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As the number of scientific publications continues to increase at a dizzying rate, researchers face challenges related to spending too much time and effort searching for appropriate papers to cite in their work. Citation recommendation models have thus been developed to automatically generate a list of relevant papers for a specific text passage, thus helping to reduce the workload for scientists and contribute to better-quality research. Consequently, this research direction has recently attracted significant interest in the scientific community. However, the current citation recommendation models still focus primarily on the citation context and do not adequately address the metadata of papers, such as the citation links, publication time, and venue. To overcome these problems, in this study, we propose the SciBERT-GraphSAGE which is a hybrid deep learning-based model for recommending a list of academic papers by considering both the citation context and this article’s metadata. Our model has two important components: 1) SciBERT for text data representation learning and 2) GraphSAGE for learning the representations of this article’s citation links. We validate the effectiveness of our model on three benchmark datasets: 1) FullTextPeerRead; 2) ACL; and 3) RefSeer. The results from experiments demonstrate that our novel SciBERT-GraphSAGE model outperforms previous advanced models in terms of Recall@K, mean reciprocal rank (MRR), and mean average precision (MAP).

Carbon fibre-reinforced polyamide 6 (PA6) composites exhibit exceptional mechanical properties, making them a highly attractive material option for various industries. Their ability to combine the advantages of carbon fibres with the versatility of PA6 provides opportunities for lightweight, high-performance applications. This work presented the fabrication of a PA6/carbon fibre composition with carbon fibre was modified by two different chemicals: nitric acid and diglycidil ether bisphenol A (DGEBA). The tensile strength at break, flexural strength, Rockwell hardness and Izod impact were measured to compare the mechanical properties of composites based on the PA6 matrix with two different modified carbon fibres. The morphology of PA6-based composite with different modified carbon fibres was observed by scanning electron microscopy. The results showed that PA6 is more compatible with acid-modified carbon fibre than DGEBA-modified carbon fibre and unmodified carbon fibre. In comparison to composite materials containing unmodified carbon fibre and DGEBA-modified carbon fibre, composite containing acid-modified carbon fibre increase tensile strength (16–38% and 7–15%, respectively), flexural strength (18–66% and 51–70%, respectively), Izod impact (23–65% and 32–78%, respectively) and Rockwell hardness (50–400% and equivalence, respectively).

Drilling pressure relief is one of the methods to reduce the risk of coal bursts in deep mines. However, the effect of the drill hole orientations has not been studied well enough to understand their impact on the burst failure mechanism. In this study, we investigated two designs of drill hole orientations. The first design includes drill holes located on the upper free face of the rectangular samples and labelled as upper hole (UH) and centre hole (CH) – the long axes of the drill holes are aligned with minor principal stress, σ3, direction. The second design includes drill holes at the top (TH) and the side (SH) of the rectangular samples in which the long axes of the drill holes are aligned with the maximum, σ1, and intermediate principal stress, σ2, directions, respectively. The coal samples with the proposed drill hole orientations were subjected to the true-triaxial unloading coal burst tests. The results show that the drill holes reduce the risk of coal bursts. However, we found that the intensity of coal burst was significantly reduced with the SH-type, followed by the CH-types. We also observed that the coal burst intensity is reduced better for the CH, UH, TH, and SH-type drilling patterns. However, it was found that the orientations of drill holes have little influence on the failure mode (splitting). The acoustic emission (AE) activities for coal with drill holes noticeably decreased, especially for the UH and CH layouts. The drill holes reduced the upper limit of the AE entropy (chaos of microcracks generation). However, regarding reducing the coal burst risk, the TH and SH are less effective than UH and CH.

The creation of self-assembled porphyrin nanostructures and their organised arrays has garnered significant attention, with the objective of mimicking natural light-harvesting mechanisms and energy storage, as well as pioneering novel nanostructured materials for use in photocatalytic processes. This study explored the formation of porphyrin nanofibers onto the surface of g-C3N4via self-assembly, creating a photoelectrode with remarkable potential for efficient photoelectrochemical (PEC) water splitting. By integrating these two distinct materials, the resultant hybrid structure leverages the unique properties of both components, enhancing the overall performance of the photoelectrochemical system. The fabrication process involves acid-base neutralization-induced self-assembly, leading to the formation of a well-distributed composite. The resulting photoelectrode exhibits improved charge separation and enhanced light absorption properties. Experimental analyses, encompassing techniques such as scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and photocurrent measurements, validate the successful integration of the hybrid material and its notable photocatalytic efficiency. The porphyrin nanofiber was evenly distributed over the surface of the generated g-C3N4@porphyrin hybrid material. The photoelectrochemical measurements showed a remarkable enhancement in the photocurrent when using g-C3N4@porphyrin photoelectrode in the light-irradiating condition compared to the dark condition. The possible PEC water-splitting mechanism by g-C3N4@porphyrin photoelectrode was also proposed and discussed. This work showcases a promising avenue for advancing the field of photoelectrochemical water splitting through innovative material design and assembly strategies.

