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The WPR-LQ-7 is a UHF (1.3575 GHz) wind profiler radar used for routine measurements of the lower troposphere at Shigaraki Middle and Upper (MU) observatory (34.85° N, 136.10° E, Japan) at a vertical resolution of 100 m and a time resolution of 10 min. Following studies carried out with the 46.5 MHz Middle and Upper atmosphere (MU) radar (Luce et al., 2018), we tested models used to estimate turbulence kinetic energy (TKE) dissipation rates ε from the Doppler spectral width in the altitude range ~0.7 to 4.0 km ASL. For this purpose, we compared LQ-7-derived ε by using processed data available on line (http://www.rish.kyoto-u.ac.jp/radar-group/blr/shigaraki/data/) with direct estimates of ε (εU) from DataHawk UAVs. The statistical results reveal the same trends as reported by Luce et al. (2018) with the MU radar, namely: (1) The simple formulation based on dimensional analysis εLout=σ3 / Lout, with Lout ~70 m, provides the best statistical agreement with εU. (2) The model εN predicting a σ2 N law (N is Brunt-Vaïsälä frequency) for stably stratified conditions tends to overestimate for εU < ~5 10−4 m2 s−3 and to underestimate for εU > ~5 10−4 m2 s−3. We also tested a model εS predicting a σ2 S law (S is the vertical shear of horizontal wind) supposed to be valid for low Richardson numbers (Ri = N2 ⁄ S2). From the case study of a turbulent layer produced by a Kelvin-Helmholtz instability, we found that εS and εLout are both very consistent with εU, while εN underestimates εU in the core of the turbulent layer where N is minimum. We also applied the Thorpe method from data collected from a nearly simultaneous radiosonde and tested an alternative interpretation of the Thorpe length in terms of the Corrsin scale defined for weakly stratified turbulence. A statistical analysis showed that εS also provides better statistical agreement with εU and is much less biased than εN. Combining estimates of N and shear from DataHawk and radar data, respectively, a rough estimate of the Richardson number at a vertical resolution of 100 m (Ri100) was obtained. We performed a statistical analysis on the Ri dependence of the models. The main outcome is that εS compares well with εU for low Ri100's (Ri100 < ~1) while εN fails. εLout varies as εS with Ri100 so that εLout remains the best (and simplest) model in the absence of information on Ri. Also, σ appears to vary as Ri100−1/2 when Ri100 > ~0.4 and shows a degree of dependence with S100 otherwise.

In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.

The Instabilities, Dynamics, and Energetics accompanying Atmospheric Layering (IDEAL) project was conceived to improve our understanding of the dynamics of sheet and layer (S&L) structures in the lower troposphere under strongly stable conditions. The approach employed a synergistic combination of targeted multi-point observations using small unmanned aircraft systems (sUAS) guiding direct numerical simulation (DNS) modeling to characterize the dynamics driving the S&L structures and associated flow features. The IDEAL research program consisted of two phases. The first was an observational field campaign to systematically probe stable lower atmosphere conditions using multiple DataHawk-2 (DH2) sUAS. Coordinated, simultaneous multi-DH2 flights were guided by concurrent Integrated Sounding System (ISS) wind profiler radar and radiosonde soundings performed by NCAR Earth Observing Laboratory (EOL) participants. Additional sUAS flight guidance was obtained from real-time sUAS measurements. Following the field campaign, the second phase focused on high-resolution DNS modeling efforts guided by in-situ observations made during the first phase. This overview focuses on the details of the observational phase that took place from 24 October to 15 November 2017 at Dugway Proving Ground (DPG), Utah. A total of 72 DH2 flights coordinated with 93 balloon-borne radiosondes were deployed in support of the IDEAL field campaign. Our discussion addresses the average atmospheric conditions, the observation strategy, and the objectives of the field campaign. Also presented are representative flight sorties and sUAS environmental and turbulence measurements.

