Incremental template updating for face recognition in home environments

The extreme variability of faces in smart environment applications, due to continuous changes in terms of pose, illumination and subject appearance (hairstyle, make-up, etc.), requires the relevant mode of variations of the subject's faces to be encoded in the templates and to be continuously updated based on new inputs. This work proposes a new video-based template updating approach suitable for home environments where the image acquisition process is totally unconstrained but a large amount of face data is available for continuous learning. A small set of labeled images is initially used to create the templates and the updating is then totally unsupervised. Although the method is here presented in conjunction with a subspace-based face recognition approach, it can be easily adapted to deal with different kinds of face representations. A thorough performance evaluation is carried out to show the efficacy and reliability of the proposed technique.     

Application of proteomic techniques to the study of urine and renal tissue

The increasing application of proteomic methods to biomedical research is providing us with important new information; it holds particular promise in advancing basic and clinical renal research, but whether proteomics can ever become a routine diagnostic tool in nephrology is still uncertain. Currently, proteomic techniques are used by many groups in the search for "biomarkers" of disease, especially kidney disease, because of the ready availability of urine as an "end-product" of renal function. However, the question as to whether any disease-specific biomarkers exist or can be identified by proteomics is also uncertain. A growing application of proteomics in biomedical research is to understand the mechanism(s) of disease. This brief review is selective; in it we consider examples of proteomic studies of human urine for biomarkers, others that have explored renal physiology, and still others that have begun to probe the proteome of organelles. No single approach is sufficiently comprehensive, and the pooled application of proteomics to renal research will undoubtedly improve our understanding of renal function and enable us to explore in more detail subcellular structures, and to characterize cellular processes at the molecular level. When combined with other techniques in renal research, proteomics, and related analytical methods could prove indispensable in modeling renal function, and perhaps also in diagnosis and management of renal disease.     

2D face recognition based on supervised subspace learning from 3D models

One of the main challenges in face recognition is represented by pose and illumination variations that drastically affect the recognition performance, as confirmed by the results of recent face recognition large-scale evaluations. This paper presents a new technique for face recognition, based on the joint use of 3D models and 2D images, specifically conceived to be robust with respect to pose and illumination changes. A 3D model of each user is exploited in the training stage (i.e. enrollment) to generate a large number of 2D images representing virtual views of the face with varying pose and illumination. Such images are then used to learn in a supervised manner a set of subspaces constituting the user's template. Recognition occurs by matching 2D images with the templates and no 3D information (neither images nor face models) is required. The experiments carried out confirm the efficacy of the proposed technique.     

The role of settling velocity formulation in the determination of gully pot trapping efficiency: comparison between analytical and experimental data

Roadside gully pots are the connecting points between surface runoff and the underground drainage network; therefore they can be considered as the most superficial component of urban drainage systems. Gully pots are supposed to trap particulate matter washed off the catchment surface, but also to collect and convey stormwater into the network. The continuous accumulation of particulate matter results in a progressive loss of the gully pot hydraulic conveyance, thereby increasing the probability of urban flooding during rainstorm events. This study has therefore the objective to determine which variables influence the gully pot capability of retaining solids (efficiency), both experimentally and analytically. Several laboratory tests have been performed on a simple plastic gully pot, with different inflow rates and using both mono and hetero-disperse particle samples. Particular attention has been given to the influence exerted by the way particle settling velocity is expressed: efficiency has been analytically determined by means of multiple settling velocity formulas proposed by various authors and eventually compared to experimental data. Results deriving from the adoption of each single settling velocity formula have been extensively analysed, showing fairly different outcomes.     

Exosomal MicroRNAs as Potential Biomarkers of Hepatic Injury and Kidney Disease in Glycogen Storage Disease Type Ia Patients

Glycogen storage disease type Ia (GSDIa) is an inherited metabolic disorder caused by mutations in the enzyme glucose-6-phosphatase-α (G6Pase-α). Affected individuals develop renal and liver complications, including the development of hepatocellular adenoma/carcinoma and kidney failure. The purpose of this study was to identify potential biomarkers of the evolution of the disease in GSDIa patients. To this end, we analyzed the expression of exosomal microRNAs (Exo-miRs) in the plasma exosomes of 45 patients aged 6 to 63 years. Plasma from age-matched normal individuals were used as controls. We found that the altered expression of several Exo-miRs correlates with the pathologic state of the patients and might help to monitor the progression of the disease and the development of late GSDIa-associated complications.     

