Research on high efficiency operation and low pollutant emission collaborative control of gas engine driven heat pump

Accurate characterization of the initial in-situ stress field is essential for stability assessment, support design, and surrounding rock control in deep underground engineering, yet field measurements are often highly scattered and three-dimensional inversion is computationally expensive. This study develops a robust and efficient inversion framework for a deeply buried underground powerhouse in the southeastern Tibetan Plateau. First, a three-dimensional borehole stress synthesis method is established by combining particle swarm optimization, the Huber loss, Levenberg-Marquardt iteration, and regularization to denoise multi-source measurements, suppress local outliers, and alleviate ill-conditioning in stress-tensor reconstruction. Second, a surrogate-assisted differential evolution workflow is constructed using a radial basis function network within a prediction-verification-correction active-learning loop to reduce the cost of repeated forward simulations while preserving global optimization capability. Application to the powerhouse shows that the mean relative error decreases from 14.12 to 9.34%, and the deviation variance decreases from 2.98 to 1.33 after optimization. The proposed framework improves both the reliability of inversion input data and the efficiency of field-scale stress reconstruction, providing practical support for stability evaluation and surrounding rock control in deep, geologically complex underground caverns.

Experimental datasets are essential for validating adaptive control strategies, data-driven monitoring approaches, and control-oriented system identification methods. Despite their importance, publicly available benchmarks based on real nonlinear processes remain limited. This work presents a collection of 25 long-duration time-series datasets totaling over 760,000 samples, obtained from a laboratory two tank water pumping plant. Experiments were conducted under closed-loop adaptive control with a 1 second sampling period, where each execution spans approximately 8.5 hours. The files capture diverse operational conditions, including steady-state baselines and disturbance scenarios with abrupt outflow variations. Each dataset contains timestamps, valve positions, tank levels, control signals, tracking errors, adaptive PID gains tuned via Dahlin's synthesis, and real-time model parameters estimated using recursive least squares. Data quality assessment confirms the integrity of the collection through exploratory analysis, controller behavior evaluation across multiple regimes, and a baseline anomaly detection case study. Capturing key nonlinearities such as turbulence and actuator saturation, this resource primarily supports control engineering tasks including adaptive control evaluation, disturbance rejection analysis, and data-driven monitoring, while also providing a testbed for control-oriented identification under realistic closed-loop conditions.

Bladder disorders such as overactive bladder and neurogenic bladder impose a major symptom burden, yet neuromodulation therapies are largely delivered with fixed open-loop settings and limited adaptation to time-varying bladder states. Bladder digital twins are patient-anchored computational models linked to sensing streams and updated via state estimation and/or data assimilation. They offer a pathway to closed-loop personalized therapy, but bladder implementations remain fragmented across modeling, sensing, and stimulation. This review synthesizes digital twin technologies relevant to bladder physiology, sensing, and neuromodulation and translates lessons from mature organ digital twins to bladder requirements for closed-loop control. We conducted targeted searches of PubMed, Web of Science, IEEE Xplore, and Google Scholar (2013 to 2025). We reviewed digital twin paradigms for the heart, brain, lungs, liver, and kidney and summarized bladder approaches including finite-element bladder-wall mechanics, conductivity-based torso models for wearable bioimpedance optimization, strain-to-geometry reconstruction using stretchable sensors, and sensor-informed closed-loop control. Clinically deployable twins pair mechanistic structure with limited reliable data streams and use hybrid estimation for indirect, noisy measurements. In bladder applications, feasibility has been demonstrated for state estimation and model-guided design; key barriers include ambulatory motion artifacts and impedance drift, sparse clinical anchors for personalization, limited longitudinal human validation, and incomplete safety engineering for stimulation control. A roadmap toward closed-loop bladder digital twins should prioritize ambulatory-grade sensing with artifact handling and recalibration, uncertainty-aware real-time state estimation, model-informed stimulation optimization, and fail-safe control with standardized reporting of accuracy, latency, uptime, and drift.

Birefringence, as a manifestation of optical anisotropy in crystalline materials, is a fundamental physical property that plays a crucial role in nonlinear optics, polarization control, and photonic device engineering. Traditionally, birefringence has been primarily ascribed to geometric anisotropy in crystal structures. However, recent research has demonstrated that anisotropic electronic distributions, even in geometrically symmetric frameworks, can significantly enhance optical anisotropy. In this work, we report on the synthesis, structural characterization, and optical property evaluation of Rb2ZnGe3Se8, a newly identified member of the AI2BIIMIV3Q8 chalcogenide family, which exhibits a large theoretical birefringence of 0.257 at the wavelength of 1064 nm. First-principles calculations reveal that the large birefringence arises from spatially anisotropic electron distributions within the [GeSe4] tetrahedra, rather than from overt structural distortion. The results highlight a distinct electronic origin of birefringence and expand the current understanding of how directionally polarized bonding interactions can induce significant optical anisotropy in nominally symmetric frameworks. This work deepens the understanding of structure-electronic-optical coupling mechanisms in layered chalcogenide frameworks and supports the rational design of materials with large birefringence.