Under stably stratified conditions, the dissipation rate ε of turbulence kinetic energy (TKE) is related to the structure function parameter for temperature , through the buoyancy frequency and the so-called mixing efficiency. A similar relationship does not exist for convective turbulence. In this paper, we propose an analytical expression relating ε and in the convective boundary layer (CBL), by taking into account the effects of nonlocal heat transport under convective conditions using the Deardorff countergradient model. Measurements using unmanned aerial vehicles (UAVs) equipped with high-frequency response sensors to measure velocity and temperature fluctuations obtained during the two field campaigns conducted at Shigaraki MU observatory in June 2016 and 2017 are used to test this relationship between ε and in the CBL. The selection of CBL cases for analysis was aided by auxiliary measurements from additional sensors (mainly radars), and these are described. Comparison with earlier results in the literature suggests that the proposed relationship works, if the countergradient term γ D in the Deardorff model, which is proportional to the ratio of the variances of potential temperature θ and vertical velocity w, is evaluated from in situ (airplane and UAV) observational data, but fails if evaluated from large-eddy simulation (LES) results. This appears to be caused by the tendency of the variance of θ in the upper part of the CBL and at the bottom of the entrainment zone to be underestimated by LES relative to in situ measurements from UAVs and aircraft. We discuss this anomaly and explore reasons for it.

Background: The common cause of axillary nerve injury is due to lack of knowledge about the safe position of the nerve during orthopedic surgeries. Many workers have studied the safe area for axillary nerve by measuring its distance from various landmarks. The aim of the present study is to find the average distance of the location of the axillary nerve from the acromion process in the cadavers. Materials and Methods: 50 Shoulder region specimens from 25 cadavers (aged 45-55 years; both male and female sex) available in the department of Anatomy, BGS Global Institute of Medical Sciences, Bengaluru were utilized for the present study. After methodical dissection of shoulder region we measured the distance from 1) Lateral aspect of acromion processes to root of axillary nerve and 2) Posterior aspect of acromion processes to root of axillary nerve using measuring tape ( in centimeters) on both sides. The descriptive statistics including mean, standard deviation and quartile range were calculated for the measurements on both sides using SPSS software version16. Results: The mean distance of axillary nerve from the lateral edge of the acromion process was 6.39±0.8 cm on right side and 6.33±0.7cm on left side. The mean distance from posterior aspect of acromion process was 5.89±0.6 cm on right side and 5.82±0.6 cm on left side. Quartile distribution showed that, in 75% individuals the distance between lateral aspect of acromion process and axillary nerve was 7cm on both sides. The distance between posterior aspect of acromion process and axillary nerve was 6.4 cm on right side and 6.5 cm on left side. Conclusion: Knowledge of morphometric distance of axillary nerve from the acromion process is important in deltoid split surgeries and while giving intramuscular injection to deltoid region.

Internal combustion engines, now a days is the best available reliable source of power for all domestic, large scale industrial and transportation applications. The major issue arises at the efficiency of these engines. The major pollutants are Un Burned Hydro Carbons (UBHC), and Oxides of Nitrogen (Nox) .These are formed due to incomplete combustion of the fuel in combustion chamber of diesel engine. One of the important factors which influence the performance and emission of diesel engine is fuel injection pressure. An experimental study was performed on a light duty direct injection diesel engine at 150 bar, 200 bar and 250 bar injection pressure to study its effect on performance and emission These emissions can be controlled by different techniques like EGR, changing the injection pressure of fuel into the combustion chamber etc., It is a well known fact that as the injection pressure of fuel increases, the mass flow rate of fuel will vary for proper mixing of fuel and air in the combustion chamber. In the present work, it is proposed to investigate the effect of variations in injection pressure on emissions and for this STAR-CD will be used as a tool. To aid the setup of these calculations, visualization and interpretation of results, CD - Adapco has developed a pre and post- processor environment, es-ice which is a special tool in STAR-CD solver which will be used for this analysis. The performance and emission characteristics were presented graphically and concluded that they were found better at the fuel injection pressure 200 bar for the light duty engine.

