Transfer learning for mobile robots

Abstract. In this project transfer learning can be defined as transferring previously learned knowledge to a new environment and making use of it to avoid obstacles. The feasibility of transfer learning was studied in a situation where a robot is given a task to navigate to a user-defined location in a virtual environment without hitting walls and utilizing reinforcement learning to teach the robot, which means that the robot will receive rewards according to the way it moves in the environment and how close it is to the goal location. In this project everything is done and tested in simulation. First the robot is trained in a standard environment, which is a simple hallway. It requires around 4000 iterations for the robot to learn better practices and reach the goal more frequently. When the training is done, the robot is moved to a test environment, which is otherwise similar to the standard one with the exception of a slanted floor, a ramp, in the beginning of the hallway. This proved to be an obstacle that the robot could not overcome without the help of sensor spoofing. Sensor spoofing in this case means inputting fake values to the robot’s laser sensor, which is responsible for detecting obstacles around the robot. The major target in this research was to transfer the previously learned data from the standard environment to the test environment and utilize sensor spoofing to help the robot overcome the slanted floor and eventually analyze if transfer learning helped the robot perform better. The performance can be compared by looking at the rewards received by the robot, since the robot receives highest rewards when reaching the goal location in the environment and negative rewards when crashing into walls. If transfer learning is beneficial for the robot, the robot should reach the goal point more frequently when making use of previously trained data from the standard environment and sensor spoofing in the test environment, compared to how it performs without them. This was also the result achieved. Even though the performance was not as good as it was without the ramp since without the ramp the robot reached the goal point every time after training around 200 episodes, the performance was better than it was without the trained model and sensor spoofing being used. As a result, transfer learning can be applied in virtual environments for mobile robots under certain restrictions. It can also be utilized in many other cases, this project is just one example. The codes and files used for this project are available on GitHub at https://github.com/lperala/Transfer_learning_for_mobile_robots.Tiivistelmä. Tässä projektissa oppimisen siirtäminen voidaan määrittää aiemmin opitun tiedon siirtämisenä uuteen ympäristöön ja sen hyödyntämisenä esteiden välttelyyn. Oppimisen siirtämisen toteutettavuutta tutkittiin tilanteessa, jossa robotille on annettu tehtävä navigoida käyttäjän määrittämään sijaintiin virtuaalisessa ympäristössä osumatta seiniin hyödyntäen vahvistavaa oppimista robotin opettamiseksi, joka tarkoittaa että robotti saa positiivisia palkkioita sen mukaan miten se liikkuu ympäristössä ja kuinka lähellä se on tavoitesijaintia. Tässä projektissa kaikki on tehty ja testattu simulaatiossa. Ensin robotti koulutetaan standardiympäristössä, joka on yksinkertainen käytävä. Robotti tarvitsee noin 4000 toistoa koulutusta, jotta se oppisi liikkumaan paremmin ja saavuttamaan tavoitesijaintinsa useammin. Kun koulutus on tehty, robotti siirretään testiympäristöön, joka on muuten samanlainen kuin standardiympäristö, mutta sisältää kaltevan rampin käytävän alussa. Tämä osottautui esteeksi, jonka yli robotti ei kyennyt liikkumaan ilman sensorin huijaamista. Sensorin huijaaminen tarkoitti tässä tapauksessa tekaistujen arvojen syöttämistä robotin lasersensorille, joka vastaa esteiden havaitsemisesta robotin ympärillä. Suurin tavoite projektissa oli siirtää aiemmin opittu data standardiympäristöstä testiympäristöön ja hyödyntää sensorin huijaamista auttaakseen robottia ylittämään ramppi ja lopulta analysoida oliko oppimisen siirtämisestä hyötyä robotin suoriutumisen kannalta. Suoriutumista voitiin tarkastella vertaamalla robotin keräämiä palkkioita, koska robotti saa isoimmat palkkionsa saavuttaessaan tavoitesijaintinsa ympäristössä ja taas negatiivisia palkkioita, mikäli se törmää seinään. Jos oppimisen siirtäminen on hyödyllistä, se tarkottaisi että robotti saavuttaisi tavoitesijainnin useammin kun se hyödyntää aiemmin opittua dataa kuin jos se suoriutuisi ilman opittua dataa. Tämä oli myös tulos johon päädyttiin. Vaikka suoriutuminen ei ollut yhtä hyvää kuin ilman ramppia, koska ilman ramppia robotti saavutti tavoitteensa jo 200 koulutusepisodin jälkeen, suoriutuminen oli parempaa kuin se oli täysin ilman koulutusta ja sensorin huijaamista. Tuloksena, oppimisen siirtämistä voidaan hyödyntää virtuaalisissa ympäristöissä mobiileille roboteille tiettyjen rajoituksin. Sitä voidaan myös hyödyntää monissa muissakin tapauksissa, tämä projekti on vain yksi esimerkki. Projektissa käytetyt tiedostot ovat saatavilla GitHubissa osoitteesta https://github.com/lperala/Transfer_learning_for_mobile_robots

