Mechanistic Features Research Articles

Overcoming a Radical Polarity Mismatch in Strain-Release Pentafluorosulfanylation of [1.1.0]Bicyclobutanes: An Entryway to Sulfone- and Carbonyl-Containing SF5-Cyclobutanes.

The first assortment of achiral pentafluorosulfanylated cyclobutanes (SF5-CBs) are now synthetically accessible through strain-release functionalization of [1.1.0]bicyclobutanes (BCBs) using SF5Cl. Methods for both chloropentafluorosulfanylation and hydropentafluorosulfanylation of sulfone-based BCBs are detailed herein, as well as proof-of-concept that the logic extends to tetrafluoro(aryl)sulfanylation, tetrafluoro(trifluoromethyl)sulfanylation, and three-component pentafluorosulfanylation reactions. The methods presented enable isolation of both syn and anti isomers of SF5-CBs, but we also demonstrate that this innate selectivity can be overridden in chloropentafluorosulfanylation; that is, an anti-stereoselective variant of SF5Cl addition across sulfone-based BCBs can be achieved by using inexpensive copper salt additives. Considering the SF5 group and CBs have been employed individually as nonclassical bioisosteres, structural aspects of these unique SF5-CB "hybrid isosteres" were then contextualized using SC-XRD. From a mechanistic standpoint, chloropentafluorosulfanylation ostensibly proceeds through a curious polarity mismatch addition of electrophilic SF5 radicals to the electrophilic sites of the BCBs. Upon examining carbonyl-containing BCBs, we also observed rare instances whereby radical addition to the 1-position of a BCB occurs. The nature of the key C(sp3)-SF5 bond formation step - among other mechanistic features of the methods we disclose - was investigated experimentally and with DFT calculations. Lastly, we demonstrate compatibility of SF5-CBs with various downstream functionalizations.

Overcoming a Radical Polarity Mismatch in Strain‐Release Pentafluorosulfanylation of [1.1.0]Bicyclobutanes: An Entryway to Sulfone‐ and Carbonyl‐Containing SF5‐Cyclobutanes

AbstractThe first assortment of achiral pentafluorosulfanylated cyclobutanes (SF5‐CBs) are now synthetically accessible through strain‐release functionalization of [1.1.0]bicyclobutanes (BCBs) using SF5Cl. Methods for both chloropentafluorosulfanylation and hydropentafluorosulfanylation of sulfone‐based BCBs are detailed herein, as well as proof‐of‐concept that the logic extends to tetrafluoro(aryl)sulfanylation, tetrafluoro(trifluoromethyl)sulfanylation, and three‐component pentafluorosulfanylation reactions. The methods presented enable isolation of both syn and anti isomers of SF5‐CBs, but we also demonstrate that this innate selectivity can be overridden in chloropentafluorosulfanylation; that is, an anti‐stereoselective variant of SF5Cl addition across sulfone‐based BCBs can be achieved by using inexpensive copper salt additives. Considering the SF5 group and CBs have been employed individually as nonclassical bioisosteres, structural aspects of these unique SF5‐CB “hybrid isosteres” were then contextualized using SC‐XRD. From a mechanistic standpoint, chloropentafluorosulfanylation ostensibly proceeds through a curious polarity mismatch addition of electrophilic SF5 radicals to the electrophilic sites of the BCBs. Upon examining carbonyl‐containing BCBs, we also observed rare instances whereby radical addition to the 1‐position of a BCB occurs. The nature of the key C(sp3)−SF5 bond formation step – among other mechanistic features of the methods we disclose – was investigated experimentally and with DFT calculations. Lastly, we demonstrate compatibility of SF5‐CBs with various downstream functionalizations.

