| 1. |
|
|
| 2. |
- Antoniadou-Plytaria, Kyriaki, 1989, et al.
(författare)
-
Effect of Short-term and High-resolution Load Forecasting Errors on Microgrid Operation Costs
- 2022
-
Ingår i: IEEE PES Innovative Smart Grid Technologies Conference Europe. - 9781665480321 ; 2022-October
-
Konferensbidrag (refereegranskat)abstract
- The aim of this paper is to evaluate the effect of the load forecasting errors to the operation costs of a grid-connected microgrid. To this end, a microgrid energy scheduling optimization model was tested with deterministic and stochastic formulations under two solution approaches i.e., day-ahead and rolling horizon optimization. In total, twelve simulation test cases were designed receiving as input the forecasts provided by one of the three implemented machine learning models: linear regression, artificial neural network with backpropagation, and long short-term memory. Simulation results of the weekly operation of a real residential building (HSB Living Lab) showed no significant differences among the costs of the test cases for a daily mean absolute percentage forecast error of about 12%. These results suggest that operators of similar microgrid systems could use simplifying approaches, such as day-ahead deterministic optimization, and forecasts of similar, non-negligible accuracy without substantially affecting the microgrid's total cost as compared to the ideal case of perfect forecast. Improving the accuracy would mainly reduce the microgrid's peak power cost as shown by its 20.2% increase in comparison to the ideal case.
|
|
| 3. |
|
|
| 4. |
- Burmeister, Jason J., et al.
(författare)
-
In vivo electrochemical studies of optogenetic control of glutamate signaling measured using enzyme-based ceramic microelectrode arrays
- 2018
-
Ingår i: Neuromethods. - New York, NY : Springer New York. - 1940-6045 .- 0893-2336. ; 130, s. 327-351
-
Bokkapitel (refereegranskat)abstract
- Direct electrochemical measurements of glutamate release in vivo were combined with optogenetics in order to examine light-induced control of glutamate neurotransmission in the rodent brain. Self-referenced recordings of glutamate using ceramic-based microelectrode arrays (MEAs) in hippocampus and frontal cortex demonstrated precise optical control of light-induced glutamate release through channelrhodopsin (ChR2) expression in both rat hippocampus and frontal cortex. Although the virus was only injected unilaterally, bilateral and rostro-caudal expression was observed in slice imaging, indicating diffusion and active transport of the viral particles. Methodology for the optogenetic control of glutamate signaling in the rat brain is thoroughly explained with special attention paid to MEA enzyme coating and cleaning for the benefit of other investigators. These data support that optogenetic control of glutamate signaling is robust with certain advantages as compared to other methods to modulate the in vivo control of glutamate signaling.
|
|
| 5. |
- Cardell, L O, et al.
(författare)
-
Genes regulating molecular and cellular functions in noninfectious nonallergic rhinitis.
- 2009
-
Ingår i: Allergy. - : Wiley. - 1398-9995 .- 0105-4538. ; 64:9, s. 1301-8
-
Tidskriftsartikel (refereegranskat)abstract
- Chronic noninfectious, nonallergic rhinitis (NINAR) is a complex syndrome with a principally unknown pathophysiology. New technology has made it possible to examine differentially expressed genes and according to network theory, genes connected by their function that might have key roles in the disease.
|
|
| 6. |
- Decressac, Mickael, et al.
(författare)
-
TFEB-mediated autophagy rescues midbrain dopamine neurons from α-synuclein toxicity.
- 2013
-
Ingår i: Proceedings of the National Academy of Sciences. - : Proceedings of the National Academy of Sciences. - 1091-6490 .- 0027-8424. ; 110:19, s. 1817-1826
-
Tidskriftsartikel (refereegranskat)abstract
- The aggregation of α-synuclein plays a major role in Parkinson disease (PD) pathogenesis. Recent evidence suggests that defects in the autophagy-mediated clearance of α-synuclein contribute to the progressive loss of nigral dopamine neurons. Using an in vivo model of α-synuclein toxicity, we show that the PD-like neurodegenerative changes induced by excess cellular levels of α-synuclein in nigral dopamine neurons are closely linked to a progressive decline in markers of lysosome function, accompanied by cytoplasmic retention of transcription factor EB (TFEB), a major transcriptional regulator of the autophagy-lysosome pathway. The changes in lysosomal function, observed in the rat model as well as in human PD midbrain, were reversed by overexpression of TFEB, which afforded robust neuroprotection via the clearance of α-synuclein oligomers, and were aggravated by microRNA-128-mediated repression of TFEB in both A9 and A10 dopamine neurons. Delayed activation of TFEB function through inhibition of mammalian target of rapamycin blocked α-synuclein induced neurodegeneration and further disease progression. The results provide a mechanistic link between α-synuclein toxicity and impaired TFEB function, and highlight TFEB as a key player in the induction of α-synuclein-induced toxicity and PD pathogenesis, thus identifying TFEB as a promising target for therapies aimed at neuroprotection and disease modification in PD.