A binary porous material of SiO2and SiO2–modified expanded graphite (MEGR) was simultaneously prepared based on a low-cost and template-free approach in which a commercially abundant sodium silicate was used as a SiO2precursor in the presence of expanded graphite (EGR). The polycondensation and excessive aggregation of SiO2on the surfaces of EGR enabled the formation of highly interconnected porous networks. Besides, the hydrophilicity of MEGR was improved due to the presence of multiple silanol groups from anchored SiO2. The SiO2/MEGR was then used as a binary porous support for the adsorption and stabilization of polyethylene glycol (PEG), forming composite phase change materials (CPCMs) for thermal energy storage. The prepared PEG/SiO2/MEGR CPCMs were investigated for thermal properties with varying PEG content (50–90%) and a fixed SiO2:MEGR ratio of 75:25. The presence of MEGR with desirable porous structure and improved hydrophilicity contributed to the PEG adsorption capacity of SiO2/MEGR. Indeed, the loading of PEG was improved from 60% of pristine SiO2to 80% of SiO2/MEGR. In addition, the thermal conductivity of the 80% PEG/SiO2/MEGR composite was enhanced to 2.865 W/m K, which was 11.2 times greater than that of pure PEG. Furthermore, the PEG/SiO2/MEGR composite retained high thermal stability and excellent thermal reliability after 500 melting/crystallization cycles. The facile preparation and high thermal performance make the PEG/SiO2/MEGR composite competitive for thermal energy storage applications.

Per- and polyfluoroalkyl substances (PFAS) are known for their high environmental persistence and potential toxicity. The presence of PFAS has been reported in many dairy products. However, the mechanisms underlying the accumulation of PFAS in these products remain unclear. Here, we used native mass spectrometry and molecular dynamics simulations to probe the interactions between 19 PFAS of environmental concern and two isoforms of the major bovine whey protein β-lactoglobulin (β-LG). We observed that six of these PFAS bound to both protein isoforms with low- to mid-micromolar dissociation constants. Based on quantitative, competitive binding experiments with endogenous ligands, PFAS can bind orthosterically and preferentially to β-LG’s hydrophobic ligand-binding calyx. β-Cyclodextrin can also suppress binding of PFAS to β-LG owing to the ability of β-cyclodextrin to directly sequester PFAS from solution. This research sheds light on PFAS–β-LG binding, suggesting that such interactions could impact lipid-fatty acid transport in bovine mammary glands at high PFAS concentrations. Furthermore, our results highlight the potential use of β-cyclodextrin in mitigating PFAS binding, providing insights toward the development of strategies to reduce PFAS accumulation in dairy products and other biological systems.

Malware authors often use cryptographic tools such as XOR encryption and block ciphers like AES to obfuscate part of the malware to evade detection. Use of cryptography may give the impression that these obfuscation techniques have some provable guarantees of success. In this paper, we take a closer look at the use of cryptographic tools to obfuscate malware. We first find that most techniques are easy to defeat (in principle), since the decryption algorithm and the key is shipped within the program. In order to clearly define an obfuscation technique’s potential to evade detection we propose a principled definition of malware obfuscation, and then categorize instances of malware obfuscation that use cryptographic tools into those which evade detection and those which are detectable. We find that schemes that are hard to de-obfuscate necessarily rely on a construct based on environmental keying. We also show that cryptographic notions of obfuscation, e.g., indistinghuishability and virtual black box obfuscation, may not guarantee evasion detection under our model. However, they can be used in conjunction with environmental keying to produce hard to de-obfuscate version of programs.

This study investigates the impact of personal information disclosure on the intention of Gen Z users in Vietnam to continue using mobile applications (m-apps). Focusing on the privacy calculus framework, the research examines how the relationship between trust and privacy concerns affects users' decisions. Data from a sample of 450 respondents were analysed using structural equation modelling. The findings reveal that mobile users conduct a trade-off assessment between perceived benefits and perceived risks when deciding to disclose their information, significantly influencing their continuance intention. Interestingly, the study finds that privacy concerns do not directly affect trust when users face the dilemma of balancing risks to their privacy with trust in decision-making. Additionally, perceived value serves as a mediating factor in the relationship between trust and continued app usage. This research contributes to the existing literature by challenging contradictory views on trust and privacy and offers valuable insights for enhancing user retention in e-commerce m-apps.

Despite social sharing platforms (SSPs) conveniently providing users with abundant information about healthcare issues, their role in formation of patients' intentions to use healthcare services remains unexplored. This study combines protection motivation theory (PMT), the health belief model (HBM), and the involvement perspective to investigate what factors influence patients' intention to use healthcare services. We analysed data from 552 patients of large clinics in Vietnam's Mekong Delta region using a structural equation model. The research contributes to the healthcare and social platform literature by: 1) proposing and validating a combined model of PMT and HBM to predict patients' use of healthcare services; 2) unveiling that, except response efficacy, perceived resilience, perceived severity, protection motivation, price reasonableness, and problem-focused copings significantly affect patients' involvement, and then their intention to use healthcare services. We make practical recommendations to help managers retain and attract patients through the effective use of SSPs.

This study leverages sentiment analysis and topic modelling to enhance understanding of customer perceptions in the hospitality industry, through an empirical analysis of user-generated content from Booking.com related to establishments in Ho Chi Minh City, Vietnam. By employing latent Dirichlet allocation, the research uncovers critical themes impacting customer satisfaction, including service quality, the overall hotel experience, location convenience, dining options, and room comfort and cleanliness. The effectiveness of various machine learning (ML) and deep learning (DL) models is evaluated for sentiment analysis. The convolutional neural network model, in particular, demonstrates superior performance with an accuracy of 0.95 and an F1-score of 0.97. Highlighting the application of sophisticated ML and DL techniques to analyse complex patterns in user-generated feedback, this research study offers valuable insights into brand equity and customer experiences within the hospitality sector.

