Intensive Observation Research Articles

Determining Ionospheric Drift and Anisotropy of Irregularities from LOFAR Core Measurements: Testing Hypotheses behind Estimation

We try to assess the validity of assumptions taken when deriving drift velocity. We give simple formulas for characteristics of the spatiotemporal correlation function of the observed diffraction pattern for the frozen flow and the more general Briggs model. Using Low-Frequency Array (LOFAR) Cassiopeia intensity observation, we compare the experimental velocity scaling factor with a theoretical one to show that both models do not follow observations. We also give a qualitative comparison of our drift velocity estimates with SuperDARN convection maps. The article is essentially an extended version of the conference paper: “Determining ionospheric drift and anisotropy of irregularities from LOFAR core measurements”, Signal Processing Symposium 2021 (SPSympo 2021).

Heterogeneous changes of chemical compositions, sources and health risks of PM2.5 with the “Clean Heating” policy at urban/suburban/industrial sites

China has enacted the “Clean Heating” (CH) policy in north China. The domain-specific impacts on PM2.5 constituents and sources in small cities are still lacking, which obstruct the further policy optimization. Here, we performed an intensive observation covering the heating period (HP) and pre-heating period (PHP) in winter of 2017 at urban (UR), industrial (IS), and suburban (SUR) sites in one of the “2 + 26” cities. The mean PM2.5 concentrations at UR and IS decreased by 15.2 % and 4.6 %, while increased by 9.8 % at SUR in the HP compared with the PHP, indicating the heterogeneous responses. The lowest contribution percentages of coal combustion (14.6 %) and industrial emissions (17.1 %) to PM2.5 at UR in the HP implied the CH policy played more effective role. The most increase in NO3−/SO42− ratio by 26.8 % and the highest NO3− concentration at UR in the HP were linked mainly with the thermal-NOx emitted from natural gas (NG) burning in view of NOx emission reductions from other sources. The highest concentrations of OC, SO42−, K+, and Cl−, and contribution percentages of biomass burning (20.0 %) and coal combustion (24.8 %) to PM2.5 at SUR in the HP evidenced the enhanced usage of biomass/coal. Coal banning in the HP at IS and UR led to the obvious decreases in OC, SO42−, As, and Sb. Secondary nitrate became the largest PM2.5 source at IS and UR in the HP. Coal banning, emission control on large-size enterprises and ignored control on small-size enterprises efficiently modified the concentrations and health risks of heavy metals. The lowest carcinogenic risks moved from SUR in the PHP to UR in the HP. The policies on de-NOx of NG-burning related enterprises, reduction of biomass/coal usage in suburban area, and strict regulation of small-size enterprises were urgently need to further improve the air quality.

Determination of species-specific leaf angle distribution and plant area index in a cool-temperate mixed forest from UAV and upward-pointing digital photography

Leaf angle distribution (LAD) is an essential canopy element that controls the foliage projection function (G-function), which is a parameter for estimating the plant area index (PAI). In recent studies, digital cover photography (DCP) has been applied to estimate the PAI (PAIDCP) in many terrestrial ecosystems. However, few studies related to this topic have been performed in mixed forests, where LAD features differ among multiple species. This study sought to evaluate the PAIDCP in a cool temperate mixed deciduous-coniferous forest in western Japan using a field-based G-function that was estimated from digital images captured by using a small uncrewed aerial vehicle (UAV; a quadcopter). The intensive UAV observations showed that measured throughout a vertical canopy profile of the deciduous broadleaved tree species, LAD was plagiophile-planophile for Fagus crenata, but was planophile throughout the canopy for Carpinus tschonoskii. Meanwhile, for the other dominant coniferous Abies firma species, we assumed either plagiophile or spherical for LAD and the G-function based on previous studies instead of measuring the parameters directly using the small UAV. With the species-specific LAD and G-function of dominant tree species, we compared the four-year PAIDCP time series with those based on a direct method using litter-trap inventories (PAIlit). The results indicate that PAIDCP provided more suitable representation of the canopy than that obtained assuming the spherical LAD for all tree species in the forest, although estimations of PAIlit includes uncertainties, mainly associating with measurements of specific leaf area (SLA). Our study highlights that in mixed forests with a tall canopy and multiple species it is important to ascertain species-specific LAD values for accurate estimation of the PAI using digital cover photography. Overall, we argue that the combined UAV–DCP photographic approach serves as a powerful tool for estimating the PAI.

