Our dataset provides detailed and precise insights into the business, commercial, and industrial aspects of any given area in the USA (Including Point of Interest (POI) Data and Foot Traffic. The dataset is divided into 150x150 sqm areas (geohash 7) and has over 50 variables. - Use it for different applications: Our combined dataset, which includes POI and foot traffic data, can be employed for various purposes. Different data teams use it to guide retailers and FMCG brands in site selection, fuel marketing intelligence, analyze trade areas, and assess company risk. Our dataset has also proven to be useful for real estate investment.- Get reliable data: Our datasets have been processed, enriched, and tested so your data team can use them more quickly and accurately.- Ideal for trainning ML models. The high quality of our geographic information layers results from more than seven years of work dedicated to the deep understanding and modeling of geospatial Big Data. Among the features that distinguished this dataset is the use of anonymized and user-compliant mobile device GPS location, enriched with other alternative and public data.- Easy to use: Our dataset is user-friendly and can be easily integrated to your current models. Also, we can deliver your data in different formats, like .csv, according to your analysis requirements. - Get personalized guidance: In addition to providing reliable datasets, we advise your analysts on their correct implementation.Our data scientists can guide your internal team on the optimal algorithms and models to get the most out of the information we provide (without compromising the security of your internal data).Answer questions like: - What places does my target user visit in a particular area? Which are the best areas to place a new POS?- What is the average yearly income of users in a particular area?- What is the influx of visits that my competition receives?- What is the volume of traffic surrounding my current POS?This dataset is useful for getting insights from industries like:- Retail & FMCG- Banking, Finance, and Investment- Car Dealerships- Real Estate- Convenience Stores- Pharma and medical laboratories- Restaurant chains and franchises- Clothing chains and franchisesOur dataset includes more than 50 variables, such as:- Number of pedestrians seen in the area.- Number of vehicles seen in the area.- Average speed of movement of the vehicles seen in the area.- Point of Interest (POIs) (in number and type) seen in the area (supermarkets, pharmacies, recreational locations, restaurants, offices, hotels, parking lots, wholesalers, financial services, pet services, shopping malls, among others). - Average yearly income range (anonymized and aggregated) of the devices seen in the area.Notes to better understand this dataset:- POI confidence means the average confidence of POIs in the area. In this case, POIs are any kind of location, such as a restaurant, a hotel, or a library. - Category confidences, for example"food_drinks_tobacco_retail_confidence" indicates how confident we are in the existence of food/drink/tobacco retail locations in the area. - We added predictions for The Home Depot and Lowe's Home Improvement stores in the dataset sample. These predictions were the result of a machine-learning model that was trained with the data. Knowing where the current stores are, we can find the most similar areas for new stores to open.How efficient is a Geohash?Geohash is a faster, cost-effective geofencing option that reduces input data load and provides actionable information. Its benefits include faster querying, reduced cost, minimal configuration, and ease of use.Geohash ranges from 1 to 12 characters. The dataset can be split into variable-size geohashes, with the default being geohash7 (150m x 150m).

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Establishment of a syndication flow from the department of Vendée (85) with the data from the “Restoration” schedule with enriched data: name, address, type of restaurant, means of communication (landline phone, e-mail and website), social networks, GPS coordinates, labels, languages spoken, payment methods accepted, opening dates, rates, details of visits, videos.

Digitalizing highway infrastructure is gaining interest in Germany and other countries due to the need for greater efficiency and sustainability. The maintenance of the built infrastructure accounts for nearly 30% of greenhouse gas emissions in Germany. To address this, Digital Twins are emerging as tools to optimize road systems. A Digital Twin of a built asset relies on a geometric-semantic as-is model of the area of interest, where an essential step for automated model generation is the semantic segmentation of reality capture data. While most approaches handle data without considering real-world context, our approach leverages existing geospatial data to enrich the data foundation through an adaptive feature extraction workflow. This workflow is adaptable to various model architectures, from deep learning methods like PointNet++ and PointNeXt to traditional machine learning models such as Random Forest. Our four-step workflow significantly boosts performance, improving overall accuracy by 20% and unweighted mean Intersection over Union (mIoU) by up to 43.47%. The target application is the semantic segmentation of point clouds in road environments. Additionally, the proposed modular workflow can be easily customized to fit diverse data sources and enhance semantic segmentation performance in a model-agnostic way.

