Miracle-dz/UniFAR-FTUs huggingface dataset:
Batchelor Prize Lecture: Measurements in wall-bounded turbulence

Abstract Our understanding of turbulent boundary layer scaling and structure has advanced greatly in the past 20 to 30 years. On the computational side, direct numerical simulations and large-eddy simulations have made extraordinary contributions as numerical methods and computational resources have advanced, while on the experimental side major advances in instrumentation have made available new imaging and quantitative techniques that provide unprecedented accuracy and detail. Here, I illustrate how the development of such experimental methods have aided our progress by reference to some particular topics related to the structure of turbulent boundary layers: the power law scaling of the mean velocity and its relationship to the mesolayer; the scaling of the outer layer with regard to the log law in turbulence; the development of the outer peak; and the scaling of the turbulent stresses in the near-wall region, with an emphasis on the streamwise component.
Assessment of the Impact of Women Development Programmes of the Technology Transfer and Extension Adminstration of Khartoum State: Case Study of Eldrushab Center

This study is designed to assess the impact of the women development programmes operated by the Technology Transfer and Extension Administration of Khartoum State. Eldrushab center for women development programmes was selected as a case study. The specific objectives of this study are to assess the impact of women development programmes on awareness of trained women. Also to know to what extent women have benefited from training programmes, and the effects of training on their lives, and to study the financing problems and other constrains that were faced by trained women. The study used primary data collected through questionnaires and direct observations plus secondary data from references, researches, reports, websites and records of the Ministry of Agriculture. The survey was conducted during the period June-July, 2005. Frequency distribution, percentages and correlation analysis were used to test the hypothesis of the study. The study concluded that women had benefited from the training courses and gained new skills in income generating activities. After training courses, most of women established small projects and there were positive changes in the educational level, nutritional level and standard of living in their families. Also women had benefited from the symposium and visits during the training courses period. The awareness and knowledge of women increased through lectures, visits, symposiums and other activities. Trained women facing many problems, those problems are lack of training materials and access to finance. The study recommends that the number of female extension officers should be increased in the different centers, and that small markets for women should be established in the different localities to ease the marketing of their products. Recommended also by the study is adequate provision of the materials needed for the different training courses. Also the coordination with banks and organizations to finance small projects of trained women is strongly recommended.
Improving Atom–Mirror Entanglement and Mechanical Squeezing in a Modulated Optomechanical System

In this paper, the macroscopic quantum entanglement and squeezing in an unresolved‐sideband atom‐optomechanical system with a modulated optical parametric amplifier (OPA) inside the cavity are studied. Increasing the parametric gain of the OPA, the quantum‐classical correspondence between the atom‐mirror entanglement and classical nonlinear dynamics can be found. The critical point where the system experiences the transition from periodic oscillation to period‐doubling motion can be characterized by the singularity of the atom–mirror entanglement. Furthermore, the dependence of the atom–mirror entanglement and mechanical squeezing on the detuning and the parametric gain of the OPA as well as the environment temperature are investigated in detail. It is found that the atom‐mirror entanglement can be enhanced and the mechanical squeezing can be generated by modulating the OPA.
Subthreshold reference circuit with curvature compensation based on the channel length modulation of MOS devices

A subthreshold nano‐power voltage and current reference with high‐order temperature compensation is proposed by taking advantage of the channel length modulation of MOS devices. Curvature compensation is implemented by providing proper compensating drain‐source voltages for the core devices of a first‐order CMOS reference such that the output nonlinear temperature factors can be compensated over a wide temperature range. In‐depth mathematical analysis is carried out to model the temperature dependency of the reference signals before and after compensation. As part of the analysis, Taylor expansion of the threshold voltage of MOS devices has been evaluated in a generalized fashion, enabling to clarify the complicated relationship between the high‐order temperature‐related terms of the output and design parameters. Simulated in a standard 0.18‐μm CMOS process, the minimum supply voltage of a proof‐of‐concept design is 1.0 V, providing 345 mV voltage reference with minimum temperature coefficient (TC) of 2.0 ppm/°C across the range of –40–140°C. The active area is 0.45 mm2 with around 200 nA current consumption. The DC line regulation is 0.23%/V, and the power supply rejection ratio (PSRR) is −63 dB at 10 Hz.
Influence of ambient day light variations and age on the Iris-pupillary area ratio in beef cattle