International audience; Midlevel Cloud-base Turbulence (MCT) caused by ice/snow precipitation from midlevel clouds falling into dry air below the cloud base and sublimating is investigated. MCT phenomena in the lower troposphere as revealed by the Middle and Upper atmosphere (MU) radar in Shigaraki, Japan, during the Shigaraki unmanned aerial vehicle and radar Experiment campaigns in the spring-summer of 2015 and 2016 are described. The MU radar was operated in a high-resolution ( 20-m) range imaging mode and hence revealed the structure of these MCTs in great detail. These MCT layers grew to hundreds of meters in thickness, often reaching nearly 2,000 m in depth, lasting often for as much as 24 hr. A simple analytical model and a second-moment closure-based turbulent mixing model are used to estimate the levels of turbulence kinetic energy and its dissipation rate in the MCT layer and compare them to those measured by the MU radar. The study shows that MCT can give rise to moderate levels of turbulence of potential interest to aviation, confirming conclusions reached by earlier pioneering studies. However, to our knowledge, this important process has not received the attention it deserves by the atmospheric community so far, and therefore, it is the principal goal of this paper to not only present some observations and preliminary modeling results, but also redraw the attention of atmospheric scientists to this important process.

International audience; The ShUREX (Shigaraki UAV Radar Experiment) 2015 campaign carried out at the Shigaraki Middle and Upper atmosphere (MU) observatory (Japan) in June 2015 provided a unique opportunity to compare vertical profiles of atmospheric parameters estimated from unmanned aerial vehicle (UAV), balloon, and radar data in the lower troposphere. The present work is intended primarily as a demonstration of the potential offered by combination of these three instruments for studying the small-scale structure and dynamics in the lower troposphere. Here, we focus on data collected almost simultaneously by two instrumented UAVs and two meteorological balloons, near the MU radar operated continuously during the campaign. The UAVs flew along helical ascending and descending paths at a nearly constant horizontal distance from the radar ( 1.0 km), while the balloons launched from the MU radar site drifted up to 3-5 km in the altitude range of comparisons ( 0.5 to 4.0 km) due to wind advection. Vertical profiles of squared Brünt-Väisälä frequency N 2 and squared vertical gradient of generalized potential refractive index M 2 were estimated at a vertical resolution of 20 m from pressure, temperature, and humidity data collected by UAVs and radiosondes. Profiles of M 2 were also estimated from MU radar echo power at vertical incidence at a vertical sampling of 20 m and various time resolutions (1-4 min). The balloons and the MU radar provided vertical profiles of wind and wind shear S so that two independent estimates of the gradient Richardson number ( Ri = N 2/ S 2) could be obtained at a range resolution of 150 m. The two estimates of Ri profiles also showed remarkable agreement at all altitudes. We show that all three instruments detected the same prominent temperature and humidity gradients, down to decameter scales in stratified conditions. These gradients extended horizontally over a few kilometers at least and persisted for hours without significant changes, indicating that the turbulent diffusion was weak . Large discrepancies between N 2and M 2 profiles derived from the balloon, UAV, and radar data were found in a turbulent layer generated by a Kelvin-Helmholtz (KH) shear flow instability in the height range from 1.80 to 2.15 km. The cause of these discrepancies appears to depend on the stage of the KH billows.

Turbulent mixing in the interior of the oceans is not as well understood as mixing in the oceanic boundary layers. Mixing in the generally stably stratified interior is primarily, although not exclusively, due to intermittent shear instabilities. Part of the energy extracted by the Reynolds stresses acting on the mean shear is expended in increasing the potential energy of the fluid column through a buoyancy flux, while most of it is dissipated. The mixing coefficient χm, the ratio of the buoyancy flux to the dissipation rate of turbulence kinetic energy ε, is an important parameter, since knowledge of χm enables turbulent diffusivities to be inferred. Theory indicates that χm must be a function of the gradient Richardson number. Yet, oceanic studies suggest that a value of around 0.2 for χm gives turbulent diffusivities that are in good agreement with those inferred from tracer studies. Studies by scientists working with atmospheric radars tend to reinforce these findings but are seldom referenced in oceanographic literature. The goal of this paper is to bring together oceanographic, atmospheric, and laboratory observations related to χm and to report on the values deduced from in situ data collected in the lower troposphere by unmanned aerial vehicles, equipped with turbulence sensors and flown in the vicinity of the Middle and Upper Atmosphere (MU) radar in Japan. These observations are consistent with past studies in the oceans, in that a value of around 0.16 for χm yields good agreement between ε derived from turbulent temperature fluctuations using this value and ε obtained directly from turbulence velocity fluctuations.

