Machine learning with active pharmaceutical ingredient/polymer interaction mechanism:Prediction for complex phase behaviors of pharmaceuticals and formulations

The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients(APIs)with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceutical formulations.In this work,a developed machine-learning model efficiently predicts the solubility of APIs in polymers by learning the phase equilibrium principle and using a few molecular descriptors.Under the few-shot learning framework,thermodynamic theory(perturbed-chain statistical associating fluid theory)was used for data augmentation,and computational chemistry was applied for molecular descriptors'screening.The results showed that the developed machine-learning model can predict the API-polymer phase diagram accurately,broaden the solubility data of APIs in polymers,and reproduce the relationship between API solubility and the interaction mechanisms between API and polymer successfully,which provided efficient guidance for the development of pharmaceutical formulations.

Strong metal–support interaction boosts the electrocatalytic hydrogen evolution capability of Ru nanoparticles supported on titanium nitride

Ruthenium(Ru)has been regarded as one of the most promising alternatives to substitute Pt for catalyzing alkaline hydrogen evolution reaction(HER),owing to its inherent high activity and being the cheapest platinum-group metal.Herein,based on the idea of strong metal–support interaction(SMSI)regulation,Ru/TiN catalysts with different degrees of TiN overlayer over Ru nanoparticles were fabricated,which were applied to the alkaline electrolytic water.Characterizations reveal that the TiN overlayer would gradually encapsulate the Ru nanoparticles and induce more electron transfer from Ru nanoparticles to TiN support by the Ru–N–Ti bond as the SMSI degree increased.Further study shows that the exposed Ru–TiN interfaces greatly promote the H_(2) desorption capacity.Thus,the Ru/TiN-300 with a moderate SMSI degree exhibits excellent HER performance,with an overpotential of 38 mV at 10 mA cm^(−2).Also,due to the encapsulation role of TiN overlayer on Ru nanoparticles,it displays super long-term stability with a very slight potential change after 24 h.This study provides a deep insight into the influence of the SMSI effect between Ru and TiN on HER and offers a novel approach for preparing efficient and stable HER electrocatalysts through SMSI engineering.

Electrostatic Interaction-directed Construction of Hierarchical Nanostructured Carbon Composite with Dual Electrical Conductive Networks for Zinc-ion Hybrid Capacitors with Ultrastability

Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.

Biological Interaction and Imaging of Ultrasmall Gold Nanoparticles

Ultrasmall gold nanoparticles(AuNPs)typically includes atomically precise gold nanoclusters(AuNCs)and AuNPs with a core size below 3 nm.Serving as a bridge between small molecules and traditional inorganic nanoparticles,the ultrasmall AuNPs show the unique advantages of both small molecules(e.g.,rapid distribution,renal clearance,low non-specific organ accumulation)and nanoparticles(e.g.,long blood circulation and enhanced permeability and retention effect).The emergence of ultrasmall AuNPs creates significant opportunities to address many challenges in the health field including disease diagnosis,monitoring and treatment.Since the nano–bio interaction dictates the overall biological applications of the ultrasmall AuNPs,this review elucidates the recent advances in the biological interactions and imaging of ultrasmall AuNPs.We begin with the introduction of the factors that influence the cellular interactions of ultrasmall AuNPs.We then discuss the organ interactions,especially focus on the interactions of the liver and kidneys.We further present the recent advances in the tumor interactions of ultrasmall AuNPs.In addition,the imaging performance of the ultrasmall AuNPs is summarized and discussed.Finally,we summarize this review and provide some perspective on the future research direction of the ultrasmall AuNPs,aiming to accelerate their clinical translation.

