Defense Against Model Extraction Attacks on Recommender Systems

The robustness of recommender systems has become a prominent topic within the research community. Numerous adversarial attacks have been proposed, but most of them rely on extensive prior knowledge, such as all the white-box attacks or most of the black-box attacks which assume that certain external knowledge is available. Among these attacks, the model extraction attack stands out as a promising and practical method, involving training a surrogate model by repeatedly querying the target model. However, there is a significant gap in the existing literature when it comes to defending against model extraction attacks on recommender systems. In this paper, we introduce Gradient-based Ranking Optimization (GRO), which is the first defense strategy designed to counter such attacks. We formalize the defense as an optimization problem, aiming to minimize the loss of the protected target model while maximizing the loss of the attacker's surrogate model. Since top-k ranking lists are non-differentiable, we transform them into swap matrices which are instead differentiable. These swap matrices serve as input to a student model that emulates the surrogate model's behavior. By back-propagating the loss of the student model, we obtain gradients for the swap matrices. These gradients are used to compute a swap loss, which maximizes the loss of the student model. We conducted experiments on three benchmark datasets to evaluate the performance of GRO, and the results demonstrate its superior effectiveness in defending against model extraction attacks

G-protein-coupled estrogen receptor agonist G-1 inhibits the proliferation of breast cancer cells through induction of apoptosis and cycle arrest

Purpose: To determine the effect of G-1, a G-protein-linked estrogen receptor (GPER) agonist on apoptosis, cell cycle, and proliferative potential of mammary tumor cells, and the associated mechanisms of action. Methods: Three groups of human breast cancer cell line MDA-MB-231 were used: control group, estradiol (E2) group and G-1 group. Control group was not treated. The effects of treatment (10 M G1) on cell proliferation were determined and compared amongst the groups. Cell cycle distribution and apoptosis were determined while expression levels of proteins related to pi3k/AKT/MAPK were assessed by western blotting. Results: Apoptosis was significantly reduced in E2 group relative to control, but was enhanced in G-1 group, when compared to the other 2 groups (p < 0.05). There were marked down-regulations in protein levels of cylinb1, p21, caspase 6, p53, p-ERK in E2 group, relative to the corresponding expression levels in the control group. Conclusion: GPER agonist G-1 suppresses the proliferation of mammary tumor cells and induces apoptotic changes and cycle blockage in the cells via inhibition of pi3k/AKT pathway and activation of MAPKs pathway. Thus, GPER is a potential target in breast tumor treatment, and G-1 is a potential new anti-tumor drug

EEG-Derived Voice Signature for Attended Speaker Detection

\textit{Objective:} Conventional EEG-based auditory attention detection (AAD) is achieved by comparing the time-varying speech stimuli and the elicited EEG signals. However, in order to obtain reliable correlation values, these methods necessitate a long decision window, resulting in a long detection latency. Humans have a remarkable ability to recognize and follow a known speaker, regardless of the spoken content. In this paper, we seek to detect the attended speaker among the pre-enrolled speakers from the elicited EEG signals. In this manner, we avoid relying on the speech stimuli for AAD at run-time. In doing so, we propose a novel EEG-based attended speaker detection (E-ASD) task. \textit{Methods:} We encode a speaker's voice with a fixed dimensional vector, known as speaker embedding, and project it to an audio-derived voice signature, which characterizes the speaker's unique voice regardless of the spoken content. We hypothesize that such a voice signature also exists in the listener's brain that can be decoded from the elicited EEG signals, referred to as EEG-derived voice signature. By comparing the audio-derived voice signature and the EEG-derived voice signature, we are able to effectively detect the attended speaker in the listening brain. \textit{Results:} Experiments show that E-ASD can effectively detect the attended speaker from the 0.5s EEG decision windows, achieving 99.78\% AAD accuracy, 99.94\% AUC, and 0.27\% EER. \textit{Conclusion:} We conclude that it is possible to derive the attended speaker's voice signature from the EEG signals so as to detect the attended speaker in a listening brain. \textit{Significance:} We present the first proof of concept for detecting the attended speaker from the elicited EEG signals in a cocktail party environment. The successful implementation of E-ASD marks a non-trivial, but crucial step towards smart hearing aids.Comment: 8 pages, 2 figure

What can we learn from failed international companies?

Purpose – The purpose of this paper is to examine how organisational closure can inform strategic foresight. Design/methodology/approach – We draw insights from illustrative cases, i.e. Swissair, Sabena and Cameroon Airlines to illustrate our theoretical analysis. Findings – The study shed light on the effects of internal and external factors in precipitating business closures. We established that top executives’ hubris, resistance to change and over-reliance on external consultants are some of precursors to organisational closure. Research limitations/implications – Our analysis provides a range of strategies that organisations can pursue to learn from other firms’ closure and improve their survivability and chances of future success. Originality/value – In spite of a growing body of literature on strategic foresight and organisational closure, the literature has largely developed in isolation and as such our understanding of the relationship between strategic foresight and organisational closure as remained severely limited. The paper integrates these two streams of research to enrich our understanding of how firms can learn from others to improve their strategic foresight

Business failure research

In spite of a growing body of literature on business failures in China and effects of government policy, our understanding of the current state of knowledge remains unclear. The study advances research on the subject by developing the “four-parties” framework to review and synthesise the literature. The paper lays the groundwork for an integrated understanding of the causes and consequences of business failure. In sharp contrast with the evolution and development of Western-based business failure research, much of the literature on China and Chinese firms has focused largely on business failure prediction models by bypassing the traditional evolution from qualitative case study/story approaches to quantitative-based approaches. The study outlines the important implications and promising avenues for future research

What can we learn from failed international companies?

Purpose – The purpose of this paper is to examine how organisational closure can inform strategic foresight. Design/methodology/approach – We draw insights from illustrative cases, i.e. Swissair, Sabena and Cameroon Airlines to illustrate our theoretical analysis. Findings – The study shed light on the effects of internal and external factors in precipitating business closures. We established that top executives’ hubris, resistance to change and over-reliance on external consultants are some of precursors to organisational closure. Research limitations/implications – Our analysis provides a range of strategies that organisations can pursue to learn from other firms’ closure and improve their survivability and chances of future success. Originality/value – In spite of a growing body of literature on strategic foresight and organisational closure, the literature has largely developed in isolation and as such our understanding of the relationship between strategic foresight and organisational closure as remained severely limited. The paper integrates these two streams of research to enrich our understanding of how firms can learn from others to improve their strategic foresight

Business failure research

In spite of a growing body of literature on business failures in China and effects of government policy, our understanding of the current state of knowledge remains unclear. The study advances research on the subject by developing the “four-parties” framework to review and synthesise the literature. The paper lays the groundwork for an integrated understanding of the causes and consequences of business failure. In sharp contrast with the evolution and development of Western-based business failure research, much of the literature on China and Chinese firms has focused largely on business failure prediction models by bypassing the traditional evolution from qualitative case study/story approaches to quantitative-based approaches. The study outlines the important implications and promising avenues for future research

MiR-135a-5p suppresses breast cancer cell proliferation, migration, and invasion by regulating BAG3

Background: MicroRNAs (miRNAs) are involved in the progression of diverse human cancers. This work aimed to delve into how microRNA-135a-5p (miR-135a-5p) affects the biological behaviors of Breast Cancer (BC) cells. Methods: Gene Expression Omnibus (GEO) datasets were used to analyze the expression differences of miR-135a-5p in cancer tissues of BC patients. Quantitative real-time PCR and western blot were conducted to detect miR-135a-5p and Bcl-2 Associated Athanogene (BAG3) expression levels in BC tissues and cells, respectively. The proliferation, migration, invasion, and cell cycle of BC cells were detected by cell counting kit-8 assay, BrdU assay, wound healing assay, transwell assay, and flow cytometry. The targeted relationship between miR-135a-5p and BAG3 mRNA 3′UTR predicted by bioinformatics was further testified by a dual-luciferase reporter gene assay. Pearson's correlation analysis was adopted to analyze the correlation between miR-135a-5p expression and BAG3 expression. The downstream pathways of BAG3 were analyzed by the LinkedOmics database. Results: MiR-135a-5p was significantly down-regulated and BAG3 expression was significantly raised in BC tissues. MiR-135a-5p overexpression repressed the viability, migration and invasion of BC cells, and blocked cell cycle progression in G0/G1 phase while inhibiting miR-135a-5p worked oppositely. BAG3 was verified as a target of miR-135a-5p. Overexpression of BAG3 reversed the impacts of miR-135a-5p on the malignant biological behaviors of BC cells. The high expression of BAG3 was associated with the activation of the cell cycle, mTOR and TGF-β signaling pathways. Conclusion: MiR-135a-5p regulates BAG3 to repress the growth, migration, invasion, and cell cycle progression of BC cells