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Irrigation and fertilization are vital to increasing crop yield, but their application often exceeds crop requirements. Excessive fertilization under inefficient irrigation depletes the already scarce water resources while contributing to water pollution. To overcome these problems, the introduction of fertigation in combination with modern irrigation technologies has been promoted in the North China Plain (NCP), but farmers have been reluctant to adopt such technologies. To better understand the current situation and farmers' perceptions, we performed a case study in the People's Victory Canal Irrigation District (PVCID) of NCP. A field survey was carried out using a participatory approach, and field monitoring was conducted on a representative farm. We found that farmers are generally satisfied with their irrigation and fertilization practices, although they result in low application efficiency and distribution uniformity. In principle, the lack of knowledge about how to implement fertigation technology, the small-scale farming conditions, and the high cost of developing advanced fertigation systems are the main obstacles for fertigation adoption. We further conclude that (i) to improve the on-farm performance in terms of efficiency and uniformity of irrigation and fertilization, evidence-based guidelines are required to help farmers to implement; (ii) for effective adoption of new technologies, consideration of farmers' situation and perspectives is critical; and (iii) surface fertigation might be a good start for fertigation promotion.

We carry out a global structure search for the Nb–Pb system based on the evolutionary algorithm and density functional theory. Based on the dynamical and mechanical stability analyses, we unveiled five new Nb–Pb binary phases.

In order to make early warning on forest fire, this paper proposes a new method that combines classification model and objection model for forest fire recognition, and builds a fire warning system based on this method. Firstly, the algorithm optimized on VGG network, and introduced transfer learning method to train smoke recognition model and flame recognition model. Secondly, consider the difficulty of small flame recognition in the early stage of fire, introduced YOLO network for fire detection, and optimization on it to improve the ability of feature extraction and multi-scale feature fusion. Finally, made use of decision tree method for joint decision of fire warning by results of classification and detection. Experiments show that the mAP of this method is 96.5%, and the detection speed is 30.9FPS, which meets the real-time requirements of fire detection.

For the problem of low accuracy and efficiency in criminal investigation image retrieval tasks, proposed a retrieval method based on deep hash coding. Adopting ResNet as backbone network for feature extraction, and adding a pyramid pooling layer to enhance the quality of image features; In order to improve the retrieval efficiency, a deep hash layer is introduced to adaptively extract binary hash code for the image. By means of image-pair training method, and Combination of classification loss and contrast loss for joint learning, optimize training effect. Experiments show that the accuracy and efficiency of image retrieval by this method are significantly improved when compared with the existing benchmark algorithms.

BACKGROUND: The aim of this study was to observe the effect of Sacubitril/Valsartan on cardiac function and remodeling in patients with heart failure with reduced ejection fraction (HFrEF). METHODS: A total of 120 patients with HFrEF were selected and given standard heart failure treatment according to the 2017 ACC/AHA/HFSA guidelines. Regardless of whether patients had taken Angiotensin-Converting Enzyme Inhibitors/Angiotensin Receptor Blockers (ACEI/ARB) medications previously, after admission they were treated with the minimum effective dose of Sacubitril/Valsartan according to their blood pressure reading. Baseline clinical data were recorded and patients were followed up at 1, 3, 6, 9, and 12 months post discharge, during which time the dose of Sacubitril/Valsartan was gradually increased to the maximum tolerated dose (dose range 25-200 mg/twice daily). During follow-up, N-terminal pro-brain natriuretic peptide (NT-proBNP), left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter (LVEDD), left ventricular end systolic diameter (LVESD), and left atrium diameter (LAD) were monitored; a 6-minute walking test and Kansas City Cardiomyopathy Questionnaire (KCCQ) scores were recorded; and adverse reactions were collected. RESULTS: Over the course of the 12-month follow-up, the plasma concentrations of NT-proBNP were significantly reduced compared with the baseline, and the longer the follow-up time, the lower the NT-proBNP levels were (P

L10-FeNi hard magnetic alloy with coercivity reaching 861 Oe was synthesized through annealing Fe42Ni41.3Si8B4P4Cu0.7 amorphous alloy, and the L10-FeNi formation mechanism has been studied. It is found the L10-FeNi in annealed samples at 400 °C mainly originated from the residual amorphous phase during the second stage of crystallization which could take place over 60 °C lower than the measured onset temperature of the second stage with a 5 °C/min heating rate. Annealing at 400 °C after fully crystallization still caused a slight increase of coercivity, which was probably contributed by the limited transformation from other high temperature crystalline phases towards L10 phase, or the removal of B from L10 lattice and improvement of the ordering quality of L10 phase due to the reduced temperature from 520 °C to 400 °C. The first stage of crystallization has hardly direct contribution to L10-FeNi formation. Ab initio simulations show that the addition of Si or Co in L10-FeNi has the effect of enhancing the thermal stability of L10 phase without seriously deteriorating its magnetic hardness. The non-monotonic feature of direction dependent coercivity in ribbon segments resulted from the combination of domain wall pinning and demagnetization effects. The approaches of synthesizing L10-FeNi magnets by adding Si or Co and decreasing the onset crystallization temperature have been discussed in detail.