FINITE ELEMENT ANALYSIS FOR CONSOLIDATION IN INTERACTION BETWEEN STRUCTURE AND SATURATED SOIL FOUNDATION

The consolidation analysis of interaction between structure and saturated soil foundation is discussed. With the use of substructure technique, the structure is condensed onto the interface of the soil, and then the consolidation governing equations to describe the interaction between soil and structure are derived, The solution with non-iterative algorithm is proposed in this paper. The pressure Master-Slave relation method is used to deal with the non-permeability conditions on soil boundaries. A numerical example is illustrated. Based on this paper, the interactive consolidation analysis between large structure and soil has been more practical.

A Prediction-Based Multi-Objective VM Consolidation Approach for Cloud Data Centers

Virtual machine(VM)consolidation aims to run VMs on the least number of physical machines(PMs).The optimal consolidation significantly reduces energy consumption(EC),quality of service(QoS)in applications,and resource utilization.This paper proposes a prediction-basedmulti-objective VMconsolidation approach to search for the best mapping between VMs and PMs with good timeliness and practical value.We use a hybrid model based on Auto-Regressive Integrated Moving Average(ARIMA)and Support Vector Regression(SVR)(HPAS)as a prediction model and consolidate VMs to PMs based on prediction results by HPAS,aiming at minimizing the total EC,performance degradation(PD),migration cost(MC)and resource wastage(RW)simultaneously.Experimental results usingMicrosoft Azure trace show the proposed approach has better prediction accuracy and overcomes the multi-objective consolidation approach without prediction(i.e.,Non-dominated sorting genetic algorithm 2,Nsga2)and the renowned Overload Host Detection(OHD)approaches without prediction,such as Linear Regression(LR),Median Absolute Deviation(MAD)and Inter-Quartile Range(IQR).

Ecological network analysis reveals complex responses of tree species life stage interactions to stand variables

Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.

Study of the Relationship Between New Ionic Interaction Parameters and Salt Solubility in Electrolyte Solutions Based on Molecular Dynamics Simulation

Studying the relationship between ionic interactions and salt solubility in seawater has implications for seawater desalination and mineral extraction.In this paper,a new method of expressing ion-to-ion interaction is proposed by using molecular dynamics simulation,and the relationship between ion-to-ion interaction and salt solubility in a simulated seawater water-salt system is investigated.By analyzing the variation of distance and contact time between ions in an electrolyte solution,from both spatial and temporal perspectives,new parameters were proposed to describe the interaction between ions:interaction distance(ID),and interaction time ratio(ITR).The best correlation between characteristic time ratio and solubility was found for a molar ratio of salt-to-water of 10:100 with a correlation coefficient of 0.96.For the same salt,a positive correlation was found between CTR and the molar ratio of salt and water.For type 1-1,type 2-1,type 1-2,and type 2-2 salts,the correlation coefficients between CTR and solubility were 0.93,0.96,0.92,and 0.98 for a salt-to-water molar ratio of 10:100,respectively.The solubility of multiple salts was predicted by simulations and compared with experimental values,yielding an average relative deviation of 12.4%.The new ion-interaction parameters offer significant advantages in describing strongly correlated and strongly hydrated electrolyte solutions.

Urban Freight Consolidation Model for Post-Hauler Planning

Freight transportation in urban areas has increased significantly in a shorter period due to the widespread use of e-commerce, fast delivery, and population growth. Recently, a noticeable government initiative aimed at creating an effective, acceptable, and sustainable city logistics policy. This paper examines freight consolidation as a transportation strategy for optimizing last-mile delivery costs. Freight consolidation involves combining smaller shipments from various origins into a single, larger shipment for more efficient transportation to a common destination. This approach is particularly beneficial for last-mile delivery, where frequent deliveries of smaller quantities are frequently visible. Finally, we provide an illustrative example targeting urban freight stakeholders for practicing possible consolidation methodology. The result in the illustrative example shows that freight with 3-day consolidation, despite the delay penalty, is cheaper than daily shipping, and both are cheaper than 2-day consolidated shipping. The study will benefit urban businesses and freight services.

