Intermodal Distance Research Articles

On the Determinants of Trade Between South Korea and Chinese Provinces: Considering Sea-Rail Intermodal Transport Distance

On the Determinants of Trade Between South Korea and Chinese Provinces: Considering Sea-Rail Intermodal Transport Distance

Heterogeneous Test-Time Training for Multi-Modal Person Re-identification

Multi-modal person re-identification (ReID) seeks to mitigate challenging lighting conditions by incorporating diverse modalities. Most existing multi-modal ReID methods concentrate on leveraging complementary multi-modal information via fusion or interaction. However, the relationships among heterogeneous modalities and the domain traits of unlabeled test data are rarely explored. In this paper, we propose a Heterogeneous Test-time Training (HTT) framework for multi-modal person ReID. We first propose a Cross-identity Inter-modal Margin (CIM) loss to amplify the differentiation among distinct identity samples. Moreover, we design a Multi-modal Test-time Training (MTT) strategy to enhance the generalization of the model by leveraging the relationships in the heterogeneous modalities and the information existing in the test data. Specifically, in the training stage, we utilize the CIM loss to further enlarge the distance between anchor and negative by forcing the inter-modal distance to maintain the margin, resulting in an enhancement of the discriminative capacity of the ultimate descriptor. Subsequently, since the test data contains characteristics of the target domain, we adapt the MTT strategy to optimize the network before the inference by using self-supervised tasks designed based on relationships among modalities. Experimental results on benchmark multi-modal ReID datasets RGBNT201, Market1501-MM, RGBN300, and RGBNT100 validate the effectiveness of the proposed method. The codes can be found at https://github.com/ziwang1121/HTT.

Non-planar graphene directly synthesized on intracavity optical microresonators for GHz repetition rate mode-locked lasers

Generation of high-speed laser pulses is essential for sustaining today’s global, hyper-connected society. One approach for achieving high spectral and temporal purity is to combine optical nonlinear materials with spectral filtering devices. In this work, a graphene-coated microresonator integrates a nonlinear material and a spectral filtering platform into a single device, creating a tunable GHz repetition rate mode-locked fiber laser. The graphene is directly synthesized on the non-planar surface of microresonator, resulting in a uniform, conformal coating with minimal optical loss in the device. The whispering gallery modes of the resonator filter the propagating modes, and the remaining modes from the interaction with graphene lock their relative phases to form short pulses at an elevated repetition rate relying on inter-modal spectral distance. Additionally, by leveraging the photo-thermal effect, all-optical tuning of the repetition rate is demonstrated. With optimized device parameters, repetition rates of 150 GHz and tuning of 6.1 GHz are achieved.

Prediction of the Occurrence Probability of Freak Waves in Unidirectional Sea State Using Deep Learning

Predicting extreme waves can foresee the hydrodynamic environment of marine engineering, critical for avoiding disaster risks. Till now, there are barely any available models that can rapidly and accurately predict the occurrence probability of freak waves in a given state. This paper develops a trained model based on the Back Propagation (BP) neural network, with wave parameters of unidirectional sea state fed into the model, such as significant wave height, wave period, spectral type, and the intermodal distance of the peak frequencies. A rapid and accurate model optimized for predicting the occurrence probability of freak waves in a unidirectional sea state, from unimodal to bimodal configuration, is achieved by iterating to reduce accumulation errors. Compared to the regression and least-squares boosting trees, the optimized model performs much better in accurately predicting the occurrence probability of freak waves. Irrespective of whether in unimodal or bimodal sea state, this optimized model is competitive in calculation accuracy compared to theoretical models such as Rayleigh prediction and MER prediction, improved by at least 41%. The established model based on the BP neural network can quickly predict the threshold of freak waves in a given sea state, guiding practical engineering applications.

Magnetic resonance imaging-based bone imaging of the lower limb: Strategies for generating high-resolution synthetic computed tomography.

