Enhancing nitrogen use efficiency in agriculture by integrating agronomic practices and genetic advances.

Nitrogen is a critical nutrient for plant growth and productivity, but inefficiencies in its use in agriculture present both economic and environmental challenges. Enhancing nitrogen use efficiency (NUE) is essential for promoting sustainable crop production and mitigating the negative impacts of nitrogen loss, such as water pollution and greenhouse gas emissions. This review discusses various strategies aimed at improving NUE, with a focus on agronomic practices, genetic advancements, and integrated management approaches.

M2OCNN: Many-to-One Collaboration Neural Networks for simultaneously multi-modal medical image synthesis and fusion.

Background And Objective: Acquiring comprehensive information from multi-modal medical images remains a challenge in clinical diagnostics and treatment, due to complex inter-modal dependencies and missing modalities. While cross-modal medical image synthesis (CMIS) and multi-modal medical image fusion (MMIF) address certain issues, existing methods typically treat these as separate tasks, lacking a unified framework that can generate both synthesized and fused images in the presence of missing modalities.

Methods: In this paper, we propose the Many-to-One Collaboration Neural Network (M2OCNN), a unified model designed to simultaneously address CMIS and MMIF.

Dual-modality visual feature flow for medical report generation.

Medical report generation, a cross-modal task of generating medical text information, aiming to provide professional descriptions of medical images in clinical language. Despite some methods have made progress, there are still some limitations, including insufficient focus on lesion areas, omission of internal edge features, and difficulty in aligning cross-modal data. To address these issues, we propose Dual-Modality Visual Feature Flow (DMVF) for medical report generation.

DAEiS-Net: Deep Aggregation Network with Edge Information Supplement for Tunnel Water Stain Segmentation.

Tunnel disease detection and maintenance are critical tasks in urban engineering, and are essential for the safety and stability of urban transportation systems. Water stain detection presents unique challenges due to its variable morphology and scale, which leads to insufficient multiscale contextual information extraction and boundary information loss in complex environments. To address these challenges, this paper proposes a method called Deep Aggregation Network with Edge Information Supplement (DAEiS-Net) for detecting tunnel water stains.

Consumer preference and willingness-to-pay for formal recycling of electric vehicle batteries: A discrete choice experiment in China.

The burgeoning electric vehicle (EV) market poses a substantial challenge to battery recycling systems, yet understanding EV battery recycling behavior from the demand side remains limited. Previous studies have analyzed perceptual or attitudinal factors, neglecting the observable attributes of EV battery recycling. To this end, we proposed a discrete choice model to investigate the differences between formal and informal recycling behaviors, identifying consumer preferences and willingness to pay.

A strategy to balance location privacy and positioning accuracy.

In privacy protection methods based on location services, constructing anonymous areas using location information shared by collaborative users is the main method. However, this collaborative process not only increases the risk of mobile users' location privacy being leaked, but also reduces positioning accuracy. In response to this problem, we propose a balancing strategy, which transforms the problem of protecting mobile users' location privacy and improving positioning accuracy into a balance issue between location privacy and positioning accuracy.

Formation of Ohmic contacts between ferromagnetic CrGeTeand two-dimensional metals.

As a ferromagnetic semiconductor, two-dimensional (2D) CrGeTeholds significant implications for electronic and spintronic devices. To achieve 2D electronics, it is essential to integrate CrGeTewith 2D electrodes to form Schottky-barrier-free Ohmic contacts with enhanced carrier injection efficiency. Herein, by using first-principles calculations based on density-functional theory, we systematically investigate the structural, energetic, electronic and magnetic properties of 2D heterojunctions by combining CrGeTewith a series of 2D metals, including graphene, ZrCl, NbS, TaS, TaSe, ZnC, HgC, and ZrN.

An Empirical Analysis of the Impact of Digital Economy on Manufacturing Green and Low-Carbon Transformation under the Dual-Carbon Background in China.

The deep integration of digital economy and green development has become an inevitable requirement and an important aid in achieving the goal of carbon peaking and carbon neutrality and promoting high-quality economic development. At the same time, the manufacturing industry is the main sector of energy consumption and carbon emissions in China and the main force for achieving the carbon peaking and carbon neutrality goals. This paper constructs a mathematical model to measure the scale of the digital economy development and the efficiency of the green, low-carbon transformation of the manufacturing industry.

A 3D reconstruction based on an unsupervised domain adaptive for binocular endoscopy.

