68 research outputs found
The Incremental Cooperative Design of Preventive Healthcare Networks
This document is the Accepted Manuscript version of the following article: Soheil Davari, 'The incremental cooperative design of preventive healthcare networks', Annals of Operations Research, first published online 27 June 2017. Under embargo. Embargo end date: 27 June 2018. The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-017-2569-1.In the Preventive Healthcare Network Design Problem (PHNDP), one seeks to locate facilities in a way that the uptake of services is maximised given certain constraints such as congestion considerations. We introduce the incremental and cooperative version of the problem, IC-PHNDP for short, in which facilities are added incrementally to the network (one at a time), contributing to the service levels. We first develop a general non-linear model of this problem and then present a method to make it linear. As the problem is of a combinatorial nature, an efficient Variable Neighbourhood Search (VNS) algorithm is proposed to solve it. In order to gain insight into the problem, the computational studies were performed with randomly generated instances of different settings. Results clearly show that VNS performs well in solving IC-PHNDP with errors not more than 1.54%.Peer reviewe
Dynamic temporary blood facility location-allocation during and post-disaster periods
The key objective of this study is to develop a tool (hybridization or integration of different techniques) for locating the temporary blood banks during and post-disaster conditions that could serve the hospitals with minimum response time. We have used temporary blood centers, which must be located in such a way that it is able to serve the demand of hospitals in nearby region within a shorter duration. We are locating the temporary blood centres for which we are minimizing the maximum distance with hospitals. We have used Tabu search heuristic method to calculate the optimal number of temporary blood centres considering cost components. In addition, we employ Bayesian belief network to prioritize the factors for locating the temporary blood facilities. Workability of our model and methodology is illustrated using a case study including blood centres and hospitals surrounding Jamshedpur city. Our results shows that at-least 6 temporary blood facilities are required to satisfy the demand of blood during and post-disaster periods in Jamshedpur. The results also show that that past disaster conditions, response time and convenience for access are the most important factors for locating the temporary blood facilities during and post-disaster periods
Adaptive mechanisms of plants against salt stress and salt shock
Salinization process occurs when soil is contaminated with salt, which consequently influences plant growth and development leading to reduction in yield of many food crops. Responding to a higher salt concentration than the normal range can result in plant developing complex physiological traits and activation of stress-related genes and metabolic pathways. Many studies have been carried out by different research groups to understand adaptive mechanism in many plant species towards salinity stress. However, different methods of sodium chloride (NaCl) applications definitely give different responses and adaptive mechanisms towards the increase in salinity. Gradual increase in NaCl application causes the plant to have salt stress or osmotic stress, while single step and high concentration of NaCl may result in salt shock or osmotic shock. Osmotic shock can cause cell plasmolysis and leakage of osmolytes in plant. Also, the gene expression pattern is influenced by the type of methods used in increasing the salinity. Therefore, this chapter discusses the adaptive mechanism in plant responding to both types of salinity increment, which include the morphological changes of plant roots and aerial parts, involvement of signalling molecules in stress perception and regulatory networks and production of osmolyte and osmoprotective proteins
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
A LOCATION-INVENTORY MODEL INCLUDING DELIVERY DELAY COST AND CAPACITY CONSTRAINTS IN A STOCHASTIC DISTRIBUTION NETWORK
<p>ENGLISH ABSTRACT: In this paper, we present a distribution network design problem in a supply chain system that minimises the total cost of location, inventory, and delivery delay. Customers’ demands are random, and multiple capacity levels are available for the distribution centers. The problem is first formulated as a mixed integer convex programming model to optimally solve medium-sized instances, and then a heuristic is developed for solving large-sized instances.</p><p>AFRIKAANSE OPSOMMING: In hierdie artikel word ‘n distribusienetwerkprobleem in ‘n voorsieningsketting voorgehou waar die totale koste van die ligging, voorraad en afleweringsvertragings geminimiseer word. Die vraag is lukraak en verskeie kapasiteitsvlakke is beskikbaar in die verspreidingsentra. Die problem word eers geformuleer as ‘n gemengde-heeltal-konvekse model sodat mediumgrootte gevalle geoptimiseer kan word, waarna ‘n heuristieke benadering ontwikkel word vir die oplos van grootskaalse aktiwiteite.</p>
Two stage heuristic algorithm for logistics network optimization of integrated location-routing-inventory
To reduce the cost of logistics, optimize logistics warehousing layout and logistics distribution efficiency, logistics network of the integrated location-routing-inventory was studied. In this paper, we present a model of integrated Location-Routing and Inventory problem (ILRIP) that considers the selection of warehouses location, the inventory of products, and vehicle routing. Aiming at the characteristics of proposed model, a two-stage optimization problem is designed, and two main objective functions are established to minimize the expected total cost of inventory and location selection and distribution costs with time windows. Considering multiple constraints, the multi-objective optimization problems is designed. We solve the developed mathematical model by genetic algorithm (GA), then we code in MATLAB, a case study is proposed to prove industrial practicality of the model
Detection of human herpes virus type-6 in patients undergoing hemodialysis
Aim: To investigate the epidemiology of human herpes virus type-6 (HHV-6) among hemodialysis (HD) patients. Materials & methods: DNA was extracted from plasma samples of 149 patients undergoing HD with no history of organ transplantation from 2011 to 2013. Presence of HHV-6 was investigated by using real-time PCR. Results: Diabetes (36.2) and hypertension (28.8) were two major factors for HD. The HHV-6 DNA was identified in eight patients (5.37). Conclusion: This study is one of the few reports of HHV-6 infection among HD patients. In HD patient population, it is critical to improve standards of infection control in dialysis and expand treatment coverage. Furthermore, studies on clinical implications of HHV-6 infection in HD patients are crucial. © 2018 Future Medicine Ltd
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