Semi-quantitative Models Research Articles

Semi-quantitative chemometric models for characterization of mixtures of sugars using infrared spectral data

Sugars (saccharides) are sweet-tasting carbohydrates that are abundant in foods and play very important roles in living organisms, particularly as sources and stores of energy, and as structural elements in cellular membranes. They are desirable therapeutic targets, as they participate in multiple metabolic processes as fundamental elements. However, the physicochemical characterization of sugars is a challenging task, mostly due to the structural similarity shared by the large diversity of compounds of this family. The need for fast, accurate enough, and cost-effective analytical methods for these substances is of extreme relevance, in particular because of the recently increasing importance of carbohydrates in Medicine and food industry. With this in view, this work focused on the development of chemometric models for semi-quantitative analysis of samples of different types of sugars (glucose, galactose, mannitol, sorbose and fructose) using infrared spectra as data, as an example of application of a novel approach, where the Principal Component Analysis (PCA) score plots are used to estimate the composition (weight-%) of the mixtures of the sugars. In these plots, polygonal geometric shapes emerge in the vectorial space of the most significant principal components, that allow grouping different types of samples on the vertices, edges, faces and interior of the polygons according to the composition of the samples. This approach was applied successfully to mixtures of up to 5 sugars and shown to appropriately extract the compositional information from the hyper-redundant complex spectral data. Thought the method has been applied here to a specific problem, it shall be considered as a general procedure for the semi-quantitative analysis of other types of mixtures and applicable to other types of data reflecting their composition. In fact, the methodology appears as an efficient tool to solve three main general problems: (i) use hyper-redundant (in variables) data, as spectral information, directly and with minimum pre-treatment, to evaluate semi-quantitatively the composition of mixtures; (ii) do this for systems which produce data that can be considered rather similar; and (iii) do it for a number of substances present in the mixtures that might be greater than that usually considered in chemistry, which in general is limited to 3 components. In addition, this work also demonstrates that, similarly to the developed analysis based on the PCA score plots, the Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) chemometric method can also be used successfully for the qualitative (when used without any previous knowledge of the components present in the samples) or semi-quantitative (when the pure components spectral profiles are provided as references) analyses of mixtures of (at least) up to 5 distinct sugars.

Assessing the use of Fisher knowledge in oceanic eco-social networks of Peru: A comprehensive approach to sustainable fisheries management and governance

This study is the first attempt to determine the local stability and resilience of the highly exploited oceanic ecosystem of Peru, integrating the use of fisher knowledge (FK) by government institutions (GI), which could increase sustainable governance and improve the design of management strategies. To do this, five simplified semi-quantitative eco-social models with different levels of complexity were constructed. The Routh-Hurwitz local stability criterion 1 (RH1) showed that all models (with and without the link between FK and GI) exhibited the highest percentages of transient stable states in the scenario of demand and fishers in self-negative feedback (D- & F-). Only the least complex eco-social models (models 1 and 2) exhibited an increase in the average values of Fs (stability) and Fn (resilience) when connecting FK with GI, whereas the more complex models showed the opposite trend. Although the link that connects FK by GI would allow increasing the number of stable transient states in the most complex eco-social models (models 3, 4 and 5), however FK would be self-controlled, that is, an evaluation of the quantity and quality of the information available is required. Since the models constructed are simplifications of the eco-social system studied, they allowed us to identify the conditions of stable/resilient (sustainable) scenarios, which would help us in decision-making and governance based on the use of FK in Peruvian fisheries management and monitoring.