The prevailing constantΛ-Gcosmological model agrees with observational evidence including the observed red shift, Big Bang Nucleosynthesis (BBN), and the current rate of acceleration. It assumes that matter contributes 27% to the current density of the universe, with the rest (73%) coming from dark energy represented by the Einstein cosmological parameterΛin the governing Friedmann-Robertson-Walker equations, derived from Einstein’s equations of general relativity. However, the principal problem is the extremely small value of the cosmological parameter (~10−52 m2). Moreover, the dark energy density represented byΛis presumed to have remained unchanged as the universe expanded by 26 orders of magnitude. Attempts to overcome this deficiency often invoke a variableΛ-Gmodel. Cosmic constraints from action principles require that either bothGandΛremain time-invariant or both vary in time. Here, we propose a variableΛ-Gcosmological model consistent with the latest red shift data, the current acceleration rate, and BBN, provided the split between matter and dark energy is 18% and 82%.Λdecreases (Λ~τ-2, whereτis the normalized cosmic time) andGincreases (G~τn) with cosmic time. The model results depend only on the chosen value ofΛat present and in the far future and not directly onG.

The Lagrangian prediction skill (model ability to reproduce Lagrangian drifter trajectories) of the nowcast/forecast system developed for the Gulf of Mexico at the University of Colorado at Boulder is examined through comparison with real drifter observations. Model prediction error (MPE), singular values (SVs) and irreversible-skill time (IT) are used as quantitative measures of the examination. Divergent (poloidal) and nondivergent (toroidal) components of the circulation attractor at 50m depth are analyzed and compared with the Lagrangian drifter buoy data using the empirical orthogonal function (EOF) decomposition and the measures, respectively. Irregular (probably, chaotic) dynamics of the circulation attractor reproduced by the nowcast/forecast system is analyzed through Lyapunov dimension, global entropies, toroidal and poloidal kinetic energies. The results allow assuming exponential growth of prediction error on the attractor. On the other hand, the q-th moment of MPE grows by the power law with exponent of 3q/4. The probability density function (PDF) of MPE has a symmetrical but non-Gaussian shape for both the short and long prediction times and for spatial scales ranging from 20km to 300km. The phenomenological model of MPE based on a diffusion-like equation is developed. The PDF of IT is non-symmetric with a long tail stretched towards large ITs. The power decay of the tail was faster than 2 for long prediction times.

For the first time, the performance of the range imaging technique of the very high frequency band middle and upper atmosphere (MU) radar (Shigaraki observatory, Japan), when using frequency diversity, is assessed. This is done by the detection of unmanned aerial vehicles (UAVs) operated near the radar during the Shigaraki UAV radar experiment campaign, carried out from June 1, 2015 to June 14, 2015. During this campaign devoted to the measurements of fine-scale turbulence and stability in the lower troposphere using the turbulence sensors on the DataHawk UAV and the MU radar, the detection of the small UAV by the MU radar provided an excellent opportunity for taking stock of the range imaging technique in the presence of a single hard target. It was found that range imaging reproduces a faithful image of the aircraft position and its displacements with an excellent accuracy (of the order of ~10 m), giving extra credence to the thin echo layers and their vertical displacements generally observed from the range imaging technique in stably stratified conditions.

