Genomic regions, cellular components and gene regulatory basis underlying pod length variations in cowpea (V. unguiculata L. Walp).

Cowpea (V. unguiculata L. Walp) is a climate resilient legume crop important for food security. Cultivated cowpea (V. unguiculata L) generally comprises the bushy, short-podded grain cowpea dominant in Africa and the climbing, long-podded vegetable cowpea popular in Asia. How selection has contributed to the diversification of the two types of cowpea remains largely unknown. In the current study, a novel genotyping assay for over 50 000 SNPs was employed to delineate genomic regions governing pod length. Major, minor and epistatic QTLs were identified through QTL mapping. Seventy-two SNPs associated with pod length were detected by genome-wide association studies (GWAS). Population stratification analysis revealed subdivision among a cowpea germplasm collection consisting of 299 accessions, which is consistent with pod length groups. Genomic scan for selective signals suggested that domestication of vegetable cowpea was accompanied by selection of multiple traits including pod length, while the further improvement process was featured by selection of pod length primarily. Pod growth kinetics assay demonstrated that more durable cell proliferation rather than cell elongation or enlargement was the main reason for longer pods. Transcriptomic analysis suggested the involvement of sugar, gibberellin and nutritional signalling in regulation of pod length. This study establishes the basis for map-based cloning of pod length genes in cowpea and for marker-assisted selection of this trait in breeding programmes

Pedestrian–bus route and pickup location planning for emergency evacuation

Planning for a bus-based regional evacuation is essential for emergency preparedness, especially for hurricane or flood prone urban environments with large numbers of transit-dependent or transit-captive populations. This paper develops an optimization-based decision-support model for pedestrian–bus evacuation planning under bus fleet, pedestrian and bus routes, and network constraints. Aiming to minimize the evacuation duration time, an optimization model is proposed to determine the optimal pickup nodes for evacuees to assemble using existing pedestrian routes, and to allocate available bus fleet via bus routes and urban road network to transport the assembled evacuees between the pickup nodes and designated public shelters. The numerical examples with two scenarios based on the Sioux Falls street network from North Dakota (United States) demonstrates that this model can be used to optimize the evacuation duration time, the location of pickup nodes and bus assignment simultaneously. First published online 13 October 202

Analysis of lncRNA Expression in Patients With Eosinophilic and Neutrophilic Asthma Focusing on LNC_000127

Long non-coding RNA (lncRNA) is important in many diseases. Some studies have shown that lncRNA affects the pathogenesis of systemic inflammation of asthma. lncRNA regulates gene transcription, protein expression, and epigenetic regulation. However, lncRNAs associated with different airway phenotypes, such as eosinophilic (Eos) and neutrophilic (Neu) asthma have not been identified. The goal of this study was to determine the differences in circulating lncRNA signatures in Eos and Neu samples. Using RNA-sequencing (RNA-seq), lncRNA expression was evaluated in peripheral whole blood samples among Eos patients, Neu patients, and healthy individuals (Control). Bioinformatic analysis was used to predict relevant biological pathways. Quantitative PCR (qPCR) was used to measure gene expression in whole blood samples, Jurkat cells, and human CD4+ T cells. Finally, a novel lncRNA, LNC_000127, was inhibited by transfection of Jurkat cells with a lentiviral vector, and the effect was examined by Human Asthma RT2 Profiler™ PCR Array and western blotting. Compared to control samples, Eos samples contained 190 unique lncRNAs and Neu samples had 166 unique lncRNAs (difference ≥2-fold). KEGG pathway annotation data and GO terms revealed that different lncRNAs are involved in different mechanisms. LNC_000127, was highly expressed in Eos samples before treatment; its expression was increased in Jurkat cells and human CD4+ T cells following stimulation with PMA/CD28. Subsequent analyses revealed that LNC_000127 functions in the Th2 inflammation pathway. The results suggest that lncRNAs are involved in different phenotypes of asthma. Whether the different phenotypes of asthma can be recognized based on these lncRNAs (as biomarkers) requires further analysis. Targeting LNC_000127 may be effective for reducing Th2 inflammation in Eos asthma

A SNP and SSR Based Genetic Map of Asparagus Bean (Vigna. unguiculata ssp. sesquipedialis) and Comparison with the Broader Species