Contact-angle hysteresis on rough surfaces: mechanical energy balance framework

Using as a starting point conservation of momentum, a multiphase mechanical energy balance equation is derived that accounts for multiple material phases and interfaces present within a moving control volume. This balance is applied to a control volume that is anchored to a three-phase contact line as it advances continuously over the surface of a rough and chemically homogeneous and inert solid. Using semi-quantitative models for the material behaviour occurring within the control volume, an order of magnitude analysis is performed to neglect insignificant terms, producing an equation for predicting contact-angle hysteresis from a knowledge of the interface dynamics occurring around the three-phase contact line. It is shown that the viscous energy dissipation that occurs during the ‘stick–slip’ motion of the three-phase contact line, being the cause of contact-angle hysteresis on rough surfaces, can be calculated from changes in intermediate equilibrium interface states. The balance is applied to the Wenzel, Cassie–Baxter and Fakir (super-hydrophobic) wetting states, showing for the Fakir case that significant dissipation occurs during both interface advance and recede, and relating these dissipations to interfacial area changes that occur around the ‘stick–slip’ events.

Qualitative Model of the Causal Interactions between Phytoplankton, Zooplankton, and Environmental Factors in the Romanian Black Sea

In order to analyze how environmental factors affect planktonic organisms along the Romanian Black Sea coast, this study created semi-quantitative models of the causal relationships between phytoplankton, zooplankton, and physicochemical parameters by utilizing user-friendly modeling tools. Eleven years of time-series data (March–September 2008–2018) were used to investigate the relationships between phytoplankton, zooplankton, and environmental factors (such as temperature, salinity, and nutrients). Variables such as marine reporting units and phytoplankton species and classes were used to identify developmental patterns, utilizing the Mental Modeler platform to consider interactions between the physicochemical parameters and phytoplankton, phytoplankton and zooplankton, and zooplankton and physicochemical parameters. Although the increase in the overall number of elements and linkages was uncertain in waters with variable salinity compared to marine ones, the semi-quantitative models created for the three marine reporting units along the Romanian Black Sea coast were comparable in terms of complexity. Across the typical and examined types of phytoplankton proliferation (normal, abundant, and blooms), the number of components and connections in the case of phytoplankton blooms substantially decreased as species- and growth-promoting variables increased.

Prebiotic synthesis on meteorite parent bodies: Insights from hydrogen and carbon isotope models

Several mechanisms could produce the biorelevant organic compounds contained in carbonaceous meteorites. The ratio of heavy-to-light stable isotopes can constrain a compound's formation history because substrates, mechanisms, and physiochemical conditions impact isotope ratios of a reaction's products. Prior stable isotope studies of meteoritic organic compounds have interpreted data via qualitative or semi-quantitative models. Here we create quantitative models (i.e., explicitly fit to measurements) for hydrogen and carbon isotope compositions of organic compounds in primitive carbonaceous meteorite and use these models to reach broader conclusions regarding the environments, substrates, and chemical processes that contributed to their synthesis.The hydrogen isotope model gathers previous molecular-average δD measurements, sorts them into compounds classes (e.g., amines, carboxylic acids), and fits the measurements in each class as linear combinations of the non-exchangeable hydrogen moieties, which are determined by their chemical environment (e.g., R-CH3, R-CH(NH2)(COOH)). In the chondrites studied, methyl hydrogens are the most deuterium-enriched moiety (up to 5000 ‰) and hydrogens attached to α‑carbons are the least. Deuterium enrichment is inversely related to a moiety's acidity and a meteorite sample's degree of aqueous alteration and terrestrial weathering, which suggests that ISM-sourced compounds reacted to form deuterium-enriched organic molecules before parent body accretion or during parent body evolution and that those D enrichments were variably attenuated through exchange with water during aqueous alteration on the parent body and subsequent terrestrial processing.The carbon isotope model tests five potential chemical reaction networks by taking δ13C of reactants for each network and applying isotope effects to determine a range of product δ13C from minimal to complete reactant conversion. The model that fits compounds in the Murchison meteorite most accurately (70% of previous measurements fall within the values predicted by model ±5‰) with the lowest average residuals (6‰) uses an integrated aldehyde network (oxidation, reductive amination, and Strecker synthesis acting on an initial pool of aldehydes and ketones) to produce straight-chain compounds, which then react with aldehydes to create branched-chain compounds. The addition of aldehydes provides a parsimonious fit the carbon isotope contents of compounds that span over 100‰ in δ13C, making it an attractive working hypothesis.