Endovascular embolization is one of the core techniques in minimally invasive interventional medicine. It allows catheters to be accurately delivered to target blood vessels under image guidance for the implantation of embolic materials to achieve vascular occlusion. Although this technique has become increasingly mature, it still faces major challenges in precise delivery due to the limitations of embolic-agent properties and design concepts, restricting further improvement of the embolization therapeutic efficacy. Driven by continuous breakthroughs in materials science and control engineering, as well as the inevitable trend of medical development toward miniaturization, precision, and intelligence, microrobots show broad application prospects in precision disease treatment. They present advantages in accurate embolization and remote control in endovascular embolization, which can effectively improve embolization outcomes and reduce the risk of ectopic embolism. Taking the embolic microrobot system as the research focus, this paper systematically elaborates the design strategies, validation models, and practical applications of magnetically actuated embolic microrobots, comprehensively evaluates various imaging systems, and summarizes the supporting magnetic actuation technologies. It concludes the multimodule collaboration and adaptation framework of embolic microrobot systems. Finally, it analyzes the current limitations and potential translational challenges and presents a systematic prospect of its future development trends.

The reversibility of Zn deposition/stripping in aqueous zinc metal batteries (ZMBs) is governed by the interfacial kinetics and unstable electrolyte-metal chemistry. Here we introduce a hybrid-entropy (HE) electrolyte that leverages entropy-driven solvation restructuring to tailor the Zn2+ coordination environment and interfacial thermodynamics. By amplifying the entropy contribution, quantified through Boltzmann's equation, HE electrolyte diminishes the Gibbs free energy of the system, thermodynamically minimizing chemical-potential gradients that promote interfacial heterogeneity. This entropic modulation triggers the spontaneous formation of an inorganic-organic composite interphase on the Zn surface, which homogenizes ion flux and shifts the Zn nucleation behavior from instantaneous to progressive modes, enabling dense and dendrite-free metal growth. These coupled mechanisms confer improved anode reversibility, delivering a cycling lifetime exceeding 3000h in Zn||Zn symmetric cells and high Coulombic efficiency of 99% over 1000 cycles in Zn||Cu cells. Consequently, practical NaV3O8||Zn pouch cells with a capacity of 1.38 Ah under high mass loading and low negative-to-positive capacity ratio (N/P) ≈ 4.2 demonstrate stable operation for over 30 days at 2.0 mA·cm-2 with negligible capacity decay. This work highlights controllable entropy engineering as an effective design principle for aqueous electrolytes and charts a viable route toward durable, high-performance ZMBs.

Modern coffee processing generates a complex, co-localized mixture of respiratory hazards, such as carbon monoxide (CO), volatile α-diketones (principally diacetyl and 2,3-pentanedione), and bio-reactive coffee dust, that challenge single-agent risk paradigms. This systematic review synthesizes quantitative exposure data, exposure-response relationships, mechanistic plausibility, and control efficacy to characterize the occupational respiratory burden associated with simultaneous exposure to these agents. A systematic search of literature (in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses - PRISMA 2020) was conducted choosing eligible studies reported quantitative exposure metrics (CO in ppm, α-diketones in ppb, particulate matter in mg/m3) and respiratory health outcomes among coffee industry workers. Task-based monitoring identified grinding, flavoring, and packaging as peak emission events. Epidemiological findings included sentinel clusters of obliterative bronchiolitis, increased prevalence of obstructive spirometric abnormalities, and measurable forced expiratory volume (FEV1) declines associated with cumulative α-diketone exposure; organic dust exposure correlated with chronic cough, dyspnea, and reduced FEV1/forced vital capacity. Co-exposure to CO, α-diketones, and coffee dust in roasting, grinding, and packaging operations produces a substantive occupational respiratory risk profile, including both acute systemic hazards and chronic small-airway injury. Preventing occupational risk requires prioritizing engineering controls, task-specific ventilation design for peak emissions, and longitudinal exposure and health surveillance to define dose-response relationships for complex mixtures and to inform evidence-based occupational exposure limits. Med Pr Work Health Saf. 2026;77(3).

