Citrus Huanglongbing detection and semi-quantification of the carbohydrate concentration based on micro-FTIR spectroscopy.

Citrus Huanglongbing (HLB) is nowadays one of the most fatal citrus diseases worldwide. Once the citrus tree is infected by the HLB disease, the biochemistry of the phloem region in midribs would change. In order to investigate the carbohydrate changes in phloem region of citrus midrib, the semi-quantification models were established to predict the carbohydrate concentration in it based on Fourier transform infrared microscopy (micro-FTIR) spectroscopy coupled with chemometrics. Healthy, asymptomatic-HLB, symptomatic-HLB, and nutrient-deficient citrus midribs were collected in this study. The results showed that the intensity of the characteristic peak varied with the carbohydrate (starch and soluble sugar) concentration in citrus midrib, especially at the fingerprint regions of 1175-900 cm-1, 1500-1175 cm-1, and 1800-1500 cm-1. Furthermore, semi-quantitative prediction models of starch and soluble sugar were established using the full micro-FTIR spectra and selected characteristic wavebands. The least squares support vector machine regression (LS-SVR) model combined with the random frog (RF) algorithm achieved the best prediction result with the determination coefficient of prediction ([Formula: see text]) of 0.85, the root mean square error of prediction (RMSEP) of 0.36%, residual predictive deviation (RPD) of 2.54, and [Formula: see text] of 0.87, RMSEP of 0.37%, RPD of 2.76, for starch and soluble sugar concentration prediction, respectively. In addition, multi-layer perceptron (MLP) classification models were established to identify HLB disease, achieving the overall classification accuracy of 94% and 87%, based on the full-range spectra and the optimal wavenumbers selected by the random frog (RF) algorithm, respectively. The results demonstrated that micro-FTIR spectroscopy can be a valuable tool for the prediction of carbohydrate concentration in citrus midribs and the detection of HLB disease, which would provide useful guidelines to detect citrus HLB disease.

Emissive Platinum(II) Cages with Reverse Fluorescence Resonance Energy Transfer for Multiple Sensing.

It is quite challenging to realize fluorescence resonance energy transfer (FRET) between two chromophores with specific positions and directions. Herein, through the self-assembly of two carefully selected fluorescent ligands via metal-coordination interactions, we prepared two tetragonal prismatic platinum(II) cages with a reverse FRET process between their faces and pillars. Bearing different responses to external stimuli, these two emissive ligands are able to tune the FRET process, thus making the cages sensitive to solvents, pressure, and temperature. First, these cages could distinguish structurally similar alcohols such as n-butanol, t-butanol, and i-butanol. Furthermore, they showed decreased emission with bathochromic shifts under high pressure. Finally, they exhibited a remarkable ratiometric response to temperature over a wide range (223-353 K) with high sensitivity. For example, by plotting the ratio of the maximum emission (I600/I480) of metallacage 4b against the temperature, the slope reaches 0.072, which is among the highest values for ratiometric fluorescent thermometers reported so far. This work not only offers a strategy to manipulate the FRET efficiency in emissive supramolecular coordination complexes but also paves the way for the future design and preparation of smart emissive materials with external stimuli responsiveness.

Pressure-Induced Emission (PIE) and Phase Transition of a Two-dimensional Halide Double Perovskite (BA)4 AgBiBr8 (BA=CH3 (CH2 )3 NH3 + ).

Two-dimensional (2D) halide perovskites have attracted significant attention due to their compositional flexibility and electronic diversity. Understanding the structure-property relationships in 2D double perovskites is essential for their development for optoelectronic applications. In this work, we observed the emergence of pressure-induced emission (PIE) at 2.5 GPa with a broad emission band and large Stokes shift from initially nonfluorescent (BA)4 AgBiBr8 (BA=CH3 (CH2 )3 NH3 + ). The emission intensity increased significantly upon further compression up to 8.2 GPa. Moreover, the band gap narrowed from the starting 2.61 eV to 2.19 eV at 25.0 GPa accompanied by a color change from light yellow to dark yellow. Analysis of combined in situ high-pressure photoluminescence, absorption, and angle-dispersive X-ray diffraction data indicates that the observed PIE can be attributed to the emission from self-trapped excitons. This coincides with [AgBr6 ]5- and [BiBr6 ]3- inter-octahedral tilting which cause a structural phase transition. High-pressure study on (BA)4 AgBiBr8 sheds light on the relationship between the structure and optical properties that may improve the material's potential applications in the fields of pressure sensing, information storage and trademark security.

Heuristic Heterogeneous Graph Reasoning Networks for Fact Verification.

