Brain‐inspired optical neural computing (ONC) is the state‐of‐the‐art scheme in modern computing, offering robust strategies to execute advanced inference with a high throughput and large‐scale ...parallelism. However, the hitherto prevalent diffractive ONC networks have watered‐down competence, which is mostly a phase‐only methodology but fails to precisely handle the Fourier transform of complex fields, thus forfeiting the integrity of the architecture and half the volume of available training weights. Here, a novel neural meta‐transformer (ONM) enabled by an optical rotation‐isolator‐assisted paradigm is proposed, whose meta‐neurons utilize structural birefringence and polarization rotation to achieve independently arbitrary tailoring of full Fourier components, that is the complete learnable parameters of diffractive ONC. The full‐Fourier‐component ONM has great merits over phase‐only counterparts in all representative cases: being a classifier, it improves the recognition accuracy, especially for input with more high‐frequency features; acting as an imager, the background noise of output is effectively diminished; and when engineering as an encoder, both near‐field grayscale nanoprinting and neural meta‐holography are yielded. The mechanism is minimalist, compact, and compatible with nonlinear activation, opening the route to fully parametric intelligent meta‐devices, with far‐reaching implications for optical computing, display, encryption, etc.
A full‐Fourier‐component diffractive neural network is constructed by birefringent metasurface units with the arbitrary and independent modulation of phase and amplitude. The proposed scheme provides multiple information storage dimensions and excellent inference capabilities for a variety of typical complex optical calculations, especially with absolute advantages for high‐frequency information processing.
Effective ground delay programs (GDP) are needed to intervene when there are bad weather or airport capacity issues. This paper proposes a new methodology for predicting the incidence of effective ...ground delay programs by utilizing machine learning techniques, which can improve the safety and economic benefits of flights. We use the combination of local weather and flight operation data along with the ATM airport performance (ATMAP) algorithm to quantify the weather and to generate an ATMAP score. We then compared the accuracy of three machine learning models, Support Vector Machine, Random Forest, and XGBoost, to estimate the probability of GDPs. The results of the weather analysis, performed by the ATMAP algorithm, indicated that the ceiling was the most critical weather factor. Lastly, we used two linear regression models (ridge and LASSO) and a non-linear regression model (decision tree) to predict departure flight delays during GDP. The predictive accuracy of the regression models was enhanced by an increase in ATMAP scores, with the decision tree model outperforming the other models, resulting in an improvement of 8.8% in its correlation coefficient (R2).
Allomelanin is a type of nitrogen-free melanin most commonly found in fungi. Its existence enhances resistance of the organisms to environmental damage and helps fungi survive harsh radiation ...conditions such as those found on spacecraft and inside contaminated nuclear power plants. We report the preparation and characterization of artificial allomelanin nanoparticles (AMNPs) via oxidative oligomerization of 1,8-dihydroxynaphthalene (1,8-DHN). We describe the resulting morphological and size control of AMNPs and demonstrate that they are radical scavengers. Finally, we show that AMNPs are taken up by neonatal human epidermal keratinocytes and packaged into perinuclear caps where they quench reactive oxygen species generated following UV exposure.
Background
The clinical progression of individuals afflicted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exhibits significant heterogeneity, particularly affecting the ...elderly population to a greater extent. Consequently, the association between nutrition and microbiota has garnered considerable interest. Hence, the objective of this study was to gather clinical data pertaining to the influence of diverse nutritional support interventions on the prognosis of geriatric patients with COVID-19, while additionally examining the fecal microbiota of these individuals to assess the repercussions of microecological alterations on their prognostic outcomes.
Results
A total of 71 elderly patients diagnosed with severe COVID-19 were included in this study. These patients were subsequently divided into two groups, namely the enteral nutrition (EN) group and the parenteral nutrition (PN) group, based on the type of nutritional support therapy they received after admission. The occurrence of complications was observed in 10.4% of patients in the EN group, whereas it was significantly higher at 69.6% in the PN group (P<0.001). Furthermore, the 60-day mortality rate was 2.1% (1/48) in the EN group, while it was notably higher at 30.4% (7/23) in the PN group (P=0.001). To identify the independent predictors of 60-day mortality, stepwise logistic regression analysis was employed. Among different bacterial groups,
Enterococcus_faecium
(18.19%) and
Pseudomonas_aeruginosa
(1.91%) had higher average relative abundance in the PN group (P<0.05). However, the relative abundance of
Ruminococcus
was higher in the EN group. Further Spearman correlation analysis showed that
Enterococcus_faecium
was positively correlated with poor clinical prognosis, while
Ruminococcus
was negatively correlated with poor clinical prognosis.
Conclusions
This study shows that the changes in the composition of intestinal flora in elderly COVID-19 patients receiving different nutritional support strategies may be related to different clinical outcomes. The abundance of
Enterococcus_faecium
in elderly COVID-19 patients receiving PN is significantly increased and is closely related to poor clinical outcomes. It highlights the potential of microbiome-centric interventions to mitigate and manage COVID-19 in older adults with different nutritional support options.
Recently, in order to ensure the reliability and safety of trains, online condition monitoring and fault diagnosis of traction induction motors have become active issues in the area of rail ...transportation. The fault diagnosis algorithm can be developed and debugged in a real-time environment based on hardware-in-the-loop simulation (HILS). However, the dynamic space model of induction motors with stator interturn short-circuit faults faces the problem that the faulty state and the healthy state are not compatible, which is inconvenient for the HILS. In this paper, a fault injection model is proposed for the first time, which can realize the online switching between the healthy state and the faulty state of the motor. The feasibility and effectiveness of the proposed model are verified by simulation experiments the based on MATLAB/Simulink and dSPACE HILS platforms.