Housekeeping genes (HKG) are constitutively expressed in all tissues while tissue-enriched genes (TEG) are expressed at a much higher level in a single tissue type than in others. HKGs serve as valuable experimental controls in gene and protein expression experiments, while TEGs tend to represent distinct physiological processes and are frequently candidates for biomarkers or drug targets. The genomic features of these two groups of genes expressed in opposing patterns may shed light on the mechanisms by which cells maintain basic and tissue-specific functions. Here, we generate gene expression profiles of 42 normal human tissues on custom high-density microarrays to systematically identify 1,522 HKGs and 975 TEGs and compile a small subset of 20 housekeeping genes which are highly expressed in all tissues with lower variance than many commonly used HKGs. Cross-species comparison shows that both the functions and expression patterns of HKGs are conserved. TEGs are enriched with respect to both segmental duplication and copy number variation, while no such enrichment is observed for HKGs, suggesting the high expression of HKGs are not due to high copy numbers. Analysis of genomic and epigenetic features of HKGs and TEGs reveals that the high expression of HKGs across different tissues is associated with decreased nucleosome occupancy at the transcription start site as indicated by enhanced DNase hypersensitivity. Additionally, we systematically and quantitatively demonstrated that the CpG islands' enrichment in HKGs transcription start sites (TSS) and their depletion in TEGs TSS. Histone methylation patterns differ significantly between HKGs and TEGs, suggesting that methylation contributes to the differential expression patterns as well.We have compiled a set of high quality HKGs that should provide higher and more consistent expression when used as references in laboratory experiments than currently used HKGs. The comparison of genomic features between HKGs and TEGs shows that HKGs are more conserved than TEGs in terms of functions, expression pattern and polymorphisms. In addition, our results identify chromatin structure and epigenetic features of HKGs and TEGs that are likely to play an important role in regulating their strikingly different expression patterns. Overall design: We performed microarray experiment on more tissues and probesets in additional to the previous GEO submission (Series GSE11863). In brief, PolyA+ purified RNA pooled from multiple donors of a single human tissue type (e.g. cerebellum) were amplified with random primers and hybridized on a two-color ink-jet oligonucletodie microarray against a common reference pool, comprising ~20 normal adult tissue pools, on custom microarray patterns containing probes to monitor every exon and exon-exon junction in transcript databases, patent databases, and predicted from mouse transcripts. Data were analyzed for gene expression (the average of multiple probes), exon and junction expression, and splice form proportionality.

We describe a bibliometric network characterizing co-authorship collaborations in the entire Italian academic community. The network, consisting of 38,220 nodes and 507,050 edges, is built upon two distinct data sources: faculty information provided by the Italian Ministry of University and Research and publications available in Semantic Scholar. Both nodes and edges are associated with a large variety of semantic data, including gender, bibliometric indexes, authors' and publications' research fields, and temporal information. While linking data between the two original sources posed many challenges, the network has been carefully validated to assess its reliability and to understand its graph-theoretic characteristics. By resembling several features of social networks, our dataset can be profitably leveraged in experimental studies in the wide social network analytics domain as well as in more specific bibliometric contexts. , The proposed network is built starting from two distinct data sources:

the entire dataset dump from Semantic Scholar (with particular emphasis on the authors and papers datasets) the entire list of Italian faculty members as maintained by Cineca (under appointment by the Italian Ministry of University and Research).

