The present study included 658 hospitalized patients with confirmed COVID‐19. Forty‐two (6.4%) out of 658 patients presented with ketosis on admission with no obvious fever or diarrhoea. They had a ...median (interquartile range IQR) age of 47.0 (38.0–70.3) years, and 16 (38.1%) were men. Patients with ketosis were younger (median age 47.0 vs. 58.0 years; P = 0.003) and had a greater prevalence of fatigue (31.0% vs. 10.6%; P < 0.001), diabetes (35.7% vs. 18.5%; P = 0.007) and digestive disorders (31.0% vs. 12.0%; P < 0.001). They had a longer median (IQR) length of hospital stay (19.0 12.8–33.3 vs. 16.0 10.0–24.0 days; P < 0.001) and a higher mortality rate (21.4% vs. 8.9%; P = 0.017). Three (20.0%) out of the 15 patients with diabetic ketosis developed acidosis, five patients (26.7%) with diabetic ketosis died, and one of these (25.0%) presented with acidosis. Two (7.4%) and four (14.3%) of the 27 non‐diabetic ketotic patients developed severe acidosis and died, respectively, and one (25.0%) of these presented with acidosis. This suggests that COVID‐19 infection caused ketosis or ketoacidosis, and induced diabetic ketoacidosis for those with diabetes. Ketosis increased the length of hospital stay and mortality. Meanwhile, diabetes increased the length of hospital stay for patients with ketosis but had no effect on their mortality.
•The relationship between the microstructure and mechanical properties of the base material and the lattice material were studied.•Bending-dominated structure BCC is more sensitive to the heat ...treatment conditions than stretching-dominated structure FCC.•The better heat treatment temperature for BCC and FCC are 920°C and 750°C respectively.•A numerical simulation model was established to show the relationship between the mechanical properties of the base material and the lattice material.
Titanium alloy lattice materials fabricated by selective laser melting (SLM) have shown great potential in many engineering applications related to energy absorption. The mechanical behavior of the titanium alloy is dependent on its microstructure that can be improved by heat treatment. However, little attention has been paid to the effects of heat treatment on the lattice materials, and the relationship between the mechanical properties of the base material and the lattice structure is unclear. In this study, based on the body-centered cubic (BCC) and face-centered cubic (FCC) titanium lattice material fabricated by SLM, different heat treatments (750-1050°C, including hot isostatic pressing) were conducted to study the relationship between the microstructure and mechanical properties of the base material and the mechanical properties of the lattice materials. The results show that bending-dominated structure BCC is more sensitive to the heat treatment conditions than stretching-dominated structure FCC. The better heat treatment temperature for BCC and FCC are 920°C and 750°C respectively. Moreover, a numerical simulation model was established to show the relationship between the mechanical properties of the base material and the lattice material. These results are significant for the design and application of titanium lattice materials.
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Two novel diamond lattice structures (Dfcc and Dhex) and the typical face-centered cubic (FCC) and body-centered cubic (BCC) lattice structures are manufactured by selective laser melting (SLM), and ...the effects of cell topology and relative density on the dynamic behavior of these structures are studied through a combination of experimental tests and numerical simulation. It is observed that in Dfcc and Dhex, failure initiates at the connection points between rods in the middle of the structure, causing a sudden drop of the measured stress value. However in FCC and BCC, failure initiates in the face-truss junction. Generally, the FCC and BCC are dominated by stretching and bending of the rods respectively, whereas the Dfcc and Dhex are a mixture of the two deformation modes. The results show that the mechanical properties of the lattice structures with different relative density can be described by a power law function. Moreover, for the lattice structures with the same rod diameter of 0.8 mm, FCC out-performs other structures in terms of specific strength, specific modulus and energy absorption. This gives evidence that lattice structures with the stretching-dominated deformation mode are more likely to exhibit better mechanical properties under dynamic loading.
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•Two novel diamond lattice structures (Dfcc and Dhex) and the typical FCC and BCC lattice structures were designed.•A numerical simulation model has been developed, and was consistent well with the experimental results.•Using a power law function to relate different mechanical properties to rod diameter or relative density for each lattice type.•Stretching-dominated structures often exhibit better dynamic mechanical properties than bending-dominated structures.
