Multilevel Structure Research Articles

Preparation of superhydrophobic membranes with ultraviolet‐absorbing capacity for oil–water separation by electrospinning

AbstractTo address the escalating issue of oily wastewater, separation membranes with special wettability on the surface are widely used in oil–water separation. The development of separation membranes with not only stable separation flux but also anti‐fouling properties is an urgent problem. Therefore, polystyrene/polyacrylonitrile‐polyvinylidene fluoride/polydimethylsiloxane‐titanium dioxide nanoparticle (PS/PAN‐PVDF/PDMS@TiO2) composite membranes with superhydrophobicity and lipophilicity were prepared by electrospinning technique. By changing the doping amount of TiO2 nanoparticles, the multilevel rough structure was constructed on the surface, and the transformation of the Ti–O–C chemical bond to the Si–O–Ti chemical bond was realized inside the composite membrane. The results showed that the composite membrane had excellent superhydrophobicity (154.9°) and mechanical properties (tensile strength of 3.54 MPa, elongation of 60.95%). The membrane can absorb ultraviolet light and exhibits enhanced resistance to fouling when exposed to visible‐UV light. Additionally, the composite membrane demonstrates an adsorption capacity of 30–100 g/g for a wide range of oils. In corrosive environments, the composite membrane maintains superhydrophobicity (above 150°) and achieves high oil–water separation efficiency (97%). After 40 cycles, the separation flux of 6000 L.h−1 m−2 can be maintained. Hence, superhydrophobic oleophilic composite membranes with a stable separation flux and resistance to fouling can be employed in the field of oil–water separation.Highlights PS/PAN‐PVDF/PDMS@TiO2 composite membrane with multilevel rough structure. PS/PAN‐PVDF/PDMS@TiO2 composite membrane with excellent UV absorption and self‐cleaning ability. PS/PAN‐PVDF/PDMS@TiO2 composite membrane with stable oil–water separation efficiency in harsh environments.

The Multilevel Factor Structure of Social Cohesion, Mutual Efficacy, and Informal Social Control: A Case for Practice-Informed Research.

Collective efficacy is the process by which social cohesion is activated as informal social control. Mutual efficacy, the perceived capability of the community, mediates the relationship between the two constructs. Interventions based on collective efficacy have a positive impact on individuals but are limited in their ability to affect the broader community. A possible explanation for this finding is that community-level theories operate differently at the individual and neighborhood levels. The present study contributes to the literature by testing the multilevel factor structure of social cohesion, mutual efficacy, and informal social control. Findings suggest that multiple-factor structures demonstrate adequate model fit. However, the three-factor model is most consistent with social work theory and practice. Social workers can foster constructive dialogue to build social cohesion, authentically engage residents to build mutual efficacy, and train residents in skills necessary to institute informal social control.

HIFINet: Examination-Diagnosis-Treatment Hierarchical Feedback Interaction Network for Medication Recommendation

Medication combination recommendation is critical in clinic, since accurately predicting therapeutic drug can provide essential decision support to physicians. However, current approaches do not consider the multilevel structure of electronic health record (EHR) data or the hierarchical dependencies between multiple visits, leading to suboptimal recommendations. To address these limitations, we propose a novel hierarchical feedback interaction network (HIFINet) to utilize an examination-diagnosis-treatment hierarchical network for modeling the inherent multilevel structure of EHR data. The feedback long short-term memory network called FeLSTM, which is the basic unit of our hierarchical network, performs hierarchical interactions and leverages change information as feedback to propagate forward among different levels. Additionally, HIFINet contains four modules. First, an embedding module is designed to learn the health information representation of patients. Second, a three-layer time-series learning module is employed to capture temporal dependencies within each sequence. Next, a differential feedback interaction module is developed to capture the difference features between visits. Finally, an attention fusion module is used to learn a comprehensive representation of the patient’s health information and to recommend next multiple treatment medications. HIFINet is compared with state-of-the-art approaches on a real-world dataset. The results indicate that HIFINet outperforms other approaches, offering more accurate recommendations.

