Buying Love Through Social Media: How Different Types Of Incentives Impact Consumers’ Online Sharing Behavior

A key issue in social media marketing is insufficient consumer participation and engagement. Oftentimes companies have to devise tactics to encourage more social sharing of brand messages, such as through the use of incentives and rewards. Previous research has investigated incentive effects under the traditional offline context, which addresses mostly economic exchanges and fails to consider the social dynamics of the social media environment. Addressing this gap, this research aims to answer the following research question: how can companies target different consumers with different incentives to maximize consumer sharing through social media? Specifically, the present research proposes three factors that can affect the relative appropriateness of monetary versus non-monetary incentives in driving consumer sharing: consumer loyalty, audience size and brand personality. Three experimental studies were conducted to examine these factors. The findings of study 1 indicate that consumers with high loyalty are more likely to engage in social sharing when faced with non-monetary incentives. In contrast, non-loyal consumers are more likely to engage in social sharing when offered monetary incentives. Study 2 shows that non-monetary incentives are more effective when sharing to a wide audience is requested, but incentive type does not make a difference when sharing is limited to specific individuals. The results of Study 3 show that, for a brand characterized by sincerity, consumers are more likely to engage in social sharing when a non-monetary incentive is used than when a monetary incentive is used. For an “exciting” brand, the incentive type does not matter. By examining these moderators, this dissertation contributes to a better understanding of how to use incentives more appropriately to increase social sharing under different situations. Moreover, the research findings here can help marketers define the appropriate strategies to target different types of social interactions, and allow them to restore some control in the co-creation of brand stories in the social media context

Obfuscation-resilient Android Malware Analysis Based on Contrastive Learning

Due to its open-source nature, Android operating system has been the main target of attackers to exploit. Malware creators always perform different code obfuscations on their apps to hide malicious activities. Features extracted from these obfuscated samples through program analysis contain many useless and disguised features, which leads to many false negatives. To address the issue, in this paper, we demonstrate that obfuscation-resilient malware analysis can be achieved through contrastive learning. We take the Android malware classification as an example to demonstrate our analysis. The key insight behind our analysis is that contrastive learning can be used to reduce the difference introduced by obfuscation while amplifying the difference between malware and benign apps (or other types of malware). Based on the proposed analysis, we design a system that can achieve robust and interpretable classification of Android malware. To achieve robust classification, we perform contrastive learning on malware samples to learn an encoder that can automatically extract robust features from malware samples. To achieve interpretable classification, we transform the function call graph of a sample into an image by centrality analysis. Then the corresponding heatmaps are obtained by visualization techniques. These heatmaps can help users understand why the malware is classified as this family. We implement IFDroid and perform extensive evaluations on two widely used datasets. Experimental results show that IFDroid is superior to state-of-the-art Android malware familial classification systems. Moreover, IFDroid is capable of maintaining 98.2% true positive rate on classifying 8,112 obfuscated malware samples

Joint relay and jammer selection improves the physical layer security in the face of CSI feedback delays

We enhance the physical-layer security (PLS) of amplify-and-forward relaying networks with the aid of joint relay and jammer selection (JRJS), despite the deliterious effect of channel state information (CSI) feedback delays. Furthermore, we conceive a new outage-based characterization approach for the JRJS scheme. The traditional best relay selection (TBRS) is also considered as a benchmark. We first derive closed-form expressions of both the connection outage probability (COP) and of the secrecy outage probability (SOP) for both the TBRS and JRJS schemes. Then, a reliable-and-secure connection probability (RSCP) is defined and analyzed for characterizing the effect of the correlation between the COP and SOP introduced by the corporate source-relay link. The reliability-security ratio (RSR) is introduced for characterizing the relationship between the reliability and security through the asymptotic analysis. Moreover, the concept of effective secrecy throughput is defined as the product of the secrecy rate and of the RSCP for the sake of characterizing the overall efficiency of the system, as determined by the transmit SNR, secrecy codeword rate and the power sharing ratio between the relay and jammer. The impact of the direct source-eavesdropper link and additional performance comparisons with respect to other related selection schemes are further included. Our numerical results show that the JRJS scheme outperforms the TBRS method both in terms of the RSCP as well as in terms of its effective secrecy throughput, but it is more sensitive to the feedback delays. Increasing the transmit SNR will not always improve the overall throughput. Moreover, the RSR results demonstrate that upon reducing the CSI feedback delays, the reliability improves more substantially than the security degrades, implying an overall improvement in terms of the security-reliability tradeoff. Additionally, the secrecy throughput loss due to the second hop feedback delay is more pronounced th- n that of the first hop