Consolidation of high replacement ratio stone column-reinforced ground:Analytical solutions incorporating clogging effect

The utilization of stone columns has emerged as a popular ground improvement strategy,whereas the drainage performance can be adversely hampered by clogging effect.Despite the ample progress of calculation methods for the consolidation of stone column-improved ground,theoretical investigations into the clogging effect have not been thoroughly explored.Furthermore,it is imperative to involve the column consolidation deformation to mitigate computational error on the consolidation of composite ground with high replacement ratios.In this context,an analytical model accounting for the initial clogging and coupled time and depth-dependent clogging of stone columns is established.Then,the resulting governing equations and analytical solutions are obtained under a new flow continuity relationship to incorporate column consolidation deformation.The accuracy and reliability of the proposed model are illustrated by degradation analysis and case studies with good agreements.Subsequently,the computed results of the current study are juxtaposed against the existing models,and an in-depth assessment of the impacts of several crucial parameters on the consolidation behavior is conducted.The results reveal that ignoring column consolidation deformation leads to an overestimate of the consolidation rate,with maximum error reaching up to 16%as the replacement ratio increases.Furthermore,the initial clogging also has a significant influence on the consolidation performance.Additionally,the increment of depth and time-clogging factors a and b will induce a noticeable retardation of the consolidation process,particularly in the later stage.

Interatomic Interaction Models for Magnetic Materials:Recent Advances

Atomistic modeling is a widely employed theoretical method of computational materials science.It has found particular utility in the study of magnetic materials.Initially,magnetic empirical interatomic potentials or spinpolarized density functional theory(DFT)served as the primary models for describing interatomic interactions in atomistic simulations of magnetic systems.Furthermore,in recent years,a new class of interatomic potentials known as magnetic machine-learning interatomic potentials(magnetic MLIPs)has emerged.These MLIPs combine the computational efficiency,in terms of CPU time,of empirical potentials with the accuracy of DFT calculations.In this review,our focus lies on providing a comprehensive summary of the interatomic interaction models developed specifically for investigating magnetic materials.We also delve into the various problem classes to which these models can be applied.Finally,we offer insights into the future prospects of interatomic interaction model development for the exploration of magnetic materials.

Effect of particle composition and consolidation degree on the wave-induced liquefaction of soil beds

The wave-induced liquefaction of seabed is responsible for causing damage to marine structures.Particle composition and consolidation degree are the key factors affecting the pore water pressure response and liquefaction behavior of the seabed under wave action.The present study conducted wave flume experiments on silt and silty fine sand beds with varying particle compositions.Furthermore,a comprehensive analysis of the differences and underlying reasons for liquefaction behavior in two different types of soil was conducted from both macroscopic and microscopic perspectives.The experimental results indicate that the silt bed necessitates a lower wave load intensity to attain the liquefaction state in comparison to the silty fine sand bed.Additionally,the duration and development depth of liquefaction are greater in the silt bed.The dissimilarity in liquefaction behavior between the two types of soil can be attributed to the variation in their permeability and plastic deformation capacity.The permeability coefficient and compression modulus of silt are lower than those of silty fine sand.Consequently,silt is more prone to the accumulation of pore pressure and subsequent liquefaction under external loading.Prior research has demonstrated that silt beds with varying consolidation degrees exhibit distinct initial failure modes.Specifically,a dense bed undergoes shear failure,whereas a loose bed experiences initial liquefaction failure.This study utilized discrete element simulation to examine the microscopic mechanisms that underlie this phenomenon.

Resistive field generation in intense proton beam interaction with solid targets

The Brown-Preston-Singleton(BPS)stopping power model is added to our previously developed hybrid code to model ion beam-plasma interaction.Hybrid simulations show that both resistive field and ion scattering effects are important for proton beam transport in a solid target,in which they compete with each other.When the target is not completely ionized,the self-generated resistive field effect dominates over the ion scattering effect.However,when the target is completely ionized,this situation is reversed.Moreover,it is found that Ohmic heating is important for higher current densities and materials with high resistivity.The energy fraction deposited as Ohmic heating can be as high as 20%-30%.Typical ion divergences with half-angles of about 5°-10°will modify the proton energy deposition substantially and should be taken into account.

