Kermesite (Sb₂S₂O), a needle-like unstable secondary oxysulfide, has made visible advancements in optimizing its triclinic crystal system through twinning discovery. However, research on twinning behavior at micro and nano scales, including its growth mechanisms and impact on kermesite morphologies, remains notably scarce. Our study focuses on kermesite crystal clusters from a private collection in Yunnan, China, confirming the chemical formula as Sb₂S_1.97O_1.03 through EPMA. Single-crystal XRD yielded refined unit cell parameters (a = 8.153(5) Å, b = 10.717(7) Å, c = 5.796(3) Å; α = 102.836(10)°, β = 110.556(8)°, γ = 100.999(12)°), revealing space group P$\overline{1}$ with Z = 4 and indicating twinning with a ratio of 27.4%. Remarkably, a Transmission Electron Microscope (TEM) provided the first direct observation of twinning in natural kermesite, revealing rotational twins with varying widths and lengths (ranging from 100 nm to several millimeters). Analysis and simulation elucidated that rotational twins, generated by a 180° rotation, align with the mineral’s elongation direction along the [Sb₂S₂O₄]_n chains (a-axis), challenging the conventional long-axis direction (b-axis) for crystal growth. This study proposes a symbiotic relationship between kermesite growth and twinning, suggesting that the observed X-shaped growth in crystal clusters results from the collaboration of single crystals (growing along b) and twins (growing along a) in the unit cell. These findings contribute to our understanding of kermesite’s structural complexities and the potential growth and formation mechanism of crystal clusters. Full article

Gear factories are most typical discrete manufacturing factories. Many gear factories are striving to explore how to achieve intelligent manufacturing in order to improve efficiency and reduce costs. Digital twin technology is currently one of the most reliable ways to achieve intelligent manufacturing. This article aims to establish a real-time control system in order to promote intelligent manufacturing for discrete manufacturing factories. Firstly, a model for a digital twin gear factory is put forward based on the characteristics of gear factories, and the composition of a real-time control system for gear factories is clarified. Then, a human–computer interaction architecture for the real-time control system is proposed. The real-time control system consists of three parts as follows: a monitoring module, a virtualizing module, and a controlling module. At work, it appears as a kind of human–machine interaction form with the three following interfaces: a monitoring window, a virtualizing window, and a controlling window. Finally, a gear factory, which is specialized in manufacturing the intermediate shaft dual gear of a new energy vehicle gearbox, develops a set of software for the real-time control system. The prototype software is obtained through some development activities such as 3D MAX and WebGL virtualization modeling and OPC UA and REST communication design. Full article

A general overview of Noise-Shaping Successive Approximation Register (SAR) analog-to-digital converters is provided, encompassing the fundamentals, operational principles, and key architectures of Noise-Shaping SAR (NS SAR). Key challenges, including inherent errors in processing circuits, are examined, along with current advancements in architecture design. Various issues, such as loop filter optimization, implementation methods, and DAC network element mismatches, are explored, along with considerations for voltage converter performance. The design of dynamic comparators is examined, highlighting their critical role in the SAR ADC architecture. Various architectures of dynamic comparators are extensively explored, including optimization techniques, performance considerations, and emerging trends. Finally, emerging trends and future challenges in the field are discussed. Full article

This review addresses the need for innovative co-culture systems integrating the enteric nervous system (ENS) with intestinal organoids. The breakthroughs achieved through these techniques will pave the way for a transformative era in gastrointestinal (GI) disease modeling and treatment strategies. This review serves as an introduction to the companion protocol paper featured in this journal. The protocol outlines the isolation and co-culture of myenteric and submucosal neurons with small intestinal organoids. This review provides an overview of the intestinal organoid culture field to establish a solid foundation for effective protocol application. Remarkably, the ENS surpasses the number of neurons in the spinal cord. Referred to as the “second brain”, the ENS orchestrates pivotal roles in GI functions, including motility, blood flow, and secretion. The ENS is organized into myenteric and submucosal plexuses. These plexuses house diverse subtypes of neurons. Due to its proximity to the gut musculature and its cell type complexity, there are methodological intricacies in studying the ENS. Diverse approaches such as primary cell cultures, three-dimensional (3D) neurospheres, and induced ENS cells offer diverse insights into the multifaceted functionality of the ENS. The ENS exhibits dynamic interactions with the intestinal epithelium, the muscle layer, and the immune system, influencing epithelial physiology, motility, immune responses, and the microbiome. Neurotransmitters, including acetylcholine (ACh), serotonin (5-HT), and vasoactive intestinal peptide (VIP), play pivotal roles in these intricate interactions. Understanding these dynamics is imperative, as the ENS is implicated in various diseases, ranging from neuropathies to GI disorders and neurodegenerative diseases. The emergence of organoid technology presents an unprecedented opportunity to study ENS interactions within the complex milieu of the small and large intestines. This manuscript underscores the urgent need for standardized protocols and advanced techniques to unravel the complexities of the ENS and its dynamic relationship with the gut ecosystem. The insights gleaned from such endeavors hold the potential to revolutionize GI disease modeling and treatment paradigms. Full article

