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The Ultrasound Velocity Profiling (UVP) technique allows real-time, non-invasive flow mapping of a fluid along a 1D-measuring line. This study explores the possibility of using the UVP technique and X-ray video-fluoroscopy (XVF) to elucidate the deglutition process with the focus on bolus rheology. By positioning the UVP probe so that the pulsed ultrasonic beam passes behind the air-filled trachea, the bolus flow in the pharynx can be measured. Healthy subjects in a clinical study swallowed fluids with different rheological properties: Newtonian (constant shear viscosity and non-elastic); Boger (constant shear viscosity and elastic); and shear thinning (shear rate-dependent shear viscosity and elastic). The results from both the UVP and XVF reveal higher velocities for the shear thinning fluid, followed by the Boger and the Newtonian fluids, demonstrating that the UVP method has equivalent sensitivities for detecting the velocities of fluids with different rheological properties. The velocity of the contraction wave that clears the pharynx was measured in the UVP and found to be independent of bolus rheology. The results show that UVP not only assesses accurately the fluid velocity in a bolus flow, but it can also monitor the structural changes that take place in response to a bolus flow, with the added advantage of being a completely non-invasive technique that does not require the introduction of contrast media. Electronic supplementary material The online version of this article (10.1007/s00455-020-10092-4) contains supplementary material, which is available to authorized users.

Purpose The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate the biomass per species and plot. Furthermore, it aims to measure forest biodiversity using established formulae for tree species diversity index, richness, evenness and accumulative curve. Design/methodology/approach Field data were collected, including stratification of forest sample plots. Statistical analysis of the data was carried out, and locally appropriate allometric equations were applied for biomass estimation. Findings Representative circular 556 forest sample plots of 1,000 m2 contained 13,135 trees belonging to nine tree species with a total aboveground biomass of 12,887 tonnes. Sixty-eight per cent of the trees were found between 2,600 and 3,400 masl; approximately 63 per cent had a diameter at breast height equal to 30 cm, and 45 per cent were less than 12 m in height. The Shannon diversity index was 1.82, and Simpson’s index of diversity was 0.813. Research limitations/implications Rough terrain, long distances, harsh weather conditions and location of forest in steep narrow valleys presented challenges for the field crews, and meant that fieldwork took longer than planned. Practical implications Estimating biomass in Gilgit-Baltistan’s forests using locally developed allometric equations will provide transparency in estimates of forest reference levels, National Forest Monitoring System in Pakistan and devising Reducing Emissions from Deforestation and Forest Degradation national strategies and for effective implementation. Originality/value This paper presents the first detailed forest inventory carried out for the dry temperate and semi-arid cold region of Gilgit-Baltistan, Pakistan.

In this study, we investigate stand-alone and combined Pleiades high-resolution passive optical and ALOS PALSAR active Synthetic Aperture Radar (SAR) satellite imagery for aboveground biomass (AGB) estimation in subtropical mountainous Chir Pine (Pinus roxburghii) forest in Murree Forest Division, Punjab, Pakistan. Spectral vegetation indices (NDVI, SAVI, etc.) and sigma nought HV-polarization backscatter dB values are derived from processing optical and SAR datasets, respectively, and modeled against field-measured AGB values through various regression models (linear, nonlinear, multi-linear). For combination of multiple spectral indices, NDVI, TNDVI, and MSAVI2 performed the best with model R2/RMSE values of 0.86/47.3 tons/ha. AGB modeling with SAR sigma nought dB values gives low model R2 value of 0.39. The multi-linear combination of SAR sigma nought dB values with spectral indices exhibits more variability as compared with the combined spectral indices model. The Leave-One-Out-Cross-Validation (LOOCV) results follow closely the behavior of the model statistics. SAR data reaches AGB saturation at around 120-140 tons/ha, with the region of high sensitivity around 50-130 tons/ha; the SAR-derived AGB results show clear underestimation at higher AGB values. The models involving only spectral indices underestimate AGB at low values (< 60 tons/ha). This study presents biomass estimation maps of the Chir Pine forest in the study area and also the suitability of optical and SAR satellite imagery for estimating various biomass ranges. The results of this work can be utilized towards environmental monitoring and policy-level applications, including forest ecosystem management, environmental impact assessment, and performance-based REDD+ payment distribution.

