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Abstract Some of the important geodetic time series used in various Earth science disciplines are provided without uncertainty estimates. This can affect the validity of conclusions based on such data. However, an efficient uncertainty quantification algorithm to tackle this problem is currently not available. Here we present a methodology to approximate the aleatoric uncertainty in time series, called Bayesian Hamiltonian Monte Carlo Autoencoders (BaHaMAs). BaHaMAs is based on three elements: (1) self-supervised autoencoders that learn the underlying structure of the time series, (2) Bayesian machine learning that accurately quantifies the data uncertainty, and (3) Monte Carlo sampling that follows the Hamiltonian dynamics. The method can be applied in various fields in the Earth sciences. As an example, we focus on Atmospheric and Oceanic Angular Momentum time series (AAM and OAM, respectively), which are typically provided without uncertainty information. We apply our methodology to 3-hourly AAM and OAM time series and quantify the uncertainty in the data from 1976 up to the end of 2022. Furthermore, since Length of Day (LOD) is a geodetic time series that is closely connected to AAM and OAM and its short-term prediction is important for various space-geodetic applications, we show that the use of the derived uncertainties alongside the time series of AAM and OAM improves the prediction performance of LOD on average by 17% for different time spans. Finally, a comparison with alternative uncertainty quantification baseline methods, i.e., variational autoencoders and deep ensembles, reveals that BaHaMAs is more accurate in quantifying uncertainty. Graphical Abstract

Abstract Prenatal alcohol-exposed (AE) infants and children often demonstrate disrupted sleep patterns, including more frequent awakenings, reduced total sleep time, and more night-to-night sleep variability. Despite the strong connection between sleep patterns and circadian rhythmicity, relatively little is known about circadian rhythm disruptions in individuals with AE. Recently, several reports demonstrated that evaluating the expression patterns of human clock genes in biological fluids could reveal an individual’s circadian phenotype. Human saliva offers an emerging and easily available physiological sample that can be collected non-invasively for core-clock gene transcript analyses. We compared the expression patterns of core-clock genes and their regulatory genes in salivary samples of children aged 6–10 years-old with and without AE during the light cycle between ZT0-ZT11. We isolated the RNA from the samples and measured the expression patterns of core clock genes and clock regulating genes using the human specific primers with quantitative real-time PCR. Analysis of core clock genes expression levels in saliva samples from AE children indicates significantly altered levels in expression of core-clock BMAL1, CLOCK, PER1-3 and CRY1,2, as compared to those in age-matched control children. We did not find any sex difference in levels of clock genes in AE and control groups. Cosinor analysis was used to evaluate the rhythmic pattern of these clock genes, which identified circadian patterns in the levels of core clock genes in the control group but absent in the AE group. The gene expression profile of a salivary circadian biomarker ARRB1 was rhythmic in saliva of control children but was arhythmic in AE children. Altered expression patterns were also observed in clock regulatory genes: NPAS2, NFL3, NR1D1, DEC1, DEC2, and DBP, as well as chromatin modifiers: MLL1, P300, SIRT1, EZH2, HDAC3, and ZR1D1, known to maintain rhythmic expression of core-clock genes. Overall, these findings provide the first evidence that AE disturbs the circadian patten expression of core clock genes and clock-regulatory chromatin modifiers in saliva.

