Molecular interactions of the chaperone CcmS and carboxysome shell protein CcmK1 that mediate ß-carboxysome assembly.

The carboxysome is a natural proteinaceous organelle for carbon fixation in cyanobacteria and chemoautotrophs. It comprises hundreds of protein homologs that self-assemble to form a polyhedral shell structure to sequester cargo enzymes, ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) and carbonic anhydrases. How these protein components assemble to construct a functional carboxysome is a central question in not only understanding carboxysome structure and function but also synthetic engineering of carboxysomes for biotechnological applications. Here, we determined the structure of the chaperone protein CcmS, which has recently been identified to be involved in ß-carboxysome assembly, and its interactions with ß-carboxysome proteins. The crystal structure at 1.99 Å resolution reveals CcmS from Nostoc sp. PCC 7120 forms a homodimer, and each CcmS monomer consists of five α-helices and four ß-sheets. Biochemical assays indicate that CcmS specifically interacts with the C-terminal extension of the carboxysome shell protein CcmK1, but not the shell protein homolog CcmK2 or the carboxysome scaffolding protein CcmM. Moreover, we solved the structure of a stable complex of CcmS and the C-terminus of CcmK1 at 1.67 Å resolution and unveiled how the CcmS dimer interacts with the C-terminus of CcmK1. These findings allowed us to propose a model to illustrate CcmS-mediated ß-carboxysome assembly by interacting with CcmK1 at the outer shell surface. Collectively, our study provides detailed insights into the accessory factors that drive and regulate carboxysome assembly, thereby improving our knowledge of carboxysome structure, function, and bioengineering.

Evidence for archaeal metabolism of D-amino acids in the deep marine sediments.

The deep marine sediments represent a major repository of organic matter whilst hosting a great number of uncultivated microbes. Microbial metabolism plays a key role in the recycling of organic matter in the deep marine sediments. D-amino acids (DAAs) and DAA-containing muropeptides, an important group of organic matter in the deep marine sediments, are primarily derived from bacterial peptidoglycan decomposition. Archaea are abundant in the deep ocean microbiome, yet their role in DAA metabolism remains poorly studied. Here, we report bioinformatic investigation and enzymatic characterization of deep marine sedimentary archaea involved in DAA metabolism. Our analyses suggest that a variety of archaea, particularly the Candidatus Bathyarchaeota and the Candidatus Lokiarchaeaota, can metabolize DAAs. DAAs are converted into L-amino acids via amino acid racemases (Ala racemase, Asp racemase and broad substrate specificity amino acid racemase), and converted into α-keto acid via d-serine ammonia-lyase, whereas DAA-containing di-/tri-muropeptides can be hydrolyzed by peptidases (dipeptidase and D-aminopeptidase). Overall, this study reveals the identity and activity of deep marine sedimentary archaea involved in DAA metabolism, shedding light on the mineralization and biogeochemical cycling of DAAs in the deep marine sediments.

Molecular insights into the catalytic mechanism of a phthalate ester hydrolase.

Phthalate esters (PAEs) are emerging hazardous and toxic chemicals that are extensively used as plasticizers or additives. Diethyl phthalate (DEP) and dimethyl phthalate (DMP), two kinds of PAEs, have been listed as the priority pollutants by many countries. PAE hydrolases are the most effective enzymes in PAE degradation, among which family IV esterases are predominate. However, only a few PAE hydrolases have been characterized, and as far as we know, no crystal structure of any PAE hydrolases of the family IV esterases is available to date. HylD1 is a PAE hydrolase of the family IV esterases, which can degrade DMP and DEP. Here, the recombinant HylD1 was characterized. HylD1 maintained a dimer in solution, and functioned under a relatively wide pH range. The crystal structures of HylD1 and its complex with monoethyl phthalate were solved. Residues involved in substrate binding were identified. The catalytic mechanism of HylD1 mediated by the catalytic triad Ser140-Asp231-His261 was further proposed. The hylD1 gene is widely distributed in different environments, suggesting its important role in PAEs degradation. This study provides a better understanding of PAEs hydrolysis, and lays out favorable bases for the rational design of highly-efficient PAEs degradation enzymes for industrial applications in future.