Factors influencing occupational exposure to pyrethroids and glyphosate: An analysis of urinary biomarkers in Malaysia, Uganda and the United Kingdom

BackgroundLong-term exposure to pesticides is often assessed using semi-quantitative models. To improve these models, a better understanding of how occupational factors determine exposure (e.g., as estimated by biomonitoring) would be valuable. MethodsUrine samples were collected from pesticide applicators in Malaysia, Uganda, and the UK during mixing/application days (and also during non-application days in Uganda). Samples were collected pre- and post-activity on the same day and analysed for biomarkers of active ingredients (AIs), including synthetic pyrethroids (via the metabolite 3-phenoxybenzoic acid [3-PBA]) and glyphosate, as well as creatinine. We performed multilevel Tobit regression models for each study to assess the relationship between exposure modifying factors (e.g., mixing/application of AI, duration of activity, personal protective equipment [PPE]) and urinary biomarkers of exposure. ResultsFrom the Malaysia, Uganda, and UK studies, 81, 84, and 106 study participants provided 162, 384 and 212 urine samples, respectively. Pyrethroid use on the sampling day was most common in Malaysia (n = 38; 47%), and glyphosate use was most prevalent in the UK (n = 93; 88%). Median pre- and post-activity 3-PBA concentrations were similar, with higher median concentrations post-compared to pre-activity for glyphosate samples in the UK (1.7 to 0.5 μg/L) and Uganda (7.6 to 0.8 μg/L) (glyphosate was not used in the Malaysia study). There was evidence from individual studies that higher urinary biomarker concentrations were associated with mixing/application of the AI on the day of urine sampling, longer duration of mixing/application, lower PPE protection, and less education/literacy, but no factor was consistently associated with exposure across biomarkers in the three studies. ConclusionsOur results suggest a need for AI-specific interpretation of exposure modifying factors as the relevance of exposure routes, levels of detection, and farming systems/practices may be very context and AI-specific.

A Proposed Method for Evaluating Management Feasibility When Determining Weed Control Priorities after Major Fires and Floods

Major fires and floods have enormous impacts on natural ecosystems and are predicted to increase in frequency with global warming. Land managers need to make decisions on the prioritisation of weeds for control in post-disturbance landscapes, but little is available in the way of guidance to support timely decision making. Semi-quantitative models (e.g., scoring systems) have been employed routinely in weed risk assessment, which considers the potential impacts posed by weeds, as well as the likelihood of these impacts being realised. Some progress has been made in the development of similar models addressing the topic of weed risk management. Under conditions prevailing after major disturbances, changes (both positive and negative) can be expected in the multiple factors that determine weed management feasibility, relative to pre-disturbance conditions. A semi-quantitative model is proposed that is based on the key factors that contribute to weed management feasibility in post-disturbance environments, along with annotated modules that could be used by land managers in both post-fire and post-flood situations. The fundamental challenge for weed management in these scenarios lies in the identification of differences between weeds and native species in relation to (1) patterns of seedling emergence; and (2) detectability relative to the growth stage. These two factors will determine the timing of control actions that are designed to address the trade-off between weed control and off-target damage during the period when both types of plants are recovering from a major disturbance event. The model is intuitively sound, but field testing is required to determine both its practical value and any necessary improvement.

The prediction of occupational health risks of benzene in the printing industry through multiple occupational health risk assessment models.

Benzene poisoning is a common occupational poisoning event in the printing industries. Up to now there is still a lack of research data on risk assessment of benzene operations in enclosed workshops. It is crucial to assess the risk level of these positions and put forward effective measures and suggestions. The information of selected companies and air samples were collected through on-site investigation, data collation and sample testing were carried out according to the requirements of Chinese standards. The Control of Substances Hazardous to Health (COSHH) Essential, the EPA non-carcinogenic risk assessment model, the Singapore exposure index method and the Chinese semi-quantitative risk assessment models were used to assess the risks of benzene. The exposed groups all worked more than 8 h per day, and the cleaning, pasting, and packaging groups used general ventilation rather than local ventilation. 28.6% of the printing group and 16.7% of the pasting group had benzene concentrations that exceeded the permissible concentration-time weighted average (PC-TWA) in China. Over 60.0% of the work groups were evaluated at high risk and over 20% of the work groups were evaluated at high cancer risk by the risk assessment models. The Chinese exposure index method and the synthesis index method may have a stronger practicability. The printing and pasting groups may have a higher risk for benzene exposure. It is necessary to increase protective measures and strengthen occupational hygiene management to reduce risks.