Abstract Background Prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher in men than in women. Hormonal and genetic causes may account for the sex differences in MASLD. Current human in vitro liver models do not sufficiently take the influence of biological sex and sex hormones into consideration. Methods Primary human hepatocytes (PHHs) were isolated from liver specimen of female and male donors and cultured with sex hormones (17β-estradiol, testosterone and progesterone) for up to 72 h. mRNA expression levels of 8 hepatic lipid metabolism genes were analyzed by RT-qPCR. Sex hormones and their metabolites were determined in cell culture supernatants by LC-MS analyses. Results A sex-specific expression was observed for LDLR (low density lipoprotein receptor) with higher mRNA levels in male than female PHHs. All three sex hormones were metabolized by PHHs and the effects of hormones on gene expression levels varied depending on hepatocyte sex. Only in female PHHs, 17β-estradiol treatment affected expression levels of PPARA (peroxisome proliferator-activated receptor alpha), LIPC (hepatic lipase) and APOL2 (apolipoprotein L2). Further changes in mRNA levels of female PHHs were observed for ABCA1 (ATP-binding cassette, sub-family A, member 1) after testosterone and for ABCA1, APOA5 (apolipoprotein A-V) and PPARA after progesterone treatment. Only the male PHHs showed changing mRNA levels for LDLR after 17β-estradiol and for APOA5 after testosterone treatment. Conclusions Male and female PHHs showed differences in their expression levels of hepatic lipid metabolism genes and their responsiveness towards sex hormones. Thus, cellular sex should be considered, especially when investigating the pathophysiological mechanisms of MASLD.

Abstract In 2021, the International Earth Rotation and Reference Systems Service (IERS) established a working group tasked with conducting the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) to assess the current accuracy of EOP forecasts. From September 2021 to December 2022, EOP predictions submitted by participants from various institutes worldwide were systematically collected and evaluated. This article summarizes the campaign's outcomes, concentrating on the forecasts of the dX, dY, and dψ, dε components of celestial pole offsets (CPO). After detailing the campaign participants and the methodologies employed, we conduct an in-depth analysis of the collected forecasts. We examine the discrepancies between observed and predicted CPO values and analyze their statistical characteristics such as mean, standard deviation, and range. To evaluate CPO forecasts, we computed the mean absolute error (MAE) using the IERS EOP 14 C04 solution as the reference dataset. We then compared the results obtained with forecasts provided by the IERS. The main goal of this study was to show the influence of different methods used on predictions accuracy. Depending on the evaluated prediction approach, the MAE values computed for day 10 of forecast were between 0.03 and 0.16 mas for dX, between 0.03 and 0.12 mas for dY, between 0.07 and 0.91 mas for dψ, and between 0.04 and 0.41 mas for dε. For day 30 of prediction, the corresponding MAE values ranged between 0.03 and 0.12 for dX, and between 0.03 and 0.14 mas for dY. This research shows that machine learning algorithms are the most promising approach in CPO forecasting and provide the highest prediction accuracy (0.06 mas for dX and 0.08 mas for dY for day 10 of prediction). Graphical abstract

The Global Navigation Satellite System (GNSS) is a key asset for tropospheric monitoring. Currently, GNSS meteorology relies primarily on geodetic-grade stations. However, such stations are too costly to be densely deployed, which limits the contribution of GNSS to tropospheric monitoring. In 2016, Google released the raw GNSS measurement application programming interface for smartphones running on Android version 7.0 and higher. Given that nowadays there are billions of Android smartphones worldwide, utilizing those devices for atmospheric monitoring represents a remarkable scientific opportunity. In this study, smartphone GNSS data collected in Germany as part of the Application of Machine Learning Technology for GNSS IoT Data Fusion (CAMALIOT) crowdsourcing campaign in 2022 were utilized to investigate this idea. Approximately 20 000 raw GNSS observation files were collected there during the campaign. First, a dedicated data processing pipeline was established that consists of two major parts: machine learning (ML)-based data selection and ionosphere-free precise point positioning (PPP)-based zenith total delay (ZTD) estimation. The proposed method was validated with a dedicated smartphone data collection experiment conducted on the rooftop of the ETH campus. The results confirmed that ZTD estimates of millimeter-level precision could be achieved with smartphone data collected in an open-sky environment. The impacts of observation time span and utilization of multi-GNSS observations on ZTD estimation were also investigated. Subsequently, the crowdsourced data from Germany were processed by PPP with the ionospheric delays interpolated using observations from surrounding satellite positioning service of the German National Survey (SAPOS) GNSS stations. The ZTDs derived from ERA5 and an ML-based ZTD product served as benchmarks. The results revealed that an accuracy of better than 10 mm can be achieved by utilizing selected high-quality crowdsourced smartphone data. This study demonstrates high-precision ZTD determination with crowdsourced smartphone GNSS data and reveals success factors and current limitations.

