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Although suppliers can sell their goods on e-retailers&rsquo, e-platforms through either a wholesale or agency contract, suppliers that produce complementary goods and have different channel roles have been confused as to how to choose an optimal distribution contract. This paper aims to study this problem by considering the combined impacts of suppliers&rsquo, channel roles, e-retailer&rsquo, s referral fees, goods&rsquo, differences in the level of complementarity and goods&rsquo, differences in potential demand. Our results show that, regardless of one supplier&rsquo, s distribution contract choice, the other supplier always prefers agency contract, which is independent of two suppliers&rsquo, channel roles, the e-retailer&rsquo, s referral fees, two goods&rsquo, differences in the level of complementarity and two goods&rsquo, differences in the potential demand. Moreover, when two suppliers use different distribution contracts to sell goods with different levels of complementarity on the same e-retailer&rsquo, s e-platform, low-complementarity goods have a larger optimal retail price only if the two goods&rsquo, differences in the level of complementarity are sufficiently high, and the supplier can obtain more profits by producing low-complementarity goods regardless of the supplier&rsquo, s distribution contract and channel role.

Currently, manufacturers can sell products on e-tailers’ online platforms through agency sales format or reselling format. However, how to choose the best sales formats has puzzled competing manufacturers in practice. The main purpose of this paper is to answer this problem by considering the combined effects of manufacturers’ leader-follower relationships, the e-tailer’s referral fees, the difference in products’ substitutable degrees and the difference in products’ market bases. Our results show that, if demand functions are linearly price-dependent, when two manufacturers sell substitutable products on the same e-tailer’s online platform, the e-tailer’s best action is always to let both manufacturers adopt reselling format; regardless of one manufacturer’s sales format, the other manufacturer always prefers agency sales format, which are independent of the e-tailer’s referral fees, the difference in two products’ substitutable degrees and the difference in two products’ market bases. Whether demand functions are linear or nonlinear in retail prices, the e-tailer’s best action is to let both manufacturers whose products are symmetric adopt reselling format; no matter what sales format one manufacturer adopts, the other manufacturer always prefers agency sales format, which are independent of the two manufacturers’ leader-follower relationships. Moreover, if two manufacturers adopt same sales format to sell symmetric products, leader role enables a manufacturer to charge higher optimal wholesale/retail price when demand functions are linear in retail prices, but the two products have equal optimal wholesale/retail prices regardless of the two manufacturers’ leader-follower relationships when demand functions are nonlinear in retail prices.

The emergence of transformer models like BERT means that deep learning language models can achieve reasonably good performance in document classification with few labelled instances. However, there is a lack of evidence for the utility of applying BERT-like models on long document classification in few-shot scenarios. This paper introduces a long-text-specific model—the Hierarchical BERT Model (HBM)—that learns sentence-level features of a document and works well in few-shot scenarios. Evaluation experiments demonstrate that HBM can, with only 50 to 200 labelled instances, achieve higher document classification performance than existing state-of-the-art methods, especially when documents are long. Also, as an extra benefit of HBM, the salient sentences identified by a HBM are useful as explanations for document classifications. A user study demonstrates that highlighting these salient sentences is an effective way to speed up the document annotation required in interactive machine learning approaches like active learning.

