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Figure 2 in EVALUATION OF THE EFFECTIVENESS OF USING A UNIVERSAL METHOD FOR ISOLATING GENOMIC dsDNA BY SALTING OUT TECHNIQUE ACCORDING TO THE S.M. ALJANABI AND I. MARTINEZ PROTOCOL FOR YEAST SACCHAROMYCES CEREVISIAE
Figure 2. Quantification of extracted Saccharomyces cerevisiae DNA by UVVis Spectrophotometry (DNA samples: 1–15).
Fig. 5 in Effects Of The Environmental Variables On The Alien Amphipod Pontogammarus Robustoides In The Daugava River And Its Reservoirs
Fig. 5. Ordination diagramm of RDA between data of the individual size groups of P. robustoides and environmental variables identified as significant (p<0.05) by Monte Carlo permutation test for study area. PR, P – Pļaviņas Reservoir, Pikstere, PR, VB - Pļaviņas Reservoir, Vārpu backwater, PR, GB - Pļaviņas Reservoir, Gobena backwater, PR, US - Pļaviņas Reservoir, upper stretch, DK – Daugava River, Klidziņa, KR, N – Ķegums Reservoir, Ņega, KR, G – Ķegums Reservoir, Graužupīte, RR, T – Riga Reservoir, Tome, RR, O - Riga Reservoir, Ogre, DR – Daugava River, Riga; ORP – oxred potential
Fig. 3 in Effects Of The Environmental Variables On The Alien Amphipod Pontogammarus Robustoides In The Daugava River And Its Reservoirs
Fig. 3. Seasonal changes of the physico-chemical parameters and relative water level in the Pļaviņas Reservoir.
Fig. 2 in Effects Of The Environmental Variables On The Alien Amphipod Pontogammarus Robustoides In The Daugava River And Its Reservoirs
Fig. 2. Seasonal changes of the water level in the Daugava River (the hydrological station at Jēkabpils) and the Pļaviņas Reservoir (the hydrological station at Pļaviņas).
Fig. 3 in An Effectiveness Of Artemia Nauplii Enrichment With Polyunsaturated Fatty Acids Using A Supplement Easy Dha Selco
Fig. 3. Lipase (А) та α-amylase (B) activities in Artemia nauplii at the different schemes of bioencapsulation with Easy DHA Selco.
Fig. 4 in Positive Effect Of Compost Application On Oil Pumpkins Growth And Zinc Enrichment
Fig. 4. Zinc accumulation in pumpkin seeds, depending on the level of zinc in compost (no significant differences; p> 0,05).
Fig. 1 in Positive Effect Of Compost Application On Oil Pumpkins Growth And Zinc Enrichment
Fig. 1. Variation in mean temperatures during vegetation season (in May-August), 2016 compared with the average multi-annual temperature DV (Galvonaitė et al. 2013).
Fig. 2 in An Effectiveness Of Artemia Nauplii Enrichment With Polyunsaturated Fatty Acids Using A Supplement Easy Dha Selco
Fig. 2. Total proteolytic activity in Artemia nauplii at the different pH during bioencapsulation with Easy DHA Selco (A – pH 4.8; B – pH 7.4; C – pH 9.0).
Fig. 5. Emys orbicularis habitat 3 in P R O J E C T S O N E M Y S O R B I C U L A R I S (R E P T I L I A: Testudines: Emydidae) In Latvia For Thirty Years (1984 - 2014): Biological Aspects, Results And Effect On Population And Ecosystems
Fig. 5. Emys orbicularis habitat 3 in Silene Nature Park before restoration (Google Earth service, SAS services).
Fig. 4. Emys orbicularis habitats 1 and 2 in P R O J E C T S O N E M Y S O R B I C U L A R I S (R E P T I L I A: Testudines: Emydidae) In Latvia For Thirty Years (1984 - 2014): Biological Aspects, Results And Effect On Population And Ecosystems
Fig. 4. Emys orbicularis habitats 1 and 2 in Silene Nature Park before (a) and after (b) restoration (Google Earth service, SAS services).
Fig. 2 in P R O J E C T S O N E M Y S O R B I C U L A R I S (R E P T I L I A: Testudines: Emydidae) In Latvia For Thirty Years (1984 - 2014): Biological Aspects, Results And Effect On Population And Ecosystems
Fig. 2. Old Emys orbicularis female, found in 1984 in Daugavpils living for 20 years in a zooculture (Photo: 2005).
Fig. 6. Emys orbicularis habitat 3 in P R O J E C T S O N E M Y S O R B I C U L A R I S (R E P T I L I A: Testudines: Emydidae) In Latvia For Thirty Years (1984 - 2014): Biological Aspects, Results And Effect On Population And Ecosystems
Fig. 6. Emys orbicularis habitat 3 in Silene Nature Park after restoration (Google Earth service, SAS services).
