Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a phenotyping protocol for combined drought and salinity stress at seedling stage in rice

Introduction The case of combined drought and salinity stress is increasingly becoming a constraint to rice production, especially in coastal areas and river deltas where low rainfall not only reduces soil moisture levels but also reduces the flow of river water, resulting in intrusion of saline sea-water. A standardized screening method is needed in order to systematically evaluate rice cultivars under combined drought+salinity at the same time because sequential stress of salinity followed by drought or vice-versa is not similar to simultaneous stress effects. Therefore, we aimed to develop a screening protocol for combined drought+salinity stress applied to soil-grown plants at seedling stage. Methods The study system used 30-L soil-filled boxes, which allowed a comparison of plant growth under control conditions, individual drought and salinity stress, as well as combined drought+salinity. A set of salinity tolerant and drought tolerant cultivars were tested, together with several popular but salinity and drought-susceptible varieties that are grown in regions prone to combined drought+salinity. A range of treatments were tested including different timings of the drought and salinity application, and different severities of stress, in order to determine the most effective that resulted in visible distinction among cultivars. The challenges related to determining a protocol with repeatable seedling stage stress treatment effects while achieving a uniform plant stand are described here. Results The optimized protocol simultaneously applied both stresses by planting into saline soil at 75% of field capacity which was then allowed to undergo progressive drydown. Meanwhile, physiological characterization revealed that chlorophyll fluorescence at seedling stage correlated well with grain yield when drought stress was applied to vegetative stage only. Discussion The drought+salinity protocol developed here can be used for screening rice breeding populations as part of a pipeline to develop new rice varieties with improved adaptation to combined stresses.
A continuous adjoint formulation for hypersonic flows inthermochemical nonequilibrium

This thesis explores the formulation, derivation, and implementation of the continuous adjoint equations for hypersonic, nonequilibrium flow environments. The adjoint method is an efficient means for acquiring sensitivity information that can be used in a gradient-based framework to perform optimal shape design of aerospace systems. A solution to the adjoint system of equations carries a computational cost roughly equal to a single solution of the flow governing equations, regardless of the dimensionality of the design space. When compared to other gradient acquisition methods, where computational costs scale with design space dimensionality, the adjoint method is superior when the dimensionality is high and when solutions to the governing equations are expensive. Such conditions are often representative of most aerospace problems of practical interest. In addition to providing gradient information, solutions to the adjoint equations may be used as `sensors' or `weighting factors' to perform error estimation and adaptive mesh refinement. Hypersonic systems operate in unique flow environments that are dominated by chemical and thermodynamic phenomena not observed at lower Mach numbers. Accurate simulations of these environments require sophisticated thermochemical models to resolve atomic-scale physical processes that have first-order effects on integrated vehicle performance metrics, including lift, drag, stability, controllability, and heat transfer. Because of the computational expense demanded by these high-fidelity tools, the conceptual vehicle design process often relies heavily on low- to medium-fidelity, correlation-based tools that are confined to narrow regions of applicability. As a consequence, the hypersonic vehicle design process has remained relatively static for the past several decades. The adjoint method enables the use of high-fidelity tools early in the design cycle of hypersonic systems, and is a transformative technology for the hypersonic community. This work provides the first derivation, implementation, and verification of the continuous adjoint equations for hypersonic flow environments in thermochemical nonequilibrium. Appropriate boundary conditions and surface sensitivities are provided for both projected force and thermal objective functions for continuum, viscous, multi-component gas mixtures. The adjoint system is implemented in a second-order, unstructured, finite-volume-method (FVM) flow solver that is representative of the state-of-the-art in high-fidelity aerothermodynamic analysis for hypersonic entry systems. Gradients from the adjoint-derived surface sensitivities are verified against gradients calculated using a finite-difference methodology for several representative geometries relevant to ballistic and lifting-body entry vehicles.
The Ads/CFT correspondence for higher spin theories.