Bias-Adjusted Three-Step Multilevel Latent Class Modeling with Covariates

We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ignoring the multilevel structure, (2) assigning units to latent classes, and (3) fitting the multilevel model with the covariates while controlling for measurement error introduced in the second step. Simulation studies and an empirical example show that the three-step method is a legitimate modeling option compared to the existing one-step and two-step methods.

Laser-Induced Skin-like Flexible Pressure Sensor for Artificial Intelligence Speech Recognition.

Skin-like flexible pressure sensors with good sensing performance have great application potential, but their development is limited owing to the need for multistep, high-cost, and low-efficiency preparation processes. Herein, a simple, low-cost, and efficient laser-induced forming process is proposed for the first time to prepare a skin-like flexible piezoresistive sensor. In the laser-induced forming process, based on the photothermal effect of graphene and the foaming effect of glucose, a skin-like polydimethylsiloxanes (PDMS) film with porous structures and surface protrusions is obtained by using infrared laser irradiation of the glucose/graphene/PDMS prepolymer film. Further, based on the skin-like PDMS film with a graphene conductive layer, a new skin-like flexible piezoresistive sensor is obtained. Due to the stress concentration caused by the surface protrusions and the low stiffness caused by the porous structures, the flexible piezoresistive sensor realizes an ultrahigh sensitivity of 1348 kPa-1 at 0-2 kPa, a wide range of 200 kPa, a fast response/recovery time of 52 ms/35 ms, and good stability over 5000 cycles. The application of the sensor to the detection of human pulses and robot clamping force indicates its potential for health monitoring and soft robots. Furthermore, in combination with the neural network (CNN) algorithm in artificial intelligence technology, the sensor achieves 95% accuracy in speech recognition, which demonstrates its great potential for intelligent wearable electronics. Especially, the laser-induced forming process is expected to facilitate the efficient, large-scale preparation of flexible devices with multilevel structures.

A self-assembled 3D nanoflowers based nano-ELISA platform for the sensitive detection of pyridaben

Biomimetic methods are invariably employed to synthesize hybrid organic–inorganic multilevel structure nanoflowers with self-assembly processes in aqueous solutions, which is an ideal way to meet the challenges of immobilizing antibodies or enzymes in nanomaterial based enzyme-linked immunosorbent assay (nano-ELISA). In this study, we developed protein-inorganic hybrid 3D nanoflowers composed of bovine serum albumin (BSA), horseradish peroxidase (HRP)-conjugated goat anti-mouse IgG (IgG-HRP) and copper(Ⅱ) phosphate (BSA-(IgG-HRP)-Cu3(PO4)2) using a self-assembly biomimetic method. The preparation process avoided the use of any organic solvent and protein immobilization did not require covalent modifications. Additionally, the unique hierarchical structure enhances the thermal and storage stability of HRP. The BSA-(IgG-HRP)-Cu3(PO4)2 hybrid 3D nanoflower was then applied to a nano-ELISA platform for pyridaben detection, achieving a 50% inhibition concentration of 3.90 ng mL−1. The nano-ELISA achieved excellent accuracy for pyridaben detection. Such a novel BSA-(IgG-HRP)-Cu3(PO4)2 hybrid 3D nanoflower provide an excellent reagent for small molecule immunoassay.

A total distance ranking approach to fuzzy AHP-based MCDM method for selecting sustainable manufacturing facility location