Failure mechanism features and precursor characteristics of coal roadway groups in fault zone under confined conditions

After the stress wave penetrates the fault, it changes the stress direction and destroys the stress balance of the deep underground mining surface and roadway during mining activities, causing the roadway and underground equipment to collapse. To reveal the failure mechanism, we studied the precursor characteristics of unstable failure of rocks in deep roadway groups. With conducting two PFC numerical models based on common roadway layouts, we studied crack development and failure conditions of surrounding rocks near roadway groups by investigating the force chain fracture, coordination number, energy evolution, and acoustic emission moment tensor in the models. The results show that the overall deformation failure of the roadway group first occurs in the upper roadway, and the weak force chain break in the force chain field of the lower roadway is obvious, especially before and after the peak value, accompanied by the coordination number in the direction of 80° with the joint plane significantly reduced. At the same time, obvious force patterns were observed in the roadway group area: irregular gathering (>90°) and swirl (<90°). These findings clarify the mechanism of fault disturbance in roadways surrounding rocks and help to better understand the deformation failure feature and energy evolution process of coal.

Abstract 5766: Fungal genomes in drug discovery: Application of CETSA to study the mechanism of action of brefeldin A

Abstract Fungal genomes encode a vast collection of chemical diversity that has evolved over millions of years to engage specific targets and modulate diverse biological processes. These Genetically Encoded small Molecules (GEMs) constitute a largely untapped source of potential therapeutics. Although fungal GEMs such as cyclosporine, lovastatin, and penicillin have revolutionized modern medicine, these GEMs were discovered serendipitously through bioactivity-guided fractionation of fungal extracts. LifeMine is redefining GEM discovery through the deployment of proprietary genomic search algorithms that enable GEM target prediction a priori. Our strategy facilitates focused search-and-retrieval campaigns to rationally discover molecules selected by Nature to modulate the desired target protein. These GEM drug leads often exhibit unique structural and mechanistic features, necessitating comprehensive deconvolution of the human target profile and mechanism of action during the development process from GEM to clinical candidate. As a proof-of-concept study, we leveraged CETSA Explore to study the biological mechanism of the fungal polyketide lactone Brefeldin A (BFA) in human THP-1 cells. This GEM, originally isolated from the filamentous fungus Penicillium brefeldianis, inhibits protein trafficking between the endoplasmic reticulum and the Golgi complex, eliciting antiviral, antifungal, and anticancer activity. Our CETSA profiling study confirmed the Golgi-associated guanine nucleotide exchange factor GBF1 as the primary target of BFA, validating the established mechanism of this GEM as an inhibitor of GBF1-mediated activation of the small GTPase ARF1. These results demonstrate the utility of integrating the LifeMine GEM discovery engine with downstream proteomic profiling technologies to facilitate the mechanistic characterization of fungal GEMs en route to novel therapeutics. Citation Format: Tomas Friman, Benjamin M. Fontaine, Alexey Chernobrovkin, Daniel Martinez Molina, Victoria Brehmer, Stina Lundgren, Paola M. Castaldi, Gregory L. Verdine. Fungal genomes in drug discovery: Application of CETSA to study the mechanism of action of brefeldin A [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5766.

Investigation of the impact of fiber incorporation on the properties of high belite cement

In contrast to ordinary portland cement (PC), the manufacturing process of high belite cement (HBC) boasts superior resource utilization, reduced energy consumption, and diminished greenhouse gas emissions. Additionally, HBC exhibits notable strengths in terms of durability and mechanical properties. This study delves into the thermal characteristics of hydration, mechanical behaviour, and failure mechanisms of HBC materials, both with and without fiber admixtures, employing a multifaceted approach encompassing hydration heat experiments, uniaxial compression tests, Brazilian tensile tests, alongside advanced techniques such as acoustic emission (AE) and digital image correlation (DIC). The results indicate that HBC has lower hydration heat release, contributing to a reduction in hydration temperature rise, offering advantages in large-scale structural construction. In terms of strength development, HBC exhibits compressive and tensile strengths similar to PC, while the strength of basalt fiber-reinforced HBC is notably lower than both. In terms of failure modes, both HBC and PC undergo shear failure in uniaxial compression tests, whereas basalt fiber-reinforced HBC experiences splitting failure. In Brazilian tensile tests, HBC and PC exhibit single-direction cracking, while basalt fiber-reinforced HBC shows synchronous cracking at the top, middle, and bottom. Due to the crack-arresting effect of basalt fibers, basalt fiber-reinforced HBC displays a bimodal feature on the stress-strain curve and features a stress plateau on both the stress-strain and strain energy development curves.

