Orchard variable-rate spraying method integrating GNSS and wind-excited audio-conducted leaf area density.

Introduction: Conventional air-assisted sprayers used in orchards often suffer from excessive pesticide waste, high residue levels, and uneven droplet distribution on fruit tree canopies. Precision spraying technologies have emerged to address these limitations by enabling dynamic regulation of spray parameters according to canopy characteristics. Among these, leaf area density is a key indicator for describing canopy sparseness.

Challenges and opportunities of ML and explainable AI in large-sample hydrology.

Machine learning (ML) is a powerful tool for hydrological modelling, prediction, dataset creation and the generation of insights into hydrological processes. As such, ML has become integral to the field of large-sample hydrology, where hundreds to thousands of river catchments are included within a single ML model to capture diverse hydrological behaviours and improve model generalizability. This manuscript outlines recent advances in ML for large-sample hydrology.

Estimation of plant leaf water content based on spectroscopy.

Introduction: Leaf water content is a key physiological indicator of plant growth and health status. Constructing leaf water content estimation models based on spectroscopy is an effective method for monitoring plant physiological conditions.

Methods: To improve the accuracy of leaf water content estimation and develop models applicable to different plants, this study collected 1,680 groups of hyperspectral and water content data from peach tree leaves.

Design of target-variable spraying system based on FAVD of fruit tree canopy.

Introduction: Using air-assisted sprayer for chemical pesticide application is the main method for controlling pests and diseases in orchards. Target-variable spray based on canopy characteristics is an effective means to solve the problems of over-spraying, excessive residues, and environmental pollution.

Methods: Foliage area volume density (FAVD), as it represents the number of pesticide targets in the canopy, can be used as a decision condition for variable spraying.

Genomic Functional Analysis and Cellulase Characterization for the Enzyme-Producing Strain Y4X3 Isolated from Saline-Alkaline Soil in Xinjiang, China.

Biotechnological research and application of microbial enzyme production have consistently been focal points for scientific inquiry and industrial advancement. In this study, Y4X3 was isolated from saline-alkaline soil in Xinjiang, China. Extracellular enzyme production analysis revealed that Y4X3 can secrete various enzymes, including cellulase, xylanase, protease, and amylase.

Improved Salt Tolerance in L. Overexpressing a Synthetic Stress-Resistant Module DICW.

Salt stress adversely impacts plant physiology by causing ionic, osmotic, and oxidative stress, ultimately hindering growth and yield. The genus contains unique stress resistance genes, and previous studies have shown that proteins such as IrrE, Csp, and WHy enhance stress tolerance in plants and microbial cells. However, their role in L.

Hydrophilic Sulfonate Covalent Organic Frameworks for Serum Glycopeptide Profiling.

Aberrant protein glycosylation is closely associated with a number of biological processes and diseases. However, characterizing the types of post-translational modifications (PTMs) from the complex biological samples is challenging for comprehensive glycoproteomic analysis. The development of high-performance enrichment materials and strategies during the sample pretreatment process is a prerequisite to glycoproteome research.

Can artificial intelligence be the future solution to the enormous challenges and suffering caused by Schizophrenia?

This study evaluated the potential of artificial intelligence (AI) in the diagnosis, treatment, and prognostic assessment of schizophrenia (SZ) and explored collaborative directions for AI applications in future medical innovations. SZ is a severe mental disorder that causes significant suffering and imposes challenges on patients. With the rapid advancement of machine learning and deep learning technologies, AI has demonstrated notable advantages in the early diagnosis of high-risk populations.

Utilizing Oxygen-Vacancy-Rich Violet Tungsten Oxide Enabling Ultralong Cycling of Nickel-Rich Cathodes at High Voltage.

Nickel-rich cathodes have become widely used recently but tend to become unstable under high voltage, resulting in metal atom rearrangement and oxygen lattice distortions. During high-voltage charging, nickel oxidation weakens oxygen-transition metal bonds, causing oxygen release and increasing risks like thermal runaway. To address these stability issues, we developed an oxygen vacancy-rich WO coating that promotes oxygen vacancy formation on the particle surface, regulating lattice oxygen release within the bulk phase.

Harnessing nanoparticles for reshaping tumor immune microenvironment of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers, characterized by high morbidity and mortality rates. Recently, immunotherapy has emerged as a crucial treatment modality for HCC, following surgery, locoregional therapies, and targeted therapies. This approach harnesses the body's immune system to target and eliminate cancer cells, potentially resulting in durable antitumor responses.

Explainable deep learning identifies patterns and drivers of freshwater harmful algal blooms.

The escalating magnitude, frequency, and duration of harmful algal blooms (HABs) pose significant challenges to freshwater ecosystems worldwide. However, the mechanisms driving HABs remain poorly understood, in part due to the strong regional specificity of algal processes and the uneven data availability. These complexities make it difficult to generalize HAB dynamics and effectively predict their occurrence using traditional models.

Neurotransmitters crosstalk and regulation in the reward circuit of subjects with behavioral addiction.

Behavioral addictive disorders (BADs) have become a significant societal challenge over time. The central feature of BADs is the loss of control over engaging in and continuing behaviors, even when facing negative consequences. The neurobiological underpinnings of BADs primarily involve impairments in the reward circuitry, encompassing the ventral tegmental area, nucleus accumbens in the ventral striatum, and prefrontal cortex.

High Detection Rate of Posterolateral Tibial Plateau Fractures and Poor Functional Outcomes in Type IIIB Impaction Fractures After Anterior Cruciate Ligament Rupture and Reconstruction.

