Compatible Functions Research Articles

The Compatible Modes and Functions of Expectation and Anti-expectation Modal Adverbs Within a Sentence

The Compatible Modes and Functions of Expectation and Anti-expectation Modal Adverbs Within a Sentence

Bayesian-neural-network accelerated design of multispectral-compatible camouflage layer with wide-band microwave absorption, customized infrared emission and visible transparency

Metasurfaces with customizable multi-spectrum compatibility have attracted a great deal of attention due to the increasing applications of stealth and camouflage. Compared with single-spectrum and fixed-scene camouflage metasurfaces, a camouflage metasurface with the designability and spectral-independence can adapt to more complex environments. However, this drastically increases the design complexity and time cost of metasurfaces. Here, we propose a method to design multispectral compatible function layer of camouflage which can achieve customizable wideband microwave absorption, visible transparency and selective infrared emission, simultaneously. The design of the camouflage layer is optimized and accelerated by Bayesian-neural network, which can be implemented based on a very limited amount of prior data and can greatly reduce the design complexity and time. To verify our method, an optical-transparent metasurface with digital infrared camouflage and low backward scattering was designed and fabricated. The simulation and experimental results well demonstrate the performance of multispectral compatible camouflage of the metasurface. We further explore the angular stability of the camouflage layer to the incident angle varying from 0 to 60° at microwaves. Our proposed design scheme provides a novel method to design spectrum-individual and devisable metasurfaces, which can be applied to camouflage in complex spectrum background

Theoretical Foundations of the Service Sector Functioning at the Present Stage

Introduction. The modern context of a practical shift towards the service sector requires to study it from a theoretical perspective. Despite a sufficient number of publications on the topic of services, many authors do not provide corresponding grounds when identifying classification groups of services. This article focuses on the specific aspects of clarifying the concept of "service", essential classification of services and functions. Materials and Methods. The theoretical basis of the research included articles from peer-reviewed journals and monographs on the topic under study. A wide range of general scientific methods was applied in the research, including analysis and synthesis, abstract-logical, systemic analysis and others. Results. Characteristics of material and immaterial services were provided in comparison, which allows for a better emphasis on the features of their provision and consumption. This approach takes into account the specifics of consumers and their role in the process, as well as the qualifications of the personnel when planning activities in the service sector. Important issues of service compatibility and service function allocation are addressed. The study highlights the need to include education and culture in the value-oriented function of services. Due to the inability of consumers to clearly express their social and spiritual needs, the authors argue for the importance and tasks of service industry workers to assist clients in forming their essential needs. Conclusions. The article compares the most important characteristics of service differentiation based on various classifications, including its specificity, evaluation, producers, producer-consumer relationships, and production technology.

A radar-infrared compatible stealth metamaterial with bird's nest morphology

The rapid development of detection technology, the technology with radar infrared compatible stealth function has become one of the important ways to improve the survivability of weapons and equipment. However, the two stealth mechanisms of radar stealth and infrared stealth are mutually exclusive. In this work, a multilayer radar-infrared compatible stealth metamaterial is presented based on SiO2 fiber reinforced aerogels skeleton (SFRAS). The prepared samples with bird 's nest microstructure showed good compressive strength (1.73–2.52 MPa) and low density (0.22–0.27 g/cm3), achieving lightweight. Moreover, the metamaterial exhibits excellent electromagnetic absorption performance, effective absorbing broadband (13 GHz), and ultra-wideband absorption of electromagnetic waves is achieved. Nanoporous structure and low thermal conductivity (0.03426–0.05011 W/ (m K)) successfully reduce the surface thermal radiation, indicating that it is a potential material for achieving infrared stealth. The new technology provides a new approach to the research of the radar-infrared compatible stealth structure.

Avoiding barren plateaus in the variational determination of geometric entanglement

The barren plateau (BP) phenomenon is one of the main obstacles to implementing variational quantum algorithms in the current generation of quantum processors. Here, we introduce a method capable of avoiding the BP phenomenon in the variational determination of the geometric measure of entanglement for a large number of qubits. The method is based on measuring compatible two-qubit local functions whose optimization allows for achieving a well-suited initial condition from which a global function can be further optimized without encountering a BP. We analytically demonstrate that the local functions can be efficiently estimated and optimized. Numerical simulations up to 18 qubit GHZ and W states demonstrate that the method converges to the exact value. In particular, the method allows for escaping from BPs induced by hardware noise or global functions defined on high-dimensional systems. Numerical simulations with noise agree with experiments carried out on IBM’s quantum processors for seven qubits.

