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PurposeThe present study seeks to identify the salient mobile shopping (m-shopping) service quality dimensions as perceived by mobile shoppers (m-shoppers) and examines the linkages between the derived m-shopping service quality dimensions, customer trust and customer loyalty.Design/methodology/approachThe research instrument is developed based upon the mostly validated measures of prior studies. A pretest of the questionnaire is conducted to assess the content validity of the measurement scales. An online survey is used to collect the required data. We employ structural equation modeling (SEM) to analyze data collected from 286 m-shoppers.FindingsWe identify five key m-shopping service quality dimensions: responsiveness, personalization, ease of use, aesthetics and perceived risk based on an extensive review of relevant literature. The SEM results show that all the five m-shopping service quality dimensions significantly impact, directly and/or indirectly, customer loyalty. Moreover, the results show that trust plays a partial mediating role in the effects of responsiveness and personalization on loyalty; a full mediating role in the effects of aesthetics and perceived risk on loyalty and no mediating role in the effect of ease of use on loyalty.Practical implicationsMobile retailers (m-retailers) can use the quality measurement tool developed in this study to detect service quality weaknesses and strengths. Based on their quality assessment, m-retailers can effectively allocate corporate resources to the important service quality attributes uncovered by this study, thereby improving their overall service quality performance and in turn expanding their loyal customer base.Originality/valuePrior studies have demonstrated that service quality and customer trust play a pivotal role in enhancing customer loyalty in both offline and online settings. Unfortunately, no research has empirically examined the relationships between service quality dimensions, trust and loyalty in the context of m-shopping. Therefore, a major contribution of this study is to address this research gap and add knowledge to the limited body of post-adoption m-shopping research.

Publicly available example datasets converted to BIDS to exemplify ASL cases.

To mitigate the climate change-induced water shortage and realize the sustainable development of agriculture, drip irrigation, a more efficient water-saving irrigation method, has been intensively implemented in most arid agricultural regions in the world. However, compared to traditional border irrigation, how drip irrigation affects the biophysical conditions in the cropland and how crops physiologically respond to changes in biophysical conditions in terms of water, heat and carbon exchange remain largely unknown. In view of the above situation, to reveal the mechanism of drip irrigation in improving spring wheat water productivity, paired field experiments based on drip irrigation and border irrigation were conducted to extensively monitor water and heat fluxes at a typical spring wheat field (Triticum aestivum L.) in Northwest China during 2017–2020. The results showed that drip irrigation improved yield by 10.3 % and crop water productivity (i.e., yield-to-evapotranspiration-ratio) by 15.6 %, but reduced LAI by 16.9 % in contrast with border irrigation. Under drip irrigation, the lateral development of spring wheat roots was promoted by higher soil temperature combined with frequent dry-wet alternation in the shallow soil layer (0–20 cm), which was the basis for efficient absorption of water and fertilizer, as well as efficient formation of photosynthate. Meanwhile, drip irrigation increased net radiation and decreased latent heat flux by inhibiting leaf growth, thereby increased sensible heat, causing a higher soil temperature (+1.10 ℃) and canopy temperature (+1.11 ℃). Further analysis proved that soil temperature was the key factor affecting yield formation. Based on the above conditions, the decrease in leaf distribution coefficient (−0.030) led to the decrease in evapotranspiration (−5.7 %) and the increase in ear distribution coefficient (+0.029). Therefore, drip irrigation emphasized the role of soil moisture in the soil-plant-atmosphere continuum, enhanced crop activity by increasing field temperature, especially soil temperature, and finally improved yield and water productivity via carbon reallocation. The study revealed the mechanism of drip irrigation for improving spring wheat yield, and would contribute to improving Earth system models in representing agricultural cropland ecosystems with drip irrigation and predicting the subsequent biophysical and biogeochemical feedbacks to climate change.

Endophytic fungi possess favorable effects on their host plants, including disease-resistance improvement, secondary metabolite induction, and growth promotion. It is therefore a promising and sustainable strategy to utilize endophytic fungi for the quality improvement of medicinal herbs or important crops. In our study, a collection of 277 strains of endophytic fungi were isolated from Anoectochilus and Ludisia orchids. Two strains J162 and J211 can be symbiotically cocultured with the tissue culture seedlings of Anoectochilus roxburghii, a popular medicinal and edible plant in southern China. Both strains can significantly enhance the biomass of A. roxburghii and induce the biosynthesis and accumulation of its active ingredients, including flavonoids, kinsenoside, and polysaccharides. J162 and J211 were further identified as Chaetomium globosum and Colletotrichum gloeosporioides based on multilocus phylogenetic analysis. Immunocytochemical staining indicated that J162 and J211 mainly colonized the intercellular gap of xylem parenchyma cells of A. roxburghii roots without obvious harm. In addition, quantitative real-time polymerase chain reaction showed that the expression of three growth-related genes, namely, uracil phosphoribosyl transferase, amino acid transmembrane transporter, and maturase K, were significantly altered in A. roxburghii plants when treated with J162 and J211. In conclusion, the two strains are highly beneficial microbial resources for the growth and accumulation of active ingredients of A. roxburghii in agricultural cultivation.