Marine green microalgae are a sustainable source of high-quality protein. However, due to their green pigmentation and composition of volatiles, their incorporation into food products is a challenge. Incorporation of cell-wall disrupted Tetraselmis chuii (Tc) into bread (0, 4, 8, 12 and 16% wheat flour substitution) affected dough rheology and bread quality negatively. These effects were more pronounced at addition levels necessary for a EFSA nutrition claim on protein enrichment (12 and 16%). Treatment of Tc with ethanol not only removed much of the green pigmentation and volatiles, but also reduced the negative impact on dough rheology and bread quality. Doughs prepared with ethanol treated Tc (TcEt) showed a clear improvement in dough rheology evident as increased dough-stability-time (DST), resistance to extension (Rmax) and elastic-recovery-compliance (Je) particularly at substitution levels >4%. This was accompanied by an increase in bread quality e.g. at 12% substitution level specific volume increased from 2.1 to 2.69 mL/g, crumb firmness decreased from 1358 to 297 g and slice brightness increased from 25.2 to 49.0. Ethanol treatment of algae may be a feasible strategy to address the sensory and structural challenges that hinder incorporation of algae into foods at levels that can potentially confer nutritional benefits.

Global soil moisture products retrieved from various remote sensing sensors are becoming readily available with a nearly daily temporal resolution. With lack of ground observations in Pakistan, microwave sensors are viable technologies for retrieving soil moisture from space. Thus, this study compares soil moisture data from Soil Moisture and Ocean Salinity (SMOS) with Advanced Microwave Scanning Radiometer (AMSR-E) for 2010 and 2011, which were years where massive flooding occurred. We find suitable correlations (r = 0.47) for Level-2 soil moisture values for both satellites and report temporal variability during the pre-monsoon, monsoon, post-monsoon and winter seasons. This study motivates using satellite retrievals as a start towards more comprehensive studies in Pakistan.

Recent field surveys have reported the presence of corals in many places in the Pakistan coastal ocean; Astola Island especially has been a subject of interest with regards to corals and overall marine biodiversity, and has in fact recently been declared Pakistan’s first Marine Protected Area. This study presents an analysis of coral reefs identification and their spatial distribution through optical satellite remote sensing in the surrounding area of Astola Island. Besides remote sensing data, the study considers sea survey data collected by divers in recent years. A benthic map of ocean ecosystem habitats is generated, through processing of Landsat 8 OLI (Operational Land Imager) imagery. The satellite data was selected at low-tide time to get maximum sunlight penetration in shallow water. Water-column correction was used to generate the depth-invariant index on multiple band-pairs. Water column corrected depth-invariant index bands were then segmented and classified through object-based classification. The results from the remote sensing data processing over Astola Island show good agreement with the field survey data, with nearly all the field survey points of coral reefs falling within the coral reefs class. Use of remote sensing imagery such as Landsat 8, and application of the water column correction method can allow for regular monitoring and management of coral reefs and other benthic ecosystems in the coastal ocean of Pakistan and coastal Arabian Sea.

The characteristics of the flows of boluses with different consistencies, i.e. different rheological properties, through the pharynx have not been fully elucidated. The results obtained using a novel in vitro device, the Gothenburg Throat, which allows simultaneous bolus flow visualisation and manometry assessments in the pharynx geometry, are presented, to explain the dependence of bolus flow on bolus consistency. Four different bolus consistencies of a commercial food thickener, 0.5, 1, 1.5 and 2 Pa s (at a shear rate of 50 s−1)—corresponding to a range from low honey-thick to pudding-thick consistencies on the National Dysphagia Diet (NDD) scale—were examined in the in vitro pharynx. The bolus velocities recorded in the simulator pharynx were in the range of 0.046–0.48 m/s, which is within the range reported in clinical studies. The corresponding wall shear rates associated with these velocities ranged from 13 s−1 (pudding consistency) to 209 s−1 (honey-thick consistency). The results of the in vitro manometry tests using different consistencies and bolus volumes were rather similar to those obtained in clinical studies. The in vitro device used in this study appears to be a valuable tool for pre-clinical analyses of thickened fluids. Furthermore, the results show that it is desirable to consider a broad range of shear rates when assessing the suitability of a certain consistency for swallowing.

This study examines ALOS-2 PALSAR L-band dual-polarization (HH and HV) SAR data and Landsat-8 optical imagery for land cover classification. The SAR data has been preprocessed first, which included radiometric calibration, geocoding, and speckle filtering. The HH/HV band ratio has been used to create the third band, and thus a synthetic RGB SAR image was created. The Landsat-8 data was also preprocessed for the classification process. For land cover classification of both SAR and optical datasets, the supervised maximum likelihood classifier was used. Training samples were selected from the Landsat-8 optical imagery with the support of information available in Google Earth; the same pixel locations of training data were used to extract training data from SAR image as well. The Landsat-8 optical imagery was classified and also used for visual assessment of the SAR land cover classification results. Accuracy assessment has been done for both the results of SAR and Landsat-8 data. The SAR classified output gives us accuracy of 93.15% and the Landsat-8 classified map accuracy was 91.34%, while the Kappa coefficient for SAR and Landsat-8 classified images is 0.92 and 0.89, respectively. Classification limitations exist in some cases, such as roads being merged in vegetation areas and some of the barren land is merged in settlements. The land cover classification can be expected to be further improved using polarimetric decomposition methods and fusion of SAR data with optical data.