This study explores the impact of innovation capability on the relationships of export assistance, and export market orientation (EMO) on the export performance of SMEs. Based on the resource-based view (RBV), by incorporating the relationship marketing theory (RMT) and domestic and firm characteristics, this study proposes and validates a research model using convenience sampling (n = 318) and a face-to-face survey of SMEs exporting agricultural products in the Mekong Delta region, Vietnam. The SmartPLS4 package was utilised for data analysis. The research findings reveal that: 1) except export assistance, factors including export market orientation, commitment, trust, and innovation significantly affect export performance; 2) while innovation acts as a mediator of the relationship between export assistance-export performance, it does not mediate the link export market orientation-export performance. This study enriches the export literature by providing original insights into the key drivers of export success for SMEs and suggests theoretical and practical implications for emerging economies.

ABSTRACT In this study, it is going to investigate properties of lightweight geopolymer specimens aerated by aluminium powder. It has been established well that aluminium powder can be appropriately used [...]

Purpose: This study explores the relationship between corruption and shadow economy (SE) by examining the potential links and interactions between these two phenomena to see whether it is a one-way or two-way relationship and a complementarity or substitution linkage. Design/methodology/approach: Using a dataset comprised of 145 countries all over the world between 1996 and 2015, the authors apply the simultaneous two-step system generalized method of moments approach to address the research question. Findings: The study findings support a positive bidirectional relationship between corruption and SE. As such, this study has provided evidence supporting the complementarity association. In the authors' further analyses, they point out that several factors can moderate this positive bidirectional linkage. In particular, while Foreign Direct Investment (FDI) inflows strengthen it, it is weakened by other institutional factors such as civil liberties and political rights. Finally, by splitting the full sample into three different subsamples and then examining countries at varying stages of economic development, the authors can gain valuable insights into the evolving dynamics of the relationship between corruption and SE. Specifically, while the authors observe that the positive direction of corruption to SE remains unchanged across different nations, they observe that the positive influence of SE on corruption is strongest among developed economies only. Practical implications: The study findings provide an important policy implication. This study highlights the synergistic relationship between SE and corruption, indicating that reducing corruption will reduce the size of the SE. Consequently, this reduction in the SE can mitigate the adverse effects of corruption on economic development. Originality/value: This paper is among the first empirical studies that critically investigate the interrelationship between SE and corruption. It then explores how this two-way linkage is conditional on some factors, such as economic development levels and institutional quality indicators.

Variants of human factor VIII (hFVIII) have been developed to further understand the structure and function of hFVIII and improve gene-based therapeutics. We have previously characterized several hFVIII variants of the furin cleavage site (1645-1648) with improved secretion. We have also identified a second cleavage site in the acidic region 3 (a3) (1657-1658) that becomes the primary hFVIII intracellular cleavage position in the absence of the furin site. We tested a hypothesis that modification of this site may confer additional functional advantages to hFVIII.

Background: Due to cognitive impairments, people with dementia (PWD) often have difficulties in eating and drinking. This study aimed to assess the nutritional status, dietary quality and eating disturbance issues among PWD in Vietnam. Methods: We conducted a cross-sectional study at the Vietnamese National Geriatric Hospital from April to December 2022. We used Mini-Mental State Exam (MMSE) to classify the severity levels of dementia. Mini Nutritional Assessment (MNA), 24-hour recall, eating disturbance questionnaires, and anthropometric indicators were used to evaluate the nutritional status, dietary quality, and eating disorders of study subjects. Results: Overall, among 63 study participants, 74.6 per cent of PWD were at risk of or having malnutrition. By dementia classification according to MMSE scale, people with moderate and severe dementia accounted for 53.3 per cent of those who met the recommended energy levels, compared to 42.4 per cent of people with mild dementia and normal people. In the above two groups, around three per cent of participants reached the recommended amount of fibre. Calcium (50–70%), vitamin A (80–90%), and D (90%) were found to be the most severe deficiency forms of minerals and vitamins in both male and female participants. The majority of participants (90.5%) had at least one form of eating disorders with the most frequent issue being appetite changes (76.2%) and swallowing issues (50.8%). Conclusions: PWD in our sample frequently experienced malnutrition, a lack of essential nutrients, difficulties swallowing, changes in eating habits and appetite. It is neccesary to early screen and assess nutritional status and swallowing disturbance in PWD, and instruct their caregivers to prepare nutritious meals for them.

Many applications involve humans in the loop, where continuous and accurate human motion monitoring provides valuable information for safe and intuitive human-machine interaction. Portable devices such as inertial measurement units (IMUs) are applicable to monitor human motions, while in practice often limited computational power is available locally. The human motion in task space coordinates requires not only the human joint motion but also the nonlinear coordinate transformation depending on the parameters such as human limb length. In most applications, measuring these kinematics parameters for each individual requires undesirably high effort. Therefore, it is desirable to estimate both, the human motion and kinematic parameters from IMUs. In this work, we propose a novel computational framework for dual estimation in real-time exploiting in-network computational resources. We adopt the concept of field Kalman filtering, where the dual estimation problem is decomposed into a fast state estimation process and a computationally expensive parameter estimation process. In order to further accelerate the convergence, the parameter estimation is progressively computed on multiple networked computational nodes. The superiority of our proposed method is demonstrated by a simulation of a human arm, where the estimation accuracy is shown to converge faster than with conventional approaches.