Abstract Past and present habitability of Mars have been intensely studied in the context of the search for signals of life. Despite the harsh conditions observed today on the planet, some ancient Mars environments could have harbored specific characteristics able to mitigate several challenges for the development of microbial life. In such environments, Fe2+ minerals like siderite (already identified on Mars), and vivianite (proposed, but not confirmed) could sustain a chemolithoautotrophic community. In this study, we investigate the ability of the acidophilic iron-oxidizing chemolithoautotrophic bacterium Acidithiobacillus ferrooxidans to use these minerals as its sole energy source. A. ferrooxidans was grown in media containing siderite or vivianite under different conditions and compared to abiotic controls. Our experiments demonstrated that this microorganism was able to grow, obtaining its energy from the oxidation of Fe2+ that came from the solubilization of these minerals under low pH. Additionally, in sealed flasks without CO2, A. ferrooxidans was able to fix carbon directly from the carbonate ion released from siderite for biomass production, indicating that it could be able to colonize subsurface environments with little or no contact with an atmosphere. These previously unexplored abilities broaden our knowledge on the variety of minerals able to sustain life. In the context of astrobiology, this expands the list of geomicrobiological processes that should be taken into account when considering the habitability of environments beyond Earth, and opens for investigation the possible biological traces left on these substrates as biosignatures.

Abstract Biochar is the product of intentional pyrolysis of organic feedstocks. It is made under controlled conditions in order to achieve desired physico‐chemical characteristics. These characteristics ultimately affect biochar properties as a soil amendment. When biochar is used for carbon storage, an important property is its persistence in soil, often described by the proportion of biochar carbon remaining in soil after a 100 years (Fperm). We analyzed published data on 1230 biochars to re‐evaluate the effect of pyrolysis parameters on biochar characteristics and the possibility to predict Fperm from the maximum temperature reached during pyrolysis (HTT). We showed that biochar ash and nitrogen (N) contents were mostly affected by feedstock type. The oxygen to carbon (O:C) and hydrogen to carbon (H:C) ratios were mostly affected by the extent of pyrolysis (a combination of HTT and pyrolysis duration), except for non (ligno)cellulosic feedstocks (plastic waste, sewage sludge). The volatile matter (VM) content was affected by both feedstock type and the extent of pyrolysis. We demonstrated that HTT is the main driver of H:C ‐‐ an indicator of persistence ‐‐ but that it is not measured accurately enough to precisely predict H:C, let alone persistence. We examined the equations to estimate Fperm available in the literature and showed that Fperm calculated from HTT presented little agreement with Fperm calculated from H:C. The sign and magnitude of the bias depended on the equation used to calculate Fperm and the dispersion was usually large. This could lead to improper compensation of carbon emissions and wrong reporting of carbon sinks in national carbon accounting schemes. We recommend not to use HTT as a predictor for persistence and stress the importance to rapidly develop more accurate proxies of biochar C persistence in soil.