By means of a custom name-identity recognition algorithm (details are available in the accompanying paper published in Scientific Data), the names of the authors in the Semantic Scholar dataset have been mapped against the names contained in the Cineca dataset and authors with no match (e.g., because of not being part of an Italian university) have been discarded. The remaining authors will compose the nodes of the network, which have been enriched with node-related (i.e., author-related) attributes. In order to build the network edges, we leveraged the papers dataset from Semantic Scholar: specifically, any two authors are said to be connected if there is at least one pap..., , # Data cleaning and enrichment through data integration: networking the Italian academia

https://doi.org/10.5061/dryad.wpzgmsbwj

Manuscript published in Scientific Data with DOI .

Description of the data and file structure

This repository contains two main data files:

• edge_data_AGG.csv, the full network in comma-separated edge list format (this file contains mainly temporal co-authorship information);
• Coauthorship_Network_AGG.graphml, the full network in GraphML format.Â

along with several supplementary data, listed below, useful only to build the network (i.e., for reproducibility only):

• University-City-match.xlsx, an Excel file that maps the name of a university against the city where its respective headquarter is located;
• Areas-SS-CINECA-match.xlsx, an Excel file that maps the research areas in Cineca against the research areas in Semantic Scholar.

Description of the main data files

The `Coauthorship_Networ...

Flow of syndication with data from the “sports and cultural activities”, “Leisure equipment”, “Cultural heritage”, “Natural heritage” and “Testations” with enriched data: name, address, type of activity/equipment, means of communication (landline phone, e-mail and website), social networks, GPS coordinates, labels, languages spoken, payment methods accepted, opening dates, rates, details of visits, videos.

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Unfortunately, no README file was found for the datano extension, limiting the ability to provide a detailed and comprehensive description. Therefore, the following description is based on the extension name and general assumptions about data annotation tools within the CKAN ecosystem. The datano extension for CKAN, presumably short for "data annotation," likely aims to enhance datasets with annotations, metadata enrichment, and quality control features directly within the CKAN environment. It potentially introduces functionalities for adding textual descriptions, classifications, or other forms of annotation to datasets to improve their discoverability, usability, and overall value. This extension could provide an interface for users to collaboratively annotate data, thereby enriching dataset descriptions and making the data more useful for various purposes. Key Features (Assumed): * Dataset Annotation Interface: Provides a user-friendly interface within CKAN for adding structured or unstructured annotations to datasets and associated resources. This allows for a richer understanding of the data's content, purpose, and usage. * Collaborative Annotation: Supports multiple users collaboratively annotating datasets, fostering knowledge sharing and collective understanding of the data. * Annotation Versioning: Maintains a history of annotations, enabling users to track changes and revert to previous versions if necessary. * Annotation Search: Allows users to search for datasets based on annotations, enabling quick discovery of relevant data based on specific criteria. * Metadata Enrichment: Integrates annotations with existing metadata, enhancing metadata schemas to support more detailed descriptions and contextual information. * Quality Control Features: Includes options to rate, validate, or flag annotations to ensure they are accurate and relevant, improving overall data quality. Use Cases (Assumed): 1. Data Discovery Improvement: Enables users to find specific datasets more easily by searching for datasets based on their annotations and enriched metadata. 2. Data Quality Enhancement: Allows data curators to improve the quality of datasets by adding annotations that clarify the data's meaning, provenance, and limitations. 3. Collaborative Data Projects: Facilitates collaborative data annotation efforts, wherein multiple users contribute to the enrichment of datasets with their knowledge and insights. Technical Integration (Assumed): The datano extension would likely integrate with CKAN's existing plugin framework, adding new UI elements for annotation management and search. It could leverage CKAN's API for programmatic access to annotations and utilize CKAN's security model for managing access permissions. Benefits & Impact (Assumed): By implementing the datano extension, CKAN users can leverage improvements to data discoverability, quality, and collaborative potential. The enhancement can help data curators to refine the understanding and management of data, making it easier to search, understand and promote data driven decision-making.

