1,721,334 research outputs found
Supporting, Not Solving: Human-Centered AI Systems in Education
Full text linkEducational technologies have evolved significantly over recent decades, with AI representing the latest frontier in this progression. Current applications range from adaptive learning platforms that personalize content delivery to automated systems that provide immediate feedback. The challenge lies in developing AI educational technologies that enhance human capabilities while respecting the autonomy and agency of learners and educators. My research aims to design, implement, and evaluate human-centered AI systems in educational contexts. By prioritizing human needs and values throughout the development process, my work seeks to advance the understanding of how AI can enhance educational practices while preserving the learner’s independence and the educator’s role
Implicazione di p27 kip1 nell'esordio e nella progressione del carcinoma mammario luminale
No full textp27kip1 is a cyclin-dependent kinase (CDK) inhibitor (CKI) and mainly acts as a negative regulator of cell proliferation. Through distinct domains, p27kip1 has also been involved in the control of other cellular processes, including migration, differentiation and cytoskeleton dynamics. p27kip1 protein is frequently inactivated in human cancer and its subcellular localization (cytoplasmic versus nuclear) can be prognostic in some tumors, such as breast, colon, prostate, lung, esophageal, and gastric cancers (Ananthanarayanan et al. 2011; Wen et al. 2012).
With the advent of next generation sequencing approaches, p27kip1 has been identified as one of the 18 most significantly mutated genes in luminal breast cancer (Stephens et al. 2012; Ellis et al. 2012; Belletti, Baldassarre et al. 2012). Furthermore, the analysis of copy number variation showed that a fraction of luminal breast cancer also displayed loss or gain of CDKN1B gene, encoding for p27kip1 (Viotto, Russo et al. 2021), reinforcing the idea that p27kip1 may be critical for luminal breast cancer onset and/or progresssion. Interestingly, many of the identified somatic mutations are located in the C-terminal domain, leading to protein loss or truncated protein formation.
Therefore, to elucidate the role of p27kip1 in luminal breast cancer, we first used a gene-editing approach in a luminal breast cancer cell line and investigated the effects induced by loss of p27kip1 and by expression of two different truncated mutants, K134fs and T171*, losing p27kip1 C-terminal domain.
Our results clearly showed that these mutants, failed to rescue most of the phenotypes induced by CDKN1B gene knock-out, indicating that the functions retained by this portion are critical for its role as an oncosuppressor, both in vitro (Viotto, Russo et al. 2021) and in vivo. Moreover, we observed that lack of p27kip1 or expression of its mutant forms increased the resistance to the treatment with Palbociclib, currently one of the most common therapeutic strategies for luminal breast cancer patients.
Finally, to evaluate whether p27kip1 could also represent a driver genetic lesion during the process of transformation, we have also shown the involvement of p27kip1 in the process of cell transformation and tumor initiation. Generating p27kip1 knock-out clones in normal human mammary luminal epithelial cell line, we have noticed its ability to significantly increase the proliferation cell rate of these normal cells. Interestingly, the only deficiency of p27kip1 seems to lead the cells toward a stem phenotype and also therapy resistance, highlight the important role of p27kip1 also in the early steps of mammary cancer formation
Lessons learned from using bio-and environmental sensing in construction: a field implementation
No full textBoth physiological status and jobsite environmental stressors influence workforce behavior and performance. Understanding these relationships at the individual worker level is paramount for sustainably managing the construction industry workforce. Astonishing improvements in sensing technology can benefit field research by providing ways to validate occupational performance models based on data that measure workers’ physiological variables and environmental stressors. However, only a few studies have taken advantage of these technological improvements to conduct construction field studies. This paper describes a field monitoring study hosted at a mid-rise, mixed-use building construction site in Seattle, WA. This study was valuable in term of its breadth and period of the observations because it used some of the latest off-the-shelf wearable biosensors to collect 339 hours of workers’ biosignal data from five subjects, during summer and fall, for a total of up to three weeks per subject. This research empirically validated that the heart rate is a good predictor of a worker’s physical strain. Descriptive statistics and a time series plot were used to analyze the heart rate pattern as a predictor of worker’s physical strain level. Correlation analysis was used to analyze the association between the workers’ heart rate and jobsite environmental stressors. Also, analyzing video recordings and questionnaires helped interpreting the analytical results. This paper reports the lessons learned and the challenges of implementing a selected combination of wearable biosensor and environmental sensing technologies. These research findings are preparatory to validating a demand and capability model to be used for predicting construction workers’ performance
Adaptation to Standards or New Design Shape? Level of Service and Safety by Varying a Grade-Level Intersection into a Roundabout
