Single State Research Articles

State-transition-aware anomaly detection under concept drifts

Detecting temporal abnormal patterns over streaming data is challenging due to volatile data properties and the lack of real-time labels. The abnormal patterns are usually hidden in the temporal context, which cannot be detected by evaluating single points. Furthermore, the normal state evolves over time due to concept drifts. A single model does not fit all data over time. Autoencoders have recently been applied for unsupervised anomaly detection. However, they are trained on a single normal state and usually become invalid after distributional drifts in the data stream. This paper uses an Autoencoder-based approach STAD for anomaly detection under concept drifts. In particular, we propose a state-transition-aware model to map different data distributions in each period of the data stream into states, thereby addressing the model adaptation problem in an interpretable way. In addition, we analyzed statistical tests to detect the drift by examining the sensitivity and powers. Furthermore, we present considerable ways to estimate the probability density function for comparing the distributional similarity for state transitions. Our experiments evaluate the proposed method on synthetic and real-world datasets. While delivering comparable anomaly detection performance as the state-of-the-art approaches, STAD works more efficiently and provides extra interpretability. We also provide insightful analysis of optimal hyperparameters for efficient model training and adaptation.

Binding mechanisms of trivalent chromium on colloidal phases from ultramafic systems: Insights from batch experiments and XAS analysis

Understanding the availability and mobility of chromium is a key factor in gaining insight into the fate of chromium and thus essential for assessing the risk of contamination and developing effective remediation strategies. In the natural environment, such as ultramafic systems, which are natural pools of chromium, chromium occurs mostly in the trivalent state (Cr(III)), which is known to have a high affinity for the solid phases such as particles and colloids. However, since Cr(VI) is more toxic, the vast majority of experimental studies focus on its reduction to Cr(III), which is often considered to form (hydr)oxide precipitates due to its poor solubility. Furthermore, while the oxidation state of Cr dictates its geochemical behavior, its interaction with particles and colloids is rarely controlled or monitored. Therefore, the interaction mechanisms between Cr(III) and particles or colloids require further attention. In this study, ten mineral phases (goethite, hematite, pyrolusite, kaolinite, montmorillonite, chlorite, serpentine, fuchsite, amphibole, and chromite) and one organic phase (humic acid), relevant to chromium bearing and carrier phases in ultramafic soils, were investigated to explore their interaction with Cr(III) species. These phases were first characterized by various techniques (including XRD, XRF, SEM, and BET). Adsorption and desorption experiments of Cr(III) on these phases were then carried out, and the distribution of Cr oxidation states in both the aqueous and solid phases was carefully monitored using UV–vis spectroscopy, geochemical speciation modeling, and Cr K-edge XAS spectroscopy. With the exception of pyrolusite, where partial oxidation of Cr(III) to Cr(VI) occurred, Cr(III) was shown to persist as a single oxidation state in all experiments. Desorption analyses showed significantly low desorbed rates, which further confirmed the prevalence of Cr(III). Experimental sorption isotherm data were interpreted using the Langmuir model and its linearized form, which provides important thermodynamic characteristics of adsorbents related to their structural and surface features. This study will provide better constraints for the understanding and prediction of Cr behavior and fate in the environment, especially in ultramafic systems.

The Logistic Function in Glass Transition Models of Amorphous Polymers: A Theoretical Framework for Isobaric Cooling Processes

AbstractStudying the macroscopic‐phenomenological behavior of amorphous polymers at glass transition is often subject to limitations because the ordinary differential equations that describe the material behavior require numerical solution. To avoid these limitations, ad‐hoc‐formulated models of the glass transition have been proposed. However, their scope of application is expected to be limited due to insufficient theoretical foundation. This work establishes a theoretical framework for models that use the logistic function to approximate the macroscopic‐phenomenological behavior of amorphous polymers at glass transition. For this purpose, an exactly‐solvable Riccati equation is derived within thermodynamics with internal state variables. A closed‐form expression in terms of mathematical functions for the temperature derivative of a single internal state variable is the result. This closed‐form expression contains the logistic function thus featuring a continuous transition region centered around a pressure and cooling‐rate dependent transition temperature. Based on comparison of existing models with the exact solution derived from the Riccati equation, generalized models that approximate the thermal expansion coefficient and heat capacity at glass transition are proposed. This work thus demonstrates the validity of the logistic function in glass transition models of amorphous polymers and provides suggestions as to how existing models can be extended in their applicability.