The main objective of the present work was to assess the ecotoxicological safety of the use of thermochemically treated sewage sludge from the wastewater treatment plant (WWTP) of a distillery plant as a soil additive in agricultural soils based on its physicochemical characteristics and the bioaccumulation of selected elements in the plant tissues of maize (Zea mays). We have carried out physicochemical characterization (pH, EC, Corg, Cinorg, CEC, N, H, ash content, PAHs) of sewage sludge feedstock (SS) and sludge-derived biochar (BC) produced by slow pyrolysis at a temperature of 400 °C. The effect of 1% (w/w) amendment of SS and BC on soil physicochemical properties (pH, EC, Cinorg), germination of ryegrass, soil rhizobacteria and microorganisms, as well as on the accumulation and translocation of selected elements in maize (Zea mays) was studied. The results show that pyrolysis treatment of distillery WWTP sludge at 400 °C increases pH (from 7.3 to 7.7), Corg(from 28.86% to 36.83%), N (from 6.19% to 7.53%), ash content (from 23.59% to 50.99%) and decreases EC (from 2.35 mS/cm to 1.06 mS/cm), CEC (from 118.66 cmol/kg to 55.66 cmol/kg), H (from 6.76% to 1.98%) and Σ18 PAHs content (from 4.03 mg/kg to 3.38 mg/kg). RFA analysis of SS and BC showed that pyrolysis treatment multiplies chromium (Cr) (2.2 times), nickel (Ni) (2.96 times), lead (Pb) (2.13 times), zinc (Zn) (2.79 times), iron (Fe) (1.26 times) in the obtained BC, but based on an ecotoxicological test with earthworms Eisenia fetida, we conclude that pyrolysis treatment reduced the amount of available forms of heavy metals in BC compared to SS. We demonstrated by a pot experiment with a maize that a 1% addition of BC increased soil pH, decreased EC and Cinorg and had no significant effect on heavy metal accumulation in plant tissues. According to the results of the three-level germination test, it also does not affect the germination of cress seeds (Lepidium sativum). There was a significant effect of 1% BC addition on soil microbial community, and we observed a decrease in total microbial biomass and an increase in fungal species variability in the soil. Based on these results, we conclude that BC represents a promising material that can serve as a soil additive and source of nutritionally important elements after optimization of the pyrolysis process.

Resumo: Esse estudo teve como objetivo analisar produções científicas sobre o Ensino de Astronomia na Educação Básica, com enfoque nos anos iniciais do Ensino Fundamental. Especificamente, examinou um período de quinze anos (2007 a 2021) das publicações da revista Caderno Brasileiro de Ensino de Física (CBEF), da UFSC. Foram analisados trabalhos publicados antes, durante e após a aprovação da BNCC e do Ano Internacional da Astronomia, em 2009. A metodologia usada foi a revisão bibliográfica sistemática. Identificou-se consenso sobre a relevância do Ensino de Astronomia, a necessidade de formação contínua de professores e a reavaliação da formação. Observou-se um grande impacto do Ano da Astronomia na quantidade de trabalhos publicados, enquanto a implementação da BNCC relaciona-se a um aumento mais modesto. Constatou-se pouca diversidade regional e de gênero nos trabalhos, apontando para um cenário multifacetado e abrangente, em um campo de pesquisa rico a ser explorado.

Abstract The two-spotted spider mite (TSSM), Tetranychus urticae, is among the most destructive piercing-sucking herbivores, infesting more than 1100 plant species, including numerous greenhouse and open-field crops of significant economic importance. Its prolific fecundity and short life cycle contribute to the development of resistance to pesticides. However, effective resistance loci in plants are still unknown. To advance research on plant-mite interactions and identify genes contributing to plant immunity against TSSM, efficient methods are required to screen large, genetically diverse populations. In this study, we propose an analytical pipeline utilizing high-resolution imaging of infested leaves and an artificial intelligence-based computer program, MITESPOTTER, for the precise analysis of plant susceptibility. Our system accurately identifies and quantifies eggs, feces and damaged areas on leaves without expert intervention. Evaluation of 14 TSSM-infested Arabidopsis thaliana ecotypes originating from diverse global locations revealed significant variations in symptom quantity and distribution across leaf surfaces. This analytical pipeline can be adapted to various pest and host species, facilitating diverse experiments with large specimen numbers, including screening mutagenized plant populations or phenotyping polymorphic plant populations for genetic association studies. We anticipate that such methods will expedite the identification of loci crucial for breeding TSSM-resistant plants.