Although the growth of the ride-hailing sector has attracted much attention from scholars and practitioners, the continued usage of ride-hailing services has yet to be studied sufficiently among its two main types of users: riders and drivers. Relying on the adaptive structuration theory for individuals, expectation-confirmation model, and the decomposed theory of planned behaviour, our study proposes a research model to examine how the users' adaptation influences continuance intention to use ride-hailing applications. Our research employs a questionnaire-based and face-to-face survey to collect data from over 500 user-drivers of the largest ride-hailing firms across Vietnam. A structural equation modelling method was used to analyse the data and validate the hypotheses. Our findings broaden the understanding of users' adaptation on their continuance intention. The study also provides fresh insight into how perceived usefulness, management support, and self-efficacy affect continuance intention to use ride-hailing applications in an emerging economy such as Vietnam.

This study examines the influences of online trust and self-efficacy on the online purchase intention of Generation Z. Based on the social cognitive theory and the decomposed theory of planned behaviour, this study proposes a research model and verifies the hypotheses using structural equation modelling and data gathered from online interviews of 366 young online buyers in Vietnam. The findings reveal that: 1) online trust, self-efficacy, subjective norm and compatibility have a determinant impact on online purchase intention; 2) online trust is verified as being a factor that plays the dual role of mediator and moderator in the relationship between self-efficacy and online purchase intention. Both theoretical and managerial implications are provided to broaden the current understanding of online trust and suggest that business managers should focus on imperative factors to drive users to choose to make online purchases.

AbstractAntibacterial foam dressing has been developed in recent years based on polymeric membranes and silver ions or silver nanoparticles as antibacterial components. However, silver ions or silver nanoparticles have cytotoxicity to humans. Herein, we used biocompatible multi-branched gold nanoparticles as an antimicrobial agent in polyurethane foam wound dressings. This study described a rapid and surfactant-free method for the preparation of multi-branched gold nanoparticles using hydroquinone as a reducing agent and chitosan as a stabilizer as well as assisted irradiation. The optimal procedure of polyurethane foam fabricated with high water absorption and small average pore size, achieved nearly 500% of absorptivity and 98 nm of pore size. The antibacterial effects of the multi-branched gold nanoparticles containing polyurethane foam against both Escherichia coliand Staphylococcus aureuswere investigated. The results demonstrated that multi-branched gold nanoparticles can be used as a viable alternative to conventional antibiotics in wound dressings.

AbstractEndophytic fungi are promising sources for the production of podophyllotoxin-an important anticancer compound, replacing depleted medical plants. In this study, the endophytes associated with Dysosma difformis-an ethnomedicinal plant species were isolated to explore novel sources of podophyllotoxin. Fifty-three endophytic fungi were isolated and identified by morphological observation and ITS-based rDNA sequencing, assigning them to 27 genera in 3 divisions. Fusariumwas found the most prevalent genus with a colonization frequency of 11.11%, followed by Trametes(9.26%) and Penicillium(7.41%). Phylogenetic trees were constructed for the endophytic fungi community in two collection sites, Ha Giang and Lai Chau, revealing the adaptation of the species to the specific tissues and habitats. Cytotoxic activity of endophytic fungal extracts was investigated on cancer cell lines such as SK-LU-1, HL-60, and HepG2, demonstrating strong anti-cancer activity of six isolates belonging to Penicillium, Trametes, Purpureocillium, Aspergillus,and Ganodermawith IC50value of lower than 10 µg/mL. The presence of podophyllotoxin was indicated in Penicillium, Trametes, Aspergillusand for the first time in Purpureocilliumand Ganoderma viahigh-performance liquid chromatography, which implied them as a potential source of this anti-cancer compound.

Composite phase change materials (CPCMs) with multifunctional thermal conversion and storage abilities have demonstrated exceptional properties for diverse energy storage applications recently; however, these composite materials often encounter limitations of low heat storage capacity and high cost. In this study, novel 1–octadecanol (OD)/expanded graphite (EG)/Fe3O4CPCMs were facilely prepared and characterized for multifunctional thermal conversion and storage properties. The composites showed excellent thermal energy storage capacities, reaching 185.5 J/g at 80 % OD accompanied by high crystallization fractions of above 95 %. In addition, they exhibited great thermal conductivities, excellent leakage resistance, thermal stability, and reliability. Under simulated solar irradiation, the prepared OD/EG/Fe3O4CPCMs exhibited a rapid temperature increase from 34 to 70 °C, achieving solar–to–thermal conversion efficiency of 80.2–90.5 %. This behavior can be attributed to its ability to capture and convert photons into thermal energy, facilitated by the synergistic effects of the conjugated double–bond system of EG and localized surface plasmon resonance of Fe3O4nanoparticles. Furthermore, the prepared OD/EG/Fe3O4CPCMs exhibited superparamagnetic properties, accelerating their temperatures from 32 °C to 88 °C within 11–23 s when subjected to an alternating magnetic field. This demonstrates magnetic–to–thermal conversion and storage ability. These findings highlight the potential of OD/EG/Fe3O4CPCMs as promising and cost–effective materials for various practical thermal storage applications.

Photonic quantum technology provides a viable route to quantum communication1,2, quantum simulation3and quantum information processing4. Recent progress has seen the realization of boson sampling using 20 single photons3and quantum key distribution over hundreds of kilometres2. Scaling the complexity requires architectures containing multiple photon sources, photon counters and a large number of indistinguishable single photons. Semiconductor quantum dots are bright and fast sources of coherent single photons5–9. For applications, a roadblock is the poor quantum coherence on interfering single photons created by independent quantum dots10,11. Here we demonstrate two-photon interference with near-unity visibility (93.0 ± 0.8)% using photons from two completely separate GaAs quantum dots. The experiment retains all the emission into the zero phonon line—only the weak phonon sideband is rejected; temporal post-selection is not employed. By exploiting quantum interference, we demonstrate a photonic controlled-not circuit and an entanglement with fidelity of (85.0 ± 1.0)% between photons of different origins. The two-photon interference visibility is high enough that the entanglement fidelity is well above the classical threshold. The high mutual coherence of the photons stems from high-quality materials, diode structure and relatively large quantum dot size. Our results establish a platform—GaAs quantum dots—for creating coherent single photons in a scalable way.