A Structural Reliability Analysis Method Considering Multiple Correlation Features

The paper analyzes the correlation features between stress strength, multiple failure mechanisms, and multiple components. It investigates the effects of different correlation features on reliability and proposes a method for structural reliability analysis that considers the joint effects of multiple correlation features. To portray the stress–strength correlation structure, the Copula function is utilized and the influence of the correlation degree parameter on reliability is clarified. The text describes the introduction of time-varying characteristics of structural strength and correlation parameters. A time-varying Copula is then constructed to calculate the structural reliability under the stress–strength correlation characteristics. Additionally, a time-varying hybrid Copula is constructed to characterize the intricate and correlation features of multiple failure mechanisms and components. The article proposes the variational adaptive sparrow search algorithm (VASSA) to obtain optimal parameters for the time-varying hybrid Copula. The effectiveness and accuracy of the proposed method are verified through actual cases. The results indicate that multiple correlation features significantly influence structural reliability. Incorporating multiple correlation features into the solution of structural reliability yields safer results that align with engineering practice.

The complement system in neurodegenerative diseases.

Complement is an important component of innate immune defence against pathogens and crucial for efficient immune complex disposal. These core protective activities are dependent in large part on properly regulated complement-mediated inflammation. Dysregulated complement activation, often driven by persistence of activating triggers, is a cause of pathological inflammation in numerous diseases, including neurological diseases. Increasingly, this has become apparent not only in well-recognized neuroinflammatory diseases like multiple sclerosis but also in neurodegenerative and neuropsychiatric diseases where inflammation was previously either ignored or dismissed as a secondary event. There is now a large and rapidly growing body of evidence implicating complement in neurological diseases that cannot be comprehensively addressed in a brief review. Here, we will focus on neurodegenerative diseases, including not only the 'classical' neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, but also two other neurological diseases where neurodegeneration is a neglected feature and complement is implicated, namely, schizophrenia, a neurodevelopmental disorder with many mechanistic features of neurodegeneration, and multiple sclerosis, a demyelinating disorder where neurodegeneration is a major cause of progressive decline. We will discuss the evidence implicating complement as a driver of pathology in these diverse diseases and address briefly the potential and pitfalls of anti-complement drug therapy for neurodegenerative diseases.

Organophotocatalytic Carbamoylation of Morita‐Baylis‐Hillman Carbonates

AbstractHerein, we demonstrate that carbamoyl radicals generated through an organophotocatalytic protocol from 4‐carbamoyl‐dihydropyridines (carbamoyl‐DHPs) can be incorporated into Morita‐Baylis‐Hillman (MBH) carbonates, affording a range of polyfunctionalized scaffolds with yields ranging from 63–98%. Reaction monitoring experiments, scale‐up, reuse of the organophotocatalyst, and the hydrogenation of the succinamic ester's alkene moiety was also conducted, in order to showcase the mechanistic features and the robustness of this photochemical protocol.

Accessibility of Urban Tourism in Historical Areas: Analysis of UNESCO World Heritage Sites in Safranbolu

