Bioindicative values of microfungi in starch and possible deficiencies of the new Serbian regulation on food hygiene

The results of tests on the presence of yeasts and molds in cornstarch [AD ‘IPOK’ Zrenjanin, 2007-2008, made at the time when previous Regulations were valid] were analyzed in terms of bioindicative values of microfungi as indicators of quality and safety of raw material or final food products. Microbiological analysis was used to detect the presence of a number of microorganisms MMI-0001, and a questionnaire was designed at the Department of Public Health in Zrenjanin town (Republic of Serbia), where the anal­yses were done, regarding the microbiological tests on starch. In order to rationalize the analyses and make them more economical, several areas of product quality control (water, food, raw materials, space) were recommended either to be excluded or regarded as optional. Thus, analysis of presence of microfungi as indicators of product quality was categorized as optional. The results obtained from this research suggest a different conclusion because the bacteria in the samples indicated ˮmicrobiologically“, namely bacteriologically, safe samples of food, while, on the contrary, the presence of some microfungi as distinct xerophilous or xerotolerant microorganisms, indicated that the food was mycologically non-safe. The obtained data are crucial for questioning the decision to exclude the earlier required (mycological) analysis of the samples (in the production of starch, or end products, etc.) and categorize such analyses in new Regulations as optional, depending on the manufacturer’s preference. Bioindicative values of microfungi as indicators of the quality of starch, clearly point to the shortsightedness of the new Regulations on food hygiene and safety, where tests on certain microorganisms (in this case, yeasts and molds) are not legally defined as mandatory, but the Law leaves manufacturers a possibility to choose (or not to choose) the testing and frequency of testing on the presence (absence) of microorganisms, which can be risky, both in the production and marketing of the finial products. [Projekat Ministarstva nauke Republike Srbije, br. OI-179079

Heavy metals concentration in soils from parks and green areas in Belgrade

The current study included the investigation of several metals and their distribution in urban soils from parks and green areas in the city of Belgrade. The soils were sampled in January and February 2008. The concentrations of Cd, Co, Cu, Pb, Mn and Zn were measured, as well as the pH values and organic matter contents. The obtained results showed that there was a significant level of contamination in some samples, especially with lead, and that it was most probably caused by anthropogenic activities, mostly from traffic. The results were compared with the National legislation and Netherlands standards. Also, the recent results were compared with the data from previous work and it was concluded that there has been a certain increase of the Pb concentration in the past three years. The level of pollution in playground soil was very high and each analyzed sample exceeded the Dutch target value for Cd, Co and Pb

Classification accuracy and compatibility across devices of a new Rapid-E+ flow cytometer

The study evaluated a new model of a Plair SA airflow cytometer, Rapid-E+, and assessed its suitability for airborne pollen monitoring within operational networks. Key features of the new model are compared with the previous one, Rapid-E. A machine learning algorithm is constructed and evaluated for (i) classification of reference pollen types in laboratory conditions and (ii) monitoring in real-life field campaigns. The second goal of the study was to evaluate the device usability in forthcoming monitoring networks, which would require similarity and reproducibility of the measurement signal across devices. We employed three devices and analysed (dis-)similarities of their measurements in laboratory conditions. The lab evaluation showed similar recognition performance to that of Rapid-E, but field measurements in conditions when several pollen types were present in the air simultaneously showed notably lower agreement of Rapid-E+ with manual Hirst-type observations than those of the older model. An exception was the total-pollen measurements. Comparison across the Rapid-E+ devices revealed noticeable differences in fluorescence measurements between the three devices tested. As a result, application of the recognition algorithm trained on the data from one device to another led to large errors. The study confirmed the potential of the fluorescence measurements for discrimination between different pollen classes, but each instrument needed to be trained individually to achieve acceptable skills. The large uncertainty of fluorescence measurements and their variability between different devices need to be addressed to improve the device usability.</p

Influence of meteorological variables and air pollutants on measurements from automatic pollen sampling devices

This study examines the influence of meteorological factors and air pollutants on the performance of automatic pollen monitoring devices, as part of the EUMETNET Autopollen COST ADOPT-intercomparison campaign held in Munich, Germany, during the 2021 pollen season. The campaign offered a unique opportunity to compare all automatic monitors available at the time, a Plair Rapid-E, a Hund-Wetzlar BAA500, an OPC Alphasense, a KH-3000 Yamatronics, three Swisens Polenos, a PollenSense APS, a FLIR IBAC2, a DMT WIBS-5, an Aerotape Sextant, to the average of four manual Hirst traps, under the same environmental conditions. The investigation aimed to elucidate how meteorological factors and air pollution impact particle capture and identification efficiency. The analysis showed coherent results for most devices regarding the correlation between environmental conditions and pollen concentrations. This reflects on one hand, a significant correlation between weather and airborne pollen concentration, and on the other hand the capability of devices to provide meaningful data under the conditions under which measurements were taken. However, correlation strength varied among devices, reflecting differences in design, algorithms, or sensors used. Additionally, it was observed that different algorithms applied to the same dataset resulted in different concentration outputs, highlighting the role of algorithm design in these systems (monitor + algorithm). Notably, no significant influence from air pollutants on the pollen concentrations was observed, suggesting that any potential difference in effect on the systems might require higher air pollution concentrations or more complex interactions. However, results from some monitors were affected to a minor degree by specific weather variables. Our findings suggest that the application of real-time devices in urban environments should focus on the associated algorithm that classifies pollen taxa. The impact of air pollution, although not to be excluded, is of secondary concern as long as the pollution levels are similar to a large European city like Munich.</p