Hitchhiking of Cas9 with nucleus-localized proteins impairs its controllability and leads to efficient genome editing of NLS-free Cas9

CRISPR/Cas9 is the most commonly used genome editing tool in eukaryotic cells. To modulate Cas9 entry into the nucleus to enable control of genome editing, we constructed a light-controlled CRISPR/Cas9 system to control exposure of the Cas9 protein NLS. Although blue light irradiation was found to effectively control the entry of Cas9 protein into the nucleus with confocal microscopy observation, effective gene editing occurred in controls with next-generation sequencing analysis. To further clarify this phenomenon, a CRISPR/Cas9 editing system without the NLS and a CRISPR/Cas9 editing system containing an NES were also constructed. Interestingly, both Cas9 proteins could achieve effective editing of target sites with significantly reduced off-target effects. Thus, we speculated that other factors might mediate Cas9 entry into the nucleus. However, NLS-free Cas9 was found to produce effective target gene editing even following inhibition of cell mitosis to prevent nuclear import caused by nuclear membrane disassembly. Furthermore, multiple nucleus-localized proteins were found to interact with Cas9, which could mediate the hitchhiking of NLS-free Cas9 into the nucleus. These findings will inform future attempts to construct controllable gene editing systems, as well as provide new insights into the evolution of the nucleus and of compatible protein functions.

Construction Strategy for Flexible and Breathable SiO2/Al/NFs/PET Composite Fabrics with Dual Shielding against Microwave and Infrared-Thermal Radiations for Wearable Protective Clothing.

Microwave and infrared-thermal radiation-compatible shielding fabrics represent an important direction in the development of wearable protective fabrics. Nevertheless, effectively and conveniently integrating compatible shielding functions into fabrics while maintaining breathability and moisture permeability remains a significant challenge. Here, we take hydrophilic PVA-co-PE nanofibrous film-coated PET fabric (NFs/PET) as a flexible substrate and deposit a dielectric/conductive (SiO2/Al) bilayer film via magnetron sputtering. This strategy endows the fabric surface with high electrical conductivity, nanoscale roughness comparable to visible and infrared waves, and a dielectric-metal contact interface possessing localized plasmon resonance and Mie scattering effects. The results demonstrate that the optimized SiO2/Al/NFs/PET composite conductive fabric (referred to as S4-1) possesses favorable X-band electromagnetic interference (EMI) shielding effectiveness (50 dB) as well as excellent long-wave infrared (LWIR) shielding or IR stealth performance (IR emissivity of 0.60). Notably, the S4-1 fabric has a cooling effect of about 12.4 °C for a heat source (80 °C) and an insulating effect of about 17.2 °C for a cold source (-20 °C), showing excellent shielding capability for heat conduction and heat radiations. Moreover, the moisture permeability of the S4-1 fabric is about 300 g/(m2·h), which is better than the requirement concerning moisture permeability for wearable fabrics (≥2500-5000 g/(m2·24 h)), indicating excellent heat and moisture comfort. In short, our fabrics have lightweight, thin, moisture-permeable and excellent shielding performance, which provides novel ideas for the development of wearable multi-band shielding fabrics applied to complex electromagnetic environments.

Dimethyl fumarate modulates the dystrophic disease program following short-term treatment.

New medicines are urgently required to treat the fatal neuromuscular disease, Duchenne muscular dystrophy (DMD). Dimethyl fumarate (DMF) is a potent immunomodulatory small molecule nuclear erythroid 2-related factor 2 (Nrf2) activator with current clinical utility in the treatment of multiple sclerosis and psoriasis that could be effective for DMD and rapidly translatable. Here, we tested two weeks of daily 100mg/kg DMF versus 5mg/kg standard care prednisone (PRED) treatment in juvenile mdx mice with early symptomatic DMD. Both drugs modulated seed genes driving the DMD disease program and improved force production in fast-twitch muscle. However, only DMF showed pro-mitochondrial effects, protected contracting muscles from fatigue, improved histopathology and augmented clinically compatible muscle function tests. DMF may be a more selective modulator of the DMD disease program than PRED warranting follow-up longitudinal studies to evaluate disease modifying impact.

