Miracle-dz/UniFAR-FTUs huggingface dataset:
Editorial: Recent advances, new perspectives and applications of conceptual density functional theory

Density Functional Theory (or DFT, for short) is a potent methodology useful for the calculation of the molecular and electronic structure of atoms, molecules, clusters, and solids, both in gas phase or in solution (Parr and Yang, 1989). The research in this area goes from the discovery of new computational methods based on the design of accurate density functionals to the application of this methodology for the prediction of the chemical and physical properties of the studied systems. Its use relies not only in the ability to calculate the molecular properties of the species of interest, but also in providing interesting concepts that allow a better comprehension of the chemical reactivity of the systems under consideration (Glossman-Mitnik, 2019; Ramasami, 2019; De Lazaro et al., 2021). Conceptual Density Functional Theory (or CDFT, for short) is a branch of DFT based on the goal of developing a chemical reactivity theory founded on DFT-based concepts with the electron density being the starting point for the design of several response functions, or descriptors, that could be of help not only in the interpretation of the chemical reactivity but also in the predictions of properties and phenomena not having accessed experimentally (Chermette, 1999; Geerlings et al., 2003; Gázquez, 2009; Domingo et al., 2016). CDFT entwines mathematical and physical rigor with qualitative chemical intuition and its scope focuses on many broad applications across all branches of chemistry, from inorganic and materials chemistry, to organic chemistry, polymer chemistry, biochemistry, catalysis and nanochemistry (Chattaraj, 2009; Poater et al., 2010; Domingo et al., 2016; Geerlings et al., 2020; Chattaraj and Chakraborty, 2021; Glossman-Mitnik, 2022; Liu, 2022). Of paramount importance for the field of Conceptual OPEN ACCESS
Moments based characterization of MAPs with reduced rank marginal ∗

The moments based characterization of MAPs with full rank marginal (FRM-MAPs) is provided in [11]. MAPs with reduced rank marginal (RRM-MAPs) diﬀer in essential properties from FRM-MAPs [10]. In this work we propose a general procedure for moments based characterization of MAPs which is applicable for both FRM-MAPs and RRM-MAPs, independent of their internal structure. We also show that the procedure terminates in a ﬁnite number of steps which is proportional to the order of the MAP.
Graphing the Future: Activity and Next Active Object Prediction using Graph-based Activity Representations

We present a novel approach for the visual prediction of human-object interactions in videos. Rather than forecasting the human and object motion or the future hand-object contact points, we aim at predicting (a)the class of the on-going human-object interaction and (b) the class(es) of the next active object(s) (NAOs), i.e., the object(s) that will be involved in the interaction in the near future as well as the time the interaction will occur. Graph matching relies on the efficient Graph Edit distance (GED) method. The experimental evaluation of the proposed approach was conducted using two well-established video datasets that contain human-object interactions, namely the MSR Daily Activities and the CAD120. High prediction accuracy was obtained for both action prediction and NAO forecasting.
Multiperiod Coordination Models of Coal-Electricity Supply Chain with Double Price Regulations

Using game models, we study multiperiod coordination contract and model of coal-electricity supply chain under the condition of double price regulations to alleviate the price conflicts of coal and electricity enterprises. The study reveals that, in boom seasons of coal demand, the multiperiod coordination mechanism may not only reduce the price of thermal coal but also increase the fulfillment rate of thermal coal. Meanwhile, the ordering quantity of thermal coal is increased and the shortage probability of electricity supply is decreased. Thereby, the conflicts between coal and electricity are also alleviated effectively.
Introducing YakuToolkit. Yakut Treebank and Morphological Analyzer.