Objective: The incidence of anterior cruciate ligament (ACL) ruptures has been increasing annually. However, clinical surgeons have overlooked the impaction fractures of the posterolateral tibial plateau and lateral femoral condyle in patients with ACL ruptures. The purpose of the present study was to report the detection rate of the posterolateral tibial plateau impaction fractures in patients with ACL ruptures, and to evaluate the functional outcomes of patients following ACL reconstruction (ACLR) without treatment of the tibial fractures at a 2-year postoperative follow-up.

The role of ferroptosis and oxidative stress in cognitive deficits among chronic schizophrenia patients: a multicenter investigation.

Oxidative stress (OS) is crucial in schizophrenia (SCZ) pathology. Ferroptosis, a recently discovered cell death pathway linked to OS, might contribute to the development of SCZ. This study investigated the association between ferroptosis markers and cognitive impairments in chronic SCZ patients.

Does Academic Burnout Alleviate or Exacerbate Internet Dependence in University Students with Depression and Anxiety?

Purpose: This study aims to investigate whether academic burnout alleviates or exacerbates internet dependence among college students with depression and anxiety. Moreover, it intends to construct a moderated mediation model to examine how academic burnout moderates the relationship between depressive and anxious emotions and internet addiction and how social support mediates this relationship to determine the psychological motivations underlying addiction.

Methods: A questionnaire survey was conducted using the simple random sampling method, which yielded 757 valid responses (response rate: a 93.

Pillar[5]arene-based Polymer Network for Efficiently Removing Perfluorooctanoic Acid through Synergistic Binding Interactions.

Perfluorooctanoic acid (PFOA) is currently one of the most important chemicals posing environmental risks, and there is an urgent need to find methods to efficiently remove PFOA from environmental media. Here, two decaamino-pillar[5]arene-based fluorine-rich polymer networks, called FA2P-P and FA6P-P, were constructed using a convenient method. FA6P-P had an excellent ability to take up PFOA, and had a capacity of 1423 (mg PFOA) (g FA6P-P), which is the second highest adsorption capacity reported for any PFOA sorbent.

Modulating Grain Boundary Networks to Achieve Superior Chemomechanical Coupling Properties in Nickel-Rich Cathode Materials.

To forge ahead with the next generation of power batteries boasting superior energy density, nickel-rich layered oxides are regarded as some of the most promising cathode materials. However, challenges such as microcracks, which are attributed to the elevated nickel content of the materials, have posed impediments to their further development and application. Consequently, this article focuses on the understanding of the materials in the deep delithiation state, dissecting their degradation mechanisms through a dual lens of electrochemical and mechanical properties.

Strategies for treating the cold tumors of cholangiocarcinoma: core concepts and future directions.

Cholangiocarcinoma (CCA) is a rare type of digestive tract cancer originating from the epithelial cells of the liver and biliary tract. Current treatment modalities for CCA, such as chemotherapy and radiation therapy, have demonstrated limited efficacy in enhancing survival rates. Despite the revolutionary potential of immunotherapy in cancer management, its application in CCA remains restricted due to the minimal infiltration of immune cells in these tumors, rendering them cold and unresponsive to immune checkpoint inhibitors (ICIs).

Identification of a novel glycoside hydrolase family 8 xylanase from Deinococcus geothermalis and its application at low temperatures.

Xylanase is the most important hydrolase in the xylan hydrolase system, the main function of which is β-1,4-endo-xylanase, which randomly cleaves xylans to xylo-oligosaccharides and xylose. Xylanase has wide ranging of applications, but there remains little research on the cold-adapted enzymes required in some low-temperature industries. Glycoside hydrolase family 8 (GH8) xylanases have been reported to have cold-adapted enzyme activity.

A Multi-Objective Optimization Problem Solving Method Based on Improved Golden Jackal Optimization Algorithm and Its Application.

The traditional golden jackal optimization algorithm (GJO) has slow convergence speed, insufficient accuracy, and weakened optimization ability in the process of finding the optimal solution. At the same time, it is easy to fall into local extremes and other limitations. In this paper, a novel golden jackal optimization algorithm (SCMGJO) combining sine-cosine and Cauchy mutation is proposed.

Understanding Quasi-Static and Dynamic Characteristics of Organic Ferroelectric Field Effect Transistors.

Leveraging poly(vinylidene fluoride-trifluoroethylene) [(PVDF-TrFE)] as the dielectric, we fabricated organic ferroelectric field-effect transistors (OFe-FETs). These devices demonstrate quasi-static transfer characteristics that include a hysteresis window alongside transient phenomena that bear resemblance to synaptic plasticity-encapsulating excitatory postsynaptic current (EPSC) as well as both short-term and long-term potentiation (STP/LTP). We also explore and elucidate other aspects such as the subthreshold swing and the hysteresis window under dynamic state by varying the pace of voltage sweeps.

Is fracture management merely a physical process? Exploring the psychological effects of internal and external fixation.

Background: Internal and external fixation are common surgical procedures for treating fractures. However, the impact of different surgical approaches (including internal and external fixations) on patients' psychological status and Quality of Life (QoL) is rarely examined. Herein, we aimed to investigate the effects of internal and external fixation on anxiety, depression, insomnia, and overall mental and physical health in Distal Radius Fractures (DRF) patients.

Compounding effects in flood drivers challenge estimates of extreme river floods.

Estimating river flood risks under climate change is challenging, largely due to the interacting and combined influences of various flood-generating drivers. However, a more detailed quantitative analysis of such compounding effects and the implications of their interplay remains underexplored on a large scale. Here, we use explainable machine learning to disentangle compounding effects between drivers and quantify their importance for different flood magnitudes across thousands of catchments worldwide.