Simulations of extensional flow in microrheometric devices

We present a detailed numerical study of the flow of a Newtonian fluid through microrheometric devices featuring a sudden contraction–expansion. This flow configuration is typically used to generate extensional deformations and high strain rates. The excess pressure drop resulting from the converging and diverging flow is an important dynamic measure to quantify if the device is intended to be used as a microfluidic extensional rheometer. To explore this idea, we examine the effect of the contraction length, aspect ratio and Reynolds number on the flow kinematics and resulting pressure field. Analysis of the computed velocity and pressure fields show that, for typical experimental conditions used in microfluidic devices, the steady flow is highly three-dimensional with open spiraling vortical structures in the stagnant corner regions. The numerical simulations of the local kinematics and global pressure drop are in good agreement with experimental results. The device aspect ratio is shown to have a strong impact on the flow and consequently on the excess pressure drop, which is quantified in terms of the dimensionless Couette and Bagley correction factors. We suggest an approach for calculating the Bagley correction which may be especially appropriate for planar microchannels

Inverse problems for Sturm-Liouville equations with boundary conditions linearly dependent on the spectral parameter from partial information

[[abstract]]Abstract.In this paper, we study the inverse spectral problems for Sturm–Liouville equations with boundary conditions linearly dependent on the spectral parameter and show that the potential of such problem can be uniquely determined from partial information on the potential and parts of two spectra, or alternatively, from partial information on the potential and a subset of pairs of eigenvalues and the normalization constants of the corresponding eigenvalues.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]紙本[[booktype]]電子版[[countrycodes]]DE

Predictors of long-term memory and network connectivity 10 years after anterior temporal lobe resection.

OBJECTIVE Anterior temporal lobe resection (ATLR) effectively controls seizures in medically refractory temporal lobe epilepsy but risks significant episodic memory decline. Beyond 1 year postoperatively, the influence of preoperative clinical factors on episodic memory and long-term network plasticity remain underexplored. Ten years post-ATLR, we aimed to determine biomarkers of successful memory network reorganization and establish presurgical features' lasting impact on memory function. METHODS Twenty-five ATLR patients (12 left-sided) and 10 healthy controls underwent a memory-encoding functional magnetic resonance imaging paradigm alongside neuropsychometry 10 years postsurgery. Generalized psychophysiological interaction analyses modeled network functional connectivity of words/faces remembered, seeding from the medial temporal lobes (MTLs). Differences in successful memory connectivity were assessed between controls and left/right ATLR. Multivariate regressions and mixed-effect models probed preoperative phenotypes' effects on long-term memory outcomes. RESULTS Ten years post-ATLR, lower baseline functioning (verbal and performance intelligence quotient) and a focal memory impairment preoperatively predicted worse long-term memory outcomes. Poorer verbal memory was significantly associated with longer epilepsy duration and earlier onset age. Relative to controls, successful word and face encoding involved increased functional connectivity from both or remnant MTL seeds and contralesional parahippocampus/hippocampus after left/right ATLR. Irrespective of surgical laterality, successful memory encoding correlated with increased MTL-seeded connectivity to frontal (bilateral insula, right anterior cingulate), right parahippocampal, and bilateral fusiform gyri. Ten years postsurgery, better memory performance was correlated with contralateral frontal plasticity, which was disrupted with longer epilepsy duration. SIGNIFICANCE Our findings underscore the enduring nature of functional network reorganizations to provide long-term cognitive support. Ten years post-ATLR, successful memory formation featured stronger connections near resected areas and contralateral regions. Preoperative network disruption possibly influenced effectiveness of postoperative plasticity. These findings are crucial for enhancing long-term memory prediction and strategies for lasting memory rehabilitation

Thalamostriatal disconnection underpins long-term seizure freedom in frontal lobe epilepsy surgery

Around 50% of patients undergoing frontal lobe surgery for focal drug-resistant epilepsy become seizure free post-operatively; however, only about 30% of patients remain seizure free in the long-term. Early seizure recurrence is likely to be caused by partial resection of the epileptogenic lesion, whilst delayed seizure recurrence can occur even if the epileptogenic lesion has been completely excised. This suggests a coexistent epileptogenic network facilitating ictogenesis in close or distant dormant epileptic foci. As thalamic and striatal dysregulation can support epileptogenesis and disconnection of cortico-thalamostriatal pathways through hemispherotomy or neuromodulation can improve seizure outcome regardless of focality, we hypothesize that projections from the striatum and the thalamus to the cortex may contribute to this common epileptogenic network. To this end, we retrospectively reviewed a series of 47 consecutive individuals who underwent surgery for drug-resistant frontal lobe epilepsy. We performed voxel-based and tractography disconnectome analyses to investigate shared patterns of disconnection associated with long-term seizure freedom. Seizure freedom after 3 and 5 years was independently associated with disconnection of the anterior thalamic radiation and anterior cortico-striatal projections. This was also confirmed in a subgroup of 29 patients with complete resections, suggesting these pathways may play a critical role in supporting the development of novel epileptic networks. Our study indicates that network dysfunction in frontal lobe epilepsy may extend beyond the resection and putative epileptogenic zone. This may be critical in the pathogenesis of delayed seizure recurrence as thalamic and striatal networks may promote epileptogenesis and disconnection may underpin long-term seizure freedom

