Integral Structure Research Articles

Mid-wave infrared transmittance filters in suspended GaAs subwavelength gratings

The high-Q resonances observed in subwavelength gratings support many applications, including optical phase arrays, refractive index sensing, enhancement of nonlinear effects, and spectral filtering. Integrating these functions with active devices opens new possibilities for microscale optical systems. GaAs high-contrast gratings (HCGs) simplify the integration of resonant structures with active III–V semiconductor devices. These structures are particularly useful in the mid-wave infrared (5–7 μm), overcoming several limitations of the material systems presented in previous works. By selectively removing an underlying AlGaAs layer, a high index contrast is introduced between suspended GaAs gratings and air without using an exotic low-index substrate. Furthermore, epitaxial growth enables precise device thickness. In this work, we demonstrate GaAs/air HCG transmittance filters for operation in the mid-wave infrared. A numerical study investigates the dependence of filter performance on substrate proximity. We fabricate experimental filters using an HBr-based plasma etch and a selective wet etch. Optical characterization demonstrates quality factors >50 and transmittance peak efficiency >50%. The observed filter performance is comparable to other mid-wave infrared subwavelength grating filters. This work concludes with discussion of experimental nonidealities, emphasizing the considerable influence of grating size and optical measurement conditions. The suspended GaAs HCG filters show potential for direct integration with active devices such as photodetectors and lasers.

Sensor Networks for Structures Health Monitoring: Placement, Implementations, and Challenges—A Review

The development of structural health monitoring (SHM) systems and their integration in actual structures has become a necessity as it can provide a robust and low-cost solution for monitoring the structural integrity of and the ability to predict the remaining life of structures. In this review, we aim at focusing on one of the important issues of SHM, the design, and implementation of sensor networks. Location and number of sensors, in any SHM system, are of high importance as they impact the system integration, system performance, and accuracy of assessment, as well as the total cost. Hence we are interested in shedding the light on the sensor networks as an essential component of SHM systems. The review discusses several important parameters including design and optimization of sensor networks, development of academic and commercial solutions, powering of sensors, data communication, data transmission, and analytics. Finally, we presented some successful case studies including the challenges and limitations associated with the sensor networks.

Integrated Photonic Structure Enhanced Infrared Photodetectors

The application fields of infrared photodetectors are quite extensive. Compared with traditional infrared photodetection materials such as IV and III–V semiconductors, newly emerging low‐dimensional materials and quantum materials (e.g., 2D materials and quantum wells) have many advantages in different aspects, such as wide spectral range, low dark current, room temperature operation, and high processing compatibility. However, the performance of photodetectors based on low‐dimensional materials is limited by the ultra small thicknesses, polarization selectivity, and the poor absorption efficiency. Therefore, improving the performance of infrared photodetectors based on low‐dimensional materials has been a focus research task in recent years. The integration of photonic structures can improve the performance of infrared photodetectors, such as enhancing absorption efficiency, reducing the volume of active materials, and increasing polarization selectivity. Herein, different kinds of photonic structure integrated infrared photodetectors, roughly divided into two categories, namely, dielectric photonic structure integrated ones and metallic photonic structure integrated ones, are reviewed. The active materials include 2D materials, quantum wells, quantum dots, and carbon nanotubes.

Cost-efficient and high precision method for the assembly of LN-based photonic crystal slabs on the fiber tip for the implementation of E-field sensors

Lab-on-fiber technology is an emerging topic for sensing cutting-edge technologies due to the high versatility and functionality that it offers when it is combined with different sensitive materials. A particular configuration, which consists of the integration of nanophotonic structures into the tip of a pigtailed fiber, allows the exploitation of light localization performances to produce high-performing sensors. However, integrating such tiny structures into the fiber facet requires complex and expensive procedures. In this work, we report a novel high precision assembly procedure that ensures the parallelism between the photonic chip and the fiber surface, in addition to the alignment with the light injection into the nanostructure. The integrated structure consists of an ultra-compact (19 μm × 19 μm) Photonic Crystal Slab (PCS) structure based on a 700 nm thin film of lithium niobate (LN) which is sensitive to external E-fields via the electro-optic effect. Thus, the assembled sensor detects electric fields, presenting great linearity and a sensitivity of 170 V/m. This technique shows a way to assemble compact planar nanostructures into fiber facets keeping high throughput, high precision, and relatively low costs.