Broad-Spectrum Antiviral Activity of the Amphibian Antimicrobial Peptide Temporin L and Its Analogs

The COVID-19 pandemic has evidenced the urgent need for the discovery of broad-spectrum antiviral therapies that could be deployed in the case of future emergence of novel viral threats, as well as to back up current therapeutic options in the case of drug resistance development. Most current antivirals are directed to inhibit specific viruses since these therapeutic molecules are designed to act on a specific viral target with the objective of interfering with a precise step in the replication cycle. Therefore, antimicrobial peptides (AMPs) have been identified as promising antiviral agents that could help to overcome this limitation and provide compounds able to act on more than a single viral family. We evaluated the antiviral activity of an amphibian peptide known for its strong antimicrobial activity against both Gram-positive and Gram-negative bacteria, namely Temporin L (TL). Previous studies have revealed that TL is endowed with widespread antimicrobial activity and possesses marked haemolytic activity. Therefore, we analyzed TL and a previously identified TL derivative (Pro³, DLeu⁹ TL, where glutamine at position 3 is replaced with proline, and the D-Leucine enantiomer is present at position 9) as well as its analogs, for their activity against a wide panel of viruses comprising enveloped, naked, DNA and RNA viruses. We report significant inhibition activity against herpesviruses, paramyxoviruses, influenza virus and coronaviruses, including SARS-CoV-2. Moreover, we further modified our best candidate by lipidation and demonstrated a highly reduced cytotoxicity with improved antiviral effect. Our results show a potent and selective antiviral activity of TL peptides, indicating that the novel lipidated temporin-based antiviral agents could prove to be useful additions to current drugs in combatting rising drug resistance and epidemic/pandemic emergencies.     

MKL-tree: an index structure for high-dimensional vector spaces

In this work, a novel hierarchical data structure for high dimensional data indexing is proposed. MKL-tree is based on dimensionality reduction operated by means of the MKL transform, a multi-space generalization of the KL transform. A local dimensionality reduction is performed at each node of the tree, allowing more selective features to be extracted and thus increasing the discriminating power of the index. The mathematical foundation for nodes and leaves representation and for the techniques aimed to manage the structure is detailed. Moreover, the algorithms for bulk loading MKL-tree (i.e., for creating the tree given a large number of objects simultaneously), for updating and splitting nodes after the insertion of new objects and for performing similarity searches are described. Results are reported for the comparison of MKL-tree with other well-known access methods in terms of I/O and CPU costs and precision of the result in the execution of similarity queries.     

Immunohistochemical study on the prognostic value of the expression of laminin and Ki-67 receptors in advanced gastric cancer

The expression of 67-KDa laminin receptor (LR) was investigated in a group of 75 patients who underwent curative gastrectomy for advanced gastric cancer, with special reference to the possible role in the tumor progression and in the overall survival. In 56 out of these 75 patients also the prognostic significance of proliferative activity was investigated using the monoclonal antibody Ki-67. The tumor LR expression and the Ki-67 labeling index (Ki-67 LI) were immunohistochemically determined in paraffin-embedded sections using the avidin-biotin immunoperoxidase method. The cumulative 5-years survival rate was 75.1% for patients without expression of LR, 52.6% for those with positive LR expression. Significant association between LR expression and depth of tumor invasion (p = 0.022) was found. By univariate analysis the presence of laminin receptor seemed to be associated with an higher risk of death (RR1.73-95% C.I. 0.71-4.20), but this effect disappeared after controlling for depth of tumor invasion. There was no significant relationship between the Ki-67 LI and wall invasion (p = 0.80) or nodal status (p = 0.73). The cumulative 5-year survival rates (95% CI) were 61.0% (35.3-79.2) in patients with Ki-67 index < 10%, 52.4% (29.7-70.9) with Ki-67 index = 10%-40%, 52.9% (27.6-73.0) with Ki-67 index > 40% and the differences were not statistically significant (p = 0.93). Also in multivariate analysis the proliferative activity did not independently affect survival (p = 0.98). An interaction between Ki-67 index and age was found and Ki-67 index > 40% was significantly associated with a poor prognosis in patients over 70 years old old (p = 0.002). In conclusion, tumor expression of laminin receptor could be correlated with gastric cancer aggressiveness, however its prognostic significance is already provided by depth of tumor invasion. The proliferative activity, determined with the monoclonal antibody Ki-67, does not seems to influence the survival except in elderly patients (> or = 70 years old).     

DLP 4D-Printing of Remotely,Modularly, and Selectively Controllable Shape Memory Polymer Nanocomposites Embedding Carbon Nanotubes

An in-depth investigation on novel electro-activated shape memory polymer composites (SMPCs) for digital light processing 3D-Printing, consisting of a poly(ethylene glycol) diacrylate/poly(hydroxyethyl methacrylate) matrix embedding multi-walled carbon nanotubes (CNTs), is reported here. The composition of the photocurable (meth)acrylate system is finely tuned to tailor the thermomechanical properties of the matrix, whereas the effect of CNTs on the photoreactivity and rheological properties of the formulations is investigated to assess the printability. Electrical measurements confirmed that the incorporation of CNT into the polymeric matrix enables the electrical conductivity and thus the possibility to remotely heat the nanocomposite using the Joule effect. The feasibility to drive a shape memory cycle via Joule heating is proved, given that the high shape fixity (R_f) and shape recovery (R_r) ratios achieved (R_f ≈ 100%, R_r > 95%) confirmed the significant electrically-triggered responsiveness of such CNT/SMPCs. Finally, it is shown how to activate a modular and selective electro-activated shape recovery, which may ultimately envisage the 4D-Printing of remotely and selectively controllable smart devices.