Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybridization and molecular geometry: A number game

Present article emphasize the new pedagogy to learn the hybridization and molecular geometry. It is always a challenge for the students to remember the hybridization and geometry of the molecule correctly. This topic has several importance in subjective and objective type questions and answers since in most of the competitive examination hybridization and molecular geometry always comprise a huge number of questions. Now in order to remember all the hybridization, this paper gives you a table of few numbers and those number are also no need to remember because they contain certain trends in period and column (subtract 8 in row and subtract 6 in column) and certainly the table will form. Here, the more focus on the domain number (total bond pair and lone pair) 6, 5 and 4 because these domain number contain various type of geometry. This article is not emphasizing the theory behind the hybridization, but only on how to remember different hybridization and their geometry as far as the competitive skill is concerned. It has also some of the restrictions (limitation) and may not work for some of the coordination complex and inorganic compounds.
In vivo classification of human skin burns using machine learning and quantitative features captured by optical coherence tomography

We report the first fully automated detection of human skin burn injuries in vivo, with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Our proposed automated procedure entails building a machine-learning-based classifier by extracting quantitative features from normal and burn tissue images recorded by OCT. In this study, 56 samples (28 normal, 28 burned) were imaged by OCT and eight features were extracted. A linear model classifier was trained using 34 samples and 22 samples were used to test the model. Sensitivity of 91.6% and specificity of 90% were obtained. Our results demonstrate the capability of a computer-aided technique for accurately and automatically identifying burn tissue resection margins during surgical treatment.
Preparation and antibacterial properties of hydrophobic Ag-loaded silica materials

ABSTRACT The Ag-loaded hydrophobic silica (Ag/M-SiO2) materials were prepared by sol-gel method with tetraethylorthosilicate (TEOS) as precursor and methyltriethoxysilane (MTES) as hydrophobic modifier. Contact angles, X-ray diffraction and X-ray photoelectron spectra were used to characterize the as-prepared Ag/M-SiO2 materials. The antibacterial properties of the Ag/M-SiO2 materials were evaluated against Escherichia coli and Staphylococcus aureus. The results indicated that the appropriate calcination temperature of keeping the hydrophobicity of Ag/M-SiO2 materials is 300∼500°C. Ag element exists in Ag/M-SiO2 materials as the elemental form and hydrophobic Si-CH3 groups have been successfully introduced into the Ag/M-SiO2 materials. The qualitative and quantitative antibacterial experiments showed that the antibacterial activity increased with the increase of silver content. When the molar ratio of Ag/TEOS is increased to 0.10, the Ag/M-SiO2 materials showed good antibacterial dissolution and broad-spectrum antibacterial property.
The Work of Sophie Germain and Niels Henrik Abel on Fermat's Last Theorem

In this thesis, we study what can be said about Fermat's Last Theorem using only elementary methods. We will study the work of Sophie Germain and Niels Henrik Abel, both who worked with Fermat's Last Theorem in the early 1800s. Abel claimed to have proven four partial results of Fermat's Last Theorem, but mentioned nothing about how he had proved them. The aim of this thesis is to rediscover these four proofs. We will show that using only elementary methods, we are able to prove parts of Abel's theorems, but we have not found it possible to prove them in full generality. We will see that allowing ourselves to use some non-elementary methods one can prove more of Abel's claims, but still not in full generality.
Revealing strong polytypism tendency in MgTe from first-principles

The search for stable polytype phases of III-V and II-VI materials has attracted great interest in recent years due to their great potential for a broad range of applications. Here using density functional theory, we systematically explore electronic structure properties of cubic (3C) and hexagonal (2H, 4H and 6H) polytypes of magnesium telluride: MgTe. Total energies and nearest-neighbor bilayer interaction energies evidence that MgTe shows a high propensity to polytypism. This finding is further supported by mechanical and phonon stabilities of all polytype phases of MgTe. Additionally, ground structural properties, energetic stability, mechanical properties, band structure energies, and dynamical properties are examined in relation with the stacking sequence of 3C, 2H, 4H, and 6H polytypes in the Mg-Te system.
Nonlinear Waves, Instabilities and Singularities in Plasma and Hydrodynamics

Nonlinear effects are present in almost every area of science as soon as one tries to go beyond the first order approximation. In particular, nonlinear waves emerge in such areas as hydrodynamics, nonlinear optics, plasma physics, quantum physics, etc. The results of this work are related to nonlinear waves in two areas, plasma physics and hydrodynamics, united by concepts of instability, singularity and advanced numerical methods used for their investigation. The first part of this work concentrates on Langmuir wave filamentation instability in the kinetic regime of plasma. In Internal Confinement Fusion Experiments (ICF) at National Ignition Facility (NIF), where attempts are made to achieve fusion by compressing a small target by many powerful lasers to extremely high temperatures and pressures, plasma is created in the first moments of the laser reaching the
Analyzing the impact of the initialization for the nonnegative tensor factorization in tensor displays

