Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensitivity of Arctic climate simulations to different boundary-layer parameterizations in a regional climate model

Arctic climate simulations with the high resolution regional climate model HIRHAM showsome deviations from station data in the planetary boundary layer (PBL) during winter, whichindicates the necessity of improvements in the atmospheric PBL parameterization for a betterdescription of the vertical stratification and atmosphere–surface energy exchange. A1-dimensional single column model scheme has been used to investigate the influence of twodifferent PBL parameterizations in monthly integrations for January 1991 and July 1990. Thefirst scheme uses the boundary layer parameterization of the atmospheric circulation modelECHAM3, including the Monin–Obukhov similarity theory in the surface layer and a mixinglength approach above. The second scheme applies the Rossby-number similarity theory forthe whole PBL, connecting external parameters with turbulent fluxes and with universal functionsdetermined on the basis of Arctic data. For both schemes the heat and humidity advectionhas been determined as residual term of the PBL balance equations. Diabatic sources havebeen computed from the current model solution and local temperature and humidity changesare estimated from radiosonde data. The simulated vertical structure and the atmosphere–surface energy exchange during January strongly depends on the used PBL parameterizationscheme. These different PBL parameterization schemes were then applied for simulations of theArctic climate in the 3-dimensional regional atmospheric climate model HIRHAM, usingECHAM3 with Monin–Obukhov similarity theory, ECHAM3 with Rossby-number similaritytheory and ECHAM4 parameterizations with a turbulent kinetic energy closure. The nearsurface temperature, the large-scale fields of geopotential and horizontal wind are simulatedsatisfactorily by all three schemes, but strong regional differences occur. The results show asensitivity to the type of turbulence exchange scheme used. The comparison with ECMWFanalyses and with radiosonde data reveals that during January ECHAM3 with Rossby numbersimilarity theory more succesfully simulates the cold and stable PBL over land surfaces, whereasover the open ocean ECHAM3 with Monin Obukhov similarity works better. ECHAM3 withRossby-number similarity theory delivers a better adapted vertical heat exchange under stableArctic conditions and reduces the cold bias at the surface. The monthly mean surface turbulentheat flux distribution strongly depends on the use of different PBL parameterizations and leadsto different Arctic climate structures throughout the atmosphere with the strongest changes atthe ice edge for January.
Graphical Regular Representations of Non-Abelian Groups, I

In this paper, all groups and graphs considered are finite and all graphs are simple (in the sense of Tutte [8, p. 50]). If X is such a graph with vertex set V(X) and automorphism group A(X), we say that X is a graphical regular representation (GRR) of a given abstract group G if (I) G ≅ A(X) , and (II) A(X) acts on V(X) as a regular permutation group; that is, given u, v ∈ V(X), there exists a unique φ ∈ A(X) for which φ(u) = v. That for any abstract group G there exists a graph X satisfying (I) is well-known (cf. [3]).
Origin of Neutrino Mass

There are strong indications that charged fermions masses have origin in the Higgs mechanism. We review here attempts that provide the same source for neutrino mass. If one sticks to simple scenarios, the type II seesaw comes closest to achieving this, whereas if one looks for more complete theories the minimal LR symmetric model stands out as the theory that led originally to neutrino mass, the seesaw mechanism and the lepton number violation at hadronic colliders. These historical developments are deeply connected with the neutrinoless double beta decay and a plethora of low energy lepton number and flavor violating processes. Moreover, the theory offers a potential LHC probe of the Higgs origin of neutrino mass in analogy with charged fermions. We offer here a short review of these issues. The examples of other well motivated theories are the MSSM and the minimal extension of the minimal SU(5) grand unified theory, discussed en passant.
1400 W, a selective inducible nitric oxide synthase inhibitor, mitigates early neuroinflammation and nitrooxidative stress in diisopropylfluorophosphate-induced short-term neurotoxicity rat model

Organophosphate nerve agent (OPNA) exposure induces acute and long-term neurological deficits. OPNA exposure at sub-lethal concentrations induces irreversible inhibition of acetylcholinesterase and cholinergic toxidrome and develops status epilepticus (SE). Persistent seizures have been associated with increased production of ROS/RNS, neuroinflammation, and neurodegeneration. A total of 1400W is a novel small molecule, which irreversibly inhibits inducible nitric oxide synthase (iNOS) and has been shown to effectively reduce ROS/RNS generation. In this study, we investigated the effects of 1400W treatment for a week or two weeks at 10 mg/kg or 15 mg/kg per day in the rat diisopropylfluorophosphate (DFP) model. 1400W significantly reduced the number of microglia, astroglia, and NeuN+FJB positive cells compared to the vehicle in different regions of the brain. 1400W also significantly reduced nitrooxidative stress markers and proinflammatory cytokines in the serum. However, neither of the two concentrations of 1400W for two weeks of treatment had any significant effect on epileptiform spike rate and spontaneous seizures during the treatment period in mixed sex cohorts, males, or females. No significant sex differences were found in response to DFP exposure or 1400W treatment. In conclusion, 1400W treatment at 15 mg/kg per day for two weeks was more effective in significantly reducing DFP-induced nitrooxidative stress, neuroinflammatory and neurodegenerative changes.
A Monte Carlo Study of the Low-Temperature Properties of Strongly Correlated Localized Particles in Disordered Systems

