[RESUMEN]. Objetivo. Los trastornos mentales, neurológicos y por consumo de sustancias psicoactivas (MNS) tienen una prevalencia alta y existe una brecha para su atención en Colombia. El Programa de acción para superar las brechas en salud mental (mhGAP, por su sigla en inglés) de la Organización Mundial de la Salud (OMS) tiene varios componentes. Uno de ellos es la Guía de intervención mhGAP 2.0, orientada a la mejora de la atención primaria en salud; se trata de una guía para la evaluación y el manejo de trastornos MNS a partir de protocolos de toma de decisiones clínicas. Se planteó como objetivo determinar las barreras que se pueden presentar en el proceso de implementación del programa. Métodos. Se realizó un estudio cualitativo con enfoque de análisis de contenido que se desarrolló en tres fases: i) preparación, organización y presentación del estudio; ii) codificación abierta, categorización y abs- tracción de los contenidos; y iii) análisis de información. El estudio incluyó la entrevista semiestructurada a 21 personas involucradas en la prestación de servicios en salud mental en Chocó (Colombia): cinco profesionales de medicina, siete de enfermería y tres de psicología, además seis profesionales que trabajaban en el área administrativa de las secretarías de salud del departamento. Se exploraron las percepciones de las partes interesadas, que eran el personal asistencial y el personal administrativo del sector salud en el departamento del Chocó. Se realizaron preguntas abiertas para explorar las experiencias con el proceso y las barreras identificadas en la práctica. Resultados. Se identificaron cuatro categorías temáticas diferentes: intersectorialidad, viejos desafíos, posibilidades e idoneidad de herramientas. Conclusiones. Se construyó un modelo teórico sobre las barreras de implementación para el Programa de mhGAP desde las percepciones de las partes interesadas. El control de las barreras se percibe como un camino posible para generar un aporte significativo para la salud poblacional.
[ABSTRACT]. Objectives. Mental, neurological, and substance use (MNS) disorders have a high prevalence in Colombia and there is a treatment gap. The World Health Organization (WHO) Mental Health Gap Action Programme (mhGAP) has various components. The mhGAP 2.0 Intervention Guide, aimed at improving primary health care, is a guide for the assessment and management of MNS disorders based on clinical decision-making protocols. The objective of this study was to determine the barriers that may hinder the program implementation process. Methods. A qualitative study with content analysis was conducted in three phases: i) study preparation, organization, and presentation; ii) open coding, categorization, and abstraction of contents; and iii) information analysis. The study included semi-structured interviews with 21 people involved in the provision of mental health services in Chocó (Colombia): five medical doctors, seven nurses, and three psychologists, as well as six professionals working in the administrative area of the department's health secretariats. The perceptions of these stakeholders were explored. Open-ended questions were asked to explore experiences with the process, as well as the barriers identified in practice. Results. Four different thematic categories were identified: intersectoral action, long-standing challenges, opportunities, and suitability of tools. Conclusions. A theoretical model of barriers to implementation of the mhGAP program was constructed, based on stakeholder perceptions. Controlling barriers is perceived as a possible way to contribute significantly to population health.