Meta-omics analysis reveals the marine arsenic cycle driven by bacteria.

Arsenic is a toxic element widely distributed in the Earth's crust and ranked as a class I human carcinogen. Microbial metabolism makes significant contributions to arsenic detoxification, migration and transformation. Nowadays, research on arsenic is primarily in areas affected by arsenic pollution associated with human health activities. However, the biogeochemical traits of arsenic in the global marine ecosystem remain to be explicated. In this study, we revealed that seawater environments were primarily governed by the process of arsenate reduction to arsenite, while arsenite methylation was predominant in marine sediments which may serve as significant sources of arsenic emission into the atmosphere. Significant disparities existed in the distribution patterns of the arsenic cycle between surface and deep seawaters at middle and low latitudes, whereas these situations tend to be similar in the Arctic and Antarctic oceans. Significant variations were also observed in the taxonomic diversity and core microbial community of arsenic cycling across different marine environments. Specifically, γ-proteobacteria played a pivotal role in the arsenic cycle in the whole marine environment. Temperature, dissolved oxygen and phosphate were the crucial factors that related to these differentiations in seawater environments. Overall, our study contributes to a deeper understanding of the marine arsenic cycle.

Benefits of Early Hyperbaric Oxygen Therapy on Attention Networks in Patients with Subarachnoid Hemorrhage.

BACKGROUND: Despite effective treatment for aneurysmal subarachnoid hemorrhage (aSAH), delayed cerebral ischemia (DCI) is a common complication that has a significant impact on the recovery of neurologic function. In this study, we aimed to investigate the efficacy of hyperbaric oxygen therapy (HBOT) in the rehabilitation treatment of aSAH. METHODS: In this study, a total of 98 patients with aSAH and 25 healthy individuals were recruited. The patients included 51 who received HBOT after the effective treatment of aSAH and 47 who received only physical rehabilitation. The modified Rankin Scale (mRS) and Mini-Mental Status Examination (MMSE) were applied for all patients at 7 days after aSAH to determine baseline neurologic deficits and cognitive function. The Attention Network Test (ANT) was performed at the sixth month. RESULTS: The results indicated that the patients receiving HBOT had a lower incidence of DCI (P = 0.026) and better improvement of executive control function (P < 0.001) of ANT compared to those without HBOT. However, there were no differences in orienting, alerting, mean reaction time, and accuracy between the 2 groups. CONCLUSIONS: In summary, early HBOT reduced the DCI rate in aSAH patients and consequently promoted improvement of the executive control function of ANT.

Prototype Learning Guided Hybrid Network for Breast Tumor Segmentation in DCE-MRI.

Automated breast tumor segmentation on the basis of dynamic contrast-enhancement magnetic resonance imaging (DCE-MRI) has shown great promise in clinical practice, particularly for identifying the presence of breast disease. However, accurate segmentation of breast tumor is a challenging task, often necessitating the development of complex networks. To strike an optimal tradeoff between computational costs and segmentation performance, we propose a hybrid network via the combination of convolution neural network (CNN) and transformer layers. Specifically, the hybrid network consists of a encoder-decoder architecture by stacking convolution and deconvolution layers. Effective 3D transformer layers are then implemented after the encoder subnetworks, to capture global dependencies between the bottleneck features. To improve the efficiency of hybrid network, two parallel encoder sub-networks are designed for the decoder and the transformer layers, respectively. To further enhance the discriminative capability of hybrid network, a prototype learning guided prediction module is proposed, where the category-specified prototypical features are calculated through online clustering. All learned prototypical features are finally combined with the features from decoder for tumor mask prediction. The experimental results on private and public DCE-MRI datasets demonstrate that the proposed hybrid network achieves superior performance than the state-of-the-art (SOTA) methods, while maintaining balance between segmentation accuracy and computation cost. Moreover, we demonstrate that automatically generated tumor masks can be effectively applied to identify HER2-positive subtype from HER2-negative subtype with the similar accuracy to the analysis based on manual tumor segmentation. The source code is available at https://github.com/ZhouL-lab/ PLHN.