Application of multiple occupational health risk assessment models in the prediction of occupational health risks of n-Hexane in the air-conditioned closed workshop.

n-Hexane (NH) poisoning is a common occupational poisoning in the hardware and electronics industries. However, there is few research data on risk assessment of positions using NH in enclosed workshops. It is very important to assess the risk level of these positions and put forward effective measures and suggestions. The information of selected companies and air samples were collected through on-site investigation, and data collation and sample testing were carried out according to the requirements of Chinese standards. The Control of Substances Hazardous to Health (COSHH) Essential, the EPA non-carcinogenic risk assessment model, the Singapore exposure index method and the Chinese semi-quantitative risk assessment models were used to assess the risks of NH. The working hours of the exposure groups, printing groups and packing groups all exceeded 9 h per day, less than 30% of each similar exposure groups (SEG) was equipped with the local exhaust ventilation, and 11.1% of the cleaning group and 8.3% of the printing group had NH concentrations in the air that exceeded the Chinese occupational exposure limit (OEL). In the EPA non-carcinogenic risk assessment model, each SEG was evaluated at high risk. In the Chinese semi-quantitative risk assessment models, all of the work groups of exposure groups, 91.7% of the work groups of printing groups, 77.8% of the work groups of printing groups, and 57.1% of the work groups of printing groups were evaluated at unacceptable risk. More than 40.0% of the work groups of printing groups and cleaning groups and over 20.0% of the work groups of exposure groups and packing groups were evaluated at high risk in the Chinese semi-quantitative risk assessment models. The Chinese exposure index method and the synthesis index method may have a stronger practicability. Some work groups that use NH in air-conditioned enclosed workshops in China, especially the cleaning groups, are still in a high-risk state. It is necessary to increase protective measures and strengthen occupational hygiene management to reduce risks.

Improvements in protective measures in factories with acetylene hydrochlorination and ethylene oxychlorination techniques declined risk assessment levels and affected liver health status.

Acetylene hydrochlorination and ethylene oxychlorination are the two most common methods of producing vinyl chloride monomer (VCM), which has been linked to liver impairment, hepatocellular carcinoma (HCC), and angiosarcoma of the liver (ASL) in occupational settings. However, whether and how these impairments could be effectively improved from workplace root causes has yet to be discovered. This study aimed to evaluate whether improvements in protective measures in groups Y (408 subjects) and Z (349 subjects) could have an influential impact on the alleviation of liver impairment by comparing risk assessment levels under several semi-quantitative models and results from liver ultrasound detection and liver function tests before and after the improvement. Importantly, significant differences in constituent ratio involved in parameters among age, length of employment, weekly exposure time, smoking status, alcohol consumption, and sleeping quality were found between Y and Z before improvement took place in 2020 (P < 0.05 or P < 0.001), and population distribution by gender between Y and Z was in a large homogeneity with differences in age and length of employment. CSTE involves ore breaking, acetylene generation, steam stripping, outward processing, and welding maintenance, was disqualified in 2020 compared to OEL, and was said to have declined to meet OEL requirements by 2021. Further, a negative correction of fresh air requirement and ventilation air changing rate with ambient concentration toward hazards in Y was stronger in 2021 than in 2020. Significant differences in risk levels in Y between 2020 and 2021 were found as ore breaking, acetylene generation, steam stripping, outward processing, VCM polymerization, welding, and repairing, decreasing to relatively lower risk levels in 2021 from the original ones in 2020 only under the semi-quantitative comprehensive index model. Abnormal rates toward other hepatic symptoms decreased in the majority of positions after the improvement, as referred to by alterations such as ALT, AST, and GGT. Overall, the effect of improvements on protective measures effectively reduced positions' risk assessment levels through ventilation enhancement and airtight strengthening, which further affected abnormal rates toward other hepatic symptoms, and alterations such as ALT, AST, and GGT were much more significant in Y than effect in Z.

