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SMC complexes play a central role in chromosome organization in all domains of life. The bacterial Smc–ScpAB complex is a three-subunit complex composed of Smc, ScpA and ScpB. ScpA bridges the two ATPase domains of the Smc homodimer, while ScpB, which belongs to the kite family of proteins, interacts with ScpA. The three subunits are known to be equally important for the function of Smc–ScpAB in bacteria. From crystallographic and biochemical studies, evidence is provided that six archaeal ScpA proteins are unable to interact with the only putative ScpB found in these species. Structure-based sequence alignment reveals that these archaeal ScpAs lack the ScpB-binding segment that is commonly present in the middle of bacterial ScpA sequences, which is thus responsible for their inability to interact with ScpB. ScpA proteins lacking the ScpB-binding segment are found to prevail in archaea. Moreover, two archaeal ScpA proteins with a longer middle region also failed to bind their putative ScpB partner. Furthermore, all or most species belonging to five out of 14 euryarchaeotal orders contain Smc and ScpA but not a detectable ScpB homologue. These data support the notion that archaeal Smc-based complexes generally function as a two-subunit complex composed of only Smc and ScpA.

At present, the incidence of tumours is increasing on a yearly basis, and tumourigenesis is usually associated with chromosomal instability and cell cycle dysregulation. Moreover, abnormalities in the chromosomal structure often lead to DNA damage, further exacerbating gene mutations and chromosomal rearrangements. However, the non-SMC condensin I complex subunit G (NCAPG) of the structural maintenance of chromosomes family is known to exert a key role in tumour development. It has been shown that high expression of NCAPG is closely associated with tumour development and progression. Overexpression of NCAPG variously affects chromosome condensation and segregation during cell mitosis, influences cell cycle regulation, promotes tumour cell proliferation and invasion, and inhibits apoptosis. In addition, NCAPG has been associated with tumour cell stemness, tumour resistance and recurrence. The aim of the present review was to explore the underlying mechanisms of NCAPG during tumour development, with a view towards providing novel targets and strategies for tumour therapy, and through the elucidation of the mechanisms involved, to lay the foundation for future developments in health.

The problem of extracting maximum power from a photovoltaic (PV) system with negligible power loss is concerned with the power generating capability of the PV array and nature of the output load. Changing weather conditions and nonlinear behavior of PV systems pose a challenge in tracking of varying maximum power point. A robust nonlinear controller is required to ensure maximum power point tracking (MPPT) by handling nonlinearities of a system and making it robust against changing environmental conditions. Sliding mode controller is robust against disturbances, model uncertainties and parametric variations. It depicts undesirable phenomenon like chattering, inherent in it causing power and heat losses. In this paper, a supertwisting sliding mode algorithm based nonlinear robust controller has been designed for MPPT of a PV system which not only removes the chattering but also enhances the overall system’s dynamic response. Moreover, supertwisting sliding mode controller is robust against changing environmental conditions like change in temperature and irradiance. Noninverting DC-DC Buck-Boost converter has been used as an interface between source and the load. The efficiency of MPPT of a PV system depends upon the accuracy of reference for peak power voltage, therefore an efficient mechanism for reference generation has also been proposed in this work. The reference for peak power voltage has been generated by using a trained artificial neural network, which is to be tracked by proposed nonlinear controllers. Sliding mode controller (SMC) and synergetic controllers have also been designed for MPPT of a PV system in order to compare them with supertwisting sliding mode controller (ST-SMC). Global asymptotic stability of the system has been ensured by using Lyapunov stability criterion. The performance of the proposed nonlinear controllers has been validated in MATLAB/Simulink ODE 45 environment. ST-SMC has also been compared with recently proposed integral backstepping controller and other conventional MPPT controllers given in the literature. The simulation results show the better performance of ST-SMC in terms of best dynamic response and robustness.

This paper investigates the optimal sliding mode control (SMC) of modular multilevel converters (MMCs) by considering control input constraints. Conventional SMC methods for MMCs typically overlook the system’s constraints. To address this, an optimal SMC approach that incorporates control input constraints through quadratic programming (QP) is proposed. The control design problem is formulated in a constrained optimization framework and solved using the infeasible active-set (IAS) method to efficiently achieve the optimal solution. By applying optimal SMC, this work contributes to the advancement of SMC strategies for MMCs by addressing both constraints and performance optimization in a systematic way. This is particularly relevant for real-world applications, where controllers may temporarily exceed their limits before enforcing constraints. To validate the proposed approach, a comparative analysis with conventional SMC methods is performed, and simulation results confirm that the proposed approach provides improved performance.

The permanent magnet synchronous motor (PMSM) is a highly efficient energy saving machine. Due to its simple structural characteristics, good heat radiation capability, and high efficiency, PMSMs are gradually replacing AC induction motors in many industrial applications. The PMSM has a nonlinear system and lies on parameters that differ over time with complex high-class dynamics. To achieve the excessive performance operation of a PMSM, it essentially needs a speed controller for providing accurate speed tracking, slight overshoot, and robust disturbance repulsion. Therefore, this article provides an overview of different robust control techniques for PMSMs and reviews the implementation of a speed controller. In view of the uncertainty factors, such as parameter perturbation and load disturbance, the H∞ robust control strategy is mainly reviewed based on the traditional control techniques, i.e., robust H∞ sliding mode controller (SMC), and H∞ robust current controller based on Hamilton–Jacobi Inequality (HJI) theory. Based on comparative analysis, this review simplifies the development trend of different control technologies used for a PMSM speed regulation system.

Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies. Single-cell and single-nucleus RNA sequencing are used to construct a cellular atlas of the human heart that will aid further research into cardiac physiology and disease.

In this study, a model-free  PIφ-sliding mode control ( PIφ-SMC) methodology is proposed to synchronize a specific class of chaotic fractional-order memristive neural network systems (FOMNNSs) with delays and input saturation. The fractional-order Lyapunov stability theory is used to design a two-level  PIφ-SMC which can effectively manage the inherent chaotic behavior of delayed FOMNNSs and achieve finite-time synchronization. At the outset, an initial sliding surface is introduced. Subsequently, a robust  PIφ-sliding surface is designed as a second sliding surface, based on proportional–integral (PI) rules. The finite-time asymptotic stability of both surfaces is demonstrated. The final step involves the design of a dynamic-free control law that is robust against system uncertainties, input saturations, and delays. The independence of control rules from the functions of the system is accomplished through the application of the norm-boundedness property inherent in chaotic system states. The soft actor-critic (SAC) algorithm based deep Q-Learning is utilized to optimally adjust the coefficients embedded in the two-level  PIφ-SMC controller’s structure. By maximizing a reward signal, the optimal policy is found by the deep neural network of the SAC agent. This approach ensures that the sliding motion meets the reachability condition within a finite time. The validity of the proposed protocol is subsequently demonstrated through extensive simulation results and two numerical examples.

Using a newly developed flow test bench, several charge configurations were analyzed to quantify the influence of the charge configuration in the mold in sheet molding compound (SMC) manufacturing. A test bench was developed to satisfy the industrial needs for the incoming goods inspection as well as the need for the flow characterization of rheological models in the simulation. The test setup has a cylindrical opening for the charge placement, from where the material is pressed into a thin flow channel, forcing the material to reorient. A comparison was performed by juxtaposing the resulting compression pressure recorded during the process. The charge for this test series, placed into the cylindrical opening, has two basal configurations, one consisting of a stack of disks, and the second in a rectangular sheet rolled up into a spiral. Six charge variations were tested in total. The amount of material, the batch, the layering and the production direction of the sheet proved to have a significant influence on the necessary compression pressure. Guidelines about the recommended charge configurations could be derived for optimized production settings, such as a reduction in the compression pressure and modifications to the charge.

Abstract Neuropathologic evaluation remains the gold standard for determining the presence and severity of aging-related neurodegenerative diseases. Researchers at U.S. Alzheimer's Disease Centers (ADCs) have worked for >30 years studying human brains, with the goals of achieving new research breakthroughs. Harmonization and sharing among the 39 current and past ADCs is promoted by the National Alzheimer's Coordinating Center (NACC), which collects, audits, and disburses ADC-derived data to investigators on request. The past decades have witnessed revised disease definitions paired with dramatic expansion in the granularity and multimodality of the collected data. The NACC database now includes cognitive test scores, comorbidities, drug history, neuroimaging, and links to genomics. Relatively, recent advances in the neuropathologic diagnoses of Alzheimer's disease, frontotemporal lobar degeneration (FTLD), and vascular contributions to cognitive impairment and dementia catalyzed a 2014 update to the NACC Neuropathology Form completed by all ADCs. New focal points include cerebrovascular disease (including arteriolosclerosis, microbleeds, and microinfarcts), hippocampal sclerosis, TDP-43, and FTLD. Here, we provide summary data and analyses to illustrate the potential for both hypothesis-testing and also generating new hypotheses using the NACC Neuropathology data set, which represents one of the largest multi-center databases of carefully curated neuropathologic information that is freely available to researchers worldwide.

It has been recently shown that zero padding (ZP)-orthogonal frequency-division multiplexing (OFDM) is a promising candidate for 6G wireless systems requiring joint communication and sensing. In this paper, we consider a multiuser uplink scenario where users are separated in power domain, i.e., non-orthogonal multiple access (NOMA), and use ZP-OFDM signals. The uplink transmission is grant-free and users are allowed to transmit asynchronously. In this setup, we address the problem of time synchronization by estimating the timing offset (TO) of all the users. We propose two non-data-aided (NDA) estimators, i.e., the joint method of moment (JMoM) and the successive moment cancellation (SMC), that employ the periodicity of the second order moment (SoM) of the received samples for TO estimation. Moreover, the coding assisted (CA) version of the proposed estimators, i.e., CA-JMoM and CA-SMC, are developed for the case of short observation samples. We also extend the proposed estimators to multiuser multiple-input multiple-output (MIMO) systems. The effectiveness of the proposed estimators is evaluated in terms of lock-in probability under various practical scenarios. Simulation results show that the JMoM estimator can reach the lock-in probability of one for the moderate range of Eb/N0 values. While existing NDA TO estimators in the literature either offer low lock-in probability, high computational complexity that prevents them from being employed in MIMO systems, or are designed for single-user scenarios, the proposed estimators in this paper address all of these issues.