This study aims at assessing approaches for generating high-resolution magnetic resonance imaging- (MRI-) based synthetic computed tomography (sCT) images suitable for orthopedic care using a deep learning model trained on low-resolution computed tomography(CT) data. To that end, paired MRI and CT data of three anatomical regions were used: high-resolution knee and ankle data, and low-resolution hip data. Four experiments were conducted to investigate the impact of low-resolution training CT data on sCT generation and to find ways to train models on low-resolution data while providing high-resolution sCT images. Experiments included resampling of the training data or augmentation of the low-resolution data with high-resolution data. Training sCT generation models using low-resolution CT data resulted in blurry sCT images. By resampling the MRI/CT pairs before the training, models generated sharper images, presumably through an increase in the MRI/CT mutual information. Alternatively, augmenting the low-resolution with high-resolution data improved sCT in terms of mean absolute error proportionally to the amount of high-resolution data. Overall, the morphological accuracy was satisfactory as assessed by an average intermodal distance between joint centers ranging from 0.7 to 1.2 mm and by an average intermodal root-mean-squared distances between bone surfaces under 0.7 mm. Average dice scores ranged from 79.8% to 87.3% for bony structures. To conclude, this paper proposed approaches to generate high-resolution sCT suitable for orthopedic care using low-resolution data. This can generalize the use of sCT for imaging the musculoskeletal system, paving the way for an MR-only imaging with simplified logistics and no ionizing radiation.

Multi-Trait Selection of Quinoa Ideotypes at Different Levels of Cutting and Spacing

Climate change has affected the food supply chain and raised serious food concerns for humans and animals worldwide. The present investigation aimed to assess the effect of environmental factors along with three different levels of cutting (i.e., cutting 1, 2, and 3 at the vegetative, budding, and flowering stages, respectively) and spacing (i.e., 21, 23, and 26 cm) on quinoa biomass and quality to select the most suitable accessions. This experiment was repeated for two years using a split–split plot experimental design. The cutting × genotype × year and cutting × space × genotype interactions were significant for most quinoa morphological traits (except for leaf area and intermodal distance), where the maximum growth in number of leaves/plant (NoL), plant height (PH), fresh weight (FW), number of branches/plant (Br), and dry weight (DW) were observed during the second growing season. Cutting and spacing levels also showed significant effects on morphological and quality traits of quinoa. Among the different levels of cutting and spacing, cutting level 3 and spacing level 2 were more effective across both years at gaining maximum biomass and quality traits such as crude fat (CF) and crude protein (CP). According to the MGIDI, only two accessions (R3 and R9) fared better in both growing seasons, and selected accessions had positive morphological and quality traits. There were moderately significant negative correlations between PH, NoL, LA, FW, and DW and anti-quality traits such as neutral detergent fiber (NDF) and acid detergent fiber (ADF), indicating that an increase in biomass decreased the concentrations of ADF and NDF in both stem and leaves. A comparison with oat accessions (G3 and G7) revealed that quinoa has higher CP and CF and lower NDF than oats in both stems and leaves (except for ADF). In conclusion, the combination of cutting level 3 and spacing level 2 (23 cm) is more suitable to obtain high-quality quinoa forage with maximum biomass production. Furthermore, the MGIDI is a useful tool for breeders to select genotypes based on their mean performance, stability, and desired traits.

ESTIMATION OF GENE ACTIONFOR THE SELECTION OF SUPERIOR PARENTS AND THEIR CROSS COMBINATIONSFOR YIELD AND FIBER ASSOCIATED ATTRIBUTES IN AMERICAN COTTON (GOSSYPIUM HIRSUTUM L.)

Cotton is very important crop regarding the global trade. It is grown for its fiber and edible oil in Pakistan. It contributes 1.5 percent to GDP and 69 percent in foreign exchange. There is need to enhance the yield per unit area of cotton by developing high yielding and stress tolerant varieties. In breeding program the parents and their crosses are selected on the basis of their combining ability. Combining ability analysis is performed to identify the general and specific combiner for yield attributed traits. This research was performed for evaluation of four lines as female parents (C-1, CIM-616, TIPO-1 and CYTO-608) and three testers as male parents (NIAB-1048, CYTO-124 and CIM-600) of cotton (Gossypium hirsutum L.). The traits such as plant height, first fruiting node, seed cotton yield, monopodial branches, sympodial branches, ginning out turn percentage, number of bolls per plant, height to node ratio and cotton seed yield was tested. The general combining ability of parental lines and specific combining ability of the F1 cross will be determined for yield related traits. The genotypes with good general combining ability and specific combining ability further exploited for hybrid/variety development programs. For most of the traits like number of monopods per plant, boll weight per plant, seed cotton yield, number of nodes per plant, 1st fruiting node, intermodal distance, ginning out turn percentage, cotton seed yield, seed index, plant height, fiber strength, fiber length, fiber uniformity and fiber fineness value had more value for dominance variance. The higher effects of GCA and SCA indicated that there is the role of additive and non-additive gene action for inheritance of traits.