A computer simulation method is presented, which yields the ground state as well as the low-energy excitations for disordered systems of many interacting particles. The efficiency of the method is demonstrated by the application to the Coulomb glass, i.e. many localized electrons with long-range interaction. The obtained knowledge about the specific configurations of a large number of excited states is only the starting point for further investigations. First results are presented which shed a new light on old controversies about the behaviour of correlated electrons within the Coulomb gap regime.
A Measure of Semantic Class Difference of Point Reprojection Pairs in Camera Pose Estimation

In this article, we propose a new measure that evaluates the semantic errors of camera poses in visual odometry (VO) and visual simultaneous localization and mapping (VSLAM). Traditionally, VO/VSLAM methods have used photometric images to estimate camera poses, but they suffer from varying illumination and viewpoint changes. Thus, methods using semantic images have been an alternative to increase consistency, as semantic information has shown its robustness even in hostile environments. Our measure compares semantic classes of map point reprojection pairs between images to improve the camera pose estimation accuracy in VO/VSLAM. To evaluate the difference between semantic classes, we adopt the normalized information distance from information theory. Furthermore, we suggest a weight parameter to balance the existing error of VO/VSLAM with the semantic error introduced by our approach. Our experimental results, obtained from the VKITTI and KITTI benchmark datasets, show that the proposed semantic error measure reduces both the relative pose error and absolute trajectory error of camera pose estimation compared to the existing photometric image-based errors of indirect and direct VO/VSLAM.
Pulse contrast enhancement by an aperiodic converter and self-focusing in hybrid Yb-fiber / Nd:glass CPA system

We introduce a hybrid CPA system of Yb-doped fibers and Nd:glass rods, with use of aperiodic-frequency-converter crystal around 526 nm, demonstrated ~40% efficiency, and ~40 dB pulse contrast improvement. New result with novel SLT-made-AFC yielded ~60% efficiency, both showed near full bandwidth conversion. A Neodymium:glass CPA pulse yielded record energy result of 320s μJ in 527 nm second harmonic with the LiNBO3. Additionally, new, very low-cost, robust method, based on time-space nonlinear-index self-focusing effect showed >20-dB contrast enhancement.
Mach–Zehnder interferometry method for decoupling electro-optic and piezoelectric effects in poled polymer films

A Mach–Zehnder interferometer (MZI) is utilized to decouple the electro-optic and piezoelectric tensor effects occurring in a poled polymer film. This method has significant advantages over the commonly used Teng-Man reflection ellipsometry technique by allowing for the independent determination of the Pockel’s coefficients r13 and r33 and the piezoelectric coefficient d33. The r33 value of a guest host polymer that consists of AJLZ53 amorphous polycarbonate was found to be 122.69 pm/V and 123.03 pm/V using the MZI and reflection ellipsometry method, respectively. The r33 data fits well to the dispersion of the second order susceptibility tensor based on the two-level model approximation.
Joint UAV Trajectory Planning, DAG Task Scheduling, and Service Function Deployment Based on DRL in UAV-Empowered Edge Computing

Unmanned aerial vehicle (UAV)-empowered edge computing has been widely investigated in obstacle-free scenarios, where a moving UAV is in charge of handling offloaded singleton tasks from mobile devices on the ground. However, little attention has been paid to the scenario, in which the UAV serves a complex area with multiple obstacles and dependent tasks. A dependent task can be formulated as a directed acyclic graph (DAG) that contains a number of subtasks; and each subtask can be executed by a corresponding service function (SF) deployed on the UAV. In this backdrop, the joint UAV trajectory planning, DAG task scheduling, and SF deployment is formulated as an optimization problem in this article. Afterwards, a deep reinforcement learning (DRL)-based algorithm is presented to tackle the NP-hard problem. The state space, action space, and the reward function of the agent, i.e., the UAV, are defined, respectively, under the DRL framework. To evaluate the effectiveness of the proposal, a series of experiments is conducted with different parameter settings. Results show that the DRL-based algorithm performs much better than three heuristic algorithms in success rate of trajectory planning, the number of executed tasks, and the average task response latency.
Weighted L 1-estimates for a VAR(p) time series model