Potential of Marine Bacterial Metalloprotease A69 in the Preparation of Peanut Peptides with Angiotensin-Converting Enzyme (ACE)-Inhibitory and Antioxidant Properties.

Marine bacterial proteases have rarely been used to produce bioactive peptides, although many have been reported. This study aims to evaluate the potential of the marine bacterial metalloprotease A69 from recombinant Bacillus subtilis in the preparation of peanut peptides (PPs) with antioxidant activity and angiotensin-converting enzyme (ACE)-inhibitory activity. Based on the optimization of the hydrolysis parameters of protease A69, a process for PPs preparation was set up in which the peanut protein was hydrolyzed by A69 at 3000 U g-1 and 60 °C, pH 7.0 for 4 h. The prepared PPs exhibited a high content of peptides with molecular weights lower than 1000 Da (>80%) and 3000 Da (>95%) and contained 17 kinds of amino acids. Moreover, the PPs displayed elevated scavenging of hydroxyl radical and 1,1-diphenyl-2-picryl-hydrazyl radical, with IC50 values of 1.50 mg mL-1 and 1.66 mg mL-1, respectively, indicating the good antioxidant activity of the PPs. The PPs also showed remarkable ACE-inhibitory activity, with an IC50 value of 0.71 mg mL-1. By liquid chromatography mass spectrometry analysis, the sequences of 19 ACE inhibitory peptides and 15 antioxidant peptides were identified from the PPs. These results indicate that the prepared PPs have a good nutritional value, as well as good antioxidant and antihypertensive effects, and that the marine bacterial metalloprotease A69 has promising potential in relation to the preparation of bioactive peptides from peanut protein.

Ratiometric electrochemical biosensor based on hybridization chain reaction signal amplification for sensitive microRNA-155 detection.

In this work, a sensitive ratiometric electrochemical biosensor for microRNA-155 (miRNA-155) detection is reported based on a hybridization chain reaction amplifying the electrochemical signal. The biosensor was fabricated using Au NPs as a modified material to assemble capture DNA labeled with ferrocene (Fc) molecules, and a DNA probe labeled with methylene blue (MB) was employed for the signal probe. In the presence of target miRNA-155, it can be dual hybridized with capture and signal probe, especially with signal probe to continuously produce long concatemers containing lots of MB molecules. The electrochemical signal of Fc was used for the internal signal, and the signal from MB was used as an indicator signal. As the concentration of miRNA-155 was altered, the internal reference signal of Fc remained constant, and only the indicator signal changed in a sensitive way. The change in the ratio (IMB/IFc) between the indicator signal of MB and internal reference signal of Fc can be used to monitor the concentration of miRNA-155. Under optimal conditions, the prepared ratiometric biosensor could detect miRNA-155 within a wide linear range from 100 fM to 100 nM with low detection limit of 33 fM (at S/N = 3). Moreover, the biosensor was evaluated with human serum samples, and satisfactory recoveries were obtained, indicating that the ratiometric biosensor can be applied to clinical sample analysis.

Structure of cryptophyte photosystem II-light-harvesting antennae supercomplex.