Segregation, precipitation, and \alpha-\alpha' phase separation in Fe-Cr alloys: a multi-scale modelling approach

Segregation, precipitation, and phase separation in Fe-Cr systems is investigated. Monte Carlo simulations using semiempirical interatomic potential, first-principles total energy calculations, and experimental spectroscopy are used. In order to obtain a general picture of the relation of the atomic interactions and properties of Fe-Cr alloys in bulk, surface, and interface regions several complementary methods has to be used. Using Exact Muffin-Tin Orbitals method the effective chemical potential as a function of Cr content (0-15 at.% Cr) is calculated for a surface, second atomic layer and bulk. At ~10 at.% Cr in the alloy the reversal of the driving force of a Cr atom to occupy either bulk or surface sites is obtained. The Cr containing surfaces are expected when the Cr content exceeds ~10 at.%. The second atomic layer forms about 0.3 eV barrier for the migration of Cr atoms between bulk and surface atomic layer. To get information on Fe-Cr in larger scales we use semiempirical methods. Using combined Monte Carlo molecular dynamics simulations, based on semiempirical potential, the precipitation of Cr into isolated pockets in bulk Fe-Cr and the upper limit of the solubility of Cr into Fe layers in Fe/Cr layer system is studied. The theoretical predictions are tested using spectroscopic measurements. Hard X-ray photoelectron spectroscopy and Auger electron spectroscopy investigations were carried out to explore Cr segregation and precipitation in Fe/Cr double layer and Fe_0.95Cr_0.05 and Fe_0.85Cr_0.15 alloys. Initial oxidation of Fe-Cr was investigated experimentally at 10^-8 Torr pressure of the spectrometers showing intense Cr_2O_3 signal. Cr segregation and the formation of Cr rich precipitates were traced by analysing the experimental spectral intensities with respect to annealing time, Cr content, and kinetic energy of the exited electron.Comment: 16 pages, 14 figures, 52 reference

ASIC-E4: Interplay of Beta-Amyloid, Synaptic Density and Neuroinflammation in Cognitively Normal Volunteers With Three Levels of Genetic Risk for Late-Onset Alzheimer's Disease – Study Protocol and Baseline Characteristics

Background: Detailed characterization of early pathophysiological changes in preclinical Alzheimer's disease (AD) is necessary to enable development of correctly targeted and timed disease-modifying treatments. ASIC-E4 study (“Beta-Amyloid, Synaptic loss, Inflammation and Cognition in healthy APOE ε4 carriers”) combines state-of-the-art neuroimaging and fluid-based biomarker measurements to study the early interplay of three key pathological features of AD, i.e., beta-amyloid (Aβ) deposition, neuroinflammation and synaptic dysfunction and loss in cognitively normal volunteers with three different levels of genetic (APOE-related) risk for late-onset AD. Objective: Here, our objective is to describe the study design, used protocols and baseline demographics of the ASIC-E4 study. Methods/Design: ASIC-E4 is a prospective observational multimodal imaging study performed in Turku PET Centre in collaboration with University of Gothenburg. Cognitively normal 60–75-year-old-individuals with known APOE ε4/ε4 genotype were recruited via local Auria Biobank (Turku, Finland). Recruitment of the project has been completed in July 2020 and 63 individuals were enrolled to three study groups (Group 1: APOE ε4/ε4, N = 19; Group 2: APOE ε4/ε3, N = 22; Group 3: APOE ε3/ε3, N = 22). At baseline, all participants will undergo positron emission tomography imaging with tracers targeted against Aβ deposition (11C-PIB), activated glia (11C-PK11195) and synaptic vesicle glycoprotein 2A (11C-UCB-J), two brain magnetic resonance imaging scans, and extensive cognitive testing. In addition, blood samples are collected for various laboratory measurements and blood biomarker analysis and cerebrospinal fluid samples are collected from a subset of participants based on additional voluntary informed consent. To evaluate the predictive value of the early neuroimaging findings, neuropsychological evaluation and blood biomarker measurements will be repeated after a 4-year follow-up period. Discussion: Results of the ASIC-E4 project will bridge the gap related to limited knowledge of the synaptic and inflammatory changes and their association with each other and Aβ in “at-risk” individuals. Thorough in vivo characterization of the biomarker profiles in this population will produce valuable information for diagnostic purposes and future drug development, where the field has already started to look beyond Aβ