This poster presents the first publicly available treebank of Yakut, a Turkic language spoken in Russia, and a morphological analyzer for this language. The treebank was annotated following the Universal Dependencies (UD) framework and the mor- phological analyzer can directly access and use its data. Yakut is an under-represented language whose prominence can be raised by making reliably annotated data and NLP tools that could process it freely accessible. The publication of both the treebank and the analyzer serves this purpose with the prospect of evolving into a benchmark for the development of NLP online tools for other languages of the Turkic family in the future.
On continuous expansions of configurations of points in Euclidean space

For any two configurations of ordered points $p=(p_{1},.,\p_{N})$ and $q=(q_{1},.,q_{N})$ in Euclidean space $E^d$ such that $q$ is an expansion of $p$, there exists a continuous expansion from $p$ to $q$ in dimension 2d; Bezdek and Connelly used this to prove the Kneser-Poulsen conjecture for the planar case. In this paper, we show that this construction is optimal in the sense that for any $d \ge 2$ there exists configurations of $(d+1)^2$ points $p$ and $q$ in $E^d$ such that $q$ is an expansion of $p$ but there is no continuous expansion from $p$ to $q$ in dimension less than 2d. The techniques used in our proof are completely elementary.
Room temperature structure of Pb(ZrxTi1−xO3) around the morphotropic phase boundary region: A Rietveld study

We have carried out a detailed Rietveld analysis of x-ray powder diffraction data of Pb(ZrxTi1−x)O3 (PZT) compositions across the morphotropic phase boundary (MPB) region (x=0.515, 0.520, 0.525, 0.530). It is shown that the structure of PZT is pure tetragonal for x⩽0.515 with space group P4mm. In the MPB region, 0.515<x<0.530, the tetragonal and monoclinic (space group: Cm) phases are found to coexist as a result of a first order phase transition between the low temperature monoclinic and high temperature tetragonal phases. Further, arguments are advanced to show that the hitherto believed rhombohedral structure (FRHT) of PZT for 0.530⩽x⩽0.62 is more likely to be monoclinic.
FeIDo: Recoverable FIDO2 Tokens Using Electronic IDs

Two-factor authentication (2FA) mitigates the security risks of passwords as sole authentication factor. FIDO2---the de facto standard for interoperable web authentication---leverages strong, hardware-backed second factors. However, practical challenges hinder wider FIDO2 user adoption for 2FA tokens, such as the extra costs (20-30 per token) or the risk of inaccessible accounts upon token loss/theft. To tackle the above challenges, we propose FeIDo, a virtual FIDO2 token that combines the security and interoperability of FIDO2 2FA authentication with the prevalence of existing eIDs (e.g., electronic passports). Our core idea is to derive FIDO2 credentials based on personally-identifying and verifiable attributes---name, date of birth, and place of birth---that we obtain from the user's eID. As these attributes do not change even for refreshed eID documents, the credentials "survive" token loss. Even though FeIDo operates on privacy-critical data, all personal data and resulting FIDO2 credentials stay unlinkable, are never leaked to third parties, and are securely managed in attestable hardware containers (e.g., SGX enclaves). In contrast to existing FIDO2 tokens, FeIDo can also derive and share verifiable meta attributes (anonymous credentials) with web services. These enable verified but pseudonymous user checks, e.g., for age verification (e.g., "is adult").
Investigating the Quality of Static Anchor Embeddings from Transformers for Under-Resourced Languages

This paper reports on experiments for cross-lingual transfer using the anchor-based approach of Schuster et al. (2019) for English and a low-resourced language, namely Hindi. For the sake of comparison, we also evaluate the approach on three very different higher-resourced languages, viz. Dutch, Russian and Chinese. Initially designed for ELMo embeddings, we analyze the approach for the more recent BERT family of transformers for a variety of tasks, both mono and cross-lingual. The results largely prove that like most other cross-lingual transfer approaches, the static anchor approach is underwhelming for the low-resource language, while performing adequately for the higher resourced ones. We attempt to provide insights into both the quality of the anchors, and the performance for low-shot cross-lingual transfer to better understand this performance gap. We make the extracted anchors and the modified train and test sets available for future research at https://github.com/pranaydeeps/Vyaapak
Statistical Steganalysis Detector Model for 8-bit Depth Images