Printed Circuit Boards (PCBs) are essential components of electronic devices containing valuable silver metal. Using sustainable methods, silver recovery from electronic trash, like PCBs, demonstrates excellent promise. This research’s objective is to determine the optimum leaching time and solid-to-liquid (S/L) ratio for extracting silver from PCB using deep eutectic solvent (DES) composed of choline chloride and glycerol (glyceline DES). The binary DES’s leaching performance was then compared to choline chloride, glycerol, and citric acid ternary systems. Fourier Transform Infrared Spectroscopy (FTIR) was carried out to analyze the bond interactions. X-ray fluorescence spectrometry (XRF) was employed to determine the PCB’s metal concentration prior to and after the leaching process. Ternary DES was viscous, colorless, stable for 60 days, and less acidic than binary DES, with a 1.21 g/mL density. FTIR peak broadening and shifting indicated the formation of a new hydrogen bond and proved a successful synthesis of ternary DES. XRF result showed that PCB’s initial silver metal content was 2.32%. The optimal silver leaching from PCB using glyceline DES was achieved after 16 hours, with a 1/20 solid-to-liquid ratio. Ternary DES demonstrated a silver leaching efficiency of 93.65%, surpassing 86.77% of glyceline. Ternary DES synthesized in this study has the potential to serve as an efficient and environmentally friendly solvent for extracting silver from PCB, providing a sustainable approach to managing electronic waste.

In this study Neem and Yellow oleander biodiesels were blended in some given proportions and characterized. An F165 diesel engine was ran with each blend and its performance parameters evaluated and compared to those obtained when the engine ran on Automotive Gas Oil (AGO). The produced neem oil biodiesel (NOB) and yellow Oleander biodiesel (YOB) were blended together in a percentage ratio of 20:80, 40:60, 60:40 and 50:50 percentages for Neem and Yellow oleander biodiesels respectively. Results show that brake power of the blends is close to that of AGO at lower torques but developed higher power at higher torques (2.69 kWh at 10Nm for N10Y40 and 2.68 kWh for AGO). The blends exhibited close comparison with the AGO in thermal efficiency. The results of the study show a diesel engine perform well with pure biodiesel blends as fuels as it does with fossil AGO, thus new biofuel was produced capable of replacing conventional diesel fuel in the transportation industry.

Background: Development of cirrhosis and hepatocellular carcinoma (HCC) in patients with high alcohol intake is modulated by genetic predispositions. Genetic variation in angiotensin II type 1 receptor (AGTR1) has been described as a risk factor for non-alcoholic fatty liver disease in Asian patients. Methods: We analysed Caucasian patients with alcohol–associated cirrhosis without (n = 238) and with (n = 339) HCC, healthy controls (n = 200), and HCV–infected cirrhotic patients with and without HCC (n = 263) for association with the polymorphisms rs3772622 and rs2276736 in AGTR1. Results: Rs2276736 in AGTR1 was associated with both low–density lipoprotein (LDL) cholesterol levels and hepatic steatosis in patients with alcohol–associated liver disease. The distribution of genotypes for both rs3772622 and rs2276736 in AGTR1 were comparable between controls, cirrhosis patients, and those with HCC. Minor allele frequencies were 32% (44%) in healthy controls, 35%/34% (46%/45%) in alcohol–associated liver disease without/with HCC and 31%/38% (43%/39%) in HCV cirrhosis and HCV HCC, respectively. The genotype of the most important genetic risk factor for fatty liver disease, PNPLA3 I148M, did not interact with the AGTR1 polymorphisms. Conclusion: Genetic variation in AGTR1, although associated with blood lipid levels and hepatic steatosis, is not a risk factor for alcohol–associated cirrhosis or HCC in Caucasians.