Spatial evolution model of port group hinterland from the perspective of intermodal transport

ABSTRACT The rapid development of the intermodal system has led to the intensification of the hinterland competition within the port group, and the spatial pattern of the hinterland has become discontinuous. Based on geographic information system technology, a spatial interaction model, in which the intermodal cost distance is computed by integrating the raster analysis method and network method, is developed to facilitate the examination of the spatial evolution process of the port group intermodal hinterland. Considering the example of the Gulf of Guinea port group in West Africa, the spatial evolution process of its five ports is simulated in three scenarios. The results indicate that intermodal transport drives the hinterland’s discontinuous development, and the direction and layout of the intermodal corridors significantly impact the hinterland competition of the port group. In most cases, the intermodal corridors can help realize connected ports to enhance the hinterland’s competitive advantage within the port group. However, adjacent ports may also benefit from this aspect under certain conditions, which implies the importance of port cooperation in planning collection and distribution corridors. The model and findings can theoretically support the decision-making of port investors and operators.

Statistics of long-crested extreme waves in single and mixed sea states

Most of the studies on extreme waves are focused on the systems with single-peak wave spectra. However, according to the statistics of occurrence, the bimodal spectral system is also frequent in real sea conditions. In order to summarize the statistics of extreme waves, irregular wave trains under single-peak and bimodal spectra for long durations are simulated in this paper, based on a two-dimensional High Order Spectral (HOS) numerical wave tank. A large number of configurations have been tested under unimodal and bimodal spectra. The investigation on the wave trains under single-peak spectrum indicates that although in conditions often referred as deep water (kph > π), the relative water depth has a significant influence on the probabilities of occurrence of extreme waves. A detailed analysis of the combined effect of Benjamin-Feir Index (BFI) and relative water depth is provided. However, the situation is more complex in real sea conditions, which may exhibit multimodal spectra. We focus in this study on long-crested bimodal spectra characterized by the same significant wave height Hs and mean zero-crossing period Tz of the sea states as the single-peak spectrum. The wave conditions under bimodal spectrum present milder extreme wave statistics than those under single-peak spectrum. In addition, mixed ocean systems with equivalent energy distribution (i.e., Sea-Swell Energy Ratio (SSER) is close to 1.0) and larger separation between partitions (i.e., Intermodal Distance (ID) > 0.10) are the less prominent to extreme waves appearance. The comparison of the mixed sea states and the corresponding single independent systems demonstrates that the complexity of the underlying physics of a given sea state (for instance the presence of modulational instability or other nonlinear process) cannot be deduced by an analysis limited to the statistical content of the combined sea state. The wave energy being distributed among frequencies plays a major role. Additionally, Gram-Charlier distribution can accurately predict the probability of large waves (1.5 < H/Hs < 2.0) compared to the MER distribution, but it underestimates the statistics of the wave height distribution when H/Hs is larger than 2.0 for both single-peak and bimodal states.

Interactive Effects of Fertigation and Varieties on Pant Growth Attributes and Yield of Soilless Cucumbers

A study was undertaken to monitor the plant growth attributes and yield of soilless cucumbers (V1: Kafka, V2: Multistar and V3: PBRK-4) in relation to differential fertigation scenarios (F1: 100%, F2: 85% and F3: 70% of nutrient solution under optimal microclimatic conditions) during two successive growing seasons of 2016-17 (Season 1: September 2016 to January 2017 and Season 2: February to May 2017). The yield of cucumbers was significantly affected by fertigation treatments in interaction with crop varieties. The plant growth attributes viz. plant height, number of nodes per plant, leaf area index (LAI), plant intermodal distance, fruit water content (FWC) and others in association affected the yield. Irrespective of the growing seasons, the average fruit yield was recorded to be in the range of 2.5-3.5 kg per plant with having highest and lowest values under F1V2 and F3V3 respectively, in relation to plant height, number of nodes per plant and inter-nodal distance per plant per variety. Among crop varieties, the highest yield was recorded under V2, chiefly due to larger intermodal distance and FWC for same average number of nodes per plant and plant height. Thus, monitoring plant growth attributes is essentially required for better understanding of their relationship with the fruit yield.