The aim of the thesis is to present a check of the Klebanov-Polyakov conjecture that relates the type. A minimal Vasiliev theory in the 4-dimensional Anti-de Sitter space with a theory of N scalar fields with on O(N) global symmetry. The test that is carried out is a comparison of 3-point correlators computed in the 2 sides of the correspondence by means of the ambient space formalism, which makes it possible to use standard Witten diagrams
Role of descemet's stripping without keratoplasty in management of endothelial disease

Purpose of review To summarize recent literature on Descemet's stripping only (DSO) in management of endothelial disease with particular focus on Fuchs endothelial corneal dystrophy (FECD). Recent findings DSO is currently indicated in patients with early FECD, central guttae, and preserved peripheral corneal endothelial cell (CEC) count. Time to corneal clearance may be accelerated and maintained with addition of topical rho-kinase inhibitor (ROCKi). There are reports describing successful use of DSO to treat endothelial disease due to iatrogenic trauma. In patients with transcription factor 4 gene mutation, increased cytosine, thymine, guanine (CTG) triplet repeat load may be associated with DSO failure risk. Emerging pharmacotherapies and cell-suspension treatments may improve procedure effectiveness and expand clinical indications. Summary DSO can be used as the initial surgical treatment in management of symptomatic endothelial disease due to FECD where peripheral CEC function appears preserved. Stand-alone DSO or DSO combined with cataract surgery is effective and postoperative topical ROCKi supplementation will improve time to corneal clearance and CEC count.
Aircraft laser sensing of sound velocity in water: Brillouin scattering

This study shows that it may be feasible using state‐of‐the‐art pulsed lasers, coupled with a novel technique for maintaining laser line stability, to design, construct, and operate an airborne laser system to remotely measure sound velocity in water. This system should be capable of yielding range‐resolved (3‐m bins) sound velocity in water to depths of 75 m to an accuracy of 1 m/s. Flying at aircraft speeds of 300 mi/h and operating at a laser repetition pulse rate of 10 pps, vertical sound profiles would be obtained every 44 ft. Such upper‐ocean high‐vertical‐resolution profiles of sound speed would be useful to various Naval applications. They could serve as stand‐alone data sets or combined with other real time and/or historical data sets to yield improved acoustic and oceanographic prediction models. [Work supported by NOARL. ]
Studies of a Quantum Degenerate Fermionic Lithium Gas

The work described in this thesis can be divided into two parts. The first part is concerned with the production of degenerate Fermi gases and Bose-Fermi mixtures. The second part of the thesis describes studies of strongly interacting spin-mixtures of ultracold fermions. We have cooled a magnetically trapped spin-polarized 6Li Fermi gas into quantum degeneracy by sympathetic cooling with bosonic 23Na. In order to do this, we have converted our previously developed apparatus for Bose-Einstein condensation of 23Na into a two-species cooling facility. We have produced 6Li samples with up to 7 × 107 atoms at temperatures below 0.5TF , and up to 3× 107 atoms at temperatures as low as 0.05TF . Further, we have also produced stable quantum degenerate mixtures of 23Na and 6Li, with several million atoms of each species. In a second set of experiments, we have studied strongly interacting spin-mixtures of 6Li. The strength of interactions was resonantly controlled by applying a magnetic field and tuning to “Feshbach resonances”, which occur when the total energy of the colliding particles coincides with the energy of a bound molecular state. These studies are relevant for the continuing quest for a superfluid transition in a Fermi gas. By studying the inelastic decay of the cloud, we have experimentally identified two Feshbach resonances for the inter-state interactions of the two lowest ground states of 6Li. Most importantly, we found that the lifetime of the strongly interacting system is long enough to observe a superfluid transition in the future. The effects of the coherent collisions in 6Li spin-mixtures were studied using radiofrequency (RF) spectroscopy. We demonstrated the absence of mean field “clock shifts” in a two-state mixture of fermions, and have introduced a three-level method to observe the interaction energy shifts. In the strongly interacting regime, near a Feshbach resonance, we have observed universal behavior of the interaction energy, independent of the value of the scattering length. Finally, we have theoretically studied the effects of Pauli blocking during a free expansion of a degenerate Fermi gas. We have concluded that a strongly interacting normal gas will undergo a hydrodynamic expansion even at zero temperature, due to inefficiency of the Pauli suppression of collisions. Therefore, the already observed hydrodynamic expansion cannot be conclusively interpreted as a signature of superfluidity. Thesis Supervisor: Wolfgang Ketterle Title: John D. MacArthur Professor of Physics
Optimized Active Collision Avoidance Algorithm of Intelligent Vehicles