•Corrosion behaviors on different planes of Sc- and Zr- modified Al-Mg alloy processed by selective laser melting were systematically studied using electrochemical measurements.•Microstructures ...including precipitations, grain size distributions and crystallographic orientations on different planes of Al-Mg-Sc-Zr alloy processed by SLM were characterized using BSE and EBSD.•Inner mechanisms for the anisotropic corrosion behavior were further proposed based on the microstructure analyses.
Electrochemical measurements and microstructural analyses were conducted to investigate the corrosion behaviors on different planes of Sc and Zr modified Al-Mg alloy produced by selective laser melting (SLM). Results indicated that the XY-plane exhibited a superior corrosion resistance with a lower current density (icorr =57.1 μA cm-2) compared to the XZ-plane in 3.5 wt.% NaCl solution at room temperature. The microstructural analyses suggested that the anisotropic corrosion resistances of the SLM produced Al-Mg-Sc-Zr alloy related to the quite different microstructures on different planes, which included the molten pool boundary density, Al3(Sc,Zr) precipitation distribution, grain size distribution, and crystallographic orientation.
High-efficiency blue phosphorescence emission is essential for organic optoelectronic applications. However, synthesizing heavy-atom-free organic systems having high triplet energy levels and ...suppressed non-radiative transitions-key requirements for efficient blue phosphorescence-has proved difficult. Here we demonstrate a simple chemical strategy for achieving high-performance blue phosphors, based on confining isolated chromophores in ionic crystals. Formation of high-density ionic bonds between the cations of ionic crystals and the carboxylic acid groups of the chromophores leads to a segregated molecular arrangement with negligible inter-chromophore interactions. We show that tunable phosphorescence from blue to deep blue with a maximum phosphorescence efficiency of 96.5% can be achieved by varying the charged chromophores and their counterions. Moreover, these phosphorescent materials enable rapid, high-throughput data encryption, fingerprint identification and afterglow display. This work will facilitate the design of high-efficiency blue organic phosphors and extend the domain of organic phosphorescence to new applications.
Modeling user intention with limited evidence in short-term historical sequences is a major challenge in session recommendation. In this domain, research exploration extends from traditional methods ...to deep learning. However, most of them solely concentrate on the sequential dependence or pairwise relations within the session, disregarding the inherent consistency among items. Additionally, there is a lack of research on context adaptation in session intention learning. To this end, we propose a novel session-based model named C-HAN, which consists of two parallel modules: the context-embedded hypergraph attention network and self-attention. These modules are designed to capture the inherent consistency and sequential dependencies between items. In the hypergraph attention network module, the different types of interaction contexts are introduced to enhance the model’s contextual awareness. Finally, the soft-attention mechanism efficiently integrates the two types of information, collaboratively constructing the representation of the session. Experimental validation on three real-world datasets demonstrates the superior performance of C-HAN compared to state-of-the-art methods. The results show that C-HAN achieves an average improvement of 6.55%, 5.91%, and 6.17% over the runner-up baseline method on Precision@K, Recall@K, and MRR evaluation metrics, respectively.
Gaming as a cutting-edge concept has recently been used by some innovative tourism sectors as a marketing tool and as a method of deeper engagement with visitors. This research aims to explore the ...gamification trend and its potential for experience development and tourism marketing. Using a focus group, this paper discusses gaming and tourism, and explores what drives tourists to play games. The results suggest tourists' game playing motivation is multidimensional. Players tend to start with purposive information seeking, then move on to an intrinsic stimulation. Socialization is also an important dimension. The research demonstrates several implications for tourism marketing.
Objectives
To investigate whether CT-based radiomics signature can predict
KRAS/NRAS/BRAF
mutations in colorectal cancer (CRC).
Methods
This retrospective study consisted of a primary cohort (n = 61) ...and a validation cohort (n = 56) with pathologically confirmed CRC. Patients underwent
KRAS/NRAS/BRAF
mutation tests and contrast-enhanced CT before treatment. A total of 346 radiomics features were extracted from portal venous-phase CT images of the entire primary tumour. Associations between the genetic mutations and clinical background, tumour staging, and histological differentiation were assessed using univariate analysis. RELIEFF and support vector machine methods were performed to select key features and build a radiomics signature.