To harness the strengths and mitigate the limitations of line-commutated converter (LCC) and modular multilevel converter (MMC) HVDC systems, the LCC-MMC hybrid HVDC system has been developed. This paper proposes a holomorphic embedding (HE)-based power flow calculation method for AC/DC power systems with the LCC-MMC hybrid HVDC system. Firstly, the methodology involves establishing the mathematical model of the LCC-MMC hybrid HVDC system and its control modes. Subsequently, the HE formulation for the constructed LCC-MMC model is derived using the HE method. The proposed method simplifies the HE formulation using substitute variables, making it adaptable to various control modes. The designed HE formulation facilitates the derivation of the germ solution and the calculation of high-order power series coefficients. A sequential solution flow chart compatible with AC power flow algorithms is constructed to enhance the practicality of the HE method for real-world large-scale systems. The accuracy and effectiveness of the proposed method are verified through numerical tests on the modified IEEE 14-bus, IEEE 57-bus, and large 2383-bus system. The proposed method provides a reliable and efficient solution for power flow analysis in hybrid HVDC systems. Full article

This article aims to introduce a set of hybrid matrix polynomials associated with $\lambda$-polynomials and explore their properties using a symbolic approach. The main outcomes of this study include the derivation of generating functions, series definitions, and differential equations for the newly introduced two-variable Hermite $\lambda$-matrix polynomials. Furthermore, we establish the quasi-monomiality property of these polynomials, derive summation formulae and integral representations, and examine the graphical representation and symmetric structure of their approximate zeros using computer-aided programs. Finally, this article concludes by introducing the idea of 1-variable Hermite $\lambda$ matrix polynomials and their structure of zeros using a computer-aided program. Full article

Brain–computer interface (BCI) systems include signal acquisition, preprocessing, feature extraction, classification, and an application phase. In fNIRS-BCI systems, deep learning (DL) algorithms play a crucial role in enhancing accuracy. Unlike traditional machine learning (ML) classifiers, DL algorithms eliminate the need for manual feature extraction. DL neural networks automatically extract hidden patterns/features within a dataset to classify the data. In this study, a hand-gripping (closing and opening) two-class motor activity dataset from twenty healthy participants is acquired, and an integrated contextual gate network (ICGN) algorithm (proposed) is applied to that dataset to enhance the classification accuracy. The proposed algorithm extracts the features from the filtered data and generates the patterns based on the information from the previous cells within the network. Accordingly, classification is performed based on the similar generated patterns within the dataset. The accuracy of the proposed algorithm is compared with the long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM). The proposed ICGN algorithm yielded a classification accuracy of 91.23 ± 1.60%, which is significantly (p < 0.025) higher than the 84.89 ± 3.91 and 88.82 ± 1.96 achieved by LSTM and Bi-LSTM, respectively. An open access, three-class (right- and left-hand finger tapping and dominant foot tapping) dataset of 30 subjects is used to validate the proposed algorithm. The results show that ICGN can be efficiently used for the classification of two- and three-class problems in fNIRS-based BCI applications. Full article

Objectives: This retrospective case-controlled study aimed to evaluate the association between the severity of fall-related injuries and fall-risk-increasing drugs (FRIDs) in hospitalized patients. Methods: Data were collected from Changhua Christian Hospital, Taiwan, of all adult inpatients who experienced falls between January 2017 and December 2021, and were divided into two groups based on whether they sustained severe fall-related injuries. Retrospective data that may affect the severity of fall-related injuries and the use of FRIDs were investigated. Results: Among 1231 documented cases of falls, 26 patients sustained severe fall-related injuries. Older patients and those with osteoporosis were more susceptible to more severe injuries from a fall. The use of mobility aids and osteoporosis medications showed protective effects against fall injuries. No significant association was observed between fall-related injuries and comorbidities or FRIDs. Multivariate analysis confirmed the inverse correlation between the use of mobility aids, osteoporosis medications, and fall severity. Patients with osteoporosis exhibited significantly higher odds of sustaining more severe injuries with a fall (odds ratio = 3.02, 95% confidence interval: 1.21–7.53). Conclusions: This study highlights the importance of addressing risk factors associated with fall severity among hospitalized patients. Providing mobility aids to persons at greater risk. Full article

