Radio Occultation (RO) is pivotal for profiling the neutral and ionized atmosphere, with the PlanetiQ mission, via its GNOMES satellites, striving to establish an advanced atmospheric observing system. However, an assessment of the spatiotemporal distributions of PlanetiQ observations and comparisons with reliable datasets are lacking. This study addresses this gap by examining the temporal and spatial distribution of RO observations from PlanetiQ during its initial 198 operational days in 2023, alongside comparisons with COSMIC and Numerical Weather Prediction (NWP) models. Data from GN02, GN03, and GN04 satellites, yielding 1099, 1313, and 1843 RO events per day, respectively, were analyzed. The satellite constellation’s observations demonstrate a generally well-distributed pattern, albeit minor deficiencies in equatorial and polar regions. Single-profile comparisons with COSMIC data reveal strong correlations for pressure, temperature, Water Vapor Pressure (WVP), and refractivity profiles, with temperature exhibiting larger variations (RMSE = 1.24 °C). Statistical analyses confirm statistically insignificant differences between the PlanetiQ and COSMIC profiles at the same spatio-temporal coordinates. Comparisons with NWP models show slight differences with GFS, with overall RMSE values of 0.23 mb (WVP), 0.6 mb (pressure), 1.3 (refractivity), and 1.5 °C (temperature). However, assessments against GFS/ECMWF models indicate overall compatibility, with insignificant differences between PlanetiQ profiles and model observations.

Accurate detection and mapping of manholes are essential for urban infrastructure management, facilitating efficient maintenance and safety. This paper introduces a novel methodology that integrates the open-world object detection model, Grounding DINO, with geographic information systems (GIS) to detect and geolocate manholes in urban environments. Unlike traditional object detection approaches that rely on extensive labelled datasets and predefined object categories, Grounding DINO, a transformer-based model, leverages natural language processing for adaptable, scalable detection. Grounding DINO processes natural language descriptions to detect the manholes in an open-world context, overcoming the limitations of predefined object categories. Detected manholes are localized using multi-view triangulation, which refines their 3D positions by leveraging redundant camera viewpoints and intrinsic calibration parameters, which ensures accurate geometric mapping of manhole centers. The resulting geospatial coordinates are transformed into the WGS84 system using a global navigation satellite system/inertial navigation system (GNSS/INS) for compatibility with GIS platforms. The proposed approach achieved sub-meter precision, with mean localization errors of 0.36 meters in easting and 0.34 meters in northing, evaluated on KITTI dataset sequences under various urban conditions. The seamless integration of object detection and geospatial mapping demonstrates the potential of this approach for efficient and scalable urban infrastructure management. Doi: 10.28991/CEJ-2025-011-04-07 Full Text: PDF

This study was conducted in the Sericulture Research Laboratory of Melkassa Research Center. Four bivoltine and one polyvoltine silkworm were involved in the crossing experiment and laid out in complete randomized design with four replications. Data was collected on fecundity, pupation rate (%), number of diseased larvae, survival rate (%), cocoon weight (g), cocoon shell weight (g), cocoon shell ratio (%) and filament length (m). Uniform and non-significant numbers of eggs produced by adults and cocooning percentages were recorded for both hybrid and parents in all the generations. Average larval weight significantly (P<0.01) reduced for F1, F2, F3 and F4 generations hybrids than parents but increased in F5, F6 and F7 generations hybrids. Silk ratios and survival rates significantly (P<0.01) increased for all hybrids than parent bivoltine in all hybrid generations. Larval period significantly (P<0.01) reduced in F5, F6 and F7 generations hybrid than parent bivoltines. Filament length significantly (P<0.01) reduced in F1, F2, F3 and F4 generations hybrids than parent bivoltine but significantly increased in F5, F6 and F7 generations hybrids than parent bivoltines. It can be concluded that instead of using parent polyvoltine and bivoltine mulberry silkworms separately for silk production, the farmers can use F5 and above generations hybrids of multivoltine x bivoltine for relatively higher disease resistance and maximum silk productions. Key words: Polyvoltine silkworm, bivoltine silkworm, hybrids.