Selecting a sustainable facility location is a crucial strategy for manufacturing companies to achieve long-term success in today’s competitive environment. Various quantitative and qualitative criteria with different importance in a multiple level structure must be considered and aggregated to assist the company in decision-making. How to determine these criteria weights and select the sustainable manufacturing facility locations have become research questions. To resolve this problem, this paper proposes a total distance ranking approach to fuzzy analytic hierarchical process (AHP)-based multiple criteria decision-making (MCDM) method. Currently, the membership functions of fuzzy weighted ratings in the MCDM with a multilevel structure cannot be developed. A ranking method is needed to defuzzify those fuzzy numbers used for fuzzy AHP and qualitative criteria in the MCDM for better executing decision-making procedure. The total distance ranking method related to the centroid on x-axis, centroid on y-axis and the distances of centroids point to the two tangent lines of a fuzzy number are considered in the proposed ranking approach. Formulas of the proposed approach will be presented, and some properties will be investigated to derive formulas for trapezoidal and triangular fuzzy numbers. A comparison with relevant ranking methods will be made to show the advantages of the proposed ranking approach. The proposed ranking approach is then applied to defuzzify the fuzzy numbers used in fuzzy AHP and linguistic values under qualitative criteria to obtain the criteria weights under multi-level structure and crisp values under qualitative criteria, respectively. The final scores of alternatives can be obtained by aggregating crisp criteria values and their corresponding weights by simple additive weighting method to obtain the ranking result. A numerical example will be conducted to show the effectiveness of the proposed model. Finally, a comparison with Best-Worst method (BWM) will be presented to show the persuasiveness of the proposed method.

Federalism, Decentral Governance, and Joint Decision-Making: Bad News for the Implementation of International Environmental Agreements?

Abstract There is a lingering myth in the international compliance literature that domestic multilevel structures have a negative impact on the fulfilment of international commitments. This article argues that this literature has failed to understand multilevel structures as a multi-layered concept. Instead of viewing multilevel governance as a one-dimensional concept or a mere system of veto-players, I propose to study the effects of the individual components, i.e., federalism, decentral governance, and joint decision-making. I test the plausibility of this approach by analyzing the implementation of the Ramsar Wetlands Convention. My findings debunk the myth about the negative effects of multilevel structures on the implementation of international agreements. I show that states in which subnational decision-makers can act autonomously from the central level are better placed to produce implementation measures in the area of environmental conservation.

The impact of different data handling strategies in exploratory and confirmatory factor analysis of diary measures: an evaluation using simulated and real-world asthma nighttime symptoms diary data

ABSTRACT Background Daily diaries are an important modality for patient-reported outcome assessment. They typically comprise multiple questions, so understanding their underlying structure is key to appropriate analysis and interpretation. Structural evaluation of such measures poses challenges due to the high volume of repeated measurements. Potential strategies include selecting a single day, averaging item-level observations over time, or using all data while accounting for its multilevel structure. Method The above strategies were evaluated in a simulated dataset via exploratory and confirmatory factor modelling by comparing their impact on various estimates (i.e., inter-item correlations, factor loadings, model fit). Each strategy was additionally explored using real-world data from an observational study (the Asthma Nighttime Symptoms Diary). Results Both single day and item average strategies resulted in biased factor loadings. The former displayed lower overall bias (single day: 0.064; item average: 0.121) and mean square error (single day: 0.007; item average: 0.016) but greater frequency of incorrect factor number identification compared with the latter (single day: 46.4%; item average: 0%). Increased estimated inter-item correlations were apparent in the item-average method. Non-trivial between- and within-person variance highlighted the utility of a multilevel approach. However, convergence issues and Heywood cases were more common under the multilevel approach (90.2% and 100.0%, respectively). Conclusions Our findings suggest that a multilevel approach can enhance our insight when evaluating the structural properties of daily diary data; however, implementation challenges still remain. Our work offers guidance on the impact of data handling decisions in diary assessment.

Cyclable Variable Path Length Multilevel Structures for Lossless Ion Manipulations (SLIM) Platform for Enhanced Ion Mobility Separations.