Optical types of inland and coastal waters

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in‐water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions

Hyperbolic contraction measuring systems for extensional flow

In this paper an experimental method for extensional measurements on medium viscosity fluids in contraction flow is evaluated through numerical simulations and experimental measurements. This measuring technique measures the pressure drop over a hyperbolic contraction, caused by fluid extension and fluid shear, where the extensional component is assumed to dominate. The present evaluative work advances our previous studies on this experimental method by introducing several contraction ratios and addressing different constitutive models of varying shear and extensional response. The constitutive models included are those of the constant viscosity Oldroyd-B and FENE-CR models, and the shear-thinning LPTT model. Examining the results, the impact of shear and first normal stress difference on the measured pressure drop are studied through numerical pressure drop predictions. In addition, stream function patterns are investigated to detect vortex development and influence of contraction ratio. The numerical predictions are further related to experimental measurements for the flow through a 15:1 contraction ratio with three different test fluids. The measured pressure drops are observed to exhibit the same trends as predicted in the numerical simulations, offering close correlation and tight predictive windows for experimental data capture. This result has demonstrated that the hyperbolic contraction flow is well able to detect such elastic fluid properties and that this is matched by numerical predictions in evaluation of their flow response. The hyperbolical contraction flow technique is commended for its distinct benefits: it is straightforward and simple to perform, the Hencky strain can be set by changing contraction ratio, non-homogeneous fluids can be tested, and one can directly determine the degree of elastic fluid behaviour. Based on matching of viscometric extensional viscosity response for FENE-CR and LPTT models, a decline is predicted in pressure drop for the shear-thinning LPTT model. This would indicate a modest impact of shear in the flow since such a pressure drop decline is relatively small. It is particularly noteworthy that the increase in pressure drop gathered from the experimental measurements is relatively high despite the low Deborah number range explored

Phytoplankton composition from sPACE: Requirements, opportunities, and challenges

Ocean color satellites have provided a synoptic view of global phytoplankton for over 25 years through near surface measurements of the concentration of chlorophyll a. While remote sensing of ocean color has revolutionized our understanding of phytoplankton and their role in the oceanic and freshwater ecosystems, it is important to consider both total phytoplankton biomass and changes in phytoplankton community composition in order to fully understand the dynamics of the aquatic ecosystems. With the upcoming launch of NASA\u27s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission, we will be entering into a new era of global hyperspectral data, and with it, increased capabilities to monitor phytoplankton diversity from space. In this paper, we analyze the needs of the user community, review existing approaches for detecting phytoplankton community composition in situ and from space, and highlight the benefits that the PACE mission will bring. Using this three-pronged approach, we highlight the challenges and gaps to be addressed by the community going forward, while offering a vision of what global phytoplankton community composition will look like through the “eyes” of PACE

Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (acdom(440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and acdom(440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and acdom(440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and acdom(440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model

Identification of alleles of carotenoid pathway genes important for zeaxanthin accumulation in potato tubers

We have investigated the genetics and molecular biology of orange flesh colour in potato (Solanum tuberosum L.). To this end the natural diversity in three genes of the carotenoid pathway was assessed by SNP analyses. Association analysis was performed between SNP haplotypes and flesh colour phenotypes in diploid and tetraploid potato genotypes. We observed that among eleven beta-carotene hydroxylase 2 (Chy2) alleles only one dominant allele has a major effect, changing white into yellow flesh colour. In contrast, none of the lycopene epsilon cyclase (Lcye) alleles seemed to have a large effect on flesh colour. Analysis of zeaxanthin epoxidase (Zep) alleles showed that all (diploid) genotypes with orange tuber flesh were homozygous for one specific Zep allele. This Zep allele showed a reduced level of expression. The complete genomic sequence of the recessive Zep allele, including the promoter, was determined, and compared with the sequence of other Zep alleles. The most striking difference was the presence of a non-LTR retrotransposon sequence in intron 1 of the recessive Zep allele, which was absent in all other Zep alleles investigated. We hypothesise that the presence of this large sequence in intron 1 caused the lower expression level, resulting in reduced Zep activity and accumulation of zeaxanthin. Only genotypes combining presence of the dominant Chy2 allele with homozygosity for the recessive Zep allele produced orange-fleshed tubers that accumulated large amounts of zeaxanthin