We tested models commonly used for estimating turbulence kinetic energy dissipation rates $$\varepsilon$$ from very high frequency stratosphere–troposphere radar data. These models relate the root-mean-square value $$\sigma$$ of radial velocity fluctuations assessed from radar Doppler spectra to $$\varepsilon$$ . For this purpose, we used data collected from the middle and upper atmosphere (MU) radar during the Shigaraki unmanned aerial vehicle (UAV)—radar experiment campaigns carried out at the Shigaraki MU Observatory, Japan, in June 2016 and 2017. On these occasions, UAVs equipped with fast-response and low-noise Pitot tube sensors for turbulence measurements were operated in the immediate vicinity of the MU radar. Radar-derived dissipation rates $$\varepsilon$$ estimated from the various models at a range resolution of 150 m from the altitude of 1.345 km up to the altitude of ~ 4.0 km, a (half width half power) beam aperture of 1.32° and a time resolution of 24.6 s, were compared to dissipation rates ( $$\varepsilon_{U}$$ ) directly obtained from relative wind speed spectra inferred from UAV measurements. Firstly, statistical analysis results revealed a very close relationship between enhancements of $$\sigma$$ and $$\varepsilon_{U}$$ for $$\varepsilon_{U} \,{ \gtrsim }\,10^{ - 5} \,{\text{m}}^{2} \,{\text{s}}^{ - 3}$$ , indicating that both instruments detected the same turbulent events with $$\varepsilon_{U}$$ above this threshold. Secondly, $$\varepsilon_{U}$$ was found to be statistically proportional to $$\sigma^{3}$$ , whereas a $$\sigma^{2}$$ dependence is expected when the size of the largest turbulent eddies is smaller than the longitudinal and transverse dimensions of the radar sampling volume. The $$\sigma^{3}$$ dependence was found even after excluding convectively generated turbulence in the planetary boundary layer and below clouds. The best agreement between $$\varepsilon_{U}$$ and radar-derived $$\varepsilon$$ was obtained with the simple formulation based on dimensional analysis $$\varepsilon = \sigma^{3} /L_{c}$$ where LC ≈ 50–70 m. This empirical expression constitutes a simple way to estimate dissipation rates in the lower troposphere from MU radar data whatever the sources of turbulence be, in clear air or cloudy conditions, consistent with UAV estimates.

15th MST Radar WorkshopSession M4: MST Radar scattering, turbulence and small-scale processesMay 30 (Tue), Poster Session

15th MST Radar WorkshopSession M4: MST Radar scattering, turbulence and small-scale processesMay 30 (Tue), Poster Session

15th MST Radar WorkshopSession M4: MST Radar scattering, turbulence and small-scale processesMay 30 (Tue), NIPR Auditorium

15th MST Radar WorkshopSession M4: MST Radar scattering, turbulence and small-scale processesMay 30 (Tue), Poster Session

15th MST Radar WorkshopSession M4: MST Radar scattering, turbulence and small-scale processesMay 30 (Tue), NIPR Auditorium

15th MST Radar WorkshopSession M4: MST Radar scattering, turbulence and small-scale processesMay 30 (Tue), Poster Session

15th MST Radar WorkshopSession M4: MST Radar scattering, turbulence and small-scale processesMay 30 (Tue), Poster Session

In this study, we model a “slippery” layer observed during September 2011 at a National Institute of Ocean Technology (NIOT) mooring deployed at 18 o N, 89 o E in the northern Bay of Bengal (BoB). The mooring was located close to the mouths of the huge rivers draining the Indian subcontinent. The lateral advection of riverine water masses past the mooring resulted in a shallow brackish layer 10–15 m deep bounded by a strong halocline below, giving rise to the possibility of a slippery layer gliding past the layers below. The strong currents in this slippery layer were simulated by a simple slab-type dynamical model. In addition, a second moment turbulence closure-based model, driven by surface data from the buoy was also used to simulate the water mass structure and upper layer currents during the event. Both the slab and turbulence-closure models reproduce currents in the slippery layer reasonably well overall, although the currents are somewhat overestimated. This “haline” slippery layer observed in the BoB complements well the “thermal” slippery layers that have been observed under certain conditions during strong diurnal heating of the upper layers of the ocean.

Turbulent mixing in the upper layers of the northern Bay of Bengal is affected by a shallow layer overlying the saline waters of the Bay, which results from the huge influx of freshwater from major rivers draining the Indian subcontinent and from rainfall over the Bay during the summer monsoon. The resulting halocline inhibits wind-driven mixing in the upper layers. The brackish layer also alters the optical properties of the water column. Air-sea interaction in the Bay is expected to play a significant role in the intraseasonal variability of summer monsoons over the Indian subcontinent, and as such the sea surface temperature (SST) changes during the summer monsoon are of considerable scientific and societal importance. In this study, data from the heavily instrumented Woods Hole Oceanographic Institution (WHOI) mooring, deployed at 18oN, 89.5oE in the northern Bay from December 2014 to January 2016, are used to drive a one-dimensional mixing model, based on second moment closure model of turbulence, to explore the intra-annual variability in the upper layers. The model results highlight the importance of the optical properties of the upper layers (and hence the penetration of solar insolation in the water column), as well as the temperature and salinity in the upper layers prescribed at the start of the model simulation, in determining the SST in the Bay during the summer monsoon. The heavy rainfall during the summer monsoon also plays an important role. The interseasonal and intraseasonal variability in the upper layers of the Bay are contrasted with those in the Arabian Sea, by the use of the same model but driven by data from an earlier deployment of a WHOI mooring in the Arabian Sea at 15.5 oN, 61.5 oE from December 1994 to December 1995.