Abstract. Tensor display is an option in glasses-free three-dimensional (3-D) display technology. An initial solution has to be set to decompose the light-field information to be represented by the system. We have analyzed the impact of the initial guess on the multiplicative update rules in terms of peak signal-to-noise ratio, and proposed a method based on depth map estimation from an input light field. Results from simulations were obtained and compared with previous literature. In our sample, the initial values used have a large influence on results and convergence to a local minimum. The quality of the output stabilizes after a certain number of iterations, suggesting that a limit on such numbers should be imposed. We show that the proposed methods outperform the pre-existing ones.
Characterization of frequency stability in electromagnetically induced transparency-based atomic clocks using a differential detection scheme

We investigate a recently proposed scheme for differential detection of the magneto-optical rotation effect and its application to electromagnetically induced transparency (EIT) atomic clocks [Opt. Lett.40, 3703 (2015)OPLEDP0146-959210.1364/OL.40. 003703]. This scheme utilizes a linearly polarized bichromatic laser field that is EIT-resonant with alkali atoms. The results of our study reveal that the suppression of the laser noise can substantially improve the signal-to-noise ratio in EIT atomic clocks. Our preliminary results demonstrate an order of magnitude improvement in clock stability under some conditions when incorporating the differential detection scheme.
Stochastic Model Speciflcation Search for Gaussian and Non-Gaussian State Space Models

Model specification for state space is a difficult task as one has to decide which components to include in the model and to specify whether these components are fixed or time-varying. To this aim a new model space MCMC method is developed in this paper. It is based on extending the Bayesian variable selection approach which is usually applied to model selection for regression models to state space models. For non-Gaussian state space models stochastic model search MCMC makes use of auxiliary mixture sampling. We focus on structural time series models including seasonal components, trend or intervention. The method is applied to various well-known time series.
Comparing Two Clusterings Using Matchings between Clusters of Clusters

Clustering is a fundamental problem in data science, yet the variety of clustering methods and their sensitivity to parameters make clustering hard. To analyze the stability of a given clustering algorithm while varying its parameters, and to compare clusters yielded by different algorithms, several comparison schemes based on matchings, information theory, and various indices (Rand, Jaccard) have been developed. We go beyond these by providing a novel class of methods computing meta-clusters within each clustering—a meta-cluster is a group of clusters, together with a matching between these. Let the intersection graph of two clusterings be the edge-weighted bipartite graph in which the nodes represent the clusters, the edges represent the nonempty intersection between two clusters, and the weight of an edge is the number of common items. We introduce the so-called D-family-matching problem on intersection graphs, with D the upper bound on the diameter of the graph induced by the clusters of any meta-cluster. First we prove NP-completeness and APX-hardness results, and unbounded approximation ratio of simple strategies. Second, we design exact polynomial time dynamic programming algorithms for some classes of graphs (in particular trees). Then we prove spanning tree–based efficient heuristic algorithms for general graphs. Our experiments illustrate the role of D as a scale parameter providing information on the relationship between clusters within a clustering and in-between two clusterings. They also show the advantages of our built-in mapping over classical cluster comparison measures such as the variation of information.
Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems

Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems Neal Kaw Master of Applied Science Graduate Department of Mechanical and Industrial Engineering University of Toronto 2017 Most inverse optimization models impute unspecified parameters of an objective function to make an observed solution optimal for a given optimization problem. In this thesis, we propose two approaches to impute unspecified left-hand-side constraint coefficients in addition to a cost vector for a given linear optimization problem. The first approach minimally perturbs prior estimates of the unspecified parameters to satisfy strong duality, while the second identifies parameters minimizing the duality gap, if it is not possible to satisfy the optimality conditions exactly. We apply these two approaches to the general linear optimization problem. We also use them to impute unspecified parameters of the uncertainty set for robust linear optimization problems under interval and cardinality constrained uncertainty. Each inverse optimization model we propose is nonconvex, but we show that a globally optimal solution can be obtained by solving a finite number of tractable optimization problems.
Efficient routing redundancy design over lossy networks

In this paper, a wireless networked control system is made robust with respect to packet losses by exploiting routing redundancy. Multiple copies of sensing and actuation data are sent via different routing paths, associated to possibly different delays. Similar to linear network coding, such data are recombined as a weighted linear combination. A MIMO output‐feedback architecture is considered. A methodology that takes into account both the network parameters and the plant dynamics is proposed to set up an optimization problem to design network weights to satisfy a robustness metric based on the notion of asymptotic mean‐square stability. Such metric induces either an objective or a constraint function that is nonlinear. For this reason, an efficient suboptimal design methodology is also proposed. Finally, the solutions are compared with the optimal choice from the communication designer point of view, which is based on the minimization of the quadratic error induced by the network on the actuation signal. The suboptimal methodology is shown, by means of a nontrivial example, to give results extremely close to the optimum with a strongly reduced computation time. It is also shown that the optimal choice from the communication design point of view, which neglects the plant dynamics, does not guarantee stochastic stability.
Effects of mixed metal exposures on MRI diffusion features in the medial temporal lobe