Aiming at the disadvantages of traditional manual attendance, this paper proposes a face recognition based attendance scheme. Through mobile platform and face recognition technology to optimize the manual attendance process. This design divides into the face recognition system of check on work attendance information input, attendance sign-in and attendance record three function module, and introduces a principle of face detection and classification, analyses the process of the construction of the face recognition classifier, the last on the Android platform design and implement a face recognition system of check on work attendance, by comparing the experiment results of face recognition accuracy, verify the feasibility of this scheme.

This paper proposed a criminal investigation image retrieval algorithm based on deep learning. First, this paper improves Faster R-CNN object detection network making it can extract multi-scale features of images, so that it can better annotation semantic information for the image. To obtain a preliminary image list through image retrieval of the semantic information. Then use ResNet50 to extract image features, perform content-based retrieval in the image list returned by the first step of semantics to obtain the final criminal investigation image retrieval result, both the semantic and the content are combined for image retrieval. The experimental results show that the criminal investigation image retrieval algorithm proposed in this paper is superior to the simple content criminal investigation image retrieval algorithm in Precision and Retrieval rate.

In response to the national energy conservation and emission reduction policy and reducing tunnel operating costs, this paper introduced automatic lighting control equipment research and development on the basis of tunnel traffic safety and comfort. This research and development is aiming for LED lights which having a broad application prospects, combined with the lighting intensity outside the tunnel, traffic and other factors. In this paper, the relationship model of power and illumination of LED light is analyzed, and the High-precision digital current stepless dimming technology is proposed. The test results demonstrate that this device can reduce the manpower and electricity consumption of tunnel illumination to a large extent while ensuring the tunnel traffic safety.

BiFeO3-LaY2Fe5O12 (BFO-LYIG) composites and the corresponding flexible films were prepared via solid-sate reaction and spin coating respectively. The composites were used for structures and magneti...

Objective To perform a prospective non-randomized comparison of the effectiveness and safety of combined neurokinin-1 antagonist aprepitant treatment with the standard multiple-day cisplatin regimen for the prevention of cisplatin-induced nausea and vomiting (CINV). Methods Patients being administered 3-day cisplatin-based chemotherapy (25 mg/m2/d) who had never received aprepitant were given either the standard regimen (tropisetron and dexamethasone) or the aprepitant regimen (aprepitant plus tropisetron and dexamethasone). The primary endpoint was the complete response (CR) in the overall phase (OP, 0–120 h) between the combined aprepitant triple regimen group and the standard group. Secondary endpoints were the CR in the acute phase (AP, 0–24 h) and delay phase (DP, 25–120 h) between the two groups. The first time of vomiting was also compared by Kaplan–Meier curves. The impact of CINV on the quality of life was assessed by the Functional Living Index-Emesis (FLIE). Aprepitant-related adverse effects (AEs) were also recorded. Results A CR was achieved by 80.0% in the aprepitant group compared with 56.0% in the standard group during the OP (P =0.018)as well as during the DP. However, during the AP, the aprepitant and standard therapy groups achieved identical CR rates (98.0%, P =1.000). A longer time to first emesis was documented for the aprepitant group than for the standard group. No effect of CINV on quality of life as assessed by FLIE was reported by 44.7% of aprepitant therapy patients and 24.0% of standard therapy patients (P=0.035). The main aprepitant-related AEs were fatigue and constipation, but there was no significant difference between groups. Conclusion Combined aprepitant therapy is recommended for the prevention of multiple-day CINV because of its improved CINV control rate and safety.

It is extremely rare for the coexistence of two spin glass transitions in single phase materials. In the present paper, the structure and magnetic properties of Tb2Ni0.8Mn0.2Si3 were investigated. For comparison, the corresponding experimental results of Tb2NiSi3 compound were also provided. In the temperature dependence of dc susceptibility measurements, there are two anomaly transitions for both Tb2Ni0.8Mn0.2Si3 and Tb2NiSi3. Further studies on the frequency dependence of ac susceptibility show a new spin-glass transition at 14 K in Tb2Ni0.8Mn0.2Si3, except for the spin-glass transition at 8 K inheriting from Tb2NiSi3. This new spin-glass transition in Tb2Ni0.8Mn0.2Si3 is absent in Tb2NiSi3. It takes place below the long-range magnetic ordered phase transition and shows cluster spin glass behaviors, and it is attributed to the introduction of Mn ions into the intermetallic compound.

Large crystal growth of Cr-doped h-YMnO3 has been investigated by using a high pressure optical floating-zone method. The size of the grown crystals is typically 60–70 mm in length and 4–5 mm in diameter. The structure of the grown crystals is analyzed by powder X-ray diffraction and scanning electron microscopy. The defects in the as-grown crystals, including low-angle grain boundary and inclusions are studied. An off-stoichiometric phenomenon is found with a slight Cr deficiency in different parts. The relationship between defects and growth conditions during crystal growth is also discussed. The magnetic properties show spin-glass phase features with weak ferromagnetic behavior below 30 K.

