Toward a New Approach for Tuning Regularization Hyperparameter in NMF

Linear Dimensionality Reduction (LDR) methods has gained much attention in the last decades and has been used in the context of data mining applications to reconstruct a given data matrix. The effectiveness of low rank models in data science is justified by the fact that one can suppose that each row or column in the data matrix is associated to a bounded latent variable, and entries of the matrix are generated by applying a piece-wise analytic function to these latent variables. Formally, LDR can be mathematically formalized as optimization problems at which regularization terms can be often added to enforce particular constraints emphasizing useful properties in data. From this point of view, the tune of the regularization hyperparameters (HPs), controlling the weight of the additional constraints, represents an interesting problem to be solved automatically rather than by a trial and error approach. In this work, we focus on the role the regularization HPs act in Nonnegative Matrix Factorizations (NMF) context and how their right choice can affect further results, proposing a complete overview and new directions for a novel approach. Moreover, a novel bilevel formulation of the regularization HP selection is proposed which incorporates the HP choice directly in the unsupervised algorithm as a part of the updating process

Methods for Hyperparameters Optimization in Learning Approaches: an overview,

Automatic learning research focuses on the development of methods capable of extracting useful information from a given dataset. A large variety of learning methods exists, ranging from biologically inspired neural networks to statistical methods. A common trait in these methods is that they are parameterized by a set of hyperparameters, which must be set appropriately by the user to maximize the usefulness of the learning approach. In this paper we review hyperparameter tuning and discuss its main challenges from an optimization point of view. We provide an overview on the most important approaches for hyperparameter optimization problem, comparing them in terms of advantages and disadvantages, focusing on Gradient-based Optimization

Bi-level algorithm for optimizing hyperparameters in penalized nonnegative matrix factorization

Learning approaches rely on hyperparameters that impact the algorithm's performance and affect the knowledge extraction process from data. Recently, Nonnegative Matrix Factoriza-tion (NMF) has attracted a growing interest as a learning algorithm. This technique cap-tures the latent information embedded in large datasets while preserving feature proper-ties. NMF can be formalized as a penalized optimization task in which tuning the penalty hyperparameters is an open issue. The current literature does not provide any general framework addressing this task. This study proposes to express the penalty hyperparam-eters problem in NMF in terms of a bi-level optimization. We design a novel algorithm, named Alternating Bi-level (AltBi), which incorporates the hyperparameters tuning proce-dure into the updates of NMF factors. Results of the existence and convergence of numer-ical solutions, under appropriate assumptions, are studied, and numerical experiments are provided.& COPY; 2023 Elsevier Inc. All rights reserved

Detecting Anomalies in Marine Data: A Framework for Time Series Analysis

An ensemble framework for the analysis of time series from marine backgrounds is proposed to finally identify and classify anomalies in data time series collected from European Union's Earth Observation Programme Copernicus and Marine-EO project. The framework aims to estimate a prediction model for anomalies detection when new records are explored and then rank the magnitude of the anomalies eventually detected in some biogeochemical parameters of marine and ocean waters, such as chlorophyll-a concentrations, surface temperature profiles and dissolved oxygen

VAT photopolymerization 3D printing optimization of high aspect ratio structures for additive manufacturing of chips towards biomedical applications

Organ-on-chip and Lab-on-chip are microfluidic devices widely applied in the biomedical field. They are traditionally produced by soft lithography: starting from a mold fabricated by optical photolithography, a Pol-ydimethylsiloxane (PDMS) device is obtained by casting and baking. While this technique offers the possibility to produce features with high resolution, it is not flexible enough to respond to the necessity of customization and prototyping. In this study, we propose as alternative the production of devices by digital light processing (DLP), a vat photopolymerization technology, in combination with a commercially available, biocompatible resin. Studying the process factors by a statistical methodology called Design of Experiment (DoE), we were able to achieve small features with high aspect ratio (60). DoE method allowed us to have a deep understanding of the process without the need of any physical inspection of the involved phenomena, and to generate empirical models, correlating the process factors to the dimensions of the final printed object. We proved that this opti-mization was beneficial also in terms of transparency (evaluated by UV-Vis spectrophotometry), and mechanical strength (evaluated by a compression test) of the printed resin. Finally, a proof-of-concept microfluidic device was fabricated, sealed to a PDMS membrane through an oxygen plasma treatment, and tested against leakage on a microfluidic circuit for one week. As result, we proved that DLP printing is not only a suitable method to develop microfluidic devices, but if correctly optimized it can also reproduce small features in the order of tens of micrometers rapidly

A new ensemble method for detecting anomalies in gene expression matrices

One of the main problems in the analysis of real data is often related to the presence of anomalies. Namely, anomalous cases can both spoil the resulting analysis and contain valuable information at the same time. In both cases, the ability to detect these occurrences is very important. In the biomedical field, a correct identification of outliers could allow the development of new biological hypotheses that are not considered when looking at experimental biological data. In this work, we address the problem of detecting outliers in gene expression data, focusing on microarray analysis. We propose an ensemble approach for detecting anomalies in gene expression matrices based on the use of Hierarchical Clustering and Robust Principal Component Analysis, which allows us to derive a novel pseudo-mathematical classification of anomalies

The 5.5–4.5 kyr climatic transition as recorded by the sedimentation pattern of coastal deposits of the Apulia region, southern Italy