Structure of Multi-State Correlation in Electronic Systems.

Beyond the Hohenberg-Kohn density functional theory for the ground state, it has been established that the Hamiltonian matrix for a finite number (N) of lowest eigenstates is a matrix density functional. Its fundamental variable─the matrix density D(r)─can be represented by, or mapped to, a set of auxiliary, multiconfigurational wave functions expressed as a linear combination of no more than N2 determinant configurations. The latter defines a minimal active space (MAS), which naturally leads to the introduction of the correlation matrix functional, responsible for the electronic correlation effects outside the MAS. In this study, we report a set of rigorous conditions in the Hamiltonian matrix functional, derived by enforcing the symmetry of a Hilbert subspace, namely the subspace invariance property. We further establish a fundamental theorem on the correlation matrix functional. That is, given the correlation functional for a single state in the N-dimensional subspace, all elements of the correlation matrix functional for the entire subspace are uniquely determined. These findings reveal the intricate structure of electronic correlation within the Hilbert subspace of lowest eigenstates and suggest a promising direction for efficient simulation of excited states.

Examining the Effect of Knowledge Seeking on Knowledge Contribution in Q&A Communities.

Based on motivational theory, this study investigated the effect of users' knowledge seeking on users' knowledge contribution in question-and-answer (Q&A) communities. We collected 4643 samples from the largest social Q&A platform in China (Zhihu) and applied a mediation effect test to the data. The results showed that knowledge seeking affects intrinsic motivations (altruism and self-efficacy) and extrinsic motivations (social support, group identity, and reputation), further affecting knowledge contribution. Our findings indicated that Q&A communities should be concerned with users' intrinsic and extrinsic motivations to ensure balanced knowledge exchange on social Q&A platforms, ultimately fostering long-term stability and growth. Existing research has mainly focused on a single behavioral state, such as knowledge seeking or knowledge contribution, and has paid little attention to the connection between these two types of user information behaviors. This study aimed to fill this gap by revealing the mechanisms through which users' knowledge seeking affects their knowledge contribution.

A novel strategy utilizing oxidation states of phosphorus for designing efficient phosphorus-containing flame retardants and its performance in epoxy resins

The oxidation state of phosphorus has a great influence on the flame retardant action of its flame retardants. In this study, a reactive phosphorus-containing flame retardant (POG-DOPO) with both low and high phosphorus oxidation states is synthesised and incorporated into epoxy resin. The results show that the part in high oxidation state act mainly in the condensed phase and the part in low oxidation state act mainly in the gas phase. Furthermore, the flame retardant exhibits a synergistic flame retardant effect, resulting in a higher flame retardant efficiency than that of flame retardants with a single phosphorus oxidation state. Compared with unmodified epoxy resin, the peak heat release rate, total heat release rate and total smoke release of POG-DOPO modified epoxy resin with only 3wt% phosphorus are reduced by 70.9%, 51.2% and 55.7%, respectively. Its LOI increases to 31.8% and vertical combustion test achieves UL-94 V-0 rating. This study provides a strategy for the structural design of efficient phosphorus-based flame retardants.

Factors Affecting the Adoption of Crowdfunding as a Source of Funding Among SMEs in Colombo Region in Sri Lanka

Small and medium enterprises (SMEs) are regarded as the backbone of economies, whether it is just for a single state or country or if considered for the globe as a whole. There are many challenges that SMEs face one of which is the financial aspect such as insufficient access to financial resources and investment capital can be a significant barrier to the growth of these SMEs. There is a suitable new way funding for this problem that is emerging in the modern world known as crowd-funding. This method mostly involves using the internet to collect money in small and medium amounts from several individuals thereby collecting the needed capital. Therefore, this study focuses on the factors affecting adoption of crowdfunding as a source of funding among SMEs in Colombo region.

Post-Transition State Bifurcation Controls Torsional Selectivity in Radical Addition of Allenes.

