48 research outputs found
LH receptor (LHR), Steroidogenic Acute Regulatory protein (StAR) and Mitochondrial Membrane Potential (MMP) in bovine granulosa cells are related to follicular size and atresia.
No full textGranulosa cells (GC) play a key role in creating a suitable environment for the growth
and the maturation of the oocyte as well as in determining the proper endocrine
conditions for breeding and fertilization. However, only the GC of the ovulatory follicle
have the opportunity to fully provide these tasks. Cumulus-oocyte complexes (COCs)
used for in vitro embryo production (IVEP) are collected from follicles whose GC have not
fully acquired or have lost these functions. This may be a reason of low IVEP efficiency.
LH receptor (LHR), Steroidogenic Acute Regulatory protein (StAR) and Mitochondrial
Membrane Potential (MMP) are direct or indirect markers of endocrine functions and
putative candidates for evaluation of follicle quality.
This study is aimed at evaluating the quality of GC of bovine ovarian follicles, classified
according to their size and atresia grade, in order to provide new information to clarify
the poor IVEP success.
Bovine ovaries were collected from abattoir and transported to the lab at 4°C. Follicles
were dissected, measured and classified according to their atresia grade (Kruip and
Dieleman, 1982). The collected COCs were morphologically classified according to criteria
related to follicular atresia (Boni et al., 2002). GC were obtained by scraping the follicular
wall and filtered on a 50 μm nylon mesh. For each follicle, a part of GC was fixed with 2%
paraformaldehyde for 1h. The remaining part was incubated with 5μM JC1 for 30 min
followed by washing and reading with a spectrofluorometer (ex. 490 nm, em. 510 to 650
nm). Negative control samples were treated with 2 μM CCCP for 1 h before reading. The
MMP values were expressed as the ratio between the fluorescence peaks at ~595 and
~525 nm. In fixed cells, immunofluorescence was carried out after treatment with
blocking solution (20% Sea Block blocking buffer in PBS) with either anti-LH receptor
antibodies (K-15) or anti-StAR antibodies (K-20) at 1:200 dilution for 90 min. After
washing twice with TPBS (PBS + 0.05% Tween), the samples were incubated with
secondary FITC-conjugated anti-goat antibodies. The samples were read at fluorescence
microscope and the fluorescence intensity analyzed by ImageJ. Statistical analysis was
carried out by ANOVA (Systat 11.0).
Follicle size negatively affected (P< 0.01) the MMP as well as the expression of both LHR
and StAR. Also the atresia grade, when evaluated on the basis of COC morphology,
negatively influenced (P< 0.01) the expression of both LHR and StAR but positively
influenced (P< 0.01) MMP. The evaluation of atresia grade on the basis of follicle
morphology did not show significant effects on both LHR and StAR expression. These
results highlight a discrepancy between the morphological characteristics of the
follicle/COC and functionality of the GC, as previously demonstrated between COC
quality and IVEP efficiency (Boni et al., 2002). Whereas the evaluated parameters
represent markers of the steroidogenic activity, it is likely that the mechanisms of
follicular regression pass through an upregulation of the GC metabolic activity
A Multi-Sensor Exportable Approach for Automatic Flooded Areas Detection and Monitoring by a Composite Satellite Constellation
No full textTimely and frequently updated information about flood-affected areas and their space-time evolution are often crucial in order to correctly manage the emergency phases. In such a context, optical data provided by meteorological satellites, offering the highest available temporal resolution (from hours to minutes), could have a great potential. As cloud cover often occurs reducing the number of usable optical satellite images, an appropriate integration of observations coming from different satellite systems will surely improve the probability to find cloud-free images over the investigated region. To make this integration effective, appropriate satellite data analysis methodologies, suitable for providing congruent results, regardless of the used sensor, are envisaged. In this paper, a sensor-independent approach (RST, Robust Satellites Techniques-FLOOD) is presented and applied to data acquired by two different satellite systems (Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration platforms and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System satellites) at different spatial resolutions (from 1 km to 250 m) in the case of Elbe flood event occurred in Germany on August 2002. Results achieved demonstrated as the full integration of AVHRR and MODIS RST-FLOOD products allowed us to double the number of satellite passes daily available, improving continuity of monitoring over flood-affected regions. In addition, the application of RST-FLOOD to higher spatial resolution MODIS (250 m) data revealed to be crucial not only for mapping purposes but also for improving RST-FLOOD capability in identifying flooded areas not previously detected at lower spatial resolution
Does Path Cleaning Help in Dynamic All-Pairs Shortest Paths?