New Insights into the Lamb Shift: The Spectral Density of the Shift

In an atom, the interaction of a bound electron with the vacuum fluctuations of the electromagnetic field leads to complex shifts in the energy levels of the electron, with the real part of the shift corresponding to a shift in the energy level and the imaginary part to the width of the energy level. The most celebrated radiative shift is the Lamb shift between the 2s1/2 and the 2p1/2 levels of the hydrogen atom. The measurement of this shift in 1947 by Willis Lamb Jr. proved that the prediction by Dirac theory that the energy levels were degenerate was incorrect. Hans Bethe’s non-relativistic calculation of the shift using second-order perturbation theory demonstrated the renormalization process required to deal with the divergences plaguing the existing theories and led to the understanding that it was essential for theory to include interactions with the zero-point quantum vacuum field. This was the birth of modern quantum electrodynamics (QED). Numerous calculations of the Lamb shift followed including relativistic and covariant calculations, all of which contain a nonrelativistic contribution equal to that computed by Bethe. The semi-quantitative models for the radiative shift of Welton and Power, which were developed in an effort to demonstrate physical mechanisms by which vacuum fluctuations lead to the shift, are also considered here. This paper describes a calculation of the shift using a group theoretical approach which gives the shift as an integral over frequency of a function, which is called the “spectral density of the shift.“ The energy shift computed by group theory is equivalent to that derived by Bethe yet, unlike in other calculations of the non-relativistic radiative shift, no sum over a complete set of states is required. The spectral density, which is obtained by a relatively simple computation, reveals how different frequencies of vacuum fluctuations contribute to the total energy shift. The analysis shows, for example, that half the radiative shift for the ground state 1S level in H comes from virtual photon energies below 9700 eV, and that the expressions of Power and Welton have the correct high-frequency behavior, but not the correct low-frequency behavior, although they do give approximately the correct value for the total shift.

Development of new QSAR models for water, sediment, and soil half-life.

Checking the persistence of a chemical in the environment is extremely important. Regulations like REACH, the European one on chemicals, require the measurements or estimates of the half-life of the chemical in water, sediment, and soil. The use of non-testing methods, like quantitative structure-activity relationship (QSAR) models, is encouraged because it reduces costs and time. To our knowledge, there are very few freely available models for these properties and some are for specific chemical classes. Here, we present three new semi-quantitative models, one for each of the required environmental compartments (water, sediment, and soil). Using literature and REACH registration data, we developed three new counter-propagation artificial neural network models using the CPANNatNIC tool. We calculated the VEGA descriptors, and selected the relevant ones using an internal method in R based on the forward selection technique. The best model for each compartment was implemented in two open-source stand-alone tools, the VEGA platform, and the JANUS tool (https://www.vegahub.eu/). These models were also used by ECHA to build their PBT profiler available in the OECD QSAR toolbox (https://qsartoolbox.org/). Screening and prioritization are also our main target. The models perform well, with R2 always above 0.8 in training and validation. The only exception is the validation set of the soil compartment, with R2 0.68, that is above 0.8 only for compounds inside the applicability domain (automatically calculated by the system). The root mean square error (RMSE) is good, 0.34 or less in log units (again, for soil validation it is higher but it reaches 0.21 when considering only the compounds in the applicability domain). Compared with one of the most widely used tools, BIOWIN3, the proposed models give better results in terms of R2 and RMSE. For the classification, the performance is better for water and soil, and comparable or lower for sediment.

