Supercapacitors (SCs) are gaining attention in energy storage due to their high-power density, rapid charge/discharge ability, and long life cycle. Improving these features relies on developing advanced electrode materials with better energy storage properties. This study explores UiO-66, a zirconium-based metal-organic framework (MOF), which offers advantages like a large surface area, tunable pore sizes, and stability. However, its poor electrical conductivity limits its use in supercapacitors. Herein, we applied the Hummers' method to oxidize UiO-66, creating an oxidized form, H-UiO-66, with enhanced conductivity. This material was characterized by various techniques, including SEM-EDX, XRD, XPS, FTIR, and BET analysis, while electrochemical tests (GCD, CV, and EIS) confirmed a significant improvement in specific capacitance-82.8 F g-1 for H-UiO-66 versus 0.18 F g-1 for pristine UiO-66 at 1 mA. These improvements stem from increased conductivity and electrochemical activity due to UiO-66 graphitization, highlighting the Hummers' method's effectiveness in transforming UiO-66 into a viable supercapacitor material.
L’enquête Tremblay-Fortin sur les comportements économiques des familles salariées du Québec, menée en 1959, a influencé l’histoire intellectuelle de la société québécoise et elle a conforté la redéfinition du Québec comme société industrielle et comme société de consommation, tant en milieu urbain qu’en milieu rural, bien loin de l’image de la folk society . Elle a documenté les nouveaux besoins des familles à l’aide d’une vaste enquête budgétaire, ainsi que l’émergence de leurs aspirations. Cette enquête révèle que les conditions de vie et les représentations sociales des Canadiens français sont celles d’une société bien entrée dans la modernisation avant les années 1960, alors que les institutions tardaient à s’ajuster aux nouvelles réalités sociales vécues par les familles. L’enquête Tremblay-Fortin a contribué à la prise de distance avec la nation canadienne-française comme référence nationale et elle a alimenté un regard neuf posé sur la société québécoise.
In spite of the legal advances in personal data protection, the issue of private data being misused by unauthorized entities is still of utmost importance. To prevent this, Privacy by Design is often proposed as a solution for data protection. In this paper, the effect of camera distortions is studied using Deep Learning techniques commonly used to extract sensitive data. To do so, we simulate out-of-focus images corresponding to a realistic conventional camera with fixed focal length, aperture, and focus, as well as grayscale images coming from a monochrome camera. We then prove, through an experimental study, that we can build a privacy-aware camera that cannot extract personal information such as license plate numbers. At the same time, we ensure that useful non-sensitive data can still be extracted from distorted images. Code is available at https://github.com/upciti/privacy-by-design-semseg .
Recent advances in immuno-oncology have significantly increased the therapeutic arsenal available for clinicians. However, being able to identify the responder to a given treatment remains difficult and time consuming. This is due to the lack of translational preclinical models that recapitulate the complete cellular and physical tumor-immune micro-environment (TME). We report for the first time a high throughput vascularized immunocompetent breast tumoroids model in standard multiwell culture plate (MW). The model uses micro physiological system (MPS) and microfabrication to recapitulate and precisely control the TME. The tumor model includes fibroblasts, tumor cells (MDA-MB-231), immune cells (CD81+, CD64+), endothelial cells (CD31+), and a collagen extra cellular matrix. These are essential for the TME and are often lacking in preclinical models, potentially biasing the observed therapeutic response. The physical microenvironment was recapitulated using Cherry Biotech’s MPS, CubiX, and 4DCell SmartSphero Plates (SSoP). A combined system, which to the best of our knowledge is the only one able to recreate the complete TME in a 24 MW with multiplexed and uniformized tumoroid sizes. The SSoP technology is based on microstructured hydrogels, where microwells with an anchoring point at the bottom, allow the formation of the tumoroids, and to keep them in place, making it easy to trace them. The non-adherent properties of the gels help maintain the tumoroids shape. The CubiX system allowed controlling the cell culture conditions: temperature (37°C) and medium perfusion (150 µL/min). The presence of an enriched gas mix with 5% CO2 and O2, was also provided to the tumoroids, and pH, lactate, glucose, O2 consumption were monitored along all culture periods. We focused on optimizing the recapitulation of the physiopathology of breast cancer in 3 aspects: growth rate; tumor cell migration; and oxygen gradient within the MW plate to mimic different depths of the tumor (normoxic to the hypoxic core). Those features are essential for accurate drug efficacy testing. We were able to grow and maintain up to 91 tumoroids per well in a 24MW. After tumoroids formation, we obtained a fully vascularized and immuno-competent model in 48h, the fastest to the best of our knowledge. The system enabled monitoring of the tumoroids growth rate, the differentiation of the endothelium cells (Kfl 2/4, Van Willebrand Factor, eNOS, -% actin fiber alignment), differentiation of CD81+ and CD64+ cells into Macrophage type 1 or 2. All cell types were kept viable for 7 days, and endothelial cells alignment was found physiological (80%). Furthermore, we were able to induce on demand the invasiveness phenotype of the tumoroids. We envision that this model will evolve into a vascularized immunocompetent patient derived tumor model that can be used routinely in precision oncology to predict the drug response of a given patient. Citation Format: Stijn Robben, Anais Peyron, Ana Rita Ribeiro, Divyasree Prabhakaran, Antoni Homs Corbera, Pierre Gaudriault, Patricia Davidson, Dario Fassini. A high throughput vascularized immunocompetent tumoroids model in a standard multiwell plate for precision oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 193.
Building continuous performance monitoring is becoming a cornerstone in ensuring energy efficiency and sobriety of existing, retrofitted and newly built buildings. Although it may help convince investors in energy efficiency projects or bridge the gap between expected and actual performance, continuous monitoring - sometimes referred to as “Advanced M&V” or continuous commissioning – is still the exception rather than the rule. Recent efforts to continuously characterize building performance usually rely on building-level analyses: previous works include leveraging a Building Energy Model (BEM), monthly calibrated on building heating, ventilation and lighting consumption using real weather data and fine grain occupancy data, for daily monitoring. While BEM calibration against sub-daily frequency data has been increasingly studied in recent years, it is, to our knowledge, seldom used for building continuous monitoring. It is, however, particularly tailored for this task, to the extent it extracts embedded physics within the BEM into actionable insights for fault detection and diagnosis. Fine grain calibration of BEM faces a number of challenges in the recent literature, among which are (i) accounting for time varying dependent functional inputs - e.g. electric equipment and lighting energy consumption altogether with building occupancy - but for sensor data in the calibration algorithm, and (ii) treating functional outputs as functional stochastic variables when comparing simulation outputs with real data. Our contribution is to enhance building-level performance monitoring by introducing a stochastic model inversion scheme, also referred to as stochastic calibration, to support robust preventive fault detection and diagnosis. Our approach extends the current state-of-the-art on Bayesian calibration of BEM by accounting for dependent functional inputs and outputs in both selecting the most influential parameters and calibrating the model, and deals with uncertainties in functional inputs such as daily profiles of lighting and electric equipment energy consumption. This methodology is illustrated against a medium-size real secondary school building, located in Rennes, France, and equipped with an Advanced Meter Infrastructure (AMI) with hundreds of sensors. A comparison between a classic calibration process and the described methodology is presented and the benefits of accounting for the functional nature of the inputs and outputs in both the Design of Experiment (DoE) and the calibration process are illustrated against this case study.
