Sampling Points Research Articles

Development and Application of a Liquid Sampling Device with Timing, Quantitative and Depth Determination

This thesis describes the development process of a liquid sampling device that can be timed, quantitative, and deep. The structural composition, working principle, and innovative features of the liquid sampling device are introduced, and the application prospects are analyzed. The device has the function of controllable and adjustable sampling point depth and sampling volume, and adopts quantitative collection and collection methods without contact with accessories. The device has a silent function in the sample body, which can realize pre-booking of collection time points and multi-point synchronous collection. Wireless remote control automatic mode is adopted for sending and stopping collection instructions, which can be sent one-to-one or one-to-many at the same time. It provides automation links for water quality monitoring projects and meets the requirements of modern scientific and technological development.

Surveillance of tick-borne pathogens in domestic dogs from Chad, Africa

BackgroundTick-borne pathogens are understudied among domestic animals in sub-Saharan Africa but represent significant threats to the health of domestic animals and humans. Specifically, additional data are needed on tick-borne pathogens in Chad, Africa. Surveillance was conducted among domestic dogs in Chad for selected tick-borne pathogens to measure (1) the prevalence of antibodies against Anaplasma spp., Borrelia burgdorferi, and Ehrlichia spp.; (2) the prevalence of infections caused by Hepatozoon spp., Ehrlichia canis, Anaplasma platys, and Babesia spp.; and (3) associations of pathogens with demographic, spatial, and temporal factors. Blood samples were collected from domestic dogs at three time points (May 2019, November 2019, June 2020) across 23 villages in southern Chad.ResultsOf the 428 dogs tested with the IDEXX SNAP 4Dx test in May 2019, 86% (n = 370, 95% CI = 83–90%) were positive for antibodies to Ehrlichia spp., 21% (n = 88, 95% CI = 17–25%) were positive for antibodies to Anaplasma spp., and 0.7% (n = 3, 95% CI = 0.1–2%) were positive for antibodies to Borrelia burgdorferi. Four different pathogens were detected via PCR. Hepatozoon spp. were most commonly detected (67.2–93.4%, depending on the time point of sampling), followed by E. canis (7.0-27.8%), A. platys (10.1–22.0%), and Babesia vogeli (0.4–1.9%). Dogs were coinfected with up to three pathogens at a single time point, and coinfections were most common in May 2019 compared to November 2019 and May 2020.ConclusionsOverall, this study provides new data about the epidemiology of tick-borne pathogens in domestic dogs in Chad, with potential implications for dog and human health.

POLLUTION OF THE FIFTH CANAL ON THE CRNA RIVER IN THE REGION OF BITOLA

Water is an irreplaceable natural resource. The main goal of this research is to see the pollution of the fifth canal on Crna River in the region of Bitola. As measuring points for sampling for this analysis are: measuring point 1 (Crna River near the village of Novaci), measuring point 2 (fifth canal exit of Bitola), measuring point 3 (fifth canal near the village of Kravari) measuring point 4 (fifth canal before flowing into the Crna River), measuring point 5 (Crna River before being mixed with water from the fifth canal), measuring point 6 (Crna River after mixing with water from the fifth canal) and measuring point 7 (Crna River near the village of Skocivir). Water samples were taken in May and November. To determine the water quality, the following physicochemical parameters were made: turbidity (by turbidimeter), suspended solids, total organic carbon, biological oxygen demand, and dissolved oxygen (determined with UV pastel). From the results, it has been concluded that the highest pollution is in the fifth channel, measuring point 2 for the following parameters in May: turbidity (35.3 mg/L), total organic carbon (210.8 mg/L), suspended solids (77.5 mg/L, and in November164.0 mg/L). Of the measuring points of Crna River, the highest pollution is in measuring point 6 in November: biological oxygen demand (14.5 mg/L), and total organic carbon (13.7 mg/L). That is why it is suggested to purify the wastewater before it is released into the rivers.