Post-transition state bifurcation (PTSB) has received wide attention in the field of reaction mechanism research due to its role in producing nonstatistical reaction selectivity, which cannot be solely explained by transition state theory. Particularly, even subtle molecular motions such as bond torsion can precipitate PTSB, thereby significantly complicating the quantitative understanding of dynamic selectivity. In this work, we found that the radical addition of allenes is an elementary transformation that generally exhibits PTSB stereoselectivity, where a single radical addition transition state can lead to both Z- and E-allylic radicals via the post-transition state allylic single bond torsion. Interestingly, dynamic Z/E-selectivity favors the Z-allylic radicals, which contrasts the thermodynamic preference. Based on the dynamics study of twenty-five radical additions of mono-substituted allenes with diverse electronic and steric effects, we have identified that this dynamic stereoselectivity is synergistically controlled by the transition state structure and the differential trends within specific dimensions of the bifurcating reaction coordinates, which also holds true for di-substituted allene substrates. This study refines the mechanism of radical addition of allenes and underscores the importance of the differential trend of the reaction coordinates in controlling dynamic selectivity, offering a deeper insight into PTSB selectivity factors.

Factors Associated with Waitlist Time on Liver Transplantation

Objectives: Liver transplantation (LT) is the main therapy for patients with cirrhosis or fulminant liver failure. However, there is a disproportion between the demand and availability of organs, such that the waitlist mortality ranged from 20 to 38% when the only allocation criterion was the time of inclusion on the waitlist. Brazil then adopted the Model for End-stage Liver Disease (MELD) score, aiming to prioritize patients with a higher risk of death for LT. !erefore, this study aimed to determine factors associated with waitlist time for LT. Methods: Retrospective cohort study of adult patients listed for LT from October 2012 to December 2019 in a single state in Brazil. Results: !e study analyzes 1,262 patients (869 males, 68.91%; median age, 53.33 ± 11.48 years; median waitlist time, 103.88 ± 162.05 days; median MELD Sodium [MELD-Na] score of 22.41 ± 6.09). Alcoholic liver cirrhosis (n = 369; 29.24%) and chronic viral hepatitis (n = 295; 23.38%) were the most prevalent reasons for LT. Blood groups O (n = 534; 42.31%) and A (n = 474; 37.56%) prevailed among the recipients. !e state capital and its metropolitan region accounted for 91.20% (n = 1,151) of all liver transplants performed. Most donors were deceased (n = 1,258; 99.68%). Patients with MELD-Na scores > 21 (p < 0.001), non-O blood group (p = 0.002), age < 53 years (p = 0.003), and those listed ≥ 2017 spent ≤ 30 days on the waitlist (p < 0.001). Conclusion: A waitlist period of ≤ 30 days was associated with higher MELD-Na scores, younger ages, non-O blood groups, and LT listings before 2017.

Light‐ and Temperature‐Controlled Hybridization, Chiral Induction and Handedness of Helical Foldamers

Helical foldamers have attracted much attention over the last decades given their resemblance to certain biomacromolecules and their potential in domains as different as pharmaceutics, catalysis and photonics. Various research groups have successfully controlled the right‐ or left‐ handedness of these oligomers by introducing stereogenic centers through covalent or non‐covalent chemistry. However, developing helical structures whose handedness can be reversibly switched remains a major challenge for chemists. To date, such an achievement has been reported with light‐responsive single‐stranded foldamers only. Herein, we demonstrate that grafting a unidirectional motor onto foldamer strands constitutes a relevant strategy to i) control the single or double helical state of a foldamer, ii) switch on the chiral induction process from the motor to the helical strands and iii) select the handedness of double helical structures through photochemical and thermal stimulations.

Light- and Temperature-Controlled Hybridization, Chiral Induction and Handedness of Helical Foldamers.