Results
The radiomics signature was significantly associated with
KRAS/NRAS/BRAF
mutations (
P
< 0.001). The area under the curve, sensitivity, and specificity for predicting
KRAS/NRAS/BRAF
mutations were 0.869, 0.757, and 0.833 in the primary cohort, respectively, while they were 0.829, 0.686, and 0.857 in the validation cohort, respectively. Clinical background, tumour staging, and histological differentiation were not associated with
KRAS/NRAS/BRAF
mutations in both cohorts (
P
>0.05).
Conclusions
The proposed CT-based radiomics signature is associated with
KRAS/NRAS/BRAF
mutations. CT may be useful for analysis of tumour genotype in CRC and thus helpful to determine therapeutic strategies.
Key Points
•
Key features were extracted from CT images of the primary colorectal tumour.
•
The proposed radiomics signature was significantly associated with KRAS/NRAS/BRAF mutations.
•
In the primary cohort, the proposed radiomics signature predicted mutations.
•
Clinical background, tumour staging, and histological differentiation were unable to predict mutations.
DNA methylation is a biochemical process in which a methyl group is added to the cytosine-phosphate-guanine (CpG) site on DNA molecules without altering the DNA sequence. Multiple CpG sites in a ...certain genome region can be differentially methylated across phenotypes. Identifying these differentially methylated CpG regions (DMRs) associated with the phenotypes contributes to disease prediction and precision medicine development.
We propose a novel DMR detection algorithm, gbdmr. In contrast to existing methods under a linear regression framework, gbdmr assumes that DNA methylation levels follow a generalized beta distribution. We compare gbdmr to alternative approaches via simulations and real data analyses, including dmrff, a new DMR detection approach that shows promising performance among competitors, and the traditional EWAS that focuses on single CpG sites. Our simulations demonstrate that gbdmr is superior to the other two when the correlation between neighboring CpG sites is strong, while dmrff shows a higher power when the correlation is weak. We provide an explanation of these phenomena from a theoretical perspective. We further applied the three methods to multiple real DNA methylation datasets. One is from a birth cohort study undertaken on the Isle of Wight, United Kingdom, and the other two are from the Gene Expression Omnibus database repository. Overall, gbdmr identifies more DMR CpGs linked to phenotypes than dmrff, and the simulated results support the findings.
Gbdmr is an innovative method for detecting DMRs based on generalized beta regression. It demonstrated notable advantages over dmrff and traditional EWAS, particularly when adjacent CpGs exhibited moderate to strong correlations. Our real data analyses and simulated findings highlight the reliability of gbdmr as a robust DMR detection tool. The gbdmr approach is accessible and implemented by R on GitHub: https://github.com/chengzhouwu/gbdmr .
An electronic nose was used to evaluate the bitterness and astringency of green tea, and the possible application of the sensor was assessed for the evaluation of different tasting green tea samples. ...Three different grades of green tea were measured with the electronic nose and electronic tongue. The sensor array of the E-nose was optimized by correlation analysis. The relationship between the signal of the optimized sensor array and the bitterness and astringency of green tea was developed using multiple linear regression (MLR), partial least squares regression (PLSR), and back propagation neural network (BPNN). BPNN is a multilayer feedforward neural network trained by an error propagation algorithm. The results showed that the BPNN model possessed good ability to predict the bitterness and astringency of green tea, with high correlation coefficients (R = 0.98 for bitterness and R = 0.96 for astringency) and relatively lower root mean square errors (RMSE) (0.25 for bitterness and 0.32 for astringency) for the calibration set. The R value is 0.92 and 0.87, and the RMSE is 0.34 and 0.55, for bitterness and astringency, respectively, of the prediction set. These results indicate that the electronic nose could be used as a feasible and reliable method to evaluate the taste of green tea. These results can provide a theoretical reference for rapid detection of the bitter and astringent taste of green tea using volatile odor information.
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