This thesis aims to develop a statistical model for steganalysis to enhance the detection of the existence of hidden data inside 8-bit depth gray-scale BMP images. The proposed model is based on enhancing the image texture features through analyzing both full-bytes and parts of bytes of an image. It is known that most steganography techniques embed the bits of a secret message within the right half of a cover image’s bytes, the least significant half of a byte, to avoid obvious visual distortion. Therefore, the focus of the steganalysis process in this work is the right half part of each byte of an image under investigation. The selected feature set is based on the gray level co-occurrence model, including contrast, homogeneity, correlation, and energy. Additional features include: entropy, coefficient of variation of the image’s right half-bytes, correlation coefficient between left and right half-bytes, and the average of difference between the intensity of right half -bytes in successive pixels.
Metabolomic study of eyeball rupture and patients with cataracts in aqueous humor

The purpose of the present study was to identify metabolic biomarkers and study the metabolic changes in relation to cataracts and eyeball rupture in human aqueous humor. This case-control study included 3 patients with traumatic ocular rupture treated by surgery as the control group, 10 patients with severe cataracts as the severe cataracts group and 10 patients with mild cataracts as the mild cataracts group. The present study used liquid chromatography-mass spectrometry to analyze the metabolomics of aqueous humor samples. Databases including the Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst were used to find potential pathways for metabolites. Aqueous humor metabolic spectrum can competently distinguish patients with different degrees of cataracts from the control group. A total of 34 metabolites were identified as potential biomarkers that could distinguish patients with different degrees of cataracts; 36 metabolites were identified as potential biomarkers that could distinguish patients with severe cataracts from the control group; 34 metabolites were identified as potential biomarkers that could distinguish patients with mild cataracts from controls. In pathway analysis, glycerolphospholipid metabolism was highly affected, which meant that these metabolic markers serve an important role in the regulation of this pathway. The present study identified valuable metabolic biomarkers and pathways, which is helpful for an improved understanding of the pathogenesis of cataracts. This discovery has transformation value for the development of new treatment methods for cataracts.
Evaluation of Surface Water and Energy Cycles in the Met Office Global NWP Model Using CEOP Data( Coordinated Enhanced Observing Period(CEOP))

Components of the surface water and energy balance are evaluated in the Met Office global Numerical Weather Prediction (NWP) 00-36 hour forecasts using (i) GEWEX Continental Scale Experiment (CSE) reference site data provided by the Coordinated Enhanced Observing Period (CEOP) project and (ii) other earth observing datasets from satellites and in-situ measurements. The global hydrological cycle in the model is in reasonable balance in recent model versions. However, comparison against available observations suggest that both precipitation and evaporation are overestimated over both land and ocean, with largest errors over the tropical oceans. Comparison of the model's seasonal and diurnal cycles of surface fluxes, temperature, precipitation, and moisture against the GEWEX/CEOP CSE sites during October 2002 to September 2003 reveals several issues concerning model parametrization performance. For the high latitude (Arctic) sites low cloud is overestimated during boreal winter leading to an enhanced greenhouse effect and too warm near surface temperatures in the model. Snow melt occurs too early in boreal spring in the model forecasts which currently have no snow analysis component. Possible reasons for early snow melt are discussed including the specification of albedo over heterogeneous terrain and excessive sublimation of snow in the model. The mid-latitude CEOP sites all show excessive evaporation and precipitation during boreal spring and early summer and comparison with the International Satellite Cloud Climatology (ISCCP) products show systematic under prediction of cloud cover over mid-latitude land in summer. Some of the largest biases in mid-latitude surface fluxes in summer are during daytime on non-precipitating cloudy days where the model overestimates the downward SW radiation, latent and sensible heat fluxes. Finally, over tropical land we see a tendency to underestimate precipitation which is in direct contrast to tropical oceans where precipitation accumulations are too large. We have also used the CEOP data to investigate structural errors in the vertical profiles of tropical humidity which suggest deficiencies in the convection scheme.
A hot universe.