Enterprise integration and formation of cluster structures in the field of food sector

Enterprise integration and formation of cluster structures in the field of food sector

Civil society participation in the legislative process

Purpose. The aim of the article is to analyze the participation of civil society in the legislative process. Method. The methodology includes a comprehensive analysis and generalization of available scientific and theoretical material and formulation of relevant conclusions. During the research, the methods of scientific cognition were used: comparative-legal, logical-semantic, functional, system-structural, and logical-normative. Results. In the course of the research, it was recognized that one of the key ways of interaction between the state and civil society is the participation of citizens in the legislative activity of the parliament. The Verkhovna Rada of Ukraine, as a representative body aimed at protecting the interests of citizens, can promote more active public involvement in its activities. The examples of the European Union countries show that there are many different forms and ways of such participation at different levels of interaction. The presented methods allow determining the general model of citizen participation in the work of the Verkhovna Rada of Ukraine. Forms of public participation in the activities of the parliament are revealed: informing, consulting and dialogue. Citizens’ participation in decision-making is a complex and complex process that takes place under the influence of various factors. Due to the incomplete process of reforming the political system of the country, the system of forms and methods of citizen participation in the decision-making process are in the process of formation and constant transformation. Scientific novelty. The study found that the formation of a model of citizen participation and civil society institutions in the legislative process should reflect the institutional mechanisms of public participation and the integration of civil society structures in the main activities of parliament. Practical significance. The applied value of the research is determined by the fact that the scientific results create a basis for improving the legislation on the participation of civil society institutions in the legislative process.

A review of the study on coherent structures in turbulence by the clustering method

The intrinsic randomness of turbulence requires that the study of coherent structures has to be from the statistical point of view. The data-based clustering method is a powerful tool to realize the deep integration of coherent structures and statistics. It makes each continuous region, i.e., an individual structure, as a statistical sample. In addition, the spatial-temporal tracking method based on the spatial overlap of individual structure between consecutive snapshots makes the evolution of individual structure during its lifetime also as a statistical sample. Thus, both the kinematics and dynamics of coherent structures can be statistically described. We reviewed the history of this method and introduced the progress on Reynolds stress structures, velocity streaks, and cascades with emphasis. These results suggest that the clustering method extraordinarily extended our understanding of turbulence compared with the traditional point-wise statistics. Further prospects are also provided for future research.

Lotus Seedpod Inspiration: Particle-Nested Double-Inverse Opal Films with Fast and Reversible Structural Color Switching for Information Security.

The integration of novel structures into colloidal crystals provides the possibility of constructing stimuli-responsive photonic materials. However, in most opal and inverse opal structures, replacing the interior air with an infiltrated liquid will cause partial refractive index matching, resulting in the reduction or even disappearance of the photonic band gap. Herein, inspired by the lotus seedpod, an innovative particle-nested double-inverse opal film with fast and reversible structural color switching (≈1 s) is first fabricated by introducing polystyrene (PS) spheres into an inverted opal backbone. Importantly, refractive index matching can be effectively avoided due to the existence of internal PS spheres, and optical switching from diffusive to photonic behavior is achieved by a liquid with low surface tension for the response. Furthermore, a reversible ethanol stimuli-response bilayer double-inverse opal film with multistate switching for information encryption is proposed by combining optical scattering and diffraction. The scattered light from the top layer caused by the randomly distributed and weakly scattering PS spheres within the pores makes the pattern at the bottom invisible. Simultaneously, the display and discoloration of the pattern can be realized instantaneously by ethanol response. Thus, this new preparation strategy exhibits great potential in the security fields.

Gaining Insights Into Metabolic Networks Using Chemometrics and Bioinformatics: Chronic Kidney Disease as a Clinical Model.