No full textThe study focused on grade-level non circular intersections and single-lane roundabouts belonging to a two-lane rural roads’ network in the Southern Italy located on a flat terrain that have been built before Italian Standard became law. A total of 104 intersections were studied during a study period of 8 years: 97 non circular intersections and 7 roundabouts. The main goal of this start-up phase about this road issue is to check whether improvements in terms of the level of safety (reduction in the number of crashes and injuries) and service (reduction in the waiting time to make the maneuver) can be achieved when two geometric solutions of intersections at grade are contemplated: (a.) adaptation to the road geometric Standards in force in Italy of non-circular existing intersections without changing the shape; (b.) shape’s modification of the non-circular intersection into a roundabout according to Italian Geometric Standard in force. According to a methodology based on the crash rates’ calculation, the results showed that 65 intersections (58 non circular intersections and 7 roundabouts) have been associated with a “low crash level”, 34 have been associated with a “high crash level” and the remaining with a “medium crash level”. The roundabouts were always characterized by a low crash level. Furthermore, the non circular intersections where additional geometric modules exist (e.g. left-turn lanes, deceleration lanes, divisional islands) as suggested by standard have low crash level as opposed to those belonging to the band of high dangerousness where these elements are missing. The results showed that the waiting times increase when the social costs increase, and that both geometric solutions are consistent to get the purpose but the roundabout is the best solution
Bridging Web and Figma: Automating Large-Scale UI Dataset Generation for AI-Enhanced Design
Full text linkLarge-scale User Interface (UI) data is essential for developing Artificial Intelligence (AI)-driven tools that can support designers in creating interfaces. However, many publicly available datasets are either manually annotated, a time-consuming and costly process that limits their scale or lack crucial structural information, such as semantic labels and hierarchical relationships, necessary for effective design assistance. Moreover, no existing dataset offers a standard format designed for seamless integration of AI models into real-world design tools. In this work, we introduce a pipeline that automatically converts any HTML content into structured, Figma-compatible representations. To validate our pipeline, we apply it to WebUI, a large-scale HTML-based dataset, and conduct a comparative evaluation by training five state-of-the-art layout generation models on our data and the manually annotated Rico dataset. Experimental results demonstrate that the models achieve comparable performance across both datasets and suggest that our pipeline can effectively produce high-quality data suitable for training AI models integrable into design workflows
Descriptors in scenic highway analysis: a test study along Italian road corridors
No full textThe following paper illustrates the application and the verification of detailed methodologies employed by international agencies to assess the Scenic Quality of a landscape.
Several States determine a landscape’s visual quality using predictor variables. This research aims to validate the recognized ability of these predictor variables to reproduce untrained observers’ preferences. The definition of the Scenic Quality of a landscape is often affected by
subjective opinions but sometimes exceptions exist. Public judgment recognizes a high Visual Quality to landscape when natural reserves, national parks, and archaeological interest exist.
Various procedures collected in international literature suggest the use of predictor indicators to evaluate public preferences. Three variables have been chosen to analyze a series of selected Italian landscapes: Vividness, Intactness and Unity. Photographic inventories were created for
different landscapes. Pools of landscape architects judged the slides associated to each landscape using a 7-point scale for the three indicators. Identical slides were then shown to untrained observers composed of 201 students that used a 10-point scale to evaluate Scenic Beauty for each picture. Students’ judgments were then related to the expert judgments. The results indicate that vividness is most correlated with Scenic Beauty that presents a much weaker correlation
with intactness
Road Safety Management Using Crash Prediction Models
No full textThe crash prediction models presented here could
significantly inform the planning phase of a given project
and help optimise design. This is especially relevant to the
evaluation and programming of road safety improvement
operations designed for provincial road networks. The
availability of the crash prediction models could notably
enable the administrative authorities to prioritise the
development of infrastructure and the allocation of public
funds towards those areas of the network that are deemed
“critical” from a safety point of view
Procedure for Making Paving Decisions with Cluster and Multicriteria Analysis