Assessing Trace Metal Contamination and Associated Risks in the Kossan River Ecosystem, Southern Côte d'Ivoire

Trace metals accumulate in aquatic systems and can pose a threat to human health and wildlife. In recent decades, human activity has become the main source of metals in the environment. In order to gain a better understanding of metal contamination in Ivorian rivers impacted by human activity, and to help set up a database, we studied the distribution of arsenics (As), cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn) in the Kossan River. A total of 21 surface water and sediment samples were taken at 7 stations along the River Kossan between March 2019 and July 2020. Total concentrations of the metals were analyzed by atomic absorption spectroscopy (AAS). Carcinogenic and non-carcinogenic risks were assessed in surface water. Contamination indices such as EF, CF; Igeo and PLI were calculated to determine the level of sediment contamination. Ecological risk indices Er and RI were used to assess the potential risks associated with metals. The concentrations of As, Pb, Cd, Cu and Zn found in surface water samples fell within the following ranges: 2.03 - 17.19, 1.752 - 13.264, 0.067 - 0.774, 17.44 - 2369.11 and 136.72 - 3669.37 µg/L, respectively and in sediment: 0.69 - 4.60, 2.10 - 11.30, 0.13 - 5.00, 1.70 - 28.20 and 4.10 - 90.30 µg/g, respectively. The results showed high levels of As, Cu, Pb and Zn contamination in places, above WHO limits. The calculation of non-carcinogenic and carcinogenic risk indices revealed that arsenic and copper can present major health risks for humans through the consumption of water. Cd concentrations exceeded geochemical background values. The results suggest moderate to very severe Cd contamination of the sediments by anthropogenic origin at certain sampling points. In general, the results of the ecological risk indices revealed low to moderate levels of contamination for metals, with the exception of heavy cadmium contamination in the river. The highest concentrations of trace metals were observed in water and sediment samples collected from stations with high anthropogenic pressure. The continuing intensification of human activity may in the long term present a major risk to man and his environment, hence the need to set up a system for monitoring river watercourses and to develop a system for remediating trace metals in river water such as phytoremediation.

Contextualising samples: supporting reference genomes of European biodiversity through sample and associated metadata collection

The European Reference Genome Atlas (ERGA) consortium aims to generate a reference genome catalogue for all of Europe's eukaryotic biodiversity. The biological material underlying this mission, the specimens and their derived samples, are provided through ERGA’s pan-European network. To demonstrate the community’s capability and capacity to realise ERGA’s ambitious mission, the ERGA Pilot project was initiated. In support of the ERGA Pilot effort to generate reference genomes for European biodiversity, the ERGA Sampling and Sample Processing committee (SSP) was formed by volunteer experts from ERGA’s member base. SSP aims to aid participating researchers through (i) establishing standards for and collecting of sample/specimen metadata; (ii) prioritisation of species for genome sequencing; and (iii) development of taxon-specific collection guidelines including logistics support. SSP serves as the entry point for sample providers to the ERGA genomic resource production infrastructure and guarantees that ERGA’s high-quality standards are upheld throughout sample collection and processing. With the volume of researchers, projects, consortia, and organisations with interests in genomics resources expanding, this manuscript shares important experiences and lessons learned during the development of standardised operational procedures and sample provider support. The manuscript details our experiences in incorporating the FAIR and CARE principles, species prioritisation, and workflow development, which could be useful to individuals as well as other initiatives.

Rapid motion planning of manipulator in three-dimensional space under multiple scenes

Most working scenes of industrial robots are static scenes and from a previous static scene to a current static scene is a multi-scene. Finding optimal paths with limited time is difficult for motion planning in a high-dimensional space or in multiple scenes. The low efficiency of motion planning of rapidly-exploring random tree star in high-dimensional spaces, low adaptability of global replanning to multiple scenes are addressed by proposing the local replanning based on goal dynamically-guiding rapidly-exploring random tree star (LR-GD-RRT*). The algorithm contributes to fast path tree exploration and multi-scene motion planning. For path tree exploration, sampling points heuristically generating and new nodes growth by goal dynamically-guiding are proposed to reduce the blind and ineffective searches. Moreover, dynamic adjustment of size of new node neighborhood according to density of the obstacles is proposed to search for more neighbor nodes to optimize the path and also to reduce ineffective computation to improve efficiency. For multi-scene, three steps of trimming, re-exploration, and reconnection for local replanning are proposed. For path tree exploration, simulations in 2D plane, 3D space, and the manipulator show that GD-RRT* improves convergence speed, shortens path length and search time, compared with RRT*. For multi-scene, simulations in 3D space and with the manipulator show that the local replanning of the current scene has both lower path cost and higher planning efficiency compared with the global replanning of the previous scene. Motion of the six-degree-of-freedom robot end in a real scene also verifies the effectiveness of the LR-GD-RRT*.