No full textIn the dynamic all-pairs shortest path problem we wish to maintain information about distances in a weighted graph subject to dynamic operations such as edge insertions, edge deletions, and edge weight updates. The most efficient algorithms for this problem maintain a suitable superset of shortest paths in the graph. This superset retains information about the history of previous graph updates so as to avoid pathological situations where algorithms are continuously forced to rebuild large portions of their data structures. On the other hand, the set of maintained paths may grow too large, resulting in both prohibitive space consumption and inefficient updates. To circumvent this problem, the algorithms perform suitable path cleaning operations. In this paper, we implement and experiment with a recent efficient algorithm by Thorup, which differs from the previous algorithms mainly in the way path cleaning is done, and we carry out a thorough experimental investigation on known implementations of dynamic shortest path algorithms. Our experimental study puts the new results into perspective with respect to previous work and gives evidence that path cleaning, although crucial for the theoretical bounds, appears to be instead of very limited impact in practice. © Springer-Verlag Berlin Heidelberg 2006
RST-BASED FLOODED AREA MAPPING AND MONITORING IN NEAR REAL-TIME BY USING MODIS DATA
No full textFlood forecast and mitigation actions need updated and timely information about precise location, extent and dynamic evolution of the flooding event. Remote sensing technology, based on microwave and optical satellite data, is currently capable of giving reliable contributions towards a rapid detection of affected areas in order to improve flood hazards management and to study remote areas where ground-based observation systems are still lacking. For a near real time monitoring and mapping of flooded areas, fundamental during the crisis and post-crisis phases to support civil protection activities, frequent observations of the Earth’s surface can be derived from optical sensors aboard meteorological satellites.
Recently, a new Robust Satellite Technique using AVHRR (Advanced very High Resolution Radiometer) observations has been proposed for mapping and monitoring flooded areas, providing good results. Afterwards, the same approach has been exported on MODIS (Moderate Resolution Imaging Spectroradiometer) data, in order to investigate if its higher spatial resolution in visible and near-infrared channels might be exploited to increase the accuracy in both near real time detection and mapping of flooded areas. Preliminary results confirmed the reliability and the sensitivity of the proposed approach but further analyses have to be carried out in order to better assess the actual reliability and efficiency of such a technique. To this aim, in this paper, the extreme flooding event which hit wide territories of Germany and Czech Republic, during the August 2002, has been studied
On the potential of multi-temporal analysis of MODIS and AVHRR data for near real time mapping and monitoring of flooded areas
No full textFloods are devastating natural disasters which may cause very high costs in lives and damages. Among the other potential contributes, satellite remote sensing may help for mapping and monitoring flooded areas. In order to support flood risk management, information coming from satellite, especially during crisis phases, need to be timely provided. Besides, suitable techniques, able to reliably detect flooded areas with a low rate of false alarms, are requested. In this context, a new technique using visible AVHRR data has been recently proposed. In this work, in order to further confirm the reliability and the sensitivity of the proposed approach we analyze the August 2002 flood which hit wide territories of Germany. Afterwards, we exported
this
approach on MODIS data, in order to exploit the higher spatial resolution in the visible and near-infrared channels offered by such a sensor, for increasing the accuracy in both near real time flooded area mapping and monitorin
REAL TIME MONITORING OF FLOODED AREAS BY A MULTI-TEMPORAL ANALYSIS OF OPTICAL SATELLITE DATA
No full textOptical sensors aboard meteorological satellites are an excellent tool to monitor floods and support the flood risk management cycle, mainly thanks to their high temporal resolution, which allow us to obtain real time and frequently updated information on environmental changes. The RST (Robust Satellite Techniques) approach, an automatic change detection scheme, has been already applied using AVHRR (Advanced very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data to detect and monitor flooded areas. Results achieved have shown its capability in automatically identify flooded areas with a low rate of false alarms, also discriminating permanent water from actual inundated areas. In this paper, in order to further assess the reliability and the sensitivity of the proposed approach in different conditions of observation, the RST methodology has been used to analyze the July 2007 and October 2008 floods occurred in the South Africa and Algeria regions
Multi-Temporal Satellite Investigation of gas Flaring in Iraq and Iran: The DAFI Porting on Collection 2 Landsat 8/9 and Sentinel 2A/B