Background: Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancer and affects a large number of individuals. The pathogenesis of PTC has not been completely elucidated thus far. Metabolic reprogramming is a common feature in tumours. Our previous research revealed the reprogramming of lipid metabolism in PTC. Further studies on lipid metabolism reprogramming may help elucidate the pathogenesis of PTC. Methods: Clinical samples of PTC and para-tumour tissue were analysed using lipidomic, proteomic, and metabolomic approaches. A multi-omics integrative strategy was adopted to identify the important pathways in PTC. The findings were further confirmed using western blotting, tissue microarray, and bioinformatics. Findings: The differentially expressed substances included 146 lipids, 2975 proteins, and 217 metabolites in PTC samples. Multi-omics data and the results of integrated analysis revealed that the three steps of fatty acid metabolism (hydrolysis, transportation, and oxidation) were significantly enhanced in PTC. The key enzymes in the three steps, namely LPL, FATP2, and CPT1A, respectively, were overexpressed. Moreover, their expression was strongly associated with the TNM stage, lymph node metastasis, and PTC prognosis. In addition, the levels of several types of phospholipids and sphingolipids increased significantly in PTC. Interpretation: Our data suggested that enhanced fatty acid metabolism supplied additional energy and substrates for tumour growth, invasion, and metastasis in PTC. This may help elucidate the mechanism underlying PTC pathogenesis and identify the potential therapeutic targets for PTC. Funding Information: Work in the authors' laboratory is supported by grants from National Natural Science Foundation of China (No. 81702647, NO. 81972819), Taishan Scholar Foundation of Shandong Province (No. tspd20181201), Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong, Natural Science Foundation of Shandong Province (No. ZR201702190483, No. ZR2020YQ57), Key Technology Research and Development Program of Shandong (No. 2016GSF201161). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This prospective study was approved by the institutional ethical committee of Qilu Hospital of Shandong University, Shandong Province, China. All the specimens were collected in the Qilu Hospital of Shandong University. The participants provided written informed consent for the use of thyroid tissue specimens for research.

Background The purpose of this study was to investigate the value of wavelet-transformed radiomic MRI in predicting the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) for patients with locally advanced breast cancer (LABC). Methods Fifty-five female patients with LABC who underwent contrast-enhanced MRI (CE-MRI) examination prior to NAC were collected for the retrospective study. According to the pathological assessment after NAC, patient responses to NAC were categorized into pCR and non-pCR. Three groups of radiomic textures were calculated in the segmented lesions, including (1) volumetric textures, (2) peripheral textures, and (3) wavelet-transformed textures. Six models for the prediction of pCR were Model I: group (1), Model II: group (1) + (2), Model III: group (3), Model IV: group (1) + (3), Model V: group (2) + (3), and Model VI: group (1) + (2) + (3). The performance of predicting models was compared using the area under the receiver operating characteristic (ROC) curves (AUC). Results The AUCs of the six models for the prediction of pCR were 0.816 ± 0.033 (Model I), 0.823 ± 0.020 (Model II), 0.888 ± 0.025 (Model III), 0.876 ± 0.015 (Model IV), 0.885 ± 0.030 (Model V), and 0.874 ± 0.019 (Model VI). The performance of four models with wavelet-transformed textures (Models III, IV, V, and VI) was significantly better than those without wavelet-transformed textures (Model I and II). In addition, the inclusion of volumetric textures or peripheral textures or both did not result in any improvements in performance. Conclusions Wavelet-transformed textures outperformed volumetric and/or peripheral textures in the radiomic MRI prediction of pCR to NAC for patients with LABC, which can potentially serve as a surrogate biomarker for the prediction of the response of LABC to NAC.

Spacecraft navigation in space requires high real-time. Towards this end, when using pulsar navigation, it is necessary to reduce the pulse profile construction time. In this paper, the method of constructing a pulse profile based on compressed sensing (CS) is improved from two aspects: Double Redundant Dictionary (DRD) search method and Same-Scale L1-Norm (SSLN) cost function. The method of calculating the optimal dimension of the DRD is given. A random observation matrix is designed. We provide both analytical and experimental evidence that supports our method. The proposed method is compared with the traditional methods of Amplitude Search (AS) and Hadamard Observation Matrix (HOM) in terms of computational complexity. Simulation using NASA data is consistent with the quantitative analysis. It is illustrated that DRD and SSLN can serve as an effective method with the resulting running time considerably less than that in AS or HOM. The proposed method gets a considerable reduction in pulse profile construction time.

