105 research outputs found

    Laplace Adomian Decomposition and Modify Laplace Adomian Decomposition Methods for Solving Linear Volterra Integro-Fractional Differential Equations with Constant Multi-Time Retarded Delay

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         في هذا العمل نقدم تحويلات لابلاس مع طريقة أدوميان التحليلية المتسلسلة و كما اننا نعدل طريقة أدوميان التحليلية للمرة الاولى لحل معادلات فولتيرا التفاضلية-التكاملية الخطيه للرتب الكسرية كما في مفهوم كابوتو مع التأخير الحدي المتضاعف الثابت. هذه الطريقة تعتمد على مزيج ممتاز من طريقة تحويلات لابلاس، طريقة تحديد المتسلسلات، طريقة متعددات الحدود لادوميان مع التعديلات. أن التقنية المستخدمة تحول التأخير الحدي للمعادلات التفاضلية ذات التكاملات الكسرية الى معادلات جبرية متكررة عندما تكون نواة الفروق من نوع المنحل البسيط. و أخيراَ أعطيت أمثلة لتوضيح فعالية و ديقة الطرق المقترحة.In this work, we present Laplace transform with series Adomian decomposition and modify Adomian decomposition methods for the first time to solve linear Volterra integro-differential equations of the fractional order in Caputo sense with constant multi-time Retarded delay. This method is primarily based on the elegant mixture of Laplace transform method, series expansion method and Adomian polynomial with modifications. The proposed technique will transform the multi-term delay integro-fractional differential equations into some iterative algebraic equations, and it is capable of reducing computational analytical works where the kernel of difference and simple degenerate types. Analytical examples are presented to illustrate the efficiency and accuracy of the proposed methods

    Heat Treated NiP–SiC Composite Coatings: Elaboration and Tribocorrosion Behaviour in NaCl Solution

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    Tribocorrosion behaviour of heat-treated NiP and NiP–SiC composite coatings was investigated in a 0.6 M NaCl solution. The tribocorrosion tests were performed in a linear sliding tribometer with an electrochemical cell interface. It was analyzed the influence of SiC particles dispersion in the NiP matrix on current density developed, on coefficient of friction and on wear volume loss. The results showed that NiP–SiC composite coatings had a lower wear volume loss compared to NiP coatings. However, the incorporation of SiC particles into the metallic matrix affects the current density developed by the system during the tribocorrosion test. It was verified that not only the volume of co-deposited particles (SiC vol.%) but also the number of SiC particles per coating area unit (and consequently the SiC particles size) have made influence on the tribocorrosion behaviour of NiP–SiC composite coatings

    A PDRMIP multi-model study on the impacts of regional aerosol forcings on global and regional precipitation

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    Atmospheric aerosols such as sulfate and black carbon (BC) generate inhomogeneous radiative forcing and can affect precipitation in distinct ways compared to greenhouse gases (GHGs). Their regional effects on the atmospheric energy budget and circulation can be important for understanding and predicting global and regional precipitation changes, which act on top of the background GHG-induced hydrological changes. Under the framework of the Precipitation Driver Response Model Inter-comparison Project (PDRMIP), multiple models were used for the first time to simulate the influence of regional (Asian and European) sulfate and BC forcing on global and regional precipitation. The results show that, as in the case of global aerosol forcing, the global fast precipitation response to regional aerosol forcing scales with global atmospheric absorption, and the slow precipitation response scales with global surface temperature response. Asian sulphate aerosols appear to be a stronger driver of global temperature and precipitation change compared to European aerosols, but when the responses are normalised by unit radiative forcing or by aerosol burden change, the picture reverses, with European aerosols being more efficient in driving global change. The global apparent hydrological sensitivities of these regional forcing experiments are again consistent with those for corresponding global aerosol forcings found in the literature. However, the regional responses and regional apparent hydrological sensitivities do not align with the corresponding global values. Through a holistic approach involving analysis of the energy budget combined with exploring changes in atmospheric dynamics, we provide a framework for explaining the global and regional precipitation responses to regional aerosol forcing

    When global norms meet local politics : localising transparency in extractive industries governance

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    Processes of norm localisation play a crucial role in shaping the extent to which global governance norms are institutionalised at national and sub‐national levels. This article explores the politics of norm localisation through an empirical investigation of how global norms of “transparency” were localised in sub‐national processes of extractive industry governance in Bojonegoro, Indonesia. Previous theories of localisation have emphasised “constructivist” dynamics through which patterns of norm localisation are shaped decisively by efforts to build normative or cognitive congruence with local ideas and identities. In contrast, the mix of a newly democratised environment, the persistent power of corporatist elite networks and a populist style of local politics prevailing in Bojonegoro have diminished the significance of such constructivist dynamics as a basis for explaining varied patterns of norm localisation. Instead, patterns of norm localisation have depended crucially on the capacity of local political leaders to harness global governance norms instrumentally as a basis for consolidating and strengthening their own local power base. These findings have important implications for both theoretical and practical understandings of how global norm localisation processes vary in response to the contrasting political contexts in which global governance norms targeting the extractive sector are implemented

    Scientific data from precipitation driver response model intercomparison project

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    This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth's radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project

    Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI’s GPT-4 model

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    The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model’s ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model’s potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback

    SVD Audio Watermarking: A Tool to Enhance the Security of Image Transmission over ZigBee Networks, Journal of Telecommunications and Information Technology, 2011, nr 4

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    The security is important issue in wireless networks. This paper discusses audio watermarking as a tool to improve the security of image communication over the IEEE 802.15.4 ZigBee network. The adopted watermarking method implements the Singular-Value Decomposition (SVD) mathematical technique. This method is based on embedding a chaotic encrypted image in the Singular Values (SVs) of the audio signal after transforming it into a 2-D format. The objective of chaotic encryption is to enhance the level of security and resist different attacks. Experimental results show that the SVD audio watermarking method maintains the high quality of the audio signals and that the watermark extraction and decryption are possible even in the presence of attacks over the ZigBee network

    Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

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    BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700
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