Abstract Chronic liver diseases are worldwide on the rise. Due to the rapidly increasing incidence, in particular in Western countries, metabolic dysfunction-associated steatotic liver disease (MASLD) is gaining importance as the disease can develop into hepatocellular carcinoma. Lipid accumulation in hepatocytes has been identified as the characteristic structural change in MASLD development, but molecular mechanisms responsible for disease progression remained unresolved. Here, we uncover in primary hepatocytes from a preclinical model fed with a Western diet (WD) an increased basal MET phosphorylation and a strong downregulation of the PI3K-AKT pathway. Dynamic pathway modeling of hepatocyte growth factor (HGF) signal transduction combined with global proteomics identifies that an elevated basal MET phosphorylation rate is the main driver of altered signaling leading to increased proliferation of WD-hepatocytes. Model-adaptation to patient-derived hepatocytes reveal patient-specific variability in basal MET phosphorylation, which correlates with patient outcome after liver surgery. Thus, dysregulated basal MET phosphorylation could be an indicator for the health status of the liver and thereby inform on the risk of a patient to suffer from liver failure after surgery.

Abstract The difference between observed and modelled precession/nutation reveals unmodelled signals commonly referred to as Celestial Pole Offsets (CPO), denoted by dX and dY. CPO are currently observed only by Very Long Baseline Interferometry (VLBI), but there is nearly 4 weeks of latency by which the data centers provide the most accurate, final CPO series. This latency problem necessitates predicting CPO for high-accuracy, real-time applications that require information regarding Earth rotation, such as spacecraft navigation. Even though the International Earth Rotation and Reference Systems Service (IERS) provides so-called rapid CPO, they are usually less accurate and therefore, may not satisfy the requirements of the mentioned applications. To enhance the quality of CPO predictions, we present a new methodology based on Neural Additive Models (NAMs), a class of interpretable machine learning algorithms. We formulate the problem based on long short-term memory neural networks and derive simple analytical relations for the quantification of prediction uncertainty and feature importance, thereby enhancing the intelligibility of predictions made by machine learning. We then focus on the short-term prediction of CPO with a forecasting horizon of 30 days. We develop an operational framework that consistently provides CPO predictions. Using the CPO series of Jet Propulsion Laboratory as the input to the algorithm, we show that NAMs predictions improve the IERS rapid products on average by 57% for dX and 25% for dY under fully operational conditions. Our predictions are both accurate and overcome the latency issue of final CPO series and thus, can be used in real-time applications. Graphical Abstract

Abstract Glucose homeostasis is maintained by hormones secreted from different cell types of the pancreatic islets and controlled by manifold input including signals mediated through G protein-coupled receptors (GPCRs). RNA-seq analyses revealed expression of numerous GPCRs in mouse and human pancreatic islets, among them Gpr116/Adgrf5. GPR116 is an adhesion GPCR mainly found in lung and required for surfactant secretion. Here, we demonstrate that GPR116 is involved in the somatostatin release from pancreatic delta cells using a whole-body as well as a cell-specific knock-out mouse model. Interestingly, the whole-body GPR116 deficiency causes further changes such as decreased beta-cell mass, lower number of small islets, and reduced pancreatic insulin content. Glucose homeostasis in global GPR116-deficient mice is maintained by counter-acting mechanisms modulating insulin degradation. Our data highlight an important function of GPR116 in controlling glucose homeostasis.

Abstract Small intestinal bacterial overgrowth and compositional changes of intestinal microbiota are pathomechanistic factors in liver cirrhosis leading to bacterial translocation and infectious complications. We analyzed the quantity and composition of duodenal bacterial DNA (bactDNA) in relation to bactDNA in blood and ascites of patients with liver cirrhosis. Duodenal fluid and corresponding blood and ascites samples from 103 patients with liver cirrhosis were collected. Non-liver disease patients (n = 22) served as controls. BactDNA was quantified by 16S-rRNA gene-based PCR. T-RFLP and 16S-rRNA amplicon sequencing were used to analyze bacterial composition. Duodenal bacterial diversity in cirrhosis was distinct to controls showing significantly higher abundances of Streptococcus, Enterococcus and Veillonella. Patients with bactDNA positive ascites revealed reduced spectrum of core microbiota with Streptococcus as key player of duodenal community and higher prevalence of Granulicatella proving presence of cirrhosis related intestinal dysbiosis. Regarding duodenal fluid bactDNA quantification, no significant differences were found between patients with cirrhosis and controls. Additionally, percentage of subjects with detectable bactDNA in blood did not differ between patients and controls. This study evaluated the diversity of bacterial DNA in different body specimens with potential implications on understanding how intestinal bacterial translocation may affect infectious complications in cirrhosis.