Effect of fertigation on different cultivars and spacing in parthenocarpic cucumber (Cucumis sativus L.) under protected condition

An experiment was conducted on two consecutive years during 2016–17 & 2017–18 to Effect of fertigation on different cultivars and spacing in parthenocaepic cucumber (Cucumis sativus L.) under protected condition at Krishi Vigyan Kendra, Raisen (M.P). The whole experiment was arranged 12 treatments consisting of three cultivars V1- Kafka, V2 - Kian and V3 -Hilton along with two levels of spacing S1- 50 × 30 cm, S2 - 50 x 50 cm and 2 levels of fertigation F1 -once in a week, F2- once in a 10th days interval (recommended dose of N P K-8:3.5:9 kg/500m2. The experiment was laid out in factorial completely randomized design with three replications. The results showed that all vegetative characters under study were significantly influenced by various cultivars along with levels of spacing and time of fertigation. The effects of cultivars, spacing and time of fertigation were significant for most of vegetative characteristics except weight fruit1. The variety Kafka was found to be significantly superior in respect of yield and yield attributing traits having maximum values of 2.78 kg and 14.92 kg yield per vine and per square meter, respectively. The characters like vine length, intermodal distance, leaf area, days to flower bud initiation, fruit set (%), fruit drop (%), no. of fruit per vine, fruit length, fruit width, yield per vine and yield per m2 were significantly influenced by interaction effect of variety, spacing and time of fertigation. The treatment of V1S1F1 registered significantly highest vegetative and yield attributing characters. However, treatment combination of V3S2F2 registered lowest yield per vine and per square meter (1.43 & 5.73kg, respectively).

Vulnerability effects of passengers' intermodal transfer distance preference and subway expansion on complementary urban public transportation systems

The vulnerability studies on urban public transportation systems have attracted growing attentions in recent years, due to their important role in the economy development of a city and the well-beings of its citizens. This paper proposes a vulnerability model of complementary urban public transportation systems (CUPTSs) composed of bus systems and subway systems, with the consideration of passengers’ intermodal transfer distance preference (PITDP) to capture different levels of complementary strength between the two systems. Based on the model, this paper further introduces a CUPTSs-aimed vulnerability analysis method from two specific aspects: (a) vulnerability effects of different PITDP values, which facilitate the design of policies to change PITDP to reduce system vulnerability; (b) vulnerability effects of different subway expansion plans, which facilitate the vulnerability investigation of current expansion plan and the identification of the optimal expansion plan from the system vulnerability perspective. The proposed CUPTSs-aimed vulnerability analysis method is applied to investigate the complementary bus and subway systems in the city of Wuhan, China. The insights from this study are helpful to analyze other CUPTSs for valuable planning suggestions from the vulnerability perspective.

Efficacy of boron and salicylic acid on quality production of sim carnation (Dianthus caryophyllus)

Flower production is an increasing activity of world’s agriculture. Carnation is one of the most important cut flower of the world which ranks only next to rose. It has been extensively cultivated to be used as cut flower because of its excellent keeping quality. The present study is therefore designed with the aim of improving the quality of Sim carnation by applying Boron (0, 5ppm, 10ppm, 15ppm, 20ppm) and Salicylic acid (0,1mM, 2mM, 3mM and 4mM). Different growth and flowering traits which include plant height, number of leaf pairs, intermodal distance, leaf area, leaf chlorophyll content, days to flower emergence, number of flowers/plant, diameter of flower, stalk length and girth, duration of flowering and dry matter content of plants was studied in the experiment. The results reveal that foliar application of boron and salicylic acid has pronounced effect on growth and quality parameters of carnation. Among all the treatment SA @ 3mM exhibited best results and among doses of boron @ 15ppm showed good results.