Radio Occultation (RO) is pivotal for profiling the neutral and ionized atmosphere, with the PlanetiQ mission, via its GNOMES satellites, striving to establish an advanced atmospheric observing system. However, an assessment of the spatiotemporal distributions of PlanetiQ observations and comparisons with reliable datasets are lacking. This study addresses this gap by examining the temporal and spatial distribution of RO observations from PlanetiQ during its initial 198 operational days in 2023, alongside comparisons with COSMIC and Numerical Weather Prediction (NWP) models. Data from GN02, GN03, and GN04 satellites, yielding 1099, 1313, and 1843 RO events per day respectively, were analyzed. The satellite constellation's observations demonstrate a generally well-distributed pattern, albeit minor deficiencies in equatorial and polar regions. Single-profile comparisons with COSMIC data reveal strong correlations for pressure, temperature, Water Vapor Pressure (WVP), and refractivity profiles, with temperature exhibiting larger variations (RMSE = 1.24°C). Statistical analyses confirm statistically insignificant differences between PlanetiQ and COSMIC profiles at the same spatio-temporal coordinates. Comparisons with NWP models show slight differences with GFS, with overall RMSE values of 0.23 mb (WVP), 0.6 mb (pressure), 1.3 (refractivity), and 1.5°C (temperature). However, assessments against GFS/ECMWF models indicate overall compatibility, with insignificant differences between PlanetiQ profiles and models observations.

In this work the Effect of storage and water rinsing in reducing the microbial contamination of carrots and Cucumbers and the time of spoilage was evaluated. In storage experiment done , washed and unwashed of carrots and cucumbers samples were stored at room and refrigerator temperatures.Washing with running tap water resulted in big reduction of the microbial load of carrots and cucumbers. The reduction ranged between 85 – 99 % for the total bacterial count, 92 % for moulds, and between 74 and 90 % for coliform bacteria. Unwashed samples and samples stored at room temperature spoiled more quickly than the washed samples and the sample stored in the refrigerator. In general carrots samples stored at room temperature spoiled in six to seven days and those store in the refrigerator spoiled in nine to ten days ,with respect to cucumbers spoilage occurred often six days at room temperature and after seven days in the refrigerator.From this experiment we found that carrots was more resistant to spoilage than the cucumbers. Carrots and cucumbers spoilage was eminent when the microbial load reached about 10⁶ ????????????/????.It was concluded that, although the thorough cleaning of salad Carrots and Cucumbers with water and their storage in refrigerator would greatly reduce their microbial load, elimination of all microbial would not be achieved.

Radio occultation (RO) has become a key technique for monitoring the ionosphere by deriving electron density (Ne) profiles and total electron content (TEC) from GNSS signals. This study assesses the newly deployed PlanetiQ GNOMES constellation by validating its ionospheric Ne profiles and profile-based TEC against collocated measurements from ionosondes and the COSMIC-2 mission under both quiet and disturbed geomagnetic conditions. Data matching for the statistical validation uses conservative spatial thresholds of less than 1° in latitude and longitude and temporal limits of 30 min for ionosondes and 1 h for COSMIC-2, supported by a dedicated sensitivity analysis, whereas storm-time case studies apply tighter temporal collocation and explicit control of the ray path geometry. Quantitative agreement is evaluated using root mean square error (RMSE), mean and absolute mean differences, correlation coefficients, regression analysis, and normalized percentage differences for key F-layer parameters, including the maximum Ne of the F2 layer (NmF2), the peak height of the F2 layer (hmF2), and the critical frequency of the F2 layer (foF2), along with altitude-dependent Ne profiles. PlanetiQ shows strong consistency with ionosonde profiles, with RMSE ranging from 2.94 × 10⁴ to 2.76 × 10⁵ el/cm³, correlations typically exceeding 0.90, and normalized absolute mean differences often near or below about 10–20%, although lower correlations of about 0.31 and 0.69 are found at Poker Flat and Awase, respectively, reflecting complex local structures and regional variability. Comparisons with COSMIC-2 during quiet conditions yield RMSE values between 7.06 × 10⁴ and 2.16 × 10⁵ el/cm³, correlations from 0.94 to 0.99, and percentage differences that generally remain within a few tens of percent, while storm-time analyses show RMSE between 1.12 × 10⁵ and 3.70 × 10⁵ el/cm³ with correlations from 0.80 to 0.99, confirming robust agreement across a wide range of geophysical conditions. Regression results demonstrate slopes near 1.00 and correlation coefficients above 0.90 for NmF2 and foF2 between PlanetiQ and both ionosondes and COSMIC-2, whereas hmF2 exhibits larger scatter, particularly during geomagnetic disturbances; additional binning by spatial and temporal separation indicates that temporal mismatches generally have a stronger impact on discrepancies than horizontal distance. Overall, the results demonstrate that PlanetiQ ionospheric RO data provide accurate and consistent measurements of key ionospheric parameters, comparable to those from COSMIC-2 and ionosondes, and can reliably complement existing observing systems for monitoring ionospheric variability and space-weather impacts.