PSIX-21 Can seeds rich in polyunsaturated fatty acids reduce methane emissions when substituting palm oil on dairy beef calves fed high-concentrate diets? In vitro screening

Abstract The aim of this study was to evaluate the rumen in vitro methane (CH4) production of concentrates feed with a different protein source (PS) replacing partially palm oil by different seeds (SE) rich in polyunsaturated fatty acids (PUFA). Concentrate PS were: T1 = 8% soybean meal; and T2 = 15% dried distillers grain. Palm oil (CTR; 4% and 3.5% for T1 and T2, respectively) was partially substituted (1%) by flax seed (FL; 2.7%), canola seed (CO; 3%) or sunflower seed (SU; 2.3%), thus 8 concentrates were tested. Samples were ground at 1-mm and used in an in vitro digestibility assay. The rumen liquid was obtained at the slaughterhouse. Two incubation sets were done; two sampling points lasted 24 and 48 h to calculate the dry matter (DM) digestibility; a third sampling point lasted 12 d to monitor the CH4 production. Data were analyzed using a mixed effects model. Net volume of CH4 per degraded DM presented a PS effect (P < 0.01); T1 produced greater net volume of CH4 per degraded DM than T2 (8.12 vs. 6.91 ± 0.330 ml/mg, respectively). Furthermore, net volume of CH4 per degraded DM presented a SE effect (P < 0.01); all concentrates with seeds tested reduced the net volume of CH4 per degraded DM compared with CTR, and specifically CO produced lower net volume of CH4 per degraded DM than FL and SU (8.91, 7.47, 6.28, 7.39 ± 0.467 ml/mg; CTR, FL, CO, SU, respectively). In conclusion, the use of flax, canola, or sunflower seeds to partially substitute palm oil in concentrate feed, regardless of its PS, can be potential strategies to reduce rumen CH4 emissions, and seems that canola seed may be the most effective one.

VARIAÇÃO BIOMÉTRICA E REPRODUÇÃO DO BIVALVE Anomalocardia flexuosa (BIVALVIA; VENERIDAE) EM DIFERENTES ÁREAS DE PESCA

The bivalve Anomalocardia flexuosa is one of the main fishing resources utilized in artisanal fishing in northeastern Brazil. The objective of the study was to identify the reproductive and biometric variations in the A. flexuosa shell across different fishing areas in the estuary of the Goiana and Megaó rivers in Northeast Brazil, generating information to support strategies for its conservation. Three bimonthly sampling points were used, with P1 being characterized by manual fishing; P2 by more intensive fishing than P1, with the use of less potent fishing gear; and P3 by high-intensity fishing with tools that enhance the collection capacity, such as long-handled nets. For each specimen collected, shell length, shell height, shell width, total weight wet weight, and meat yield were measured to assess size patterns of the organisms and meat yield. Histological analyses were also conducted to identify the reproductive stages. From the analysis of 5,188 captured specimens, it was observed that with P3 presented the lowest body sizes, possibly reflecting overfishing at the site. Growth models were isometric for shell measurements and negative allometric for the length-weight relationship in P1 and P2, and positive allometric in P3. Photomicrographs were taken of 32 specimens for P1, withe 45% males, 48% females and 7% unidentified; and 25 specimens in P3, 12% males, 52% females and 36% unidentified. Regarding reproductive stages, the most representative were the “maturation” and “mature” stages. Due to the evidence of overfishing in P3 and high potential yield in other points, we highlight the need for efficient management actions that mitigate the impacts of overfishing, such as rotation of fishing areas.