Introduction: Welding fumes contain a mixture of metals and are an epitype for environmental metal-related neurotoxicity. Past studies of welders focused largely on basal ganglia regions and their association with parkinsonism. This study evaluated medial temporal lobe (MTL) structures that play a key role in Alzheimer's disease-like pathology. Methods: Exposure history and whole blood metal levels were obtained from subjects with/without a history of welding (42 welders; 31 controls). MTL regions of interest (ROI) (hippocampus, entorhinal and parahippocampal cortices) were assessed by morphologic (volume and cortical thickness) and diffusion tensor imaging [mean (MD), axial (AD), radial diffusivity (RD) and fractional anisotropy (FA)] metrics. Cognition was evaluated using standard neuropsychological tests. Results: Welders had higher blood levels of Cu, Fe, K, Mn, Pb, Se, and Zn (p's<0.026) than controls. Welders had higher MD, AD, and RD in all MTL ROIs (p's<0.040) and lower FA in the entorhinal and parahippocampal cortices (p's<0.033) without significant morphologic differences. Welders also exhibited lower performance on processing/psychomotor speed, executive, and visuospatial function domains (p's<0.046). Greater welding years predicted lower parahippocampal FA (p=0.011), where greater short-term welding intensity (E90) predicted worse Symbol coding digit scores (p=0.019). Blood Mn and Cu levels demonstrated robust relationships with entorhinal diffusivity (p's<0.009) and story recall performance (p=0.003), respectively, throughout correlation, semi-parametric regression, and Bayesian kernel machine regression analyses. Discussion: Welding fumes and related metal exposures are associated with MTL features of early Alzheimer's disease. Given the ubiquitous nature of metal exposure, future studies are warranted and may have public health implications.
Task-dependent Alteration in Delta Band Corticomuscular Coherence during Standing in Chronic Stroke Survivors

Balance control is an important indicator of mobility and independence in activities of daily living. How the changes in functional integrity of corticospinal tract due to stroke affects the maintenance of upright stance remains to be known. We investigated the changes in functional coupling between the cortex and lower limb muscles during a challenging balance task over multiple frequency bands in chronic stroke survivors. Eleven stroke patients and nine healthy controls performed a challenging balance task. They stood on a computerized platform with/without somatosensory input distortion created by sway-referencing the support surface, thereby varying the difficulty levels of the task. We computed corticomuscular coherence between Cz (electroencephalography) and leg muscles and assessed balance performance using Berg Balance scale (BBS), Timed-up and go (TUG) and center of pressure (COP) measures. We found lower delta frequency band coherence in stroke patients when compared with healthy controls under medium difficulty condition for distal but not proximal leg muscles. For both groups, we found similar coherence at other frequency bands. On BBS and TUG, stroke patients showed poor balance. However, similar group differences were not consistently observed across COP measures. The presence of distal versus proximal effect suggests differences in the (re)organization of the corticospinal connections across the two muscles groups for balance control. We argue that the observed group difference in the delta coherence might be due to altered mechanisms for the detection of somatosensory modulation resulting from sway-referencing of the support platform for balance control.
Analysis of ITER NbTi and Nb3Sn CICCs experimental minimum quench energy with JackPot, MCM and THEA models

Cable-in-conduit conductors (CICCs) for ITER magnets are subjected to fast changing magnetic fields during the plasma-operating scenario. In order to anticipate the limitations of conductors under the foreseen operating conditions, it is essential to have a better understanding of the stability margin of magnets. In the last decade ITER has launched a campaign for characterization of several types of NbTi and Nb3Sn CICCs comprising quench tests with a singular sine wave fast magnetic field pulse and relatively small amplitude. The stability tests, performed in the SULTAN facility, were reproduced and analyzed using two codes: JackPot-AC/DC, an electromagnetic-thermal numerical model for CICCs, developed at the University of Twente (van Lanen and Nijhuis 2010 Cryogenics 50 139–148) and multi-constant-model (MCM) (Turck and Zani 2010 Cryogenics 50 443–9), an analytical model for CICCs coupling losses. The outputs of both codes were combined with thermal, hydraulic and electric analysis of superconducting cables to predict the minimum quench energy (MQE) (Bottura et al 2000 Cryogenics 40 617–26). The experimental AC loss results were used to calibrate the JackPot and MCM models and to reproduce the energy deposited in the cable during an MQE test. The agreement between experiments and models confirm a good comprehension of the various CICCs thermal and electromagnetic phenomena. The differences between the analytical MCM and numerical JackPot approaches are discussed. The results provide a good basis for further investigation of CICC stability under plasma scenario conditions using magnetic field pulses with lower ramp rate and higher amplitude.
Appendix for “Boundary-enhanced Co-training for Weakly Supervised Semantic Segmentation”