Cryptophytes are ancestral photosynthetic organisms evolved from red algae through secondary endosymbiosis. They have developed alloxanthin-chlorophyll a/c2-binding proteins (ACPs) as light-harvesting complexes (LHCs). The distinctive properties of cryptophytes contribute to efficient oxygenic photosynthesis and underscore the evolutionary relationships of red-lineage plastids. Here we present the cryo-electron microscopy structure of the Photosystem II (PSII)-ACPII supercomplex from the cryptophyte Chroomonas placoidea. The structure includes a PSII dimer and twelve ACPII monomers forming four linear trimers. These trimers structurally resemble red algae LHCs and cryptophyte ACPI trimers that associate with Photosystem I (PSI), suggesting their close evolutionary links. We also determine a Chl a-binding subunit, Psb-γ, essential for stabilizing PSII-ACPII association. Furthermore, computational calculation provides insights into the excitation energy transfer pathways. Our study lays a solid structural foundation for understanding the light-energy capture and transfer in cryptophyte PSII-ACPII, evolutionary variations in PSII-LHCII, and the origin of red-lineage LHCIIs.

Discovery of a class of glycosaminoglycan lyases with ultrabroad substrate spectrum and their substrate structure preferences.

Glycosaminoglycan (GAG) lyases are often strictly substrate specific, and it is especially difficult to simultaneously degrade GAGs with different types of glycosidic bonds. Herein, we found a new class of GAG lyases (GAGases) from different bacteria. These GAGases belong to polysaccharide lyase 35 family and share quite low homology with the identified GAG lyases. The most surprising thing is that GAGases can not only degrade three types of GAGs: hyaluronan, chondroitin sulfate, and heparan sulfate but also even one of them can also degrade alginate. Further investigation of structural preferences revealed that GAGases selectively act on GAG domains composed of non/6-O-/N-sulfated hexosamines and d-glucoronic acids as well as on alginate domains composed of d-mannuronic acids. In addition, GAG lyases were once speculated to have evolved from alginate lyases, but no transitional enzymes have been found. The discovery of GAGases not only broadens the category of GAG lyases, provides new enzymatic tools for the structural and functional studies of GAGs with specific structures, but also provides candidates for the evolution of GAG lyases.

Alternative dimethylsulfoniopropionate biosynthesis enzymes in diverse and abundant microorganisms.

Dimethylsulfoniopropionate (DMSP) is an abundant marine organosulfur compound with roles in stress protection, chemotaxis, nutrient and sulfur cycling and climate regulation. Here we report the discovery of a bifunctional DMSP biosynthesis enzyme, DsyGD, in the transamination pathway of the rhizobacterium Gynuella sunshinyii and some filamentous cyanobacteria not previously known to produce DMSP. DsyGD produces DMSP through its N-terminal DsyG methylthiohydroxybutyrate S-methyltransferase and C-terminal DsyD dimethylsulfoniohydroxybutyrate decarboxylase domains. Phylogenetically distinct DsyG-like proteins, termed DSYE, with methylthiohydroxybutyrate S-methyltransferase activity were found in diverse and environmentally abundant algae, comprising a mix of low, high and previously unknown DMSP producers. Algae containing DSYE, particularly bloom-forming Pelagophyceae species, were globally more abundant DMSP producers than those with previously described DMSP synthesis genes. This work greatly increases the number and diversity of predicted DMSP-producing organisms and highlights the importance of Pelagophyceae and other DSYE-containing algae in global DMSP production and sulfur cycling.

Global nitrous oxide emissions from livestock manure during 1890-2020: An IPCC tier 2 inventory.

