Modeling the behavior of persons with mild cognitive impairment or Alzheimer’s for intelligent environment simulation

User Modeling and User-Adapted Interaction - Intelligent environments may improve the independence and quality of life of persons with mild cognitive impairment (MCI) or Alzheimer’s disease...     

Inductive transfer for learning Bayesian networks

In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with different conditions; or in industrial diagnosis, where there is equipment with similar specifications. In these cases it is common to have plenty of data for some scenarios but very little for others. In order to learn accurate models for rare cases, it is desirable to use data and knowledge from similar cases; a technique known as transfer learning. In this paper we propose an inductive transfer learning method for Bayesian networks, that considers both structure and parameter learning. For structure learning we use conditional independence tests, by combining measures from the target task with those obtained from one or more auxiliary tasks, using a novel weighted sum of the conditional independence measures. For parameter learning, we propose two variants of the linear pool for probability aggregation, combining the probability estimates from the target task with those from the auxiliary tasks. To validate our approach, we used three Bayesian networks models that are commonly used for evaluating learning techniques, and generated variants of each model by changing the structure as well as the parameters. We then learned one of the variants with a small dataset and combined it with information from the other variants. The experimental results show a significant improvement in terms of structure and parameters when we transfer knowledge from similar tasks. We also evaluated the method with real-world data from a manufacturing process considering several products, obtaining an improvement in terms of log-likelihood between the data and the model when we do transfer learning from related products.     

Improving Scalability of Application-Level Checkpoint-Recovery by Reducing Checkpoint Sizes

The execution times of large-scale parallel applications on nowadays multi/many-core systems are usually longer than the mean time between failures. Therefore, parallel applications must tolerate hardware failures to ensure that not all computation done is lost on machine failures. Checkpointing and rollback recovery is one of the most popular techniques to implement fault-tolerant applications. However, checkpointing parallel applications is expensive in terms of computing time, network utilization and storage resources. Thus, current checkpoint-recovery techniques should minimize these costs in order to be useful for large scale systems. In this paper three different and complementary techniques to reduce the size of the checkpoints generated by application-level checkpointing are proposed and implemented. Detailed experimental results obtained on a multicore cluster show the effectiveness of the proposed methods to reduce checkpointing cost.     

Zr‐Doped Indium Oxide (IZRO) Transparent Electrodes for Perovskite‐Based Tandem Solar Cells

Parasitic absorption in transparent electrodes is one of the main roadblocks to enabling power conversion efficiencies (PCEs) for perovskite‐based tandem solar cells beyond 30%. To reduce such losses and maximize light coupling, the broadband transparency of such electrodes should be improved, especially at the front of the device. Here, the excellent properties of Zr‐doped indium oxide (IZRO) transparent electrodes for such applications, with improved near‐infrared (NIR) response, compared to conventional tin‐doped indium oxide (ITO) electrodes, are shown. Optimized IZRO films feature a very high electron mobility (up to ≈77 cm² V^?1 s^?1), enabling highly infrared transparent films with a very low sheet resistance (≈18 Ω □^?1 for annealed 100 nm films). For devices, this translates in a parasitic absorption of only ≈5% for IZRO within the solar spectrum (250–2500 nm range), to be compared with ≈10% for commercial ITO. Fundamentally, it is found that the high conductivity of annealed IZRO films is directly linked to promoted crystallinity of the indium oxide (In₂O₃) films due to Zr‐doping. Overall, on a four‐terminal perovskite/silicon tandem device level, an absolute 3.5 mA cm^?2 short‐circuit current improvement in silicon bottom cells is obtained by replacing commercial ITO electrodes with IZRO, resulting in improving the PCE from 23.3% to 26.2%.     

Altered Distribution and Expression of Syndecan-1 and -4 as an Additional Hallmark in Psoriasis

Syndecans act as independent co-receptors to exert biological activities and their altered function is associated with many pathophysiological conditions. Here, syndecan-1 and -4 were examined in lesional skin of patients with psoriasis. Immunohistochemical staining confirmed altered syndecan-1 distribution and revealed absence of syndecan-4 expression in the epidermis. Fibronectin (FN)—known to influence inflammation and keratinocyte hyperproliferation via α5β1 integrin in psoriasis—was also decreased. Syndecan-1 and -4 expression was analyzed in freshly isolated lesional psoriatic human keratinocytes (PHK) characterized based on their proliferation and differentiation properties. mRNA levels of syndecan-1 were similar between healthy and PHK, while syndecan-4 was significantly decreased. Cell growth and release of the pro-inflammatory Tumor Necrosis Factor-alpha (TNFα) were selectively and significantly induced in PHKs plated on FN. Results from co-culture of healthy keratinocytes and psoriatic fibroblasts led to the speculation that at least one factor released by fibroblasts down-regulate syndecan-1 expression in PHK plated on FN. To assay if biological treatments for psoriasis target keratinocyte proliferation, gelatin-based patches enriched with inteleukin (IL)-17α or TNFα blockers were prepared and tested using a full-thickness healthy epidermal model (Phenion^®). Immunohistochemistry analysis showed that both blockers impacted the localisation of syndecan-1 within the refined epidermis. These results provide evidence that syndecans expression are modified in psoriasis, suggesting that they may represent markers of interest in this pathology.     