Because of its ability to generate biological hypotheses, metabolomics offers an innovative and promising approach in many fields, including clinical research. However, collecting specimens in this setting can be difficult to standardize, especially when groups of patients with different degrees of disease severity are considered. In addition, despite major technological advances, it remains challenging to measure all the compounds defining the metabolic network of a biological system. In this context, the characterization of samples based on several analytical setups is now recognized as an efficient strategy to improve the coverage of metabolic complexity. For this purpose, chemometrics proposes efficient methods to reduce the dimensionality of these complex datasets spread over several matrices, allowing the integration of different sources or structures of metabolic information. Bioinformatics databases and query tools designed to describe and explore metabolic network models offer extremely useful solutions for the contextualization of potential biomarker subsets, enabling mechanistic hypotheses to be considered rather than simple associations. In this study, network principal component analysis was used to investigate samples collected from three cohorts of patients including multiple stages of chronic kidney disease. Metabolic profiles were measured using a combination of four analytical setups involving different separation modes in liquid chromatography coupled to high resolution mass spectrometry. Based on the chemometric model, specific patterns of metabolites, such as N-acetyl amino acids, could be associated with the different subgroups of patients. Further investigation of the metabolic signatures carried out using genome-scale network modeling confirmed both tryptophan metabolism and nucleotide interconversion as relevant pathways potentially associated with disease severity. Metabolic modules composed of chemically adjacent or close compounds of biological relevance were further investigated using carbon transfer reaction paths. Overall, the proposed integrative data analysis strategy allowed deeper insights into the metabolic routes associated with different groups of patients to be gained. Because of their complementary role in the knowledge discovery process, the association of chemometrics and bioinformatics in a common workflow is therefore shown as an efficient methodology to gain meaningful insights in a clinical context.

Kinematic Prediction and Experimental Demonstration of Conditioning Process for Controlling the Profile Shape of a Chemical Mechanical Polishing Pad

The uniformity of the wafer in a chemical mechanical polishing (CMP) process is vital to the ultra-fine and high integration of semiconductor structures. In particular, the uniformity of the polishing pad corresponding to the tool directly affects the polishing uniformity and wafer shape. In this study, the profile shape of a CMP pad was predicted through a kinematic simulation based on the trajectory density of the diamond abrasives of the diamond conditioner disc. The kinematic prediction was found to be in good agreement with the experimentally measured pad profile shape. Based on this, the shape error of the pad could be maintained within 10 μm even after performing the pad conditioning process for more than 2 h, through the overhang of the conditioner.

MAIN STAGES OF AUTOMATED SYSTEM OF PROCESSES FOR DETERMINING AND ENSURING FUNCTIONAL AND PARAMETRIC COMPATIBILITY OF PRODUCTION AND TECHNOLOGICAL SYSTEMS

This article presents the main stages of the development of an automated system of processes for determining and ensuring functional and parametric compatibility (FPC) of components of production and technological systems (PTS), in particular production and technological modules (PTM) of machine-building production, respectively, based on the analysis and systematization of technological zones of loading of the main technological equipment (MTE) and the construction of coating surfaces, the main parameters of industrial robots and storage systems (SS), determination and mathematical formalization of coating surfaces and guiding planes of MTE loading zones, formation of types of analytical dependences of FPC PTM functions, development of a mathematical model for automating the processes of determining and providing FPC of PTM components. The present developed automated system can be used in the processes of restructuring and modernization of domestic machine-building production systems by automating the processes of building optimal production and technological structures of various hierarchical levels for the purpose of information, technological and functional-parametric integration of domestic and foreign production structures of mechanical engineering.