Lessons learned from disastrous hurricanes in recent years, especially Katrina, Ike, Irene, Isaac and Sandy are discussed, and improved ways to inform the public about the potential impact of tropical cyclones are presented. An alternative classification system is shown to be more informative than the Saffir–Simpson scale currently in use, and should prove beneficial to the general public and the coastal engineering community. The most important lesson is that the size of the hurricane matters , not just its intensity .

The Shigaraki unmanned aerial vehicle (UAV)-Radar Experiment (ShUREX) is an international (USA-Japan-France) observational campaign, whose overarching goal is to demonstrate the utility of small, lightweight, inexpensive, autonomous UAVs in probing and monitoring the lower troposphere and to promote synergistic use of UAVs and very high frequency (VHF) radars. The 2-week campaign lasting from June 1 to June 14, 2015, was carried out at the Middle and Upper Atmosphere (MU) Observatory in Shigaraki, Japan. During the campaign, the DataHawk UAV, developed at the University of Colorado, Boulder, and equipped with high-frequency response cold wire and pitot tube sensors (as well as an iMET radiosonde), was flown near and over the VHF-band MU radar. Measurements in the atmospheric column in the immediate vicinity of the radar were obtained. Simultaneous and continuous operation of the radar in range imaging mode enabled fine-scale structures in the atmosphere to be visualized by the radar. It also permitted the UAV to be commanded to sample interesting structures, guided in near real time by the radar images. This overview provides a description of the ShUREX campaign and some interesting but preliminary results of the very first simultaneous and intensive probing of turbulent structures by UAVs and the MU radar. The campaign demonstrated the validity and utility of the radar range imaging technique in obtaining very high vertical resolution (~20 m) images of echo power in the atmospheric column, which display evolving fine-scale atmospheric structures in unprecedented detail. The campaign also permitted for the very first time the evaluation of the consistency of turbulent kinetic energy dissipation rates in turbulent structures inferred from the spectral broadening of the backscattered radar signal and direct, in situ measurements by the high-frequency response velocity sensor on the UAV. The data also enabled other turbulence parameters such as the temperature structure function parameter CT2 and refractive index structure function parameter Cn2 to be measured by sensors on the UAV, along with radar-inferred refractive index structure function parameter Cn, radar2. The comprehensive dataset collected during the campaign (from the radar, the UAV, the boundary layer lidar, the ceilometer, and radiosondes) is expected to help obtain a better understanding of turbulent atmospheric structures, as well as arrive at a better interpretation of the radar data., The Correction to this article has been published in Progress in Earth and Planetary Science 2018 5:48

A wide range of morphological varieties and developmental anomalies of the thyroid gland have been reported in literature such as hypoplasia, ectopic thyroid, hemi agenesis and agenesis. Out of these the incidence of agenesis of the isthmus of thyroid gland is rare and very few cases have been reported. During routine dissection of the male cadaver, agenesis of isthmus of thyroid gland in the midline was noted. It resulted in two lateral lobes and the arteries supplying the gland were confined only to the respective lobe with absence of anastomosis. Agenesis of Isthmus of thyroid has clinical, phylogenetic and surgical significance.

Ecosystem models, used mainly in studying the interactions between different trophic levels, can also be used for ocean circulation model skill assessment, with the help of satellite ocean color data. This paper presents how the use of a simple NPZ primary productivity ecosystem model, coupled to a hydrodynamical model, can help assessing the skill of the physical ocean model in depicting realistically the prevailing mesoscale features of the upper layers of the Gulf of Mexico. Results indicate that the physical model effectively reproduces the mesoscale features of circulation underlying the resulting chlorophyll concentrations, especially when circulation fronts exist.