Transmission matrix inference via pseudolikelihood decimation

Recently, significant efforts in medical imaging are towards the exploitation of disordered media as optics tools. Among several approaches, the transmission matrix description is promising for characterizing complex structures and, currently, has enabled imaging and focusing through disorder. In the present work, we report a statistical mechanics description of the transmission problem. We convert a linear input–output transmission recovery into the statistical inference of an effective interaction matrix. We do this by relying on a pseudolikelihood maximization process based on random intensity observations. Our aim is to bridge results from spin-glass theory to the field of disordered photonics, uncovering insights from the scattering problem and encouraging the development of novel imaging techniques for better medical investigations.

Snowband Characteristics Associated With Lake‐Effect Misovortices During the OWLeS Project

AbstractVortices of diameters 100 m to 10 km have been observed during lake‐effect snowstorms. Lines of misovortices (diameters = 40–4,000 m) have recently been documented forming over Lake Ontario during long lake‐axis‐parallel (LLAP)‐type lake‐effect storms. Using National Weather Service Weather Surveillance Radar—1988 Doppler (WSR‐88D) and Doppler on Wheels radar data from the Ontario Winter Lake‐effect Systems (OWLeS) project, lines of misovortices (also referred to as “misovortex lines” in this study) were investigated for intensive observation period (IOP)7 (7 January 2014) and IOP9 (9 January 2014). Results revealed that the misovortex lines formed on the southern or northern side of the west‐to‐east‐oriented LLAP band, whichever was closest to a low‐level boundary nearest the corresponding south or north shoreline (northern part in IOP7, southern part in IOP9). Examination of these two IOPs in the context of a total of 23 OWLeS IOPs, 11 of which had predominantly LLAP band morphology, showed that, in 4 of the 11 LLAP IOPs, horizontal shear zones/reflectivity bands formed in preferred regions over Lake Ontario and nearby land areas where low‐level boundaries (e.g., land breeze fronts) have been noted to develop near shoreline irregularities. Horizontal shear zones were predominant in approximately half of the OWLeS LLAP IOPs and were associated with storms having a well‐organized, solid banded reflectivity structure. Misovortices occurred when horizontal shear zones were prevalent, supporting the idea that horizontal shearing instability was important to their formation.

Going Mobile to Address Emerging Climate Equity Needs in the Heterogeneous Urban Environment

Abstract The Brookhaven National Laboratory Center for Multiscale Applied Sensing (CMAS) aims to address environmental equity needs in the context of a changing climate. As a first step toward this goal, the center developed a one-of-a-kind observatory tailored to the study of highly heterogeneous urban environments. This article describes the features of the mobile observatory that enable its rapid deployment either on or off the power grid, as well as its instrument payload. Beyond its unique design, the observatory optimizes data collection within the obstacle-laden urban environment using a new smart sampling paradigm. This setup facilitated the collection of previously poorly documented environmental properties, including wind profiles throughout the atmospheric column. The mobile observatory captured unique observations during its first few intensive observation periods. Vertical air motion and infrared temperature measurements collected along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY, reveal how solar and anthropogenic heating affect wind flow and thus the venting of heat, pollution, and contaminants in urban street canyons. Also, air temperature measurements collected during travel along a 150-km transect between Upton and Manhattan, NY, offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the city across different neighborhoods. Ultimately, the datasets collected by CMAS are poised to help guide equitable urban planning by highlighting existing disparities and characterizing the impact of urban features on the urban microclimate with the goal of improving human comfort.