Introduction Iris-pupillary area ratio (IPR) is an objective and non-invasive index of autonomic nervous system activity and stress, which can be confounded by light intensity or age of an individual. Evaluating the influence of ambient light intensity variations or age on IPR is necessary to improve the validity of IPR for its clinical application in objective assessment of welfare and stress. Materials and Methods In this study we evaluated the influence of ambient light intensity variations and age on IPR in beef cattle breeds (Limousin, Belgian Blue and Charolais) and analysed the data using correlation statistics. Results The correlation between the light intensity (20 to 500 lux; r = 0.22, p = 0.08) or age (10 to 145 months, r = 0.20, p = 0.12) and IPR was weak and statistically not significant. A sub-group analysis assessing the influence of gender on correlation between the light intensity and IPR also was not statistically significant. Conclusion Our results suggest that within the ambient light intensity (20 to 500 lux) and age (10 to 145 months) the variation in IPR is minimal. Hence our results validate the merit of IPR in objectively measuring autonomic activity/stress and demonstrate the practicality of using IPR for welfare assessment under ambient light conditions in wider age cohorts of beef cattle.
Normative sleep spindle database and findings from 772 healthy children from birth through 18 years

Work in the last two decades has identified sleep spindles, discrete “sigma band” oscillations during stage 2 sleep, as a key oscillatory mechanism required for off-line memory consolidation. Although, sleep spindles are known to evolve concomitant with brain maturation and reflect cognitive function across the lifespan, the details of this developmental trajectory are unknown. To address this, we curated a database of sleep electroencephalograms from 772 developmentally normal children to characterize spindles from birth through 18 years. After validating an automated spindle detector against ~20,000 hand-marked spindles across ages, we demonstrate that sleep spindle features follow distinct age-specific patterns in distribution, rate, duration, frequency, estimated refractory period, and inter-hemispheric spindle lag. These data expand our current knowledge of normal physiological brain development and provide a large normative database to detect deviations in sleep spindles to aid discovery, biomarker development, and diagnosis in pediatric neurodevelopmental disorders.
Imaging optically thick tissues simply and reproducibly: a practical guide to Lightsheet Macroscopy

Lightsheet microscopy offers an ideal method for imaging of large (mm-cm scale) biological tissues rendered transparent via optical clearing protocols. However the diversity of clearing technologies and tissue types, and how these are adapted to the microscope can make tissue mounting glitchy and somewhat irreproducible. Tissue preparation for imaging can involve glues and or equilibration in a variety of expensive and/or proprietary formulations. Here we present practical advice for mounting and capping cleared tissues in optical cuvettes for macroscopic imaging, providing a standardized 3D cell that can be imaged routinely and relatively inexpensively. We show that acrylic cuvettes should be non-aberrating with objective numerical apertures less than 0.65, and present an inexpensive tool for alignment and calibration of standard lightsheet parameters. Mouse embryo, liver and heart imaging are demonstrated as examples with practical recommendations for acquisition and post-processing.
Dual pathway architecture underlying vocal learning in songbirds

Song acquisition and production in songbirds is governed by a dedicated neural circuitry that involves two parallel pathways: a motor pathway for the production and a basal ganglia (BG) pathway for the acquisition. Juveniles learn by imitating adult vocalizations and proceed by trial and error, errors being conveyed by a dopaminergic signal. The complex nature of the relationship between neural control and syrinx musculature makes song learning a complicated problem to solve. Reinforcement learning (RL) has been widely hypothesized to underlie such sensorimotor learning even though this can lead to sub-optimal solutions under uneven contours in continuous action spaces. In this article, we propose to re-interpret the role of a dual pathway architecture, underlying avian vocal learning, that helps overcome these limitations. We posit that the BG pathway conducts exploration by inducing large daily shifts in the vocal production while the motor pathway gradually consolidates this exploration. This process can be understood as a modified form of a simulated annealing process. Simulations on Gaussian performance landscapes and a syrinx-based performance landscape are demonstrated and compared with standard approaches. Taking behavioral constraints into account (60 days of learning, 1000 trials per day), the model allows to reach the global optimum in complex landscapes and thus provides a sound insight into the role of the dual pathway architecture underlying vocal learning.
Hybrid model of arm for analysis of regional blood oxygenation in non-invasive optical diagnostics

The paper presents a new comprehensive approach to modeling and analysis of processes occurring during the blood flow in the arm‟s small vessels as well as non-invasive measurement method of mixed venous oxygen saturation. During the work, a meta-analysis of available physiological data was performed and based on its result a hybrid model of forearm vascular tree was proposed. The model, in its structure, takes into account a classical nonlinear hydro-electric analogy in conjunction with light-tissue interaction. Several geometries of arm vascular tree obtained from magnetic resonance angiography (MRA) image were analyzed which allowed to proposed the structure of electrical analog network. Proposed model allows to simulate the behavior of forearm blood flow from the vascular tree mechanics point of view, as well as effects of the impact of cuff and vessel wall mechanics on the recorded photoplethysmographic signals. In particular, it allows to analyze the reaction and anatomical effects in small vessels and microcirculation caused by occlusive maneuver in selected techniques, what was of particular interest to authors and motivation to undertake research in this area. Preliminary studies using proposed model showed that inappropriate selection of occlusion maneuver parameters (e.g. occlusion time, cuff pressure etc.), cause dangerous turbulence of blood flow in the venous section of the vascular tree.
Shedding Light on the Black Box of a Neural Network Used to Detect Prostate Cancer in Whole Slide Images by Occlusion-Based Explainability