Synthesis of β-cyclodextrin-based per-6-phosphoramidates

An convenient methodology is reported to obtain β-cyclodextrin (CD) derivatives perfunctionalized with phosphoramidates by reacting a per-6-azido-β-CD substrate with various phosphites. This Staudinger-like ligation reaction can be successfully profited to prepare a range of novel per-6-substituted β-CD derivatives in moderate to excellent yields. The methodology worked well with phosphites containing less sterically hindered primary alkyl groups but showed limited scope for phosphites containing secondary alkyl groups. Some compatible functionality, such as alkene functionality, can be effectively embedded in the alkyl groups to obtain functionalized β-CD-phosphoramidates for future chemical derivatization. The benefits of this methodology include the metal-free coupling to easily accessible per-6-azides of β-CD that complement the popularly used copper(I)-catalyzed Huisgen azide-alkyne cycloaddition.

No Adversaries to Zero-Shot Learning: Distilling an Ensemble of Gaussian Feature Generators.

In zero-shot learning (ZSL), the task of recognizing unseen categories when no data for training is available, state-of-the-art methods generate visual features from semantic auxiliary information (e.g., attributes). In this work, we propose a valid alternative (simpler, yet better scoring) to fulfill the very same task. We observe that, if first- and second-order statistics of the classes to be recognized were known, sampling from Gaussian distributions would synthesize visual features that are almost identical to the real ones as per classification purposes. We propose a novel mathematical framework to estimate first- and second-order statistics, even for unseen classes: our framework builds upon prior compatibility functions for ZSL and does not require additional training. Endowed with such statistics, we take advantage of a pool of class-specific Gaussian distributions to solve the feature generation stage through sampling. We exploit an ensemble mechanism to aggregate a pool of softmax classifiers, each trained in a one-seen-class-out fashion to better balance the performance over seen and unseen classes. Neural distillation is finally applied to fuse the ensemble into a single architecture which can perform inference through one forward pass only. Our method, termed Distilled Ensemble of Gaussian Generators, scores favorably with respect to state-of-the-art works.

Generative design: Integrating rent and retail compatibility goals for automated tenant mix layout

Tenant mix is a central issue in the development and operation of shopping malls. An effective tenant layout can enhance the consumer experience and increase shop sales. So it is crucial to comprehensively consider the rent and retail compatibility when crafting the tenant mix. Developers mainly considered the rent income from anchor and non-anchor tenants. But many studies ignored the externality effect of anchor tenants on the rent of non-anchor tenants. Furthermore, the relationship between different tenant type and retail compatibility under customers' behavioral preferences is not adequately studied. In addition, existing optimization methods is inefficient, poorly integrated and cannot rapidly explore design options. Therefore, this paper aims to achieve automatic generation and optimization of tenant mix layouts considering the rent and retail compatibility objective. Firstly, a bi-objective model consisting of the rent and retail compatibility objectives is developed to evaluate the performance of the generated schemes. The rent objective function quantifies the externality of anchor shop on the rent of non-anchor shops in the shopping center. The retail compatibility function quantifies the relationship between the consumers’ behavior preferences and retail types. Then this paper proposed a generative mechanism consisting of parametric design, scheme optimization and decision making processes. The results of the case study show that the optimized scheme outperforms the original scheme in terms of both rent and retail compatibility objectives. The proposed generative mechanism achieves automatic generation and optimization of tenant mix layouts, and greatly improves the efficiency of the design process.

Improved XFEM for 3D interfacial crack modeling

The conventional extended finite element method (XFEM) usually suffers from the crack tip enrichment for removing the blending elements. This may be inconvenient when treating the three dimensional (3D) and curved crack modeling since the crack tip enrichment is usually defined in the local coordinate system depending on the crack front. To avoid these shortcomings of the XFEM, an improved enrichment scheme is proposed for the 3D interfacial crack modeling. The proposed enrichment scheme removes the crack tip enrichment and two weight functions are introduced to capture the strong and weak discontinuities in the element including the crack front. The new enrichment scheme has advantages for the 3D curved interfacial cracks since all the enrichment functions are defined in the global system and it is unnecessary to introduce additional coordinate systems. Several benchmark problems including the mixed mode stress intensity factors (SIFs), anti-plane load and curved cracks are analyzed by the proposed method with the local refinement technology. Numerical results demonstrate that the proposed method can obtain accurate 3D energy release rate and SIFs. In addition, the proposed method enhances the applications of XFEM and has the potential abilities to the multiple-fields coupling and interfacial crack growth phenomena due to the fact that compatible enrichment functions are utilized.