Enapotamab Vedotin,an AXL-Specific Antibody-Drug Conjugate,Demonstrates Antitumor Efficacy in Patient-Derived Xenograft Models of Soft Tissue Sarcoma

Doxorubicin (doxo) remains the standard of care for patients with advanced soft tissue sarcoma (STS), even though response rates to doxo are only around 14% to 18%. We evaluated enapotamab vedotin (EnaV), an AXL-specific antibody-drug conjugate (ADC), in a panel of STS patient-derived xenografts (PDX). Eight models representing multiple STS subtypes were selected from our STS PDX platform (n = 45) by AXL immunostaining on archived passages. Models were expanded by unilateral transplantation of tumor tissue into the left flank of 20 NMRI nu/nu mice. Once tumors were established, mice were randomized into an EnaV treatment group, or a group treated with isotype control ADC. Treatment efficacy was assessed by tumor volume evaluation, survival analysis, and histological evaluation of tumors, and associated with AXL expression. EnaV demonstrated significant tumor growth delay, regression, and/or prolonged survival compared to isotype control ADC in 5/8 STS PDX models investigated. Experimental passages of responding models were all found positive for AXL at varying levels, but no linear relationship could be identified between the level of expression and level of response to EnaV. One model was found negative for AXL on experimental passage and did not respond to EnaV. This study provides a preclinical rationale for the evaluation of AXL-targeting ADCs in the treatment of AXL-expressing sarcomas.     

Thermo-Metallurgical Modeling of Nodular Cast Iron Cooling Process

A new numerical model to describe the microstructural evolution of a eutectic nodular cast iron during its cooling is presented. In particular, equiaxial solidification assuming an independent nucleation of austenite and graphite nodules is considered. In this context, the austenite has dendritic growth whereas the graphite grows with a spherical shape. After solidification occurs, the model assumes that the graphite nodules present in the cast iron continue growing since the carbon content in austenite decreases. Once the stable eutectoid temperature is reached, the alloy undergoes the austenite-ferrite transformation. The nucleation of the ferrite takes place at the contour of the spherical graphite nodules where austenite has low carbon concentration. A ferrite shell surrounding the graphite nodules is formed afterward by means of a process governed by carbon diffusion. Then, a ferrite-pearlite competitive transformation occurs when the temperature is below the metastable temperature. This thermo-metallurgical model is discretized and solved by means of the finite element method. The model allows the computation of cooling curves, fraction evolution for each component, and size and distribution of graphite nodules. The present numerical results are compared with experiments using standardized Quick-cup-type cups, and satisfactory numerical predictions of the final microstructure and cooling curves are achieved.     

Processing of graded anode-supported micro-tubular SOFCs based on samaria-doped ceria via gel-casting and spray-coating

A simple gel-casting method was successfully combined with the spray-coating technique to manufacture graded anode-supported micro-tubular solid oxide fuel cells (MT-SOFCs) based on samaria-doped ceria (SDC) as an electrolyte. Micro-tubular anodes were shaped by a gel-casting method based on a new and simple forming technique that operates as a syringe. The aqueous slurry formulation of the NiO–SDC substrate using agarose as a gelling agent, and the effect of spray-coating parameters used to deposit the anode functional layers (AFLs) and electrolyte were investigated. Furthermore, pre-sintering temperature of anode substrates was systematically studied to avoid the anode–electrolyte delamination and obtain a dense electrolyte without cracks, after co-sintering process at 1450 °C. Despite the high shrinkage of substrate (～70%), an anode porosity of ～37% was achieved. MT-SOFCs with ～2.5 mm of outer diameter, 370 μm thick substrate, 20 μm thick AFLs and 15 μm thick electrolyte were successfully obtained. The use of AFLs with 30:70 and 50:50 wt% NiO–SDC allowed to obtain a continuous gradation of composition and porosity in the anode–electrolyte interface.