Helical foldamers have attracted much attention over the last decades given their resemblance to certain biomacromolecules and their potential in domains as different as pharmaceutics, catalysis and photonics. Various research groups have successfully controlled the right- or left- handedness of these oligomers by introducing stereogenic centers through covalent or non-covalent chemistry. However, developing helical structures whose handedness can be reversibly switched remains a major challenge for chemists. To date, such an achievement has been reported with light-responsive single-stranded foldamers only. Herein, we demonstrate that grafting a unidirectional motor onto foldamer strands constitutes a relevant strategy to i) control the single or double helical state of a foldamer, ii) switch on the chiral induction process from the motor to the helical strands and iii) select the handedness of double helical structures through photochemical and thermal stimulations.

Ab initio study of Z(N) = 6 magicity* *This work is partially supported by the National Natural Science Foundation of China (Grant Nos. 12175280, 12250610193, 12375143, 11975282, 11705240, 11435014), the Natural Science Foundation of Gansu Province, China (Grant Nos. 20JR10RA067, 23JRRA675), the Chinese Academy of Sciences "Light of West China" Program, the Key Research Program of the Chinese Academy of

The existence of magic numbers of protons and neutrons in nuclei is essential for understanding the nuclear structure and fundamental nuclear forces. Over decades, researchers have conducted theoretical and experimental studies on a new magic number, Z(N)=6, focusing on observables such as radii, binding energy, electromagnetic transition, and nucleon separation energies. We performed ab initio no-core shell model calculations for the occupation numbers of the lowest single particle states in the ground states of Z(N)=6 and Z(N)=8 isotopes (isotones). The results of our calculations do not support Z(N)=6 as a magic number over a range of atomic numbers. However, 14C and 14O exhibit the characteristics of double-magic nuclei.

Accurate deep learning-based filtering for chaotic dynamics by identifying instabilities without an ensemble.

We investigate the ability to discover data assimilation (DA) schemes meant for chaotic dynamics with deep learning. The focus is on learning the analysis step of sequential DA, from state trajectories and their observations, using a simple residual convolutional neural network, while assuming the dynamics to be known. Experiments are performed with the Lorenz 96 dynamics, which display spatiotemporal chaos and for which solid benchmarks for DA performance exist. The accuracy of the states obtained from the learned analysis approaches that of the best possibly tuned ensemble Kalman filter and is far better than that of variational DA alternatives. Critically, this can be achieved while propagating even just a single state in the forecast step. We investigate the reason for achieving ensemble filtering accuracy without an ensemble. We diagnose that the analysis scheme actually identifies key dynamical perturbations, mildly aligned with the unstable subspace, from the forecast state alone, without any ensemble-based covariances representation. This reveals that the analysis scheme has learned some multiplicative ergodic theorem associated to the DA process seen as a non-autonomous random dynamical system.

Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.

Understanding cell state transitions and their governing regulatory mechanisms remains one of the fundamental questions in biology. We develop a computational method, state transition inference using cross-cell correlations (STICCC), for predicting reversible and irreversible cell state transitions at single-cell resolution by using gene expression data and a set of gene regulatory interactions. The method is inspired by the fact that the gene expression time delays between regulators and targets can be exploited to infer past and future gene expression states. From applications to both simulated and experimental single-cell gene expression data, we show that STICCC-inferred vector fields capture basins of attraction and irreversible fluxes. By connecting regulatory information with systems' dynamical behaviors, STICCC reveals how network interactions influence reversible and irreversible state transitions. Compared to existing methods that infer pseudotime and RNA velocity, STICCC provides complementary insights into the gene regulation of cell state transitions.

Electric-Field Manipulation of Magnetic Chirality in a Homo-Ferro-Rotational Helimagnet.

Ferro-rotational (FR) materials, renowned for their distinctive material functionalities, present challenges in the growth of homo-FR crystals (i.e., single FR domain). This study explores a cost-effective approach to growing homo-FR helimagnetic RbFe(SO4)2 (RFSO) crystals by lowering the crystal growth temperature below the TFR threshold using the high-pressure hydrothermal method. Through polarized neutron diffraction experiments, it is observed that nearly 86% of RFSO crystals consist of a homo-FR domain. Notably, RFSO displays remarkable stability in the FR phase, with an exceptionally high TFR of ≈573K. Furthermore, RFSO exhibits a chiral helical magnetic structure with switchable ferroelectric polarization below 4K. Importantly, external electric fields can induce a single magnetic domain state and manipulate its magnetic chirality. The findings suggest that the search for new FR magnets with outstanding material properties should consider magnetic sulfates as promising candidates.