In minimally invasive surgery, endoscopic image quality plays a crucial role in surgery. Aiming at the lack of a real parallax in binocular endoscopic images, this article proposes an unsupervised adaptive neural network. The network combines adaptive smoke removal, depth estimation of binocular endoscopic images, and the 3D display of high-quality endoscopic images.

COVID-19 CT image segmentation method based on swin transformer.

Owing to its significant contagion and mutation, the new crown pneumonia epidemic has caused more than 520 million infections worldwide and has brought irreversible effects on the society. Computed tomography (CT) images can clearly demonstrate lung lesions of patients. This study used deep learning techniques to assist doctors in the screening and quantitative analysis of this disease.

SparNet: A Convolutional Neural Network for EEG Space-Frequency Feature Learning and Depression Discrimination.

Depression affects many people around the world today and is considered a global problem. Electroencephalogram (EEG) measurement is an appropriate way to understand the underlying mechanisms of major depressive disorder (MDD) to distinguish depression from normal control. With the development of deep learning methods, many researchers have adopted deep learning models to improve the classification accuracy of depression recognition.

Generating diagnostic report for medical image by high-middle-level visual information incorporation on double deep learning models.

Background And Objectives: Writing diagnostic reports for medical images is a heavy and tedious work. The automatic generation of medical image diagnostic reports can assist doctors to reduce their workload and improve diagnosis efficiency. It is of great significance to introduce image caption algorithm into medical image processing.

Tunable electronic structures and half-metallicity in two-dimensional InSe functionalized with magnetic superatom.

Based on first-principles calculations, we investigate the geometric, energetic and electronic properties of two-dimensional (2D) InSe functionalized with magnetic superatoms (MnCl). As a nonmagnetic semiconductor, 2D InSe exhibits non-covalent interaction with MnCland provides an ideal substrate for the assembly of magnetic superatoms. We show that with a low coverage of MnCl, the functionalized system behaves as a magnetic semiconductor with spin-polarized superatomic states residing inside the energy gap of InSe.

Design of Double-Shelled CuS Nanocages to Optimize Electrocatalytic Dynamic for Sensitive Detection of Ascorbic Acid.

Although transition metal sulfides have presented prospect in electrochemical sensing, their electrocatalytic performance still cannot meet the demands for practical applications due to the difficulties in mass transport and electron transfer. In this work, double-shelled CuS nanocages (2-CuS NCs) were prepared for enzyme-free ascorbic (AA) sensor through a CuO- templated method. The unique double-shelled hollow structure displayed large specific surface areas, ordered diffusion channels, increased volume occupying rate, and accelerated electron transfer rate, resulting in enhanced electrochemical dynamic.

Design of Ni(OH) nanocages@MnO nanosheets core-shell architecture to jointly facilitate electrocatalytic dynamic for highly sensitive detection of dopamine.

In this work, Ni(OH) nanocages@MnO nanosheets core-shell architecture (Ni(OH) NCs@MnO NSs CSA) was successfully prepared through coordinated etching and precipitation (CEP) route followed by hydrothermal reaction, and then tested as sensitive electrode material for detection of dopamine (DA). The three dimensional (3D) hollow Ni(OH) core effectively prevented the aggregation of MnO NSs, leading to high utilization rate of MnO NSs. Meanwhile, the two dimensional (2D) MnO shell endowed Ni(OH) NCs with larger specific area and abundant diffusion channels, facilitating mass transport.

Amphiphilic N-(2,3-dihydroxypropyl)-chitosan-cholic acid micelles for paclitaxel delivery.

Self-assembled amphiphilic N-(2,3-dihydroxypropyl)-chitosan-cholic acid (DHP-CS-CHO) micelle was prepared as a carrier for paclitaxel. DHP-CS-CHO was synthesized by grafted small molecules cholic acid and glycidol onto primary amine group of chitosan, respectively. The DHP-CS-CHO formed uniform micelles (size=212.

[Electronic spectra and energy levels analysis of Ho3+ in Cs2NaYF6].

The electronic spectra and energy levels of Ho3+ in Cs2NaYF6 were studied on basis of rare earth (RE) spectrum, quantum mechanics and crystal field theory. Detailed analysis on electronic absorption spectra at temperatures down to 10 K in the range of 4600-24,000 cm(-1) was carried out. The transitions, with zero phonon lines (ZPL) and abundant vibronic sidebands, from ground states to different excited states such as 5I(J); (J = 7, 6, 5, 4), 5F(S) (S = 5, 4, 3), 5G(P) (P = 6, 5) and (3)K8 were clearly observed.