Ion mobility-mass spectrometry (IMS-MS) is used to analyze complex samples and provide structural information on unknown compounds. As the complexity of samples increases, there is a need to improve the resolution of IMS-MS instruments to increase the rate of molecular identification. This work evaluated a cyclable and variable path length (and hence resolving power) multilevel Structures for Lossless Ion Manipulations (SLIM) platform to achieve a higher resolving power than what was previously possible. This new multilevel SLIM platform has eight separation levels connected by ion escalators, yielding a total path length of ∼88 m (∼11 m per level). Our new multilevel SLIM can also be operated in an "ion cycling" mode by utilizing a set of return ion escalators that transport ions from the eighth level back to the first, allowing even extendable path lengths (and higher IMS resolution). The platform has been improved to enhance ion transmission and IMS separation quality by reducing the spacing between SLIM boards. The board thickness was reduced to minimize the ions' escalator residence time. Compared to the previous generation, the new multilevel SLIM demonstrated better transmission for a set of phosphazene ions, especially for the low-mobility ions. For example, the transmission of m/z 2834 ions was improved by a factor of ∼3 in the new multilevel SLIM. The new multilevel SLIM achieved 49% better resolving powers for GRGDS1+ ions in 4 levels than our previous 4-level SLIM. The collision cross-section-based resolving power of the SLIM platform was tested using a pair of reverse sequence peptides (SDGRG1+, GRGDS1+). We achieved 1100 resolving power using 88 m of path length (i.e., 8 levels) and 1400 following an additional pass through the eight levels. Further evaluation of the multilevel SLIM demonstrated enhanced separation for positively and negatively charged brain total lipid extract samples. The new multilevel SLIM enables a tunable high resolving power for a wide range of ion mobilities and improved transmission for low-mobility ions.

Single-Shot Readout of a Solid-State Electron Spin Qutrit.

Quantum systems usually feature a rich multilevel structure with promising resources for developing superior quantum technologies compared with their binary counterpart. Single-shot readout of these high-dimensional quantum systems is essential for exploiting their potential. Although there have been various high-spin systems, the single-shot readout of the overall state of high-spin systems remains a challenging issue. Here we demonstrate a reliable single-shot readout of spin qutrit state in a low-temperature solid-state system utilizing a binary readout scheme. We achieve a single-shot readout of an electron spin qutrit associated with a single nitrogen-vacancy center in diamond with an average fidelity of 87.80%. We use this spin qutrit system to verify quantum contextuality, a fundamental test of quantum mechanics. We observe a violation of the noncontextual hidden variable inequality with the developed single-shot readout in contrast to the conventional binary readout. These results pave the way for developing quantum information processing based on spin qutrits.

Multilevel dimension-independent likelihood-informed MCMC for large-scale inverse problems

We present a non-trivial integration of dimension-independent likelihood-informed (DILI) MCMC (Cui et al 2016) and the multilevel MCMC (Dodwell et al 2015) to explore the hierarchy of posterior distributions. This integration offers several advantages: First, DILI-MCMC employs an intrinsic likelihood-informed subspace (LIS) (Cui et al 2014)—which involves a number of forward and adjoint model simulations—to design accelerated operator-weighted proposals. By exploiting the multilevel structure of the discretised parameters and discretised forward models, we design a Rayleigh–Ritz procedure to significantly reduce the computational effort in building the LIS and operating with DILI proposals. Second, the resulting DILI-MCMC can drastically improve the sampling efficiency of MCMC at each level, and hence reduce the integration error of the multilevel algorithm for fixed CPU time. Numerical results confirm the improved computational efficiency of the multilevel DILI approach.

Family in Crisis: Do Halfway Houses Perform Better Than Families with Expressed Emotion toward Patients with Schizophrenia? A Direct Adjusted Comparison

Expressed emotion (EE) toward patients with schizophrenia is typically reported to be lower in psychiatric halfway houses than in families. This is the first study directly comparing EE between these settings and investigating the pathways mediating EE differences. We included 40 inpatients in halfway houses and 40 outpatients living with their families and recorded 22 psychiatric nurses’ and 56 parents’ EE, respectively, through Five Minutes Speech Samples. Each inpatient was rated by 2–5 nurses and each outpatient by 1–2 parents. As EE ratings had a multilevel structure, generalized linear mixed models were fitted, adjusting for patient-related confounders and caregiver demographics. Mediatory effects were investigated in multilevel structural equation models. Outpatients were younger, less chronic, and better educated, with higher negative symptoms and perceived criticism than inpatients. Nurses were younger and better educated than parents. Before adjustment, EE rates were equally high across settings. After adjusting for patient-related confounders, emotional overinvolvement was significantly higher in parents. However, after also adjusting for caregiver demographics, only criticism was significantly higher in nurses. Patients’ age, negative symptoms, and perceived criticism and caregivers’ age and sex significantly mediated EE group differences. Our findings highlight pathways underlying EE differences between halfway houses and families and underscore the importance of staff and family psychoeducation.

