loss, may contribute to central presbycusis development.

Swell-shrink characteristic soils exhibit a high susceptibility to cracking during the drying process, which poses a significant risk of various geological disasters. Among these, the occurrence of drying shrinkage acts as a prerequisite for the cracking phenomenon. Therefore, it is of utmost importance to comprehend the specific characteristics associated with the drying shrinkage mechanism. To investigate the drying shrinkage behavior of swell-shrink characteristic soils, a series of drying shrinkage experiments were conducted on long strip samples of red clay and expansive soil. Utilizing three-dimensional digital image correlation (DIC) technology, the surface displacement, strain, and anisotropic shrinkage rates of the soil samples during the drying process were obtained, and the size effect on the drying shrinkage of swell-shrink characteristic soil were analyzed. The research findings are as follows: The displacement development of the soil samples in the X and Y directions can be divided into two stages: a linear growth stage and a stable displacement stage. In the Z direction, the soil surface deformation can be divided into three stages: soil surface arching, vertical shrinkage, and shrinkage stabilization. The drying shrinkage of swell-shrink characteristic soil exhibits anisotropy, with the vertical shrinkage rate being the largest, followed by the longitudinal and then the transverse directions. Additionally, the soil sample shrinkage exhibits a size effect, whereby the shrinkage rates in all directions increase with increasing sample width and thickness. During the drying shrinkage process, the stress state on the soil surface evolves from initial tensile strain to subsequent compressive strain. The strain at different positions and times within the soil sample is not uniform, resulting in the non-uniformity and anisotropy of the sample shrinkage. This study provides important insights into the cracking mechanism of swell-shrink characteristic soils and serves as a valuable reference for related laboratory experiments, which will contribute to better prediction and control the geological hazards caused by the drying shrinkage of swell-shrink characteristic soils.

This study explores the potential of untapped lithium hydroxide (LiOH) as a phase change material for thermal energy storage. By overcoming the challenges associated with the liquid LiOH leakage, we successfully thermal-cycled LiOH in a laboratory scale experimentation, and observed its stability (>500 thermal cycles), without chemical decomposition. This step has never been performed to date. Its solid-to-liquid reversible transitions temperatures and related solidification/melting enthalpies values have been verified. Then, the first experimental characterization of LiOH\'s thermal properties shows unexpected values for its heat capacity, thermal conductivity and diffusivity, in contradiction with the few ones available in literature. This opens avenues for LiOH\'s applications for the storage of sensible and latent heat, as shown through the increased cycle efficiency potential of a thermal energy storage system if based on its energy storage capacity; up to six times more volumetric energy density compared to traditional Solar Salt-based systems used in the solar tower plant (4.5 GJ/m3 vs. 0.76 GJ/m3 over 1000 thermal cycles). Additionally, we observed a softening phenomenon that occurs inconsistently during heating, but which may account for its excellent melting properties and the interplay with other raw chemicals. This new insight contributes certainly to the underlying mechanisms in the synthesis of another promising heat storage material in development: the peritectic compound Li4Br(OH)3. This pioneering work suggests LiOH as a promising ultra-compact thermal energy storage material for filling the intermediary gap from current to next-generation solar power plants, although its large-scale application requires further investigation to achieve economic viability.

Restricted, repetitive behaviors are common symptoms in neurodevelopmental disorders including autism spectrum disorder. Despite being associated with poor developmental outcomes, repetitive behaviors remain poorly understood and have limited treatment options. Environmental enrichment attenuates the development of repetitive behaviors, but the exact mechanisms remain obscure. Using the C58 mouse model of repetitive behavior, we performed diffusion tensor imaging to examine microstructural alterations associated with the development of repetitive behavior and its attenuation by environmental enrichment. The C57BL/6 mouse strain, which displays little or no repetitive behavior, was used as a control group. We observed widespread differences in diffusion metrics between C58 mice and C57BL/6 mice. In juvenile C58 mice, repetitive motor behavior displayed strong negative correlations with fractional anisotropy in multiple gray matter regions, whereas in young adult C58 mice, high repetitive motor behavior was most strongly associated with lower fractional anisotropy and higher radial diffusivity in the striatum. Environmental enrichment increased fractional anisotropy and axial diffusivity throughout gray matter regions in the brains of juvenile C58 mice and overlapped predominantly with cerebellar and sensory regions associated with repetitive behavior. Our results suggest environmental enrichment reduces repetitive behavior development by altering gray matter microstructure in the cerebellum, medial entorhinal cortex, and sensory processing regions in juvenile C58 mice. Under standard laboratory conditions, early pathology in these regions appears to contribute to later striatal and white matter dysfunction in adult C58 mice. Future studies should examine the role these regions play in the development of repetitive behavior and the relationship between sensory processing and cerebellar deficits and repetitive behavior.