The objective of this chapter is to interpret a supply chain as an ontological entity with being-in-the-world of spacetimemattering. A case study approach is adopted to reveal the strategies undertaken by one of China’s fastest growing Internet companies – Xiaomi Inc. – to create competitive advantage through its management of product design and supply chain integration. Utilizing publicly available data, we analyze the company with quantum storytelling and network analysis techniques. Our analysis concludes that Xiaomi’s success originates from two aspects. First, Xiaomi is a good storyteller, who makes stories appealing to customers by involving them into product design and branding. Second, Xiaomi’s parsimonious supply chain substantially improves its market responsiveness and reduces disruption risks; more importantly, it helps to offer products of great value to customers.

Cloud storage service allows data owners to store their (encrypted) data in a remote and may be untrusted cloud server. Attribute-Based Encryption (ABE) provides an excellent and flexible solution for data access control. As more and more applications evolved, ABE schemes may not handle all scenarios, in particular, if the access control has a time and location constraint. Time and location attributes are not as static as other general attributes. Existing ABE schemes cannot efficiently handle the continuous range of an attribute making it impractical for temporal and spatial constraints that are changing dynamically. In this paper, we propose a novel temporal and spatial constrained attribute-based access control (TSC-ABAC) scheme to solve this problem. Our system adopts a redesigned access structure and makes use of multi-dimensional range derivation function to match the time domain. This is the first ABE scheme that can efficiently handle time and location elements simultaneously. We further propose an extended TSC-ABAC scheme, which aims at reducing the decryption cost imposed on user. A thorough security and performance analysis shows that our design is secure and efficient. The result of our work could provide a feasible and practical data access control scheme for cloud storage services.

Deep neural networks are extensively used in image recognition. However, its integrity is compromised by evasion attacks. Attackers can easily craft adversarial examples that make DNNs unknowingly output the labels they want rather than the right labels. In a recent study, it was shown that existing detection methods are not effective in identifying these adversarial examples, i.e., it is a realistic threat to existing systems. Unlike the previous detection methods, we observe that the classification probability distributions of adversarial examples and those of untampered examples exhibit a big difference, which can be easily identified based on the output of a DNN without getting into the complicated DNN internal structure. Based on this new insight, we propose a new light-weight detection method by transforming the detection of adversarial examples into a binary classification problem. The detector we train achieves almost 100% accuracy on adversarial examples. Moreover, we propose a detector-corrector network that effectively reduces successful rate of existing state-of-the-art evasion attacks under three commonly used distance metrics. In particular, for the common L2 attack, DCN mitigates 99% adversarial examples on MNIST and 95% on CIFAR-10. Our evaluation demonstrates that DCN is significantly more effective and efficient against various evasion attacks than existing methods.

The study finds that green consumption is the tradeoff that consumers are forced to make between collective interests and personal interests. In reality, consumers think that green consumption is a kind of fashion, and they tend to use herd mentality to choose green consumption, or in order to show their uniqueness that are almost not affected by the influence of the negative features such as high price of green products. This paper explores the relationship between social comparison orientation and green consumption, and examines the mediating effects of in-group identification and the moderating effects of face consciousness, thereby building the conceptual model of this study.

Service supply chain, the new research tendency of supply chain management, is considered to be the most effective tool for enterprises to retain competitive advantages. It has attracted the attention of scholars and practitioners in the field of different disciplines. Based on bibliometric methods and the data of CNKI and Web of Science&#153 from 2000 to 2014, the paper makes a statistic analysis on service supply chain from the amount, subjects and methods. It also makes a summary of the subjects (definition, modeling, service capability, the relationship between management and performance, application, measurement, and coordination mechanism), providing references for the further study.

Ciphertext-Policy Attribute-based Encryption (CP-ABE) is a useful cryptographic scheme and is being considered for cloud application as more and more users leverage cloud platforms to store and process their data. However, existing CP-ABE schemes still have a number of limitations that make it not effective to be used in a practical application. Firstly, the size of the ciphertext and the time for decryption grow with the complexity of the access formula. This efficiency issue becomes a problem when using a cloudplatform and mobile devices with limited processing capacity. Secondly, in reality, the attributes of users may be changed from time to time, or some users may eventually leave the system due to resignation. This practical concern requires a scheme with flexible and fine-grained revocation optionsupporting attribute-level changes. Lastly, traceability is also an important feature to track potential traitors who leak the partial decryption keys if ABE is used in a real scenario. None of the existing CP-ABE schemes are able to satisfy these three properties simultaneously. In this paper, we propose apractical CP-ABE that can achieve all three requirements. Our system adopts techniques on secure outsourcing of pairings to support efficient outsourcing computation and makes use of a subset cover algorithm to meet the requirements of revocation and traceability. Our scheme is proved to be a selectively replayable chosen-ciphertext attack (RCCA) secure in random oracle model. The result of our work could provide a feasible, reliable and practical CP-ABE scheme for the realistic application.