This research introduces an innovative strategy to impede and lessen lateral and rear-end vehicular collisions by consolidating braking systems with active emergency steering controls. This study puts forward a T-type active emergency steering method, designed to circumvent both lateral and rear-end collisions at vehicular intersections. To secure vehicular stability and condense the time required for steering during the T-type active emergency process, this research formulates a nonlinear dynamic model for the vehicle, in addition to a nonlinear tire model. This study also engages in a thorough analysis of the constraints linked to the initial and terminal states of the steering process. The issue at hand is articulated as an optimization control problem with boundary value restrictions, which is subsequently resolved using the Radau pseudospectral method. Simulation results corroborate that the prompt commencement of the anti-collision strategy can effectively deter potential collisions. This pioneering approach shows considerable promise in augmenting the active safety of intelligent vehicles and bears meaningful implications for high-precision automotive collision evasion systems.
Design and Numerical Study of the Over-Under TBCC Exhaust System

[Abstract] According to the representative working condition of a TBCC (Turbine Based Combined Cycle) engine, an Over-under TBCC exhaust system with twin throats was designed by the MOC( Method of Characteristic), and the flowfield under the different flying conditions of the flight corridor from Ma=0 to Ma=4 , with the mode transition at Mach 2.5 , was numerically studied by the CFD software Fluent. The detailed flowfield structure and the variation of the performance parameters of the over-under TBCC exhaust system, such as the thrust coefficient, lift and the pitch moment, were obtained and analysized. From the result it was shown that during the whole flight corridor, the thrust coefficient of the exhaust system was decreased at first from the take off to the transonic region, where it reached its minimum (it was only 0.21 for Ma =0.9 without the afterburning, and was 0.56 at the same flight Mach number with the afterburning). During the supersonic region, the thrust coefficient of the exhaust system was increased steadily with the flight Mach number was increased. For the flight Mach number reached the mode transition point of Mach 2.5, the performance of the whole exhaust system was rather good, until it reached its maximum at design point Ma=4. The lift and the pitch moment were relatively poor at the subsonic and transonic zone, and they would get better with the Mach number was increased. From the detailed flowfield it was shown that the whole exhaust system was seriously over expanded in the range of subsonic and transonic. Therefore, it was necessary to take some means in order to improve the aerodynamic performance of the Over-under TBCC exhaust system at low Mach number.
Review of retrieval of aerosol optical depth to estimate particle concentration and its challenges based on spatiotemporal relationships by various spectroradiometer models

This review was carried out to understand the retrieval of aerosol optical depth (AOD) datasets for estimating particle concentration and its influence on ambient air and surroundings by various models. Several studies have evaluated particle (PM10 and PM2.5) concentration profiles present in the lowest layers of the atmosphere by using AOD datasets. This study aimed at identifying consistent and precise particle estimation by various datasets retrieved by satellite‐based models for the ground‐level PM concentration. Extremities of satellite sensor data, like specific capabilities, as well as a few drawbacks are presented. Multi‐angle imaging spectroradiometer (MISR), visible infrared imaging radiometer suite (VIIRS) datasets, mixed‐effect model (MEM), and geographically weighted regression (GWR) models outperformed to estimate AOD and PM in comparison with the moderate resolution imaging spectroradiometer (MODIS) and other datasets. The improvised algorithms with higher resolution in the upcoming research would provide an even better estimation for AOD and PM.
Filtering 2D-3D Outliers by Camera Adjustment for Visual Odometry