New types of extruded snack pellets of wheat-corn blend base and fresh lucerne sprouts were devel-oped. The aim of the study was to examine the effect of fresh lucerne sprouts addition on the water consumption, processing efficiency and the specific mechanical energy during production of wheat-maize snack pellets. Additionally, the total phenolic content and antiradical activity, as well as the water absorption and water solubility indices in samples processed under variable processing conditions were tested. The extrusion-cooking of blends consisted of 10, 20 and 30% of lucerne sprouts was carried out using a single screw extruder at screw speeds of 60 and 100 rpm, and at moisture contents of 32, 34 and 36%. Replacement of wheat-corn flour blends by fresh lucerne sprouts at various levels (10, 20 and 30%) allowed to sufficient reduction of technological water which is needed in extrusion-cooking process of snacks pellets. The limitation of water was from 89 to 100% if fresh lucerne sprouts were used, depending on the recipe and dough moisture level tested. Total phenolic content and antioxidant activity increased significantly due to lucerne sprouts addition. Furthermore, higher water absorption and water solubility index was noted if increased initial mois-ture content was applied during snack pellets processing. It can be concluded that fresh lucerne sprouts can be valuable additives allowing to save the technological water in production process and to obtain the nutritionally valuable supplemented wheat-corn-based snack pellets.

Raw observations (carrier-phase and code observations) from the Global Navigation Satellite System (GNSS) can now be accessed from Android mobile phones (Version 7.0 onwards). This paves the way for GNSS data to be utilized for low-cost precise positioning or in ionospheric or tropospheric applications. This paper presents results from data collection campaigns using the CAMALIOT mobile app. In the first campaign, 116.3 billion measurements from 11,828 mobile devices were collected from all continents. Although participation decreased during the second campaign, data are still being collected globally. In this contribution, we demonstrate the potential of volunteered geographic information (VGI) from mobile phones to fill data gaps in geodetic station networks that collect GNSS data, e.g. in Brazil, but also how the data can provide a denser set of observations than current networks in countries across Europe. We also show that mobile phones capable of dual-frequency reception, which is an emerging technology that can provide a richer source of GNSS data, are contributing in a substantial way. Finally, we present the results from a survey of participants to indicate that participation is diverse in terms of backgrounds and geography, where the dominant motivation for participation is to contribute to scientific research.

The article presents the possibilities of using by-products from the agri-food industry in the form of fruit and vegetable pomace as a supplementary ingredient to extruded food products in the form of snack pellets. In the recipe based on potato starch, pomace from apples, chokeberries, pumpkin, nigella seed and flaxseed were added in amounts of 10%, 20% and 30%. The prepared raw material blends were processed using a single-screw extruder-cooker with a plastification system L/D = 20 and variable screw speed. The aim of the research was to determine the effect of pomace addition on the extrusion-cooking process, i.e., efficiency and energy consumption, as well as on selected physical properties of the obtained food pellets, such as expansion index, bulk density and durability. The addition of selected pomace influenced the extrusion-cooking process and the physical properties of the extrudates. A percentage contribution ranging from 10 to 20% can optimize the extrusion-cooking process and improve the quality characteristics of the final product, while simultaneously utilizing by-products from the agri-food industry and reducing their negative environmental impact.