[RESUMO]. Objetivo. Os transtornos mentais, neurológicos e por uso de substâncias psicoativas são muito prevalentes, e há uma lacuna na atenção a esses transtornos na Colômbia. O Programa de Ação para Reduzir as Lacunas em Saúde Mental (mhGAP, na sigla em inglês) da Organização Mundial da Saúde (OMS) consta de vários componentes. Um deles é o Manual de Intervenções mhGAP 2.0, elaborado para aprimorar a atenção primária à saúde. O documento contém orientações para avaliação e manejo de transtornos mentais, neurológicos e por uso de substâncias psicoativas e foi elaborado com base em protocolos para a tomada de decisões clínicas. O objetivo do estudo foi determinar as barreiras que podem surgir no processo de imple- mentação do programa. Métodos. Estudo qualitativo com enfoque de análise de conteúdo desenvolvido em três fases: i) preparação, organização e apresentação do estudo; ii) codificação aberta, categorização e abstração do conteúdo; e iii) análise das informações. O estudo incluiu entrevistas semiestruturadas com 21 pessoas envolvidas na prestação de serviços de saúde mental em Chocó (Colômbia): cinco profissionais da medicina, sete de enfermagem e três de psicologia, bem como seis profissionais que trabalham na área administrativa das secretarias de saúde do departamento. As percepções das partes interessadas, ou seja, do pessoal assisten- cial e administrativo do setor de saúde no departamento de Chocó, foram exploradas. Foram feitas perguntas abertas a fim de investigar suas experiências com o processo de atenção e as barreiras identificadas na prática. Resultados. Foram identificadas quatro categorias temáticas: intersetorialidade, desafios de longa data, possibilidades e adequação das ferramentas. Conclusões. Elaborou-se um modelo teórico sobre as barreiras de implementação do Programa mhGAP com base nas percepções das partes interessadas. O controle das barreiras é visto como uma possível forma de contribuir significativamente para a saúde da população.
Models, Theoretical , Barriers to Access of Health Services , Mental Health , Primary Health Care , Colombia , Models, Theoretical , Barriers to Access of Health Services , Mental Health , Primary Health Care , Barriers to Access of Health Services , Mental Health , Primary Health Care , Colombia
In order to investigate the development of the temperature field of a new type of freezing reinforcement under seepage conditions, in this paper, COMSOL finite element software was used to simplify the model and simulate the effect of groundwater seepage on the development of the temperature field of frozen pipes by coupling the Darcy's law module and the heat transfer module for porous media. The heads of water were also varied to simulate the change in seepage velocity to further investigate the effect of seepage velocity on the temperature field. The results of the study show that the freezing wall formed in the high head region was thinner than that in the low head region due to the effect of seepage, and this phenomenon was aggravated with the increase of seepage rate; The effect of seepage action on the temperature field had a hysteresis along the seepage direction; When the seepage rate was greater than 1.65 m/d, the soil in the center of the device feezed better and could form a tight and dense freezing wall comparable to the size of the freezing device; When the seepage rate was greater than 5.78 m/d, the temperature of the center soil body gradually increased, and eventually the freezing curtain cannot be formed.
Computer Simulation , Freezing , Temperature , Models, Theoretical , Groundwater
Energy-related occupant behaviour in the built environment is considered crucial when aiming towards Energy Efficiency (EE), especially given the notion that people are most often unaware and disengaged regarding the impacts of energy-consuming habits. In order to affect such energy-related behaviour, various approaches have been employed, being the most common the provision of recommendations towards more energy-efficient actions. In this work, the authors extend prior research findings in an effort to automatically identify the optimal Persuasion Strategy (PS), out of ten pre-selected by experts, tailored to a user (i.e., the context to trigger a message, allocate a task or providing cues to enact an action). This process aims to successfully influence the employees' decisions about EE in tertiary buildings. The framework presented in this study utilizes cultural traits and socio-economic information. It is based on one of the largest survey datasets on this subject, comprising responses from 743 users collected through an online survey in four countries across Europe (Spain, Greece, Austria and the UK). The resulting framework was designed as a cascade of sequential data-driven prediction models. The first step employs a particular case of matrix factorisation to rank the ten PP in terms of preference for each user, followed by a random forest regression model that uses these rankings as a filtering step to compute scores for each PP and conclude with the best selection for each user. An ex-post assessment of the individual steps and the combined ensemble revealed increased accuracy over baseline non-personalised methods. Furthermore, the analysis also sheds light on important user characteristics to take into account for future interventions related to EE and the most effective persuasion strategies to adopt based on user data. Discussion and implications of the reported results are provided in the text regarding the flourishing field of personalisation to motivate pro-environmental behaviour change in tertiary buildings.