Isotope Tracking of Surface Water Groundwater Interaction in the Beninese Part of the Iullemeden Aquifer System

The Kandi basin is located in northeast Benin (West Africa). This study is focused on the estimation of water fluxes exchanged between the river Niger (and its tributaries) and the transboundary Iullemeden Aquifer System. In that framework, an innovative approach based on the application of the Bayesian Mixing Model (MixSIAR) analysis on water isotopes (oxygen-18, deuterium and tritium) was performed. Moreover, to assess the relevance of the model outputs, Pearson’s correlation and Principal Component Analysis (PCA) have been done. A complex relationship between surface water and groundwater has been found. Sixty percent (60%) of groundwater samples are made of more than 70% river water and rainwater;while 31.25% of surface water samples are made of about 84% groundwater. To safeguard sustainable water resources for the well-being of the local communities, surface water and groundwater must be managed as a unique component in the Kandi basin.

Numerical investigation of the effects of soil-structure and granular material-structure interaction on the seismic response of a flat-bottom reinforced concrete silo

In this work,a numerical study of the effects of soil-structure interaction(SSI)and granular material-structure interaction(GSI)on the nonlinear response and seismic capacity of flat-bottomed storage silos is conducted.A series of incremental dynamic analyses(IDA)are performed on a case of large reinforced concrete silo using 10 seismic recordings.The IDA results are given by two average IDA capacity curves,which are represented,as well as the seismic capacity of the studied structure,with and without a consideration of the SSI while accounting for the effect of GSI.These curves are used to quantify and evaluate the damage of the studied silo by utilizing two damage indices,one based on dissipated energy and the other on displacement and dissipated energy.The cumulative energy dissipation curves obtained by the average IDA capacity curves with and without SSI are presented as a function of the base shear,and these curves allow one to obtain the two critical points and the different limit states of the structure.It is observed that the SSI and GSI significantly influence the seismic response and capacity of the studied structure,particularly at higher levels of PGA.Moreover,the effect of the SSI reduces the damage index of the studied structure by 4%.

Temporal trends and cohort variations of gender-specific major depressive disorders incidence in China:analysis based on the age-period-cohortinteraction model

Background Major depressive disorders(MDDs)impose substantial burdens on individuals and society;however,further detailed analysis is still needed for its long-term trends.Aims This study aimed to analyse the gender-specific temporal trends and cohort variations of MDD incidence among Chinese residents over the past three decades.Methods Employing the age-period-cohort-interaction model and leveraging data from the Global Burden of Disease Study 2019,this research identified and analysed incidence trends of MDD among Chinese males and females aged 5-94 years from 1990 to 2019 across three dimensions,encompassing age,period and birth cohort.Results The analysis reveals age-related effects,indicating heightened MDD risk among adolescents and older adults.Specifically,individuals entering the older adulthood at the age of 65-69 significantly increased the risk of MDD by 64.9%.People aged 90-94 years witnesseda 105.4%increase in MDD risk for the overall population,with females and males in this age group experiencing a 75.1%and 103.4%increase,respectively.In terms of period effects,the risk of MDD displayed a decline from 1990 to 1994,followed by a rebound in 2008.Cohort effects demonstrated diverse generational patterns,with generationⅠand generationⅢmanifesting opposing‘age-as-level'trends.GenerationⅡand generationⅣexhibited'cumulative disadvantage'and'cumulative advantage'patterns,respectively.Age effects indicated an overall higher risk of MDD incidence in females,while cohort effects showed greater variations of MDD incidence among females.Conclusions The study underscores the substantial effects of age,period and cohort on MDD across genders in China.Priority interventions targeting vulnerable populations,including children,adolescents,older adults,females and the post-millennium birth cohort,are crucial to mitigate the impact of MDD.

