Precise Formulation Research Articles

Research on Identification of Factors Influencing Low Carbon Buildings in Hebei Province

In the context of actively addressing climate change and vigorously advocating energy conservation and emission reduction globally, low-carbon buildings have become an important direction for the sustainable development of the construction industry. This study closely focuses on the theme of low-carbon buildings in Hebei Province, and conducts in-depth and systematic identification of influencing factors. Through extensive literature review and comprehensive integration of relevant research results at home and abroad, combined with multiple representative practical cases for in-depth analysis, we accurately grasp the key links in low-carbon building practice, and conduct in-depth interviews with senior experts in the field of architecture in Hebei Province to fully draw professional insights and practical experience. Through comprehensive research, it has been found that in terms of policies and regulations, the implementation of building energy-saving standards is insufficient, incentive policies are not yet perfect, and there are obvious loopholes in regulatory mechanisms, resulting in a lack of strong institutional guarantees for the development of low-carbon buildings. At the technical level, the promotion and application of energy-saving technologies are relatively low, the ability for technological innovation is seriously insufficient, and the integration and collaboration between various technologies are poor, making it difficult to support the efficient implementation of low-carbon buildings. In terms of economic costs, the high initial investment costs and uncertainty in operation and maintenance costs have brought significant economic pressure to developers and owners, hindering the market promotion of low-carbon buildings. In the field of social cognition, the public's awareness of environmental protection is weak, and their acceptance and recognition of low-carbon buildings are low. At the same time, there is a shortage of professional talents and insufficient demand for the development of the construction industry. These factors interact and constrain each other, forming a complex mechanism of action that seriously hinders the development process of low-carbon buildings in Hebei Province from multiple aspects. This research provides a solid theoretical basis and decision support for the precise formulation of targeted and feasible strategic measures in the future, which helps to break the current development bottleneck, effectively promote the steady progress of the construction industry in Hebei Province towards a low-carbon development track, and contribute key forces to the achievement of energy-saving and emission reduction goals in the province. It has significant value in improving the environmental, economic, and social benefits of buildings in Hebei Province, and also provides useful reference examples and practical inspirations for the development of low-carbon buildings in other regions of China, in order to jointly promote the green and low-carbon transformation and sustainable development of the construction industry in China.

Extending the QMM Framework to the Strong and Weak Interactions

We extend the Quantum Memory Matrix (QMM) framework, originally developed to reconcile quantum mechanics and general relativity by treating space–time as a dynamic information reservoir, to incorporate the full suite of Standard Model gauge interactions. In this discretized, Planck-scale formulation, each space–time cell possesses a finite-dimensional Hilbert space that acts as a local memory, or quantum imprint, for matter and gauge field configurations. We focus on embedding non-Abelian SU(3)c (quantum chromodynamics) and SU(2)L× U(1)Y (electroweak interactions) into QMM by constructing gauge-invariant imprint operators for quarks, gluons, electroweak bosons, and the Higgs mechanism. This unified approach naturally enforces unitarity by allowing black hole horizons, or any high-curvature region, to store and later retrieve quantum information about color and electroweak charges, thereby preserving subtle non-thermal correlations in evaporation processes. Moreover, the discretized nature of QMM imposes a Planck-scale cutoff, potentially taming UV divergences and modifying running couplings at trans-Planckian energies. We outline major challenges, such as the precise formulation of non-Abelian imprint operators and the integration of QMM with loop quantum gravity, as well as possible observational strategies—ranging from rare decay channels to primordial black hole evaporation spectra—that could provide indirect probes of this discrete, memory-based view of quantum gravity and the Standard Model.

Enhanced siRNA Delivery with Novel Smart Chitosan-Based Formulations.