Segregation, precipitation, and α-α' phase separation in Fe-Cr alloys

Iron-chromium alloys, the base components of various stainless steel grades, have numerous technologically and scientifically interesting properties. However, these features are not yet sufficiently understood to allow their full exploitation in technological applications. In this work, we investigate segregation, precipitation, and phase separation in Fe-Cr systems analyzing the physical mechanisms behind the observed phenomena. To get a comprehensive picture of Fe-Cr alloys as a function of composition, temperature, and time the present investigation combines Monte Carlo simulations using semiempirical interatomic potential, first-principles total energy calculations, and experimental spectroscopy. In order to obtain a general picture of the relation of the atomic interactions and properties of Fe-Cr alloys in bulk, surface, and interface regions several complementary methods have to be used. Using the exact muffin-tin orbitals method with the coherent potential approximation (CPA-EMTO) the effective chemical potential as a function of Cr content (0–15 at. % Cr) is calculated for a surface, second atomic layer, and bulk. At ∼10 at. % Cr in the alloy the reversal of the driving force of a Cr atom to occupy either bulk or surface sites is obtained. The Cr-containing surfaces are expected when the Cr content exceeds ∼10 at. %. The second atomic layer forms about a 0.3 eV barrier for the migration of Cr atoms between the bulk and surface atomic layer. To get information on Fe-Cr in larger scales we use semiempirical methods. However, for Cr concentration regions less than 10 at. %, the ab initio (CPA-EMTO) result of the important role of the second atomic layer to the surface is not reproducible from the large-scale Monte Carlo molecular dynamics (MCMD) simulation. On the other hand, for the nominal concentration of Cr larger than 10 at. % the MCMDsimulations show the precipitation of Cr into isolated pockets in bulk Fe-Cr and the existence of the upper limit of the solubility of Cr into Fe layers in Fe/Cr layer systems. For high Cr concentration alloys the performed spectroscopic measurements support the MCMD simulations. Hard x-ray photoelectron spectroscopy and Auger electron spectroscopy investigations were carried out to explore Cr segregation and precipitation in the Fe/Cr double layer and Fe0.95Cr0.05 and Fe0.85Cr0.15 alloys. Initial oxidation of Fe-Cr was investigated experimentally at 10−8 Torr pressure of the spectrometers showing intense Cr2O3 signal. Cr segregation and the formation of Cr-rich precipitates were traced by analyzing the experimental atomic concentrations and chemical shifts with respect to annealing time, Cr content, and kinetic energy of the exited electron.</p

Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts

BackgroundRegular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.ObjectiveTo identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.DesignWe conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.ResultsHeritability estimates for fish and EPA+DHA consumption ranged from 0.13–0.24 and 0.12–0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA.ConclusionsThese novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.</div

Validation of the Finnish version of the SCOFF questionnaire among young adults aged 20 to 35 years

<p>Abstract</p> <p>Background</p> <p>We tested the validity of the SCOFF, a five-question screening instrument for eating disorders, in a general population sample.</p> <p>Methods</p> <p>A random sample of 1863 Finnish young adults was approached with a questionnaire that contained several screens for mental health interview, including the SCOFF. The questionnaire was returned by 1316 persons. All screen positives and a random sample of screen negatives were invited to SCID interview. Altogether 541 subjects participated in the SCID interview and had filled in the SCOFF questionnaire. We investigated the validity of the SCOFF in detecting current eating disorders by calculating sensitivity, specificity, and positive and negative predictive values (PPV and NPV) for different cut-off scores. We also performed a ROC analysis based on these 541 persons, of whom nine had current eating disorder.</p> <p>Results</p> <p>The threshold of two positive answers presented the best ability to detect eating disorders, with a sensitivity of 77.8%, a specificity of 87.6%, a PPV of 9.7%, and a NPV of 99.6%. None of the subjects with current eating disorder scored zero points in the SCOFF.</p> <p>Conclusion</p> <p>Due to its low PPV, there are limitations in using the SCOFF as a screening instrument in unselected population samples. However, it might be used for ruling out the possibility of eating disorders.</p

Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts

Background: Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences. Objective: To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption. Design: We conducted genome-wide association (GWA) meta-analysis of fish (n = 86, 467) and EPA +DHA (n = 62, 265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts. Results: Heritability estimates for fish and EPA+DHA consumption ranged from 0.13

Gene × dietary pattern interactions in obesity: Analysis of up to 68 317 adults of European ancestry

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GR