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Advancements in artificial intelligence have significantly improved the monitoring of tool wear in machining processes, thereby enhancing the overall quality of machining. However, the scarcity of tool wear samples poses a challenge to the enhancement of model precision. This necessitates the exploration of monitoring techniques that are effective even with small sample sizes. A method involving a triplet long short-term memory (LSTM) neural network is introduced, which offers the potential for superior accuracy even with limited training data. During the machining process, spindle vibrations are captured using a triaxial accelerometer. The raw data is processed by a triplet network, which uses an LSTM as the base model, thereby facilitating the aggregation within classes and separation between classes. A soft-max classification layer is subsequently integrated into the model, which enables the precise determination of tool wear states. The base model is optimized using a Genetic Algorithm to ensure model efficiency and accuracy before it is expanded into a triplet network. Experimental results from a vertical machining center confirm that the triplet LSTM network offers superior accuracy compared to a standard LSTM network, even when the sample size is small. [ABSTRACT FROM AUTHOR]

Developing sensitive metal–organic framework (MOF) systems to overcome the ubiquitous trade-off between porosity and conductivity remains a formidable yet sought-after endeavor. This pursuit is of great significance for the development of MOF-based chemiresistive sensors with enhanced sensitivity and selectivity. Herein, we present an innovative template assisted strategy that utilizes the two-dimensional properties and good conductivity of MXene nanosheets, as well as lattice matching between MXene (Nb2C) and selected Ni3(HITP)2, to achieve controllable self-assembly of Ni3(HITP)2 on MXene sheets. This results in Ni3(HITP)2/MXene (HITP: 2,3,6,7,10,11-hexaaminotriphenylene) heterostructures with considerable conductivity, porosity, and solution processability. The powder and film electrical conductivity are 4.8 × 103 and 5.3 × 105 S m−1, respectively, and the BET specific surface area can reach 797.8 m2 g−1. It is worth noting that excellent solution processability helps to prepare large-area films (23 cm × 9 cm) with good uniformity. Gas sensors based on Ni3(HITP)2/MXene heterostructures exhibit high sensitivity (LOD ∼ 5 ppb) and selectivity towards ultratrace ethanol at room temperature, setting a new benchmark. Such sensing behavior stems from the strong coupling of Ni3(HITP)2/MXene heterostructures and their enhanced interaction with ethanol, evidenced by experimental results and theoretical calculations. Real-time respiratory sensing assessments underscore their practicality in healthcare monitoring. This straightforward approach simplifies the integration of MOF-related materials on miniaturized devices with outstanding performance. [ABSTRACT FROM AUTHOR]

To address the low clearance rate issue of the anti-blocking mechanism for maize no-till planters in the Huang-Huai-Hai Plain of China, experiments and simulations were conducted to analyze the individual and collective movements of straw under the action of the round roller-claw anti-blocking mechanism. A tracer-based measurement method for straw displacement was applied firstly. Experimental results showed that the straw forward displacement could be characterized by the average horizontal displacements of longitudinal and lateral tracers, while the straw side displacement could be characterized by the lateral displacement of the longitudinal tracer. The straw forward displacement was 58.95% greater than the side displacement. Forward, side, and total displacements of straw increased as the mechanism's forward speed increased from 3 km/h to 7 km/h, with corresponding rates of increase at 233.98%, 43.20%, and 162.47%, respectively. Furthermore, a model of straw–soil–mechanism interaction was constructed in EDEM 2022 software. The relative error between experimental and simulated straw clearance rates was 11.20%, confirming the applicability of the simulation model for studying straw–soil–mechanism interaction. Based on the simulation model, three straw tracers of different lengths were selected to study the motion behavior of straw. It was inferred that despite differences in straw length, the movement behaviors of the three straw tracers under the influence of the anti-blocking mechanism were similar. Additionally, longer straws exhibited greater displacements in all directions. This paper serves as a reference for studying straw motion behavior influenced by anti-blocking mechanisms. [ABSTRACT FROM AUTHOR]

Maize seeding is greatly affected by improper seed placement and poor planter performance under a no-tillage mechanisation system. To overcome the issue, we explored the impact of separating board and anti-blocking mechanism (0, 1/4, 1/2, 2/3, 3/4, and 1 type) on maize seeding under different forward speeds (3, 5, 7 km/h) and rotational speeds (260, 400, 530, 740 rpm), where the performance metrics included the mass of straw coiled, seeding height, emergence rate, soil mound depth, straw movement, and straw clearance. The study results show that separating board helps to increase forward and side displacements of the straw, which avoids localized accumulation of straw around the antiblocking mechanism. The straw clearance rate of the anti-blocking mechanism with a separating board is greater than that without the separating board. Therefore, the 2/3 type anti-blocking mechanism with a separating board is recommended for maize seeding at a forward speed of 5 km/h and a rotational speed of 400 rpm.

Background: ASXL2 encodes proteins involved in epigenetic regulation and the assembly of transcription factors at specific genomic loci. Germline de novo truncating variants in ASXL2 have been implicated in Shashi‐Pena syndrome, which results in features of developmental delay (DD), glabellar nevus flammeus, hypotonia, and cardiac disorders. However, the variants are rare, and the clinical spectrum may be incomplete. Methods: The clinical data such as brain MRI were collect. The whole exome sequencing was performed for genetic etiology analysis. Results: Here, we report a patient with DD, hypotonia, early atrial septal defect, and abnormal white matter signal. She presented with Shashi–Pena syndrome with a truncated variant in ASXL2 (NM_018263.6, c.2142_2152del, p.Ser714Argfs*5). She died of a digestive tract infection when she was 1 year and 6 months old. Conclusions: Our study further expanded the spectrum of phenotypes and genetic variations of the syndrome, and we believe that it is necessary to screen the ASXL2 gene in patients with DD and cardiac and bone disorders. [ABSTRACT FROM AUTHOR]