Cyberbullying on social networking sites (SNS bullying) is an emerging societal challenge related to the deviant use of technologies. To address the research gaps identified in the literature, we ...draw on crime opportunity theory and the affordance perspective to propose a meta-framework that guides our investigation into SNS bullying. The meta-framework explains how SNS affordances give rise to the evaluation of favorable SNS environmental conditions for SNS bullying, which, in turn, promote SNS bullying. The research model was empirically tested using a longitudinal online survey of 223 SNS users. The results suggest that the evaluation of SNS environmental conditions predict SNS bullying, and SNS affordances influence the evaluation of these environmental conditions. This work offers a new theoretical perspective to study SNS bullying, highlighting the critical impacts of environmental conditions in shaping such behavior. It also provides actionable insights into measures that combat SNS bullying.
•Blockchain improves the security of transactions and data exchanges.•Blockchain enhances the efficiency and the quality of communication.•Blockchain facilitates the expression of ...benevolence.•Blockchain increases the predictability of trading partners.•Hyperledger technologies offer configurational flexibility to businesses.
Blockchain technology has been advocated as a possible solution to enduring trust issues among trading partners in trade finance. We conducted in-depth interviews with industry experts to examine how blockchain technology influences the trust relationships among trading partners. Our results show that the technology enhances trust relationships by (1) improving the security of transactions and data exchanges, (2) facilitating the expression of benevolence, (3) enhancing the efficiency and the quality of communication, and (4) increasing the predictability of trading partners. The paper concludes with implications for both research and practice.
Suspension bridges are flexible and vibration sensitive structures that exhibit complex and multi-modal vibration. Due to this, the usual vibration based methods could face a challenge when used for ...damage detection in these structures. This paper develops and applies a mode shape component specific damage index (DI) to detect and locate damage in a suspension bridge with pre-tensioned cables. This is important as suspension bridges are large structures and damage in them during their long service lives could easily go un-noticed. The capability of the proposed vibration based DI is demonstrated through its application to detect and locate single and multiple damages with varied locations and severity in the cables of the suspension bridge. The outcome of this research will enhance the safety and performance of these bridges which play an important role in the transport network.
•Damage detection in a suspension bridge is treated using vibration Characteristics.•Component specific damage indices (DIs) are developed and applied to detect damage•Vertical damage index can detect and locate damage in the suspension bridge cables•This damage index DIV performs well even in the presence of noise in modal data.•The dominant vibration mode being in the vertical direction DIV performs better
Online impulse buying has drawn increasing scholarly attention across disciplines. However, little effort has been made to evaluate the status of research and consolidate the findings in the ...literature. To address this research gap, we conducted a systematic review of studies of online impulse buying, and used the Stimulus–Organism–Response (SOR) framework to identify and classify the factors that affect online impulse buying. We then built a conceptual framework to explain the interrelationships between the three key elements of online impulse buying. Finally, we discussed the future research directions and implications for research.
Purpose
The purpose of this paper is to examine the effects of inhibiting, motivating, and technological factors on users’ intention to participate in the sharing economy.
Design/methodology/approach
...A self-reported online survey was conducted among Uber users in Hong Kong. A total of 295 valid responses were collected. The research model was empirically tested using the structural equation modeling technique.
Findings
The results suggested that perceived risks, perceived benefits, trust in the platform, and perceived platform qualities were significant predictors of users’ intention to participate in Uber.
Research limitations/implications
This study bridged the research gaps in the sharing economy literature by examining the effects of perceived risks, perceived benefits, and trust in the platform on users’ intention to participate in the sharing economy. Moreover, this study enriched the extended valence framework by incorporating perceived platform qualities into the research model, responding to the calls for the inclusion of technological variables in information systems research.
Practical implications
The findings provided practitioners with insights into enhancing users’ intention to participate in the sharing economy.
Originality/value
This study presented one of the first attempts to systematically examine the effects of inhibiting, motivating, and technological factors on users’ intention to participate in the sharing economy.