Materials exhibiting thermally activated delayed fluorescence (TADF) are now key components of some of the most advanced organic light-emitting diodes, photocatalysts, and bioimaging probes. Designing a TADF emitter requires a precise understanding of its frontier molecular orbitals (FMOs), yet rarely are these orbitals visualized experimentally. Here, we use scanning tunneling microscopy on Ag(111) to probe the electronic structures of high-performance TADF materials with different orbital landscapes based on s-triazine and s-heptazine acceptors. These materials exhibit room-temperature phosphorescence or thermally activated delayed fluorescence, deep-blue (452 nm) to red (615 nm) emission, near-unity photoluminescence quantum yields, exceptional photostability, and two-photon absorption cross sections as high as 2098 GM. Overall, this work demonstrates the potential of s-heptazines as optoelectronic materials, as well as the utility of direct FMO visualization in material design.

AbstractLatouche and Nguyen (2015b) constructed a sequence of stochastic fluid processes and showed that it converges weakly to a Markov-modulated Brownian motion (MMBM). Here, we construct a different sequence of stochastic fluid processes and show that it converges strongly to an MMBM. To the best of our knowledge, this is the first result on strong convergence to a Markov-modulated Brownian motion. Besides implying weak convergence, such a strong approximation constitutes a powerful tool for developing deep results for sophisticated models. Additionally, we prove that the rate of this almost sure convergence is $o(n^{-1/2} \log n)$ . When reduced to the special case of standard Brownian motion, our convergence rate is an improvement over that obtained by a different approximation in Gorostiza and Griego (1980), which is $o(n^{-1/2}(\log n)^{5/2})$ .

A new hybrid discrete–continuum numerical approach that explores the key advantages of both discrete and continuum approaches is proposed to model unsaturated seepage flows through porous media. In contrast to existing approaches where a porous medium is often represented by a continuum medium or required a background mesh, the proposed approach explicitly exploits the discrete contact network formed by an assembly of discrete solid particles. Each solid particle is assumed to occupy an equivalent-continuum space, over which the governing equations for unsaturated seepage flow are derived. These governing equations are then discretised and solved on the discrete contact network through a new numerical procedure that links micro-diffusivity to the macro-one. Thanks to this concept, the proposed approach is capable of describing the nature of flow in unsaturated porous media at the microscale level. This unique feature also enables the proposed approach to naturally simulate the water flow through the heterogeneous porous media without any ad hoc treatments. In this paper, the mathematical concept of the proposed approach together with its implementation features and performances for a rigid porous media is presented and discussed. The focus is placed on its application to the discrete element method (DEM), although the proposed concept, in general, can be applied to any other methods possessing similar features.

This study investigates the influences of management support and behavioural adaptation on continuance intention to use ride-hailing services. Based on an extended expectation-confirmation model and by incorporating management support and user adaptation, this study proposes a research model and verifies the hypotheses using structural equation modelling with data gathered from face-to-face interviews of 472 user-drivers of dominant ride-hailing companies in Vietnam. The findings reveal that (1) perceived usefulness, satisfaction and behavioural adaptation have a determinant impact on continuance intention, (2) while management support has no significant direct association with continuance intention, the link is fully mediated by behavioural adaptation, and (3) user adaptation is also verified to be a partial mediator of the relationship of perceived usefulness and continuance intention. Both theoretical and managerial implications are provided to broaden the current understanding of the adaptation literature, suggesting that firms build stronger relationships with their user-drivers, thus sustaining firm success.

Fuzzy association rule mining is one of the important problems in fuzzy machine learning. The fuzzy association rule is intended to handle quantitative data that was indecisive in the classical association rule. However, the fuzzy set of quantitative attributes and their membership functions depends on expert opinion, subjective or available. In this paper, we propose a Node-list Pre-order Size Fuzzy Frequent (NPSFF) algorithm in fuzzy association rule mining based on Node-list data structure combined with the Pre-order Size Code structure suitable for the organization of fuzzy data and the manipulation of this structure. This organization speeds up tree building and finds frequent fuzzy item sets. To increase the efficiency of the NPSFF algorithm, we performed the data preprocessing by applying affinity propagation clustering (AP) technique to specify the suitable number of clusters. Next, we convert the quantitative values of the clusters to the fuzzy values using fuzzy partitioning method. Experiment results show that NPSFF algorithm efficiency is always better than FFP Growth and MFFP algorithms in execution time and memory usage.

Semiconducting polymer dots (Pdots) have emerged as versatile probes for bioanalysis and imaging at the single-particle level. Despite their utility in multiplexed analysis, deep blue Pdots remain rare due to their need for high-energy excitation and sensitivity to photobleaching. Here, we describe the design of deep blue fluorophores using structural constraints to improve resistance to photobleaching, two-photon absorption cross sections, and fluorescence quantum yields using the hexamethylazatriangulene motif. Scanning tunneling microscopy was used to characterize the electronic structure of these chromophores on the atomic scale as well as their intrinsic stability. The most promising fluorophore was functionalized with a polymerizable acrylate handle and used to give deep-blue fluorescent acrylic polymers with Mn> 18 kDa and Đ< 1.2. Nanoprecipitation with amphiphilic polystyrene-graft-(carboxylate-terminated poly(ethylene glycol)) gave water-soluble Pdots with blue fluorescence, quantum yields of 0.81, and molar absorption coefficients of (4 ± 2) × 108M–1cm–1. This high brightness facilitated single-particle visualization with dramatically improved signal-to-noise ratio and photobleaching resistance versus an unencapsulated dye. The Pdots were then conjugated with antibodies for immunolabeling of SK-BR3 human breast cancer cells, which were imaged using deep blue fluorescence in both one- and two-photon excitation modes.