Diagnostic histopathology is facing increasing demands due to aging populations and expanding healthcare programs. Semi-automated diagnostic systems employing deep learning methods are one approach to alleviate this pressure, with promising results for many routine diagnostic procedures. However, one major issue with deep learning approaches is their lack of interpretability—after adequate training they perform their assigned tasks admirably, but do not explain how they reach their conclusions. Knowledge of how a given method performs its task with high sensitivity and specificity would be advantageous to understand the key features responsible for diagnosis, and should in turn allow fine-tuning of deep learning approaches. This paper presents a deep learning-based system for carcinoma detection in whole slide images of prostate core biopsies, achieving state-of-the-art performance; 100% area under curve and sensitivity of 0.978 for 8 detected false positives on average per slide. Furthermore, we investigated various methods to extract the key features used by the neural network for classification. Of these, the technique called occlusion, adapted to whole slide images, analyzes the sensitivity of the detection system to changes in the input images. This technique produces heatmaps indicating which parts of the image have the strongest impact on the system’s output that a histopathologist can examine to identify the network’s reasoning behind a given classification. Reassuringly, the heatmaps identified several prevailing histomorphological features characterizing carcinoma, e.g. single-layered epithelium, presence of small lumina, and hyperchromatic nuclei with halos. A convincing finding was the recognition of their mimickers in non-neoplastic tissue. The results show that the neural network approach to recognize prostatic cancer is similar to that taken by a human pathologist at medium optical resolution. The use of explain-ability heatmaps provides added value for automated digital pathology to analyze and fine-tune deep learning systems, and improves trust in computer-based decisions.
Bladder cancer organoids as a functional system to model different disease stages and therapy response

Bladder Cancer (BLCa) inter-patient heterogeneity is the primary cause of treatment failure, suggesting that patients could benefit from a more personalized treatment approach. Patient-derived organoids (PDOs) have been successfully used as a functional model for predicting drug response in different cancers. In our study, we establish PDO cultures from different BLCa stages and grades. PDOs preserve the histological and molecular heterogeneity of the parental tumors, including their multiclonal genetic landscapes, and consistently share key genetic alterations, mirroring tumor evolution in longitudinal sampling. Our drug screening pipeline is implemented using PDOs, testing standard-of-care and FDA-approved compounds for other tumors. Integrative analysis of drug response profiles with matched PDO genomic analysis is used to determine enrichment thresholds for candidate markers of therapy response and resistance. Finally, by assessing the clinical history of longitudinally sampled cases, we can determine whether the disease clonal evolution matched with drug response. Bladder cancer heterogeneity can limit treatment efficacy in individual patients. Here, the authors use patient derived organoids to develop a drug screening pipeline and identify markers of treatment response.
Surface curvature and basal hydraulic stress induce spatial bias in cell extrusion

Epithelial cell extrusion is employed in maintaining a healthy epithelium. It remains unclear how environmental conditions specific to various epithelial tissues, such as geometry and fluid osmolarity, affect cell extrusions. We found that, over curved surfaces, epithelial monolayers exhibited higher extrusion rates in concave regions than convex ones. This difference, and overall extrusions, decreased when osmotically induced basal hydraulic stress was reduced by increasing media osmolarity or by culturing monolayers on hydrogels. Mechanistically, basal fluid accumulation antagonized cell-substrate adhesions and the subsequent FAK-Akt survival pathway, leading to apoptotic cell death. Convex surfaces induced cellular forces that acted against osmosis, thereby promoting adhesions and lowering apoptosis. This effect was reversed in concave regions, and together, resulted in the curvature induced spatial bias in cell extrusions. One-Sentence Summary Curvature induces forces in cell-sheets that act against/with osmosis to reduce/elevate fluid stress driven cell extrusions.
Endo-lysosomal assembly variations among human leukocyte antigen class I (HLA class I) allotypes