Inducing a probability distribution in Stochastic Multicriteria Acceptability Analysis

In multiple criteria decision aiding, very often the alternatives are compared by means of a value function compatible with the preferences expressed by the Decision Maker. The problem is that, in general, there is a plurality of compatible value functions, and providing a final recommendation on the problem at hand considering only one of them could be considered arbitrary to some extent. For such a reason, Stochastic Multicriteria Acceptability Analysis gives information in statistical terms by taking into account a sample of models compatible with the provided preferences. These statistics are given assuming the existence of a probability distribution in the space of value functions being defined a priori. In this paper, we propose some methods aiming to build a probability distribution on the space of value functions considering the preference information given by the Decision Maker. To prove the goodness of our proposal we performed an extensive set of simulations. Moreover, a sensitivity analysis on the variables of our procedure has been done.

Deep Deterministic Policy Gradient With Compatible Critic Network.

Deep deterministic policy gradient (DDPG) is a powerful reinforcement learning algorithm for large-scale continuous controls. DDPG runs the back-propagation from the state-action value function to the actor network's parameters directly, which raises a big challenge for the compatibility of the critic network. This compatibility emphasizes that the policy evaluation is compatible with the policy improvement. As proved in deterministic policy gradient, the compatible function guarantees the convergence ability but restricts the form of the critic network tightly. The complexities and limitations of the compatible function impede its development in DDPG. This article introduces neural networks' similarity indices with gradients to measure the compatibility concretely. Represented as kernel matrices, we consider the actor network's and the critic network's training dataset, trained parameters, and gradients. With the sketching trick, the calculation time of the similarity index decreases hugely. The centered kernel alignment index and the normalized Bures similarity index provide us with consistent compatibility scores empirically. Moreover, we demonstrate the necessity of the compatible critic network in DDPG from three aspects: 1) analyzing the policy improvement/evaluation steps; 2) conducting the theoretic analysis; and 3) showing the experimental results. Following our research, we remodel the compatible function with an energy function model, enabling it suitable to the sizeable state-action space problem. The critic network has higher compatibility scores and better performance by introducing the policy change information into the critic-network optimization process. Besides, based on our experiment observations, we propose a light-computation overestimation solution. To prove our algorithm's performance and validate the compatibility of the critic network, we compare our algorithm with six state-of-the-art algorithms using seven PyBullet robotics environments.

Discriminative and Robust Attribute Alignment for Zero-Shot Learning

Zero-shot learning (ZSL) aims to learn models that can recognize images of semantically related unseen categories, through transferring attribute-based knowledge learned from training data of seen classes to unseen testing data. As visual attributes play a vital role in ZSL, recent embedding-based methods usually focus on learning a compatibility function between the visual representation and the class semantic attributes. While in this work, in addition to simply learning the region embedding of different semantic attributes to maintain the generalization capability of the learned model, we further consider to improve the discrimination power of the learned visual features themselves by contrastive embedding. It exploits both the class-wise and instance-wise supervision for GZSL, under the attribute guided weakly supervised representation learning framework. To further improve the robustness of the ZSL model, we also propose to train the model under the consistency regularization constraint, through taking full advantages of self-supervised signals of the image under various perturbed augmentation situations, which could make the model robust to some occluded or un-related attribute regions. Extensive experimental results demonstrate the effectiveness of the proposed ZSL method, achieving superior performances to state-of-the-art methods on three widely-used benchmark datasets, namely CUB, SUN, and AWA2. Our source code is released at https://github.com/KORIYN/CC-ZSL.

Explored the Function of Electromagnetic Compatibility (EMC) of Medical Devices from the Perspective of Test

To improve the electromagnetic compatibility (EMC) quality of medical devices, improve the efficiency of EMC testing, and promote the speed of market approval. The unqualified cases of EMC test items of medical devices in recent years were statistically analyzed, and the reasons of low EMC quality of medical devices were analyzed from the perspective of test. Based on the analysis of the reasons, the suggestions were given from the perspectives of medical device manufacturers and testing organizations. In order to ensure the quality of EMC of medical devices, medical device manufacturers, regulatory authorities and inspection and testing institutions should strengthen the monitoring and evaluation of medical device electromagnetic compatibility, to ensure the safety of products work together to promote the development of the medical device industry healthily and orderly.

Nickel-Doped Graphite and Fusible Alloy Bilayer Back Electrode for Vacuum-Free Perovskite Solar Cells.

With the rapid development of perovskite solar cells (PSCs), lowering fabrication costs for PSCs has become a prominent challenge for commercialization. At present, gold is commonly used as the back metal electrode in state-of-the-art n-i-p structured PSCs due to its compatible work function, chemical inertness, and high conductivity. However, the high cost of gold and the expensive and time-consuming vacuum-based thin-film coating facilities may impede large-scale industrialization of PSCs. Here, we report a bilayer back electrode configuration consisting of an Ni-doped natural graphite layer with a fusible Bi-In alloy. This back electrode can be deposited in a vacuum-free approach and enables PSCs with a power conversion efficiency of 21.0%. These inexpensive materials and facile ambient fabrication techniques provide an appealing disruptive solution to low-cost PSC industrialization.