Spatial Distribution of Soil Nutrients in Farmland in a Hilly Region of the Pearl River Delta in China Based on Geostatistics and the Inverse Distance Weighting Method

Soil nutrients are essential factors that reflect farmland quality. Nitrogen, phosphorus, and potassium are essential elements for plants, while silicon is considered a “quasi-essential” element. This study investigated the spatial distribution of plant nutrients in soil in a hilly region of the Pearl River Delta in China. A total of 201 soil samples were collected from farmland topsoil (0–20 cm) for the analysis of total nitrogen (TN), available phosphorus (AP), available potassium (AK), and available silicon (ASi). The coefficients of variation ranged from 47.88% to 76.91%. The NSRs of TN, AP, AK, and ASi were 0.15, 0. 07, 0.12, and 0.13, respectively. The NSRs varied from 0.02 to 0.20. All variables exhibited weak spatial dependence (R2 < 0.5), except for TN (R2 = 0.701). After comparing the prediction accuracy of the different methods, we used the inverse distance weighting method to analyze the spatial distribution of plant nutrients in soil. The uniform spatial distribution of AK, TN overall showed a trend of increasing from northeast to southwest, and the overall spatial distribution of AP and ASi showed that the northeast was higher than the southwest. This study provides support for the delimitation of basic farmland protection areas, the formulation of land use spatial planning, and the formulation of accurate farmland protection policies

The effects of body dissatisfaction, sleep duration, and exercise habits on the mental health of university students in southern China during COVID-19.

Following the outbreak of COVID-19 at the end of 2019, universities around the world adopted a closed management model and various restrictive measures intended to reduce human contact and control the spread of the disease. Such measures have had a profound impact on university students, with a marked increase in depression-related psychological disorders. However, little is known about the specific status and factors influencing the impact of the pandemic on student mental health. Addressing this gap, this study examines the body dissatisfaction, physical activity, and sleep of university students during the pandemic, and uses their levels of depression to provide a theoretical basis for the development of mental health interventions for university students in the post-epidemic era. To achieve this, a total of 1,258 university students were randomly recruited for this cross-sectional study. Collected data included respondents' anthropometric measurements, body dissatisfaction levels, dietary habits, sleep status, physical activity levels, and depression levels. The overall detection rate of depression was 25.4%, with higher levels of depression among women. Multiple regression analysis showed that the PSQI score (β = 1.768, P < 0.01) and physical activity scores (β = -0.048, P < 0.01) were significant predictors of depression in men, while the PSQI score (β = 1.743, P < 0.01) and body dissatisfaction scores (β = 0.917, P < 0.01) were significant predictors of depression in women. Mental health problems were prevalent among university students during the COVID-19 pandemic. Results indicate the possibility of alleviating depression among university students by improving their body dissatisfaction, physical activity, and sleep. However, as this study was limited to Ganzhou City, it is challenging to extrapolate the findings to other populations. As this was a cross-sectional study, a causal relationship between depression levels and lifestyle habits cannot be determined

Effect of astragaloside IV on indoxyl sulfate-induced kidney injury in mice via attenuation of oxidative stress

Abstract Background Astragalus membranaceus, a traditional Chinese medicine (TCM), has been widely used in the treatment of chronic kidney disease (CKD) in China. Astragaloside IV is one of the major compounds of Astragalus membranaceus. Recent research has shown that astragaloside IV demonstrates pharmacological effects, such as anti-inflammatory, anti-fibrotic and anti-oxidative stress activities. Our aim was to investigate the effects of astragaloside IV on indoxyl sulfate (IS)-induced kidney injury in vivo, and to study the underlying mechanism. Methods Forty C57BL/6 mice with ½ nephrectomy were divided into four groups: control group (n = 10), IS group (n = 10), IS plus 10 mg/kg of astragaloside IV group (n = 10) and IS plus 20 mg/kg of astragaloside IV group (n = 10). IS intraperitoneal injection and astragaloside IV treatment were administered continuously for 1 month. Next, the blood urea nitrogen (BUN) level, serum IS level, tubulointerstitial injury, renal oxidative stress and inflammatory injury were assessed. Results The IS intraperitoneal injection mouse group showed increasing levels of serum IS, BUN, tubulointerstitial injury, renal oxidative stress and inflammatory injury. Astragaloside IV treatment couldn’t reduce the serum IS level or renal nuclear factor-κB and interleukin-1β levels. However, 20 mg/kg astragaloside IV treatment reduced the BUN level and significantly attenuated IS-induced tubulointerstitial injury. Renal oxidative stress was decreased by the administration of astragaloside IV. Conclusions These results suggest that astragaloside IV prevents IS-induced tubulointerstitial injury by ameliorating oxidative stress and may be a promising agent for the treatment of uremia toxin-induced injury