Models, Theoretical , Humans , Surveys and Questionnaires , Female , Male , Adult , Persuasive Communication
In this paper, the Integrated Nested Laplace Algorithm (INLA) is applied to the Epidemic Type Aftershock Sequence (ETAS) model, and the parameters of the ETAS model are obtained for the earthquake sequences active in different regions of Xinjiang. By analyzing the characteristics of the model parameters over time, the changes in each earthquake sequence are studied in more detail. The estimated values of the ETAS model parameters are used as inputs to forecast strong aftershocks in the next period. We find that there are significant differences in the aftershock triggering capacity and aftershock attenuation capacity of earthquake sequences in different seismic regions of Xinjiang. With different cutoff dates set, we observe the characteristics of the earthquake sequence parameters changing with time after the mainshock occurs, and the model parameters of the Ms7.3 earthquake sequence in Hotan region change significantly with time within 15 days after the earthquake. Compared with the MCMC algorithm, the ETAS model fitted with the INLA algorithm can forecast the number of earthquakes in the early period after the occurrence of strong aftershocks more effectively and can forecast the sudden occurrence time of earthquakes more accurately.
Algorithms , Earthquakes , Forecasting , China , Forecasting/methods , Humans , Models, Theoretical , Spatio-Temporal Analysis
The time fractional Schrödinger equation contributes to our understanding of complex quantum systems, anomalous diffusion processes, and the application of fractional calculus in physics and cubic B-spline is a versatile tool in numerical analysis and computer graphics. This paper introduces a numerical method for solving the time fractional Schrödinger equation using B-spline functions and the Atangana-Baleanu fractional derivative. The proposed method employs a finite difference scheme to discretize the fractional derivative in time, while a θ-weighted scheme is used to discretize the space directions. The efficiency of the method is demonstrated through numerical results, and error norms are examined at various values of the non-integer parameter, temporal directions, and spatial directions.
Algorithms , Models, Theoretical , Quantum Theory , Computer Simulation
The study of thermal therapy to tumors and the response of living cells to this therapy used to treat tumor is very important due to the complexity of heat transfer in biological tissues. In the past few years, there has been a growing interest among clinicians, mathematicians, and engineers regarding the use of computational and mathematical methods to simulate biological systems. Numerous medical proceedings also employ mathematical modeling and engineering techniques as a means to guarantee their safety and evaluate the associated risks effectively. This manuscript provides an analytical solution used for the first time to study the mechanism of biological thermal response during heat therapy on spheroidal skin tumor. The proposed method used a generalized thermoelasticity model with one relaxation time. The influence of relaxation times on the responses of diseased and healthy tissues is studied and interpreted graphically. Also, the impact of different laser irradiance on the thermal profile of the malignant tumor cells over a period of 2 minutes is interpreted graphically. To investigate the transfer of heat within biological tissues during the thermal therapy, the Laplace transform and inverse Laplace transform methods were applied. A comparison of the present generalized thermoelasticity model and different models based on Pennes bioheat transfer PBT shows that our proposed model yields more realistic and accurate predictions. The current model can be used to explain various therapeutic methods.
Hot Temperature , Hyperthermia, Induced , Skin Neoplasms , Humans , Skin Neoplasms/therapy , Skin Neoplasms/pathology , Hyperthermia, Induced/methods , Hot Temperature/therapeutic use , Models, Biological , Models, Theoretical
In the era of computational advancements, harnessing computer algorithms for approximating solutions to differential equations has become indispensable for its unparalleled productivity. The numerical approximation of partial differential equation (PDE) models holds crucial significance in modelling physical systems, driving the necessity for robust methodologies. In this article, we introduce the Implicit Six-Point Block Scheme (ISBS), employing a collocation approach for second-order numerical approximations of ordinary differential equations (ODEs) derived from one or two-dimensional physical systems. The methodology involves transforming the governing PDEs into a fully-fledged system of algebraic ordinary differential equations by employing ISBS to replace spatial derivatives while utilizing a central difference scheme for temporal or y-derivatives. In this report, the convergence properties of ISBS, aligning with the principles of multi-step methods, are rigorously analyzed. The numerical results obtained through ISBS demonstrate excellent agreement with theoretical solutions. Additionally, we compute absolute errors across various problem instances, showcasing the robustness and efficacy of ISBS in practical applications. Furthermore, we present a comprehensive comparative analysis with existing methodologies from recent literature, highlighting the superior performance of ISBS. Our findings are substantiated through illustrative tables and figures, underscoring the transformative potential of ISBS in advancing the numerical approximation of two-dimensional PDEs in physical systems.