Expansion of cities with population growth leads to the differentiation of urban texture, negatively affecting the accessibility of tourism areas in historical regions. For this reason, there is a need to develop tourism areas that enable people to experience the areas of historical heritage. Sustainable urban development, which is also the theory of the study, has become an agenda for the protection and revitalization of historical areas in order to increase accessibility to tourism. The Safranbolu Protected Area, which is one of the oldest settlements with its traditional housing texture and which is included in the UNESCO World Heritage Sites List in Turkey, was chosen as the study area. In this study, the aim is to examine the accessibility of historical tourism centers, analyze the spatial configuration of the street texture in the city of Karabük and determine the features of the formation mechanism of the Safranbolu historical region. The research questions are based on the impact of (1) the accessibility of the street network on the formation mechanism of the urban architecture and (2) the shaping of urban tourism areas in historical cities. The space syntax method was used to examine the relationship between the building features of the Safranbolu Urban Protected Area and the formation features of the space. Within the scope of the study, the accessibility of the Safranbolu historical center was examined through the street texture that shapes the city form using data from Open Street Map. Segment and axial analyses were made based on the current street network data of the city. The key findings of the research revealed that the accessibility level of the city’s street network was practically effective in shaping the Safranbolu Urban Protected Area. It was theoretically found that the streets with a high global integration value in the city have an impact on the shaping of traditional architecture and constitute important routes for tourism in sustainable development. The findings serve as a reference for researchers in sustainable development, urban planners and local governments who will use it to test the methodology for understanding the street layout of the historical area and improving the experiential characteristics of the users.

Ceramic metal oxide coatings formation by hybrid plasma electrolytic treatment: Interaction scenarios of ceramic NPs with oxide layers

Understanding the formation of protective ceramic metal oxide (CMO) coatings (layers) on the surface of light alloys remains a pressing task in light of products operating in extreme conditions. Plasma electrolytic oxidation (PEO) of light alloy surfaces has recently been modified by introducing various ceramic nanoparticles (NPs) into the electrolyte to perform hybrid plasma electrolytic treatment (HPET). In this work, the general and distinctive features of the interaction mechanisms of TiC, SiO2 and ZrO2 nanoparticles (NPs) with the CMO coating formed by HPET of Al–Si and Mg-based alloys were summarized and theoretically substantiated. The interaction of charged ceramic NPs accelerated by an electric field with the oxide layer is determined by transformation of the NPs kinetic energy into heating and plastic deformation, into phase transformations, as well as into the creation of new surface defects. One of the controlling factors is the ratio of the particle and the oxide layer hardnesses. In the case of SiO2 in Al–Si alloys, the formed coating is harder than the ceramic NPs while in other cases, the NPs are harder than the CMO coating, which determines the different scenarios for the interaction of NPs with the coating under HPET. In summary 7 different scenarios for the interaction of ceramic NPs added to the electrolyte with the СМO layer during its formation put forward, which depending on the ratio of the hardness of the CMO layer and the added particles, temperature/pressure conditions of the phase transformations in the NP (including its melting), the particles size distribution and the base PEO process parameters.

Theoretical formulation of chemical equilibrium under vibrational strong coupling

Experiments have suggested that strong interactions between molecular ensembles and infrared microcavities can be employed to control chemical equilibria. Nevertheless, the primary mechanism and key features of the effect remain largely unexplored. In this work, we develop a theory of chemical equilibrium in optical microcavities, which allows us to relate the equilibrium composition of a mixture in different electromagnetic environments. Our theory shows that in planar microcavities under strong coupling with polyatomic molecules, hybrid modes formed between all dipole-active vibrations and cavity resonances contribute to polariton-assisted chemical equilibrium shifts. To illustrate key aspects of our formalism, we explore a model SN2 reaction within a single-mode infrared resonator. Our findings reveal that chemical equilibria can be shifted towards either direction of a chemical reaction, depending on the oscillator strength and frequencies of reactant and product normal modes. Polariton-induced zero-point energy changes provide the dominant contributions, though the effects in idealized single-mode cavities tend to diminish quickly as the temperature and number of molecules increase. Our approach is valid in generic electromagnetic environments and paves the way for understanding and controlling chemical equilibria with microcavities.

Molecular Mechanism for Converting Carbon Dioxide Surrounding Water Microdroplets Containing 1,2,3-Triazole to Formic Acid.