Carbon-sequestering microorganisms play an important role in the carbon cycle of wetland ecosystems. However, the response mechanism of carbon-sequestering microbial communities to wetland type changes and their relationship with soil carbon remain unclear. To explore these differences and identify the main influencing factors, this study selected marsh wetlands, river wetlands and lakeside wetlands around Qinghai Lake as research subjects. High-throughput sequencing was employed to analyze the functional gene cbbM of carbon-sequestering microorganisms. The results revealed that the alpha diversity of cbbM carbon-sequestering microorganisms mirrored the trend in total carbon content, with the highest diversity observed in marsh wetlands and the lowest in lakeside wetlands. The dominant bacterial phylum was Proteobacteria, with prevalent genera including Thiothrix, Acidithiobacillus, and Thiodictyon. Acidithiobacillus served as a biomarker in lakeside wetlands, while two other genera were indicative of marsh wetlands. The hierarchical partitioning analysis indicated that the diversity of cbbM carbon-fixing microorganisms was primarily influenced by the total nitrogen content, while the community structure was significantly affected by the soil total carbon content. Moreover, an increased soil temperature and humidity were found to favor the carbon fixation processes of Thiomicrospira, Thiomonas, Polaromonas, and Acidithiobacillus. In summary, changes in wetland types seriously affected the characteristics of cbbM carbon sequestration in microbial communities, and a warm and humid climate may be conducive to wetland carbon sequestration. Full article

Cancer stem cells (CSCs) play a key role in tumor progression, as they are often responsible for drug resistance and metastasis. Environmental pollution with polystyrene has a negative impact on human health. We investigated the effect of polystyrene nanoparticles (PSNPs) on cancer cell stemness using flow cytometric analysis of CD24, CD44, ABCG2, ALDH1 and their combinations. This study uses simultaneous in vitro cell lines and an in silico machine learning (ML) model to predict the progression of cancer stem cell (CSC) subpopulations in colon (HCT-116) and breast (MDA-MB-231) cancer cells. Our findings indicate a significant increase in cancer stemness induced by PSNPs. Exposure to polystyrene nanoparticles stimulated the development of less differentiated subpopulations of cells within the tumor, a marker of increased tumor aggressiveness. The experimental results were further used to train an ML model that accurately predicts the development of CSC markers. Machine learning, especially genetic algorithms, may be useful in predicting the development of cancer stem cells over time. Full article

Previous studies suggested that spring precipitation over the tropical western Pacific Ocean can influence the development of El Niño–Southern Oscillation (ENSO). To identify crucial precipitation patterns for post-spring ENSO evolution, a singular value decomposition (SVD) method was applied to spring precipitation and sea surface temperature (SST) anomalies, and three precipitation and ENSO types were obtained with each highlighting precipitation over the Maritime Continent (MC) or western north Pacific (WNP). High MC spring precipitation corresponds to the slow decay of a multi-year La Niña event. Low MC spring precipitation is associated with a rapid El Niño-to-La Niña transition. High WNP spring precipitation is related to positive north Pacific meridional mode and induces the El Niño initiation. Among the three ENSO types, ocean current and heat content behave differently. Based on these spring precipitation and oceanic factors, a statistical model was established aimed at predicting winter ENSO state. Compared to a full dynamical model, this model exhibits higher prediction skills in the winter ENSO phase and amplitude for the period of 1980–2022. The explained total variance of the winter Niño-3.4 index increases from 43% to 75%, while the root-mean-squared error decreases from 0.82 °C to 0.53 °C. The practical utility and limitations of this model are also discussed. Full article

