How Story Works in Mobile App Stores? Exploring the Same-Side Effect from the Storytelling Perspective

The growing number of mobile apps has contributed to an innovation diffusion paradox whereby the accelerated pace with which mobile apps are being developed and updated has stymied their own diffusion. Due to consumers’ limited personal involvement with mobile apps, storytelling, as an emerging and novel product recommendation format, is gaining traction as a promotional mechanism for diffusing mobile apps within the ecosystem. Storytelling is particularly amenable to the context of mobile app stores by giving affective meaning to the focal app being promoted and strengthening its association with other apps available from these stores. To this end, we construct a research model to illustrate how consumers’ demand for related mobile apps is shaped by similarity in functional and visual attributes between these apps and the focal app being promoted via storytelling. Our model also sheds light on how the preceding effects could be mitigated by within-developer influence

Telling an Attractive Digital Story: Unraveling the Effects of Digital Product Placement Strategy on Product Exposure

The accelerated pace with which mobile apps are being launched has translated into an innovation diffusion paradox for mobile app stores. To cope with the avalanche of newly launched apps, conventional product promotion has given way to digital storytelling as a means of bolstering individuals’ exposure to these apps. Digital storytelling, as an emerging and novel format of product placement, has been credited for boosting consumers’ receptivity to featured products through compelling narrative, direct links, and rich media. In this study, we construct and empirically validate a research model that illustrates how digital storytelling can be strategized for product promotion in mobile app stores. In so doing, we endeavor to not only offer an in-depth appreciation of how digital storytelling can aid in promoting mobile apps through the presentation of engaging content but to also shed light on how these promotional effects could be moderated through rich delivery

Come Rain and Shine? Exploring the Effects of Mobile Weather Applications on Users’ Movements

All Weather conditions affect human behaviors and the growing number of Mobile Weather Applications (MWAs) has amplified this effect. Yet, little is known about how human seek to actively control their behavior by appropriating mobile technology to anticipate changing weather conditions. Guided by Anticipatory Behavioral Control Theory (ABCT), this study endeavors to bride the abovementioned knowledge gap by investigating how the interface design and usage of MWAs would impact the relationship between abnormal weather conditions and users’ movement patterns. From analyzing panel data collected on the hourly movement trajectories of over 1.95 million anonymous mobile phone users over a 2-month period, we strive to shed light on the moderating influence of content representation and usage intensity of MWAs on the relationship between weather conditions and human behaviors

The Society for Immunotherapy of Cancer perspective on regulation of interleukin-6 signaling in COVID-19-related systemic inflammatory response

The pandemic caused by the novel coronavirus SARS-CoV-2 has placed an unprecedented burden on healthcare systems around the world. In patients who experience severe disease, acute respiratory distress is often accompanied by a pathological immune reaction, sometimes referred to as ‘cytokine storm’. One hallmark feature of the profound inflammatory state seen in patients with COVID-19 who succumb to pneumonia and hypoxia is marked elevation of serum cytokines, especially interferon gamma, tumor necrosis factor alpha, interleukin 17 (IL-17), interleukin 8 (IL-8) and interleukin 6 (IL-6). Initial experience from the outbreaks in Italy, China and the USA has anecdotally demonstrated improved outcomes for critically ill patients with COVID-19 with the administration of cytokine-modulatory therapies, especially anti-IL-6 agents. Although ongoing trials are investigating anti-IL-6 therapies, access to these therapies is a concern, especially as the numbers of cases worldwide continue to climb. An immunology-informed approach may help identify alternative agents to modulate the pathological inflammation seen in patients with COVID-19. Drawing on extensive experience administering these and other immune-modulating therapies, the Society for Immunotherapy of Cancer offers this perspective on potential alternatives to anti-IL-6 that may also warrant consideration for management of the systemic inflammatory response and pulmonary compromise that can be seen in patients with severe COVID-19

The prognostic value of whole-genome DNA methylation in response to Leflunomide in patients with Rheumatoid Arthritis