Soybean (Glycine max) is a major grain and oil crop worldwide, but low phosphorus (LP) in soil severely limits the development of soybean production. Dissecting the regulatory mechanism of the ...phosphorus (P) response is crucial for improving the P use efficiency of soybean. Here, we identified a transcription factor, GmERF1 (ethylene response factor 1), that is mainly expressed in soybean root and localized in the nucleus. Its expression is induced by LP stress and differs substantially in extreme genotypes. The genomic sequences of 559 soybean accessions suggested that the allelic variation of GmERF1 has undergone artificial selection, and its haplotype is significantly related to LP tolerance. GmERF1 knockout or RNA interference resulted in significant increases in root and P uptake efficiency traits, while the overexpression of GmERF1 produced an LP-sensitive phenotype and affected the expression of 6 LP stress-related genes. In addition, GmERF1 directly interacted with GmWRKY6 to inhibit transcription of GmPT5 (phosphate transporter 5), GmPT7, and GmPT8, which affects plant P uptake and use efficiency under LP stress. Taken together, our results show that GmERF1 can affect root development by regulating hormone levels, thus promoting P absorption in soybean, and provide a better understanding of the role of GmERF1 in soybean P signal transduction. The favorable haplotypes from wild soybean will be conducive to the molecular breeding of high P use efficiency in soybean.
The essence of enterotypes is to stratify the entire human gut microbiota, and dysregulation of gut microbiota is closely related to the development of colorectal adenoma. Enterotypes may therefore ...be a useful target for the prevention of colorectal adenoma. However, the relationship between gut microbiota and colorectal adenoma has not been fully elucidated. In this study, we aimed to analyze the differences in gut microbiome composition between adenoma and control populations.
We recruited 31 patients with colorectal adenoma and 71 non-adenoma controls. Patient demographics, risk factors, fecal samples from each subject were collected and metagenomic sequencing was performed. LEfSe analysis was used to reveal differences in intestinal microbiome composition. Multiple logistic regression analysis was used to determine the association between enterotypes and colorectal adenoma.
The results showed that
enterotype (enterotype 4) is only present in adenoma group. Logistic regression analysis showed that
enterotype was an independent risk factor for colorectal adenoma.
The
enterotype may increase the occurrence of colorectal adenoma through inflammatory association and interference with glucose and lipid metabolism in human body. In conclusion, the differences we observed between different enterotypes add a new potential factor to the development of colorectal adenoma.
In the multi-step cutting process, the final machined surface quality is affected by the entire cutting process, especially the effect of work hardening and thermal softening induced by the previous ...steps (roughing or semi-finishing machining). In this paper, two-step (roughing-finishing) and three-step (roughing-semi-finishing-finishing) turning operations were designed by a single-factor experiment, and the effect of the change of cutting parameters in the previous steps on finishing surface quality was analyzed. Experimental results indicated that the microhardness in the machined surface layer of semi-finishing was smaller than that of roughing at the same depth, and the depth affected by work hardening of semi-finishing was thinner. Therefore, compared to two-step machining, the surface roughness affected by the work hardening and thermal softening of the previous steps was smaller after three-step machining, and the variation range of surface roughness with the change of the cutting parameters was smaller. Moreover, the relative height between the convex peak and the concave valley was larger. And the spacing between adjacent two convex peaks became larger and more uneven after three-step machining. The disturbed layer depth or the plastic deformation layer (PDL) depth was obviously reduced. However, the grains were severely distorted and stretched. It was because that semi-finishing weakened the work hardening of roughing in the three-step cutting process; therefore, the surface quality was better after finishing. By studying the effect of work hardening and thermal softening induced by the previous steps on finishing surface quality, the cutting parameters of roughing and semi-finishing were optimized to ultimately improve surface quality.
Carbamazepine (CBZ) antibiotic organic contamination wastewater poses a huge threat to environmental safety. An advanced oxidation technology (Fe0/PDS/US) of using ultrasound (US) enhanced ...zero-valent iron/potassium persulfate (Fe0/PDS) can remove CBZ effectively. The optimal reaction conditions were determined by exploring the effect of single-factor experimental conditions such as ultrasonic power, ultrasonic frequency, CBZ concentration, solution pH, PDS dosage, and Fe0 dosage on the removal of CBZ. In addition, we also investigated into the effect of background ions (PO43−, HCO3−, Cl− and HA) on Fe0/PDS/US and analyzed the related results. The mechanism of CBZ removal in Fe0/PDS/US were explored by analyzing CBZ removal efficiency and reaction rates, the ion concentration of S2O82−, SO42−, Fe2+ and Fe3+, pH and the active radicals. The result indicates that US can improve the efficiency of activated PDS and expand the pH range of Fe0/PDS. It has prominent performance in catalytically degrading CBZ when the pH is 10.0. SO4•-, •OH and O2•- all coexist in the Fe0/PDS/US and make contribution to CBZ removal, whereas the SO4•− plays a key role. US can greatly promotes the degradation of target pollutant CBZ by speeding up the dissolution of the outer portion of iron powder, producing sufficient amount of Fe2+ with a continuous and stable way, and better activating S2O82− to generate sufficient SO4•− radicals. The degradation of CBZ may embrace three reaction processes, in which organic intermediate products with low molecular weight and biological toxicity is produced, boosting further mineralization and biodegradation of products. The Fe0/PDS/US is of great potential application value in removal of organic pollution and environmental purification.
Display omitted
•Ultrasound (US) significantly enhances CBZ removal in Fe0/PDS/US, and expands the pH adaptive range.•US makes Fe0 to produce sufficient amount of Fe2+ with a continuous and stable way.•The intermediate products of CBZ have low molecular weight and biological toxicity.•The SO4.•-, •OH and O2•- make contribution to CBZ removal, whereas SO4•- plays a key role.
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