Assessing the impact of employing machine learning-based baseline load prediction pipelines with sliding-window training scheme on offered flexibility estimation for different building categories

The present study is focused on assessing the impact of the performance of baseline load prediction pipelines on the estimation (by the grid operator) accuracy of the flexibility offered by different categories of buildings. Accordingly, the corresponding impact of employing different machine learning (ML) algorithms, with sliding-window and offline training schemes, for hour-ahead baseline load prediction has been investigated and compared. Using a smart meter measurements dataset, training window sizes and the most promising pipeline for each building category are first identified. Next, the consumption profiles of five buildings (belonging to each category), with the regular operation (baseline load) and while offering flexibility, are physically simulated. Finally, the identified pipelines are used for predicting the baseline loads, and the resulting error in estimating the provided flexibility is determined. Obtained results demonstrate that the identified most promising prediction pipeline (extra trees algorithm with a sliding window of 5 weeks) offers a notably superior performance compared to that of offline training (average R2 score of 0.91 vs. 0.87). Employing these pipelines permits estimating the provided flexibility with acceptable accuracy (flexibility index's mean relative error between -2.45% to +2.79%), permitting the grid operator to guarantee fair compensation for buildings' offered flexibility

5-Meth­oxy-1-(3,4,5-trimethoxy­phen­yl)-1H-indole

The title compound, C18H19NO4, was prepared as an indole derivative with possible anti­mitotic properties. The planes of the indole and trimethoxy­phenyl rings make a dihedral angle of 45.35 (5)° with one another. In the crystal, mol­ecules related by a twofold screw axis exhibit arene C—H⋯arene-π inter­actions which are 3.035 (1) Å in length

Methyl 5,6-dimeth­oxy-1H-indole-2-carboxyl­ate

The title compound, C12H13NO4, was prepared as a precursor to an indole derivative with possible anti­mitotic properties. The mol­ecule is very nearly planar; the maximum deviation of any non-H atom from the mean plane of the indole ring is 0.120 (3) Å for each of two meth­oxy C atoms. The pairs of mol­ecules related by the inversion centre at (0,0,) are connected by two symmetry-equivalent N—H⋯O hydrogen bonds, while the pairs of mol­ecules related by the inversion centre at (0,0,0) exhibit a π-stacking inter­action of the indole rings, with an inter­planar separation of 3.39 (3) Å

Geographic distribution of haplotype diversity at the bovine casein locus

The genetic diversity of the casein locus in cattle was studied on the basis of haplotype analysis. Consideration of recently described genetic variants of the casein genes which to date have not been the subject of diversity studies, allowed the identification of new haplotypes. Genotyping of 30 cattle breeds from four continents revealed a geographically associated distribution of haplotypes, mainly defined by frequencies of alleles at CSN1S1 and CSN3. The genetic diversity within taurine breeds in Europe was found to decrease significantly from the south to the north and from the east to the west. Such geographic patterns of cattle genetic variation at the casein locus may be a result of the domestication process of modern cattle as well as geographically differentiated natural or artificial selection. The comparison of African Bos taurus and Bos indicus breeds allowed the identification of several Bos indicus specific haplotypes (CSN1S1*C-CSN2*A2-CSN3*AI/CSN3*H) that are not found in pure taurine breeds. The occurrence of such haplotypes in southern European breeds also suggests that an introgression of indicine genes into taurine breeds could have contributed to the distribution of the genetic variation observed

Quantifying and Mitigating Motor Phenotypes Induced by Antisense Oligonucleotides in the Central Nervous System [preprint]

Antisense oligonucleotides (ASOs) are emerging as a promising class of therapeutics for neurological diseases. When injected directly into the cerebrospinal fluid, ASOs distribute broadly across brain regions and exert long-lasting therapeutic effects. However, many phosphorothioate (PS)-modified gapmer ASOs show transient motor phenotypes when injected into the cerebrospinal fluid, ranging from reduced motor activity to ataxia or acute seizure-like phenotypes. The effect of sugar and phosphate modifications on these phenotypes has not previously been systematically studied. Using a behavioral scoring assay customized to reflect the timing and nature of these effects, we show that both sugar and phosphate modifications influence acute motor phenotypes. Among sugar analogues, PS-DNA induces the strongest motor phenotype while 2’-substituted RNA modifications improve the tolerability of PS-ASOs. This helps explain why gapmer ASOs have been more challenging to develop clinically relative to steric blocker ASOs, which have a reduced tendency to induce these effects. Reducing the PS content of gapmer ASOs, which contain a stretch of PS-DNA, improves their toxicity profile, but in some cases also reduces their efficacy or duration of effect. Reducing PS content improved the acute tolerability of ASOs in both mice and sheep. We show that this acute toxicity is not mediated by the major nucleic acid sensing innate immune pathways. Formulating ASOs with calcium ions before injecting into the CNS further improved their tolerability, but through a mechanism at least partially distinct from the reduction of PS content. Overall, our work identifies and quantifies an understudied aspect of oligonucleotide toxicology in the CNS, explores its mechanism, and presents platform-level medicinal chemistry approaches that improve tolerability of this class of compounds