Online learning's application in the language learning process has become an important topic as the COVID-19 crisis has restricted in-person classes. This study investigates student satisfaction in an online language learning course at a higher educational institution in Vietnam. The study tested the influence of learner-learner, learner-content, and learner-instructor interactions; internet self-efficacy; and self-regulation on student course satisfaction. The effects of student background variables were also explored. Linear regression analysis was conducted to determine the contribution of predictor variables to student satisfaction. The findings showed that student interaction with peers, content, and instructors and self-regulation were good predictors of student satisfaction; however, internet self-efficacy was not a good predictor. Additionally, there were no differences in effects of gender and prior online language learning experience on student course satisfaction.

Approximately 20% of adults in Vietnam have hypertension, and management of this chronic condition remains challenging. This study aimed to assess the effectiveness of a multicomponent intervention in reducing blood pressure (BP) in adults with uncontrolled hypertension.

Attribute reduction is a crucial problem in the process of data mining and knowledge discovery in big data. In incomplete decision systems, the model using tolerance rough set is fundamental to solve the problem by computing the redact to reduce the execution time. However, these proposals used the traditional filter approach so that the reduct was not optimal in the number of attributes and the accuracy of classification. The problem is critical in the dynamic incomplete decision systems which are more appropriate for real-world applications. Therefore, this paper proposes two novel incremental algorithms using the combination of filter and wrapper approach, namely IFWA_ADO and IFWA_DEO, respectively, for the dynamic incomplete decision systems. The IFWA_ADO computes reduct incrementally in cases of adding multiple objects while IFWA_DEO updates reduct when removing multiple objects. These algorithms are also verified on six data sets. Experimental results show that the filter-wrapper algorithms get higher performance than the other filter incremental algorithms.

Patients who have undergone mastectomy, with or without reconstruction, are not universally screened with mammography or US. Therefore, clinical breast examination by the physician and patient-detected palpable abnormalities are crucial for detecting breast cancer or recurrence. Diagnostic US is the first-line modality for evaluation of postmastectomy palpable masses, with occasional adjunct use of diagnostic mammography for confirming certain benign masses. In the setting of a negative initial imaging evaluation with continued clinical concern, diagnostic MRI may aid in improving sensitivity. Knowledge of the typical multimodality imaging appearances and locations of malignant palpable abnormalities—such as invasive carcinoma recurrence, cancer in residual breast tissue, radiation-induced sarcoma, and metastatic disease—is crucial in diagnosis and treatment of these entities. In addition, familiarity with the range of benign palpable postmastectomy processes—including fat necrosis, fat graft, seroma, granuloma, neuroma, fibrosis, and infection—may help avoid unnecessary biopsies and reassure patients. The authors review common and rare benign and malignant palpable masses in mastectomy patients, describe multimodality diagnostic imaging evaluation of each entity, review radiologic and pathologic correlation, and acquaint the radiologist with management when these findings are encountered.©RSNA, 2021

The significantly greater cost of proton therapy compared with X‐ray therapy is frequently justified by the expected reduction in normal tissue toxicity. This is often true for indications such as paediatric and skull base cancers. However, the benefit is less clear for other more common indications such as breast cancer, and it is possible that the degree of benefit may vary widely between these patients. The aim of this work was to demonstrate a method of individualised selection of left‐sided breast cancer patients for proton therapy based on cost‐effectiveness of treatment. 16 left‐sided breast cancer patients had a treatment plan generated for the delivery of intensity‐modulated proton therapy (IMPT) and of intensity‐modulated photon therapy (IMRT) with the deep inspiration breath‐hold (DIBH) technique. The resulting dosimetric data was used to predict probabilities of tumour control and toxicities for each patient. These probabilities were used in a Markov model to predict costs and the number of quality‐adjusted life years expected as a result of each of the two treatments. IMPT was not cost‐effective for the majority of patients but was cost‐effective where there was a greater risk reduction of second malignancies with IMPT. The Markov model predicted that IMPT with DIBH was only cost‐effective for selected left‐sided breast cancer patients where IMRT resulted in a significantly greater dose to normal tissue. The presented model may serve as a means of evaluating the cost‐effectiveness of IMPT on an individual patient basis. The aim of this work was to demonstrate an individualised selection method for proton therapy of left‐sided breast cancer patients based on cost‐effectiveness of treatment. A Markov model is used to predict costs and the number of quality adjusted life years expected for a small cohort of patients. The presented model may serve as a means of evaluating the cost‐effectiveness of intensity modulated proton therapy on an individual patient basis.