Multilevel sociality in the spotted hyaena: How to live in large groups without falling prey to the infertility trap

AbstractSpotted hyaenas live in unusually large social groups for a carnivore. Since, all else equal, the ‘infertility trap’ (a negative relationship between fertility and the number of females in a group) limits social group sizes to ~5 reproductive females in mammals, hyaena must, like other very social species, have found a way to mitigate the stresses involved in order to do so. From a comparative analysis of data from 19 well‐studied Crocuta crocuta populations, I show (1) that the distribution of hyaena clan sizes is multimodal, with a fractal scaling ratio close to 3 and a base unit of 12–15 individuals (3–5 reproductive females), (2) that fertility is a negative function of number of females in the group and (3) that there is a trade‐off between the benefits of having more males in the group and the costs incurred by having more females. Although females do buffer themselves against the infertility trap by forming matrilineal alliances (thereby creating a primate‐like multilevel structure), males seem to play an important role, such that, in areas with a low density of males, clan sizes are much smaller.

A sequential three-way decision model for classification with multilevel information gain and regret value optimization

The sequential three-way decision (S3WD) model plays a vital role in solving classification problems. This model comprises three fundamental elements, namely, conditional probability, cost function, and decision thresholds. The typical conditional probability estimation methods are bifurcated into two branches: equivalence class-based methods, which coincide with human recognition, and machine learning-based methods that rely on big data for high precision. This study synergizes two branches by introducing a novel algorithm that integrates the K-nearest neighbor method and Bayes rule for estimating conditional probabilities, enhancing both interpretability and precision. Regarding the cost function and decision thresholds, the inherent weak point in existing cost-sensitive S3WD models is the computation of three pairwise adjacent regions with subjectively given cost values and decision thresholds. To overcome the subjective arbitrariness bottleneck, an objective function is established by extending the definitions of information gain and regret value across a multilevel granularity structure. Subsequently, an adapted particle swarm optimization algorithm is utilized to optimize the decision thresholds and tri-partitions. Accordingly, a novel framework of the S3WD model is constructed. Finally, extensive experimental results substantiate the effectiveness and superiority of the proposed model in the realm of classification, as evidenced from both technical and empirical standpoints.

Multiscale modelling for the thermal transport behaviour of ceramic matrix composites with hierarchical structures

Ceramic matrix composites contain many initial defects due to their “ceramic” properties and process characteristics, which presents challenges for the accurate prediction of their material equivalent properties. In this paper, multiscale and high-fidelity modelling of fibre-reinforced C/SiC composites are carried out on a “macro-meso-micro” cross-scale, and the thermal conductivity and relative thermal conductivity of multilevel structure composites based on a hierarchical multiscale model are proposed. The influence laws of SiC porous matrix, carbon fibre volume fraction and temperature on the thermal conductivity of composite materials are given. These findings provide useful insights into equivalent computational methods for material properties under the defect growth of thermomechanical loading.

Microcrack behavior in bone: Stress field analysis at osteon cement line tips.

Bone microstructure governs microcrack propagation complexity. Current research, relying on linear elastic fracture mechanics, inadequately considers authentic multi-level structures, like cement lines and osteons, impacting stress intensity at cracks. This study, by constructing models encompassing single or multiple osteons, delves into the influence of factors like crack length, osteon radius, and modulus ratio on the stress intensity factor at the crack tip. Employing a fracture mechanics phase-field approach to simulate crack propagation paths, it particularly explores the role of cement lines as weak interfaces in crack extension. The aim is to comprehensively and systematically elucidate the critical factors of bone microstructure in the context of crack propagation.