Nitrous oxide (N2O) emissions from livestock manure contribute significantly to the growth of atmospheric N2O, a powerful greenhouse gas and dominant ozone-depleting substance. Here, we estimate global N2O emissions from livestock manure during 1890-2020 using the tier 2 approach of the 2019 Refinement to the 2006 IPCC Guidelines. Global N2O emissions from livestock manure increased by ~350% from 451 [368-556] Gg N year-1 in 1890 to 2042 [1677-2514] Gg N year-1 in 2020. These emissions contributed ~30% to the global anthropogenic N2O emissions in the decade 2010-2019. Cattle contributed the most (60%) to the increase, followed by poultry (19%), pigs (15%), and sheep and goats (6%). Regionally, South Asia, Africa, and Latin America dominated the growth in global emissions since the 1990s. Nationally, the largest emissions were found in India (329 Gg N year-1), followed by China (267 Gg N year-1), the United States (163 Gg N year-1), Brazil (129 Gg N year-1) and Pakistan (102 Gg N year-1) in the 2010s. We found a substantial impact of livestock productivity, specifically animal body weight and milk yield, on the emission trends. Furthermore, a large spread existed among different methodologies in estimates of global N2O emission from livestock manure, with our results 20%-25% lower than those based on the 2006 IPCC Guidelines. This study highlights the need for robust time-variant model parameterization and continuous improvement of emissions factors to enhance the precision of emission inventories. Additionally, urgent mitigation is required, as all available inventories indicate a rapid increase in global N2O emissions from livestock manure in recent decades.

High-Level Extracellular Production of a Trisaccharide-Producing Alginate Lyase AlyC7 in Escherichia coli and Its Agricultural Application.

Alginate oligosaccharides (AOS), products of alginate degradation by endotype alginate lyases, possess favorable biological activities and have broad applications. Although many have been reported, alginate lyases with homogeneous AOS products and secretory production by an engineered host are scarce. Herein, the alginate lyase AlyC7 from Vibrio sp. C42 was characterized as a trisaccharide-producing lyase exhibiting high activity and broad substrate specificity. With PelB as the signal peptide and 500 mM glycine as the additive, the extracellular production of AlyC7 in Escherichia coli reached 1122.8 U/mL after 27 h cultivation in Luria-Bertani medium. The yield of trisaccharides from sodium alginate degradation by the produced AlyC7 reached 758.6 mg/g, with a purity of 85.1%. The prepared AOS at 20 µg/mL increased the root length of lettuce, tomato, wheat, and maize by 27.5%, 25.7%, 9.7%, and 11.1%, respectively. This study establishes a robust foundation for the industrial and agricultural applications of AlyC7.

Three-dimensional architecture of ESCRT-III flat spirals on the membrane.

The endosomal sorting complexes required for transport (ESCRTs) are responsible for membrane remodeling in many cellular processes, such as multivesicular body biogenesis, viral budding, and cytokinetic abscission. ESCRT-III, the most abundant ESCRT subunit, assembles into flat spirals as the primed state, essential to initiate membrane invagination. However, the three-dimensional architecture of ESCRT-III flat spirals remained vague for decades due to highly curved filaments with a small diameter and a single preferred orientation on the membrane. Here, we unveiled that yeast Snf7, a component of ESCRT-III, forms flat spirals on the lipid monolayers using cryogenic electron microscopy. We developed a geometry-constrained Euler angle-assigned reconstruction strategy and obtained moderate-resolution structures of Snf7 flat spirals with varying curvatures. Our analyses showed that Snf7 subunits recline on the membrane with N-terminal motifs α0 as anchors, adopt an open state with fused α2/3 helices, and bend α2/3 gradually from the outer to inner parts of flat spirals. In all, we provide the orientation and conformations of ESCRT-III flat spirals on the membrane and unveil the underlying assembly mechanism, which will serve as the initial step in understanding how ESCRTs drive membrane abscission.

Phytoplankton-derived polysaccharides and microbial peptidoglycans are key nutrients for deep-sea microbes in the Mariana Trench.

