The Paradox of Noise: An Empirical Study of Noise-Infusion Mechanisms to Improve Generalization, Stability, and Privacy in Federated Learning

In a data-centric era, concerns regarding privacy and ethical data handling grow as machine learning relies more on personal information. This empirical study investigates the privacy, generalization, and stability of deep learning models in the presence of additive noise in federated learning frameworks. Our main objective is to provide strategies to measure the generalization, stability, and privacy-preserving capabilities of these models and further improve them. To this end, five noise infusion mechanisms at varying noise levels within centralized and federated learning settings are explored. As model complexity is a key component of the generalization and stability of deep learning models during training and evaluation, a comparative analysis of three Convolutional Neural Network (CNN) architectures is provided. The paper introduces Signal-to-Noise Ratio (SNR) as a quantitative measure of the trade-off between privacy and training accuracy of noise-infused models, aiming to find the noise level that yields optimal privacy and accuracy. Moreover, the Price of Stability and Price of Anarchy are defined in the context of privacy-preserving deep learning, contributing to the systematic investigation of the noise infusion strategies to enhance privacy without compromising performance. Our research sheds light on the delicate balance between these critical factors, fostering a deeper understanding of the implications of noise-based regularization in machine learning. By leveraging noise as a tool for regularization and privacy enhancement, we aim to contribute to the development of robust, privacy-aware algorithms, ensuring that AI-driven solutions prioritize both utility and privacy

Time-series Analysis for Detecting Structure Changes and Suspicious Accounting Activities in Public Software Companies

AbstractThis paper offers a novel methodology using several new ratios and comparison approaches to investigate public software companies’ financial activities and condition. The methodology focuses on time-series data mining, monitoring and analyzing. The dataset is based on 100 U.S. software companies with least ten-year SEC verified income statement, balance sheets and cash flow statement. The contribution of this paper is creating and applying several new financial ratios combined with traditional approach to detect companies’ financial structure changes and accounts manipulation. For cash flow statement operating section, our proposed major account to operating net cash inflow and outflow ratios provide a better visualization of the cash sources and usage, which help analysts to observe major cash flow structure changes and make predication. For investing section, our proposed investing cash flow growth contribution ratio is used to identify irregular investment behavior. Combining with the traditional financial ratio tests, we believe that our approach significantly facilitates early detection on suspicious financial activities and the evaluation of its financial status

Papillary Thyroid Carcinoma Intertwined with Hashimoto’s Thyroiditis: An Intriguing Correlation

Illustrating the ancient link connecting inflammation with cancer, the correlation of papillary thyroid carcinoma (PTC) with Hashimoto’s thyroiditis (HT) has long been pursued as intersection of autoimmunity-induced chronic inflammation and tumor-induced immunity. The dramatic rise of the incidence of PTC οver the last decades—the main culprit for “thyroid cancer (TC) epidemic”—parallels the increasing incidence of HT, potentially reflecting a pathogenetic link that could be harnessed in diagnostics and therapeutics. Prompted by this perspective, in the present chapter, we dissect the hitherto elusive interrelationship of PTC with HT, focusing on four issues: firstly, an unresolved conundrum is whether PTC emerges due to or notwithstanding immune response or mirrors the “tumor defense-induced autoimmunity.” Secondly, the interrelationship of HT with PTC may be merely epiphenomenon of selection bias inherent in thyroidectomy series. Thirdly, the impact of HT on coexistent PTC is equivocal—host protective versus tumor protective. Fourthly, translating serum concentrations of thyroid autoantibodies and thyroid-stimulating hormone (TSH) into predictive and prognostic PTC biomarkers dichotomizes, till now, the researchers. In the era of precision medicine, illuminating whether HT precipitates PTC or vice versa is awaited with anticipation in order to refine the preventive and therapeutic policy counteracting “TC epidemic.

Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations

In the growing world of artificial intelligence, federated learning is a distributed learning framework enhanced to preserve the privacy of individuals' data. Federated learning lays the groundwork for collaborative research in areas where the data is sensitive. Federated learning has several implications for real-world problems. In times of crisis, when real-time decision-making is critical, federated learning allows multiple entities to work collectively without sharing sensitive data. This distributed approach enables us to leverage information from multiple sources and gain more diverse insights. This paper is a systematic review of the literature on privacy-preserving machine learning in the last few years based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Specifically, we have presented an extensive review of supervised/unsupervised machine learning algorithms, ensemble methods, meta-heuristic approaches, blockchain technology, and reinforcement learning used in the framework of federated learning, in addition to an overview of federated learning applications. This paper reviews the literature on the components of federated learning and its applications in the last few years. The main purpose of this work is to provide researchers and practitioners with a comprehensive overview of federated learning from the machine learning point of view. A discussion of some open problems and future research directions in federated learning is also provided