The most common method of estimating the parameters of a vector-valued autoregressive time series model is the method of least squares (LS). However, since LS estimates are sensitive to the presence of outliers, more robust techniques are often useful. This paper investigates one such technique, weighted-L 1 estimates. Following traditional methods of proof, asymptotic uniform linearity and asymptotic uniform quadricity results are established. Additionally, the gradient of the objective function is shown to be asymptotically normal. These results imply that the weighted-L 1 parameter estimates for this model are asymptotically normal at rate n −1/2. The results rely heavily on covariance inequalities for geometric absolutely regular processes and a Martingale central limit theorem. Estimates for the asymptotic variance–covariance matrix are also discussed. A finite-sample efficiency study is presented to examine the performance of the weighted-L 1 estimate in the presence of both innovation and additive outliers. Specifically, the classical LS estimate is compared with three versions of the weighted- L 1 estimate. Finally, a quadravariate financial time series is used to demonstrate the estimation procedure. A brief residual analysis is also presented.
Linear dependence relations of nonrecurrent syndromes in decoding cyclic codes beyond their design distance

In 1994, Feng at. al. gave a procedure for decoding cyclic codes that is bounded by the minimum distance of a code. The significance of their work lies in the fact that conventional decoding procedures based on the classical key equation are design distance-bounded and so do not exploit the full error-correcting capability of a code. A crucial step in Feng's decoding procedure is the computation of unknown syndromes using linear dependence relations. We present some results that may be used to carry out this important task.
Systematic assessment and review of techniques based on tumour detection in brain using MRI

ABSTRACT Detecting tumour with Magnetic Resonance imaging (MRI) has been promising in recent years. The current tumour detection strategies are used for visualising, digitising and modelling the images for medical diagnosis. Automatic tumour region segmentation from 3D MRIs is essential for monitoring, diagnosing, and planning the treatment remedies for the disease. However, manual outlining needs an anatomical understanding which requires more time and can be imprecise due to human error. Brain tumour is serious diseases whose exposure must be quick and precise. It is attained by the accomplishment of the automatic detection of the tumour using MRI. Several automatic strategies are employed in literary works, which utilise image segmentation. Here, 50 research papers are surveyed with brain tumour detection strategies like ANN, clustering, deep learning, edge-based techniques, optimisation and transformation strategies. Furthermore, complete exploration is done in terms of publication year, employed strategy, datasets utilised, execution tool, performance measures and its values. At last, the problems of classical strategies and its issues with classical brain tumour detection methods are illustrated to generate the contribution.
NAD+ biosynthesis metabolism predicts prognosis and indicates immune microenvironment for breast cancer

The growing evidence implies that tumor cells need to increase NAD+ levels by upregulating NAD+ biosynthesis to satisfy their growth demand. NAD+ biosynthesis metabolism is implicated in tumor progression. Breast cancer (BC) is the most common malignant malignancy in the world. Nevertheless, the prognostic significance of NAD+ biosynthesis and its relationship with the tumor immune microenvironment in breast cancer still need further investigation. In this study, we obtained the mRNA expression data and clinical information of BC samples from public databases and calculated the level of NAD+ biosynthesis activity by single-sample gene set enrichment analysis (ssGSEA). We then explored the relationship between the NAD+ biosynthesis score, infiltrating immune cells, prognosis significance, immunogenicity and immune checkpoint molecules. The results demonstrated that patients with high NAD+ biosynthetic score displayed poor prognosis, high immune infiltration, high immunogenicity, elevated PD-L1 expression, and might more benefit from immunotherapy. Taken together, our studies not only deepened the understanding of NAD+ biosynthesis metabolism of breast cancer but also provided new insights into personalized treatment strategies and immunological therapies to improve the outcomes of breast cancer patients.
Should the Democrats Move to the Left on Economic Policy?

Could John Kerry have gained votes in the recent Presidential election by more clearly distinguishing himself from George Bush on economic policy? At first thought, the logic of political preferences would suggest not: the Republicans are to the right of most Americans on economic policy, and so in a one-dimensional space with party positions measured with no error, the optimal strategy for the Democrats would be to stand infinitesimally to the left of the Republicans. The median voter theorem suggests that each party should keep its policy positions just barely distinguishable from the opposition. In a multidimensional setting, however, or when voters vary in their perceptions of the parties’ positions, a party can benefit from putting some daylight between itself and the other party on an issue where it has a public-opinion advantage (such as economic policy for the Democrats). We set up a plausible theoretical model in which the Democrats could achieve a net gain in votes by moving to the left on economic policy, given the parties’ positions on a range of issue dimensions. We then evaluate this model based on survey data on voters’ perceptions of their own positions and those of the candidates in 2004. Under our model, it turns out to be optimal for the Democrats to move slightly to the right but staying clearly to the left of the Republicans’ current position on economic issues.
Two fluid space-time discontinuous Galerkin finite element method. Part I: numerical algorithm