ObjectiveAlthough Leflunomide (LEF) is effective in treating rheumatoid arthritis (RA), there are still a considerable number of patients who respond poorly to LEF treatment. Till date, few LEF efficacy-predicting biomarkers have been identified. Herein, we explored and developed a DNA methylation-based predictive model for LEF-treated RA patient prognosis.MethodsTwo hundred forty-five RA patients were prospectively enrolled from four participating study centers. A whole-genome DNA methylation profiling was conducted to identify LEF-related response signatures via comparison of 40 samples using Illumina 850k methylation arrays. Furthermore, differentially methylated positions (DMPs) were validated in the 245 RA patients using a targeted bisulfite sequencing assay. Lastly, prognostic models were developed, which included clinical characteristics and DMPs scores, for the prediction of LEF treatment response using machine learning algorithms.ResultsWe recognized a seven-DMP signature consisting of cg17330251, cg19814518, cg20124410, cg21109666, cg22572476, cg23403192, and cg24432675, which was effective in predicting RA patient’s LEF response status. In the five machine learning algorithms, the support vector machine (SVM) algorithm provided the best predictive model, with the largest discriminative ability, accuracy, and stability. Lastly, the AUC of the complex model(the 7-DMP scores with the lymphocyte and the diagnostic age) was higher than the simple model (the seven-DMP signature, AUC:0.74 vs 0.73 in the test set).ConclusionIn conclusion, we constructed a prognostic model integrating a 7-DMP scores with the clinical patient profile to predict responses to LEF treatment. Our model will be able to effectively guide clinicians in determining whether a patient is LEF treatment sensitive or not

How to Tell an Attractive Digital Story? The Revolution of Product Placement in the Mobile App Store

The accelerated pace with which mobile applications are developed has translated into an innovation diffusion paradox for mobile app stores. To cope with the avalanche of newly launched apps, conventional product promotion has given way to digital storytelling as a means of bolstering individuals’ exposure to these apps. Digital storytelling, as an emerging and novel product placement format, has been credited for boosting consumers’ receptivity to featured products through compelling narrative, direct links, and rich media, especially in the context of mobile app stores. To this end, we construct a research model to illustrate how to develop an effective strategy for digital storytelling in mobile app stores. In so doing, we endeavor to not only offer an in-depth appreciation of the effects of digital storytelling on mobile app promotion from the perspective of story content but to also shed light on how these effects could be moderated through story delivery

Fuzzy-PID-Based Atmosphere Packaging Gas Distribution System for Fresh Food

The regulation process of gas distribution systems for atmosphere packaging has the characteristics of being nonlinear time varying and having hysteric delay. When the conventional proportional-integral-derivative (PID) control algorithm is applied to this kind of system, it is difficult to set the parameters as the process is time consuming and has poor reliability. For these reasons, this paper designs a gas distribution system for fresh food atmosphere packaging based on a fuzzy PID controller. The step response method is used to construct the system’s mathematical model under the given conditions and to optimize the gas distribution control flow. A simulation experimental platform to compare between the fuzzy PID controller and a conventional PID controller is designed, and the effectiveness of the fuzzy PID control strategy is verified, which proves that it can improve the performance of the monitoring system. The system can realize the remote monitoring of the gas distribution processes through the use of a mobile phone communication network. The data transmission is reliable, the operation is convenient, and, at the same time, the overall efficiency is improved. The results of the system simulation and the gas distribution for atmosphere packaging show that the fuzzy PID algorithm has a faster gas distribution speed and good environmental adaptability as the controller of the gas distribution system. The results show that the stability time of the fuzzy PID controller is about 38 s, while the stability time of the conventional PID controller is about 85 s. The concentration error of fresh gases is ±0.25% floating, the accuracy is increased by 12 times, and the gas distribution speed is increased by about 50% when the system is stable

Catching Audiences’ Attention through Narrative Sensory Cues on Digital Distribution Platforms

Advances in information technologies have radically altered the methods of distributing information goods, which in turn gives rise to the growing prominence of digital storytelling as a means of promoting products to their targeted audience through multimedia. To this end, we attempt to disentangle the effects of narrative sensory cues (i.e., character identifiability and plot imageability) from digital stories on audiences’ visual attention from the theoretical lens of narrative transportation. To do so, we plan to advance a machine learning procedure to simulate audiences’ visual attention. Findings from this study hence offer an in-depth appreciation of the impact of digital storytelling on the diffusion of information goods