Addressing the Challenge of a Simultaneous Destructive Assay of Plutonium and Uranium: Highly Precise, Robust, Universal, and Reagent-Free Differential Pulse Voltametric Method Development in Biodegradable Methanesulfonic Acid Medium.

The destructive assay of bulk uranium and plutonium, a cornerstone for chemical quality control and nuclear material accounting of fuel matrices, mandates robust and precise methodologies. Despite ongoing research, simultaneous, matrix independent determination of U and Pu has eluded solution owing to inherent limitations in aqueous acid medium, viz., coexistence of multiple oxidation states, coupled electrochemical reactions, smaller potential window, and requirement for multistep sample preconditioning and tedious electrode modification. The present study addresses this challenge wherein non-aqueous methanesulfonic acid (MSA) served the dual role of solvent and analyte media with a bare glassy carbon (GC) electrode. Fuel matrices, viz., (U, Pu)C, (U, Pu)O2, PuO2, UO3, UO2, and U3O8, were quantitatively dissolved in biodegradable MSA, without using any additives. Redox speciation of the analytes, U and Pu, in MSA was probed by ultraviolet-visible spectrophotometry and electrometry, revealing the absence of electrocatalytic regeneration and stabilization of single oxidation state, viz., U(VI) and Pu(IV), along with relevant redox-energetic (electron transfer and reversibility) and kinetic data. Bidentate coordination of MSA with the U analyte was indicated by X-ray absorption spectroscopy studies and was corroborated by density functional theory-based investigations, providing the optimized structure, viz., [UO2(MSA)2] and [Pu(MSA)4], binding modes and energy, partial charges, and molecular orbital diagrams. Based on these insights, the feasibility of differential pulse voltammetry (DPV)-based assay method development for U and Pu separately and in different U/Pu ratios, representing assorted fuel matrices, was probed. Analytical figures of merit for both U and Pu (detection limit of ∼10-5 M, precision of ∼0.2%, accuracy of ∼0.2%, high sensitivity, repeatability, and non-influence of relevant interferences) were determined, method validated employing actual fuel samples, and compared with the established, multi-step biamperometry method. Hence, a universal, simultaneous U and Pu destructive assay method in non-aqueous MSA media based on DPV with a commercial GC electrode was demonstrated.

ASEAN Outlook on The Indo-Pacific Concerning The Implementation of National Determined Contributions To Achieve Sustainable Development Goal 13

The aim of the research is to analyze comprehensively the ASEAN Outlook on the Indo-Pacific (AOIP) concerning the Implementation of National Determined Contributions (NDCs) to achieve Sustainable Development Goal 13, namely “take urgent action to combat climate change and its impacts”. The bad impacts of climate change do not only cause serious impacts to the environment but also to the economic, social life and culture. International cooperation both regional and universal are important due to an individual state will not be able to overcome the bad impacts of climate change. The ambitious commitment of a single state as a member of the Paris Agreement to reduce emission stipulated in the NDCs should be performed in good faith. Indeed, the success of the NDCs will depend on the commitment of individual state to comply and perform the commitment due to the voluntarily character of the NDCs. The AOIP was formulated to guide cooperation and to create the environment for peace, stability, and prosperity while upholding the rules-based regional architecture. However, the AOIP is not legally binding. The research is a normative juridical research, and the approaches are employed are conceptual approach and statutory approach. The results of this research demonstrates that the implementation of NDCs faces many challenges in the ASEAN and Indo-Pacific which depend on the situation and condition of each state, however, there are some opportunities that can be performed.