Algorithms , Models, Theoretical , Computer Simulation
Accurate modelling of complex social systems, where people interact with each other and those interactions change over time, has been a research challenge for many years. This study proposes an evolutionary Digital Twin-Oriented Complex Networked System (DT-CNS) framework that considers heterogeneous node features and changeable connection preferences. We create heterogeneous preference mutation mechanisms to characterise nodes' adaptive decisions on preference mutation in response to interaction patterns and epidemic risks. In this space, we use nodes' interaction utilities to characterise the positive feedback from interactions and negative impact of epidemic risks. We also introduce social capital constraint to harness the density of social connections better. The nodes' heterogeneous preference mutation styles include the (i)inactive style that keeps initial social preferences, (ii) ignorant style that randomly mutates preferences, (iii) egocentric style that optimises individual interaction utility, (iv) cooperative style that optimises the total interaction utilities by group decisions and (v) collaborative style that further allows the cooperative nodes to transfer social capital. Our simulation experiments on evolutionary DT-CNSs reveal that heterogeneous preference mutation styles lead to various interaction and infection patterns. The results also show that (i) increasing social capital enables higher interactions but higher infection risks and uncertainty in decision-making; (ii) group decisions outperform individual decisions by eliminating the unawareness of the decisions of other nodes; (iii) the collaborative nodes under a strict social capital limit can promote interactions, reduce infection risks and achieve higher overall interaction utilities.
Mutation , Humans , Computer Simulation , Models, Theoretical , Biological Evolution , Social Networking
This paper studies the recycling and remanufacturing mode and sales channel issues in the closed-loop supply chain. Specifically, this study establishes an e-commerce closed-loop supply chain consisting of a manufacturer and an e-commerce platform, and divides the recycling model into recycling by the manufacturer or recycling by the platform. Considering two common sales models in e-commerce platforms: the resale model and agency model, combined with the recycling model, four different research scenarios are formed. We use backward induction to solve the Stackelberg game problem and explore the remanufacturing and channel strategies of the manufacturer and the e-commerce platform. The research results show that for the manufacturer, under the same recycling model, when consumers' preference for remanufactured products and the sensitivity of recycling volume to recycling prices are low, he will prefer the resale model. Under the same sales model, the manufacturer always prefers the recycling model in which he is responsible for recycling. However, the choice of platform is contrary to that of the manufacturer. In the resale model, both the manufacturer and the platform will choose to recycle by themselves, which cannot achieve a win-win situation. Under the agency model, when consumers' preference for remanufactured products is high and the sensitivity coefficient of recycling volume to recycling price is low, supply chain members can achieve a win-win situation, and the scope of the win-win situation decreases as the unit production cost of new products increases. In addition, rising consumer preference for remanufactured products will lead to lower consumer surplus.
Commerce , Recycling , Consumer Behavior , Humans , Models, Theoretical
We have a poor understanding of how urban drainage and other engineered components interact with more natural hydrological processes in green and blue spaces to generate stream flow. This limits the scientific evidence base for predicting and mitigating the effects of future development of the built environment and climate change on urban water resources and their ecosystem services. Here, we synthesize > 20 years of environmental monitoring data to better understand the hydrological function of the 109-km2 Wuhle catchment, an important tributary of the river Spree in Berlin, Germany. More than half (56%) of the catchment is urbanized, leading to substantial flow path alterations. Young water from storm runoff and rapid subsurface flow provided around 20% of stream flow. However, most of it was generated by older groundwater (several years old), mainly recharged through the rural headwaters and non-urban green spaces. Recent drought years since 2018 showed that this base flow component has reduced in response to decreased recharge, causing deterioration in water quality and sections of the stream network to dry out. Attempts to integrate the understanding of engineered and natural processes in a traditional rainfall-runoff model were only partly successful due to uncertainties over the catchment area, effects of sustainable urban drainage, adjacent groundwater pumping, and limited conceptualization of groundwater storage dynamics. The study highlights the need for more extensive and coordinated monitoring and data collection in complex urban catchments and the use of these data in more advanced models of urban hydrology to enhance management.