No full textFor many years now, a lot of research has been carried out to assess the affordability of whether to pave or not to pave a road. Today, the rise in construction and maintenance costs of traditional asphalt pavement systems has persuaded many civil administrations, regional councils and agencies to replace paving with gravel surfaces. Low-volume roads (LVRs), as they are presented in this paper, constitute a significant proportion of the road network in Italy and in many other countries through out the world, making up around 80% of the total road network in Italy. These infrastructures are a vital part of the road network, but at the same time their construction can have a significant adverse impact on the environment, which means that these roads need to be well planned, well designed, well-constructed, and properly maintained to create minimal adverse impact and to be cost effective in the long term with acceptable maintenance and repair costs. Limited resources often exist for LVRs and whether to use paved surfaces or gravel surfaces has become a frequent decision-making problem. In many cases the choice depends only on economic considerations which must also take maintenance costs into account. Using a Cluster and Multi-Criteria Analysis the authors illustrate a complete procedure to decide, on 77 the basis of different geometric, traffic and environmental layouts, whether to pave or not to pave gravel road 78 surfaces
Safety performance functions for crash severity on undivided rural roads
No full texttThe objective of this paper is to explore the effect of the road features of two-lane rural road networkson crash severity. One of the main goals is to calibrate Safety Performance Functions (SPFs) that canpredict the frequency per year of injuries and fatalities on homogeneous road segments. It was foundthat on more than 2000 km of study-road network that annual average daily traffic, lane width, curvaturechange rate, length, and vertical grade are important variables in explaining the severity of crashes. Acrash database covering a 5-year period was examined to achieve the goals (1295 injurious crashes thatincluded 2089 injuries and 235 fatalities). A total of 1000 km were used to calibrate SPFs and the remaining1000 km reflecting the traffic, geometric, functional features of the preceding one were used to validatetheir effectiveness. A negative binomial regression model was used. Reflecting the crash configurationsof the dataset and maximizing the validation outcomes, four main sets of SPFs were developed as follows:(a) one equation to predict only injury frequency per year for the subset where only non-fatal injuriesoccurred, (b) two different equations to predict injury frequency and fatality frequency per year per sub-set where at least one fa tality occurred together with one injury, and (c) only one equation to predict thetotal frequency per year of total casualties correlating accurate percentages to obtain the final expectedfrequency of injuries and fatalities per year on homogeneous road segments. Residual analysis confirmsthe effectiveness of the SPFs
Passivation strategies for the optimization of perovskite solar cells
Full text linkThis thesis focuses on developing environmentally sustainable strategies to enhance the performance, stability, and scalability of PSCs, among the most promising PV technologies of the current scenario.
The experimental results are organized in three sections, chapters 3 to 5, the first one employing bio-derived materials as components of the PSC device foreseeing the amelioration of the photoactive film characteristics combined with the engineering of device interfaces. In details, chapter 3 reports on the use of β-carotene and PHB, to improve the environmental stability and optoelectronic properties of perovskite films. β-carotene, which scavenges oxidizing species, mitigates perovskite degradation, leading to increased material stability and prolonged charge carrier lifetimes. Devices incorporating β-carotene achieve a PCE of 20%, highlighting its potential to improve the lifespan and sustainability of solar cells. Similarly, PHB, a biodegradable polymer, enhances the mechanical flexibility and crystalline quality of perovskite films, and surpasses the reference efficiency, achieving a PCE of 9.3%. This suggests the potential of PHB to contribute to the development of more sustainable, flexible, and eco-friendly perovskite-based devices. The second section is focused on the key role of device interfaces for fully inorganic CsPbI3-based solar cells.
The incorporation of PCBM as an interlayer between C60 and CsPbI3 enhances energy level alignment and reduces defects, contributing to more efficient charge transfer. Successively, the introduction of TTH as a novel interlayer further improves device performance, with a PCE of 8.12% surpassing the reference efficiency of 6%, by reducing interfacial recombination and facilitating efficient charge separation. These innovations demonstrate the potential to optimize perovskite-based devices for more sustainable energy solutions.
Finally, in chapter 5 plasma-based treatments are explored as environmentally friendly surface modification methods for MAPbI3 perovskite films. Plasma treatments with gases like Ar and H2 enhance device performance by selectively removing organic components and introducing chemical functionalities that improve the stability and efficiency of the interfaces. Unlike traditional chemical treatments, plasma-based methods offer a less invasive and potentially more eco-friendly approach to surface engineering.
In conclusion, this thesis demonstrates the potential of combining bio-inspired additives, interlayer engineering, and plasma treatments to address key challenges in perovskite solar cell technology. These advancements not only improve the efficiency and stability of the devices but also pave the way for the development of more environmentally sustainable and scalable photovoltaic solutions, contributing to the global transition towards clean and renewable energy sources
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