Empirical logic (EL) is a bio-inspired soft computing approach to rule-based decision-making that emphasizes intuitive, experience-based reasoning. While its theoretical foundations have been established in previous work, its practical applicability and accessibility have so far received less attention. This paper addresses this gap by providing two representative application examples from distinct domains: control engineering and cluster analysis. The first example demonstrates the use of EL for the speed control of a DC drive, highlighting its ability to achieve competitive dynamic performance with a small number of intuitive rules. The second example introduces a novel approach to cluster analysis, where cluster structures emerge from the collective interaction of EL rules rather than from the optimization of a predefined objective function. In addition, the paper emphasizes the availability of publicly accessible software realizations of EL, including a Maple-based prototype and a Python framework, which enable direct experimentation and practical use. By combining illustrative applications with executable tools, the paper aims to facilitate the transition from conceptual understanding to practical deployment and to support further exploration of EL in applied soft computing contexts.

Phosphoric acid-doped polybenzimidazole membranes are a leading fluorine-free electrolyte platform for high-temperature proton exchange membrane fuel cells, enabling proton transport under anhydrous conditions. However, recent evidence shows that conductivity, mechanical stability, and acid retention are intrinsically coupled, preventing independent optimization of these properties. This review establishes a unified framework in which membrane performance is governed by a multidimensional design space defined by acid doping level, activation energy (Ea), hydrogen-bond network topology, and mechanical confinement. Conductivity is shown to scale with both carrier density and hopping energetics, while mechanical stability decays with increasing ADL due to acid-induced plasticization, described through a semi-empirical relationship. Analysis across molecular architectures, including molecular weight control, crosslinking, backbone modification, topological design, and free-volume engineering, demonstrates that performance emerges from a balance between transport efficiency and structural stability. Device-level benchmarking further reveals that similar conductivity values can correspond to orders-of-magnitude differences in voltage decay rate, confirming that durability is governed primarily by mechanical confinement and acid mobility rather than σ alone. A multivariate stability corridor is identified, within which phosphoric acid-doped polybenzimidazole membranes achieve σ ≈ 0.14-0.20 S·cm-1 while maintaining low degradation rates under realistic high temperature proton exchange membrane conditions. Based on this framework, quantitative design rules are derived linking acid doping level, activation, topology, and mechanical properties. This work shifts membrane design from conductivity-driven optimization toward predictive structure-property-durability engineering, providing a basis for the development of next-generation HT-PEM fuel cells with sustained long-term performance.

Hydrogen is a promising clean-energy carrier, but its low ignition energy, high diffusivity, and wide flammability range demand reliable leak detection. Chemiresistive sensors based on n-type metal oxide semiconductors are attractive owing to their simple architecture, low cost, large resistance modulation, thermal robustness, and compatibility with miniaturized devices. This review focuses on n-type metal oxide semiconductor nanomaterials for hydrogen sensing, particularly ZnO, SnO2, In2O3, WO3, TiO2, and related mixed oxides. The fundamental sensing mechanisms are examined, including oxygen chemisorption, electron-depletion-layer modulation, grain-boundary barrier control, catalytic hydrogen spillover, and hydrogen-induced surface reduction or metallization, together with the way these mechanisms compete and cooperate under different operating conditions. Recent performance-enhancement strategies are organized around morphology and porosity control, noble-metal sensitization, defect and dopant engineering, n-n heterojunctions, molecular sieving, and low-temperature activation. Density functional theory is discussed as a design tool for evaluating adsorption energetics, vacancy formation, work-function shifts, band alignment, and interfacial charge transfer, along with its current limitations for modeling humid surfaces. Finally, key challenges and future directions, including humidity tolerance, standardized reporting, device integration, and emerging materials, are summarized to guide the development of high-performance hydrogen sensors.

Exponential synchronization of T-S fuzzy complex-valued BAM neural networks with mixed time-varying delays via event-triggered control engineering and applications.

(a) surgical masks provide inadequate protection against airborne pathogens; (b) the current WHO guidelines are harming healthcare workers (HCWs) and patients; and (c) WHO as a global healthcare safety leader has the power to reduce disease burden in healthcare settings through more effective advocacy. WHO should lead decisively toward safer healthcare by establishing respirators as the universal default for all healthcare encounters, with clearly defined, locally-determined off-ramps based on transparent risk indicators and the use of effective engineering controls. This recommendation would align WHO policy with science and existing safety standards and would improve safety for both patients and healthcare providers.

Programmable methylation engineering: Design principles from alkaloid biosynthesis.

