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To control the rapid spread of COVID-19, we consider deploying a set of Unmanned Aerial Vehicles (UAVs) to form a quarantine barrier such that anyone crossing the barrier can be detected. We use a charging pile to recharge UAVs. T...
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To control the rapid spread of COVID-19, we consider deploying a set of Unmanned Aerial Vehicles (UAVs) to form a quarantine barrier such that anyone crossing the barrier can be detected. We use a charging pile to recharge UAVs. The problem is scheduling UAVs to cover the barrier, and, for any scheduling strategy, estimating theminimum number of UAVs needed to cover the barrier forever. We propose breaking the barrier into subsegments so that each subsegment can be monitored by a single UAV. We then analyze two scheduling strategies, where the first one is simple to implement and the second one requires fewer UAVs. The first strategy divides UAVs into groups with each group covering a subsegment. For this strategy, we derive a closed-form formula for the minimum number of UAVs. In the case of insufficient UAVs, we give a recursive function to compute the exact coverage time and give a dynamic-programming algorithm to allocate UAVs to subsegments to maximize the overall coverage time. The second strategy schedules all UAVs dynamically. We prove a lower and an upper bound on the minimum number of UAVs. We implement a prototype system to verify the proposed coverage model and perform simulations to investigate the performance.
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The Birnbaum-Saunders distribution is a positively skewed distribution that is frequently used for analyzing lifetime data. Regression analysis is widely used in this context when some covariates are involved in the life-test. In ...
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The Birnbaum-Saunders distribution is a positively skewed distribution that is frequently used for analyzing lifetime data. Regression analysis is widely used in this context when some covariates are involved in the life-test. In this article, we discuss the maximum likelihood estimation of the model parameters and associated inference. We discuss the likelihood-ratio tests for some hypotheses of interest as well as some interval estimation methods. A Monte Carlo simulation study is then carried out to examine the performance of the proposed estimators and the interval estimation methods. Finally, some numerical data analyses are done for illustrating all the inferential methods developed here.
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In this paper, we propose two moment-type estimation methods for the parameters of the generalized bivariate Birnbaum-Saunders distribution by taking advantage of some properties of the distribution. The proposed moment-type estim...
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In this paper, we propose two moment-type estimation methods for the parameters of the generalized bivariate Birnbaum-Saunders distribution by taking advantage of some properties of the distribution. The proposed moment-type estimators are easy to compute and always exist uniquely. We derive the asymptotic distributions of these estimators and carry out a simulation study to evaluate the performance of all these estimators. The probability coverages of confidence intervals are also discussed. Finally, two examples are used to illustrate the proposed methods.
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Plant genetic engineering is essential for improving crop yield, quality, and resistance to abiotic/biotic stresses for sustainable agriculture. Agrobacterium-, biolistic bombardment-, electroporation-, and poly(ethylene glycol) (...
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Plant genetic engineering is essential for improving crop yield, quality, and resistance to abiotic/biotic stresses for sustainable agriculture. Agrobacterium-, biolistic bombardment-, electroporation-, and poly(ethylene glycol) (PEG)-mediated genetic-transformation systems are extensively used in plant genetic engineering. However, these systems have limitations, including species dependency, destruction of plant tissues, low transformation efficiency, and high cost. Recently, nanotechnology-based gene-delivery methods have been developed for plant genetic transformation. This nanostrategy shows excellent transformation efficiency, good biocompatibility, adequate protection of exogenous nucleic acids, and the potential for plant regeneration. However, the nanomaterial-mediated gene-delivery system in plants is still in its infancy, and there are many challenges for its broad applications. Herein, the conventional genetic transformation techniques used in plants are briefly discussed. After that, the progress in the development of nanomaterial-based gene-delivery systems is considered. CRISPR-Cas-mediated genome editing and its combined applications with plant nanotechnology are also discussed. The conceptual innovations, methods, and practical applications of nanomaterial-mediated genetic transformation summarized herein will be beneficial for promoting plant genetic engineering in modern agriculture.
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Bloodstream infections caused by nontyphoidal Salmonella are a major public health concern in Africa, causing similar to 49,600 deaths every year. The most common Salmonella enterica pathovariant associated with invasive nontyphoi...
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Bloodstream infections caused by nontyphoidal Salmonella are a major public health concern in Africa, causing similar to 49,600 deaths every year. The most common Salmonella enterica pathovariant associated with invasive nontyphoidal Salmonella disease is Salmonella Typhimurium sequence type (ST)313. It has been proposed that antimicrobial resistance and genome degradation has contributed to the success of ST313 lineages in Africa, but the evolutionary trajectory of such changes was unclear. Here, to define the evolutionary dynamics of ST313, we sub-sampled from two comprehensive collections of Salmonella isolates from African patients with bloodstream infections, spanning 1966 to 2018. The resulting 680 genome sequences led to the discovery of a pan-susceptible ST313 lineage (ST313 L3), which emerged in Malawi in 2016 and is closely related to ST313 variants that cause gastrointestinal disease in the United Kingdom and Brazil. Genomic analysis revealed degradation events in important virulence genes in ST313 L3, which had not occurred in other ST313 lineages. Despite arising only recently in the clinic, ST313 L3 is a phylogenetic intermediate between ST313 L1 and L2, with a characteristic accessory genome. Our in-depth genotypic and phenotypic characterization identifies the crucial loss-of-function genetic events that occurred during the stepwise evolution of invasive S. Typhimurium across Africa.