This study aims to develop an innovative multifunctional and dual responsive drug formulation for precise siRNA delivery to breast cancer sites, addressing the challenges posed by conventional cancer treatments which often result in adverse side effects due to their non-specific nature. The formulation made by incorporating gold coated superparamagnetic iron oxide nanoparticles (Au-SPIONs) into chitosan microspheres, which were subsequently loaded with siRNA. Comprehensive characterization, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier-transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDS) confirmed the formulation's favourable morphology, particle size distribution, chemical composition, and stability, indicating its strong potential for effective siRNA drug delivery applications. The developed formulation demonstrated siRNA encapsulation efficiencies ranging from 27.4% to 88.6% and loading capacity from 0.291% to 1.59%, these values particularly higher for medium molecular weight chitosan. These results were compared across different formulations, showing that variations in chitosan type and crosslinker concentration significantly influenced encapsulation efficiency and drug release profiles. Additionally, our results were compared to previous studies on chitosan microspheres encapsulating organic drugs and siRNA, where the developed system demonstrated similar encapsulation and release properties.. The type of chitosan and the choice of crosslinker significantly influenced the drug release patterns. Diverse release profiles across batches highlighted the necessity for precise formulation control. Incorporating SPIONs into chitosan microspheres presents a promising strategy for magnetically driven, site-specific drug delivery. The dual pH-responsive and magnetic properties enable rapid and targeted siRNA release, leveraging the acidic tumor microenvironment as an internal stimulus in addition to external magnetic stimuli. This novel combination of SPIONs, chitosan microspheres, and siRNA encapsulation represents a new approach for targeted drug delivery. While further research is needed to refine and optimize this approach, our study provides a proof of concept for advancing targeted cancer therapies.

Control Principles of Neural Dynamics Revealed by the Neurobiology of Timing.

Cognition unfolds dynamically over flexible timescales. A major goal of the field is to understand the computational and neurobiological principles that enable this flexibility. Here, we argue that the neurobiology of timing provides a platform for tackling these questions. We begin with an overview of proposed coding schemes for the representation of elapsed time, highlighting their computational properties. We then leverage the one-dimensional and unidirectional nature of time to highlight common principles across these coding schemes. These principles facilitate a precise formulation of questions related to the flexible control, variability, and calibration of neural dynamics. We review recent work that demonstrates how dynamical systems analysis of thalamocortical population activity in timing tasks has provided fundamental insights into how the brain calibrates and flexibly controls neural dynamics. We conclude with speculations about the architectural biases and neural substrates that support the control and calibration of neural dynamics more generally.

Models for information propagation on graphs

Abstract We propose and unify classes of different models for information propagation over graphs. In a first class, propagation is modelled as a wave, which emanates from a set of known nodes at an initial time, to all other unknown nodes at later times with an ordering determined by the arrival time of the information wave front. A second class of models is based on the notion of a travel time along paths between nodes. The time of information propagation from an initial known set of nodes to a node is defined as the minimum of a generalised travel time over subsets of all admissible paths. A final class is given by imposing a local equation of an eikonal form at each unknown node, with boundary conditions at the known nodes. The solution value of the local equation at a node is coupled to those of neighbouring nodes with lower values. We provide precise formulations of the model classes and prove equivalences between them. Finally, we apply the front propagation models on graphs to semi-supervised learning via label propagation and information propagation on trust networks.

Defining Health Management: A Conceptual Foundation for Excellence Through Efficiency, Sustainability and Equity.

The practice of healthcare management is essential for the efficient operation of health services, encompassing leadership, management, and direction within healthcare organisations. 'Health management' extends beyond healthcare management by integrating principles of public health and health policy. As health management is commonly practised but not cohesively recognised, the European Health Management Association (EHMA) conducted this study to develop a cohesive definition of health management. Developed through a qualitative methodology comprising focus group discussions and validation through quantitative expert interviews, this study proposed a holistic definition of health management, incorporating social, environmental and economic determinants of health, cross-sector collaboration, and the 'One Health' approach. The publication of this unified definition has important implications for professional training, policy development, and health outcomes. It provides a foundational framework for curricula, informs precise policy formulation, and promotes excellence through health service delivery that reflects efficiency, sustainability, and equity.