Objectives: This study entailed a weekly analysis of real-world data (RWD) on the safety and efficacy of intravitreal (IVT) faricimab in neovascular age-related macular degeneration (nAMD). Methods: A retrospective, single-centre clinical trial was conducted at the Department of Ophthalmology, University Hospital Zurich, University of Zurich, Switzerland, approved by the Cantonal Ethics Committee of Zurich, Switzerland. Patients with nAMD were included. Data from patient charts and imaging were analysed. The safety and efficacy of the first faricimab injection were evaluated weekly until 4 weeks after injection. Results: Sixty-three eyes with a complete 4-week follow-up were enrolled. Six eyes were treatment-naïve; fifty-seven eyes were switched to faricimab from another treatment. Neither group showed signs of retinal vasculitis during the 4 weeks after injection. Central subfield thickness (CST) and volume (CSV) showed a statistically significant decrease compared to the baseline in the switched group (CST: p = 0.00383; CSV: p = 0.00702) after 4 weeks. The corrected visual acuity returned to the baseline level in both groups. The macular neovascularization area decreased in both groups, but this was not statistically significant. A complete resolution of sub- and intraretinal fluid after 4 weeks was found in 40% (switched) and 75% (naïve) of the treated patients. Conclusions: The weekly follow-ups reflect the structure–function relationship beginning with a fast functional improvement within two weeks after injection followed by a return to near-baseline levels after week 3. The first faricimab injection in our cohort showed a high safety profile and a statistically significant reduction in macular oedema in switched nAMD patients. Full article

The global food trade network (FTN) is a critical infrastructure for achieving the Sustainable Development Goals (SDGs). The FTN’s vulnerability to geopolitical conflicts, public health crises, and climate change events directly impacts food security and the ability to meet the SDGs. This study aims to analyze the dynamic evolution of the vulnerability of FTN, focusing on the period from 2000 to 2022, to aim for strategies for enhancing the resilience and sustainability of the global food system. Based on complex network analysis, we examine the structural characteristics and evolution of FTN for four major crops: soybeans, wheat, rice, and maize. We identify a trend towards increased network density and regionalization, with a decline in average shortest path length (ASPL) and an increase in the average clustering coefficient (ACC). These changes indicate a shift towards a more interconnected and resilient FTN in response to various shocks, including the COVID-19 pandemic and the Russia–Ukraine conflict. The findings suggest that the global FTN has adapted to increase resilience, which is essential for achieving the SDGs related to food security and sustainable development. The study’s insights can guide policy interventions to further strengthen the network against future shocks and promote global food security. Full article

Cooperative adaptive cruise control (CACC) is one of the main features of connected and autonomous vehicles (CAVs), which uses connectivity to improve the efficiency of adaptive cruise control (ACC). The addition of reliable communication systems to ACC reduces fuel consumption, maximizes road capacity, and ensures traffic safety. However, the performance, stability, and safety of CACC could be affected by the transmission of outdated data caused by communication delays. This paper proposes a Lyapunov-based nonlinear controller to mitigate the impact of time-varying delays in the communication channel of CACC. This paper uses Lyapunov–Krasovskii functionals in the stability analysis to ensure semi-global uniformly ultimately bounded tracking. The efficaciousness of the proposed CACC algorithm is demonstrated in simulation and through experimental implementation. Full article

Orthodontic space closure following tooth extraction is often hindered by alveolar bone deficiency. This study investigates the therapeutic use of nuclear factor-kappa B (NF-κB) decoy oligodeoxynucleotides loaded with polylactic-co-glycolic acid nanospheres (PLGA-NfDs) to mitigate alveolar bone loss during orthodontic tooth movement (OTM) following the bilateral extraction of maxillary first molars in a controlled experiment involving forty rats of OTM model with ethics approved. The decreased tendency of the OTM distance and inclination angle with increased bone volume and improved trabecular bone structure indicated minimized alveolar bone destruction. Reverse transcription-quantitative polymerase chain reaction and histomorphometric analysis demonstrated the suppression of inflammation and bone resorption by downregulating the expression of tartrate-resistant acid phosphatase, tumor necrosis factor-α, interleukin-1β, cathepsin K, NF-κB p65, and receptor activator of NF-κB ligand while provoking periodontal regeneration by upregulating the expression of alkaline phosphatase, transforming growth factor-β1, osteopontin, and fibroblast growth factor-2. Importantly, relative gene expression over the maxillary second molar compression side in proximity to the alveolus highlighted the pharmacological effect of intra-socket PLGA-NfD administration, as evidenced by elevated osteocalcin expression, indicative of enhanced osteocytogenesis. These findings emphasize that locally administered PLGA-NfD serves as an effective inflammatory suppressor and yields periodontal regenerative responses following tooth extraction. Full article