Existing studies on table-based fact verification generally capture linguistic evidence from claim-table subgraphs or logical evidence from program-table subgraphs independently. However, there is insufficient association interaction between the two types of evidence, which makes it difficult to obtain valuable consistency features between them. In this work, we propose heuristic heterogeneous graph reasoning networks (H2GRN) to capture the shared consistent evidence by strengthening associations between linguistic and logical evidence from two perspectives of graph construction and reasoning mechanism. Specifically, 1) to enhance the close connectivity of the two subgraphs, rather than simply connecting two subgraphs by the nodes with the same content (the constructed graph in this way has severe sparsity), we construct a heuristic heterogeneous graph, which relies on claim semantics as heuristic knowledge to guide the connections of the program-table subgraph, and in turn expands the connectivity of the claim-table subgraph through logical information of programs as heuristic knowledge; and 2) to establish adequate association interaction between linguistic evidence and logical evidence, we design multiview reasoning networks. In detail, we propose local-view multihop knowledge reasoning (MKR) networks to enable the current node to establish association not only with one-hop neighbors, but also with multihop neighbors, to capture context-richer evidence information. We execute MKR on heuristic claim-table and program-table subgraphs to learn context-richer linguistic evidence and logical evidence, respectively. Meanwhile, we develop global-view graph dual-attention networks (DAN) that execute on the entire heuristic heterogeneous graph, reinforcing global-level significant consistency evidence. Finally, the consistency fusion layer is devised to weaken the disagreement between the three types of evidence to assist in capturing consistent shared evidence for verifying claims. Experiments on TABFACT and FEVEROUS demonstrate the effectiveness of H2GRN.

Analysis of the Impact of Medical Features and Risk Prediction of Acute Kidney Injury for Critical Patients Using Temporal Electronic Health Record Data With Attention-Based Neural Network.

Acute kidney injury (AKI) is one of the most severe consequences of kidney injury, and it will also cause or aggravate the complications by the fast decline of kidney excretory function. Accurate AKI prediction, including the AKI case, AKI stage, and AKI onset time interval, can provide adequate support for effective interventions. Besides, discovering how the medical features affect the AKI result may also provide supporting information for disease treatment. An attention-based temporal neural network approach was employed in this study for AKI prediction and for the analysis of the impact of medical features from temporal electronic health record (EHR) data of patients before AKI diagnosis. We used the publicly available dataset provided by the Medical Information Mart for Intensive Care (MIMIC) for model training, validation, and testing, and then the model was applied in clinical practice. The improvement of AKI case prediction is around 5% AUC (area under the receiver operating characteristic curve), and the AUC value of AKI stage prediction on AKI stage 3 is over 82%. We also analyzed the data by two steps: the associations between the medical features and the AKI case (positive or inverse) and the extent of the impact of medical features on AKI prediction result. It shows that features, such as lactate, glucose, creatinine, blood urea nitrogen (BUN), prothrombin time (PT), and partial thromboplastin time (PTT), are positively associated with the AKI case, while there are inverse associations between the AKI case and features such as platelet, hemoglobin, hematocrit, urine, and international normalized ratio (INR). The laboratory test features such as urine, glucose, creatinine, sodium, and blood urea nitrogen and the medication features such as nonsteroidal anti-inflammatory drugs, agents acting on the renin-angiotensin system, and lipid-lowering medication were detected to have higher weights than other features in the proposed model, which may imply that these features have a great impact on the AKI case.

Pressure-Induced Broadband Emission of 2D Organic-Inorganic Hybrid Perovskite (C6H5C2H4NH3)2PbBr4.

2D Ruddlesden-Popper halide perovskites, which incorporate hydrophobic organic interlayers to considerably improve environmental stability and optical properties diversity, have attracted substantial research attention for optoelectronic applications. The burgeoning broad emission arising from exciton self-trapping of 2D perovskites shows a strong dependence on a deformable structure. Here, the pressure-induced broadband emission of layered (001) Pb-Br perovskite with a large Stokes shift in the visible region is observed by finely improving lattice distortion to increase exciton-phonon coupling under hydrostatic pressure. Band gap narrows ≈0.5 eV under modest pressure, mainly due to the large compressibility of the orientational organic layer, confirming that the bulky organic cations notably influence the structure and, in turn, the various properties of materials. Sequential amorphization of the organic and inorganic layer is confirmed by high pressure Raman and X-ray diffraction measurements, suggesting the particularity of layered crystal structures. The mechanism constructed here offers a new route for tuning the optical properties of 2D perovskites.

High-Pressure Band-Gap Engineering and Metallization in the Perovskite Derivative Cs3 Sb2 I9.

Among photovoltaic materials, the antimony-based, perovskite-like structure Cs3 Sb2 I9 stands out owing to its low toxicity and air stability. Here, changes in the optoelectronic properties and crystal structure of the lead-free perovskite derivative Cs3 Sb2 I9 are reported, caused by pressure-induced lattice compression. At 20.0 GPa, Cs3 Sb2 I9 with a wide band gap (2.34 eV) successfully broke through the Shockley-Queisser limit (1.34 eV), accompanied by clear piezochromism from orange-yellow to opaque black. Additionally, Cs3 Sb2 I9 experienced completely reversible amorphization at 20.0 GPa. These optical changes could be attributed to atomic-orbital overlap enhancement caused by contraction of the Sb-I bond length and diminution of the Sb-I bond angle. In addition, Cs3 Sb2 I9 underwent a transition from semiconductor to conductor upon compression and obtained metallic properties at 44.3 GPa, indicating new electronic properties. The obtained results may further broaden the research prospects of halide perovskite materials in the field of photovoltaics.