Bioimaging and detecting endogenous and exogenous cyanide in foods, living cells and mice based on a turn-on mitochondria-targeted fluorescent probe

A novel fluorescent probe, with advanced features including “turn-on” fluorescence response, high sensitivity, good compatibility, and mitochondria-targeting function, has been synthesized based on structural design for detecting and visualizing cyanide in foods and biological systems. An electron-donating triphenylamine group (TPA) was employed as the fluorescent and an electron-accepting 4-methyl-N-methyl-pyridinium iodide (Py) moiety was used as a mitochondria-targeted localization unit, which formed intramolecular charge transfer (ICT) system. The “turn-on” fluorescence response of the probe (TPA-BTD-Py, TBP) toward cyanide is attributed two reasons, one is the insertion of an electron-deficient benzothiadiazole (BTD) group into the conjugated system between TPA and Py, and the other is the inhibition of ICT induced by the nucleophilic addition of CN–. Two active sites for reacting with CN− were involved in TBP molecule and high response sensitivity were observed in tetrahydrofuran solvent containing 3 % H2O. The response time could be reduced to 150 s, the linear range was 0.25–50 μM, and the limit of detection was 0.046 μM for CN− analysis. The TBP probe was successfully applied to the detection of cyanide in food samples prepared in aqueous solution, including the sprouting potato, bitter almond, cassava, and apple seeds. Furthermore, TBP exhibited low cytotoxicity, clear mitochondria-localizing capability in HeLa cells and excellent fluorescence imaging of exogenous and endogenous CN– in living PC12 cells. Moreover, exogenous CN– with intraperitoneal injection in nude mice could be well monitored visually by the “turn-on” fluorescence. Therefore, the strategy based on structural design provided good prospects for optimizing fluorescent probes.

SeqWiz: a modularized toolkit for next-generation protein sequence database management and analysis

BackgroundCurrent proteomic technologies are fast-evolving to uncover the complex features of sequence processes, variations and modifications. Thus, protein sequence database and the corresponding softwares should also be improved to solve this issue.ResultsWe developed a state-of-the-art toolkit (SeqWiz) for constructing next-generation sequence databases and performing proteomic-centric sequence analyses. First, we proposed two derived data formats: SQPD (a well-structured and high-performance local sequence database based on SQLite), and SET (an associated list of selected entries based on JSON). The SQPD format follows the basic standards of the emerging PEFF format, which also aims to facilitate the search of complex proteoform. The SET format is designed for generating subsets with with high-efficiency. These formats are shown to greatly outperform the conventional FASTA or PEFF formats in time and resource consumption. Then, we mainly focused on the UniProt knowledgebase and developed a collection of open-source tools and basic modules for retrieving species-specific databases, formats conversion, sequence generation, sequence filter, and sequence analysis. These tools are implemented by using the Python language and licensed under the GNU General Public Licence V3. The source codes and distributions are freely available at GitHub (https://github.com/fountao/protwiz/tree/main/seqwiz).ConclusionsSeqWiz is designed to be a collection of modularized tools, which is friendly to both end-users for preparing easy-to-use sequence databases as well as bioinformaticians for performing downstream sequence analysis. Besides the novel formats, it also provides compatible functions for handling the traditional text based FASTA or PEFF formats. We believe that SeqWiz will promote the implementing of complementary proteomics for data renewal and proteoform analysis to achieve precision proteomics. Additionally, it can also drive the improvement of proteomic standardization and the development of next-generation proteomic softwares.

Statistical evidence and surprise unified under possibility theory

AbstractSander Greenland argues that reported results of hypothesis tests should include the surprisal, the base‐2 logarithm of the reciprocal of a p‐value. The surprisal measures how many bits of evidence in the data warrant rejecting the null hypothesis. A generalization of surprisal also can measure how much the evidence justifies rejecting a composite hypothesis such as the complement of a confidence interval. That extended surprisal, called surprise, quantifies how many bits of astonishment an agent believing a hypothesis would experience upon observing the data. While surprisal is a function of a point in hypothesis space, surprise is a function of a subset of hypothesis space. Satisfying the conditions of conditional min‐plus probability, surprise inherits a wealth of tools from possibility theory. The equivalent compatibility function has been recently applied to the replication crisis, to adjusting p‐values for prior information, and to comparing scientific theories.