As compared with conventional methods for measuring ocean surface currents, spaceborne synthetic aperture radar (SAR) offers cloud-penetrating ocean-current observation capability at high spatial resolution. While some studies have shown the potential of SAR for studying ocean surface currents through feature tracking, they have only analyzed a few images to demonstrate the basic measurement technique, and no concise general technique has been developed. This paper shows the application of the maximum cross correlation (MCC) method to generate ocean surface currents from nearly two years of available sequential spaceborne C-band SAR imagery from the Envisat ASAR and ERS-2 Advanced Microwave Instrument SAR sensors over the coastal California Current System. The data processing strategies are discussed in detail, and results are compared with HF radar measured currents. One-dimensional wavenumber spectra of the SAR-derived surface currents agree with the $k^{-2}$ power law, as predicted by submesoscale resolution models. Comparisons with HF radar currents show encouraging results with MCC SAR vectors oriented slightly counterclockwise relative to HF radar vectors. MCC SAR surface currents are found to have larger magnitudes than HF radar currents ( $\approx$ 11 cm/s), which may be due to the fact that SAR penetrates only a few centimeters into the ocean surface whereas HF radar currents are averaged over the top 1 m of the ocean surface. The larger part of this magnitude difference is contained in the along-shore component, which can be attributed to higher HF radar accuracy in the direct radial cross-shore measurements as compared with along-shore components derived from multiple cross-shore radial measurements.

This chapter gives an overview of the in vitro models that are currently used for studying swallowing. The focus is on the construction, geometry, and performance of mechanical models. Swallowing simulations and mathematical modeling are also considered. The in vitro models that are concerned with the oral, pharyngeal, and esophageal phases of swallowing linked to bolus properties are discussed. The pharyngeal phase is given special consideration, as it is involved in both food transport to the stomach and air transport to the lungs, and therefore constitutes the most critical phase of swallowing.

Sustainability of desert ecosystem is highly dependent upon water availability from different sources. Paleochannels are important sources of groundwater, and exploiting such resources involves their identification/mapping and subsequent investigation for fresh groundwater. A study in which multisensor (optical/infrared Landsat 8 OLI and active microwave Envisat ASAR) images of the Cholistan desert of Pakistan were processed and analyzed to identify and map Hakra River paleochannels is presented. Radiometrically corrected optical and synthetic aperture radar datasets were fused using principal components image fusion method. The paleochannels were extracted from the analysis of this fused output, and normalized difference vegetative index analysis of Landsat 8 OLI atmospheric corrected images was used as supporting information. Identification and alignment of an identified paleochannel was validated with geophysical ground measurements (electrical resistivity and conductivity surveys) and historical records. The presence of high apparent electrical resistivity with corresponding low soil water conductivity values intersects well with the paleochannels identified from the remote sensing data. The results were also confirmed with historical evidence such as old wells beside forts and proposed ground water harvesting sites. The proposed methodology in this study could be adopted in other parts of the world for mapping of paleochannels.

Maintaining a reference background resides at the heart of any video surveillance system. Dynamic background presents impediment in the establishment of an accurate background model for video surveillance. Existing approaches utilize both statistical and non-statistical techniques for maintaining an approximation of the background. Statistical methods are computationally intensive but produce accurate results. Mixture of Gaussians is an efficient adaptive technique for background modeling. Different variants of the techniques are given in literature. In this research study, various novel approaches were proposed and employed for background representation through mixture of Gaussian models. Subtle improvement in foreground detection is reported in some specific cases.

The EONav ship routing service uses near real time observations of ocean surface currents, waves, wind and sea ice conditions, in conjunction with forecasts from numerical weather and ocean models, to plan the optimal route for a vessel. Products from the Copernicus Marine Environment Monitoring Service (CMEMS) and several national weather services are used together with in-house products developed for Synthetic Aperture Radar (SAR) data from satellites such as Sentinel-1, Radarsat-2 and COSMO-SkyMed. A novel data selection algorithm automatically ranks the various data sets and combines them to provide the most reliable met-ocean information. A sail plan optimized e.g. to reduce fuel consumption is determined based on the met-ocean information and is communicated to the ships to assist captains in selecting the best route and speed pattern to their destination.