Structural Optimization of Locally Continuous Fiber-Reinforcements for Short Fiber-Reinforced Plastics

The integration of continuous fiber-reinforced structures into short or long fiber-reinforced plastics allows a significant increase in stiffness and strength. In order to make the best possible use of the high stiffness and strength of continuous fiber-reinforcements, they must be placed in the direction of load in the most stressed areas. A frequently used tool for identifying the most heavily loaded areas is topology optimization. Commercial topology optimization programs usually do not take into account the material properties associated with continuous fiber-reinforced hybrid structures. The anisotropy of the reinforcing material and the stiffness of the base material surrounding the reinforcement are not considered during topology optimization, but only in subsequent steps. Therefore in this publication, existing optimization methods for hybrid and anisotropic materials are combined to a new approach, which takes into account both the anisotropy of the continuous fiber-reinforcement and the stiffness of the base material. The results of the example calculations not only show an increased stiffness at the same material input but also a simplification of the resulting reinforcement structures, which allows more economical manufacturing.

Biohybrid soft robots with self-stimulating skeletons.

Bioinspired hybrid soft robots that combine living and synthetic components are an emerging field in the development of advanced actuators and other robotic platforms (i.e., swimmers, crawlers, and walkers). The integration of biological components offers unique characteristics that artificial materials cannot precisely replicate, such as adaptability and response to external stimuli. Here, we present a skeletal muscle-based swimming biobot with a three-dimensional (3D)-printed serpentine spring skeleton that provides mechanical integrity and self-stimulation during the cell maturation process. The restoring force inherent to the spring system allows a dynamic skeleton compliance upon spontaneous muscle contraction, leading to a cyclic mechanical stimulation process that improves the muscle force output without external stimuli. Optimization of the 3D-printed skeletons is carried out by studying the geometrical stiffnesses of different designs via finite element analysis. Upon electrical actuation of the muscle tissue, two types of motion mechanisms are experimentally observed: directional swimming when the biobot is at the liquid-air interface and coasting motion when it is near the bottom surface. The integrated compliant skeleton provides both the mechanical self-stimulation and the required asymmetry for directional motion, displaying its maximum velocity at 5 hertz (800 micrometers per second, 3 body lengths per second). This skeletal muscle-based biohybrid swimmer attains speeds comparable with those of cardiac-based biohybrid robots and outperforms other muscle-based swimmers. The integration of serpentine-like structures in hybrid robotic systems allows self-stimulation processes that could lead to higher force outputs in current and future biomimetic robotic platforms.

Cohomology of Lie Groupoid Modules and the Generalized van Est Map

Abstract The van Est map is a map from Lie groupoid cohomology (with respect to a sheaf taking values in a representation) to Lie algebroid cohomology. We generalize the van Est map to allow for more general sheaves, namely to sheaves of sections taking values in a (smooth or holomorphic) $G$-module, where $G$-modules are structures, which differentiate to representations. Many geometric structures involving Lie groupoids and stacks are classified by the cohomology of sheaves taking values in $G$-modules and not in representations, including $S^1$-groupoid extensions and equivariant gerbes. Examples of such sheaves are $\mathcal{O}^*$ and $\mathcal{O}^*(*D)\,,$ where the latter is the sheaf of invertible meromorphic functions with poles along a divisor $D\,.$ We show that there is an infinitesimal description of $G$-modules and a corresponding Lie algebroid cohomology. We then define a generalized van Est map relating these Lie groupoid and Lie algebroid cohomologies and study its kernel and image. Applications include the integration of several infinitesimal geometric structures, including Lie algebroid extensions, Lie algebroid actions on gerbes, and certain Lie $\infty $-algebroids.

Integration of Constructed Floodplain Ponds into Nature-Like Fish Passes Supports Fish Diversity in a Heavily Modified Water Body

Fish passes facilitate fish movement in fragmented river systems, yet they can also provide important habitat functions. This study investigated the fish community composition of different constructed habitat types (fluvial habitats, floodplain ponds) within fish passes in relation to habitat characteristics in order to deduce recommendations for fish-friendly designs of such structures. Fish community structures within passes differed significantly from those in the main river, comprising a high number of rheophilic species in fluvial habitats (Thymallus thymallus, Hucho hucho, Salmo trutta, Cottus gobio, Chondrostoma nasus, and Barbus barbus), and of stagnophilic species in floodplain ponds (Rhodeus amarus, Scardinius erythrophthalmus, Misgurnus bipartitus, and Tinca tinca). During summer, floodplain ponds also provided important juvenile habitats for the target species C. nasus and B. barbus. Differences between the two habitat types in fish abundance were mostly explained by differences in macrophyte coverage, gravel, boulders, temperature, and current speed. The findings of this study stress the important habitat functions of fish passes. They also suggest that integration of diverse habitat structures, especially of currently hardly considered constructed floodplain ponds into fish passes, can greatly enhance their fish communities and contribute to the restoration of several declining target species of conservation.