Water Reuse: A Risk Assessment Model for Water Resources

The increasing demands for water for multiple purposes combined with climate change challenges are leading to water scarcity and quality deterioration. Portugal is vulnerable to the impacts of climate change and therefore, the use of reclaimed waters has been identified as a suitable alternative water source for non-potable uses, such as irrigation, to overcome water shortages. In the last two years, new policies for water reuse have been approved at the Portuguese and European levels. The legal frameworks are supported in the international guidelines developed by the International Organization for Standardization, namely for irrigation, urban uses and health risk assessment. In this way, all reuse projects must follow a fit-for-purpose approach, i.e., the water quality needs to meet the requirements of its specific end-uses without compromising public health or the surrounding environment, and all reuse projects must conduct a risk assessment for health and the environment. Quantitative, qualitative or semiquantitative models can be used. Although a quantitative assessment may be desirable, these models tend to be complex and present high uncertainty. Furthermore, these usually require extensive data which are often not available. Accordingly, this study intended to develop a conceptual model to deal with the risk assessment for water resources, namely surface and ground waters. A semi-quantitative approach was employed for the risk characterization, using empirical qualitative judgment to assess the relative importance of hazards, exposure routes, scenarios and barriers in place. The use of a strategic assessment allows the quality standards that meet the needs of each project to be validated. The developed model was applied to a case study to illustrate its applicability.&#x0D; Keywords: water reuse, water resources, risk assessment, semi-quantitative model, compounds of emerging concern

Citrus Huanglongbing detection and semi-quantification of the carbohydrate concentration based on micro-FTIR spectroscopy.

Citrus Huanglongbing (HLB) is nowadays one of the most fatal citrus diseases worldwide. Once the citrus tree is infected by the HLB disease, the biochemistry of the phloem region in midribs would change. In order to investigate the carbohydrate changes in phloem region of citrus midrib, the semi-quantification models were established to predict the carbohydrate concentration in it based on Fourier transform infrared microscopy (micro-FTIR) spectroscopy coupled with chemometrics. Healthy, asymptomatic-HLB, symptomatic-HLB, and nutrient-deficient citrus midribs were collected in this study. The results showed that the intensity of the characteristic peak varied with the carbohydrate (starch and soluble sugar) concentration in citrus midrib, especially at the fingerprint regions of 1175-900cm-1, 1500-1175cm-1, and 1800-1500cm-1. Furthermore, semi-quantitative prediction models of starch and soluble sugar were established using the full micro-FTIR spectra and selected characteristic wavebands. The least squares support vector machine regression (LS-SVR) model combined with the random frog (RF) algorithm achieved the best prediction result with the determination coefficient of prediction ([Formula: see text]) of 0.85, the root mean square error of prediction (RMSEP) of 0.36%, residual predictive deviation (RPD) of 2.54, and [Formula: see text] of 0.87, RMSEP of 0.37%, RPD of 2.76, for starch and soluble sugar concentration prediction, respectively. In addition, multi-layer perceptron (MLP) classification models were established to identify HLB disease, achieving the overall classification accuracy of 94% and 87%, based on the full-range spectra and the optimal wavenumbers selected by the random frog (RF) algorithm, respectively. The results demonstrated that micro-FTIR spectroscopy can be a valuable tool for the prediction of carbohydrate concentration in citrus midribs and the detection of HLB disease, which would provide useful guidelines to detect citrus HLB disease.

Application of multiple occupational health risk assessment models in occupation health risk prediction of trichloroethylene in the electroplating and electronics industries

Objectives. This study assessed the occupational health risks of work group exposure to trichloroethylene (TCE) in the electroplating and electronics industries in China. Methods. The UK Control of Substances Hazardous to Health (COSHH) Essential, the US Environmental Protection Agency (EPA) and the Singapore and the Chinese semiquantitative risk assessment models were used to assess the risks of TCE. Twenty degreasing groups and 14 cleaning groups were recruited in the companies selected. Results. The concentrations of TCE in 66.7% of the cleaning groups and 35.0% of the degreasing groups exceeded the permissible concentration time-weighted average (PC-TWA) in China, and the concentrations of TCE in 100.0% of the cleaning groups and 70.0% of the degreasing groups exceeded the permissible concentration short-term exposure limit (PC-STEL) in China. Over 60.0% of the work groups were evaluated at high risk and over half of the work groups were evaluated at high cancer risk by the risk assessment models. Conclusion. Most work groups exposed to TCE in the electroplating and electronics industries in China are at high risk. The cleaning groups may have a higher risk for TCE exposure. The Chinese exposure index method and the synthesis index method are more practical than the other methods.