Vertical and spatial differences in ozone formation sensitivities under different ozone pollution levels in eastern Chinese cities

Ozone is the primary air pollutant in eastern China during the warm season. Clarifying the differences in the spatio–temporal evolution of the ozone formation sensitivity between ozone polluted days and clean air days is key for the precise formulation of ozone prevention policies. By combining ground–and satellite–based remote sensing with ground station observations, we identified large spatio–temporal differences in the ozone formation sensitivity in eastern Chinese cities under different ozone pollution levels. Diurnally, the NO2 concentration was higher in the morning and lower at noon on the ozone exceedance days. The HCHO concentration was higher throughout the day, and the transition limited regime or NOx–limited regime contributed more to the ozone formation sensitivity on the ozone exceedance days. Vertically, the ratio of HCHO to NO2 (FNR) was higher on ozone exceedance days, and the contributions of NOx–limited regime at 0–2 km and the transition limited regime at 0–1 km on ozone exceedance days increased considerably. Spatially, HCHO in the North China Plain and middle–lower Yangtze River Plain was significantly increased on ozone exceedance days, while the NO2 concentration in the southeast hills was increased on ozone exceedance days. The difference in FNR values between northern and southern cities in eastern China on O3 exceedance days narrowed, and the ozone formation sensitivity in eastern China tended to be under a transition limited regime. The shifts in the ozone formation sensitivity under different ozone pollution levels implies that controlling only one of the precursors cannot achieve the best O3 prevention effect, and the most appropriate ratio of O3 precursor emission reductions should be designed according to ozone formation sensitivity in the different regions.

Analytical formulation of synthetic minority oversampling technique (SMOTE) for imbalanced learning

Imbalanced data is an issue that affects various applications in machine learning and data science. Synthetic minority oversampling technique (SMOTE) is a common method used to artificially balance the data. Despite the popularity of SMOTE, there is limited information about its analytical properties. In this paper, we develop a precise theoretical formulation of the sampling distribution of SMOTE in several important cases. We also examine the convergence of the SMOTE distribution to the underlying distribution in mean. The results provide a better understanding of SMOTE and other sampling algorithms. In addition, we uncover surprising connections to other fields such as information theory, Euler's constant, and compound distributions. Finally, we show that the SMOTE-generated distribution Z converges to that of the true underlying distribution X in mean.

Linking Animal Feed Formulation to Milk Quantity, Quality, and Animal Health Through Data-Driven Decision-Making.

The global demand for high-quality animal products, particularly dairy, has intensified the need for more precise and efficient livestock feed formulation. This review connects data-driven decision-making in optimizing feed formulation to enhance milk quantity and quality while addressing animal health implications. Modern feed formulation has evolved into a sophisticated, data-centric process by integrating diverse data sources such as nutritional databases, environmental data, and animal performance metrics. Leveraging advanced analytical techniques, such as machine learning and optimization algorithms, have created highly accurate feed formulations tailored to specific livestock needs. These innovations increase milk yield and contribute to developing dairy products with higher nutritional value. Decision Support Systems play a complementary role by offering real-time decision-making capabilities, enabling farmers to make data-informed adjustments composition based on changing conditions. However, despite its potential, the widespread adoption of data-driven feed formulation faces challenges such as data quality, technological limitations, and industry resistance, mostly disjointed processes. The objectives of this review are: (i) to explore the current advancements and challenges of data-driven decision-making in feed formulation, focusing on its connection to milk quantity and quality, and (ii) to highlight how this optimized feed formulation strategy improves sustainable dairy production.

Formulation and characterization of capecitabine muco adhesive beads for the treatment of colorectal cancer

This study focuses on the formulation and characterisation of Capecitabine muco-adhesive beads for the treatment of colorectal cancer. The alginate beads were synthesised using the ionotropic external gelation technique. To maximise encapsulation efficiency and control the release of Capecitabine from the alginate beads, precise formulation conditions were implemented. Results from in vitro dissolution studies revealed that formulations incorporating increasing concentrations of sodium alginate with SCMC released the drug more rapidly compared to those formulated with sodium alginate and HPMC. Moreover, beads prepared using a 2% w/v aluminum chloride solution as the gelling agent demonstrated greater rigidity compared to those formed with a 2% w/v calcium chloride solution. This highlights the importance of selecting an appropriate gelling agent to optimise bead structure and functionality. Further research is necessary to develop the most effective formulations of Capecitabine for improved therapeutic outcomes in colorectal cancer treatment.