Bayesian Kernel Methods for Non-Gaussian Distributions: Binary and Multi- class Classification Problems

Project Objective: The objective of this project is to develop a Bayesian kernel model built around non- Gaussian prior distributions to address binary and multi-class classification problems.Recent advances in data mining have integrated kernel functions with Bayesian probabilistic analysis of Gaussian distributions. These machine learning approaches can incorporate prior information with new data to calculate probabilistic rather than deterministic values for unknown parameters. This paper analyzes extensively a specific Bayesian kernel model that uses a kernel function to calculate a posterior beta distribution that is conjugate to the prior beta distribution. Numerical testing of the beta kernel model on several benchmark data sets reveal that this model’s accuracy is comparable with those of the support vector machine and relevance vector machine, and the model runs more quickly than the other algorithms. When one class occurs much more frequently than the other class, the beta kernel model often outperforms other strategies to handle imbalanced data sets. If data arrive sequentially over time, the beta kernel model easily and quickly updates the probability distribution, and this model is more accurate than an incremental support vector machine algorithm for online learning when fewer than 50 data points are available.U.S. Army Research OfficeSponsor/Monitor's Report Number(s): 61414-MA-II.3W911NF-12-1-040

Synthesis and anticancer activity of novel 3,6-disubstituted 1,2,4-triazolo-[3,4-b]-1,3,4-thiadiazole derivatives

AbstractThe development of new antitumor agents is one of the most pressing research areas in medicinal chemistry and medicine. The importance of triazole and thiadiazole rings as scaffolds present in a wide range of therapeutic agents has been well reported and has driven the synthesis of a large number of novel antitumor agents. The presence of these heterocycles furnishes extensive synthetic possibilities due to the presence of several reaction sites. Prompted by these data we designed, synthesized and evaluated a series of novel 3,6-disubstituted 1,2,4-triazolo-[3,4-b]-1,3,4-thiadiazole derivatives as potential anticancer agents. We emphasized in the strategy of combining two chemically different but pharmacologically compatible molecules (the 1,2,4-triazole and 1,3,4 thiadiazole) in one frame. Several of the newly synthesized 1,2,4-triazolo-[3,4-b]-1,3,4-thiadiazole derivatives showed substantial cytostatic and cytotoxic antineoplastic activity invitro, while they have produced relatively low acute toxicities invivo, giving potentially high therapeutic ratios. Insilico screening has revealed several protein targets including apoptotic protease-activating factor 1 (APAF1) and tyrosine-protein kinase HCK which may be involved in the biological activities of active analogues

Novel Docosahexaenoic Acid Ester of Phloridzin Inhibits Proliferation and Triggers Apoptosis in an In Vitro Model of Skin Cancer

Skin cancer is among the most common cancer types accompanied by rapidly increasing incidence rates, thus making the development of more efficient therapeutic approaches a necessity. Recent studies have revealed the potential role of decosahexaenoic acid ester of phloridzin (PZDHA) in suppressing proliferation of liver, breast, and blood cancer cell lines. In the present study, we investigated the cytotoxic potential of PZDHA in an in vitro model of skin cancer consisting of melanoma (A375), epidermoid carcinoma (A431), and non-tumorigenic (HaCaT) cell lines. Decosahexaenoic acid ester of phloridzin led to increased cytotoxicity in all cell lines as revealed by cell viability assays. However, growth inhibition and induction of both apoptosis and necrosis was more evident in melanoma (A375) and epidermoid carcinoma (A431) cells, whereas non-tumorigenic keratinocytes (HaCaT) appeared to be more resistant as detected by flow cytometry. More specifically, PZDHA-induced cell cycle growth arrest at the G2/M phase in A375 and A431 cells in contrast to HaCaT cells, which were growth arrested at the G0/G1 phase. Elevated intracellular generation of reactive oxygen species ROS was detected in all cell lines. Overall, our findings support the potential of PZDHA as a novel therapeutic means against human skin cancer

Chemical Characterization and Biological Evaluation of \u3ci\u3eEpilobium parviflorum\u3c/i\u3e Extracts in an In Vitro Model of Human Malignant Melanoma