Nano- and Micropatterning on Optical Fibers by Bottom-Up Approach: The Importance of Being Ordered

The realization of advanced optical fiber probes demands the integration of materials and structures on optical fibers with micro- and nanoscale definition. Although researchers often choose complex nanofabrication tools to implement their designs, the migration from proof-of-principle devices to mass production lab-on-fiber devices requires the development of sustainable and reliable technology for cost-effective production. To make it possible, continuous efforts are devoted to applying bottom-up nanofabrication based on self-assembly to decorate the optical fiber with highly ordered photonic structures. The main challenges still pertain to “order” attainment and the limited number of implementable geometries. In this review, we try to shed light on the importance of self-assembled ordered patterns for lab-on-fiber technology. After a brief presentation of the light manipulation possibilities concerned with ordered structures, and of the new prospects offered by aperiodically ordered structures, we briefly recall how the bottom-up approach can be applied to create ordered patterns on the optical fiber. Then, we present un-attempted methodologies, which can enlarge the set of achievable structures, and can potentially improve the yielding rate in finely ordered self-assembled optical fiber probes by eliminating undesired defects and increasing the order by post-processing treatments. Finally, we discuss the available tools to quantify the degree of order in the obtained photonic structures, by suggesting the use of key performance figures of merit in order to systematically evaluate to what extent the pattern is really “ordered”. We hope such a collection of articles and discussion herein could inspire new directions and hint at best practices to fully exploit the benefits inherent to self-organization phenomena leading to ordered systems.

Constraints associated with captivity alter craniomandibular integration in wild boar.

The domestication process is associated with substantial phenotypic changes through time. However, although morphological integration between biological structures is purported to have a major influence on the evolution of new morphologies, little attention has been paid to the influence of domestication on the magnitude of integration. Here, we assessed the influence of constraints associated with captivity, considered as one of the crucial first steps in the domestication process, on the integration of cranial and mandibular structures. We investigated the craniomandibular integration in Western European Sus scrofa using three-dimensional (3D) landmark-based geometric morphometrics. Our results suggest that captivity is associated with a lower level of integration between the cranium and the mandible. Plastic responses to captivity can thus affect the magnitude of integration of key functional structures. These findings underline the critical need to develop integration studies in the context of animal domestication to better understand the processes accountable for the set-up of domestic phenotypes through time.

What place does nurse-led research have in the COVID-19 pandemic?

AimReflect upon the visibility of nursing‐led research during the COVID‐19 pandemic.BackgroundThe emerging SARS‐CoV‐2 infection has galvanized collaborative and multidisciplinary efforts in clinical and research practice worldwide. The scarce evidence‐base to manage patients with COVID‐19 has included limited nurse‐led research.IntroductionClinical research nurses have greatly contributed to the delivery of COVID‐19 research, yet the number of COVID‐19 nursing‐led research papers appears to be limited, with even fewer nurse‐led research projects funded.MethodsAuthors’ views and PubMed search on ‘COVID‐19 and nursing’.FindingsThere is a dearth of nursing‐led research. Most papers describe the nursing contribution to COVID‐19 care, changes in nursing working arrangements and emotional burden. There are opportunities to explore the consequences to vulnerable population groups of public health measures implemented to stop the progress of the COVID‐19 pandemic.DiscussionWorkforce gaps, limited integration in research structures and clinical redeployment may have hampered nurse‐led research. COVID‐19 may exacerbate staffing deficits by disrupting the education pipeline, obstructing the transition from clinical to academic practice, particularly in areas where clinical academic roles are yet to emerge.ConclusionThe absence of nurse‐led research in COVID‐19 can be explained by chronic, underlying factors and the features of the pandemic response. Emerging models of care, effective staffing and inequalities related to COVID‐19 appear obvious research areas. Nursing leadership needs to strengthen its political voice and lobbying skills to secure nurse‐led research funding.Implications for Nursing PolicyEmbracing international nursing research, strengthening collaborations and lobbying policymakers for investment in nurse‐sensitive research would enhance the response to COVID‐19.