Flavonoids and stilbenoids, crucial secondary metabolites abundant in plants and fungi, display diverse biological and pharmaceutical activities, including potent antioxidant, anti-inflammatory, and antimicrobial effects. However, conventional production methods, such as chemical synthesis and plant extraction, face challenges in sustainability and yield. Hence, there is a notable shift towards biological production using microorganisms like Escherichia coli and yeast. Yet, the drawbacks of using E. coli and yeast as hosts for these compounds persist. For instance, yeast’s complex glycosylation profile can lead to intricate protein production scenarios, including hyperglycosylation issues. Consequently, Corynebacterium glutamicum emerges as a promising alternative, given its adaptability and recent advances in metabolic engineering. Although extensively used in biotechnological applications, the potential production of flavonoid and stilbenoid in engineered C. glutamicum remains largely untapped compared to E. coli. This review explores the potential of metabolic engineering in C. glutamicum for biosynthesis, highlighting its versatility as a cell factory and assessing optimization strategies for these pathways. Additionally, various metabolic engineering methods, including genomic editing and biosensors, and cofactor regeneration are evaluated, with a focus on C. glutamicum. Through comprehensive discussion, the review offers insights into future perspectives in production, aiding researchers and industry professionals in the field. Full article

Although, in recent years, it has been common to monitor players in team sports using EPTSs (Electronic Performance and Tracking Systems) devices, most of the studies have focused on the optimization of individual performance rather than collective work or tactical analysis. Moreover, almost all these studies focus on men’s teams with little focus on women’s teams. In this work, data from women’s soccer teams at different levels (competition and grassroots) have been collected using both a low-cost personally developed EPTS and a commercial EPTS. With these systems, we have built a dataset consisting of more than 16 million records, paying special attention to spatio-temporal variables collected in the form of geographical coordinates. Different methods have been applied to the collected dataset to solve the problem of determining the position (individual role) of each player on the field based solely on spatio-temporal variables. The methods include algorithms based on clustering, centroid calculation, and computer vision. We have verified the effectiveness of these methods and propose an alternative method based on image recognition algorithms applied to heat maps generated from the position of the players monitored during the matches. As shown in this paper, the validity of the proposed method has been verified, exceeding the performance of existing methods and extending the range of application of these techniques. Full article

Microdroplets generated in microfluidic devices are attracting attention as a new chemical reaction field and are expected to improve reactivity. One of the effects of microscaling is that the ratio of the force that acts on the diffusion and movement of substances to gravity is different from that of ordinary solvents. Recently, we proposed a hypothesis for determining reaction acceleration through micro-miniaturization: If a reaction is inhibited by setting the volume and viscosity of the solution to conditions that are unfavorable to the reaction on a normal scale, that reaction can be promoted in microfluidics. Therefore, for the purpose of this verification, (1) we used an amino acid Schiff base copper(II) complex with an azobenzene group to demonstrate the polarization-induced orientation in a polymer film (the redirection that is mechanically maintained in a soft matter matrix). Numerical data on optical anisotropy parameters were reported. (2) When the reaction is confirmed to be promoted in laminar flow in a microfluidic device and its azo derivative, a copper(II) complex is used to increase the solvent viscosity or diffusion during synthesis on a normally large scale. We will obtain and discuss data on the investigation of changing the solvent volume as a region. The range of experimental conditions for volume and viscosity did not lead to an improvement in synthetic yield, nor did (3) the comparison of solvents and viscosity for single-crystal growth of amino acid Schiff base copper(II) complexes having azobenzene groups. A solvent whose viscosity was measured was used, but microcrystals were obtained using the diffusion method. Full article

With respect to a traditional point-to-point (P-P) network, a hub-and-spoke (H-S) network not only uses a smaller number of links/paths but also utilizes the scale economy advantage on consolidated flows on hub–hub links and at hubs. However, the inevitable delays through hubs have always been a critical concern. Therefore, this paper develops an H-S model considering flow delay costs and applies the model to a logistics case in Eastern China. The integer quadratic term in the model’s objective function is linearized using the algebraic method. Our model is applied to develop an H-S network for its 13-node express package delivery operation, using the particle swarm optimization (PSO) algorithm. The results show using the H-S can save more than 14.1% of the total cost annually. The model also provides an applied case to the H-S configuration, especially for urban express delivery logistics in China. Full article