|
|
| 7. |
- Gil-Lespinard, Mercedes, et al.
(författare)
-
Plasma concentration of 36 (poly)phenols and prospective body weight change in participants from the EPIC cohort
- 2024
-
Ingår i: Annals of Nutrition and Metabolism. - : S. Karger. - 0250-6807 .- 1421-9697. ; 80:2, s. 87-100
-
Tidskriftsartikel (refereegranskat)abstract
- Introduction: Dietary intake of (poly)phenols has been linked to reduced adiposity and body weight (BW) in several epidemiological studies. However, epidemiological evidence on (poly)phenol biomarkers, particularly plasma concentrations, is scarce. We aimed to investigate the associations between plasma (poly)phenols and prospective BW change in participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.Methods: This study included 761 participants with data on BW at baseline and after 5 years of follow-up. Plasma concentrations of 36 (poly)phenols were measured at baseline using liquid chromatography-tandem mass spectrometry. Associations were assessed through general linear mixed models and multinomial logistic regression models, using change in BW as a continuous or as a categorical variable (BW loss, maintenance, gain), respectively. Plasma (poly)phenols were assessed as log2-transformed continuous variables. The false discovery rate (FDR) was used to control for multiple comparisons.Results: Doubling plasma (poly)phenol concentrations showed a borderline trend towards a positive association with BW loss. Plasma vanillic acid showed the strongest association (−0.53 kg/5 years; 95% confidence interval [CI]: −0.99, −0.07). Similar results were observed for plasma naringenin comparing BW loss versus BW maintenance (odds ratio: 1.1; 95% CI: 1.0, 1.2). These results did not remain significant after FDR correction.Conclusion: Higher concentrations of plasma (poly)phenols suggested a tendency towards 5-year BW maintenance or loss. While certain associations seemed promising, they did not withstand FDR correction, indicating the need for caution in interpreting these results. Further studies using (poly) phenol biomarkers are needed to confirm these suggestive protective trends.
|
|
| 8. |
- Haubro Andersen, Pia, et al.
(författare)
-
Towards Machine Recognition of Facial Expressions of Pain in Horses
- 2021
-
Ingår i: Animals. - : MDPI. - 2076-2615. ; 11:6
-
Forskningsöversikt (refereegranskat)abstract
- Simple Summary Facial activity can convey valid information about the experience of pain in a horse. However, scoring of pain in horses based on facial activity is still in its infancy and accurate scoring can only be performed by trained assessors. Pain in humans can now be recognized reliably from video footage of faces, using computer vision and machine learning. We examine the hurdles in applying these technologies to horses and suggest two general approaches to automatic horse pain recognition. The first approach involves automatically detecting objectively defined facial expression aspects that do not involve any human judgment of what the expression "means". Automated classification of pain expressions can then be done according to a rule-based system since the facial expression aspects are defined with this information in mind. The other involves training very flexible machine learning methods with raw videos of horses with known true pain status. The upside of this approach is that the system has access to all the information in the video without engineered intermediate methods that have filtered out most of the variation. However, a large challenge is that large datasets with reliable pain annotation are required. We have obtained promising results from both approaches. Automated recognition of human facial expressions of pain and emotions is to a certain degree a solved problem, using approaches based on computer vision and machine learning. However, the application of such methods to horses has proven difficult. Major barriers are the lack of sufficiently large, annotated databases for horses and difficulties in obtaining correct classifications of pain because horses are non-verbal. This review describes our work to overcome these barriers, using two different approaches. One involves the use of a manual, but relatively objective, classification system for facial activity (Facial Action Coding System), where data are analyzed for pain expressions after coding using machine learning principles. We have devised tools that can aid manual labeling by identifying the faces and facial keypoints of horses. This approach provides promising results in the automated recognition of facial action units from images. The second approach, recurrent neural network end-to-end learning, requires less extraction of features and representations from the video but instead depends on large volumes of video data with ground truth. Our preliminary results suggest clearly that dynamics are important for pain recognition and show that combinations of recurrent neural networks can classify experimental pain in a small number of horses better than human raters.
|
|
| 9. |
- Hounkpatin, Ozias, et al.