As part of immune surveillance, killer T lymphocytes search for cancer cells and destroy them. Some cancer cells, however, develop escape mechanisms to evade detection and destruction. One of these mechanisms is the expression of cell surface proteins which allow the cancer cell to bind to proteins on T cells called checkpoints to switch off and effectively evade T-cell–mediated destruction. Immune checkpoint inhibitors (ICIs) are antibodies that block the binding of cancer cell proteins to T-cell checkpoints, preventing the T-cell response from being turned off by cancer cells and enabling killer T cells to attack. In other words, ICIs restore innate antitumor immunity, as opposed to traditional chemotherapies that directly kill cancer cells. Given their relatively excellent risk–benefit ratio when compared to other forms of cancer treatment modalities, ICIs are now becoming ubiquitous and have revolutionized the treatment of many types of cancer. Indeed, the prognosis of some patients is so much improved that the threshold for admission for intensive care should be adjusted accordingly. Nevertheless, by modulating immune checkpoint activity, ICIs can disrupt the intricate homeostasis between inhibition and stimulation of immune response, leading to decreased immune self-tolerance and, ultimately, autoimmune complications. These immune-related adverse events (IRAEs) may virtually affect all body systems. Multiple IRAEs are common and may range from mild to life-threatening. Management requires a multidisciplinary approach and consists mainly of immunosuppression, cessation or postponement of ICI treatment, and supportive therapy, which may require surgical intervention and/or intensive care. We herein review the current literature surrounding IRAEs of interest to anesthesiologists and intensivists. With proper care, fatality (0.3%–1.3%) is rare.

The increasing demand for resources and depletion of near ground mineral resources caused deeper mining operations under high-stress rock mass conditions. As a result of this, strain burst, which is the sudden release of stored strain energy in the surrounding rock mass, has become more prevalent and created a considerable threat to workers and construction equipment. It is, therefore, imperative to understand how strain burst mechanism and stored excess strain energy are affected due to the high confinement in deep underground conditions. For this purpose, post-peak energy distributions for brittle rocks were investigated using a newly developed energy calculation method associated with acoustic emission (AE). A series of quasi-static uniaxial and triaxial compression tests controlled by the circumferential expansion were conducted. Snap-back behaviour known as Class-II behaviour associated with energy evolution and the material response under self-sustaining failure were analysed on granites under a wide range of confining pressures (0–60 MPa). The experimental results underline that the energy evolution characteristics are strongly linked to confinement. Stored elastic strain energy (dUE), energy consumed by dominating cohesion weakening (dΦCW) and energy dissipated during mobilisation of frictional failure (dΦFM) showed a rising trend as the confining pressure was increased. An intrinsic ejection velocity was proposed to express the propensity of strain burst that was purely determined by the excess strain energy released from Class II rock.

Organophosphates (OPs) are used worldwide as pesticides. However, acute and chronic exposure to OPs can cause serious adverse health effects. The mechanism of delayed OP toxicity is thought to involve off-target inhibition of serine proteases, although the precise molecular details remain unclear owing to the lack of an analytical method for global detection of protein targets of OPs. Here, we report the development of a mass spectrometry method to identify OP-adducted proteins from complex mixtures in a nontargeted manner. Human plasma was incubated with the OP dichlorvos that was 50% isotopically labeled and 50% unlabeled. Proteins and protein adducts were extracted, digested, and analyzed by liquid chromatography–tandem mass spectrometry (LC-MS/MS) to detect “twin ions” of peptides that were covalently modified by a chemical reaction with dichlorvos. The LC-MS/MS data were processed by a blended data analytics software (Xenophile) to detect the amino acid residue sites of proteins that were covalently modified by exposure to OPs. We discovered that OPs can transmethylate the N, S, and O side chains of His, Cys, Glu, Asp, and Lys residues. For model systems, such transmethylation reactions were confirmed by LC-MS, nuclear magnetic resonance (NMR), and rationalized using electronic structure calculations. Methylation of the ubiquitous antioxidant glutathione by dichlorvos can decrease the reducing/oxidizing equilibrium of glutathione in liver extracts, which has been implicated in diseases and pathological conditions associated with delayed OP toxicity.

In a multi-electron atom, an excited electron can decay by emitting a photon. Typically, the leftover electrons are in their ground state. In a radiative Auger process, the leftover electrons are in an excited state and a redshifted photon is created1–4. In a semiconductor quantum dot, radiative Auger is predicted for charged excitons5. Here we report the observation of radiative Auger on trions in single quantum dots. For a trion, a photon is created on electron–hole recombination, leaving behind a single electron. The radiative Auger process promotes this additional (Auger) electron to a higher shell of the quantum dot. We show that the radiative Auger effect is a powerful probe of this single electron: the energy separations between the resonance fluorescence and the radiative Auger emission directly measure the single-particle splittings of the electronic states in the quantum dot with high precision. In semiconductors, these single-particle splittings are otherwise hard to access by optical means as particles are excited typically in pairs, as excitons. After the radiative Auger emission, the Auger carrier relaxes back to the lowest shell. Going beyond the original theoretical proposals, we show how applying quantum optics techniques to the radiative Auger photons gives access to the single-electron dynamics, notably relaxation and tunnelling. This is also hard to access by optical means: even for quasi-resonant p-shell excitation, electron relaxation takes place in the presence of a hole, complicating the relaxation dynamics. The radiative Auger effect can be exploited in other semiconductor nanostructures and quantum emitters in the solid state to determine the energy levels and the dynamics of a single carrier.