Street-food grilling is a common occupation in Asia, yet the occupational health risks associated with cooking-generated polycyclic aromatic hydrocarbons (PAHs) exposure, occurring alongside plausible unmeasured co-exposures such as ambient heat and physical workload, remain under-researched. This study investigated the internal dose of PAH exposure and its association with early biological effects and physiological strain among grill restaurant workers. A cross-sectional study was conducted involving grill workers and 20 age/BMI-matched controls. Urinary 1-hydroxypyrene (1-OHP) was utilized as the primary exposure biomarker. The study assessed early biological effects such as oxidative stress (8-OHdG, F2-isoprostanes), lung epithelial integrity (CC16), and genotoxicity (BPDE-DNA adducts) via ELISA. Physiological parameters, including blood pressure and heart rate, were recorded to evaluate acute cardiovascular strain. Workers had significantly elevated urinary 1-OHP levels compared to controls (Hodges-Lehmann ratio = 3.66, 95% CI: 1.68-7.12, representing a 3.7-fold median increase), with exposure levels increasing proportionally to smoke proximity. Notably, workers demonstrated a significantly higher median resting heart rate (HL ratio = 1.13, 95% CI: 1.05-1.23; +12.9%) and systolic blood pressure (HL ratio = 1.09, 95% CI: 1.00-1.18; +8.9%) compared to their office-based peers. Although strong correlations were observed among biological effect biomarkers (rs = 0.42-0.63), there were no significant differences between groups for 8-OHdG, CC16, or BPDE-DNA adducts, suggesting that cardiovascular parameters reflect acute short-term responses, while genomic damage markers may require higher cumulative exposure thresholds to become detectable. The study revealed that grill restaurant workers face substantial internal PAH exposure and significant cardiovascular strain, occurring alongside plausible unmeasured co-exposures including ambient heat and physical workload. The prevalence of chronic cough and elevated heart rate is a critical early warning sign for occupational health. Our findings indicate that current general ventilation is inadequate, highlighting an urgent need for localized engineering controls and comprehensive health surveillance, including cardiovascular monitoring in the service sector.

Recently, Al2O3/TiO2 nanolaminates (ATA NLs) have emerged as promising materials because of their excellent optical, mechanical, and dielectric properties. However, as individual sublayer thicknesses (ts) decrease into the subnanometer range, the impact of interfacial structure evolution on performance degradation remains poorly understood. Here, we have fabricated a series of amorphous subnanometric ATA NLs, with ts values ranging from ∼1 to 0.17 nm, using atomic layer deposition (ALD) and systematically investigated how interfacial evolution affects their structural, electronic, and dielectric properties, particularly their Maxwell-Wagner (M-W) relaxation behavior. The XRR and TEM measurements of NLs confirm the formation of artificial periodic structures with discrete sublayers as thin as ∼0.67 nm. The NL with a ts of 0.67 nm exhibited enhanced M-W interfacial polarization-assisted high k (∼230) and low loss (∼0.07) values, whereas the submonolayer systems suffered from degraded dielectric performance. A comprehensive suite of characterization techniques revealed a critical transition in interface morphology, sublayer density, interface chemistry, and functionality in dielectric behavior near the monolayer thickness regime (ts ≈ 0.35 nm), marking a transition from continuous-to-discontinuous layer growth with an increased level of intermixing. Electronic structure analyses revealed an associated redistribution of Ti3+ and oxygen vacancy-induced in-gap states and strong interfacial interdiffusion-driven Al-Ti-O compound formation in the submonolayer regime. These chemical changes from the hybridized electronic environments detrimentally affect dielectric properties due to compromised interfacial confinement. These findings establish a ts of ≈0.35 nm as the practical lower bound for maintaining atomically discrete oxide layers, underscoring the pivotal role of nanoscale interface engineering and defect control in optimizing dielectric behavior in ultrathin oxide heterostructure-based devices.

Bupleurum chinense DC. is a commonly used medicinal plant, and the main bioactive compounds are saikosaponins (SSs), which significantly influence its therapeutic quality. 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is the first rate-limiting enzyme in the mevalonate (MVA) pathway, providing precursors for SSs biosynthesis. The lack of studies on the HMGR gene family in B. chinense has limited further understanding of the SSs biosynthesis mechanism. This study performed a genome-wide analysis of the BcHMGR gene family, including phylogenetic and gene structure analysis, cis-elements prediction, quantitative real-time PCR (qRT-PCR) in different tissues, and high-performance liquid chromatography (HPLC) analysis after phytohormone treatments, and explored the potential relationship between BcHMGR expression and SSs biosynthesis. Four Bupleurum chinense HMGR genes (BcHMGRs) were classified into two subfamilies, distributed across two chromosomes, and appeared to have expanded via segmental duplication. The BcHMGR proteins may possess highly conserved catalytic domains, and their promoters contain stress- and hormone-responsive cis-elements. Phytohormone treatments regulated BcHMGR expression and influenced SSs accumulation in a genotype-dependent manner. BcHMGR1, BcHMGR3, and BcHMGR4 showed root-predominant expression across most genotypes. This pattern is consistent with the accumulation sites of SSs and suggests a potential association. In particular, the relative expression levels of BcHMGR3 and BcHMGR4 showed significant increases after exogenous hormone treatment. These results suggest that they may be candidate genes involved in SSs biosynthesis, although their specific functions still require further verification. These findings provide candidate genes for future functional studies and potential regulation of SSs production in B. chinense and offer a theoretical basis for future metabolic engineering and artificial control of SSs biosynthesis.

