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Does AI Help or Hurt Learning?

AI is transforming how students learn, raising concerns about whether it expands educational opportunities or widens existing gaps. We examine this question in a preregistered lab experiment (N=572) in which students study a novel topic under one of three conditions: browsing only (control), AI-assisted, or AI-guided, and then complete an exam without AI access. We find no overall effect of AI acc

3D Line Mapping Revisited

In contrast to sparse keypoints, a handful of line segments can concisely encode the high-level scene layout, as they often delineate the main structural elements. In addition to offering strong geometric cues, they are also omnipresent in urban landscapes and indoor scenes. Despite their apparent advantages, current line-based reconstruction methods are far behind their point-based counterparts.

Experimental benchmarking of dielectric models for simulating the localized surface plasmon resonance in Au-Ag alloy nanospheres

The optical response of gold-silver (Au-Ag) alloy nanoparticles is strongly influenced by their localized surface plasmon resonance (LSPR), which can be tuned by varying the particle composition. Accurate simulation of LSPR, often performed using Mie theory, critically depends on the choice of dielectric function, yet available datasets for gold, silver, and their alloys vary widely. In this work,

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran

Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learning models: boosted regression tree (BRT), classification and regression tree (CART), and random forest (RF). Thirteen hydrological-geological-physiogra

'Democratic Necessity' Mischaracterized? Reconciling Child Protection with Respect for Cultural Diversity. A Critical Analysis of ECtHR Jurisprudence on Child Protection Interventions Involving Minority Children

This thesis is motivated by the aim of ascertaining whether the ECtHR is limiting the ECHR’s potential, if any, to contribute to the curbing of child welfare disproportionality rates in CoE MSs. It provides a critical analysis of ECtHR jurisprudence on child protection interventions involving minority children – namely, children belonging to ethnic, religious, or linguistic minority groups or whos

Vilka ramar formar framtiden? En analys av epistemologiska förhållningssätt i energistrategiskt arbete

Kultur och kunskap som praktik i statlig energistrategisk planering. Vad accepteras som giltig kunskap för strategisk energiplanering? Möjliggör detta en hållbar energiomställning? Utvinningen av den fossila energin har bidragit till en ökad koncentration av bland annat koldioxid i atmosfären, vilket orsakar en global klimatförändring. Detta innebär att vi står inför en energiomställning för att mThe energy sector's dominant share of the anthropogenic environmental and climate impact makes the subject highly relevant for sustainable development. The paper aims to shed light on what influences energy strategy work in order to contribute to perspectives on which knowledge is prioritized. My method was of an ethnographic approach, where I was given the opportunity to do an internship at

Photobiomodulation in the parotid and submandibular glands : a Monte Carlo simulation of photon penetration using 525-nm, 660-nm, and 850-nm wavelengths

There are ongoing questions about the most effective wavelength for photobiomodulation (PBM) on major salivary glands due to the specific anatomical location and unique optical properties of the tissues surrounding the glands. The aim of this study was to analyze the photon propagation in the major salivary glands region of humans and rats using Monte Carlo (MC) stochastic simulation. Phantoms wer

A Reinforcement Learning Approach Based on Group Relative Policy Optimization for Economic Dispatch in Smart Grids

The Economic Dispatch Problem (EDP) plays a critical role in power system operations by trying to allocate power generation across multiple units at minimal cost while satisfying complex operational constraints. Traditional optimization techniques struggle with the non-convexities introduced by factors such as valve-point effects, prohibited operating zones, and spinning reserve requirements. Whil

Flood susceptibility mapping in the Nyabarongo Catchment, Rwanda, based on data analysis and modeling

Rwanda’s Nyabarongo catchment frequently experiences floods, highlighting the need for effective flood susceptibility analysis and management. This study mapped flood susceptibility in the catchment using the random forest (RF), support vector machine (SVM), eXtreme Gradient Boosting (XGBoost), SHapley Additive exPlanations (SHAP) models, as well as various conditioning factors including elevation

“Jag vill att dom visar att dom bryr sig!” En studie om gymnasieelevers perspektiv på elevhälsoteam

Studiens syfte var att undersöka och kartlägga gymnasieelevers syn på elevhälsan samt att konstruera ett mätinstrument för att genomföra undersökningen. Mot bakgrund av ökande psykisk ohälsa bland unga samt bristande nationell kartläggning av ungdomars perspektiv gällande elevhälsan var ansatsen med studien att lyfta gymnasieelevernas egna perspektiv i frågan. Studien genomfördes som en tvärsnittsThe aim of the current study was to explore high school students’ perspectives on the Swedish student health system (elevhälsan), as well as the construction of a survey instrument to implement the study. Due to the general increase in adolescent mental health issues alongside a lack of national research regarding adolescent views on elevhälsan, this cross-sectional explorative study seeked to amp

Cycle Conditioning for Robust Representation Learning from Categorical Data

This paper introduces a novel diffusion-based method for learning representations from categorical data. Conditional diffusion models have demonstrated their potential to extract meaningful representations from input samples. However, they often struggle to yield versatile, multi-task information, limiting their adaptability to unforeseen tasks. To address this, we propose a cycle conditioning app

Out-of-Distribution Detection in Point-of-Care Ultrasound Breast Imaging Using Variational Autoencoders

Out-of-distribution (OOD) detection is a crucial step in ensuring robustness and trustworthiness for deep learning (DL) models. This is particularly important for classification tasks in medical applications. Previous work has shown that point-of-care ultrasound (POCUS) imaging combined with a DL classification network could improve access to early breast cancer diagnosis. In this work, we investi

Multi-Objective MILP Models for Optimizing Makespan and Energy Consumption in Additive Manufacturing Systems

Additive manufacturing (AM) is revolutionizing industrial production by enabling the fabrication of complex, customized components with reduced material waste. However, the scheduling of AM machines presents significant challenges in terms of optimizing both time-related performance and energy consumption. This paper introduces a novel multi-objective mixed-integer linear programming (MILP) model

Männens sak är vår - en komparativ studie av argumentationen för att omfatta kvinnor i den allmänna värnplikten i Sverige och Danmark

Allmän värnplikt blev i praktiken könsneutral i Sverige för första gången 2018 och i Danmark trädde ändring i kraft år 2025. Den här uppsatsen syftar till att undersöka den bakomliggande argumentation till lagändringen som medförde att även kvinnor omfattades av den allmänna värnplikten. Det görs med ett komparativt perspektiv mellan Sverige och Danmark med syfte att undersöka om det föreligger liConscription became gender-neutral in practice in Sweden for the first time in 2018. In Denmark the amendment of the law became effective in 2025. This paper aims to examine the underlying arguments for the amendment of the law that meant that women were also included in conscription. This is done with a comparative perspective between Sweden and Denmark with the aim of examining whether there are

Intelligent multi-agent reinforcement learning model for resources allocation in cloud computing

Now more than ever, optimizing resource allocation in cloud computing is becoming more critical due to the growth of cloud computing consumers and meeting the computing demands of modern technology. Cloud infrastructures typically consist of heterogeneous servers, hosting multiple virtual machines with potentially different specifications, and volatile resource usage. This makes the resource alloc

Prognostic Significance of GPR55 mRNA Expression in Colon Cancer

G protein-coupled receptor 55 (GPR55) probably plays a role in innate immunity and tumor immunosurveillance through its effect on immune cells, such as T cells and NK cells. In this study, the prognostic value of GPR55 in colon cancer (CC) was investigated. mRNA expression levels of GPR55 were determined in 382 regional lymph nodes of 121 CC patients with 12 years observation time after curative s