Sustainability evaluation for selecting the best optimized structural designs of a tall building

To resolve social and environmental issues and prepare the required residences in megacities, a sustainable development analysis of the structural designs should be carried because a building is designed for a long life span. Based on CEN TC350, life cycle assessment (LCA) indicators, and EN standards, the life cycle assessment of a building should be conducted in the initial steps of the design process. The main target of this study is related to the sustainability evaluation of the optimized structural designs by the various lateral force-resisting system to select the best structural system for a tall building. According to interviews with 28 experts, condition and location of the study area, and intensive observation, 12 lateral force resisting systems were proposed to design a 17-storey five-bay structure. Each structural design was optimized by the optimization modules of SAP2000. Eleven indicators were selected based on data availability, experts' opinions, and authors' opinions. The weight and effect value (EV) of changes intensity were calculated based on interviewing experts. The values of the indicators were calculated using an indirect and direct manner based on SAP2000 results. A technique for order of preference by similarity to ideal solution (TOPSIS) approach was employed for integrating the values of the proposed indicators. Moreover, an applied effect of changes intensity in each indicator (AECIEI) method, which is one of the simplified MCDA approaches, was utilized to evaluate the sustainability of all scenarios. After sorting all scenarios based on TOPSIS and AECIEI, the results of these methods were compared. The results show that AECIEI can apply the effect of changes intensity and critical indicator on sustainability evaluation; thus, its results are more accurate than the results of TOPSIS. The combination of the steel moment frame and the special reinforced concrete shear wall in both directions was chosen as the best optimized structure based on AECIEI's results. This scenario with sustainable value (SV) of 0.014 was selected as the best option with respect to ductility with a value of 4.17 and the emitted air pollution with a value of 20.40 Ton.

Analysis of regional CO2 contributions at the high Alpine observatory Jungfraujoch by means of atmospheric transport simulations and δ13C

Abstract. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch (JFJ, Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period 2009–2017 with stable carbon isotope (δ13C–CO2) information. We applied two Lagrangian particle dispersion models driven by output from two different numerical weather prediction systems (FLEXPART–COSMO and STILT-ECMWF) in order to simulate CO2 concentration at JFJ based on regional CO2 fluxes, to estimate atmospheric δ13C–CO2, and to obtain model-based estimates of the mixed source signatures (δ13Cm). Anthropogenic fluxes were taken from a fuel-type-specific version of the EDGAR v4.3 inventory, while ecosystem fluxes were based on the Vegetation Photosynthesis and Respiration Model (VPRM). The simulations of CO2, δ13C–CO2, and δ13Cm were then compared to observations performed by quantum cascade laser absorption spectroscopy. The models captured around 40 % of the regional CO2 variability above or below the large-scale background and up to 35 % of the regional variability in δ13C–CO2. This is according to expectations considering the complex Alpine topography, the low intensity of regional signals at JFJ, and the challenging measurements. Best agreement between simulations and observations in terms of short-term variability and intensity of the signals for CO2 and δ13C–CO2 was found between late autumn and early spring. The agreement was inferior in the early autumn periods and during summer. This may be associated with the atmospheric transport representation in the models. In addition, the net ecosystem exchange fluxes are a possible source of error, either through inaccuracies in their representation in VPRM for the (Alpine) vegetation or through a day (uptake) vs. night (respiration) transport discrimination to JFJ. Furthermore, the simulations suggest that JFJ is subject to relatively small regional anthropogenic contributions due to its remote location (elevated and far from major anthropogenic sources) and the limited planetary boundary layer influence during winter. Instead, the station is primarily exposed to summertime ecosystem CO2 contributions, which are dominated by rather nearby sources (within 100 km). Even during winter, simulated gross ecosystem respiration accounted for approximately 50 % of all contributions to the CO2 concentrations above the large-scale background. The model-based monthly mean δ13Cm ranged from − 22 ‰ in winter to − 28 ‰ in summer and reached the most depleted values of − 35 ‰ at higher fractions of natural gas combustion, as well as the most enriched values of − 17 ‰ to − 12 ‰ when impacted by cement production emissions. Observation-based δ13Cm values were derived independently from the simulations by a moving Keeling-plot approach. While model-based estimates spread in a narrow range, observation-based δ13Cm values exhibited a larger scatter and were limited to a smaller number of data points due to the stringent analysis prerequisites.