We study the problem of the discrepancy between model predictions and image measurements in the form of keypoint locations for perspective cameras. In this process, the prediction is made by projecting given 3-D points using the known pose of a calibrated camera. We test whether some small camera pose adjustment exists for each measurement such that the mentioned discrepancy vanishes. Such adjustment would allow us to quantify the effect of each measurement on the camera pose. In this article, we show for the first time that the pose influence assessment of individual measurements can be used to select a subset of the correspondences for accurate 3-D triangulation from two views. We further demonstrate via several experiments that the obtained 3-D points are well suited to the task of absolute localization. When the 3-D points are provided from an anonymized source, the proposed method also selects a suitable subset of 3-D points for accurate localization around an initial guess. The long-term effectiveness of our filtration method is demonstrated by integrating the method within a typical framework of visual odometry (VO). The proposed method is evaluated on ETH3D and EuRoC benchmarks with real-world data. The results indicate that the proposed method outperforms the state-of-the-art methods in terms of the point uncertainty measure and camera pose estimation accuracy.
Histone Deacetylase GiSRT2 Negatively Regulates Flavonoid Biosynthesis in Glycyrrhiza inflata

Glycyrrhiza inflata Batalin is a medicinal licorice species that has been widely used by humans for centuries. Licochalcone A (LCA) is a characteristic flavonoid that accumulates in G. inflata roots with high economical value. However, the biosynthetic pathway and regulatory network of its accumulation remain largely unknown. Here we found that a histone deacetylase (HDAC) inhibitor nicotinamide (NIC) could enhance the accumulation of LCA and total flavonoids in G. inflata seedlings. GiSRT2, a NIC-targeted HDAC was functionally analyzed and its RNAi transgenic hairy roots accumulated much more LCA and total flavonoids than its OE lines and the controls, indicating a negative regulatory role of GiSRT2 in the accumulation of LCA and total flavonoids. Co-analysis of transcriptome and metabolome of RNAi-GiSRT2 lines revealed potential mechanisms in this process. An O-methyltransferase gene, GiLMT1 was up-regulated in RNAi-GiSRT2 lines and the encoded enzyme catalyzed an intermediate step in LCA biosynthesis pathway. Transgenic hairy roots of GiLMT1 proved that GiLMT1 is required for LCA accumulation. Together, this work highlights the critical role of GiSRT2 in the regulation of flavonoid biosynthesis and identifies GiLMT1 as a candidate gene for the biosynthesis of LCA with synthetic biology approaches.
Using Assurance Cases to assure the fulfillment of non-functional requirements of AI-based systems - Lessons learned

While AI as a cross-sector technology is applied to more and more use cases and contexts, concerns and questions about the impact of this use on the people involved and society as a whole are increasing. Many companies want to act on these concerns and put a high emphasize on the ethical and fair use of AI in their use cases. But up to date easily applicable methods to translate ethical values, such as fairness, into technical specifications are often missing. One method to do so previously described in literature is the development of an Assurance Case. An Assurance Case presents the argument structure of how a claim ("The system is fair") can be substantiated by evidences like tests. To test the application of the method for fairness requirements in the real world and derive important insights for future use, the method was tested with the real life use case of a software product, which assigns positions in the training of doctors in hospitals.By testing the method in a real life setting, it was possible to develop it further and both, increase its usability and facilitate the focus on ethical aspects such as fairness.Fundamental questions were: Can the method of Assurance Cases be used to enhance fairness of an AI system? What is the application like in an industry context? How can one improve the method of Assurance Cases to be applicable for the assessment of fairness in AI systems? Together with developers, software and domain experts as well as AI and Open Innovation experts and researchers, the method was applied to the use case of an industry partner.Key insights are that the developed Assurance Case is of great help to the industry partner, especially when thinking about future adaptions, communication and potential regulations or required evidences to support their claim of a fair system. Based on the insights derived from testing the process, the method can be improved, enabling it to be applied more efficiently on future use cases and thus enhancing the fairness of AI systems in the long term.Based on our experience, we consider the Assurance Case framework to be helpful and useful to be able to assure fairness of AI systems.
The MCLIB library: Monte Carlo simulation of neutron scattering instruments