Information on the clinical outcomes of feline azotemia using ultrasound examinations is limited. This study aimed to understand the correlation between cortical anisotropy backscattering artifact (CABA) and serum creatinine (sCr) changes in feline azotemia after hospitalization and to investigate whether CABA is useful for predicting the clinical outcome of feline azotemia. Sixty-five hospitalized cats with azotemia, including 49 cats with moderate or severe azotemia (severe group) and 16 cats with mild azotemia (mild group). This retrospective study reviewed the CABA using ultrasound images of cats hospitalized with azotemia between 2016 and 2021. The correlation between CABA and the clinical outcomes of cats with azotemia was investigated using the chi-squared or Fisher\'s exact test, and the intra- and inter-observer agreements in CABA were assessed using McNemar\'s and Cohen\'s kappa tests. The presence of CABA was significantly positively correlated with the clinical outcomes of cats with azotemia only in the severe group (p = 0.0034, odds ratio = 8.57). There was no association between CABA and clinical outcomes in cats with mild azotemia (p = 0.75). CABA can be used for clinical outcome prediction in moderate and severe feline azotemia, with a sensitivity of 80.8% and a specificity of 73.9%. Also, satisfactory intra- and inter-observer agreements were revealed in the detection of CABA during ultrasound image review. Our study demonstrated that cats with moderate and severe azotemia with CABA observed during ultrasonography might have better clinical outcomes. These findings provide additional information on the prognosis and treatment of feline azotemia.

In the present work, the mechanical anisotropic behavior of low-carbon (Fe-0.07C) steel processed by asymmetric cold rolling was investigated. Three different types of dynamic recrystallization (DRX) mechanisms (continuous, discontinuous, and geometric) were observed in the microstructure of the 75 % cold-rolled sheet. The average intensity of γ-fiber was remarkably enhanced to 2.8 × R as rolling deformation increased to 50 % due to the formation of many deformation bands. After 75 % cold rolling, the average intensity of γ-fiber was significantly decreased to 1.4 × R due to the creation of new recrystallized grains. The results exhibited that the hardness of the low-carbon steel sheet was 260.1 HV by 75 % cold rolling, which was 1.75 times larger than the initial low-carbon steel sheet. With increasing deformation degree, the average yield and tensile strengths gradually improved and reached a peak value of 844.8 MPa and 881.7 MPa after 75 % cold rolling, respectively, which were 2.8 and 2.1 times that of the initial low-carbon steel sheet. By increasing the rolling reduction up to 50 %, the mechanical anisotropy gradually enhanced and by further increasing the cold deformation to 75 %, the anisotropy rapidly decreased due to the weakening of the γ-fiber texture. The strength was the highest along the transverse direction (90°) in all low-carbon steel sheets, and decreased at 0° and 45°. The dσ/dε-ε curves of the 50 % cold-rolled low-carbon steel sheet for the 45° and 90° tensile directions exhibited two distinct stages during the loading, however, that for the 0° revealed only one stage. A large number of parallel striations were present on the fracture surface of the 50 % deformed low-carbon steel sheet at 90° due to the presence of parallel deformation bands.

The influence of acoustic anisotropy on ultrasonic testing reliability poses a challenge in evaluating products from additive technologies (AT). This study investigates how elasticity constants of anisotropic materials affect defect signal amplitudes in AT products. Experimental measurements on AT samples were conducted to determine elasticity constants. Using Computational Modeling and Simulation Software (CIVA), simulations explored echo signal changes across ultrasound propagation directions. The parameters A13 (the ratio between the velocities of ultrasonic transverse waves with vertical and horizontal polarizations at a 45-degree angle to the growth direction), A3 (the ratio for waves at a 90-degree angle), and Ag (the modulus of the difference between A13 and A3) were derived from wave velocity relationships and used to characterize acoustic anisotropy. Comparative analysis revealed a strong correlation (0.97) between the proposed anisotropy coefficient Ag and the amplitude changes. Threshold values of Ag were introduced to classify anisotropic materials based on observed amplitude changes in defect echo signals. In addition, a method leveraging deep learning to predict Ag based on data from other anisotropy constants through genetic algorithm (GA)-optimized neural network (NN) architectures is proposed, offering an approach that can reduce the computational costs associated with calculating such constants.