The MyShake App: User Experience of Early Warning Delivery and Earthquake Shaking

Abstract MyShake is a free citizen science and public safety smartphone application that delivers the United States ShakeAlert program’s Earthquake Early Warning to the public in the states of California, Oregon, and Washington. Although smartphone notifications have long been a component of the ShakeAlert warning delivery plan, very little data has been published on the efficiency and accuracy of such communication. MyShake records timestamps in its alert processing system, including the time it takes for a phone to receive and acknowledge an alert’s delivery. We use data collected for five representative earthquakes—three in urban regions, two rural events—since October 2019 to assess MyShake alert delivery latencies and ground-motion prediction accuracy. For these events, MyShake was capable of efficiently processing and delivering warnings. For the smaller urban events that occur beneath the target population, about half of recipients received a warning before the estimated onset of the S-wave, and up to 90% received an alert prior to experiencing peak shaking. When earthquakes occur further from populated areas, the warning time naturally increases. Smartphone acceleration recordings can also be used to quantify the user experience during earthquakes because they are colocated with people. A review of waveforms collected by MyShake shows a systematic amplification of shaking recorded by smartphones relative to nearby traditional stations. The median amplification calculated using records from all five sample events is a factor of 3.1. Once this correction is applied, MyShake peak accelerations are generally consistent with the distribution of shaking intensities in the U.S. Geological Survey ShakeMap product, whereas also showing some individual sites with substantial amplification and de-amplification. In addition to delivering early warnings, therefore, MyShake provides a waveform observation dataset to densify shaking intensity observations and thereby improve our understanding of earthquake effects and evaluate the accuracy of ShakeAlert’s alerting regions.

Narrating Homosexuality across Borders and Beyond Boundaries in Hanan Al-Shaykh's Only in London (2001)

The present paper examines Hanan al-Shaykh's interrogations of homosexuality across borders and beyond the boundaries of East and West in ‘Only in London’ (2001), a diasporic novel with a Lebanese homosexual protagonist, Samir. It analyzes the ways in which the heterosexual, social, and power networks established to ostensibly force Samir's homosexuality into the closet work to eliminate the existence of homosexuality as an independent identity in Arab society. Drawing on Michael Foucault's framework of sexuality and biopolitical analysis, the paper negotiates the depiction of mental hospital scenes, the medicalization of Samir's homosexuality, and the social pathologization of his alternative gender and sexuality as instruments of "bio-politics of the population" designed to lock homosexuality into a "pathological phenomenon", which has to be medicalized in order to conform to homonormative mainstream culture. It demonstrates how through the mechanisms of biopower, and techniques of surveillance of bodies, Samir's homosexuality is turned into an object of intense observation, study, and power relations. It maintains that the pathologizing psychiatric discourse, the heterosexual institution of marriage, Samir's family, and the state are all complicit with the heteropatriarchal taxonomies of sexuality. The paper further illustrates how being Arab, an immigrant, and a homosexual in London complicate Samir's existence as an alien homosexual being in exile.

Spontaneous defervescence and its prediction in the acute phase of Kawasaki disease.

BackgroundIn Kawasaki disease (KD), fever occasionally resolves spontaneously before 10 days from the onset, right after diagnosing. However, there is not enough evidence of intravenous immunoglobulin (IVIG) treatment in this case. The aim of this study was to investigate the relationship between spontaneous defervescence and coronary artery aneurysm and to develop a scoring model for its prediction in acute KD.MethodsAll patients admitted for acute KD in Asan Medical Center were considered for inclusion. Acute management involved the administration of 2 g/kg of IVIG and 5 mg/kg/day of aspirin. The patient whose temperature was <37.5°C for more than 48 h from the diagnosis was discharged under the judgment of spontaneous defervescence, without IVIG administration.ResultsThe incidence of coronary artery aneurysm was 5.7% in 94 defervesced patients and 4.6% in the 1,277 patients treated with IVIG in the subacute phase (P = 0.593), and 2.5 and 2.2% in respective patient groups in the convalescent phase (P = 0.924). A scoring model which predicted spontaneous defervescence under the combination of C-reactive protein ≤10mg/dL and ≥2 conditions of no rash, neutrophil ≤65%, and/or alanine aminotransferase ≤80 IU/L, was developed and showed 80.7% sensitivity, 68.8% specificity, 15.8% positive predictive value, and a 97.8% negative predictive value.ConclusionThe incidence of coronary artery aneurysm in patients with the defervesced KD was not different from the IVIG treated patients. In the cases suitable for the predictive model, patients can wait for the spontaneous defervescence under intensive observation by medical professionals.