For example, there is an important event, roughly 300,000 years after the Big Bang, when atoms form for the first time. Prior to this, the temperature was higher than the 13.6 eV binding energy of hydrogen, and the electrons were stripped from the protons. This moment in time is known as recombination and will be described in Section 2.3. (Obviously a better name would simply be “combination” since the electrons and protons combined for the first time, but we don’t get to decide these things). This is a key moment in the history of the universe. Prior to this time, space was filled with a charged plasma through which light is unable to propagate. But when the electrons and protons form to make (mostly) neutral hydrogen, the universe becomes transparent. The cosmic microwave background, which will be discussed in Section 2.2, dates from this time.
APPLICATIONS OF THE MEAN CURVATURE FLOW ASSOCIATED TO ANISOTROPIC GENERALIZED LAGRANGE METRICS IN IMAGE PROCESSING

The Geodesic Active Field (GAF) approach from image processing - whose mathematical background is the Riemannian theory of submanifolds, was recently extended by the authors to the Finslerian setting, for certain specific metrics of Randers type. The present work studies the significantly more flexible Generalized Lagrange (GL) extension, which allows a versatile adapting of the GAF process to Finslerian, pseudo-Finslerian and Lagrangian structures. The mathematically essential GAF mean curvature flow PDEs of three such GL structures (Randers-Ingarden, Synge-Beil and proper Generalized Lagrange) are explicitly obtained, discussed, implemented, and their corresponding feature evolution is compared with the classic results produced by the established original Riemannian GAF model.
Recent Process in Microrobots: From Propulsion to Swarming for Biomedical Applications

Recently, robots have assisted and contributed to the biomedical field. Scaling down the size of robots to micro/nanoscale can increase the accuracy of targeted medications and decrease the danger of invasive operations in human surgery. Inspired by the motion pattern and collective behaviors of the tiny biological motors in nature, various kinds of sophisticated and programmable microrobots are fabricated with the ability for cargo delivery, bio-imaging, precise operation, etc. In this review, four types of propulsion—magnetically, acoustically, chemically/optically and hybrid driven—and their corresponding features have been outlined and categorized. In particular, the locomotion of these micro/nanorobots, as well as the requirement of biocompatibility, transportation efficiency, and controllable motion for applications in the complex human body environment should be considered. We discuss applications of different propulsion mechanisms in the biomedical field, list their individual benefits, and suggest their potential growth paths.
Bayes quadratic unbiased estimator of spatial covariance parameters

This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes estimator of variance components with too many unknown parameters is complicated to be solved analytically. Hence, in order to facilitate the handling with this system, BAIQUE of spatial covariance model with two parameters is considered. Bayesian estimation arises as a solution of a linear equations system which requires the linearity of the covariance functions in the parameters. Here the availability of prior information on the parameters is assumed. This information includes a priori distribution functions which enable to find the first and the second moments matrix. The Bayesian estimation suggested here depends only on the second moment of the prior distribution. The estimation appears as a quadratic form y′Ay , where y is the vector of filtered data observations. This quadratic estimator is used to estimate the linear function of unknown variance components. The matrix A of BAIQUE plays an important role. If such a symmetrical matrix exists, then Bayes risk becomes minimal and the unbiasedness conditions are fulfilled. Therefore, the symmetry of this matrix is elaborated in this work. Through dealing with the infinite series of matrices, a representation of the matrix A is obtained which shows the symmetry of A. In this context, the largest singular value of the decomposed matrix of the infinite series is considered to deal with the convergence condition and also it is connected with Gerschgorin Discs and Poincare theorem. Then the BAIQUE model for some experimental designs is computed and compared. The comparison deals with different aspects, such as the influence of the position of the design points in a fixed interval. The designs that are considered are those with their points distributed in the interval [0, 1]. These experimental structures are compared with respect to the Bayes risk and norms of the matrices corresponding to distances, covariance structures and matrices which have to satisfy the convergence condition. Also different types of the regression functions and distance measurements are handled. The influence of scaling on the design points is studied, moreover, the influence of the covariance structure on the best design is investigated and different covariance structures are considered. Finally, BAIQUE is
The Impact of Viral Marketing on the Live Broadcasting Industry under the Influence of COVID-19