Polycrystalline YMn1−x Co x O3 with x ranging from 0 to 0.1 was synthesized by solid-state reaction method. The magnetic and magnetocaloric properties were investigated by superconducting quantum interference design magnetometer. With the increasing of Co-doping, the YMn1−x Co x O3 shows complex magnetic properties, including the existence of ferromagnetic component and spin glass state. The Curie temperature and maximum magnetic entropy change are also strongly dependent on Co content. Those results were ascribed to the complex mixed valence characteristics of Mn ions originated from the Co-doping.

The structures and magnetic properties of YMn1−xCrxO3 (x=0-0.1) were investigated in this study. Powder x-ray diffraction shows that YMn1−xCrxO3 (x=0-0.1) maintains a hexagonal structure with P63cm space group, as observed for YMnO3. The temperature dependence of magnetization indicates that the magnetization of YMn1−xCrxO3 increases as Cr doping concentration increases at low temperatures, and the spin-glass state appeared in the Cr doped samples. The antiferromagnetic transition temperature increases in the Cr-doped YMnO3, which is originated from the magnetic coupling between the Mn3+ ions in the inter-plane. The spin glass phase providing a pinning force from some frozen spins to the rotatable spins gives the key to explain the exchange bias effects.

The recognition and separation of fully overlapping handwritten digits is an effective means to test the recognition ability of the network. It is also the basis of separating overlapping complex handwritten characters. This paper constructs a deep capsule network, FOD_DCNet, for the recognition and separation of fully overlapping handwritten digits. Firstly, we used small sized convolution kernels to extract features, which is conducive to extracting fine-grained features while reducing training parameter; secondly, we expanded the capsules dimension to express the extracted features to avoid the loss and omission of features; thirdly, we proposed "series dual dynamic routing collocation" to optimize the routing classification function. Compared with CapsNet, our FOD_DCNet reduces the number of iterations of each route, and increases the classification efficiency. The classification accuracy of FOD_DCNet can reach 93.53%, which is 5.43% higher than CapsNet and its parameter amount is only 55.61% of CapsNet.

The Bi2Te3/graphite/polythiophene composites were prepared by solution mixing, mechanical ball milling, cold pressing and spark plasma sintering (SPS) in order to utilize and integrate the high Seebeck coefficient of Bi2Te3, high electrical conductivity of graphite (G) and low thermal conductivity of polythiophene (PTh). The structures and properties of the composites were characterized by scanning electron microscope, thermo gravimetric analyzer, x-ray diffraction and ULVAC ZEM-2 Seebeck coefficient measurement. The results showed that the related components were uniformly dispersed in the composites, and the electrical conductivity of the composites increased significantly with increasing G content. A small addition of Bi2Te3 to the matrix contributed to an increase in Seebeck coefficient and the thermal conductivity of the composites stayed at a low level owing to the low thermal conductivity of PTh. These composites prepared by SPS show an increase in Seebeck coefficient but a decrease in electrical conductivity as compared to corresponding composites prepared by cold pressing.

Currently, the three-dimensional distribution of interlayer is realized by stochastic modeling. Traditionally, the three-dimensional geological modeling controlled by sedimentary facies models is built on the basis of logging interpretation parameters and geophysical information. Because of shallow gas-cap, the quality of three-dimensional seismic data vertical resolution in research area cannot meet the interlayer research that is below ten meters. Moreover, sedimentary facies cannot commendably reveal interlayer distribution and the well density is very sparse in research area. So, it is difficult for conventional technology to finely describe interlayers. In this document, it uses L 1 -L 2 combined norm constrained inversion to enhance the recognition capability of interlayer in seismic profile and improve the signal to noise ratio, the wave group characteristics and the vertical resolution of three-dimensional data and classifies petrophysical facies of interlayer based on core, sedimentary facies and logging interpretation. The interlayer model which is based on seismic inversion model and petrophysical facies can precisely simulate the distribution of reservoir and interlayer. The results show that the simulation results of this new methodology are consistent with the dynamic production perfectly which provide a better basis for producing and mining remaining oil and a new interlayer modeling method for sparse well density.

For perpendicular exchange-biased IrMn/Pt/ Co/Pt multilayers with bidomain state, double hysteresis loops (DHLs) are achieved. It is found that exchange bias field and coercivity in full loop and two subloops’ training show different dependencies on the cycle number. Further studies show that the negative-biased (positive-biased) subloop measurement will influence training effect of the positive-biased (negative-biased) subloop, acting as a recovery process. This recovery procedure is different from the conventional ways, i.e., by applying a magnetic field perpendicular to the initial pinning direction or by leaving the sample alone for several days without any applied magnetic fields. This recovery effect can be explained by the re-rotation of antiferromagnet (AFM) spins after corresponding subloop magnetic moment reversal during the full loop measurement, which cannot happen during the subloop measurement.