Identification the Causes of Diseases Caused by Fungi and the Intensity of Their Attacks on Shallots (Allium ascalonicum L.) in Bungaraya Village, Bungaraya Sub-district, Siak district

The demand of shallots that increase are not balanced with their productions especially in Riau. One of the main cause of low productivity is the attack of nuisance plant organism. The research aims to analyze the diseases that are caused by fungi and the intensity of their attacks on Shallots in Bungaraya Village, Bungaraya Sub District, Siak Regency. The research is done by using an exploration method; observing the diseases attacks intensity in field and observation; isolation and purification of shallots’ fungi, identification of fungi’ isolate on shallots. The intensity observation of diseases attack in field is done by diagonal method by determining the 5 points of samples randomly, then observing the kind of diseases that are found base on the symptoms and their intensity of attacks. The Identification of disease cause Fungi isolate observed the characteristic of macroscopic and microscopic mushroom. The result shows that the early diagnosis of diseases in the field on shallots in Bungaraya Village, Bungaraya Sub District, Siak Regency is withered fusarium diseases that is caused by A. porri fungi. The attack intensity of withered fusarium diseases is 80,51% and the attack intensity of purple spot diseases is 2,85%

Evaluation of a forest parameterization to improve boundary layer flow simulations over complex terrain. A case study using WRF-LES V4.0.1

Abstract. We evaluate the influence of a forest parametrization on the simulation of the boundary layer flow over moderate complex terrain in the context of the Perdigão 2017 field campaign. The numerical simulations are performed using the Weather Research and Forecasting model in large eddy simulation mode (WRF-LES). The short-term, high-resolution (40 m horizontal grid spacing) and long-term (200 m horizontal grid spacing) WRF-LES are evaluated for an integration time of 12 h and 1.5 months, respectively, with and without forest parameterization. The short-term simulations focus on low-level jet events over the valley, while the long-term simulations cover the whole intensive observation period (IOP) of the field campaign. The results are validated using lidar and meteorological tower observations. The mean diurnal cycle during the IOP shows a significant improvement of the along-valley wind speed and the wind direction when using the forest parametrization. However, the drag imposed by the parametrization results in an underestimation of the cross-valley wind speed, which can be attributed to a poor representation of the land surface characteristics. The evaluation of the high-resolution WRF-LES shows a positive influence of the forest parametrization on the simulated winds in the first 500 m above the surface.

Puzzling large-scale polarization in the galaxy cluster Abell 523

ABSTRACT Large-scale magnetic fields reveal themselves through diffuse synchrotron sources observed in galaxy clusters such as radio halos. Total intensity filaments of these sources have been observed in polarization as well, but only in three radio halos out of about 100 currently known. In this paper we analyse new polarimetric Very Large Array data of the diffuse emission in the galaxy cluster Abell 523 in the frequency range 1–2 GHz. We find for the first time evidence of polarized emission on scales of ∼2.5 Mpc. The total intensity emission is observed only in the central part of the source, likely due to observational limitations. To look for total intensity emission beyond the central region, we combine these data with single-dish observations from the Sardinia Radio Telescope and we compare them with multifrequency total intensity observations obtained with different instruments, including the LOw Frequency ARray and the Murchison Widefield Array. By analysing the rotation measure properties of the system and utilizing numerical simulations, we infer that this polarized emission is associated with filaments of the radio halo located in the outskirts of the system, in the peripheral region closest to the observer.