BACKGROUND: The deep sea represents the largest marine ecosystem, driving global-scale biogeochemical cycles. Microorganisms are the most abundant biological entities and play a vital role in the cycling of organic matter in such ecosystems. The primary food source for abyssal biota is the sedimentation of particulate organic polymers. However, our knowledge of the specific biopolymers available to deep-sea microbes remains largely incomplete. One crucial rate-limiting step in organic matter cycling is the depolymerization of particulate organic polymers facilitated by extracellular enzymes (EEs). Therefore, the investigation of active EEs and the microbes responsible for their production is a top priority to better understand the key nutrient sources for deep-sea microbes. RESULTS: In this study, we conducted analyses of extracellular enzymatic activities (EEAs), metagenomics, and metatranscriptomics from seawater samples of 50-9305 m from the Mariana Trench. While a diverse array of microbial groups was identified throughout the water column, only a few exhibited high levels of transcriptional activities. Notably, microbial populations actively transcribing EE genes involved in biopolymer processing in the abyssopelagic (4700 m) and hadopelagic zones (9305 m) were primarily associated with the class Actinobacteria. These microbes actively transcribed genes coding for enzymes such as cutinase, laccase, and xyloglucanase which are capable of degrading phytoplankton polysaccharides as well as GH23 peptidoglycan lyases and M23 peptidases which have the capacity to break down peptidoglycan. Consequently, corresponding enzyme activities including glycosidases, esterase, and peptidases can be detected in the deep ocean. Furthermore, cell-specific EEAs increased at 9305 m compared to 4700 m, indicating extracellular enzymes play a more significant role in nutrient cycling in the deeper regions of the Mariana Trench. CONCLUSIONS: Transcriptomic analyses have shed light on the predominant microbial population actively participating in organic matter cycling in the deep-sea environment of the Mariana Trench. The categories of active EEs suggest that the complex phytoplankton polysaccharides (e.g., cutin, lignin, and hemicellulose) and microbial peptidoglycans serve as the primary nutrient sources available to deep-sea microbes. The high cell-specific EEA observed in the hadal zone underscores the robust polymer-degrading capacities of hadal microbes even in the face of the challenging conditions they encounter in this extreme environment. These findings provide valuable new insights into the sources of nutrition, the key microbes, and the EEs crucial for biopolymer degradation in the deep seawater of the Mariana Trench. Video Abstract.

Coherent potential approximation study of impurity effect on monolayer hexagonal boron phosphide.

Impurity doping is a necessary technology for the application of semiconductor materials in microelectronic devices. The quantification of doping effects is crucial for controlling the transport properties of semiconductors. Here, taking two-dimensional (2D) hexagonal boron phosphide semiconductor as an example, we employ coherent potential approximation method to investigate the electronic properties of 2D semiconductor materials at low doping concentrations, which cannot be exploited with conventional density function theory. The results demonstrate that the positive or negative impurity potential in 2D semiconductors determines whether it is p-type or n-type doping, while the impurity potential strength decides whether it is shallow-level or deep-level doping. Impurity concentration has important impacts on not only the intensity but also the broadening of impurity peak in band gap. Importantly, we provide the operating temperature range of hexagonal boron phosphide as a semiconductor device under different impurity concentrations and impurity potentials. The methodology of this study can be applied to other 2D semiconductors, which is of great significance for quantitative research on the application of 2D semiconductors for electronic devices.

Effect of a stranded hole type on the performance of corn stover composite pipe.

To promote the comprehensive utilization of corn stover and the development of field water-saving irrigation technology, a method of returning corn stover to the field was prosed; in this method, the crop stalks were crushed, mixed with soil in different proportions of adulteration, and then extruded to form hollow round tubes. To compare the influence of the winch blade with or without a diameter change on the composite pipe molding performance, two composite pipe molding devices were theoretically designed, simulated, and analyzed using discrete element simulation software, and a composite pipe molding bench test was performed. The simulation test revealed that the composite pipe molding rate of the winch blade without the reducer molding device was 3.45 kg/s, the output power of the winch shaft was 20.7 kW, the composite pipe molding rate of the winch blade with the reducer molding device was 1.20 kg/s, and the output power of the winch shaft was 18.75 kW. By calculating the weighted average of two indices, the composite pipe forming rate and the winch shaft output power, the comprehensive performance index of the composite pipe forming device without a reducer was greater than that of the device with a reducer. The composite pipe forming bench test revealed two kinds of molding devices with an extrusion molding with an outer diameter of 100 mm and an inner diameter of 30 mm. The composite pipe density test average was greater than 1.30 g/cm3 and met the requirements of composite pipe molding; the winch blade without a reducer molding device had an average composite pipe molding rate of 3.23 kg/s, and the winch blade with an average reducer molding rate of 2.07 kg/s. The forming rate of the composite pipe without a reducer was faster. Therefore, a winch blade without a reducer composite pipe molding device is more conducive to improving the composite pipe molding performance.