Abstract Background: Arterial hypertension is a precursor to the development of heart and renal failure, furthermore is associated with elevated oxidative markers. Environmental enrichment of rodents increases performance in memory tasks, also appears to exert an antioxidant effect in the hippocampus of normotensive rats. Objectives: Evaluate the effect of environmental enrichment on oxidative stress in the ventrolateral medulla, heart, and kidneys of renovascular hypertensive rats. Methods: Forty male Fischer rats (6 weeks old) were divided into four groups: normotensive standard condition (Sham-St), normotensive enriched environment (Sham-EE), hypertensive standard condition (2K1C-St), and hypertensive enriched environment (2K1C-EE). Animals were kept in enriched or standard cages for four weeks after all animals were euthanized. The level of significance was at p < 0.05. Results: 2K1C-St group presented higher mean arterial pressure (mmHg) 147.0 (122.0; 187.0) compared to Sham-St 101.0 (94.0; 109.0) and Sham-EE 106.0 (90.8; 117.8). Ventrolateral medulla from 2K1C-EE had higher superoxide dismutase (SOD) (49.1 ± 7.9 U/mg ptn) and catalase activity (0.8 ± 0.4 U/mg ptn) compared to SOD (24.1 ± 9.8 U/mg ptn) and catalase activity (0.3 ± 0.1 U/mg ptn) in 2K1C-St. 2K1C-EE presented lower lipid oxidation (0.39 ± 0.06 nmol/mg ptn) than 2K1C-St (0.53 ± 0.22 nmol/mg ptn) in ventrolateral medulla. Furthermore, the kidneys of 2K1C-EE (11.9 ± 2.3 U/mg ptn) animals presented higher superoxide-dismutase activity than those of 2K1C-St animals (9.1 ± 2.3 U/mg ptn). Conclusion: Environmental enrichment induced an antioxidant effect in the ventrolateral medulla and kidneys that contributes to reducing oxidative damage among hypertensive rats.

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Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.

One manifestation of individualization is a progressively differential response of individuals to the non-shared components of the same environment. Individualization has practical implications in the clinical setting, where subtle differences between patients are often decisive for the success of an intervention, yet there has been no suitable animal model to study its underlying biological mechanisms. Here we show that enriched environment (ENR) can serve as a model of brain individualization. We kept 40 isogenic female C57BL/6JRj mice for 3 months in ENR and compared these mice to an equally sized group of standard-housed control animals, looking at the effects on a wide range of phenotypes in terms of both means and variances. Although ENR influenced multiple parameters and restructured correlation patterns between them, it only increased differences among individuals in traits related to brain and behavior (adult hippocampal neurogenesis, motor cortex thickness, open field and obje...

ABSTRACT This study compared the growth curve models for the live weight and body length of Japanese quail raised under lights of various colors. The Brody, Gompertz, and von Bertalanffy growth models were used to investigate the effect of different colored lights on Japanese quail growth over a period of six weeks (1-42 days). Four lights of different colors, comprising yellow, red, blue, and white, were used in the study. According to the different light colors, the mean and standard error for the live weight and body length on day 42 were calculated as 196.09 and 3.87 g and 29.48 and 0.192 cm, respectively. Furthermore, while the differences in live weight according to the color of the light being used were statistically significant on days 14, 21, and 28, there were significant differences in body length on days 7, 28, 35, and 42, depending on the color of the light used. The highest values of R2 for body length and live weight were 0.9935 and 0.9988; the lowest sum of square error values for body length and live weight were 9.6588 and 10.6623 according to the Gompertz model. Test results did not reveal autocorrelation among serial data except for those grown under red colored lights.

BackgroundHigh throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data.MethodsIn this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data.Results and ConclusionsThe adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied.