Droughts , Environmental Monitoring , Rivers , Urbanization , Environmental Monitoring/methods , Rivers/chemistry , Water Movements , Groundwater/chemistry , Hydrology , Models, Theoretical , Germany , Climate Change
In response to increasingly complex social emergencies, this study realizes the optimization of logistics information flow and resource allocation by constructing the Emergency logistics information Traceability model (ELITM-CBT) based on alliance blockchain technology. Using the decentralized, data immutable and transparent characteristics of alliance blockchain technology, this research breaks through the limitations of traditional emergency logistics models and improves the accuracy and efficiency of information management. Combined with the hybrid genetic simulated Annealing algorithm (HGASA), the improved model shows significant advantages in emergency logistics scenarios, especially in terms of total transportation time, total cost, and fairness of resource allocation. The simulation results verify the high efficiency of the model in terms of timeliness of emergency response and accuracy of resource allocation, and provide innovative theoretical support and practical scheme for the field of emergency logistics. Future research will explore more efficient consensus mechanisms, and combine big data and artificial intelligence technology to further improve the performance and adaptability of emergency logistics systems.
Algorithms , Blockchain , Resource Allocation , Emergencies , Models, Theoretical , Humans
Research is ongoing to find solutions to the problem of Consolidation and seepage in saturated clay in enclosure space. Firstly, the boundary of non-zero-constant values is established, considering the seepage boundary of the clay is affected by pumping water or lowering boundary pressure on the site. Secondly, the differential equation is established to reflect the spatial and temporal variations of excess pore water pressure dissipation in the clay in enclosure space, and the solution is derived using variable separation methods. Finally, based on results of the solution derived, contour maps of the water pressure are drawn corresponding with the different inhomogeneous boundary conditions.
Clay , Clay/chemistry , Water/chemistry , Pressure , Models, Theoretical , Aluminum Silicates/chemistry , Solutions
BACKGROUND: Adverse drug reactions (ADRs), which are the phenotypic manifestations of clinical drug toxicity in humans, are a major concern in precision clinical medicine. A comprehensive evaluation of ADRs is helpful for unbiased supervision of marketed drugs and for discovering new drugs with high success rates. OBJECTIVE: In current practice, drug safety evaluation is often oversimplified to the occurrence or nonoccurrence of ADRs. Given the limitations of current qualitative methods, there is an urgent need for a quantitative evaluation model to improve pharmacovigilance and the accurate assessment of drug safety. METHODS: In this study, we developed a mathematical model, namely the Adverse Drug Reaction Classification System (ADReCS) severity-grading model, for the quantitative characterization of ADR severity, a crucial feature for evaluating the impact of ADRs on human health. The model was constructed by mining millions of real-world historical adverse drug event reports. A new parameter called Severity_score was introduced to measure the severity of ADRs, and upper and lower score boundaries were determined for 5 severity grades. RESULTS: The ADReCS severity-grading model exhibited excellent consistency (99.22%) with the expert-grading system, the Common Terminology Criteria for Adverse Events. Hence, we graded the severity of 6277 standard ADRs for 129,407 drug-ADR pairs. Moreover, we calculated the occurrence rates of 6272 distinct ADRs for 127,763 drug-ADR pairs in large patient populations by mining real-world medication prescriptions. With the quantitative features, we demonstrated example applications in systematically elucidating ADR mechanisms and thereby discovered a list of drugs with improper dosages. CONCLUSIONS: In summary, this study represents the first comprehensive determination of both ADR severity grades and ADR frequencies. This endeavor establishes a strong foundation for future artificial intelligence applications in discovering new drugs with high efficacy and low toxicity. It also heralds a paradigm shift in clinical toxicity research, moving from qualitative description to quantitative evaluation.