Oral Lactoferrin-Responsive Formulation Anchoring around Inflammatory Bowel Region for IBD Therapy.

Oral formulation is the ideal treatment method for inflammatory bowel disease (IBD) therapy, but the mucosal damage and diarrhea symptoms impede the drug retention around the inflammatory region, severely limiting IBD therapeutic efficacy. To address this, an oral astaxanthin (Ast) precise delivery formulation is developed with the selective Ast anchoring around the inflammatory region by the novel lactoferrin (LF)-responsive flocculation. This formulation also heightens the apparent solubility of Ast with the minimized edible safety risks for the edible raw materials. For in vivo IBD therapy, the precise delivery formulation exhibits remarkable outcomes, including a significant increase in colon length and a 100% survival rate. Furthermore, it is verified that the mechanism of treatment is primarily attributed to the improved immunoregulation, epithelial repair, and gut microbiota remodeling after the LF-responsive flocculation. This effective inflammatory-responsive delivery design is instructive and valuable to develop more precise delivery systems for IBD therapy.

Triadic percolation in computer virus spreading dynamics

Abstract In recent years, the threats posed by computer viruses have become increasingly diverse and complex. While classic percolation theory provides a novel perspective for analyzing epidemics and information dissemination, it fails to capture the temporal dynamics of these systems and the effects of virus invasion and governmental regulation. Triadic percolation theory, a recent advancement, addresses these limitations. In this paper, we apply this new percolation mechanism to model the diffusion of computer viruses, deriving a precise mathematical formulation of the triadic percolation model and providing an analytical solution of the triadic percolation threshold. Additionally, we investigate the impact of nonlinear transmission probability characteristics on virus propagation. Numerical simulations demonstrate that reducing the network’s average degree (or the positive regulation) or increasing regulatory interventions raises the outbreak threshold for computer viruses while decreasing their final size. Moreover, the study reveals that nonlinear transmission probabilities result in an increased number of solutions for the final size of the computer viruses. Our findings contribute new insights into controlling the spread of computer viruses.

Exploring the potential molecular targets of hydroxymethylbutyrate and glucosamine fortified whey protein drink to modulate sarcopenia and Alzheimer's disease by in silico and in vitro studies

Fortified foods have garnered significant attention as potential therapeutic strategies with less adverse effects and ready accessibility. However, precise formulation is required to optimize their beneficial effects. Our study aimed to unravel the mechanisms of a functional protein beverage, hydroxymethylbutyrate and glucosamine fortified whey protein drink (HG-WPD), as a possible intervention combatting sarcopenia and Alzheimer's disease (AD) by network pharmacology, molecular docking, and experimental assays. This study investigates the molecular pathways through which HG-WPD acts, by combining in silico and in vitro analyses. Our in silico study predicted the important target proteins, including acetylcholinesterase (AChE), matrix metalloproteinase 9 (MMP9), and angiotensin-converting enzyme (ACE), linked to both diseases. The molecular docking analysis showed that hydroxymethylbutyrate and glucosamine exhibited a notable binding affinity to these proteins, therefore suggesting their possible use as multi-target medicinal agents. In vitro studies on C2C12 myotubes showed that HG-WPD reduced dexamethasone-induced cell death highlighting its potential anti-sarcopenic actions. Furthermore, confirming their possible function in reducing cognitive impairment in AD, the antioxidant tests showed great activity of both substances. The results imply that HG-WPD is potentially effective for future therapeutic approaches as a functional food product with dual benefits in combatting sarcopenia and AD.