Detecting 3D Salinity Anomalies from Soil Sampling Points: A Case Study of the Yellow River Delta, China

Rapidly capturing the spatial distribution of soil salinity plays important roles in saline soils’ management. Existing studies mostly focus on the macroscopic distribution of soil-salinity changes, lacking effective methods to detect the structure of micro-regional areas of soil-salinity anomalies. To overcome this problem, this study proposes a 3D Soil-Salinity Anomaly Structure Extraction (3D-SSAS) methodology to discover soil-salinity anomalies and step forward in revealing the irregular 3D structure of soil-anomaly salinity areas from limited sampling points. We first interpolate the sampling points to soil voxels using 3D EBK. A novel concept, the Local Anomaly Index (LAI), is developed to identify the candidate soil-salinity anomalies with the greatest amplitude of change. By performing differential calculations on the LAI sequence to determine the threshold, the anomaly candidates are selected. Finally, we adopt 3D DBSCAN to construct anomalous candidates as a 3D soil-salinity anomaly structure. The experimental results from the Yellow River Delta data set show that 3D-SSAS can effectively identify the 3D structure of salinity-anomaly areas, which are highly correlated with the geographical distribution mechanism of soil salinity. This study provides a novel method for soil science, which is conducive to further research on the complex variation process of soil salinity’s spatial distribution.

Lateral flow immunoassay device to detect staphylococcal enterotoxin B (SEB) in durian candy.

Staphylococcal enterotoxin B (SEB), a potent enterotoxin produced by Staphylococcus aureus, has been implicated in incidences of Staphylococcal food poisoning in the Philippines. The use of lateral flow immunoassay devices to detect this toxin in solid food samples, like durian candy, at the point of sampling is constrained by the requirement for sample purification (e.g. centrifugation). This problem is also true with the other applications of LFIA devices on food samples. To overcome this challenge, a lateral flow immunoassay (LFIA) device capable of detecting SEB in unpurified durian candy sample was developed in this study. A modified LFIA device was assembled with three layers of glass fiber pads functioning as sample pads instead of a conventional cellulose fiber pad. Unlike with the cellulose fiber pad, the glass fiber sample pads acted as filter and allowed the flow of a 1:5 dilution of durian candy. The LFIA device applied to spiked 1:5 diluted durian candy samples achieved a visual limit of detection of 5ng/mL for SEB, which is twofold lower than reported for previous LFIA devices designed to detect SEB in food samples.

On the effectiveness of multi-scale landscape metrics in soil organic carbon mapping

Soil organic carbon (SOC) mapping delivers invaluable information to the global carbon budget and climate change mitigation endeavour. Environmental variables at sample locations are frequently used as explanatory variables for simulating the spatial distribution of soil properties. However, these may not fully capture the spatial information generated by soil-forming processes. We applied multi-scale landscape metrics that can comprehensively characterize the surrounding landscape information of sample points. The metrics were extracted at two levels (landscape level and class level) and include the diversity, shape and area, fragmentation and connectivity with a buffer distance from 500 m to 5,000 m. We then investigated its effectiveness as environmental variables via recursive feature elimination, random forests, and quantile regression forests. The Jianghan Plain, China, was selected as the study area, where over 19,000 topsoil samples were collected. Results indicated that multi-scale landscape metrics enhanced the predictability of SOC mapping, with R2 increased by 43 %. Specifically, Shannon’s diversity index, the percentage of landscape index, interspersion and juxtaposition index, and patch cohesion index outperformed environmental variables that were extracted at the sample location. In addition, the relationships between SOC and landscape metrics were found to be scale-dependent. Landscape metrics demonstrated significant explanatory capacity for SOC across various spatial scales. Notably, as the scale surpassed 3,000 m, there was a discernible improvement in the explanatory effectiveness of the landscape metrics for SOC. Our findings highlight that landscape metrics are effective in characterising the soil-landscape relationship that is generated by multi-scale natural and anthropogenic soil-forming processes. Meanwhile, knowledge of the intricate relationship between landscape characteristics and SOC is crucial for informing land management decisions aimed at enhancing carbon sequestration, mitigating climate change, and maintaining soil fertility.

