Customizing the promotion strategies of integrated air-bus service based on passenger satisfaction

The integrated air-bus service expands the catchment area and alleviates congestion of regional airports. To gain further insights into the unexplored potential attributes of the integrated service that generate passenger satisfaction, this paper utilizes a two-stage analysis approach to identify the key promotion factors for passengers from different constituents. Based on the survey data collected in Nanjing Lukou International Airport, this paper 1) uses k-means clustering to categorize respondents into four groups. 2) Combines the gradient boosting decision tree and impact asymmetry analysis to identify the attributes that have nonlinear influences on the overall service satisfaction for each group respectively. Results suggest that the timetable of the airport bus is critical for all passenger groups. Interestingly, there are noticeable differences in passenger satisfaction with the accessibility, cost affordability, comfort, reliability, and integration of the integrated service, providing the basis for customizing service promotion strategies among different passenger groups and airports.</p

NASICON-type air-stable and all-climate cathode for sodium-ion batteries with low cost and high-power density

The development of low-cost and long-lasting all-climate cathode materials for the sodium ion battery has been one of the key issues for the success of large-scale energy storage. One option is the utilization of earth-abundant elements such as iron. Here, we synthesize a NASICON-type tuneable Na4Fe3(PO4)2(P2O7)/C nanocomposite which shows both excellent rate performance and outstanding cycling stability over more than 4400 cycles. Its air stability and all-climate properties are investigated, and its potential as the sodium host in full cells has been studied. A remarkably low volume change of 4.0% is observed. Its high sodium diffusion coefficient has been measured and analysed via first-principles calculations, and its three-dimensional sodium ion diffusion pathways are identified. Our results indicate that this low-cost and environmentally friendly Na4Fe3(PO4)2(P2O7)/C nanocomposite could be a competitive candidate material for sodium ion batteries

miR159 Represses a Constitutive Pathogen Defense Response in Tobacco

MicroR159 (miR159) regulation of GAMYB expression is highly conserved in terrestrial plants; however, its functional role remains poorly understood. In Arabidopsis (Arabidopsis thaliana), although GAMYB-like genes are constitutively transcribed during vegetative growth, their effects are suppressed by strong and constitutive silencing by miR159. GAMYB expression occurs only if miR159 function is inhibited, which results in detrimental pleiotropic defects, questioning the purpose of the miR159-GAMYB pathway. Here, miR159 function was inhibited in tobacco (Nicotiana tabacum) and rice (Oryza sativa) using miRNA MIM159 technology. Similar to observations in Arabidopsis, inhibition of miR159 in tobacco and rice resulted in pleiotropic defects including stunted growth, implying functional conservation of the miR159-GAMYB pathway among angiosperms. In MIM159 tobacco, transcriptome profiling revealed that genes associated with defense and programmed cell death were strongly activated, including a suite of 22 PATHOGENESIS-RELATED PROTEIN (PR) genes that were 100- to 1,000-fold upregulated. Constitutive expression of a miR159-resistant GAMYB transgene in tobacco resulted in phenotypes similar to that of MIM159 tobacco and activated PR gene expression, verifying the dependence of the above-mentioned changes on GAMYB expression. Consistent with the broad defense response, MIM159 tobacco appeared immune to Phytophthora infection. These findings suggest that the tobacco miR159-GAMYB pathway functions in the biotic defense response, which becomes activated upon miR159 inhibition. However, PR gene expression was not upregulated in Arabidopsis or rice when miR159 was inhibited, suggesting that miR159-GAMYB pathway functional differences exist between species, or factors in addition to miR159 inhibition are required in Arabidopsis and rice to activate this broad defense response

From Plate to Prevention: A Dietary Nutrient-aided Platform for Health Promotion in Singapore

Singapore has been striving to improve the provision of healthcare services to her people. In this course, the government has taken note of the deficiency in regulating and supervising people's nutrient intake, which is identified as a contributing factor to the development of chronic diseases. Consequently, this issue has garnered significant attention. In this paper, we share our experience in addressing this issue and attaining medical-grade nutrient intake information to benefit Singaporeans in different aspects. To this end, we develop the FoodSG platform to incubate diverse healthcare-oriented applications as a service in Singapore, taking into account their shared requirements. We further identify the profound meaning of localized food datasets and systematically clean and curate a localized Singaporean food dataset FoodSG-233. To overcome the hurdle in recognition performance brought by Singaporean multifarious food dishes, we propose to integrate supervised contrastive learning into our food recognition model FoodSG-SCL for the intrinsic capability to mine hard positive/negative samples and therefore boost the accuracy. Through a comprehensive evaluation, we present performance results of the proposed model and insights on food-related healthcare applications. The FoodSG-233 dataset has been released in https://foodlg.comp.nus.edu.sg/

