Water softening using a light-responsive, spiropyran-modified nanofiltration membrane

A novel technique for the covalent attachment of a light-responsive spiropyran onto polyamide thin film composite nanofiltration (NF) membranes in a one-step reaction using low-energy electron beam technology is described. The effect of illumination of the immobilized spiropyran was studied, as well as the resulting membrane properties with respect to MgSO4 retention, water permeability rate, and chlorine resistance. Electron beam irradiation showed a direct effect on the transformation of the rough PA NF membrane surface into a ridge-and-valley structure. Upon UV light irradiation, the spiropyran transformed into zwitterionic merocyanine, which had shown MgSO4 removal of >95% with water permeation rates of 6.5 L/(m2·h·bar). Alternatively, visible light was used to convert merocyanine to spiropyran, which achieved >95% of MgSO4 retention with a water flux of around 5.25 L/(m2·h·bar). The modified NF membranes showed higher chlorine resistance as well as a higher normalized water flux as compared to the reference membrane, without a loss of ion retention. All the NF membranes were characterized by scanning electron microscopy and X-ray photoelectron spectroscopy. This study demonstrates a simple and inexpensive method for the immobilization of molecules onto polymeric membranes, which may be applied in water softening

A three-dimensional customer commitment model : its impact on relational outcomes

Customer's ever increasing bargaining power makes it particularly important that practitioners and researchers more thoroughly understand the complex nature of customer commitment. Not surprisingly, however, although the construct of commitment has emerged as one of the key constructs in relationship marketing and has been widely studied in literature, there has been very little agreement on the conceptualisation of the construct. Building upon relationship marketing and organisational behaviour literature, the aim of this research is to extend our understanding of the nature of customer commitment by developing a three-dimensional customer commitment model relaying on commitment theory from the organisational behaviour literature; affective desire-based (AC), calculative cost-based (CC), and normative obligation-based (NC). Relationships among the commitment dimensions and relationships with a number of loyalty relational outcomes, namely, intention to stay (ITS), word of mouth (WOM), and willingness to pay (WTP) were investigated in this study. Using survey questionnaire distributed among customers of cell phone services (N=525), the data was analysed by structural equation modeling (SEM) and then additional analysis was employed to further demystify the complexity of the commitment concept. The results suggest that AC is the dominant source that generates customer loyalty, in line with the state of literature. Both cost-based and surprisingly obligation-based have shown detrimental effects on maintaining and developing the customer-service provider relationship. Additional analysis with various scenarios was implemented using mean split as cut score for high/low commitment dimensions. The findings suggest NC turns to have important positive role on relational outcomes when both AC and CC are below the mean split. When both AC and CC are high NC negatively affect at least ITS but at the same time make a clear positive effect on WTP. The findings can be instructional for identifying how firms can bend various marketing sources to secure more loyal customers to the service provider.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A three-dimensional customer commitment model : its impact on relational outcomes

Customer's ever increasing bargaining power makes it particularly important that practitioners and researchers more thoroughly understand the complex nature of customer commitment. Not surprisingly, however, although the construct of commitment has emerged as one of the key constructs in relationship marketing and has been widely studied in literature, there has been very little agreement on the conceptualisation of the construct. Building upon relationship marketing and organisational behaviour literature, the aim of this research is to extend our understanding of the nature of customer commitment by developing a three-dimensional customer commitment model relaying on commitment theory from the organisational behaviour literature; affective desire-based (AC), calculative cost-based (CC), and normative obligation-based (NC). Relationships among the commitment dimensions and relationships with a number of loyalty relational outcomes, namely, intention to stay (ITS), word of mouth (WOM), and willingness to pay (WTP) were investigated in this study. Using survey questionnaire distributed among customers of cell phone services (N=525), the data was analysed by structural equation modeling (SEM) and then additional analysis was employed to further demystify the complexity of the commitment concept. The results suggest that AC is the dominant source that generates customer loyalty, in line with the state of literature. Both cost-based and surprisingly obligation-based have shown detrimental effects on maintaining and developing the customer-service provider relationship. Additional analysis with various scenarios was implemented using mean split as cut score for high/low commitment dimensions. The findings suggest NC turns to have important positive role on relational outcomes when both AC and CC are below the mean split. When both AC and CC are high NC negatively affect at least ITS but at the same time make a clear positive effect on WTP. The findings can be instructional for identifying how firms can bend various marketing sources to secure more loyal customers to the service provider.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Analysis and Modification of a Particle Filter Algorithm for Sensorless Control of BLDC Machine

This paper investigates the performance of a newly developed particle filter (PF) algorithm for sensorless control of the Brushless DC (BLDC) machines. A number of modifications have also been incorporated to the proposed PF algorithm in order to improve its performance with respect to resampling process and robust operation when unpredicted disturbances are occurred. The disturbances investigated in this paper include the presence of unconventional Non-Gaussian noises, changes in machine’s parameters, and occurrence of inter-turn short circuit fault. In addition, the paper proposes several measures in order to improve the estimation accuracy of the filter and enhance the filter robustness against system uncertainties. In order to evaluate the performance of the PF algorithm, the sensorless control system of a 1.5 kW BLDC machine is simulated in MATLAB/Simulink environment. Simulation results show that the introduced techniques considerably improve the performance of the PF algorithm as state estimator

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Monte Carlo simulation for investigation of morphology dependent charge transport in bulk-heterojunction organic solar cells

Morphology, the spatial distribution of traps, interdomain connectivity, and phase separation of the active layer play a critical role in the performance of the bulk heterojunction (BHJ) organic solar cells (OSCs). In this work, we utilize the hopping transport model to simulate the effect of morphological and structural parameters on the diffusion coefficient and efficiency of the polymer-fullerene BHJ solar cells. In BHJ solar cells there are two distinct phases as electron transport material (acceptor) and hole transport material (donor). Here we try to create an almost realistic network containing P3HT polymer chains and PCBM clusters for simulating the charge transport in the active layer. The blend ratio of P3HT:PCBM polymers and alignment of these bicontinuous networks of active layer are considered here as the morphological parameter affecting the cell performance. The dependency of the charge transport on such morphological parameters is obtained in this study by using Monte Carlo continues time random walk simulations