Potential impact of climate change and water resources development on the epidemiology of schistosomiasis in China

Schistosomiasis japonica, caused by the blood fluke Schistosoma japonicum, has been endemic in China since ancient times. An estimated 11 million people were infected in the mid-1950s. Recognizing the huge public health significance and the economic impact of the disease, the central government of China implemented a large-scale control programme, which has been sustained and constantly adapted over the past half century. Today, the endemic areas are mainly confined to the lake and marshland regions along the Yangtze River in five provinces, namely Jiangsu, Anhui, Jiangxi, Hunan and Hubei. It is estimated that currently about 800,000 people are infected and that 40 million people are at risk of infection. Historically, the northern geographical limit where schistosomiasis transmission occurred was around the 33°15’ N latitude (e.g. in Baoying county, Jiangsu province), governed by low temperature thresholds. Based on various climate models, the Intergovernmental Panel of Climate Change (IPCC) recently concluded that the Earth has warmed by approximately 0.6°C over the past 100 years. This unusual warming has been particularly pronounced during the last three decades. There is growing consensus that the global trend of climate warming will continue in the 21st century. It has been suggested that climate change could impact on the distribution of the intermediate host snail of S. japonicum, i.e. Oncomelania hupensis. The frequency and transmission dynamics of schistosomiasis can also be affected by waterresource development and management. Among others, the South-to-North Water Transfer (SNWT) project” is currently under construction in China, which intends to divert water from South (the snail-infested Yangtze River) to North (Beijing and Tianjing) via the lakes of Gaoyou, Hongze and others. The implementation and operation of this project could further amplify the negative effects of climate change and facilitate the northward spread of O. hupensis. The main objective of this PhD thesis was to explore the potential impact of climate change and the SNWT project on the future distribution of schistosomiasis japonica, particularly in eastern China. The techniques used were geographic information system (GIS) and remote sensing (RS), coupled with Bayesian spatial statistics, which have become key tools for disease mapping and prediction. First, we reviewed the application of GIS/RS techniques for the epidemiology and control of schistosomiasis in China. The applications included mapping prevalence and intensity data of S. japonicum at a large scale, and identifying and predicting suitable habitats for O. hupensis at a small scale. Other prominent applications were the prediction of infection risk due to ecological transformations, particularly those induced by floods and water-resource development projects, and the potential impact of climate change. We discussed the limitations of the previous work, and outlined potential new applications of GIS/RS techniques, namely quantitative GIS, WebGIS and the utilization of emerging satellite-derived data, as they hold promise to further enhance infection risk mapping and disease prediction. We also stressed current research needs to overcome some of the remaining challenges of GIS/RS applications for schistosomiasis, so that further and sustained progress can be made towards the ultimate goal to eliminate the disease from China. Second, recognizing the advantages of combining GIS/RS techniques with advanced spatial statistical approaches, we developed Bayesian spatio-temporal models to analyze the relationship between key climatic factors and the risk of schistosomiasis infection. We used parasitological data collected annually from 1990 to 1998 by means of cross-sectional surveys carried out in 47 counties of Jiangsu province. Climatic factors, namely land surface temperature (LST) and normalized difference vegetation index (NDVI), were obtained from satellite sensors. Our analysis suggested a negative association between NDVI and the risk of S. japonicum infection, whereas an increase in LST contributed to a significant increase in S. japonicum infection prevalence. Third, in order to better understand the changes in the frequency and transmission dynamics of schistosomiasis in a warmer future China, a series of laboratory experiments were conducted to assess the effect of temperature on the parasite-intermediate host snail interaction. We found a positive linear relationship between the development of. S. japonicum larvae harboured in O. hupensis and temperature. In snails kept at 15.3°C, S. japonicum larvae tend to halt their development, while peak development occurs at 30°C. The temperature at which half of the snails were in hibernation is 6.4°C. A statistically significant positive association was observed between temperature and oxygen intake of O. hupensis at temperatures below 13.0°C. We also detected a logistic relationship between snails’ oxygen intake and their hibernation rate. Our results underscored the important role temperature plays both for the activity of O. hupensis and the development of S. japonicum larvae harboured in the intermediate host snail. Fourth, to substantiate the claim that global warming might alter the frequency and transmission dynamics of S. japonicum in China, we conducted a time-series analysis from 1972-2002, using temperature data from 39 counties of Jiangsu province. Using annual growing degree days (AGDDs) with a temperature threshold of 15.3°C, we forecasted changes in S. japonicum transmission. The final model included a temporal and a spatial component. The temporal trend consisted of second order polynomials in time plus a seasonality component, while the spatial trend was formed by second order polynomials of the coordinates plus the thin plate smoothing splines. The AGDDs of S. japonicum in 2003 and 2006 and their difference were calculated. The temperatures at the 39 locations showed an increasing temporal trend and seasonality with periodicities of 12, 6 and 3 months. The predicted AGDDs increased gradually from north to south in both 2003 and 2006. The increase in AGDD was particularly pronounced in the southern part of the study area. Our results suggest that alterations in the transmission intensity of S. japonicum in south Jiangsu will be more pronounced than in the northern part of the province. Fifth, we further assessed the potential impact of climate change on the distribution of O.hupensis via a spatially-explicit analytical approach. We employed two 30-year composite datasets comprising average monthly temperatures collected at 623 meteorological stations throughout China, spanning the periods 1961-1990 and 1971-2000. Temperature changes were assessed spatially between the 1960s and the 1990s for January, as this is the critical month for survival of O. hupensis. Our results show that the mean January temperatures increased at 590 stations (94.7%), and that China’s average January temperature in the 1990s was 0.96°C higher than 30 years earlier. The historical 0-1°C January isotherm, which has been considered the approximate northern limit of S. japonicum transmission, has shifted from 33°15’ N to 33°41’ N, expanding the potential transmission area by 41,335 km2. This translates to an estimated additional 21 million people at risk of schistosomiasis. Two lakes that form part of the SNWT project are located in this new potential transmission area, namely Hongze and Baima. Finally, we applied GIS/RS techniques to predict potentially new snail habitats around the lakes of Hongze and Baima, as well as Gaoyou lake, which is considered as a habitat where O. hupensis could re-emerge. A model based on flooding areas, NDVI and a wetness index extracted from Landsat images was developed to predict the snail habitats at a small scale. A total of 163.6 km2 of potential O. hupensis habitats were predicted around the three study lakes. In conclusion, our work suggests that global warming and a major water-resource development project could impact on the distribution of S. japonicum and its intermediate host snail in China and demonstrates that the combination of GIS, RS and Bayesian spatial statistical methods is a powerful approach in estimating their extent. The predictions can serve as a basis for health policy makers and disease control managers, and can be of use in the establishment and running of schistosomiasis surveillance systems. It is further suggested that an efficient early warning system should be set up in potential new endemic areas to monitor subtle changes in snail habitats due to climate change and major ecological transformations, and to assure the early detection of emerging and re-emerging schistosomiasis