No full textThe synergic use of satellite data at moderate spatial resolution (i.e., 20–30 m) from the new Collection 2 (C2) Landsat-8/9 (L8/9) Operational Land Imager (OLI) and Sentinel-2 (S2) Multispectral Instrument (MSI) provides a new perspective in the remote sensing applications for gas flaring (GF) identification and monitoring, thanks to a significant improvement in the revisiting time (up to ~3 days). In this study, the daytime approach for gas flaring investigation (DAFI), recently developed for identifying, mapping and monitoring GF sites on a global scale using the L8 infrared radiances, has been ported on a virtual constellation (VC) (formed by C2 L8/9 + S2) to assess its capability in understanding the GF characteristics in the space-time domain. The findings achieved for the regions of Iraq and Iran, ranked at the second and third level among the top 10 gas flaring countries in 2022, demonstrate the reliability of the developed system, with improved levels of accuracy and sensitivity (+52%). As an outcome of this study, a more realistic picture of GF sites and their behavior is achieved. A new step aimed at quantifying the GFs radiative power (RP) has been added in the original DAFI configuration. The preliminary analysis of the daily OLI- and MSI-based RP, provided for all the sites by means of a modified RP formulation, revealed their good matching. An agreement of 90% and 70% between the annual RPs computed in Iraq and Iran and both their gas-flared volumes and carbon dioxide emissions were also recorded. Being that gas flaring is one of the main sources of greenhouse gases (GHG) worldwide, the RP products may concur to infer globally the GHGs GF emissions at finer spatial scales. For the presented achievements, DAFI can be seen as a powerful satellite tool able to automatically assess the gas flaring dimension on a global scale
Toward the estimation of river discharge variations using MODIS data in ungauged basins
No full textThis study investigates the capability of the Moderate resolution Imaging Spectroradiometer (MODIS) to estimate river discharge, even for ungauged sites. Because of its frequent revisits (as little as every 3 h) and adequate spatial resolution (250 m), MODIS bands 1 and 2 have significant potential for mapping the extent of flooded areas and estimating river discharge even for medium-sized basins. Specifically, the different behaviour of water and land in the Near Infrared (NIR) portion of the electromagnetic spectrum is exploited by computing the ratio (C/M) of the MODIS channel 2 reflectance values between two pixels located within (M) and outside (C), but close to, the river. The values of C/M increase with the presence of water and, hence, with discharge. Moreover, in order to reduce the noise effects due to atmospheric contribution, an exponential smoothing filter is applied, thus obtaining C/M⁎.
Time series of hourly mean flow velocity and discharge between 2005 and 2011 measured at four gauging stations located along the Po river (Northern Italy) are employed for testing the capability of C/M⁎ to estimate discharge/flow velocity. Specifically, the meanders and urban areas are considered the best locations for the position of the pixels M and C, respectively. Considering the optimal pixels, the agreement between C/M⁎ and discharge/flow velocity is fairly good with values in the range of 0.65–0.77. Additionally, the application to ungauged sites is tested by deriving a unique regional relationship between C/M⁎ and flow velocity valid for the whole Po river and providing only a slight deterioration of the performance. Finally, the sensitivity of the results to the selection of the C and M pixels is investigated by randomly changing their location. Also in this case, the agreement with in situ observations of velocity is fairly satisfactory (r ~ 0.6). The obtained results demonstrate the capability of MODIS to monitor discharge (and flow velocity). Therefore, its application for a larger number of sites worldwide will be the object of future studies
A Tailored Approach for the Global Gas Flaring Investigation by Means of Daytime Satellite Imagery
No full textThe Daytime Approach for gas Flaring Investigation (DAFI), running in Google Earth Engine (GEE) environment, exploits a Normalized Hotspot Index (NHI), analyzing near-infrared and short-wave infrared radiances, to detect worldwide high-temperature gas flaring sites (GFs). Daytime Landsat 8—Operational Land Imager (OLI) observations, of 2013–2021, represents the employed dataset. A temporal persistence criterion is applied to a gas flaring customized NHI product to select the GFs. It assures the 99% detection accuracy of more intense and stable GFs, with a very low false positive rate. As a result, the first daytime database and map of GF sites, operating during the last 9 years at global scale, has been generated. For each site, geographical metadata, frequency of occurrence and time persistence levels, at both monthly and annual scale, may be examined, through the specific developed GEE App. The present database will complement/integrate existing gas flaring maps. The joint use of global scale daytime and nighttime GFs inventories, in fact, will allow for tracking gas flaring dynamics in a timely manner. Moreover, it enables a better evaluation of GF emissions into the atmosphere. Finally, the next DAFI implementation on Landsat 9 and Sentinel 2 data will further improve our capabilities in identifying, mapping, monitoring and characterizing the GFs
The VIIRS-Based RST-FLARE configuration: The Val d'Agri Oil Center Gas Flaring Investigation in between 2015-2019
No full textThe RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d'Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring
