Robocall and fake caller-id detection

Spam phone calls are a source of user unhappiness, and a tool for unscrupulous operators to prey on vulnerable individuals. Spam callers use increasingly sophisticated methods, e.g., disguising a call with a fake caller-id, such that a receiver of the call is given an impression that someone from their contact list is calling. Robocalls, wherein an automated program originates phone calls that targets individuals, e.g., for unsolicited sales or other purposes are a source of annoyance for phone users. One approach to eliminate such calls is to require authentication by a call originating party. However, spam or robocallers are unlikely to identify themselves as such. Techniques described herein utilize signaling messages of a phone call to serve as a signature or fingerprint for the phone call. Legitimate phone calls have distinct signatures, while spam-calls, robocalls, and calls with fake caller-id have their own distinct pattern. This difference is leveraged to detect and thwart unwanted calls

Can the Black Lives Matter Movement Reduce Racial Disparities? Evidence from Medical Crowdfunding

Using high-frequency donation records from a major medical crowdfunding site and careful difference-in-difference analysis, we demonstrate that the 2020 BLM surge decreased the fundraising gap between Black and non-Black beneficiaries by around 50\%. The reduction is largely attributed to non-Black donors. Those beneficiaries in counties with moderate BLM activities were most impacted. We construct innovative instrumental variable approaches that utilize weekends and rainfall to identify the global and local effects of BLM protests. Results suggest a broad social movement has a greater influence on charitable-giving behavior than a local event. Social media significantly magnifies the impact of protests

Study on the Effectiveness of the Equity Incentive Plan of Private Enterprises in Zhuhai City: Taking TongWang Technology as an Example

The study of the effectiveness of equity incentive has always been the focus of the academic circle. Whether it is foreign or domestic, there is no conclusive evidence at present. This paper is divided into three parts: Firstly, it summarized the literature research conclusion of equity incentive at home and abroad. Secondly, the author analyzes the incentive scheme and the implementation effect of the equity incentive scheme of the same-looking science and technology as an example. Finally, the author puts forward the feasibility of improving equity incentive measures for private enterprises in China

Efficiency Analysis of Equity Incentive in Private Listed Companies-By Taking the Example of By-Health

At present, more and more private listed companies in our country realize the importance of corporate governance structure and equity structure, and also start to adopt a variety of equity incentive models to stimulate the business operators. How to evaluate the effect of private listed company's equity incentive measures? By taking the example of By-Health, this paper analyzes the effect of implementing equity incentive from financial performance, manager's behavior and market performance from three aspects: financial performance, manager's behavior and market performance, and puts forward relevant suggestions. With a view to providing useful reference and reference for improving the management of private enterprises and implementing equity incentives smoothly

MC-Stereo: Multi-peak Lookup and Cascade Search Range for Stereo Matching

Stereo matching is a fundamental task in scene comprehension. In recent years, the method based on iterative optimization has shown promise in stereo matching. However, the current iteration framework employs a single-peak lookup, which struggles to handle the multi-peak problem effectively. Additionally, the fixed search range used during the iteration process limits the final convergence effects. To address these issues, we present a novel iterative optimization architecture called MC-Stereo. This architecture mitigates the multi-peak distribution problem in matching through the multi-peak lookup strategy, and integrates the coarse-to-fine concept into the iterative framework via the cascade search range. Furthermore, given that feature representation learning is crucial for successful learn-based stereo matching, we introduce a pre-trained network to serve as the feature extractor, enhancing the front end of the stereo matching pipeline. Based on these improvements, MC-Stereo ranks first among all publicly available methods on the KITTI-2012 and KITTI-2015 benchmarks, and also achieves state-of-the-art performance on ETH3D. Code is available at https://github.com/MiaoJieF/MC-Stereo.Comment: Accepted to 3DV 202

Genetic associations in ankylosing spondylitis: circulating proteins as drug targets and biomarkers

BackgroundAnkylosing spondylitis (AS) is a complex condition with a significant genetic component. This study explored circulating proteins as potential genetic drug targets or biomarkers to prevent AS, addressing the need for innovative and safe treatments.MethodsWe analyzed extensive data from protein quantitative trait loci (pQTLs) with up to 1,949 instrumental variables (IVs) and selected the top single-nucleotide polymorphism (SNP) associated with AS risk. Utilizing a two-sample Mendelian randomization (MR) approach, we assessed the causal relationships between identified proteins and AS risk. Colocalization analysis, functional enrichment, and construction of protein-protein interaction networks further supported these findings. We utilized phenome-wide MR (phenMR) analysis for broader validation and repurposing of drugs targeting these proteins. The Drug-Gene Interaction database (DGIdb) was employed to corroborate drug associations with potential therapeutic targets. Additionally, molecular docking (MD) techniques were applied to evaluate the interaction between target protein and four potential AS drugs identified from the DGIdb.ResultsOur analysis identified 1,654 plasma proteins linked to AS, with 868 up-regulated and 786 down-regulated. 18 proteins (AGER, AIF1, ATF6B, C4A, CFB, CLIC1, COL11A2, ERAP1, HLA-DQA2, HSPA1L, IL23R, LILRB3, MAPK14, MICA, MICB, MPIG6B, TNXB, and VARS1) that show promise as therapeutic targets for AS or biomarkers, especially MAPK14, supported by evidence of colocalization. PhenMR analysis linked these proteins to AS and other diseases, while DGIdb analysis identified potential drugs related to MAPK14. MD analysis indicated strong binding affinities between MAPK14 and four potential AS drugs, suggesting effective target-drug interactions.ConclusionThis study underscores the utility of MR analysis in AS research for identifying biomarkers and therapeutic drug targets. The involvement of Th17 cell differentiation-related proteins in AS pathogenesis is particularly notable. Clinical validation and further investigation are essential for future applications

Drug Target Prediction Based on the Herbs Components: The Study on the Multitargets Pharmacological Mechanism of Qishenkeli Acting on the Coronary Heart Disease

In this paper, we present a case study of Qishenkeli (QSKL) to research TCM's underlying molecular mechanism, based on drug target prediction and analyses of TCM chemical components and following experimental validation. First, after determining the compositive compounds of QSKL, we use drugCIPHER-CS to predict their potential drug targets. These potential targets are significantly enriched with known cardiovascular disease-related drug targets. Then we find these potential drug targets are significantly enriched in the biological processes of neuroactive ligand-receptor interaction, aminoacyl-tRNA biosynthesis, calcium signaling pathway, glycine, serine and threonine metabolism, and renin-angiotensin system (RAAS), and so on. Then, animal model of coronary heart disease (CHD) induced by left anterior descending coronary artery ligation is applied to validate predicted pathway. RAAS pathway is selected as an example, and the results show that QSKL has effect on both rennin and angiotensin II receptor (AT1R), which eventually down regulates the angiotensin II (AngII). Bioinformatics combing with experiment verification can provide a credible and objective method to understand the complicated multitargets mechanism for Chinese herbal formula

Understanding tcp incast throughput collapse in datacenter networks

ABSTRACT TCP Throughput Collapse, also known as Incast, is a pathological behavior of TCP that results in gross under-utilization of link capacity in certain many-to-one communication patterns. This phenomenon has been observed by others in distributed storage, MapReduce and web-search workloads. In this paper we focus on understanding the dynamics of Incast. We use empirical data to reason about the dynamic system of simultaneously communicating TCP entities. We propose an analytical model to account for the observed Incast symptoms, identify contributory factors, and explore the efficacy of solutions proposed by us and by others