Nucleation of recrystallization: A new approach to consider the evolution of the substructure in the system

The mechanisms of nucleation during dynamic and static recrystallization still remain unclear, particularly with respect to their precise formulation into equations, and the specific implications of subgrains features on these mechanisms. In this paper, it is proposed to correlate the grain nucleation with subgrains and low-angle boundaries misorientation evolution. A nucleation criterion that takes into account the low-angle boundary density evolution in the system is established based on thermodynamic considerations. This new approach is based on a reformulation of the Bailey-Hirsch criterion and is derived from calculations of the equilibrium pressure on grain boundaries. The free energy calculations associated with this criterion allow a fine phenomenological description of the associated nucleation frequency. This new approach is tested in the case of recrystallization of a ferritic stainless steel grade during hot compression tests. The evolution of the substructure is then studied for different holding times up to 20 s after hot compression. It appears that the nucleation frequency based on the proposed nucleation criterion is in agreement with the nucleation frequency derived from experimental observations. This approach allows a better understanding of the mechanisms governing the ability of a subgrain to nucleate in a given system, using rather simple assumptions.

Optimization of Amylose to Amylopectin Ratio and Degree of Substitution in Quaternized Starch as a Tool to Improve Paper Strength

AbstractCationic starch serves as a prevalent wet‐end additive in the papermaking industry. Yet, the definitive effects of the ratio between the two principal components—amylose (AM) and amylopectin (AP)—and the degree of substitution (DS) on the mechanical strength enhancement of paper sheets remain incompletely understood. This study synthesizes a series of quaternized amylose (QAM) and quaternized amylopectin (QAP) with varying DS levels and blended these derivatives in diverse ratios. Subsequently, these mixtures are integrated into pulp suspensions to ascertain the DS and the AM‐to‐AP ratio that optimize paper strength. These results indicate that a QAM‐to‐QAP blend with a DS of 0.08 at a ratio of 2:8 yielded the most pronounced improvement in paper mechanical properties. This precise formulation significantly enhances tensile, burst, and tear strength indices, increasing by approximately 55.0%, 44.4%, and 78.4%, respectively, under the most favorable conditions and with an additive dosage of 1 wt.%. This investigation provides substantive and actionable knowledge for selecting starch additives in the wet‐end of papermaking, which can significantly augment the efficiency and efficacy of paper manufacturing processes.

Wood–Cement Composites: A Sustainable Approach for Mitigating Environmental Impact in Construction

The construction industry’s environmental impact has become a growing concern, largely due to the energy-intensive production of conventional building materials. This paper explores the potential of wood–cement composites as a more sustainable alternative through a comprehensive literature review, including a bibliometric and scientometric analysis of research trends. Our analysis traces the evolution of wood–cement composites from early studies focused on mechanical properties, to recent investigations into their environmental benefits and practical applications. Key findings suggest that optimal performance can be achieved by treating wood with tetraethyl orthosilicate, incorporating additives like cellulose nanocrystals or wollastonite, and using wood from species such as Pinus. While partial cement replacement with wood waste and ash offers significant environmental advantages, precise formulations are needed to maintain structural integrity. This study also acknowledges certain methodological limitations, such as the reliance on keyword-based filtering, which may have excluded some relevant studies. Future research should address long-term durability, economic feasibility, and standardized testing methodologies to facilitate the adoption of wood–cement composites in the construction industry. These materials, particularly suitable for non-structural applications and insulation, hold promise as viable, eco-friendly building solutions capable of reducing the construction industry’s carbon footprint.

The term substitution in phonodidactics and speech therapy: A comparative analysis

The article examines the term substitution by focusing on the ways in which it has been defined and/or applied in the context of pronunciation errors, especially by two different scientific disciplines: Polish language teaching (more precisely: phonodidactics) and speech therapy. Interestingly, despite the fact that the term refers to the same or similar object of study, it is not necessarily used with the same meaning. The paper opens with a review of definitions from general and specialized dictionaries along with a formulation of the concept. The study was carried out according to a socio-terminology approach, taking into account the contextual updating of meanings, observed polysemy and synonymy, as well as a socio-cognitive approach, checking the popularity of using the term and ways of understanding it in a specific context. Both the general term and the term specified by a modifier (e.g., phonetic, phonological substitution) have been described and exemplified thanks to the database of texts from both disciplines to show similarities and differences resulting from the adopted perspectives or goals (research or practical ones) that the representatives of each fi eld of study set for themselves. The analysis made it possible to observe the process of determinologization, as well as the co-occurrence of several different concepts in both disciplines, referenced by the same terms. The study fi ts into the descriptivist trend, but it aspires to be a point in the discussion about the precise formulation of descriptions, especially in disciplines that share interests with other fitelds of science.