Monte Carlo is a method to integrate over a large number of variables. Random numbers are used to select a value for each variable, and the integrand is evaluated. The process is repeated a large number of times and the resulting values are averaged. For a neutron transport problem, first select a neutron from the source distribution, and project it through the instrument using either deterministic or probabilistic algorithms to describe its interaction whenever it hits something, and then (if it hits the detector) tally it in a histogram representing where and when it was detected. This is intended to simulate the process of running an actual experiment (but it is much slower). This report describes the philosophy and structure of MCLIB, a Fortran library of Monte Carlo subroutines which has been developed for design of neutron scattering instruments. A pair of programs (LQDGEOM and MC{_}RUN) which use the library are shown as an example.
Revealing Social Group Long-Term Survival for Smart Cities Based on Behavior Graph Structures Using Virtual Game

With the transformation of human life into virtual worlds based on the reality, current researches of smart cities and sustainability should integrate the factors of virtual social behaviors. Virtual games are an ideal domain and tools for exploring social science. Therefore, our work innovatively using Nova Empire as a case study to reveal the social group long-term survival via complexity analysis of behavior graph structural properties for building smart cities. Specifically, behavioral data of 101424 players and 5324 alliances from September 2021 to February 2022 are used. Our observations show that the phenomenon of “gap of wealth” in real society also exists in the virtual game. Meanwhile, the player online time is significantly positive related to alliance survival time, which is the foundation of our work. Then, correlation and regression analysis are performed to understand the significance of different structural properties on alliance survival time. Our original findings demonstrate that larger alliance, more subgroups, balanced player distribution, and frequent behavioral interactions will promote long-term survival of the alliance. Small subgroup and a relaxed social environment can improve player online time. Furthermore, we transfer the conclusions from virtual game to real society based on the mapping principle. Finally, new virtual tools and solutions for policymakers to improve smart cities and sustainable society ecosystem, and operation strategies for game designers to improve players retention rate are proposed.
High resolution image reconstruction method for a double-plane PET system with changeable spacing

Breast-dedicated positron emission tomography (PET) imaging techniques have been developed in recent years. Their capacities to detect millimeter-sized breast tumors have been the subject of many studies. Some of them have been confirmed with good results in clinical applications. With regard to biopsy application, a double-plane detector arrangement is practicable, as it offers the convenience of breast immobilization. However, the serious blurring effect of the double-plane PET, with changeable spacing for different breast sizes, should be studied. We investigated a high resolution reconstruction method applicable for a double-plane PET. The distance between the detector planes is changeable. Geometric and blurring components were calculated in real-time for different detector distances, and accurate geometric sensitivity was obtained with a new tube area model. Resolution recovery was achieved by estimating blurring effects derived from simulated single gamma response information. The results showed that the new geometric modeling gave a more finite and smooth sensitivity weight in the double-plane PET. The blurring component yielded contrast recovery levels that could not be reached without blurring modeling, and improved visual recovery of the smallest spheres and better delineation of the structures in the reconstructed images were achieved with the blurring component. Statistical noise had lower variance at the voxel level with blurring modeling at matched resolution, compared to without blurring modeling. In distance-changeable double-plane PET, finite resolution modeling during reconstruction achieved resolution recovery, without noise amplification.