Uncertainty analysis of FLiNaK thermophysical properties on convective heat transfer characteristics in circular tube

Molten salts have attracted a spate of quantity of interests in energy and chemistry fields due to their large volumetric capacity, and thermodynamic stability at elevated temperature. However, there are significant uncertainties in the physical properties of molten salts, such as density, specific heat capacity, dynamic viscosity, and thermal conductivity, due to inexperienced measurement techniques and technology. These uncertainties could have certain impact on the evaluation of molten salts heat transfer characteristics. Therefore, an uncertainty analysis is performed regarding FLiNaK thermophysical properties on convective heat transfer characteristics in circular tube. Then, a polynomial chaos expansion (PCE) method is performed to study the uncertainty affecting the heat transfer characteristic. In the process of uncertainty analysis, tensor product quadrature nodes are used to calculate representative sample points and reduce computational costs. Three primary physical properties of molten salt are taken into account as the input parameters. The Sobol composition method is also used to analyze the contributions of each parameter to heat transfer. The results of the uncertainty analysis suggest that the uncertainties in dynamic viscosity, thermal conductivity, and specific heat capacity have a significant impact on the heat transfer of molten salt, contributing to 80 %, 14 %, and 6 % of the total variability, respectively. It also suggests that the polynomial chaos expansion methodology is both novel and reliable when applied to uncertainty analysis of molten salt.

Ecological quality of the Jucusbamaba River, a high Andean urban river in northeastern Peru

The Jucusbamaba River, located in the northeastern region of Peru, flows through two towns that use its waters for agricultural activities. However, these activities generate waste discharged back into the river, which is additionally polluted by untreated domestic wastewater discharges. The main objective was to evaluate the ecological quality of this lotic system, analyzing biotic and abiotic parameters during two seasons. The biotic parameters included microinvertebrates and fecal coliforms, while the abiotic parameters encompassed temperature, pH, dissolved oxygen, electrical conductivity, turbidity, total dissolved solids, and biochemical oxygen demand. Six sampling points were established where physicochemical and microbiological parameters were analyzed. Simultaneously, quantitative sampling of macroinvertebrates was carried out at the same points to evaluate their diversity using Shannon- Wiener, Margalef and Simpson indices. The Andean Biotic Index (ABI) and the Biotic Family Index (FBI) were calculated to determine the ecological quality of the river using macroinvertebrates. Finally, the spatio-temporal variation of macroinvertebrate composition and physicochemical and microbiological parameters were analyzed. Very high concentrations of BOD, total dissolved solids, and electrical conductivity were obtained in the dry season, while in the rainy season, they were pH, dissolved oxygen, and turbidity. 12548 individuals from 6 classes, 11 orders, and 26 families were collected. The greatest richness of macroinvertebrate families was found at points 1 and 2, with Trichoptera, Ephemeroptera and Plecoptera individuals predominating. There was evidence of temporal variation in physicochemical and microbiological parameters, as well as in macroinvertebrate composition. It was concluded that the ecological quality of the Jucusbamba River decreases as it follows its course due to anthropic disturbances. This research can be used to develop management plans, awareness-raising, and sanitation measures to ensure the protection and conservation of the Jucusbamaba River.

Physics-Informed Active Learning for Accelerating Quantum Chemical Simulations.

Quantum chemical simulations can be greatly accelerated by constructing machine learning potentials, which is often done using active learning (AL). The usefulness of the constructed potentials is often limited by the high effort required and their insufficient robustness in the simulations. Here, we introduce the end-to-end AL for constructing robust data-efficient potentials with affordable investment of time and resources and minimum human interference. Our AL protocol is based on the physics-informed sampling of training points, automatic selection of initial data, uncertainty quantification, and convergence monitoring. The versatility of this protocol is shown in our implementation of quasi-classical molecular dynamics for simulating vibrational spectra, conformer search of a key biochemical molecule, and time-resolved mechanism of the Diels-Alder reaction. These investigations took us days instead of weeks of pure quantum chemical calculations on a high-performance computing cluster.

Maximum Correntropy Polynomial Chaos Kalman Filter for Underwater Navigation

This paper develops an underwater navigation solution that utilizes a strapdown inertial navigation system (SINS) and fuses a set of auxiliary sensors such as an acoustic positioning system, Doppler velocity log, depth meter, and magnetometer to accurately estimate an underwater vessel's position and orientation. The conventional integrated navigation system assumes Gaussian measurement noise, while in reality, the noises are non-Gaussian, particularly contaminated by heavy-tailed impulsive noises. To address this issue, and to fuse the system model with the acquired sensor measurements efficiently, we develop a square root polynomial chaos Kalman filter based on maximum correntropy criteria. The proposed method uses Hermite polynomial chaos expansion to tackle the nonlinearity, and it has the potential to estimate the states in a more accurate way in presence of a non-Gaussian measurement noise. The filter is initialized using acoustic beaconing to accurately locate the initial position of the vehicle. The computational complexity of the proposed filter is calculated in terms of flops count. The proposed method is compared with the existing maximum correntropy sigma point filters in terms of estimation accuracy and computational complexity. It is found from the simulation results that the proposed method is more accurate compared to the conventional deterministic sample point filters and Huber's M-estimator.