A novel numerical method for two fluid flow computations is presented, which combines the space-time discontinuous Galerkin finite element discretization with the level set method and cut-cell based interface tracking. The space-time discontinuous Galerkin (STDG) finite element method offers high accuracy, an inherent ability to handle discontinuities and a very local stencil, making it relatively easy to combine with local {\it hp}-refinement. The front tracking is incorporated via cut-cell mesh refinement to ensure a sharp interface between the fluids. To compute the interface dynamics the level set method (LSM) is used because of its ability to deal with merging and breakup. Also, the LSM is easy to extend to higher dimensions. Small cells arising from the cut-cell refinement are merged to improve the stability and performance. The interface conditions are incorporated in the numerical flux at the interface and the STDG discretization ensures that the scheme is conservative as long as the numerical fluxes are conservative.
Co-regulatory effects of hormone and mRNA–miRNA module on flower bud formation of Camellia oleifera

Few flower buds in a high-yield year are the main factors restricting the yield of Camellia oleifera in the next year. However, there are no relevant reports on the regulation mechanism of flower bud formation. In this study, hormones, mRNAs, and miRNAs were tested during flower bud formation in MY3 (“Min Yu 3,” with stable yield in different years) and QY2 (“Qian Yu 2,” with less flower bud formation in a high-yield year) cultivars. The results showed that except for IAA, the hormone contents of GA3, ABA, tZ, JA, and SA in the buds were higher than those in the fruit, and the contents of all hormones in the buds were higher than those in the adjacent tissues. This excluded the effect of hormones produced from the fruit on flower bud formation. The difference in hormones showed that 21–30 April was the critical period for flower bud formation in C. oleifera; the JA content in MY3 was higher than that in QY2, but a lower concentration of GA3 contributed to the formation of the C. oleifera flower bud. JA and GA3 might have different effects on flower bud formation. Comprehensive analysis of the RNA-seq data showed that differentially expressed genes were notably enriched in hormone signal transduction and the circadian system. Flower bud formation in MY3 was induced through the plant hormone receptor TIR1 (transport inhibitor response 1) of the IAA signaling pathway, the miR535-GID1c module of the GA signaling pathway, and the miR395-JAZ module of the JA signaling pathway. In addition, the expression of core clock components GI (GIGANTEA) and CO (CONSTANS) in MY3 increased 2.3-fold and 1.8-fold over that in QY2, respectively, indicating that the circadian system also played a role in promoting flower bud formation in MY3. Finally, the hormone signaling pathway and circadian system transmitted flowering signals to the floral meristem characteristic genes LFY (LEAFY) and AP1 (APETALA 1) via FT (FLOWERING LOCUS T) and SOC1 (SUPPRESSOR OF OVEREXPRESSION OF CO 1) to regulate flower bud formation. These data will provide the basis for understanding the mechanism of flower bud alternate formation and formulating high yield regulation measures for C. oleifera.
The transport dynamics of tens of micrometer-sized water droplets in RF atmospheric pressure glow discharges

Charging of particles having diameters of tens of microns has been extensively studied at atmospheric pressure in the context of, for example, electrostatic precipitators where the focus was on unipolar charging. The ambipolar charging of particles in atmospheric pressure plasmas, and of droplets in particular, has received less attention. The plasma activation of droplets is of interest for water purification, fertilizer production and materials synthesis, all of which depend on the transport of the droplets through the plasma, which in turn depends on their charging. In this paper, we report on the transport dynamics of water droplets, tens of microns in diameter, carried by the gas flow through an atmospheric pressure radiofrequency glow discharge sustained in helium. The droplets pass through the plasma with minimal evaporation and without reaching the Rayleigh limit. The droplet trajectory in the presence and absence of the plasma provides insights on the forces acting on the droplet. The measurements were analyzed using results from a three-dimensional fluid model and a two-dimensional plasma hydrodynamics model. We found that the transport dynamics as the droplet enters and leaves the plasma are due to differential charging of the droplet in the plasma gradients of the bounding sheaths to the plasma.
Genetic/Protein Association of Atopic Dermatitis and Tooth Agenesis

Atopic dermatitis and abnormalities in tooth development (including hypomineralization, hypodontia and microdontia) have been observed to co-occur in some patients. A common pathogenesis pathway that involves genes and protein interactions has been hypothesized. This review aims to first provide a description of the key gene mutations and signaling pathways associated with atopic dermatitis and tooth agenesis (i.e., the absence of teeth due to developmental failure) and identify the possible association between the two diseases. Second, utilizing a list of genes most commonly associated with the two diseases, we conducted a protein–protein network interaction analysis using the STRING database and identified a novel association between the Wnt/β-catenin signaling pathway (major pathway responsible for TA) and desmosomal proteins (component of skin barrier that affect the pathogenesis of AD). Further investigation into the mechanisms that may drive their co-occurrence and underlie the development of the two diseases is warranted.