(författare)
-
Predicting the spatial distribution of soil organic carbon stock in Swedish forests using a group of covariates and site-specific data
- 2021
-
Ingår i: Soil. - : Copernicus GmbH. - 2199-3971 .- 2199-398X. ; 7, s. 377-398
-
Tidskriftsartikel (refereegranskat)abstract
- The status of the soil organic carbon (SOC) stock at any position in the landscape is subject to a complex interplay of soil state factors operating at different scales and regulating multiple processes resulting either in soils acting as a net sink or net source of carbon. Forest landscapes are characterized by high spatial variability, and key drivers of SOC stock might be specific for sub-areas compared to those influencing the whole landscape. Consequently, separately calibrating models for sub-areas (local models) that collectively cover a target area can result in different prediction accuracy and SOC stock drivers compared to a single model (global model) that covers the whole area. The goal of this study was therefore to (1) assess how global and local models differ in predicting the humus layer, mineral soil, and total SOC stock in Swedish forests and (2) identify the key factors for SOC stock prediction and their scale of influence.We used the Swedish National Forest Soil Inventory (NFSI) database and a digital soil mapping approach to evaluate the prediction performance using random forest models calibrated locally for the northern, central, and southern Sweden (local models) and for the whole of Sweden (global model). Models were built by considering (1) only site characteristics which are recorded on the plot during the NFSI, (2) the group of covariates (remote sensing, historical land use data, etc.) and (3) both site characteristics and group of covariates consisting mostly of remote sensing data.Local models were generally more effective for predicting SOC stock after testing on independent validation data. Using the group of covariates together with NFSI data indicated that such covariates have limited predictive strength but that site-specific covariates from the NFSI showed better explanatory strength for SOC stocks. The most important covariates that influence the humus layer, mineral soil (0-50 cm), and total SOC stock were related to the site-characteristic covariates and include the soil moisture class, vegetation type, soil type, and soil texture. This study showed that local calibration has the potential to improve prediction accuracy, which will vary depending on the type of available covariates.
|
|
| 10. |
- Leclercq, Anna, et al.
(författare)
-
Perceived sidedness and correlation to vertical movement asymmetries in young warmblood horses
- 2023
-
Ingår i: PLoS ONE. - 1932-6203. ; 18
-
Tidskriftsartikel (refereegranskat)abstract
- The prevalence of vertical asymmetries is high in "owner-sound" warmblood riding horses, however the origin of these asymmetries is unknown. This study investigated correlations between vertical asymmetries and motor laterality. Young warmblood riding horses (N = 65), perceived as free from lameness were evaluated on three visits, each comprising objective gait analysis (inertial measurement units system) and a rider questionnaire on perceived sidedness of the horse. A subgroup (N = 40) of horses were also subjected to a forelimb protraction preference test intended as an assessment of motor laterality. We hypothesized associations between vertical asymmetry and motor laterality as well as rider-perceived sidedness. Vertical asymmetry was quantified as trial means of the stride-by-stride difference between the vertical displacement minima and maxima of the head (HDmin, HDmax) and pelvis (PDmin, PDmax). Laterality indexes, based on counts of which limb was protracted, and binomial tests were used to draw conclusions from the preference tests. In the three visits, 60-70% of horses exhibited vertical asymmetries exceeding clinically used thresholds for & GE;1 parameter, and 22% of horses exhibited a side preference in the preference test as judged by binomial tests. Linear mixed models identified a weak but statistically significant correlation between perceived hindlimb weakness and higher PDmin values attributable to either of the hindlimbs (p = 0.023). No other statistically significant correlations to vertical asymmetry were seen for any of the questionnaire answers tested. Tests of correlation between the absolute values of laterality index and asymmetry parameters (HDmin, HDmax, PDmin, PDmax) identified a weak correlation (p = 0.049) with PDmax, but when accounting for the direction of asymmetry and motor laterality, no correlations were seen for either of the asymmetry parameters. No convincing evidence of associations between vertical asymmetries and motor laterality were seen and further studies investigating motor laterality and the origin of vertical asymmetries are needed.
|
|