Coastal marine Holocene deposits of the Apulia region, considered as indicators of palaeoclimatic conditions, were studied. Our data show that (1) up to c. 5500 cal. yr BP, a phase of accumulation of flint pebbles from the Gargano headland occurred at the Riviera sud di Manfredonia (Adriatic coast); their transport from the Gargano headland (north of the study site) is incompatible with the current northward littoral drift and is best explained by a prevalence and dominance of NE and E winds and (2) after c. 4500 cal. yr BP, there was a rapid accumulation of sediments at the Marina di Ugento (Ionian coast), which is best explained by a prevalence and dominance of S, SW and SE winds. The two different wind regimes identified can be explained by a change in the mean pressure configuration in the central Mediterranean. The first phase (until c. 5500 cal. yr BP) consisted of more frequent cyclogenesis to the east-southeast of the Italian Peninsula, followed by a second phase (from c. 4500 cal. yr BP) of more frequent cyclogenesis to the west-northwest. The period between 5500 and 4500 cal. yr BP represents a transitional phase between the two different regimes. In other words, there was a ‘retreat’ of the central Mediterranean cyclogenesis towards the west-northwest. This pattern is contemporaneous with the termination of the African Humid period. We interpret both the ‘retreat’ of the Mediterranean cyclogenesis and the termination of the African Humid period as the expression of an expansion of the tropical dry Saharan belt

Ataluren improves myelopoiesis and neutrophil chemotaxis by restoring ribosome biogenesis and reducing p53 levels in Shwachman–Diamond syndrome cells

Shwachman-Diamond syndrome (SDS) is characterized by neutropenia, exocrine pancreatic insufficiency and skeletal abnormalities. SDS bone marrow haematopoietic progenitors show increased apoptosis and impairment in granulocytic differentiation. Loss of Shwachman-Bodian-Diamond syndrome (SBDS) expression results in reduced eukaryotic 80S ribosome maturation. Biallelic mutations in the SBDS gene are found in ~90% of SDS patients, ~55% of whom carry the c.183-184TA>CT nonsense mutation. Several translational readthrough-inducing drugs aimed at suppressing nonsense mutations have been developed. One of these, ataluren, has received approval in Europe for the treatment of Duchenne muscular dystrophy. We previously showed that ataluren can restore full-length SBDS protein synthesis in SDS-derived bone marrow cells. Here, we extend our preclinical study to assess the functional restoration of SBDS capabilities in vitro and ex vivo. Ataluren improved 80S ribosome assembly and total protein synthesis in SDS-derived cells, restored myelopoiesis in myeloid progenitors, improved neutrophil chemotaxis in vitro and reduced neutrophil dysplastic markers ex vivo. Ataluren also restored full-length SBDS synthesis in primary osteoblasts, suggesting that its beneficial role may go beyond the myeloid compartment. Altogether, our results strengthened the rationale for a Phase I/II clinical trial of ataluren in SDS patients who harbour the nonsense mutation

Edoxaban versus warfarin in patients with atrial fibrillation

Contains fulltext : 125374.pdf (publisher's version ) (Open Access)BACKGROUND: Edoxaban is a direct oral factor Xa inhibitor with proven antithrombotic effects. The long-term efficacy and safety of edoxaban as compared with warfarin in patients with atrial fibrillation is not known. METHODS: We conducted a randomized, double-blind, double-dummy trial comparing two once-daily regimens of edoxaban with warfarin in 21,105 patients with moderate-to-high-risk atrial fibrillation (median follow-up, 2.8 years). The primary efficacy end point was stroke or systemic embolism. Each edoxaban regimen was tested for noninferiority to warfarin during the treatment period. The principal safety end point was major bleeding. RESULTS: The annualized rate of the primary end point during treatment was 1.50% with warfarin (median time in the therapeutic range, 68.4%), as compared with 1.18% with high-dose edoxaban (hazard ratio, 0.79; 97.5% confidence interval [CI], 0.63 to 0.99; P<0.001 for noninferiority) and 1.61% with low-dose edoxaban (hazard ratio, 1.07; 97.5% CI, 0.87 to 1.31; P=0.005 for noninferiority). In the intention-to-treat analysis, there was a trend favoring high-dose edoxaban versus warfarin (hazard ratio, 0.87; 97.5% CI, 0.73 to 1.04; P=0.08) and an unfavorable trend with low-dose edoxaban versus warfarin (hazard ratio, 1.13; 97.5% CI, 0.96 to 1.34; P=0.10). The annualized rate of major bleeding was 3.43% with warfarin versus 2.75% with high-dose edoxaban (hazard ratio, 0.80; 95% CI, 0.71 to 0.91; P<0.001) and 1.61% with low-dose edoxaban (hazard ratio, 0.47; 95% CI, 0.41 to 0.55; P<0.001). The corresponding annualized rates of death from cardiovascular causes were 3.17% versus 2.74% (hazard ratio, 0.86; 95% CI, 0.77 to 0.97; P=0.01), and 2.71% (hazard ratio, 0.85; 95% CI, 0.76 to 0.96; P=0.008), and the corresponding rates of the key secondary end point (a composite of stroke, systemic embolism, or death from cardiovascular causes) were 4.43% versus 3.85% (hazard ratio, 0.87; 95% CI, 0.78 to 0.96; P=0.005), and 4.23% (hazard ratio, 0.95; 95% CI, 0.86 to 1.05; P=0.32). CONCLUSIONS: Both once-daily regimens of edoxaban were noninferior to warfarin with respect to the prevention of stroke or systemic embolism and were associated with significantly lower rates of bleeding and death from cardiovascular causes. (Funded by Daiichi Sankyo Pharma Development; ENGAGE AF-TIMI 48 ClinicalTrials.gov number, NCT00781391.)