Asparagus bean (Vigna. unguiculata ssp. sesquipedialis) is a distinctive subspecies of cowpea [Vigna. unguiculata (L.) Walp.] that apparently originated in East Asia and is characterized by extremely long and thin pods and an aggressive climbing growth habit. The crop is widely cultivated throughout Asia for the production of immature pods known as ‘long beans’ or ‘asparagus beans’. While the genome of cowpea ssp. unguiculata has been characterized recently by high-density genetic mapping and partial sequencing, little is known about the genome of asparagus bean. We report here the first genetic map of asparagus bean based on SNP and SSR markers. The current map consists of 375 loci mapped onto 11 linkage groups (LGs), with 191 loci detected by SNP markers and 184 loci by SSR markers. The overall map length is 745 cM, with an average marker distance of 1.98 cM. There are four high marker-density blocks distributed on three LGs and three regions of segregation distortion (SDRs) identified on two other LGs, two of which co-locate in chromosomal regions syntenic to SDRs in soybean. Synteny between asparagus bean and the model legume Lotus. japonica was also established. This work provides the basis for mapping and functional analysis of genes/QTLs of particular interest in asparagus bean, as well as for comparative genomics study of cowpea at the subspecies level

Project O2 - Macroscopic Fundamental Diagram Based Discrete Transportation Network Design

The presence of demand uncertainty brings challenges to network design problems (NDP), because fluctuations in origin-destination (OD) demand have a prominent effect on the corresponding total travel time, which is usually adopted as an index to evaluate the network design problem. Fortunately, the macroscopic fundamental diagram (MFD) has been proved to be a property of the road network itself, independent of the origin-destination demand. Such characteristics of an MFD provide a new theoretical basis to assess the traffic network performance and further appraise the quality of network design strategies. Focusing on improving network capacity under the NDP framework, this paper formulates a bi-level programming model, where at the lower level, flows are assigned to the newly extended network subject to user equilibrium theory, and the upper level determines which links should be added to achieve the maximum network capacity. To solve the proposed model, we design an algorithm framework, where traffic flow distribution of each building strategy is calculated under the dynamic user equilibrium (DUE), and updated through the VISSIM-COM-Python interaction. Then, the output data are obtained to shape MFDs, and "jats:italic"k"/jats:italic"-means clustering algorithm is employed to quantify the MFD-based network capacity. Finally, the methodology is implemented in a test network, and the results show the benefits of using the MFD-based method to solve the network design problem under stochastic OD demands. Specifically, the capacity paradox is also presented in the test results. Document type: Articl

The Peak Stability Analysis through Hysteresis Phenomenon on Heterogeneous Networks

The macroscopic fundamental diagram (MFD) is a nonuniversal changing process over network traffic status which indicates different shapes in different networks. Hysteresis is observed in the MFD of some urban networks. It is a unique phenomenon when the network remains at low stability level and usually appears around the congestion period. This paper analyzed network peak stability through focusing on hysteresis. The formation mechanism of hysteresis is deduced from the mathematical method based on previous research studies. The precondition of hysteresis and the changing process of network state can be figured by mathematical deduction. It indicates that hysteresis only occurs conditionally in the period of macroscopic congestion and is not a universal phenomenon. Heterogeneity is an important factor leading to network instability. The hysteresis patterns of different peaks in MFD are different due to the variation of network flow. Real data are collected from Atlanta’s urban network to verify the analysis of hysteresis. To discuss the changing process of hysteresis in different peaks, a three-stage division is proposed and time series is presented as a third dimension in MFD. It is worth noticing that the existence and form of hysteresis in morning and evening peaks are different. Although there is a higher peak flow in the morning peak, the stability of the evening peak performs better when hysteresis occurs in the network. The different fluctuations in the morning and evening peaks are exhibited through the 3D version of MFD. The otherness of hysteresis in different peaks is explained through a 3D coordinate system with cross-compared corresponding indexes