// Jinghui Lu 1 , Sanyuan Hu 1 , Paolo Miccoli 2 , Qingdong Zeng 1 , Shaozhuang Liu 1 , Lin Ran 3 , Chunxiao Hu 1 1 Department of General Surgery, Qilu Hospital of Shandong University, Jinan 250012, P.R. China 2 Department of General Surgery, University of Pisa, Pisa 56126, Italy 3 Medical College of Shandong University, Jinan 250012, P.R. China Correspondence to: Sanyuan Hu, email: husanyuan1962@hotmail.com Keywords: papillary thyroid microcarcinoma, metabolomics, diagnosis, NMR Received: August 20, 2016 Accepted: October 22, 2016 Published: November 07, 2016 ABSTRACT Papillary thyroid microcarcinoma (PTMC) is a subtype of papillary thyroid carcinoma (PTC). Because its diameter is less than 10 mm, diagnosing it accurately is difficult with traditional methods such as image examinations and FNA (Fine Needle Aspiration). Investigating the metabolic changes induced by PTMC may enhance the understanding of its pathogenesis and provide important information for a new diagnosis method and treatment plan. In this study, high resolution magic angle spin (HRMAS) spectroscopy and 1 H-nuclear magnetic resonance ( 1 H-NMR) spectroscopy were used to screen metabolic changes in thyroid tissues and plasma from PTMC patients respectively. The results revealed reduced levels of fatty acids and elevated levels of several amino acids (phenylalanine, tyrosine, lactate, serine, cystine, lysine, glutamine/glutamate, taurine, leucine, alanine, isoleucine and valine) in thyroid tissues, as well as reduced levels of amino acids such as valine, tyrosine, proline, lysine, leucine and elevated levels of glucose, mannose, pyruvate and 3-hydroxybutyrate in plasma, are involved in the metabolic alterations in PTMC. In addition, a receiver operating characteristic (ROC) curve model for PTMC prediction was able to classify cases with good sensitivity and specificity using 9 significant changed metabolites in plasma. This work illustrates that the NMR-based metabolomics approach is capable of providing more sensitive diagnostic results and more systematic therapeutic information for PTMC.

Previous studies have demonstrated that microRNA (miR)-760 serves an important role in various cancer types. However, to the best of our knowledge, its role in hepatocellular carcinoma (HCC) has not been fully elucidated. The current study investigated the prognostic role of miR-760 in HCC by using the Kaplan-Meier plotter database. The current data indicated that low expression of miR-760 was associated with higher overall survival (OS) for all patients with HCC from both the RNA-seq [hazard ratio (HR)=2.04; 95% confidence interval (CI)=1.44–2.89; P=4.9×10−5] and the non-commercial spotted microarray (HR=1.71; CI=1.05–2.76; P=0.028). In the RNA-seq platform, a lower expression of miR-760 was strongly associated with improved OS in male patients with HCC, but not in female patients with HCC. Additionally, low expression of miR-760 was associated with improved OS in patients with stage I, II and III HCC, and was associated with improved OS in Asian and Caucasian patients. The current results indicated that miR-760 serves as an oncogene for HCC and high expression of miR-760 is significantly associated with tumor progression and poor prognosis in patients with HCC.

This paper investigates the optimal strategies of information sharing and sales patterns in a supply chain with one supplier and one e-tailer who operates an e-platform. The supplier sells green products on the e-tailer’s e-platform either only through reseller pattern or through both reseller and agency sales patterns, and the e-tailer possesses private demand information and chooses whether to share it with the supplier. Our results illustrate that, for given information sharing strategies, the supplier adopts both reseller and agency sales patterns when the production costs are relatively low, but as the production costs increase further and become relatively large, the supplier adopts only reseller pattern. We also find that whatever sales pattern the supplier adopts, whether information sharing benefits the e-tailer depends on some supply chain parameters’ values. Moreover, regardless of the supplier’s sales patterns and e-tailer’s information sharing strategies, the higher the consumers sensitivity towards product’s green level is, the higher channel members’ expected profits and product’s prices and green level are.

Purpose This paper examines the role of export intermediaries in the internationalization of small and medium sized companies in Finland. The empirical study focuses on small Finnish food companies that export to German and Chinese markets. Design/methodology/approach The research method of this study is qualitative. Data is collected through semi-structured interviews with six respondents presenting exporting companies and export consultants. Findings The paper provides an empirical contribution to the food internationalization debate. First, the paper discusses the definitions of export intermediaries and their role in export based on the literature. Second, by examining how Finnish food companies experience the role of export intermediaries, the paper contributes to the current discussion on internationalization modes. The empirical results highlight that export companies need transaction-creating services from intermediaries especially when entering physically and culturally distant markets like China. Research limitations/implications Limitations of the research generally relate to the use of a small case sample. Practical implications The paper holds a number of relevant insights for food companies seeking to enter to German and Chinese markets. Identifying the export services needed by small food companies might help export intermediaries and public policy agencies to better focus their supporting initiatives. Originality/value The findings add to the current body of knowledge on the key influence on internationalization modes within the food sector.