The extreme polymorphisms of HLA-I proteins enable the presentation of diverse peptides to cytotoxic T lymphocytes (CTL). The canonical endoplasmic reticulum (ER) HLA-I assembly pathway enables presentation of cytosolic peptides, but effective intracellular surveillance requires multi-compartmental antigen sampling. Endo-lysosomes are generally sites of HLA class II assembly, but human monocytes and monocyte-derived dendritic cells (moDCs) also contain significant reserves of endo-lysosomal HLA-I molecules. We hypothesized variable influences of HLA-I polymorphisms upon outcomes of endo-lysosomal trafficking, as the stabilities and peptide occupancies of cell surface HLA-I are variable. For example, in moDCs, compared with HLA-B*08:01, HLA-B*35:01 displays reduced cell-surface stability and greater receptivity to exogenous peptide. Perturbations of endo-lysosomal pH negatively affect the surface expression of moDC HLA-B*35:01 but not HLA-B*08:01, causing HLA-B*35:01 accumulation in LAMP1+ compartments. These findings reveal the intersection of the vacuolar cross-presentation pathway with a constitutive assembly pathway for HLA-B*35:01. Notably, cross-presentation of epitopes derived from two soluble antigens was also more efficient for B*35:01 compared to B*08:01, even when matched for T cell response sensitivity, and more affected by cathepsin inhibition. Thus, HLA-I polymorphisms dictate the degree of endo-lysosomal assembly, which can supplement ER assembly for constitutive HLA-I expression and increase the efficiency of cross-presentation.
Padé SSA: A frequency domain method for estimating the dynamics of stochastic reaction networks

Dynamic analysis and control of living cells relies on mathematical representations of cellular processes that are themselves modelled as biomolecular reaction networks. Stochastic models for biomolecular reaction networks are commonly employed for analysing intracellular networks having constituent species with low-copy numbers. In such models, the main object of interest is the probability distribution of the state vector of molecular counts which evolves according to a set of ordinary differential equations (ODEs) called the Chemical Master Equation (CME). Typically this set is very large or even infinite, making the CME practically unsolvable in most cases. Hence the outputs based on the CME solution, like the statistical moments of various state components, are generally estimated with Monte Carlo (MC) procedures by simulating the underlying Markov chain with Gillespie’s Stochastic Simulation Algorithm (SSA). However to obtain statistical reliability of the MC estimators, often a large number of simulated trajectories are required, which imposes an exorbitant computational burden. The aim of this paper is to present a frequency domain method for mitigating this burden by exploiting a small number of simulated trajectories to robustly estimate certain intrinsic eigenvalues of the stochastic dynamics. This method enables reliable estimation of time-varying outputs of interest from a small number of sampled trajectories and this estimation can be carried out for several initial states without requiring additional simulations. We demonstrate our method with a couple of examples.
A retrospective and stepwise learning strategy revealed by neuronal activity in the basal forebrain

Associative learning is a fundamental cognitive capacity that allows animals and humans to learn the predictive relationship between behavioral events and rewarding outcomes. While the process of learning is commonly conceptualized as a prospective strategy (learning how behavioral events predict future rewards), here we provide behavioral and neurophysiological evidence to show that animals may instead employ a retrospective and stepwise learning strategy (learning how the reward is predicted by preceding behavioral events). In rats learning a new association in which the reward was paired with a sequence of behavioral events, learning started from the event closest to the reward and sequentially incorporated earlier events into animals’ internal model. The learning of each behavioral event as a new reward predictor was accompanied by the emergence of basal forebrain (BF) neuronal responses toward that event. BF activities quantitatively conveyed a reward prediction error signal associated with the behavioral event, and promoted reward-seeking behavioral sequences containing the newly learned event. As the internal model incorporated more behavioral events as reward predictors, non-rewarded behavioral sequences that were once compatible with the internal model during early stages of learning became incompatible and were sequentially eliminated. Together, these results demonstrate how the retrospective and stepwise learning strategy can effectively establish animals’ internal model during the learning process and lead to the sequential refinement of reward-seeking behaviors. These results also highlight the functional significance of BF neuronal activities, which provided unique insights into the covert dynamics of the learning process in single trials.
Effect of tempol on post-thaw semen parameters and fertility during chicken semen cryopreservation

The present study evaluated addition of tempol during chicken semen cryopreservation on post-thaw semen parameters and fertility. Adult PD-1 line semen was cryopreserved using 4% dimethyl sulfoxide (DMSO) in Sasaki diluent (SD). In the semen cryomixture tempol (1 and 5 mM) was added at final concentrations. The semen with additives were filled in 0.5 ml French straws and exposed to liquid nitrogen vapours for 30 min and then stored in liquid nitrogen. The semen straw was thawed at 5°C for 100 sec and evaluated for sperm motility, live, abnormal and acrosome intact sperm. The seminal plasma was evaluated for lipid peroxidation. Fertilizing potential of the cryopreserved sperm was evaluated after insemination in the PD-1 line hens. The post-thaw sperm parameters were significantly (P<0.05) lower in the cryopreserved groups. The lipid peroxidation was significantly (P<0.05) higher in cryopreserved groups. The fertility was significantly (P<0.05) lower in all the cryopreserved groups. In conclusion, addition of tempol to cryopreservation mixture did not improve the post-thaw semen parameters or fertility.