Under the influence of the new crown virus, many industries have been greatly affected using traditional marketing methods, but some industries have made great progress through the combination of network and marketing, using viral marketing. Among them, the most representative is the live broadcasting industry. This paper aims to study the benefits of the viral marketing strategy in the background of COVID-19, and what has brought the rapid development of the live broadcasting industry in such a short period of time. At the same time, it will also analyze the disadvantages and risks hidden in viral marketing behind such great benefits to the live broadcasting industry. After analysis, the company must use the right methods and methods when using viral marketing strategy, so as to maximize the benefits, minimize the disadvantages and produce better results.
Admission Serum Iron as an Independent Risk Factor for Postoperative Delayed Cerebral Ischemia Following Aneurysmal Subarachnoid Hemorrhage: A Propensity-Matched Analysis

This study aimed to investigate the association between serum iron (SI) and postoperative delayed cerebral ischemia (DCI) following aneurysmal subarachnoid hemorrhage (aSAH). We retrospectively analyzed 985 consecutive adult patients diagnosed with aSAH. Demographic, clinical, and laboratory data were recorded. Univariate and multivariate analyses were employed to assess the association between SI and DCI. Propensity-score matching (PSM) analysis was implemented to reduce confounding. Postoperative DCI developed in 14.38% of patients. Lower SI upon admission was detected in aSAH patients with severe clinical conditions and severe aSAH. SI was negatively correlated with WFNS grade (r = −0.3744, p < 0.001) and modified Fisher (mFisher) grade (r = −0.2520, p < 0.001). Multivariable analysis revealed lower SI was independently associated with DCI [odds ratios (OR) 0.281, 95% confidence interval (CI) 0.177–0.448, p < 0.001], while WFNS grade and mFisher grade were not. The receiver-operating characteristics (ROC) curve analysis of SI for DCI gave an area under the curve (AUC) of 0.7 and an optimal cut-off of 7.5 μmol/L (95% CI 0.665 to 0.733, p < 0.0001). PSM demonstrated the DCI group had a significantly lower SI than the non-DCI group (10.91 ± 6.86 vs. 20.34 ± 8.01 μmol/L, p < 0.001). Lower SI remained a significant independent predictor for DCI and an independent poor prognostic factor of aSAH in multivariate analysis (OR 0.363, 95% CI 0.209–0.630, p < 0.001). The predictive performance of SI for poor outcome had a corresponding AUC of 0.718 after PSM. Lower SI upon admission is significantly associated with WFNS grade, mFisher grade, and predicts postoperative DCI and poor outcome at 90 days following aSAH.
Insights into Allosteric Mechanisms of the Lung-Enriched p53 Mutants V157F and R158L

Lung cancer is a leading fatal malignancy in humans. p53 mutants exhibit not only loss of tumor suppressor capability but also oncogenic gain-of-function, contributing to lung cancer initiation, progression and therapeutic resistance. Research shows that p53 mutants V157F and R158L occur with high frequency in lung squamous cell carcinomas. Revealing their conformational dynamics is critical for developing novel lung therapies. Here, we used all-atom molecular dynamics (MD) simulations to investigate the effect of V157F and R158L substitutions on the structural properties of the p53 core domain (p53C). Compared to wild-type (WT) p53C, both V157F and R158L mutants display slightly lesser β-sheet structure, larger radius of gyration, larger volume and larger exposed surface area, showing aggregation-prone structural characteristics. The aggregation-prone fragments (residues 249–267 and 268–282) of two mutants are more exposed to water solution than that of WT p53C. V157F and R158L mutation sites can affect the conformation switch of loop 1 through long-range associations. Simulations also reveal that the local structure and conformation around the V157F and R158L mutation sites are in a dynamic equilibrium between the misfolded and properly folded conformations. These results provide molecular mechanistic insights into allosteric mechanisms of the lung-enriched p53 mutants.