Malignant melanoma is an aggressive type of skin cancer characterised by high metastatic capacity and mortality rate. On the other hand, Epilobium parviflorum is known for its medicinal properties, including its anticancer potency. In this context, we aimed to (i) isolate various extracts of E. parviflorum, (ii) characterize their phytochemical content, and (iii) determine their cytotoxic potential in an in vitro model of human malignant melanoma. To these ends, we utilized various spectrophotometric and chromatographic (UPLC-MS/MS) approaches to document the higher content of the methanolic extract in polyphenols, soluble sugars, proteins, condensed tannins, and chlorophylls -a and -b as opposed to those of dichloromethane and petroleum. In addition, the cytotoxicity profiling of all extracts was assessed through a colorimetric-based Alamar Blue assay in human malignant melanoma (A375 and COLO-679) as well as non-tumorigenic immortalized keratinocyte (HaCaT) cells. Overall, the methanolic extract was shown to exert significant cytotoxicity, in a timeand concentration-dependent manner, as opposed to the other extracts. The observed cytotoxicity was confined only to human malignant melanoma cells, whereas non-tumorigenic keratinocyte cells remained relatively unaffected. Finally, the expression levels of various apoptotic genes were assessed by qRT-PCR, indicating the activation of both intrinsic and extrinsic apoptotic cascades. Supplement attached below

An Evaluation of the Anti-Carcinogenic Response of Major Isothiocyanates in Non-Metastatic and Metastatic Melanoma Cells

Malignant melanoma is one of the most deadly types of solid cancers, a property mainly attributed to its highly aggressive metastatic form. On the other hand, different classes of isothiocy- anates, a class of phytochemicals, present in cruciferous vegetables have been characterized by considerable anti-cancer activity in both in vitro and in vivo experimental models. In the current study, we investigated the anti-cancer response of five isothiocyanates in an in vitro model of melanoma consisting of non-metastatic (A375, B16F-10) and metastatic (VMM1, Hs294T) malignant melanoma as well as non-melanoma epidermoid carcinoma (A431) and non-tumorigenic melanocyte-neighboring keratinocyte (HaCaT) cells. Our aim was to compare different endpoints of cytotoxicity (e.g., reactive oxygen species, intracellular glutathione content, cell cycle growth arrest, apoptosis and necrosis) descriptive of an anti-cancer response between non-metastatic and metastatic melanoma as well as non-melanoma epidermoid carcinoma and non-tumorigenic cells. Our results showed that exposure to isothiocyanates induced an increase in intracellular reactive oxygen species and glutathione contents between non-metastatic and metastatic melanoma cells. The distribution of cell cycle phases followed a similar pattern in a manner where non-metastatic and metastatic melanoma cells appeared to be growth arrested at the G2/M phase while elevated levels of metastatic melanoma cells were shown to be at sub G1 phase, an indicator of necrotic cell death. Finally, metastatic melanoma cells were more sensitive apoptosis and/or necrosis as higher levels were observed compared to non-melanoma epidermoid carcinoma and non-tumorigenic cells. In general, non-mela- noma epidermoid carcinoma and non-tumorigenic cells were more resistant under any experimental exposure condition. Overall, our study provides further evidence for the potential development of isothiocyanates as promising anti-cancer against non-metastic and metastatic melanoma cells, a property specific for these cells and not shared by non-melanoma epidermoid carcinoma or non-tumorigenic melanocyte cells

Polyphenolics, glucosinolates and isothiocyanates profiling of aerial parts of \u3ci\u3eNasturtium officinale\u3c/i\u3e (Watercress)

Watercress (Nasturtium officinale) is a rich source of secondary metabolites with disease-preventing and/or health-promoting properties. Herein, we have utilized extraction procedures to isolate fractions of polyphenols, glucosinolates and isothiocyanates to determine their identification, and quantification. In doing so, we have utilized reproducible analytical methodologies based on liquid chromatography with tandem mass spectrometry by either positive or negative ion mode. Due to the instability and volatility of isothiocyanates, we followed an ammonia derivatization protocol which converts them into respective ionizable thiourea derivatives. The analytes’ content distribution map was created on watercress flowers, leaves and stems. We have demonstrated that watercress contains significantly higher levels of gluconasturtiin, phenethyl isothiocyanate, quercetin-3-O-rutinoside and isorhamnetin, among others, with their content decreasing from flowers (82.11 ± 0.63, 273.89 ± 0.88, 1459.30 ± 12.95 and 289.40 ± 1.37 ng/g of dry extract respectively) to leaves (32.25 ± 0.74, 125.02 ± 0.52, 1197.86 ± 4.24 and 196.47 ± 3.65 ng/g of det extract respectively) to stems (9.20 ± 0.11, 64.7 ± 0.9, 41.02 ± 0.18, 65.67 ± 0.84 ng/g of dry extract respectivbely). Pearson’s correlation analysis has shown that the content of isothiocyanates doesn’t depend only on the bioconversion of individual glucosinolates but also on other glucosinolates of the same group. Overall, we have provided comprehensive analytical data of the major watercress metabolites thereby providing an opportunity to exploit different parts of watercress for potential therapeutic applications