Ecosystems are connected by flows of nutrients and organisms. Changes to connectivity and nutrient enrichment may destabilise ecosystem dynamics far from the nutrient source. We used gradostats to examine the effects of trophic connectivity (movement of consumers and producers) versus nutrient-only connectivity on the dynamics of Daphnia pulex (consumers) and algae (resources) in two metaecosystem configurations (linear vs. dendritic). We found that Daphnia peak population size and instability (coefficient of variation; CV) increased as distance from the nutrient input increased, but these effects were lower in metaecosystems connected by all trophic levels compared to nutrient-only connected systems and/or in dendritic compared to linear systems. We examined the effects of trophic connectivity (i.e. both trophic levels move rather than one or the other) using a generic model to qualitatively assess whether the expectations align with the ecosystem dynamics we observed. Analysis of our model shows that increased Daphnia population sizes and fluctuations in consumer-resource dynamics are expected with nutrient connectivity, with this pattern being more pronounced in linear rather than dendritic systems. These results confirm that connectivity may propagate and even amplify instability over a metaecosystem to communities distant from the source disturbance, and suggest a direction for future experiments, that recreate conditions closer to those found in natural systems.

Methods Our gradostat flasks contained simple communities of the water flea Daphnia pulex consuming a mix of three algal species (Pseudokirchneriella subcapitata, Scenedesmus quadricauda, Ankistrodesmus falcatus). This experiment employed a 2x2x2 factorial design to test the importance of ecosystem trophic connectivity (a treatment considering movement of medium only vs. movement of media, phytoplankton and Daphnia between flasks) and metaecosystem configuration (linear or dendritic) on the stability of Daphnia populations and algal communities with two levels of enriched medium input (regular and phosphorus-enriched). Four replicates of this whole design were established, for a total of 32 metaecosystems, run in 9 blocks due to time and space constraints. Each metaecosystem consisted of four “nodes” of 500 mL Erlenmeyer flasks with a foam stopper to allow for gas exchange (128 flasks total), seeded initially with 100 mL algal mix (total average algal density of 2.22 x106 +/- 1.3x104 cells/mL) to which 50 adult Daphnia with eggs (which produce broods of about 15 individuals each week in good conditions (Schwartz 1984) were added before topping off the flask to 500 mL with FLAMES media (Celis-Salgado et al. 2008). Configuration was controlled by unidirectionally connecting flasks in either a linear configuration (in →1→2→3→4→out) or a dendritic configuration (in →1, in→2, 1→3, 2→3, 3→4→out). We chose this as the simplest possible design in which a linear network could be compared to a branched network, with four nodes being the smallest possible number of nodes to create a dendritic configuration, and the two nodes branching into a third, similar to headwater in a river. Flasks were then connected by Tygon tubing and from an inflow reservoir of FLAMES medium (10 μgP/L) or enriched P (70 μgP /L) medium which was pumped through the array of flasks using peristaltic pumps (Watson-Marlow 503S/RL and Rainin Dynamix RP-1). Pumps were set on automatic timers to run for one hour each day at a speed adjusted to move a specific volume of media over that hour. The dilution rate was 10% of the total volume per for all flasks in the linear configurations and the “hub” (3) and “terminal” (4) nodes of the dendritic configurations (50 mL), and 5% per day (25 mL) for the “upstream” nodes in the dendritic configurations (Figure 1). We also controlled functional connectivity, contrasting metaecosystem dynamics when only nutrients moved versus the case when nutrients, resources and consumers moved. To block the flow of organisms in the nutrient-only connectivity treatment, outflow tubing was placed inside an 80-µm nylon mesh held in place with the stopper. Due to colony formation of the phytoplankton and clogging of the mesh, this proved to be an effective retention mechanism also for the algal resources, thus we believe flow of algae was significantly reduced in these treatments compared the trophic connectivity treatments. Though it is possible a small portion of single cells were able to pass through, Scenedesmus is known to form four-cell colonies in the presence of consumers (which we also observed in our algal counts), which are too large to pass through the mesh. As D. pulex were unable to fit through the tubing or survive moving through the peristaltic pumps, in the trophic connectivity treatment, D. pulex were manually moved using a 2mL transfer pipette at a rate of 10% of the population per day (20% were moved after each