Exact Expressions for Kullback-Leibler Divergence for Univariate Distributions.

The Kullback-Leibler divergence (KL divergence) is a statistical measure that quantifies the difference between two probability distributions. Specifically, it assesses the amount of information that is lost when one distribution is used to approximate another. This concept is crucial in various fields, including information theory, statistics, and machine learning, as it helps in understanding how well a model represents the underlying data. In a recent study by Nawa and Nadarajah, a comprehensive collection of exact expressions for the Kullback-Leibler divergence was derived for both multivariate and matrix-variate distributions. This work is significant as it expands on our existing knowledge of KL divergence by providing precise formulations for over sixty univariate distributions. The authors also ensured the accuracy of these expressions through numerical checks, which adds a layer of validation to their findings. The derived expressions incorporate various special functions, highlighting the mathematical complexity and richness of the topic. This research contributes to a deeper understanding of KL divergence and its applications in statistical analysis and modeling.

The structure of the artistic conflict in the story by L. Petrushevskaya "Time Night"

The purpose of this study is to identify the structure of artistic conflict in the story of the Soviet and Russian writer, playwright and screenwriter Lyudmila Petrushevskaya "Time Night". The study provides a more precise formulation of the concept of artistic conflict, provides a typology of conflict: internal conflict, interpersonal conflict, conflict of time and space. The artistic conflict in the story has a complex structure and affects the formation of the plot and characters of the work. The author analyzes the internal and external contradictions that the heroine of the story faces, emphasizing their psychological depth and multi-layeredness. Particular attention is paid to how conflicts reveal the themes of loneliness, the search for the meaning of life and the interaction of the individual with the outside world. The article offers an interpretation of L. Petrushevskaya's artistic techniques and their role in creating the emotional tension of the story, and also examines how conflicts contribute to the disclosure of the key ideas of the story. Typological analysis, cultural approach and others were used as research methods. In the story "Time Night" by Lyudmila Petrushevskaya, a multi-layered conflict is depicted as internal and external contradictions that reinforce each other, creating a tense atmosphere of the narrative. Through the conflict, the author reveals the deep feelings and experiences of the heroine, her struggle with difficult life circumstances, and also conveys the social and historical reality of the late Soviet period. The conflict covers not only external disagreements, but also the antinomy between the closed inner world of the heroes and external reality. L. S. Petrushevskaya focuses not on the transformation of the environment, but on how this environment is projected into the heart of the main character and breaks her spirit.

Enhanced characteristic equation method for single-stage absorption heat pumps

The method of characteristic equations aims to describe the part-load behavior of sorption heat pumps and chillers as well as heat transformers as simply as possible but yet still accurately. Based on an approach by T. Furukawa for heat transformers, the method was further developed by F. Ziegler and others for absorption heat pumps and generalized for application in multistage processes. Clever simplifications were made, to represent the cooling capacity Q˙E of absorption chillers with a characteristic temperature difference ΔΔt as a simple linear equation Q˙E=sE·(ΔΔt−ΔΔtmin,E). In ΔΔt, the average hot, cooling, and chilled water temperatures are combined, and the slope and loss parameters, sE and ΔΔtmin,E are constant. However, in practical applications of this established method, inconsistencies arise. For example, the calculated slope parameter sE does not match the slope when plotting simulated or measured cooling capacities against ΔΔt. Furthermore, the loss parameter ΔΔtmin,E is actually not constant.In this work a more precise formulation of the characteristic equation is derived which takes into account that the solution entering the absorber and desorber is generally superheated or subcooled. By means of a domain-wise heat transfer calculation, these effects can be implemented into the method and explain the above mentioned inconsistencies. The new formulation allows for explicit consideration of different heat exchanger designs and cooling water configurations. No iterations or regression analyses are required. Thus, the calculation method can be easily implemented into industrial controllers e.g. for the model predictive control of absorption chillers and heat pumps.