Differential correlates of criticism versus emotional overinvolvement towards patients with schizophrenia living in halfway houses or with their families

PurposeThis study systematically searched for differential correlates of criticism vs. emotional overinvolvement (EOI) towards patients with schizophrenia in families and halfway houses, which have only incidentally been reported in previous research. Identified patterns were compared across settings.MethodsWe included 40 inpatients with schizophrenia living in halfway houses and 40 outpatients living with their families and recorded the expressed emotion (EE) of 22 psychiatric nurses or 56 parents, respectively, through Five Minutes Speech Samples. Each nurse rated 1–12 inpatients and each inpatient was rated by 2–5 nurses. Each outpatient was rated by one or both parents. As EE ratings had a multilevel structure, weighted Spearman correlations of criticism and EOI with various patient- and caregiver-related characteristics were calculated and compared with Meng’s z-test.ResultsCriticism was weakly negatively correlated with EOI in nurses but negligibly in parents. Distinct patterns of significant differential correlates arose across settings. Outpatients’ aggressive behavior and parents’ related burden were mainly associated with higher criticism. Inpatients’ symptoms (agitation/aggression, negative and other psychotic symptoms) and nurses’ burnout (Depersonalization) were mainly associated with lower EOI. Inpatients’ perceived criticism and outpatients’ previous suicide attempts were equally associated with higher criticism and lower EOI (mirror correlations). Finally, various inpatient attributes (older age, chronicity, unemployment and smoking) triggered higher EOI only. Inpatients’ age, psychopathology (esp. agitation/aggression and negative symptoms) and perceived criticism survived adjustment for multiple comparisons.ConclusionOur findings suggest setting-specific pathogenetic pathways of criticism and EOI and might help customize psychoeducational interventions to staff and families.

Molecularly Detailed View of Strong Coupling in Supramolecular Plexcitonic Nanohybrids.

Plexcitons constitute a peculiar example of light-matter hybrids (polaritons) originating from the (strong) coupling of plasmonic modes and molecular excitations. Here we propose a fully quantum approach to model plexcitonic systems and test it against existing experiments on peculiar hybrids formed by Au nanoparticles and a well-known porphyrin derivative, involving the Q branch of the organic dye absorption spectrum. Our model extends simpler descriptions of polaritonic systems to account for the multilevel structure of the dyes, spatially varying interactions with a given plasmon mode, and the simultaneous occurrence of plasmon-molecule and intermolecular interactions. By keeping a molecularly detailed view, we were able to gain insights into the local structure and individual contributions to the resulting plexcitons. Our model can be applied to rationalize and predict energy funneling toward specific molecular sites within a plexcitonic assembly, which is highly valuable for designing and controlling chemical transformations in the new polaritonic landscapes.

A Hierarchical Energy Dissipated Structure Enabled Strong, Ultra‐Tough, and Sustainable Adhesives

AbstractSustainable adhesives with simultaneous high strength and excellent ductility are important but still challenging. Here, an epoxy adhesive with simultaneously strong, tough, and sustainable features by designing a new hierarchical energy‐dissipated cross‐linking structure is reported: an annular structure containing quadruple internal B─N coordination boronic esters (AQBN). Under small strain, the AQBN structure is rigid to enhance the tensile strength of the adhesive. With medium strain applied, its non‐coplanar ring and internal quadruple B─N coordination can orderly open, providing mechanical energy dissipation and excellent ductility. Therefore, this multilevel structure can endow epoxy adhesives with both high strength and toughness. Besides, the rapid dynamic exchange and internal B─N coordination in boronic esters enable the adhesives to have good sustainability and environmental tolerance, respectively. As a result, the epoxy adhesives exhibit simultaneous high adhesive strength (18.5 MPa), outstanding toughness (work of debonding of 29692 N m−1), good chemical/physical recyclability, and excellent environmental reliability (humidity, water, high/ultralow temperature, and organic solvents). This work provides a new strategy for balancing the strength, toughness, and sustainability of adhesives.