Background: Wound healing competence is implied in the nursing profession, but there is no standardized content regulation for wound care in university curricula. The primary objective of this study was to identify the barriers to the acquisition of knowledge about skin integrity impairment. Methods: A quasi-experimental pre-test and post-test study with an ad hoc questionnaire involved 304 students (control: 165; intervention: 139) from June to July 2023. A 10-hour educational intervention focused on skin integrity assessment and treatment was conducted. Results: The control group, scoring 17 ± 0.22 out of a maximum of 61, achieved a significantly lower final test score (p < 0.001) compared to the wound care educational intervention group, with the pre-test group scoring 30 ± 0.76 and the post-test group scoring 43 ± 0.61. The educational intervention in wound care program improved nursing students' knowledge of prevention, assessment/diagnosis, treatment, lower limb wounds, and wound bed preparation by replacing the number of "Don't know" answers in the post-test group with correct answers. Conclusions: The barriers identified to the acquisition of knowledge about skin integrity impairment in nursing studies are the following: the transversality of teaching, the teaching and evaluation system, and the variability in the training of professionals and teachers in charge of their education. The educational intervention can be used to consolidate knowledge and to enhance students’ self-confidence in caring for patients with wounds. Full article

(1) Background: Various guidelines address patient preparation and its importance for venous blood sampling, such as the GP41 guideline issued by the Clinical Laboratory Standards Institute (CLSI) and the blood collection guidelines published by the World Health Organisation. Recommendations provided by national societies or international organisations in the field of radiology, such as The Contrast Media Safety Committee of the European Society of Urogenital Radiology, or in the field of laboratory medicine, such as the Working Group for Preanalytical Phase (WG-PRE) of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and the Latin American Working Group for Preanalytical Phase (WG-PRE-LATAM) of the Latin American Confederation of Clinical Biochemistry (COLABIOCLI), also guide this practice. There is a notable lack of understanding regarding the viewpoints held by non-laboratory healthcare professionals concerning the significance of patient preparation for laboratory testing and the impact of typical factors associated with patient preparation. This study endeavours to bridge this gap by assessing the attitude of non-laboratory healthcare professionals in Lithuania regarding these pivotal aspects. (2) Methods: A self-designed anonymous questionnaire was disseminated among 141 public healthcare institutions in Lithuania. The internal consistency of the questionnaire was evaluated by computing Cronbach’s alpha. Descriptive statistics were utilised for the variables, while comparisons of attitude among groups were conducted using Mann–Whitney U (for two groups) or Kruskal–Wallis (for more than two groups) for categorical and discrete indicators. The Kruskal–Wallis post-hoc test was employed for pairwise comparisons. A significance level of p-Value < 0.05 was applied to establish statistical significance. (3) Results: A total of 158 respondents constituted two distinct groups of healthcare professionals: nurses and physicians. Most of the participants either agreed or strongly agreed that patient preparation could introduce bias into laboratory test results. Professionals with less than 20 years of work experience or those who attended training in patient preparation for sampling within a 5-year timeframe exhibited stronger agreement regarding different preanalytical factors in patient preparation and their impact on laboratory test results compared to their counterparts. (4) Conclusions: Non-laboratory healthcare professionals who participated in this survey consider proper patient preparation for laboratory testing to be a significant step towards obtaining accurate test results. They also recognize the commonly acknowledged preanalytical factors as important for ensuring reliable test results. However, attitudes towards the importance of several preanalytical factors vary depending on whether non-laboratory healthcare professionals have more or less than 20 years of work experience, as well as whether they have attended any training on this topic within the last five years or have never attended such training. Full article

The aim of this work was the investigation of novel organocatalysts for the Michael addition of diethyl malonate to β-nitrostyrene. The methodology of the study included NMR titration, reaction monitoring by NMR spectroscopy and electrospray ionization mass spectrometry (ESI-MS), product characterization by MALDI, IR spectroscopy, scanning electron microscopy (SEM), thermal gravimetric analysis (TGA), and elemental analysis. As a result, evidence of supramolecular interactions between two pairs of components of the reaction was found. In addition to the supramolecular complexes, an unusual reaction, i.e., the Michael addition of NH-bispidines to β-nitrostyrene, was found, which led to previously unknown oligomers of β-nitrostyrene. A new mechanism for the catalytic action of NH-bispidine was proposed, which involved catalysis not by the initial organocatalyst but rather by its adduct with β-nitrostyrene. Thus, in this reaction, N-benzylbispidine acted as an initiator, and the real catalyst was the betaine formed during the initiation stage. Full article