Spraying water microdroplets containing 1,2,3-triazole (Tz) has been found to effectively convert gas-phase carbon dioxide (CO2), but not predissolved CO2, into formic acid (FA). Herein, we elucidate the reaction mechanism at the molecular level through quantum chemistry calculations and ab initio molecular dynamics (AIMD) simulations. Computations suggest a multistep reaction mechanism that initiates from the adsorption of CO2 by Tz to form a CO2-Tz complex (named reactant complex (RC)). Then, the RC either is reduced by electrons that were generated at the air-liquid interface of the water microdroplet and then undergoes intramolecular proton transfer (PT) or switches the reduction and PT steps to form a [HCO2-(Tz-H)]- complex (named PC-). Subsequently, PC- undergoes reduction and the C-N bond dissociates to generate COOH- and [Tz-H]- (m/z = 69). COOH- easily converts to HCOOH and is captured at m/z = 45 in mass spectroscopy. Notably, the intramolecular PT step can be significantly lowered by the oriented electric field at the interface and a water-bridge mechanism. The mechanism is further confirmed by testing multiple azoles. The AIMD simulations reveal a novel proton transfer mechanism where water serves as a transporter and is shown to play an important role dynamically. Moreover, the transient •COOH captured by the experiment is proposed to be partly formed by the reaction with H•, pointing again to the importance of the air-water interface. This work provides valuable insight into the important mechanistic, kinetic, and dynamic features of converting gas-phase CO2 to valuable products by azoles or amines dissolved in water microdroplets.

First-Principles High-Throughput Inverse Design of Direct Momentum-Matching Band Alignment van der Waals Heterostructures Utilizing Two-Dimensional Indirect Semiconductors.

Two-dimensional (2D) van der Waals (vdW) heterostructures have attracted widespread attention in photocatalysis. Herein, we employ a novel strategy utilizing first-principles high-throughput inverse design of 2D Z-scheme heterojunctions for photocatalysis. This approach is anchored in high-throughput screening conditions, which are fundamentally based on the characteristics of carrier mechanisms influenced significantly by Z-scheme heterojunctions. A pivotal element of our screening process is the integration of the indirect-to-direct bandgap transition with momentum-matching band alignment in k-space, guiding us to combine two 2D indirect bandgap monolayers into direct Z-scheme heterojunctions characterized by pronounced interlayer excitons. Various stacking modes introduce extra and distinct degrees of freedom that can be useful for tuning the properties of heterostructures, encompassing factors such as components, stacking patterns, and sequences. We demonstrate that various stacking modes can facilitate the indirect-to-direct bandgap transition and the emergence of interlayer excitons. These findings provide exciting opportunities for designing Z-scheme heterojunctions in photocatalysis.

Key mechanistic features of the trade-off between antibody escape and host cell binding in the SARS-CoV-2 Omicron variant spike proteins

Since SARS-CoV-2 Omicron variant emerged, it is constantly evolving into multiple sub-variants, including BF.7, BQ.1, BQ.1.1, XBB, XBB.1.5 and the recently emerged BA.2.86 and JN.1. Receptor binding and immune evasion are recognized as two major drivers for evolution of the receptor binding domain (RBD) of the SARS-CoV-2 spike (S) protein. However, the underlying mechanism of interplay between two factors remains incompletely understood. Herein, we determined the structures of human ACE2 complexed with BF.7, BQ.1, BQ.1.1, XBB and XBB.1.5 RBDs. Based on the ACE2/RBD structures of these sub-variants and a comparison with the known complex structures, we found that R346T substitution in the RBD enhanced ACE2 binding upon an interaction with the residue R493, but not Q493, via a mechanism involving long-range conformation changes. Furthermore, we found that R493Q and F486V exert a balanced impact, through which immune evasion capability was somewhat compromised to achieve an optimal receptor binding. We propose a “two-steps-forward and one-step-backward” model to describe such a compromise between receptor binding affinity and immune evasion during RBD evolution of Omicron sub-variants.