sampling count as sampling was only done every two days) in all linear nodes and the hub and terminal dendritic nodes, and 5% per day (10% moved after sampling) in the upstream dendritic nodes, in the same downstream direction as media. This type of passive movement at the flow rate of the system would be typical of planktonic animals in rivers that cannot swim upstream. Inflow stock solutions were prepared using FLAMES media (10 μgP/L). Finally, we modified our inflow reservoirs to contain either additionally P-enriched (high P) or regular (low P) FLAMES media. To increase P in the additionally nutrient-enriched treatment without changing pH, 132 μg/L of H2KPO4 and 168 μg/L H2KPO4 were added to our increased P treatment inflow stock solution. For the less-phosphorus treatment, no additional phosphorus was added, but 218 μg/L KCl were added to control for the K added to the high-P medium. See Figure S1 for a photograph of the experimental setup. Experimental Sampling The gradostats were sampled every other day for 30 days. In each node, the concentration of each algal species was measured using a haemocytometer. To estimate Daphnia population size, a 2mL plastic transfer pipette was used to gently agitate, and then sample each node. The number of individuals and two age classes (adult or juvenile) in the pipette were determined and then replaced to the experimental flask. This process was repeated five times, and the average D. pulex count of the five samples was used to estimate Daphnia density/2mL (total number estimated per flask = sampled count average *250). A pilot experiment testing this method proved it had an average error of 17.41 %, equating to 2.5 Daphnia more or less than the expected count at known densities; there is no reason to believe this error was systematic in one direction or the other, or to be systematically biased among our treatments. On Day 30 of the experiment, 40mL samples were taken from each flask to be analysed for total phosphorus concentration (TP). Phosphorus samples were analysed using a standard protocol (Wetzel and Likens 2013) at the GRIL-Université du Québec à Montréal analytical laboratory. Statistical Analysis To quantify the instability of Daphnia populations in experimental gradostats, we determined the peak total Dapnhia population size (as estimated by our density samples) and the coefficient of variation (CV) of Daphnia population size over the course of the experiment. These variables were calculated for each node within each gradostat, as well as in aggregate summed across all nodes for additive Daphnia metapopulation peak and CV. Similarly, population CV and peak density were calculated for each species of alga but we analyse here values based on total algal community density (sum of all species present), as Pseudorkirchinella and Ankistrodesmus were undetectable in most flasks for most of the experiment. Scenedesmus was mostly observed in 4-cell colonies, which is common in the presence of consumers, but we counted the total number of cells, not colonies. All analyses of experimental gradostat data were conducted in R version 4 (Team 2020). Statistical tests of the hypothesis were two-sided and with a level of significance of α=0.05. To determine whether metaecosystem connectivity, configuration and nutrient enrichment, as well as node position (1 upstream to 4 terminal), influenced node Daphnia population instability downstream of the nutrient enrichment source, we analysed the effects of these factors on mean Daphnia population and algal community peak values, on mean Daphnia population and algal community CV log-transformed (natural logarithm) values, and on mean final TP concentrations values, using linear mixed-effects models with the four factors as fixed effects. The mixed model included a random effect for ‘system’ which allowed us to account for a possible clustering in the response variables since the four nodes were connected as metaecosystems. For each of these models, pairwise interactions between factors were tested and terms for non-significant interactions were removed from the final models we report. Assumptions on the model errors (randomness, normality, and homoscedasticity) and the presence of possible influential observations or outliers were assessed with diagnostic plots of the model residuals. Robust standard errors (Huang and Li 2022) were used to adjust for heteroscedasticity. We also measured Daphnia metapopulation and algal metacommunity instability at the scale of the entire metaecosystem. To determine whether metaecosystem connectivity, configuration and nutrient enrichment influenced Daphnia metapopulation and algal metacommunity instability, we analysed the effects of these factors on mean Daphnia metapopulation and algal metacommunity peak values, and on mean CV values, using linear mixed-effects models with the three factors as fixed effects, using the block in which a metaecosystem was run