Pharmacologic prevention of migraine Tzankova, Velina; Becker, Werner J; Chan, Tommy L H
CMAJ. Canadian Medical Association journal,
02/2023, Letnik:
195, Številka:
5
Journal Article
Diagnosis and acute management of migraine Tzankova, Velina; Becker, Werner J; Chan, Tommy L H
CMAJ. Canadian Medical Association journal,
01/2023, Letnik:
195, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Migraine affects about 12% of adults, with a prevalence of 18% in women and 6% in men. Globally, in 2019, migraine was the second leading cause of disability among men and women across all age ...groups, and the leading cause of disability in women aged 15-49 years (expressed as years lived with disability). In the US, more than 70% of all migraine-related visits are to primary care providers, who play a central role in diagnosing and managing migraine. Recently, several new classes of migraine-specific medications have been shown to be effective and the evidence for the effectiveness of nonpharmacologic interventions is growing. Here, Tzankova et al discuss the diagnosis and acute management of migraine, based on original research evidence, reviews and clinical practice guidelines.
Four new methods have been developed to overcome the ill-posed problems inherently existing in moving force identification (MFI) in previous studies. This paper is an extension of the work to ...evaluate the overall performance of these presented methods by numerical simulations and experiment verifications in laboratory. A simply-supported bridge and two types of moving forces are adopted to evaluate the identification accuracy and ill-posed immunity of these new approaches. Bending moment and acceleration responses are measured when the time-varying forces moving across the bridge deck at constant speed. Numerical simulations of both uniaxial and biaxial forces include 12 cases, which are used to compare the identification accuracy and ill-posed immunity of these methods in detail. Finally, a hinge supported steel beam model and a vehicle model were designed and fabricated in laboratory. Then a series of experimental studies on MFI with these four methods are performed in laboratory. Both numerical and experimental results show that these four approaches can accurately identify moving forces with strong robustness and ill-posed immunity. Moreover, the truncated generalized singular value decomposition (TGSVD) method has higher identification accuracy than the piecewise polynomial truncated singular value decomposition (PP-TSVD) method, and the modified preconditioned conjugate gradient (M-PCG) method has higher identification efficiency than the preconditioned least square QR-factorization (PLSQR) method. To summarize, if the first goal in MFI is to improve the identification accuracy, the TGSVD method is recommended due to its high identification accuracy and stability in different cases. If the first goal in MFI is to improve the identification efficiency, the M-PCG method is recommended due to its high identification efficiency and easy to determine the optimal number of iterations.
•Comparative studies have been carried out to evaluate the proposed four methods.•A guideline on selecting the best method for practical MFI has been provided.•Studies show that the PP-TSVD method is the worst among these four methods.•The TGSVD method is recommended for improving the identification accuracy.•The M-PCG method is recommended for improving the identification efficiency.
•The proposed method does not require eigenvalue analysis and optimization process.•The method can identify light damage with good accuracy with noise polluted data.•PCA is done for subsets ...separately hence main features are extracted precisely.•It is noted that method is able to detect multiple faults.•Networks trained with summation FRFs were better than the individual networks.
Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated.
The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein.
A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.
To compare the accuracy and precision of the new Hill-RBF version 2.0 (Hill-RBF 2) formula with other formulas (Barrett Universal II, Haigis, Hoffer Q, Holladay 1, and SRK/T) in predicting residual ...refractive error after phacoemulsification in high axial myopic eyes.
Retrospective case series.
127 eyes of 127 patients with axial length (AL) ≥26 mm were included. The refractive prediction error (PE) was calculated as the difference between the postoperative refraction and the refraction predicted by each formula for the intraocular lens (IOL) power actually implanted. Standard deviation (SD) of PE, median absolute PE (MedAE), proportion of eyes within ±0.25, ±0.50, and ±1.00 diopter (D) of PE were compared. A generalized linear model was used to model the mean function and variance function of the PE (indicative of the accuracy and precision) with respect to biometric variables.
The MedAE and SD of Hill-RBF 2 were lower than that of Hoffer Q, Holladay 1, and SRK/T (P ≤ .036) and were comparable to Barrett Universal II and Haigis (P ≥ .077). Hill-RBF 2 had more eyes within ±0.25 D of the intended refraction (76 out of 127 eyes 59.84%) compared to other formulas (P ≤ .034) except Barrett Universal II (P = .472). AL was associated with the mean function or variance function of the PE for all formulas except Hill-RBF 2.
In this study, the precision of Hill-RBF 2 is comparable to Barret Universal II and Haigis. Unlike the other 5 formulas, its dispersion and the accuracy of the refractive prediction is independent of the AL.
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