Effects of anthropogenic activities on the microbial community diversity of Ologe Lagoon sediment in Lagos State, Nigeria.

The impact of pollution on the Ologe Lagoon was assessed by comparing physicochemical properties, hydrocarbon concentrations and microbial community structures of the sediments obtained from distinct sites of the lagoon. The locations were the human activity site (OLHAS), industrial-contaminated sites (OLICS) and relatively undisturbed site (OLPS). The physicochemical properties, heavy metal concentrations and hydrocarbon profiles were determined using standard methods. The microbial community structures of the sediments were determined using shotgun next-generation sequencing (NGS), taxonomic profiling was performed using centrifuge and statistical analysis was done using statistical analysis for metagenomics profile (STAMP) and Microsoft Excel. The result showed acidic pH across all sampling points, while the nitrogen content at OLPS was low (7.44 ± 0.085mg/L) as compared with OLHAS (44.380 ± 0.962mg/L) and OLICS (59.485 ± 0.827mg/L). The levels of the cadmium, lead and nickel in the three sites were above the regulatory limits. The gas chromatography flame ionization detector (GC-FID) profile revealed hydrocarbon contaminations with nC14 tetradecane > alpha xylene > nC9 nonane > acenaphthylene more enriched at OLPS. Structurally, the sediments metagenomes consisted of 43 phyla,75 classes each, 165, 161, 166 orders, 986, 927 and 866 bacterial genera and 1476, 1129, 1327 species from OLHAS, OLICS and OLPS, respectively. The dominant phyla in the sediments were Proteobacteria, Firmicutes, Actinobacteria, and Chloroflexi. The principal component ordination (PCO) showed that OLPS microbial community had a total variance of 87.7% PCO1, setting it apart from OLHAS and OLICS. OLICS and OLHAS were separated by PCO2 accounting for 12.3% variation, and the most polluted site is the OLPS.

Effect of the Bioprotective Properties of Lactic Acid Bacteria Strains on Quality and Safety of Feta Cheese Stored under Different Conditions

Lately, the inclusion of additional lactic acid bacteria (LAB) strains to cheeses is becoming more popular since they can affect cheese’s nutritional, technological, and sensory properties, as well as increase the product’s safety. This work studied the effect of Lactiplantibacillus pentosus L33 and Lactiplantibacillus plantarum L125 free cells and supernatants on feta cheese quality and Listeria monocytogenes fate. In addition, rapid and non-invasive techniques such as Fourier transform infrared (FTIR) and multispectral imaging (MSI) analysis were used to classify the cheese samples based on their sensory attributes. Slices of feta cheese were contaminated with 3 log CFU/g of L. monocytogenes, and then the cheese slices were sprayed with (i) free cells of the two strains of the lactic acid bacteria (LAB) in co-culture (F, ~5 log CFU/g), (ii) supernatant of the LAB co-culture (S) and control (C, UHT milk) or wrapped with Na-alginate edible films containing the pellet (cells, FF) or the supernatant (SF) of the LAB strains. Subsequently, samples were stored in air, in brine, or in vacuum at 4 and 10 °C. During storage, microbiological counts, pH, and water activity (aw) were monitored while sensory assessment was conducted. Also, in every sampling point, spectral data were acquired by means of FTIR and MSI techniques. Results showed that the initial microbial population of Feta was ca. 7.6 log CFU/g and consisted of LAB (>7 log CFU/g) and yeast molds in lower levels, while no Enterobacteriaceae were detected. During aerobic, brine, and vacuum storage for both temperatures, pathogen population was slightly postponed for S and F samples and reached lower levels compared to the C ones. The yeast mold population was slightly delayed in brine and vacuum packaging. For aerobic storage at 4 °C, an elongation in the shelf life of F samples by 4 days was observed compared to C and S samples. At 10 °C, the shelf life of both F and S samples was extended by 13 days compared to C samples. FTIR and MSI analyses provided reliable estimations of feta quality using the PLS-DA method, with total accuracy (%) ranging from 65.26 to 84.31 and 60.43 to 89.12, respectively. In conclusion, the application of bioprotective LAB strains can result in the extension of feta’s shelf life and provide a mild antimicrobial action against L. monocytogenes and spoilage microbiota. Furthermore, the findings of this study validate the effectiveness of FTIR and MSI techniques, in tandem with data analytics, for the rapid assessment of the quality of feta samples.