Supplementary materials (Appendix A and B) for the article:

Traffic Information Enrichment: Creating Long-Term Traffic Speed Prediction Ensemble Model for Better Navigation through Waypoints

Abstract: Traffic speed prediction for a selected road segment from a short-term and long-term perspective is among the fundamental issues of intelligent transportation systems (ITS). During the course of the past two decades, many artefacts (e.g., models) have been designed dealing with traffic speed prediction. However, no satisfactory solution has been found for the issue of a long-term prediction for days and weeks using the vast spatial and temporal data. This article aims to introduce a long-term traffic speed prediction ensemble model using country-scale historic traffic data from 37,002 km of roads, which constitutes 66% of all roads in the Czech Republic. The designed model comprises three submodels and combines parametric and nonparametric approaches in order to acquire a good-quality prediction that can enrich available real-time traffic information. Furthermore, the model is set into a conceptual design which expects its usage for the improvement of navigation through waypoints (e.g., delivery service, goods distribution, police patrol) and the estimated arrival time. The model validation is carried out using the same network of roads, and the model predicts traffic speed in the period of 1 week. According to the performed validation of average speed prediction at a given hour, it can be stated that the designed model achieves good results, with mean absolute error of 4.67 km/h. The achieved results indicate that the designed solution can effectively predict the long-term speed information using large-scale spatial and temporal data, and that this solution is suitable for use in ITS.

Simunek, M., & Smutny, Z. (2021). Traffic Information Enrichment: Creating Long-Term Traffic Speed Prediction Ensemble Model for Better Navigation through Waypoints. Applied Sciences, 11(1), 315. https://doi.org/10.3390/app11010315

Appendix A Examples of the deviation between the average speed and the FreeFlowSpeed for selected hours.

Appendix B The text file provides a complete overview of all road segments on which basis summary test results were calculated in Section 6 of the article.

A high-throughput method was developed for the automated enrichment of newly synthesized proteins (NSPs), which are labeled metabolically by substituting methionine with the “click-able” analogue azidohomoalanine (AHA). A suitable conjugate containing a dibenzocyclooctyne (DBCO) group allows the specific selection of NSPs by a fast 1 h click chemistry-based reaction with AHA. Through an automated pipetting platform, the samples are loaded into streptavidin cartridges for the selective binding of the NSPs by means of a biotin bait contained in the conjugate. The enriched proteins are eluted by a reproducible chemical cleavage of the 4,4-dimethyl-2,6-dioxocyclohexylidene (Dde) group in the conjugate, which increases selectivity. The NSPs can be collected and digested in the same well plate, and the resulting peptides can be subsequently loaded for automated cleanup, followed by mass spectrometry analysis. The proposed automated method allows for the robust and effective enrichment of samples in 96-well plates in a period of 3 h. Our developed enrichment method was comprehensively evaluated and then applied to the proteomics analysis of the melanoma A375 cell secretome, after treatment with the cytokines interferon α (IFN-α) and γ (IFN-γ), resulting in the quantification of 283 and 263 proteins, respectively, revealing intricate tumor growth-supportive and -suppressive effects.

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List of 1655 genes with a negative jGRP statistic meaning a down-regulation in LUAD tissues relative to normal tissues on the three LUAD data sets. Table S2. List of 1626 genes with a positive jGRP statistic meaning a up-regulation in LUAD tissues relative to normal tissues on the three LUAD data sets. Table S3. List of 42 KEGG pathways significantly enriched in the DEG lists of jGRP (τ = 0.7) by DAVID. Table S4. List of 57 KEGG pathways significantly enriched in the DEG lists of Fisher’s by DAVID. Table S5. List of 53 KEGG pathways significantly enriched in the DEG lists of AW by DAVID. Table S6. List of 40 KEGG pathways significantly enriched in the DEG lists of RP by DAVID. Table S7. List of 20 KEGG pathways significantly enriched in the DEG lists of Pooled cor by DAVID. (RAR 259 kb)