Dynamical nonlinear excitations induced by interaction quench in a two-dimensional box-trapped Bose-Einstein condensate

Manipulating nonlinear excitations,including solitons and vortices,is an essential topic in quantum many-body physics.A new progress in this direction is a protocol proposed in[Phys.Rev.Res.2043256(2020)]to produce dark solitons in a one-dimensional atomic Bose–Einstein condensate(BEC)by quenching inter-atomic interaction.Motivated by this work,we generalize the protocol to a two-dimensional BEC and investigate the generic scenario of its post-quench dynamics.For an isotropic disk trap with a hard-wall boundary,we find that successive inward-moving ring dark solitons(RDSs)can be induced from the edge,and the number of RDSs can be controlled by tuning the ratio of the after-and before-quench interaction strength across different critical values.The role of the quench played on the profiles of the density,phase,and sound velocity is also investigated.Due to the snake instability,the RDSs then become vortex–antivortex pairs with peculiar dynamics managed by the initial density and the after-quench interaction.By tuning the geometry of the box traps,demonstrated as polygonal ones,more subtle dynamics of solitons and vortices are enabled.Our proposed protocol and the discovered rich dynamical effects on nonlinear excitations can be realized in near future cold-atom experiments.

Dzyaloshinskii–Moriya interaction and field-free sub-10 nm topological magnetism in Fe/bismuth oxychalcogenides heterostructures

Topological magnetism with strong robustness,nanoscale dimensions and ultralow driving current density(106 A/m^(2))is promising for applications in information sensing,storage,and processing,and thus sparking widespread research interest.Exploring candidate material systems with nanoscale size and easily tunable properties is a key for realizing practical topological magnetism-based spintronic devices.Here,we propose a class of ultrathin heterostructures,Fe/Bi_(2)O_(2)X(X=S,Se,Te)by deposing metal Fe on quasi-two-dimensional(2D)bismuth oxychalcogenides Bi_(2)O_(2)X(X=S,Se,Te)with excellent ferroelectric/ferroelastic properties.Large Dzyaloshinskii–Moriya interaction(DMI)and topological magnetism can be realized.Our atomistic spin dynamics simulations demonstrate that field-free vortex–antivortex loops and sub-10 nm skyrmions exist in Fe/Bi_(2)O_(2)S and Fe/Bi_(2)O_(2)Se interfaces,respectively.These results provide a possible strategy to tailor topological magnetism in ultrathin magnets/2D materials interfaces,which is extremely vital for spintronics applications.

The Gravitational Interaction between Moving Mass Particles Explained by the Theory of Informatons

In the article “Newtons Law of Universal Gravitation Explained by the Theory of Informatons” the gravitational interaction between mass particles at rest has been explained by the hypothesis that g-information carried by informatons is the substance of the medium that the interaction in question makes possible. It has been showed that, on the macroscopic level, that medium—the “gravitational field”—manifests itself as the vector field Eg. In this article we will deduce from the postulate of the emission of informatons, that the informatons emitted by a moving mass particle carry not only information about the position (g-information) but also about the velocity (“β-information”) of their emitter. It follows that the gravitational field of a moving mass particle is a dual entity always having a field- and an induction-component (Egand Bg) simultaneously created by their common sources: time-variable masses and mass flows and that the gravitational interaction is the effect of the fact that an object in a gravitational field always tends to become “blind” for that field by accelerating according to a Lorentz-like law.

Dynamics of Non-Markovianity, Quantum Correlations and Information Scrambling of Three Qubits Systems Interacting via Rashba Interaction

The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate between their upper and lower bounds, where the number of oscillations increases as the Rashba interaction strength increases. The exchanging rate of these three quantities depends on the Rashba strength, and whether the entangled state is generated via direct/indirect interaction. Moreover, the coherence parameter can be used as a control parameter to maximize or minimize the three physical quantities.