ABSTRACT This study aims to evaluate musculoskeletal disorders and ergonomic risk factors among elderly care technicians. Adopting a near-census design, the study included 52 elderly care technicians (94.5% participation rate) working in a public institution. Musculoskeletal disorders of employees were assessed using the Cornell Musculoskeletal Discomfort Questionnaire, while ergonomic risk levels were analyzed with the QEC (Quick Exposure Check) method method using representative task photographs. The obtained data were statistically examined using independent sample t-tests and One-Way ANOVA, supplemented by post-hoc power and effect size analyses. According to the analysis results, the body regions most frequently reported with discomfort among elderly care personnel were the lower back, knees, back, and neck. The QEC analysis revealed the highest-risk tasks to be transferring elderly individuals (75%), toilet assistance (73%), and repositioning elderly persons in bed (67%). Large effect sizes and high observed power were observed primarily for gender and professional experience after Bonferroni correction (p < .0042), while age- and education-related patterns were interpreted as exploratory trends. The study demonstrates that elderly care personnel are highly exposed to ergonomic risks and commonly experience musculoskeletal disorders. Preventive measures should prioritize a hierarchy of controls, focusing on engineering controls, such as mechanical support during resident transfers, and should be complemented by task redesign and structured staff training within a broader risk-management framework. Future studies should focus on longitudinal research assessing the long-term impacts of ergonomic improvements and comparing different ergonomic analysis methods.

Supramolecular self-assembly provides an attractive route to organic semiconducting nanotubes, yet concurrent control over tube diameter, helicity and wall number remains elusive. Here we report a dynamic-covalent strategy that converts a single perylene diimide aldehyde precursor (PDIOA) into a family of nanotubes through one-pot imine formation with small amines. Combining microscopy, diffraction and DFT analysis, we show that steric congestion at the ortho position programs a helical packing mode that nucleates and propagates tubular architectures. Crucially, the nanotube inner diameter can be predictably "dialled" by the steric demand of the amine: increasing steric bulk progressively contracts the tube cavity. Enantiomeric amines further translate molecular chirality into opposite supramolecular helicities, affording mirror-image helical nanotubes. Moreover, tuning monomer concentration and solvent composition enables uniform double- and triple-walled nanotubes, demonstrating controllable wall-layer engineering within the same chemical platform. The resulting nanotubes exhibit dimension-dependent photoconductive responses, linking programmable nanoscale structure to optoelectronic function. This work establishes a modular, high-throughput and recyclable route to chiral, multiwalled perylene diimide nanotubes with independently addressable diameter, helicity and wall number.

Covalent organic frameworks (COFs) are emerging crystalline porous materials with precisely defined architectures and tunable chemistry, offering strong potential for next-generation gas separation membranes. This review provides a material-centric perspective on COF-based membranes, emphasizing how framework design governs molecular transport behavior. We discuss key structure-property relationships in COF synthesis, highlighting the roles of crystallinity and chemical functionality in regulating selective transport. Recent advances in synthetic methods are compared in terms of framework order, pore alignment, and scalability. The evolution of COF membrane fabrication is then reviewed, from mixed-matrix systems to in situ grown and freestanding membranes, with attention to interfacial engineering, mechanical stability, and orientation control. Fundamental transport mechanisms are summarized to connect pore chemistry with separation performance. Application-focused progress in CO2 and H2 separations is highlighted, where COF membranes have achieved ultrahigh permeance and selectivity exceeding the Robeson upper bound. Finally, we identify key challenges, including defect control, mechanical robustness, scalable manufacturing, and long-term stability under realistic conditions, and outline future directions toward industrial deployment. By integrating framework chemistry, membrane architecture, and transport mechanisms, this review establishes COFs as a versatile platform for energy-efficient gas separations and provides general design principles for crystalline membrane materials.