Energetic and exergetic evaluation of methanol synthesis process in a hybridized system of methane cracking, chemical looping combustion, thermal desalination and photovoltaic panels

Due to limited energy supply sources and environmental issues, the use of renewable energy to replace fossil fuels and reduce pollution has increased. One of the easiest, safest, and most portable ways to store renewable energy for a long time is to convert it to liquid methanol. In this paper, a novel integrated system is developed for cogeneration of liquid methanol and freshwater using methane cracking unit integrated with chemical looping combustion, methanol production cycle, multi-effect desalination, and photovoltaic panels. The thermal integration of new structures for cogeneration leads to a reduction in the number of equipment used and an increase in efficiency. This integrated structure produces 23.97 kmol h−1 liquid methanol, 204.3 kmol h−1 desalinated water, 42.49 kmol h−1 solid carbon, 58.52 kmol h−1 nitrogen, and 668.9 kmol h−1 hot water. The waste heat of the chemical looping combustion is used to supply methane cracking unit, which produces 84.99 kmol h−1 hydrogen, 7.582 kmol h−1 carbon dioxide, and 24.74 kW power. These products and the excess carbon dioxide supplied from outside are used as input feed for the liquid methanol production cycle. Waste heat from the liquid methanol production cycle is used to supply heat to the thermal desalination cycle and produce hot water. The thermal energy and exergy efficiencies of the integrated structure are 48.64% and 71.68%, respectively. In the hybrid structure, the largest share of exergy destruction belongs to reactors (65.61%), photovoltaic panels (17.73%), and heat exchangers (10.97%), respectively. Sensitivity analysis in different operating conditions is used to investigate the sensitivity and changes in the output and important parameters of the process.

Predictive value of metabolic and perfusion changes outside the seizure onset zone for postoperative outcome in patients with refractory focal epilepsy.

The value of functional molecular changes outside the seizure onset zone as independent predictive factors of surgical outcome has been scarcely evaluated. The aim of this retrospective study was to evaluate relative metabolic and perfusion changes outside the seizure onset zone as predictors of postoperative outcome in patients with unifocal refractory focal epilepsy. Eighty-six unifocal epilepsy patients who underwent 18F-FDG PET prior to surgery were included. Ictal and interictal perfusion SPECT was available in 65 patients. Good postoperative outcome was defined as the International League against Epilepsy class 1. Using univariate statistical analysis, the predictive ability of volume-of-interest based relative metabolism/perfusion for outcome classification was quantified by AUC ROC-curve, using composite, unilateral cortical (frontal, orbitofrontal, temporal, parietal, occipital) and central volumes-of-interest. The results were cross-validated, and a false discovery rate (FDR) correction was applied. As a secondary objective, a subgroup analysis was performed on temporal lobe epilepsy patients (N = 64). Increased relative ictal perfusion in the contralateral central volume-of-interest was significantly associated with the good surgical outcome both in the total population (AUC 0.79, pFDR = 0.009) and the temporal lobe epilepsy subgroup (AUC 0.80, pFDR = 0.028). No other significant associations between functional molecular changes and postoperative outcome were found. Increased relative ictal perfusion in the contralateral central region significantly predicted outcome after epilepsy surgery in patients with refractory focal epilepsy. We postulate that these relative perfusion changes could be an expression of better preoperative neuronal network integration and centralization in the contralateral central structures, which is suggested to be associated with better postoperative outcome.