Effects of Weather Conditions on the Public Demand for Weather Information via Smartphone in Multiple Regions of China

Abstract Understanding when weather information is required by the public is essential for evaluating and improving user-oriented weather services. Because of the popularity of smartphones, most people can easily access weather information via smartphone applications. In this study, we analyzed usage data for the Moji Weather smartphone application in 2017 and 2018 and devised a demand index to determine how often the weather information was used by the public under different weather conditions. Using hourly observations of surface temperature, wind intensity, precipitation, and visibility, we quantified the relationship between the demand for weather information and weather conditions in different regions of China. In general, the demand index increased with increases in local hourly precipitation or surface wind intensity in all regions; however, there were notable regional differences in the increasing trends. Extreme hot weather was found to increase the demand index in Northern China, Xinjiang, and the Sichuan Basin while in Southern China it increased more in response to extreme cold weather. We quantified the relationships between the demand index and weather conditions by performing a polynomial regression analysis for each weather element and region. The high-demand thresholds were found to vary among regions, suggesting the need for customized weather services for users in different geographical regions. The study also revealed the contribution of weather warnings to weather information demand in two megacities and showed that warnings were effective for conveying information about weather-related risks.

Tethered Cord Syndrome in Patient with Lipomyelomeningocele: A Case Study

Introduction: Tethered Cord Syndrome (TCS) is a condition that occurs due to spinal cord traction caused by the attachment of the spinal cord to the surrounding tissues. The incidence of TCS is quite rare, approximately 0.25 per 1,000 live births Case Presentation: We reported a 4-year-old female patient with a lump on her sacral region since birth which enlarged over time. The patient experienced intermittent fever for 1 month before hospital admission and constipation since infancy. Physical examination revealed a lump with a diameter of 6 cm on her sacral region with no neurological abnormality. Ultrasonography examination showed an anechoic lesion with multiple linear structures on supragluteal sinistra with a size of 2.2 x 2.5 x 2.1 cm. MSCT findings showed spina bifida at L5 until S2 level with features of lipomyelomeningocele and tethered cord started from L2 level. Bilateral hydronephrosis, hydroureter, and distended bladder (pine tree appearance) with the possibility of the neurogenic bladder were also found on MSCT examination. The patient underwent surgery to excise the lump and to release the tethered cord. Microscopic findings from excised mass showed a group of neuronal and glial cells, the syncytial sheet pattern of meningothelial cells, and foci of calcification which supported lipomyelomeningocele diagnosis. Conclusions: : Intensive follow-up care and observation must be carried out in children with spinal dysraphism because it may be associated with TCS which may be asymptomatic at an early stage.

Deep transfer learning in sheep activity recognition using accelerometer data

Machine learning and sensor devices lined up with agriculture for the development of systems can efficiently provide real-time knowledge on animal behavior without the need of intense human observation, which is time consuming and labor demanding. In this study, we propose an intelligent system to classify the three important activities of sheep namely, “grazing”, “active”, and “inactive” states. We acquire primary data from Hebridean ewes using two types of sensors to capture the required activities. To address the problem of sensor heterogeneity in data and sensor orientation placement, we use convolutional neural networks (CNN) in conjunction with hand-crafted features, to improve the model generalization, specifically in terms of sensor orientation and position. Additionally, we utilise transfer learning (TL) for the model generalisation, which indicates substantial potential in future studies concerning animal activity recognition. More specifically, we use the TL to enable the reusability of pre-trained model for purely unseen data without performing model training and data labelling, which are highly time-consuming tasks. We performed experiments on datasets using CNN with automatic learned features, and on datasets using additional hand-crafted features. Our method obtained an overall accuracy of 98.55% on the source data (i.e., dataset captured via first sensor), and 96.59% on the target data (i.e., dataset captured via second sensor) when using the datasets which comprised the supplementary features. On the other hand, when CNN was applied to the raw datasets without any additional features, an accuracy of 97.46% and 94.79% was obtained on the source and target dataset respectively. This study is the first of its kind to propose convolutional neural network-based TL for the sheep activity recognition and demonstrate the significance of proposed approach in the context of data capturing, data labelling, and heterogeneity of sensor devices.