Compressing material and texture attributes for triangular meshes

A novel scheme for single-rate compression of material and texture attributes for triangular meshes is proposed in this work. For the material coding, it proposes a novel approach based on breadth-first surface traversal, exploiting the local coherence of the material attributes among neighboring facets; for the texture coordinate coding, it proposes a similar-triangle-based prediction method, exploiting the correlation between 3D geometry and its texture-space parameterization. As a result, the proposed algorithm achieves efficient coding of the material and the texture attributes, as experimentally demonstrated.EICPCI-S(ISTP)[email protected]; [email protected]; [email protected]; [email protected]

An improved vertex-clustering-based progressive mesh encoder

In this work, we propose improvements on a state-of-the-art scheme for progressive triangular mesh compression, which is based on hierarchical vertex clustering. Specifically, we fix several shortcomings of that scheme including quantization error accumulation, false facet generation and lack of facet orientation encoding. In addition, the resultant mesh encoder yields better rate-distortion performance than another state-of-the-art one on our test model, as demonstrated by the experiments.EICPCI-S(ISTP)[email protected]; [email protected]; [email protected]; [email protected]

DEASeq2Seq: An attention based sequence to sequence model for short-term metro passenger flow prediction within decomposition-ensemble strategy

Short-term passenger flow prediction has practical significance for metro management and operation. However, the complex nonlinear and non-stationary characteristics make it challenging to detect evolution characteristics of passenger flow. To address this problem, a hybrid short-term metro passenger flow prediction model named decomposition ensemble attention sequence to sequence (DEASeq2Seq) is proposed in this paper. The proposed DEASeq2Seq includes three phases: decomposition, ensemble, and prediction. First, complete empirical mode decomposition with adaptive noise (CEEMDAN) is utilized to decompose the original passenger flow data into several intrinsic mode functions (IMFs) and a residue. Second, recurrence quantification analysis (RQA) is performed to reconstruct the decomposed modes into a stochastic part, a deterministic part, and a trend part via determinism evaluation. Third, a Seq2Seq model with the attention mechanism is proposed to execute multistep prediction for short-term passenger flow and explore the influence mechanism of the reconstructed components on the prediction targets. The real dataset from Chengdu metro, China, is used to verify the proposed model. The experiment results show that the proposed DEASeq2Seq model outperforms the benchmark models. Further model interpretations are conducted to analyze the impacts of decomposition strategy, ensemble strategy, and attention mechanism

Development and Validation of a Photoplethysmography System for Noninvasive Monitoring of Hemoglobin Concentration

Background. Traditional invasive hemoglobin (Hb) detection led to delayed diagnosis, operational inefficiency, incorrect critical decision making, and uncomfortable patient experience. To facilitate real-time total hemoglobin (tHb) monitoring, a portable prototype of a noninvasive Hb detection system was developed, and the accuracy of Hb predicted based on partial least squares (PLS) as well as backpropagation artificial neural network (BP-ANN) models was validated. Results. The prototype was combined with a signal processing circuit and a spectrophotometric probe containing 8 wavelength LEDs light source and photodiode array. Laboratory invasive Hb (Lab_tHb) and spot check Hb measurements with PLS (SpHb_PLS) and BP (SpHb_BP) methods were obtained simultaneously by hematology analyzer and the designed system. The invasive and noninvasive estimates of the Hb levels were analyzed using Spearman correlation as well as Bland–Altman plot and receiver operating characteristic (ROC) curve analysis. A total of 238 volunteers had attempted laboratory invasive and noninvasive spot check Hb measurements. Mean Lab_tHb, SpHb_PLS, and SpHb_BP were 13.6 ± 1.80 g/dL, 13.5 ± 1.07 g/dL, and 13.6 ± 1.06 g/dL, respectively. Noninvasive SpHb_PLS (r = 0.61, p<0.001) and SpHb_BP (r = 0.62, p<0.001) had a strong correlation with invasive tHb values. The Bland–Altman plot showed excellent consistency between the proposed noninvasive methods and laboratory invasive reference. In ROC analysis, PLS and BP models were good at predicting Hb ≥ 12 g/dL with area under the curve of 0.828 and 0.824, respectively. Observed differences between invasive and noninvasive Hb measurements displayed no significant correlation with perfusion index values. Conclusions. The result confirmed that noninvasive Hb monitoring had an excellent correlation with traditional invasive Hb measurement. Furthermore, it is suggested that the developed prototype has the potential for the noninvasive detection of Hb concentration with the methods of PLS and BP-ANN