A. Experiments 1 A.1. More Implementation Details . 1 A.2. Additional Results Using Different Deeplab . 1 A.3. Boundary Weight λ for the BECO Loss . 2 A.4. Ratio r for Offline Confidence Mask Generation . 2 A.5. Threshold τ for Generating Online Confidence Mask . 2 A.6. Analysis of the Coupling Effect of Co-training 2 A.7. Quantitative Results of Boundary Improvement. 3 A.8. Visualization on MS COCO 2014 . 3
Geometric phase for a periodic non-Hermitian Hamiltonian

In a system described by the time-dependent Hamiltonian H( ~ X(t)) through a slowly varying parameter ~ X(t), an eigenstate of the Hamiltonian develops besides an expected dynamical phase, a geometrical or Berry’s phase γn [1], whose value depends on the closed path C in the space of parameters. Removing the adiabatic hypothesis, Aharonov and Anandan [2] generalized Berry’s result and showed that such a phase might appear for any state cyclic with respect to some evolution. (Cyclicity means that the state returns to itself, after some time, up to a phase factor; in Berry’s approach, the adiabatic hypothesis ensures the cyclicity of eigenstates of H after one loop). Therefore, a natural (but not unique) way to obtain a basis of cyclic states is to consider the following: i) The eigenvectors of a Hermitian periodic invariant I(t) which obeys the equation
Replies to Referee #1’s comments on “Improving interpretation of sea-level projections through a machine learning-based local explanation approach ”. (egusphere- 2022-435)

The manuscript "Improving interpretation of sea-level projections through a machine learningbased local explanation approach" provides a novel approach to analyzing multimodel sea level projections, using machine learning. The method put forward in this study has two parts: (1) using ML models as surrogates for the projection ensemble, (2) explaining the role of various modeling assumptions in generating the differences between sea level projections. The method is novel for our community and provides a potentially powerful was to analyze MIP output in a way that can guide potential future development (though this part needs more elucidation). I have some questions about particular choices in the methods and in general the writing would benefit from clarification. However, overall I find the contribution to be interesting and appropriate for The Cryosphere. We thank Referee #1 for their positive analysis.
Intercomparison of simulations using 4 WRF microphysical schemes with dual-polarization data for a German squall line

Improvements in computational power in recent years have allowed for increasing use of fully explicit numerical models for weather prediction. It is well-known that the use of convective parameterizations in models introduces substantial error, and the use of near-cloud resolving grid spacings may reduce the error since convective schemes can be eliminated. However, microphysical schemes may also introduce great uncertainty into forecasts (e.g., Jankov et al. 2005), and far fewer studies have been done to verify the results from different microphysical packages.
Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands

Abstract. Adapting and improving the hydrological processes in land surface models are crucial given the increase in the resolution of the climate models to correctly represent the hydrological cycle. The present paper introduces a floodplain scheme adapted to the higher-resolution river routing of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model. The scheme is based on a sub-tile parameterisation of the hydrological units – a hydrological transfer unit (HTU) concept – based on high-resolution hydrologically coherent digital elevation models, which can be used for all types of resolutions and projections. The floodplain scheme was developed and evaluated for different atmospheric forcings and resolutions (0.5∘ and 25 km) over one of the world's largest floodplains: the Pantanal, located in central South America. The floodplain scheme is validated based on the river discharge at the outflow of the Pantanal which represents the hydrological cycle over the basin, the temporal evolution of the water mass over the region assessed by the anomaly of total water storage in the Gravity Recovery And Climate Experiment (GRACE), and the temporal evaluation of the flooded areas compared to the Global Inundation Extent from Multi-Satellites version 2 (GIEMS-2) dataset. The hydrological cycle is satisfactorily simulated; however, the base flow may be underestimated. The temporal evolution of the flooded area is coherent with the observations, although the size of the area is underestimated in comparison to GIEMS-2. The presence of floodplains increases the soil moisture up to 50 % and decreases average temperature by 3 ∘C and by 6 ∘C during the dry season. The higher soil moisture increases the vegetation density, and, along with the presence of open-water surfaces due to the floodplains, it affects the surface energy budget by increasing the latent flux at the expense of the sensible flux. This is linked to the increase in the evapotranspiration related to the increased water availability. The effect of the floodplain scheme on the land surface conditions highlights that coupled simulations using the floodplain scheme may influence local and regional precipitation and regional circulation.