Design and Efficacy of a Data Lake Architecture for Multimodal Emotion Feature Extraction in Social Media

In the rapidly evolving landscape of social media, the demand for precise sentiment analysis (SA) on multimodal data has become increasingly pivotal. This paper introduces a sophisticated data lake architecture tailored for efficient multimodal emotion feature extraction, addressing the challenges posed by diverse data types. The proposed framework encompasses a robust storage solution and an innovative SA model, multilevel spatial attention fusion (MLSAF), adept at handling text and visual data concurrently. The data lake architecture comprises five layers, facilitating real-time and offline data collection, storage, processing, standardized interface services, and data mining analysis. The MLSAF model, integrated into the data lake architecture, utilizes a novel approach to SA. It employs a text-guided spatial attention mechanism, fusing textual and visual features to discern subtle emotional interplays. The model’s end-to-end learning approach and attention modules contribute to its efficacy in capturing nuanced sentiment expressions. Empirical evaluations on established multimodal sentiment datasets, MVSA-Single and MVSA-Multi, validate the proposed methodology’s effectiveness. Comparative analyses with state-of-the-art models showcase the superior performance of our approach, with an accuracy improvement of 6% on MVSA-Single and 1.6% on MVSA-Multi. This research significantly contributes to optimizing SA in social media data by offering a versatile and potent framework for data management and analysis. The integration of MLSAF with a scalable data lake architecture presents a strategic innovation poised to navigate the evolving complexities of social media data analytics.

A thin-walled cavity structure with double-layer tapered scatterer locally resonant metamaterial plates for extreme low-frequency attenuation

Locally resonant acoustic metamaterials (LRAMs) are effective spatial frequency filters due to their local resonance system. However, they own narrow stopbands, charge additional weight on the primary system, and operate only at the adjusted frequency range. In this paper, a novel dual-target LRAM is proposed based on coupling the cavity and convex mechanisms, utilizing the benefits of both sound-barrier and sound-absorbing types of acoustic metamaterials. A combination of the cavity and convex structures is presented and investigated for the first time, which exploits both the reflection and absorption theories simultaneously to improve the sound attenuation performance of acoustic metamaterials. By arranging two-layer finite periodic of 5×5 proposed convex unit cells along x and y directions and separating them by an air cavity, a supercell named hybrid locally resonant acoustic metamaterials (HLRAM) baffle is designed. The band structures, transmission spectrum, and displacement vector fields are calculated employing the finite element method (FEM). In addition, vibration modes at the edges of stopbands are computed and carefully analyzed to determine the formation mechanism, mechanics/dynamic response, and dispersion features of stopbands. Meanwhile, sensitivity analyses have been conducted on the model to investigate the influence of material and geometry parameters on dispersion characteristics. Equivalent spring-mass analytic models are used to direct the modifications of structure and the adjustment of structural and material parameters in order to achieve a wide stopband with a low opening frequency. Thereby, the effective stiffness and mass values influencing the starting and cutoff frequencies are adjusted in a desirable manner. The results show that the structure can generate a wide stopband that covers the frequency range of 64.9-805.6Hz, allowing the structure to block incoming acoustic waves with 35.42dB root mean square of noise attenuation (RMSNA) the given frequency range (0-1kHz). This study indicates that the HLRAM has a preponderance among conventional techniques as we can manipulate dispersion characteristics and the sound transmission loss (STL) based on the desired sound reduction level and shift stopbands to the intended frequency range. This can be achieved by altering cavity size, material, or geometry parameters.

Inferring brain causal and temporal-lag networks for recognizing abnormal patterns of dementia

Brain functional network analysis has become a popular method to explore the laws of brain organization and identify biomarkers of neurological diseases. However, it is still a challenging task to construct an ideal brain network due to the limited understanding of the human brain. Existing methods often ignore the impact of temporal-lag on the results of brain network modeling, which may lead to some unreliable conclusions. To overcome this issue, we propose a novel brain functional network estimation method, which can simultaneously infer the causal mechanisms and temporal-lag values among brain regions. Specifically, our method converts the lag learning into an instantaneous effect estimation problem, and further embeds the search objectives into a deep neural network model as parameters to be learned. To verify the effectiveness of the proposed estimation method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database by comparing the proposed model with several existing methods, including correlation-based and causality-based methods. The experimental results show that our brain networks constructed by the proposed estimation method can not only achieve promising classification performance, but also exhibit some characteristics of physiological mechanisms. Our approach provides a new perspective for understanding the pathogenesis of brain diseases. The source code is released at https://github.com/NJUSTxiazw/CTLN.