The loss of riparian vegetation along streams causes morphological divergences in functional traits of semiaquatic insects (Heteropteran: Gerromorpha) in the eastern Amazon.

Understanding the effects of mining activities on Amazonian streams and their impact on aquatic communities is of paramount importance in the current context of resource overexploitation in society. In this study, we assessed the significance of the environment and interspecific interactions on the organization patterns of semiaquatic insect species in a mineral extraction region in the eastern Amazon. We utilized the morpho functional characteristics of 22 species from the suborder Gerromorpha (Heteropteran), considering both the abundance and sexual dimorphism of these species. Additionally, we quantified the density of riparian vegetation surrounding each stream to categorize sampling points and evaluate whether there are differences in species distribution patterns among categories. We sampled 16 sites, categorized into two treatments based on the percentage of riparian vegetation in forested and deforested areas located in the Capim River Basin. We did not find the action of environmental filters on the total assembly; however, we found significant morphological divergence for all the traits analyzed. On the other hand, the separation of streams into treatments with different portions of riparian vegetation showed that there are significant differences between them regarding species distribution patterns. Forested streams within a 500-m radius have species distributed over a larger area, indicating that these streams have greater resource availability or that species can use these resources more efficiently. Our results demonstrate the importance of riparian vegetation for the studied communities, as well as for mitigating the impacts caused by mining activities.

Assessment of thermal and physicochemical properties of mechanic village soils derived from two different geological formations in Ogun State, Nigeria

This study assessed and compared selected soil properties, oil and grease content, and thermophysical parameters of sandy loam soils from two representative automobile mechanic village (MV) on two different geological formations in Ogun State, Nigeria. The two locations: Abeokuta and Sagamu are situated on a basement complex and Cretaceous-sedimentary formations, respectively. Ten sample points were established on each MV. Physico-chemical and in-situ thermal properties were measured using standard methods and KD2 Pro thermal analyzer, respectively. Three different regression models (linear, semi-log and double-log) were generated for the prediction of thermal conductivity ( λ s ) and specific heat capacity ( C s ). Topsoils in both MVs are slightly acidic to neutral, with an average oil and grease content > 100 mg/kg. Results of thermophysical parameters revealed that the average λ s values in MV soils of basement complex and sedimentary backgrounds were 1.656 and 1.988 W/mK, respectively. The average C s values in Abeokuta and Sagamu MV soils are 2.295 and 3.043 MJ/m3K, respectively. The regression analysis showed that the double log model performed better than both linear and semi log models for predicting λ s at both locations. All the tested regression models have good prediction effects on C s at location within cretaceous sedimentary, whereas linear and double-log models proved feasible for predicting C s at location underlain by basement complex.

Deep learning-driven optimization of real-time ray tracing for enhanced immersive virtual reality

Photorealistic rendering is essential for immersive virtual reality and real-time ray tracing is required for this, yet the necessary computational load has so far hindered its use in scenarios where a fast response and high frame rates are paramount. To overcome this challenge, we present a deep learning-based model that optimises the computational load of ray tracing through utilising convolutional neural networks (CNNs) to predict lightscene interactions. We achieve this by training CNNs from datasets with offline ray-traced images. Using this learning process, we approximate the contents of light transport simulations from scene point sampling. The use of this optimised algorithm in virtual reality scenes, thus, enables renderings of more complex scenes, with dynamic lighting, complex geometry and interactive elements under high frame rates, keeping users immersed and responsive to events. Our results show that this method achieves visual similarities to traditional ray tracing, which is photorealistic rendering, but can be performed in real-time in virtual reality. We anticipate this work leads to many potential applications of ray tracing in many scenarios in virtual reality, such as gaming, architectural rendering and training.