Fig. 4 in The role of vegetated areas on fish assemblage of the Paraná River floodplain: effects of different hydrological conditions
Fig. 4. NMDS ordination of dominant fish for different hydrologic condition (HW = high water, FW receding water, IS isolation) and sites (S). Ope = Odontostilbe pequira, Cvo = Cyphocharax voga, Spi = Serrapinnus calliurus, Abi = Astyanax bimaculatus, Pli = Prochilodus lineatus, Mdi = Moenkhausia dichroura, Gba = Gymnogeophagus balzanii, Rbo = Roeboides microlepis, Opa = Odontostilbe paraguayensis, Dte = Diapoma terofali.
Fig. 2 in The role of vegetated areas on fish assemblage of the Paraná River floodplain: effects of different hydrological conditions
Fig. 2. Water level fluctuations of the Paraná River at Corrientes between 1997 and 2001. The Sites were connected with the Paraná River above the hydrological level indicated by the horizontal lines. The number of flooding days (in parentheses) indicates the connectivity between the floodplain and the river channel.
Fig. 3 in The role of vegetated areas on fish assemblage of the Paraná River floodplain: effects of different hydrological conditions
Fig. 3. Cluster analysis based on Jaccard distance (UPGMA method) of fish assemblages in the seven floodplain lakes. A. March 1999 (after a long lasting inundation phase of the Paraná River), B-September 1999 (at receding water) and C- February 2000 (during isolation).
Data from: Evaluating Window Size Effects on Univariate Time Series Forecasting with Machine Learning
<p>In the realm of time series prediction modeling, the window size (w) is a critical hyperparameter that determines the number of time units included in each example provided to a learning model. This hyperparameter is crucial because it allows the learning model to recognize both long-term and short-term trends, as well as seasonal patterns, while reducing sensitivity to random noise. This study aims to elucidate the impact of window size on the performance of machine learning algorithms in univariate time series forecasting tasks. To achieve this, we employed 40 time series from two different domains, conducting experiments with varying window sizes using four types of machine learning algorithms: Bagging, Boosting, Stacking, and a Recurrent Neural Network (RNN) architecture. The results reveal that increasing the window size generally enhances the evaluation metric values up to a stabilization point, beyond which further increases do not significantly improve predictive accuracy. This stabilization effect was observed in both domains when w values exceeded 100 time steps. Moreover, the study found that RNN architectures do not consistently outperform ensemble models in various univariate time series forecasting scenarios.</p>
Data for: Effects of testosterone on gene expression are concordant between sexes but divergent across species of Sceloporus lizards
<p>Hormones mediate sexual dimorphism by regulating sex-specific patterns of gene expression, but it is unclear how much of this regulation involves sex-specific hormone levels versus sex-specific transcriptomic responses to the same hormonal signal. Moreover, transcriptomic responses to hormones can evolve, but the extent to which hormonal pleiotropy in gene regulation is conserved across closely related species is not well understood. We addressed these issues by elevating testosterone levels in juvenile females and males of three <em>Sceloporus </em>lizard species prior to sexual divergence in circulating testosterone<em>, </em>then characterizing transcriptomic responses in the liver. In each species, more genes were responsive to testosterone in males than in females, suggesting that early developmental processes prime sex-specific transcriptomic responses to testosterone later in life. However, overall transcriptomic responses to testosterone were concordant between sexes, with no genes exhibiting sex-by-treatment interactions. By contrast, hundreds of genes exhibited species-by-treatment interactions, particularly when comparing distantly related species with different patterns of sexual dimorphism, suggesting evolutionary lability in gene regulation by testosterone. Collectively, our results indicate that early organizational effects may lead to sex-specific differences in the magnitude, but not the direction, of transcriptomic responses to testosterone, and that the hormone-genome interface accrues regulatory changes over evolutionary time.</p>
Figure 2 in Effects of dams on demographic structures of amphidromous fish and crustacean species in Caribbean rivers
Figure 2. – Individual number histograms of each species broken down by size classes (mm) (left chart) and cohort extraction (right chart) downstream of the Grand Carbet River in March. Right chart: red curves are each cohort extracted by the model; green curve is the cumulative individual number in the modelled age groups.
Figure 1 in Effects of dams on demographic structures of amphidromous fish and crustacean species in Caribbean rivers
Figure 1. – Map of Guadeloupe with the three sampled rivers (bold lines) and study sites: downstream and upstream the water intakes (●) and the first riffle from the mouth of the rivers (Ì).
Figure 7 in Effects of dams on demographic structures of amphidromous fish and crustacean species in Caribbean rivers
Figure 7. – Individual number histograms of each species broken down by size classes (mm) for the three stations (top chart) and porosity chart of the Moreau River water intake (bottom chart). Bottom chart: dotted black line indicates 50% crossing; dotted grey lines indicate the mean crossing rate for these size classes. The size of the downstream and upstream populations of Macrobrachium faustinum and M. heterochirus are too small and fragmented to be presented.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.