The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets

BackgroundMethamphetamine use disorder (MUD) poses a considerable public health threat, and its identification remains challenging due to the subjective nature of the current diagnostic system that relies on self-reported symptoms. Recent studies have suggested that MUD patients may have gut dysbiosis and that gut microbes may be involved in the pathological process of MUD. We aimed to examine gut dysbiosis among MUD patients and generate a machine-learning model utilizing gut microbiota features to facilitate the identification of MUD patients.MethodFecal samples from 78 MUD patients and 50 sex- and age-matched healthy controls (HCs) were analyzed by 16S rDNA sequencing to identify gut microbial characteristics that could help differentiate MUD patients from HCs. Based on these microbial features, we developed a machine learning model to help identify MUD patients. We also used public data to verify the model; these data were downloaded from a published study conducted in Wuhan, China (with 16 MUD patients and 14 HCs). Furthermore, we explored the gut microbial features of MUD patients within the first three months of withdrawal to identify the withdrawal period of MUD patients based on microbial features.ResultsMUD patients exhibited significant gut dysbiosis, including decreased richness and evenness and changes in the abundance of certain microbes, such as Proteobacteria and Firmicutes. Based on the gut microbiota features of MUD patients, we developed a machine learning model that demonstrated exceptional performance with an AUROC of 0.906 for identifying MUD patients. Additionally, when tested using an external and cross-regional dataset, the model achieved an AUROC of 0.830. Moreover, MUD patients within the first three months of withdrawal exhibited specific gut microbiota features, such as the significant enrichment of Actinobacteria. The machine learning model had an AUROC of 0.930 for identifying the withdrawal period of MUD patients.ConclusionIn conclusion, the gut microbiota is a promising biomarker for identifying MUD and thus represents a potential approach to improving the identification of MUD patients. Future longitudinal studies are needed to validate these findings

Xenotime-type high-entropy (Dy1/7Ho1/7Er1/7Tm1/7Yb1/7Lu1/7Y1/7)PO4: A promising thermal/environmental barrier coating material for SiCf/SiC ceramic matrix composites

Rare-earth phosphates (REPO4) are regarded as one of the promising thermal/environmental barrier coating (T/EBC) materials for SiCf/SiC ceramic matrix composites (SiC-CMCs) owing to their excellent resistance to water vapor and CaO–MgO–Al2O3–SiO2 (CMAS). Nevertheless, a relatively high thermal conductivity (κ) of the REPO4 becomes the bottleneck for their practical applications. In this work, novel xenotime-type high-entropy (Dy1/7Ho1/7Er1/7Tm1/7Yb1/7Lu1/7Y1/7)PO4 (HE (7RE1/7)PO4) has been designed and synthesized for the first time to solve this issue. HE (7RE1/7)PO4 with a homogeneous rare-earth element distribution exhibits high thermal stability up to 1750 ℃ and good chemical compatibility with SiO2 up to 1400 ℃. In addition, the thermal expansion coefficient (TEC) of HE (7RE1/7)PO4 (5.96×10−6 ℃−1 from room temperature (RT) to 900 ℃) is close to that of the SiC-CMCs. What is more, the thermal conductivities of HE (7RE1/7)PO4 (from 4.38 W·m−1·K−1 at 100 ℃ to 2.25 W·m−1·K−1 at 1300 ℃) are significantly decreased compared to those of single-component REPO4 with the minimum value ranging from 9.90 to 4.76 W·m−1·K−1. These results suggest that HE (7RE1/7)PO4 has the potential to be applied as the T/EBC materials for the SiC-CMCs in the future

Field Instruction Multiple Data

Fully homomorphic encryption~(FHE) has flourished since it was first constructed by Gentry~(STOC 2009). Single instruction multiple data~(SIMD) gave rise to efficient homomorphic operations on vectors in $(\mathbb{F}_{t^d})^\ell$, for prime $t$. RLWE instantiated with cyclotomic polynomials of the form $X^{2^N}+1$ dominate implementations of FHE due to highly efficient fast Fourier transformations. However, this choice yields very short SIMD plaintext vectors and high degree extension fields, e.g. $\ell 100$ for small primes~($t = 3, 5, \dots$). In this work, we describe a method to encode more data on top of SIMD, \emph{Field Instruction Multiple Data}, applying reverse multiplication friendly embedding~(RMFE) to FHE. With RMFE, length-$k$ $\mathbb{F}_{t}$ vectors can be encoded into $\mathbb{F}_{t^d}$ and multiplied once. The results have to be recoded~(decoded and then re-encoded) before further multiplications can be done. We introduce an FHE-specific technique to additionally evaluate arbitrary linear transformations on encoded vectors for free during the FHE recode operation. On top of that, we present two optimizations to unlock high degree extension fields with small $t$ for homomorphic computation: $r$-fold RMFE, which allows products of up to $2^r$ encoded vectors before recoding, and a three-stage recode process for RMFEs obtained by composing two smaller RMFEs. Experiments were performed to evaluate the effectiveness of FIMD from various RMFEs compared to standard SIMD operations. Overall, we found that FIMD generally had $>2\times$ better (amortized) multiplication times compared to FHE for the same amount of data, while using almost $k/2 \times$ fewer ciphertexts required