Construction and Multi-Mode Motion Analysis of Single-Degree-of-Freedom Four-Bar Multi-Mode Planar Mechanisms Based on Singular Configuration

Abstract The traditional four-bar mechanism is renowned for its simple structure, dependable performance, and wide range of applications. The single-degree-of-freedom (DOF) four-bar multi-mode planar mechanism (MMPM) is a type of four-bar mechanism that not only has the structural characteristics of the traditional four-bar mechanisms but also can achieve multiple motion modes by changing its structure. It has the advantage of performing diverse functions while conserving resources, which opens up new possibilities for research and application of the four-bar mechanism. However, due to the lack of a systematic configuration construction method, the design and application of single-DOF four-bar MMPMs are seriously limited. This paper presents a systematic method to construct a set of single-DOF four-bar MMPMs based on the loop equations and the proposed multi-mode modules (MMMs). First, depending on the loop equations, the four-bar planar mechanism containing two branches is identified by the corresponding branch graphs. Then, three kinds of MMMs are systematically proposed for the first time, helping the identified mechanism realize multiple motion modes. Subsequently, single-DOF four-bar MMPMs are constructed by replacing the specific component of the planar mechanism with the MMMs. Furthermore, the replacement rules of MMMs and the corresponding construction steps are summarized. Finally, 14 kinds of single-DOF four-bar MMPMs are listed, and the corresponding multi-mode motion analysis is discussed at the end of this paper. The proposed method is a straightforward one, which will provide great convenience for the configuration design of single-DOF four-bar MMPMs and promote the development and application of MMPMs.

IPO algorithm on the platform of the Belarusian currency and stock exchange

Studying the features of the IPO mechanism on the platform of the Belarusian сurrency and stock еxchange is an important task, the solution of which will allow enterprises to increase investment potential or attract financing through the stock market of the Republic of Belarus, which is relevant for the agricultural sector in matters of regulating solvency and economic efficiency.Based on the systematization and development of the methodological foundations for analyzing and identifying trends on the issues under study, a recommendation has been developed for conducting a public offering of shares on the stock market. It involves a detailed breakdown of each stage of the IPO from the moment of decision making to summing up the results.

Fault diagnosis of gearbox driven by vibration response mechanism and enhanced unsupervised domain adaptation

Although data-driven model has achieved remarkable results in gearbox fault diagnosis, its diagnostic accuracy is still highly dependent on large amounts of high-quality labeled samples. Some data generation methods, such as generative adversarial network, are utilized to address this problem. However, the generated simulation samples not only lack fault mechanism features with clear physical meaning, but also have distribution differences with the real samples. Aiming at the above problems, an enhanced unsupervised domain adaption method combined with vibration response mechanism is proposed for gearbox fault diagnosis. Firstly, various fault types of labeled simulation signals with clear physical meaning are generated based on vibration response mechanism of gearbox, alleviating the lack of large amounts of high-quality labeled samples for data-driven models. Secondly, to narrow the inevitable domain discrepancy between simulation samples and experimental samples, a domain mapping method is raised to both transform their distributions to normal distribution by optimizing an alignment function, which also could effectively improve the diagnostic speed and accuracy of intelligent models. Finally, the mapped samples are directly fed into an arbitrary unsupervised domain adaptation model to achieve fault diagnosis in the absence of any label information of measured samples. Importantly, the proposed domain mapping method can be simply appended to any existing core network to enhance diagnostic accuracy without necessitating modifications to its structure or training procedure. Experiments on two gearbox datasets suggest that the proposed method can effectively boost the performance of diagnosis issues with only a small number of experimental samples and outperform existing diagnosis approaches.