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Water and land resources are important material bases of economic and social development, and their spatial patterns determine the pattern of the urban development. The development and expansion of coal-resource-based cities have ...
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Water and land resources are important material bases of economic and social development, and their spatial patterns determine the pattern of the urban development. The development and expansion of coal-resource-based cities have introduced new societal problems, such as the overlapping of new city construction areas and underground coal resources. Underground coal mining also leads to surface subsidence, which destroys water and land resources and seriously affects the sustainable development of coal-resource-based cities. The surface subsidence area takes a long time to stabilize, and may form a large waterlogging area due to the high groundwater level, thereby increasing the difficulty of reconstructing mining subsidence areas. In this context, a scientific and complete method for reconstructing the spatial pattern of water and land resources in unstable coal mining subsidence areas within urban is proposed in this paper. This method initially predicts the surface subsidence value and then divides the subsidence area within the urban region into the waterlogging area and the non-waterlogging area according to the surface subsidence value. The waterlogging area will be renovated into a landscape lake district in the city by a series of transformation measures. Afterwards, goaf rock mass activation and surface stability evaluation analyses are performed in the non-waterlogging area. According to the evaluation results, land resources can be divided into unaffected, restricted and prohibited building areas, with each area being transformed differently. The Lv Jin Lake in Huaibei is selected as a case study, and the proposed method is applied to reconstruct its water and land resources. The original spatial pattern of the large-scale waterlogging area and abandoned land due to mining subsidence in urban areas is then reconstructed into a spatial pattern that integrates the urban landscape, scenario living and eco-tourism. Compared with traditional subsidence area management, the proposed method greatly increases the utilization value of water and land resources, improves the urban ecological environment, enhances the urban quality and effectively alleviates the problems of land shortage and human–land conflict in coal-resource-based cities.
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We consider the cache placement problem in campus networks where routers have heterogeneous cache capacity and the objective is to minimize the total delay of all requests. We prove that the problem is NP-hard to approximate to wi...
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We consider the cache placement problem in campus networks where routers have heterogeneous cache capacity and the objective is to minimize the total delay of all requests. We prove that the problem is NP-hard to approximate to within any factor less than n/m(epsilon) + poly(m), where n is the number of routers, m is the number of contents, epsilon is any fixed positive constant, and poly(m) is any polynomial function of m. We propose (exponential-time) exact algorithms based on integer linear programming and propose techniques to decompose the network and remove redundant variables for speeding up the computation. By relaxing the integer linear programs, we also propose three (polynomial-time) heuristic algorithms. Numerical results show that the proposed algorithms give a shorter delay than existing cache decision algorithms for content-centric networks.
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The exponential-geometric distribution has been proposed as a simple and useful reliability model for analyzing lifetime data. For this distribution, some recurrence relations are established for the single moments and product mom...
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The exponential-geometric distribution has been proposed as a simple and useful reliability model for analyzing lifetime data. For this distribution, some recurrence relations are established for the single moments and product moments of order statistics. Using these recurrence relations, the means, variances and covariances of all order statistics can be computed for all sample sizes in a simple and efficient recursive manner. Next, we discuss the maximum likelihood estimation of the model parameters as well as some simple modified methods of estimation. Then, a Monte Carlo simulation study is carried out to evaluate the performance of all these methods of estimation in terms of their bias and mean square error as well as the percentage of times the estimates converged. Two illustrative examples are finally presented to illustrate all the inferential results developed here.
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In this paper, we will first derive explicit expressions for the predictive maximum likelihood estimators (PMLEs) for Laplace distribution based on a time-constrained life-testing experiment. Next, we derive the exact conditional ...
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In this paper, we will first derive explicit expressions for the predictive maximum likelihood estimators (PMLEs) for Laplace distribution based on a time-constrained life-testing experiment. Next, we derive the exact conditional distribution of the likelihood predictor of the s-th failure through the use of exact conditional moment generating function (MGF). We develop three different exact prediction intervals for the future failure, and a Monte Carlo simulation study is then carried out to check the accuracy of the derived exact inference. Finally, an example is presented to illustrate all the inferential results developed here.
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Introduction: Pre-eclampsia is a serious pregnancy complication and a major global concern for the mortality of both mother and fetus. Existing symptomatic treatments do not delay disease progression; thus, timely delivery of the ...
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Introduction: Pre-eclampsia is a serious pregnancy complication and a major global concern for the mortality of both mother and fetus. Existing symptomatic treatments do not delay disease progression; thus, timely delivery of the baby is the most effective measure. However, the risk of various maternal and fetal injuries remains. Areas covered: In this review, we summarize potential strategies for pharmacologic interventions in pre-eclamptic therapy. Specifically, we discuss the pathophysiological process of various effective candidate therapeutics that act on potential pathways and molecular targets to inhibit key stages of the disease. We refer to this pathogenesis-focused drug discovery model as a pathogenesis-target- drug (P-T-D) strategy. Finally, we discuss the introduction of nanotechnologies to improve the safety and efficacy of therapeutics via their specific placental targeting ability and placental retention effects. Expert opinion: Despite the active development of novel pharmacological treatments based on our current knowledge of pre-eclamptic pathogenesis, investigations are still in the early phase. Thus, further exploration of the pathological mechanisms, integrated with the P-T-D strategy and novel nanosystems, could encourage more effective and safer strategies. Such advances could lead to a shift from expectant management to mechanistic-based therapy for pre-eclampsia.
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