Big Data , Data Mining , Drug-Related Side Effects and Adverse Reactions , Humans , Data Mining/methods , Pharmacovigilance , Models, Theoretical , Adverse Drug Reaction Reporting Systems/statistics & numerical data
Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event. In this study, 40 years (1982-2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series. From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment.
Hydrology , Rain , India , Climate Change , Models, Theoretical , Floods
Peer effects can directly or indirectly rely on interaction networks to drive people to follow ideas or behaviours triggered by a few individuals, and such effects can be largely improved by targeting the so-called influential individuals. In this article, we study the current most promising seeding strategy used in field experiments, the one-hop strategy, where the underlying interaction networks are generally too impractical or prohibitively expensive to be obtained, and propose an individual-centralized seeding approach to target influential seeds in information-limited networks. The presented strategy works by reasonable follow-up questions to respondents, such as Who do you think has more connections/friends?, and constructs the seeding set by those nodes with the most nominations. In this manner, the proposed method could acquire more information about the studied interaction network from the inference of respondents without surveying additional individuals. We evaluate our strategy on networks from various experimental datasets. Results show that the obtained seeds are much more influential compared to the one-hop strategy and other methods. We also show how the proposed approach could be implemented in field studies and potentially provide better interventions in real scenarios.
Models, Theoretical , Humans
Unsafe behavior among construction personnel poses significant risks in petroleum engineering construction projects. This study addresses this issue through the application of a multi-field coupled homogeneous analysis model. By conducting case analyses of petroleum engineering construction accidents and utilizing the WSR methodology, the influencing factors of unsafe behaviors among construction personnel are systematically categorized into organizational system factors, equipment management factors, and construction personnel factors. Subsequently, employing Risk coupling theory, the study delves into the analysis of these influencing factors, discussing their coupling mechanisms and classifications, and utilizing the N-K model to elucidate the coupling effect among them. Furthermore, a novel approach integrating coupling analysis and multi-agent modeling is employed to establish an evolutionary model of construction personnel's unsafe behavior. The findings reveal that a two-factor control method, concurrently reinforcing equipment and construction personnel management, significantly mitigates unsafe behavior. This study provides valuable insights into the evolution of unsafe behavior among construction personnel and offers a robust theoretical framework for targeted interventions. Significantly, it bears practical implications for guiding safety management practices within petroleum engineering construction enterprises. By effectively controlling unsafe behaviors and implementing targeted safety interventions, it contributes to fostering sustainable development within the petroleum engineering construction industry.
Construction Industry , Humans , Models, Theoretical , Petroleum , Accidents, Occupational/prevention & control , Safety Management
For a narrow-brand seismograph with a flat response range limited, it cannot precisely record the signal of a ground motion and output the records with the low-frequency components cut down. A transfer function is usually used to spread the spectrum of the narrow-brand seismic records. However, the accuracy of the commonly used transfer function is not high. The authors derive a new transfer function based on the Laplace transform, bilinear transform, and Nyquist sampling theory to solve this problem. And then, the derived transfer function is used to correct the narrow-band velocity records from the Hi-net. The corrected velocity records are compared with the velocities integrated from the synchronously recorded broad-band acceleration at the same station with Hi-net. Meanwhile, the corrected records are compared with those corrected by the Nakata transfer function. The results show that the calculation accuracy of the derived transfer function is higher than the Nakata transfer function. However, when the signal-to-noise ratio is below 24, its accuracy diminishes, and it is unable to recover signals within the 0.05-0.78Hz frequency band.