Co-existence of wind seas and swells along the west coast of India during non-monsoon season

Abstract. An attempt has been made to understand the co-existence of wind seas and swells along the west coast of India during non-monsoon season. Wave data were collected in different years during non-monsoon season (off Goa during May 2005, off Ratnagiri during January–February 2008 and off Dwarka during December 2007–January 2008), which is fairly a calm weather season along these regions. Diurnal variation in wave parameters is noticeable along the central west coast of India (off Goa and Ratnagiri), which is due to the interaction of multidirectional waves (both wind seas and swells) of varying magnitudes and frequencies. Swells are predominantly mature (91%) and old (88%) during late pre-monsoon and post-monsoon seasons, respectively. Sea Swell Energy Ratio quantifies wind sea, swell and mixed seas prevailing in these regions during non-monsoon season. Intermodal distance (ID) between the energy peaks is moderately separated during non-monsoon season, whereas, during the shamal events, energy peaks are very close to each other (ID ∼ 0). However, pure wind seas (ID ∼ 1) are weakly present and found to co-exist with the swells almost all the time during non-monsoon season. Wind sea growth has been found while the swell propagates opposite to the direction of the wind and wind sea. Wind seas have minimum angular spreads in multimodal state. Under low winds, the interaction between wind sea and swell dominates and thereby the multimodal state reduces to unimodal state. The fetch available for the evolution of the wind sea spectrum has been estimated, and it is found to be less than 150 km. For the fetch limited condition, a non-dimensional empirical relation has been derived relating the significant wind sea height in terms of wind speed and peak wind sea period, and this relation fits for the west coast of India.

Effect of different doses of gamma radiation on growth parameters of Mulberry (Morus) variety Kosen

The present study was carried out to evaluate the effect of different doses of gamma radiations(1kR-10kR from co60)on different growth parameters of mulberry variety Kosen.Overall results revealed that a declined trend in all the growth parameters i.e. sprouting (83.66%-18.66%), rooting (77.96%-19.59%), height of the plant (105.00 cm-58.03 cm), number of the branches (7.73-4.23), intermodal distance (3.76 cm-3.94 cm), petiole length (2.89 cm-2.59 cm) and pollen fertility (77.93%-40.66%) were recorded and showed a deleterious effect. But the response of growth parameters against different doses showed variant behaviour in case of rooting as constant declined trend was not observed. Similarly fluctuating state has been found in other growth parameters also.

Phenotypic Divergence in Mulberry (Morus spp.) Germplasm Collections

To improve mulberry foliage productivity, identification of suitable genes related to agronomically important traits in the available mulberry germplasm is essential. Twenty-five indigenous mulberry accessions representing five different species of Morus from seven diverse parts of the India were evaluated via principal component analysis (PCA) for 22 aboveground and underground morphometric traits and silkworm cocoon yield during 2002–2005 in the agro-climates of Berhampore, West Bengal, India. Significant differences among germplasm accessions were observed for all 22 traits and cocoon yield. Six principal components were identified, which explained >88% of total variation. Though 18 major variables were included in the principal components, longest shoot length, leaf area, intermodal distance, green and dry leaf weight, lamina length, lamina weight, root volume, and fresh and dry root weight were recognized as important variables that had direct effect on silkworm cocoon yield. These 10 variables appeared to be minimal traits for quick selection of mulberry progenies in breeding programs. Four distinct groups of accessions obtained after a cluster analysis were partly associated with their places of origin. In addition, the study highlighted a number of distinctive morphological characters in many of the accessions studied. The identified 10 minimum morphological descriptors were expected to be highly discriminating, thus they would help in quick characterization of mulberry germplasm. In addition, the distantly related germplasm were identified on the basis of cluster analysis and can be utilized in targeted mulberry improvement programs.

Mast cells in rat dermis and jejunal lamina propria show a five-fold difference in unit granule volume

The cytoplasmic granules of mast cells have a periodic multimodal size distribution in which the volumes of individual granules are integral multiples of the intermodal distance, a volume defined as the "unit granule" or v1. In this study, we used two 3-month-old male rats to analyze two classical mast cell subpopulations, dermal "connective tissue-type mast cells" and jejunal lamina propria "mucosal mast cells", for the morphometric characteristics of their cytoplasmic granules. Both v1 and the mean volume of individual cytoplasmic granules were much smaller in dermal than in jejunal mast cells (ratios of 1:5.5 and 1:4.2, respectively), but dermal mast cells contained 150% more granules per cell than did jejunal mast cells. The two types of mast cells did not differ significantly in total cell volume, nucleus volume, aggregate volume of cytoplasmic granules per cell or numbers of unit granules comprising a granule of mean volume. These findings add unit granule volume to the list of phenotypic characteristics which express significant variation in anatomically distinct populations of mast cells.