Semi-Quantitative Half-Life Qsar Models for Water, Sediment, and Soil

Semi-Quantitative Half-Life Qsar Models for Water, Sediment, and Soil

Quantifying the origin of membrane polarization

SUMMARY There has been substantial interest in applying induced polarization phenomena, which broadly include electrode and membrane polarization, to characterize organic contamination and biogeochemical environments. Several phenomenological models, semi-quantitative models and models for particular pore shapes have been proposed for understanding membrane polarization. Here, we present a theoretical framework that directly relates membrane polarization to intrinsic statistical properties of porous materials through a two-point correlation function of fixed charges in the pore space. Our framework provides a new way of modelling complex pore structures with a few statistical parameters and quantifies how two distinct physical processes drive complex conductivity response in the absence of conducting grains. One process is a coupling of the static inhomogeneous conductivity to the induced oscillatory electric field, whereas the second process is a coupling of the static electric field to the induced conductivity modulation. Including both effects, we quantitatively predict the frequency-dependent membrane polarization and show excellent agreement between our predictions and experiments in model porous materials.

Overview of resilience: a concept to assess healthcare infrastructure preparedness against disasters. Evaluation of existing models and applicability to HVAC systems

Healthcare infrastructures are critical and have elements which are likely to fail or to get collapsed in disaster scenarios (earthquakes, pandemics, etc.). There are many parameters and factors to evaluate their preparedness, but resilience has outstood in recent investigations. Hospitals must not only be prepared for disasters to come, but also to reach the nominal operation in the aftermath as soon as possible, as these infrastructures play a critical role in modern societies. The aim of the study is to evaluate and assess different insights into resilience, as well as marking possible improvements, providing a deeper understanding about the topic and concepts that surround the definition of resilience. The result is the constitution of a new assessment tool based on semi-quantitative and quantitative models. The model can be scaled and applied to internal systems in healthcare infrastructure such as HVAC facilities.

Worldlines and social networks

Familiar laws of physics are applied to study human relations, modelled by their world lines (worldlines) combined with social networks. We focus upon the simplest, basic element of any society: a married couple, stable due to the dynamic balance between attraction and repulsion. By building worldlines (worldsheets), we arrive at a two-level coordinate systems: one describing the behaviour of a string-like binary system (here, a married couple), the other one, external, corresponding to the motion of this couple in the medium, in which the worldline is embedded, sweeping there a string-like sheet or brane. The approach is illustrated by simple examples (semi-quantitative toy models) of worldlines (sheets), open to further extension, perfections and generalisation. Worldlines are combined with social networks. Simple illustrative examples with empirical inputs taken from intuition and (or) observation are appended.

Game theory model for a virtual water strategy: Scenarios under rational and semirational game play

AbstractThe virtual water strategy (VWS) provides a theoretically feasible method to transport virtual water (VW) and balance regional differences in water resource endowments. However, the practical implementation of VWS faces selective resistance due to the lack of research in motivation analysis across potential executor regions. Game theory provides a new approach to study the decision‐making mechanism and behavioural motivation in the implementation of VWS. This study builds some semiquantitative game models to analyse the regions’ potential acceptance of VWS in decision‐making, especially concerning economic development, water sustainability, and trade patterns. The result shows the factors like external incentives and stability of game can affect the payoffs and strategy selections on VWS in rational and semirational games. To achieve a mutual benefit equilibrium towards an effective VWS framework, improvement efforts could include mechanisms for rewards or punishments, promoting long‐term cooperation, and promulgation and education.