Method for Predicting Bound Water Saturation in Tight Sandstone Reservoirs Using Morphology and Fractal Models

The nuclear magnetic resonance T2 spectrum was used to identify the T2 cut-off value, which is the key to determining the irreducible water saturation of a reservoir. In this paper, the saturation and centrifugal T2 spectra of sandstone and coal samples were used to explore the correlation between each parameter and the T2 cut-off value, using a single fractal dimension, a multifractal dimension and a spectral morphology discrimination method. The conclusions are as follows: (1) The T2 spectra of nine sandstone samples in this paper can be divided into four types. Type A is represented by sample 2, wherein the T2 spectrum shows a bimodal state and the area of the right T2 spectrum (2.5~100 ms) is larger than that of the left T2 spectrum (T2 < 2.5 ms), indicating that the sample has good pore connectivity and belongs to the macroporous development sample. The B-type T2 spectrum is unimodal, and the pore connectivity is poor, indicating that it is a large-pore development sample. The T2 spectrum of the C-type sample is unimodal, and the pore connectivity is very poor, indicating that it is a mesoporous development sample. The T2 spectrum of the D-type sample shows a single peak state, and the main T2 is distributed within 0.1~2.5 ms. The pore connectivity is very poor, which indicates that it belongs to the small pore development type sample. (2) The single fractal model shows that, compared with other single fractal parameters, D2 increases with the increase in the T2 cut-off value, but the correlation is weak. Therefore, it is not feasible to predict the T2 cut-off value using the single fractal dimension parameter. (3) The multifractal model shows that D−10–D10 increases linearly with the increase in D−10–D0, but there is no obvious linear correlation between D0–D10 and D−10–D10, indicating that the low pore volume area in this kind of sample controls the overall heterogeneity of pore distribution. (4) The related parameters affecting the T2 cut-off value include D−10–D10, D−10/D10, D−10–D0, TM and D2. Therefore, based on the above five parameters, a T2 cut-off value prediction model is constructed. The T2 cut-off value calculated by the model is highly consistent with the experimental value, which proves the reliability of the model.

NJGCG: A node-based joint Gaussian copula graphical model for gene networks inference across multiple states

Inferring the interactions between genes is essential for understanding the mechanisms underlying biological processes. Gene networks will change along with the change of environment and state. The accumulation of gene expression data from multiple states makes it possible to estimate the gene networks in various states based on computational methods. However, most existing gene network inference methods focus on estimating a gene network from a single state, ignoring the similarities between networks in different but related states. Moreover, in addition to individual edges, similarities and differences between different networks may also be driven by hub genes. But existing network inference methods rarely consider hub genes, which affects the accuracy of network estimation. In this paper, we propose a novel node-based joint Gaussian copula graphical (NJGCG) model to infer multiple gene networks from gene expression data containing heterogeneous samples jointly. Our model can handle various gene expression data with missing values. Furthermore, a tree-structured group lasso penalty is designed to identify the common and specific hub genes in different gene networks. Simulation studies show that our proposed method outperforms other compared methods in all cases. We also apply NJGCG to infer the gene networks for different stages of differentiation in mouse embryonic stem cells and different subtypes of breast cancer, and explore changes in gene networks across different stages of differentiation or different subtypes of breast cancer. The common and specific hub genes in the estimated gene networks are closely related to stem cell differentiation processes and heterogeneity within breast cancers.

A promising sustainable green nanosilver formula for p-nitrophenol and methylene blue remediation from wastewater

In an attempt to create wastewater treatment “green” techniques that are both economically feasible and sustainable without using any dangerous chemicals, barley grain (Hordeum vulgare L.) water extract was used to phyto-synthesize silver nanoparticles (Ag°). Barley grains served as a natural reductant and stabilizer at the same time. The role of different synthesis conditions and their effect on the efficiency of the green synthesis process were studied and confirmed with characterization using several techniques (UV–vis, SEM, EDX, sizing distribution, and FTIR). The Ag°9 formula catalytic reduction was inspected against p-nitrophenol (PNP) and methylene blue (MB) as a model of nitroaromatic components and dyes, respectively. The removal studies were conducted using the target pollutants in a single or mixed liquid state. Remarkably, the Ag°9 particle size was around 20 nm, and its final concentration in the current formula was 2.2 × 10−7 mol L−1. The adsorption mechanism of the PNP and MB was pseudo-second order. The good fit with the pseudo-second-order kinetic model suggests that chemisorption occurs in the sorption process. The formula catalytic activity to remove PNP and MB was 99 and 66% at levels 60 and 500 µL from the Ag°9 formula, respectively, within less than 5 min.