OpenEHR is an open standard specification for developing flexible electronic health record (EHR) management system. It defines the standard service models and APIs, and offers a whole lifetime data storage method to the patient's record. As an important OpenEHR system component, EHRServer plays the role of back-end services repository for data storage and query. It complies with the openEHR specifications and adopts MySQL database. However, current EHRServer has many limitations. For example, its official requirement stresses that one organization cannot access the EHR owned by other organizations. The original EHRServer database is in plaintext format. It can lead to the risk of electronic record leakage. Encryption is one common protection method, but the current EHRServer APIs do not support encrypted data query. That restricts building EHRServer on the cloud. What's more, the inconvenience of information sharing among different organizations may also hinder the extension of OpenEHR coverage to more domains and countries. To solve the above open problems, in this paper, we explore two approaches which guarantee the security and flexibility of sharing EHR on the cloud and thus propose a new architecture called Crypt-EHRServer. Firstly, we use attribute-based encryption to realize flexible EHR access authority for different authorized organizations. Secondly, we learn from an efficient ciphertext query model, CryptDB, and adopt their onion encryption approach to support standard SQL queries on the encrypted EHR. The result of our work could provide a flexible, scalable and secure EHR system. Crypt-EHRServer will benefit OpenEHR's widespread adoption in the world, and will also arouse people's awareness about incorporating security criteria into the design of electronic health records management systems.

Herein, we rationally design and construct a novel type of sparsely studded noble-metal nanocrystals inside graphene hollow sphere network (abbreviated as noble-metal@G HSN) through an electrostatic-attraction-directed self-assembly approach. The formation of Pt@G and Pd@G hollow sphere networks have been illustrated as examples using SiO2 spheres as templates. Moreover, the electrocatalytic performance of the Pt@G HSN for methanol oxidation reaction has been examined as a proof-of-concept demonstration of the compositional and structural superiorities of noble-metal@G HSN toward electrocatalyst utilization. The as-prepared Pt@G HSN manifests higher catalytic activity and markedly enhanced long-term durability in comparison with commercial Pt/C catalyst.

In this paper, the problem is described which of storing massive digital evidence and preventing potential information leaks in forensics. The strategy of cloud encrypted database is therefore to be proposed. Existing encrypted database frameworks and solutions do not provide a satisfactory result to solve the problem. They either cause potential information leaks or have unacceptable data redundancy. We propose an efficient encrypted database model adopting initialization vector transfer and numerical order replacement. Experimental results show that the ciphertext retrieval speed can be significantly matched with what of plaintext.

In this paper, we describe the problem of checking the integrity of log in monitoring system for forensics investigation. Existing frameworks and solutions do not provide a satisfactory result to solve the problem. They either require a mass amount of storage overhead to store the hash values of the events or may not be able to match the situation in an effective way if some events have been modified. We propose an efficient hashing scheme with Shifted Transversal Design Group Testing algorithm to calculate hash values for all events in a log file as the integrity proof and precisely locate the events which have been corrupted. Experimental results show that the storage overhead can be significantly decreased by adopting the scheme.

Endophytic fungi possess favorable effects on their host plants, including disease-resistance improvement, secondary metabolite induction, and growth promotion. It is therefore a promising and sustainable strategy to utilize endophytic fungi for the quality improvement of medicinal herbs or important crops. In our study, a collection of 277 strains of endophytic fungi were isolated from Anoectochilus and Ludisia orchids. Two strains J162 and J211 can be symbiotically cocultured with the tissue culture seedlings of Anoectochilus roxburghii, a popular medicinal and edible plant in southern China. Both strains can significantly enhance the biomass of A. roxburghii and induce the biosynthesis and accumulation of its active ingredients, including flavonoids, kinsenoside, and polysaccharides. J162 and J211 were further identified as Chaetomium globosum and Colletotrichum gloeosporioides based on multilocus phylogenetic analysis. Immunocytochemical staining indicated that J162 and J211 mainly colonized the intercellular gap of xylem parenchyma cells of A. roxburghii roots without obvious harm. In addition, quantitative real-time polymerase chain reaction showed that the expression of three growth-related genes, namely, uracil phosphoribosyl transferase, amino acid transmembrane transporter, and maturase K, were significantly altered in A. roxburghii plants when treated with J162 and J211. In conclusion, the two strains are highly beneficial microbial resources for the growth and accumulation of active ingredients of A. roxburghii in agricultural cultivation.