A good understanding of the fading characteristics in high speed railway environment is essential for the design of a high reliable railway wireless network. In this paper, measurements have been taken in both high speed viaduct and terrain cutting scenarios using track side base stations (BSs) of the railway wireless network in China. The measurement sites have been chosen with special care; thus the whole measured route can be characterized either by viaduct or terrain cutting. Kolmogorov-Smirnov (K-S) test has been first introduced in the statistical analysis to find out which is the most appropriate model for the small scale fading envelope. Though both Rice and Nakagami distributions provide a good fit to the first-order envelope data in both scenarios, only the Rice model generally fits the second-order statistics data accurately. For the viaduct scenario, higher RiceKfactor can be observed. The change tendency of theKfactor as a function of distance in the two scenarios is completely different. It can be concluded that the over bridges which span the railway tracks in terrain cutting scenario would affect the RiceKvalue severely.

To establish effective information exchange among applications in a distributed environment, participants not only share their functions and service interfaces, but often exchange data models. This paper proposes the use of ontologies to represent data models thus allowing applications to locate and integrate these models. A reference ontology based approach for service oriented ontology management is introduced. Specifically, a domain-specific reference ontology for use in the evaluation of a practical case is developed. To validate and evaluate the approach, a prototype system is developed to provide ontology deploying, browsing and mapping operations based on a service-oriented system. Experiments provide promising results that are consistent with the original ideas of managing ontologies and optimizing ontology mappings to facilitate data interoperability in a distributed environment.

A high performance wireless network is essential for for the railway communication and control systems. Research on the fading characteristics in railway environment is of great importance for the design of the railway wireless network. In this paper, measurements are taken in railway terrain cuttings area using track side base stations of the GSM-R network. The fitted path loss model, shadow fading, and dynamaic range of the small scale fading are obtained and compared to the results of viaduct scenario. The propagation environment of the terrain cuttings turns out to be worse than the viaduct area. The path loss exponent is found to be 4.3. The shadow loss can be reasonably described by a log-normal distribution. It is also found that the bridges over the cuttings can cause extra loss of about 5 dB. The dynamaic range of the small scale fading is from 27 dB to 40 dB with a mean value of about 33 dB.

In order to ensure the safety of the running train, wireless communication system for train communications and control must provide a network with high quality of service (QoS). And wireless network design will directly influence the performance of the whole network. In the process of the network design, choosing the appropriate prediction model, predicting the coverage, and determining base station site, are all related to the local environment. To improve the quality of the railway wireless network, the base station site selection for railway wireless network is optimized based on GIS (geographic information system). A new propagation model selection method based on GIS is also proposed. With the help of GIS, the accuracy of the prediction model and the efficiency of the base station site selection can be greatly improved.

A network with high quality of service (QoS) is required for railway wireless communication and control systems. Research on radio-wave propagation in railway environment has great significance for the design and optimization of the railway wireless network. In this paper, measurements are taken in railway viaduct area using track side base stations of the GSM-R network. Comparison between the measured path loss values and the estimated values by a few prediction models shows a large deviation. Thus a new path loss prediction model for viaduct area is derived from statistical analysis of the measurement results in this paper. The novel proposed model has proven to be accurate for the planning of the railway wireless network.

We use reflectivity changes at an interface functionalized with molecular probes to detect label-free biomolecular binding. Attachment of the target molecules to the surface alters the effective thickness of an antireflective coating formed by thermal oxidation of a silicon wafer to remove destructive interference of the reflected waves. The thermal oxide thickness is adjusted for precise interference using electrostatic layer-by-layer self-assembly of polyelectrolytes to which the molecular probes can be bound covalently. Reflectivity increases of over a factor of 100 are observed for binding of 2.5 nm of streptavidin to biotinylated polyelectrolytes, considerably more sensitive than surface plasmon resonance detection. Theoretical modeling is in agreement with the experimentally observed reflectivity increases and suggests the sensitivity is at present limited by the roughness of the oxide.