Perfluoroalkyl substances (PFASs) persist and are ubiquitous in the environment. The origins of PFAS toxicity and how they specifically affect the functions of proteins remain unclear. Herein, we report that PFASs can strongly inhibit the activity of human carbonic anhydrases (hCAs), which are ubiquitous enzymes that catalyze the hydration of CO2, are abundant in the blood and organs of mammals, and involved in pH regulation, ion homeostasis, and biosynthesis. The interactions between PFASs and hCAs were investigated using stopped-flow kinetic enzyme-inhibition measurements, native mass spectrometry (MS), and ligand-docking simulations. Narrow-bore emitters in native MS with inner diameters of ∼300 nm were used to directly and simultaneously measure the dissociation constants of 11 PFASs to an enzyme, which was not possible using conventional emitters. The data from native MS and stopped-flow measurements were in excellent agreement. Of 15 PFASs investigated, eight can inhibit at least one of four hCA isozymes (I, II, IX, and XII) with submicromolar inhibition constants, including perfluorooctanoic acid, perfluorooctanesulfonamide, and perfluorooctanesulfonic acid. Some PFASs, including those with both short and long perfluoromethylene chains, can effectively inhibit at least one hCA isozyme with low nanomolar inhibition constants.

Analysis of rural vulnerability to weather shocks requires an accurate exposure record. Both self-reported and weather data records have been used with potential biases. We are the first to evaluate these biases by constructing two comparable records: self-reported weather shocks from a rural household panel dataset and measured weather shocks from weather data. Despite their positive relationship and similar average welfare effects, the two records display a large discrepancy. Being endogenous, the self-reported record introduces the attenuation bias in analysing non-farm labour allocation in response to shocks. We suggest to instrument the self-reported shock with the measured shock for better analytical quality.

Development of selective and cost-effective sorbents used for gold separation from electronic waste (e-waste) leachates is crucible to simplify post-processing steps and reduce the capital costs associated with gold recovery technologies. Despite numerous reported sorbents showing promising results, the practical applications are hindered by the use of expensive chemicals and complex synthesis procedures. Herein, we proposed a facile and low-cost composite of coconut fibers biochar (CFB) modified with zero-valent iron (ZVI), named CFB@Fe, and examined the gold sorption properties from simulated acid-leached e-waste solutions, which was compared to those of CFB and its acid-modified biochar (HCFB). All materials exhibited rapid adsorption kinetics of Au(III), reaching equilibrium sorption in 5 min. The ZVI modification of CFB compensated for the pH dependence, maintaining high Au(III) adsorption efficiency (∼100%) across the pH range of 1 and 7. In addition, CFB@Fe demonstrated a significant enhancement in Au(III) sorption capacity, with Freundlich constants (KF) related to adsorption capacity in the order of CFB@Fe (155.4) > CFB (122.2) > HCFB (101.4). The selective sorption of Au(III) on CFB@Fe was enhanced in the presence of high concentrations of co-leached ions. Examining the Au(III) sorption mechanisms on CFB@Fe revealed an adsorption-reduction process, leading to the generation and deposition of metallic gold on the sorbent. The mechanisms were discussed concerning the roles played by the surface–OH functional groups of CFB and ZVI particles. These findings suggest a great potential for CFB@Fe as a low-cost and efficient material for large-scale separation and enrichment of gold from acidic e-waste leachates.

We report atomically precise pentagonal PdSe2nanoribbons (PNRs) fabricated on a pristine PdSe2substrate with a hybrid method of top-down and bottom-up processes. The PNRs form a uniform array of dimer structure with a width of 2.4 nm and length of more than 200 nm. In situfour-probe scanning tunneling microscopy (STM) reveals metallic behavior of PNRs with ballistic transport for at least 20 nm in length. Density functional theory calculations produce a semiconducting density of states of isolated PNRs and find that the band gap narrows and disappears quickly once considering coupling between PNR stacking layers or interaction with the PdSe2substrate. The coupling of PNRs is further corroborated by Raman spectroscopy and field-effect transistor measurements. The facile method of fabricating atomically precise PNRs offers an air-stable functional material for dimensional control.

Covalent organic frameworks (COFs) are molecule-based 2D and 3D materials that possess a wide range of mechanical and electronic properties. We have performed a joint experimental and theoretical study of the electronic structure of boroxine-linked COFs grown under ultrahigh vacuum conditions and characterized using scanning tunneling spectroscopy on Au(111) and hBN/Cu(111) substrates. Our results show that a single hBN layer electronically decouples the COF from the metallic substrate, thus suppressing substrate-induced broadening and revealing new features in the COF electronic local density of states (LDOS). The resulting sharpening of LDOS features allows us to experimentally determine the COF band gap, bandwidths, and the electronic hopping amplitude between adjacent COF bridge sites. These experimental parameters are consistent with the results of first-principles theoretical predictions.

Netropsin is one of the first ligands to be discovered that selectively binds to the minor groove of DNA and is actively used as a scaffold for developing potential anticancer and antibiotic agents. The mechanism by which netropsin binds to hairpin DNA remains controversial with two competing mechanisms having been proposed. In one mechanism, netropsin binding induces a hairpin-to-duplex DNA transition. Alternatively, netropsin binds in two thermodynamically different modes at a single duplexed AATT site. Here, results from native mass spectrometry (MS) with nanoscale ion emitters indicate that netropsin can simultaneously and sequentially bind to both hairpin and duplex DNA. Duplex DNA was not detected using conventional MS with larger emitters because nanoscale emitters significantly reduce the extent of salt adduction to ligand–DNA complex ions, including in the presence of relatively high concentrations of nonvolatile salts. Based on native MS and polyacrylamide gel electrophoresis results, the abundances of hairpin and duplex DNA are unaffected by the addition of netropsin. By native MS, the binding affinities for five ligand–DNA and DNA–DNA interactions can be rapidly obtained simultaneously. This research indicates a “simultaneous binding mechanism” for the interactions of netropsin with DNA.