Subsurface Water Property Structures Along 80°E Under the Positive Indian Ocean Dipole Mode in December 2019

High-accuracy ship-based observations were conducted at 80°E in the Indian Ocean. Salinity below the mixed layer in 2019 was observed to be lower than that in 1995. This decrease in salinity was mainly attributed to anomalous advection associated with one of the strongest positive Indian Ocean dipole (pIOD) events in 2019 through analysis of the gridded time series of the salinity distributions based on the Argo float array. Increases and decreases in nitrate and dissolved inorganic carbon (DIC) and dissolved oxygen (DO), respectively, were also detected on the isopycnal surfaces where decreases in salinity were observed, suggesting that the anomalous upwelling and westward advection associated with the pIOD in the eastern part of the equatorial region resulted in low-salinity, low-oxygen, and nutrient-rich waters in the central off-equatorial region of the Indian Ocean. However, downward isopycnal heaving, which was also associated with the pIOD, was too strong to have increased nitrate below the mixed layers, and thus might have suppressed biological activity. The heaving also affected the DIC and DO distributions, and the effect of interannual changes such as those associated with the Indian Ocean dipole is essential to estimating changes in anthropogenic carbon storage. This research represents a case study, based on only two occupations; therefore, an assessment utilizing more intensive observations and more realistic numerical simulations is necessary in the future.

Precipitation Estimation from the NASA TROPICS Mission: Initial Retrievals and Validation

This paper describes the initial results of precipitation estimates from the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter-wave Sounder (TMS) using the Precipitation Retrieval and Profiling Scheme (PRPS). The TROPICS mission consists of a Pathfinder CubeSat and a constellation of six CubeSats, providing a low-cost solution to the frequent sampling of precipitation systems across the Tropics. The TMS instrument is a 12-channel cross-track scanning radiometer operating at frequencies of 91.655 to 204.8 GHz, providing similar resolutions to current passive microwave sounding instruments. These retrievals showcase the potential of the TMS instrument for precipitation retrievals. The PRPS has been modified for use with the TMS using a database based upon observations from current sounding sensors. The results shown here represent the initial postlaunch version of the retrieval scheme, as analyzed for the Pathfinder CubeSat launched on 30 June 2021. In terms of monthly precipitation estimates, the results fall within the mission specifications and are similar in performance to retrievals from other sounding instruments. At the instantaneous scale, the results are very promising.

Characteristics of ESBL-Infected Intensive Observation Room Patients From 2019-2020 With Microbiology And Resistance Pattern Results

BACKGROUND Uncontrolled antibiotic use causes the rise of antibiotic-resistant bacteria, one of which is ESBL. ESBL is a resistance mechanism developed by several gram-negative bacteria which can render beta-lactam antibiotics ineffective against them. Infections caused by ESBL bacteria are on the rise in the whole world and can raise the cost of hospitalisation. Indonesia is one of countries with limited data regarding infections by antibiotic-resistant bacteria. Thus, a research regarding the characteristics of Intensive Observation Room patients with ESBL producing bacterial infection is urgent to be researched. METHODS This research is a descriptive retrospective research with the whole ESBL-infected patients? data of RSUD Dr. Soetomo?s Intensive Observation Room from 2019-2020 as its population. Sampling is done by total sampling for all data which fits the inclusion and exclusion criteria. The variables included in this research are patients? age, patients? sex, invasive devices installed, culture samples, bacteria species, and antibiotic resistance patterns. RESULTS Based on available data which fits the inclusion and exclusion criteria, there are 81 patients with 10 patients cultured more than once which results in 91 culture data. From the patients? characteristics, patients? ages are dominated in the 18-60 y/o group with 51 patients (63%), male sex with 47 patients (58%), and appendicitis as the dominant diagnosis with 11 patients (13,6%). Ventilators and Nutrition Tubes are the most installed invasive devices with each being installed in 67 patients (82,7%). Microbiology data shows Escherichia coli is the dominant species with positive results showing from 51 cultures. Amikacin is the antibiotic with the least resistance of all samples.