Algorithms , Models, Theoretical , Signal-To-Noise Ratio
To develop and validate a 3D simulation model to calculate laser ablation (LA) zone size and estimate the volume of treated tissue for thyroid applications, a model was developed, taking into account dynamic optical and thermal properties of tissue change. For validation, ten Yorkshire swines were equally divided into two cohorts and underwent thyroid LA at 3 W/1,400 J and 3 W/1,800 J respectively with a 1064-nm multi-source laser (Echolaser X4 with Orblaze™ technology; ElEn SpA, Calenzano, Italy). The dataset was analyzed employing key statistical measures such as mean and standard deviation (SD). Model simulation data were compared with animal gross histology. Experimental data for longitudinal length, width (transverse length), ablation volume and sphericity were 11.0 mm, 10.0 mm, 0.6 mL and 0.91, respectively at 1,400 J and 14.6 mm, 12.4 mm, 1.12 mL and 0.83, respectively at 1,800 J. Gross histology data showed excellent reproducibility of the ablation zone among same laser settings; for both 1,400 J and 1,800 J, the SD of the in vivo parameters was ≤ 0.7 mm, except for width at 1,800 J, for which the SD was 1.1 mm. Simulated data for longitudinal length, width, ablation volume and sphericity were 11.6 mm, 10.0 mm, 0.62 mL and 0.88, respectively at 1,400 J and 14.2 mm, 12.0 mm, 1.06 mL and 0.84, respectively at 1,800 J. Experimental data for ablation volume, sphericity coefficient, and longitudinal and transverse lengths of thermal damaged area showed good agreement with the simulation data. Simulation datasets were successfully incorporated into proprietary planning software (Echolaser Smart Interface, Elesta SpA, Calenzano, Italy) to provide guidance for LA of papillary thyroid microcarcinomas. Our mathematical model showed good predictability of coagulative necrosis when compared with data from in vivo animal experiments.
Laser Therapy , Thyroid Gland , Animals , Laser Therapy/methods , Laser Therapy/instrumentation , Thyroid Gland/surgery , Thyroid Gland/pathology , Swine , Computer Simulation , Models, Theoretical , Reproducibility of Results
Changes in climate shift the geographic locations that are suitable for malaria transmission because of the thermal constraints on vector Anopheles mosquitos and Plasmodium spp. malaria parasites and the lack of availability of surface water for vector breeding. Previous Africa-wide assessments have tended to solely represent surface water using precipitation, ignoring many important hydrological processes. Here, we applied a validated and weighted ensemble of global hydrological and climate models to estimate present and future areas of hydroclimatic suitability for malaria transmission. With explicit surface water representation, we predict a net decrease in areas suitable for malaria transmission from 2025 onward, greater sensitivity to future greenhouse gas emissions, and different, more complex, malaria transmission patterns. Areas of malaria transmission that are projected to change are smaller than those estimated by precipitation-based estimates but are associated with greater changes in transmission season lengths.
Anopheles , Hydrology , Malaria , Mosquito Vectors , Animals , Malaria/transmission , Africa , Anopheles/parasitology , Mosquito Vectors/parasitology , Climate Change , Humans , Seasons , Rain , Models, Theoretical , Water , Greenhouse Gases/analysis
From over-exploitation of resources to urban pollution, sustaining well-being requires solving social dilemmas of cooperation. Often such dilemmas are studied assuming that individuals occupy fixed positions in a network or lattice. In spatial settings, however, agents can move, and such movements involve costs. Here we investigate how mobility costs impact cooperation dynamics. To this end, we study cooperation dilemmas where individuals are located in a two-dimensional space and can be of two types: cooperators-or cleaners, who pay an individual cost to have a positive impact on their neighbours-and defectors-or polluters, free-riding on others' effort to sustain a clean environment. Importantly, agents can pay a cost to move to a cleaner site. Both analytically and through agent-based simulations we find that, in general, introducing mobility costs increases pollution felt in the limit of fast movement (equivalently slow strategy revision). The effect on cooperation of increasing mobility costs is non-monotonic when mobility co-occurs with strategy revision. In such scenarios, low (yet non-zero) mobility costs minimise cooperation in low density environments; whereas high costs can promote cooperation even when a minority of agents initially defect. Finally, we find that heterogeneity in mobility cost affects the final distribution of strategies, leading to differences in who supports the burden of having a clean environment.
Cooperative Behavior , Humans , Game Theory , Models, Theoretical , Social Welfare/economics