Exploring the ecological meanings of temperature sensitivity of ecosystem respiration from different methods.

Temperature sensitivity (Q10) of ecosystem respiration (Re) is a critical parameter for predicting global terrestrial carbon dynamics and its response to climate warming. However, the determination of Q10 has been controversial. In this study, we scrutinized the underpinnings of three mainstream methods to reveal their relationships in estimating Q10 for Re in the Heihe River Basin, northwest China. Specifically, these methods are Q10 estimated from the long-term method (Q10_long), short-term method (Q10_short), and the low-frequency (Q10_lf) and high-frequency (Q10_hf) signals decomposed by the singular spectrum analysis (SSA) method. We found that: 1) Q10_lf and Q10_long are affected by the confounding effects caused by non-temperature factors, and are 1.8 ± 0.3 and 1.7 ± 0.3, respectively. 2) The high-frequency signals of the SSA method and short-term method have consistent roles in removing the confounding effects. Both Q10_short and Q10_hf reflect the actual response of respiration to temperature. 3) Overall, Q10_long has a larger variability (1.7 ± 0.3) across different biomes, whereas Q10_short and Q10_hf show convergence (1.4 ± 0.2 and 1.3 ± 0.1, respectively). These results highlight the fact that Q10 can be overestimated by the long-term method, whereas the short-term method and high-frequency signals decomposed by the SSA method can obtain closer and convergent values after removing the confounding effects driven by non-temperature factors. Therefore, it is recommended to use the Q10 value estimated by the short-term method or high-frequency signals decomposed by the SSA method to predict carbon dynamics and its response to global warming in Earth system models.

Analysis of the Spatial-Temporal Distribution Characteristics of Climate and Its Impact on Winter Wheat Production in Shanxi Province, China, 1964-2018.

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964-2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha-1 yr-1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008-2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region.

A correction method for radial distortion and nonlinear response of infrared cameras.

The key feature of non-contact temperature measurement provided by infrared (IR) cameras underpins their versatility. However, the accuracy of temperature measurements with IR cameras depends on imaging quality due to their non-contact nature, such as the lens, body temperature, and measurement environment. This paper addresses the correction of radial distortion and nonlinear response issues in IR cameras. To address radial distortion, we have designed a passive checkerboard calibration board specifically for infrared cameras. This board is used to calibrate the IR camera and derive the necessary camera parameters. Subsequently, these parameters are applied during the actual measurement process to rectify radial distortion effectively. Building on the radial distortion correction method mentioned above, we propose a multi-point segmented calibration approach that considers different temperature ranges and imaging regions. This method alleviates the issue of reduced temperature measurement accuracy due to variations in camera responses by computing gain and offset coefficient matrices for each temperature range. Experimental results demonstrate the effectiveness of the calibration board in correcting radial distortion in IR cameras, with a mean reprojection error of less than 0.16 pixels. Regarding the nonlinear response problem, the introduced method significantly reduces the relative error in temperature measurement. In the verification phase, spanning from 100 to 500 °C, the average relative error in temperature measurement decreases by 0.49% from 1.61% before and after correction, which highlights a substantial improvement in temperature measurement accuracy. This work gives a useful reference to improve the imaging quality and temperature measurement accuracy using infrared cameras.