Suchergebnisse

Agricultural mechanization is essential to increase farmers' income in modern agriculture. However, the use of machinery for crop production in China is quite inefficient. To understand the obstacles limiting farmers' use of machinery, we conducted face-to-face interview surveys with 1023 farmers (including cooperative directors, machine operators, and farmers without machines) in two major cereal-producing regions with large differences in farming scale: the North China Plain (2.7 ha per capita) and the Northeast China Plain (12.8 ha per capita). The results revealed that farmers in both regions had strong will to use machines. The obstacle preventing farmers from buying machines was the lack of machinery training in the Northeast China Plain and land fragmentation in the North China Plain. Among different farmer groups, land fragmentation was the main barrier for cooperative directors. Farmers without machines thought that there was lack of machinery training and that the cost of machinery purchase was high. Machine operators believed that machine maintenance was too expensive. The income and age also had an effect on the different groups of farmer. It is concluded that, to improve mechanization efficiency and stimulate farmers' intention to use machinery, the government should make policies to encourage the merge of fragmented farmlands, provide targeted subsidies for agricultural machinery, and organize machinery training in an efficient way.

Laser speech measurement is a new sound capture technology based on Laser Doppler Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote speech acquisition, which has led to its wide-scale adoption for military and security applications. However, lasers are easily affected by complex detection environments. Thus, speckle noise often appears in the measured speech, seriously affecting its quality and intelligibility. This paper examines all of the characteristics of impulsive noise in laser measured speech and proposes a novel automatic impulsive noise detection and removal method. This method first foregrounds noise using decorrelation based on a linear prediction (LP) model that improves the noise-to-signal ratio (NSR) of the measured signal. This makes it possible to detect the position of noise through a combination of the average short-time energy and kurtosis. The method not only precisely locates small clicks (with a duration of just a few samples), but also finds the location of longer bursts and scratches (with a duration of up to a hundred samples). The located samples can then be replaced by more appropriate samples whose coding is based on the LP model. This strategy avoids unnecessary processing and obviates the need to compromise the quality of the relatively large fraction of samples that are unaffected by speckle noise. Experimental results show that the proposed automatic speckle noise detection and removal method outperforms other related methods across a wide range of degraded audio signals.

Lq-penalized regression arises in multidimensional statistical modelling where
all or part of the regression coefficients are penalized to achieve both accuracy and parsimony
of statistical models. There is often substantial computational difficulty except for the quadratic
penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited
from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient
optimization algorithms. The new method has immediate applications in statistics, notably in penalized
spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time
solvable. Numerical studies show promise of our approach.

The preparation and manipulation of crystalline yet bendable functional complex oxide membranes has been a long-standing issue for a myriad of applications, in particular, for flexible electronics. Here, we investigate the viability to prepare magnetic and crystalline CoFe2O4 (CFO) membranes by means of the Sr3Al2O6 (SAO) sacrificial layer approach using chemical deposition techniques. Meticulous chemical and structural study of the SAO surface and SAO/CFO interface properties have allowed us to identify the formation of an amorphous SAO capping layer and carbonates upon air exposure, which dictate the crystalline quality of the subsequent CFO film growth. Vacuum annealing at 800 °C of SAO films promotes the elimination of the surface carbonates and the reconstruction of the SAO surface crystallinity. Ex-situ atomic layer deposition of CFO films at 250 °C on air-exposed SAO offers the opportunity to avoid high-temperature growth while achieving polycrystalline CFO films that can be successfully transferred to a polymer support preserving the magnetic properties under bending. Float on and transfer provides an alternative route to prepare freestanding and wrinkle-free CFO membrane films. The advances and challenges presented in this work are expected to help increase the capabilities to grow different oxide compositions and heterostructures of freestanding films and their range of functional properties. ; This work was funded by MICIN/AEI/10.13039/501100011033/FEDER through the projects Severo Ochoa FUNFUTURE CEX2019-00917-S and PID2020-114224RB-I00. We also acknowledge the financial support from the 2020 Leonardo Grant for Researchers and Cultural Creators BBVA Foundation, the i-link A20346-CSIC project, the National Key RD Program of China (2018YFA0305800), and the Beijing Outstanding Young Scientist Program (BJJWZYJH01201914430039). The project that gave rise to these results received the support of a fellowship from the "la Caixa" Foundation LCF/BQ/DI19/11730026. D.Z. acknowledges the funding and financial support of the Fund of Chemical Industries (Kekulé fellowship) for his Ph.D. research. The authors are thankful to R. Solanas for his help with the RHEED measurements. This work has been done in the framework of the doctorate in material science of the Autonomous University of Barcelona. ; With funding from the Spanish government through the 'Severo Ochoa Centre of Excellence' accreditation (CEX2019-000917-S). ; Peer reviewed