Changes in muscle contractile characteristics and jump height following 24 days of unilateral lower limb suspension

We measured changes in maximal voluntary and electrically evoked torque and rate of torque development because of limb unloading. We investigated whether these changes during single joint isometric muscle contractions were related to changes in jump performance involving dynamic muscle contractions and several joints. Six healthy male subjects (21 ± 1 years) underwent 3 weeks of unilateral lower limb suspension (ULLS) of the right limb. Plantar flexor and knee extensor maximal voluntary contraction (MVC) torque and maximal rate of torque development (MRTD), voluntary activation, and maximal triplet torque (thigh; 3 pulses at 300 Hz) were measured next to squat jump height before and after ULLS. MVC of plantar flexors and knee extensors (MVCke) and triplet torque decreased by 12% (P = 0.012), 21% (P = 0.001) and 11% (P = 0.016), respectively. Voluntary activation did not change (P = 0.192). Absolute MRTD during voluntary contractions decreased for plantar flexors (by 17%, P = 0.027) but not for knee extensors (P = 0.154). Absolute triplet MRTD decreased by 17% (P = 0.048). The reduction in MRTD disappeared following normalization to MVC. Jump height with the previously unloaded leg decreased significantly by 28%. No significant relationships were found between any muscle variable and jump height (r < 0.48), but decreases in torque were (triplet, r = 0.83, P = 0.04) or tended to be (MVCke r = 0.71, P = 0.11) related to decreases in jump height. Thus, reductions in isometric muscle torque following 3 weeks of limb unloading were significantly related to decreases in the more complex jump task, although torque in itself (without intervention) was not related to jump performance

<em>Euclid</em>: The Early Release Observations Lens Search Experiment

\ua9 The Authors 2025. We investigated the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we performed a systematic visual inspection of the 0.7 deg2 Euclid Early Release Observations data towards the Perseus cluster using both the high-resolution IE band and the lower-resolution YE, JE, and HE bands. Each extended source brighter than magnitude 23 in IE was inspected by 41 expert human classifiers. This amounts to 12 086 stamps of 1000 7 1000. We found 3 grade A and 13 grade B candidates. We assessed the validity of these 16 candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling, and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full 14 000 deg2 of the Euclid Wide Survey should contain 100 000+-7030000000 galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of 170 000 discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range 000 . 68 &lt; θE &lt; 100 . 24, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small-Einstein-radius systems. Whilst it is implausible to visually inspect the full Euclid dataset, our results corroborate the promise that Euclid will ultimately deliver a sample of around 105 galaxy-scale lenses

Euclid: The Early Release Observations Lens Search Experiment

We investigated the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we performed a systematic visual inspection of the 0.7 deg2 Euclid Early Release Observations data towards the Perseus cluster using both the high-resolution IE band and the lower-resolution YE, JE, and HE bands. Each extended source brighter than magnitude 23 in IE was inspected by 41 expert human classifiers. This amounts to 12 086 stamps of 1000 × 1000. We found 3 grade A and 13 grade B candidates. We assessed the validity of these 16 candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling, and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full 14 000 deg2 of the Euclid Wide Survey should contain 100 000+-7030000000 galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of 170 000 discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range 000 . 68 &lt; θE &lt; 100 . 24, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small-Einstein-radius systems. Whilst it is implausible to visually inspect the full Euclid dataset, our results corroborate the promise that Euclid will ultimately deliver a sample of around 105 galaxy-scale lenses

<em>Euclid</em>: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field

\ua9 The Authors 2025.The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. As a result, machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates, such that the usage of CNNs in lens identification has increased. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate, thus producing a pure and complete sample of strong lens candidates from Euclid with a limited need for visual inspection. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. This work is vital in preparing our CNN-based detection pipelines to be able to produce a pure sample of the &gt;100 000 strong gravitational lensing systems widely predicted for Euclid. We select all sources with VIS IE &lt; 23 mag from the Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just ∼11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artifacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected ∼105 lensing systems in Euclid, this implies 106 objects for human classification, which while very large is not in principle intractable and not without precedent

<i>Euclid</i>: The Early Release Observations Lens Search Experiment

We investigated the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we performed a systematic visual inspection of the 0.7 deg2 Euclid Early Release Observations data towards the Perseus cluster using both the high-resolution IE band and the lower-resolution YE , JE , and HE bands. Each extended source brighter than magnitude 23 in IE was inspected by 41 expert human classifiers. This amounts to 12086 stamps of 10″ × 10″. We found 3 grade A and 13 grade B candidates. We assessed the validity of these 16 candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling, and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full 14 000 deg2 of the Euclid Wide Survey should contain 100 000−30 000+70 000 galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of 170 000 discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range 0'.'68 Euclid dataset, our results corroborate the promise that Euclid will ultimately deliver a sample of around 10 5 galaxy-scale lenses

Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field

The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. As a result, machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates, such that the usage of CNNs in lens identification has increased. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate, thus producing a pure and complete sample of strong lens candidates from Euclid with a limited need for visual inspection. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. This work is vital in preparing our CNN-based detection pipelines to be able to produce a pure sample of the >100 000 strong gravitational lensing systems widely predicted for Euclid. We select all sources with VIS IE Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just ∼11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artifacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected ∼105 lensing systems in Euclid, this implies 106 objects for human classification, which while very large is not in principle intractable and not without precedent