Accelerating Data Loading in Deep Neural Network Training

Data loading can dominate deep neural network training time on large-scale systems. We present a comprehensive study on accelerating data loading performance in large-scale distributed training. We first identify performance and scalability issues in current data loading implementations. We then propose optimizations that utilize CPU resources to the data loader design. We use an analytical model to characterize the impact of data loading on the overall training time and establish the performance trend as we scale up distributed training. Our model suggests that I/O rate limits the scalability of distributed training, which inspires us to design a locality-aware data loading method. By utilizing software caches, our method can drastically reduce the data loading communication volume in comparison with the original data loading implementation. Finally, we evaluate the proposed optimizations with various experiments. We achieved more than 30x speedup in data loading using 256 nodes with 1,024 learners.Comment: 11 pages, 12 figures, accepted for publication in IEEE International Conference on High Performance Computing, Data and Analytics (HiPC) 201

Green-Aware Virtual Machine Migration Strategy in Sustainable Cloud Computing Environments

As cloud computing develops rapidly, the energy consumption of large-scale datacenters becomes unneglectable, and thus renewable energy is considered as the extra supply for building sustainable cloud infrastructures. In this chapter, we present a green-aware virtual machine (VM) migration strategy in such datacenters powered by sustainable energy sources, considering the power consumption of both IT functional devices and cooling devices. We define an overall optimization problem from an energy-aware point of view and try to solve it using statistical searching approaches. The purpose is to utilize green energy sufficiently while guaranteeing the performance of applications hosted by the datacenter. Evaluation experiments are conducted under realistic workload traces and solar energy generation data in order to validate the feasibility. Results show that the green energy utilization increases remarkably, and more overall revenues could be achieved

Optimization of CNOT circuits on topological superconducting processors

We focus on optimization of the depth/size of CNOT circuits under topological connectivity constraints. We prove that any $n$-qubit CNOT circuit can be paralleled to $O(n)$ depth with $n^2$ ancillas for $2$-dimensional grid structure. For the high dimensional grid topological structure in which every quibit connects to $2\log n$ other qubits, we achieves the asymptotically optimal depth $O(\log n)$ with only $n^2$ ancillas. We also consider the synthesis without ancillas. We propose an algorithm uses at most $2n^2$ CNOT gates for arbitrary connected graph, considerably better than previous works. Experiments also confirmed the performance of our algorithm. We also designed an algorithm for dense graph, which is asymptotically optimal for regular graph. All these results can be applied to stabilizer circuits

A Neutrosophic Approach Based on TOPSIS Method to Image Segmentation

Neutrosophic set (NS) is a formal framework proposed recently. NS can not only describe the incomplete information in the decision-making system but also depict the uncertainty and inconsistency, so it has applied successfully in several fields such as risk assessment, fuzzy decision and image segmentation. In this paper, a new neutrosophic approach based on TOPSIS method, which can make full use of NS information, is proposed to separate the graphics. Firstly, the image is transformed into the NS domain. Then, two operations, a modified alpha-mean and the beta-enhancement operations are used to enhance image edges and to reduce uncertainty. At last, the segmentation is achieved by the TOPSIS method and the modified fuzzy c-means (FCM). Simulated images and real images are illustrated that the proposed method is more effective and accurate in image segmentation

Pregnancy outcomes following natural conception and assisted reproduction treatment in women who received COVID-19 vaccination prior to conception: a population-based cohort study in China

IntroductionThe coronavirus disease-2019 (COVID-19) pandemic has swept across the world and continues to exert serious adverse effects on vulnerable populations, including pregnant women and neonates. The vaccines available at present were designed to prevent infection from COVID-19 strains and control viral spread. Although the incidence of pregnancy cycle outcomes are not likely to increase patients vaccinated prior to pregnancy compared with unvaccinated patients based on our knowledge of vaccination safety, there is no specific evidence to support this hypothesis. Therefore, the current study aimed to investigate the association between maternal vaccination prior to conception and pregnancy outcomes.MethodsWe retrospectively analyzed 2,614 women who received prenatal care and delivered in the Obstetrical Department of The First Affiliated Hospital of Anhui Medical University between February 2022 and November 2022. Of the 1,380 eligible pregnant women, 899 women who had received preconception vaccination were assigned to a vaccine group and 481 women who were not vaccinated were control group. Of the enrolled patients, 291 women received fertility treatment (141 vaccinated women, 150 unvaccinated women). The primary outcomes were pregnancy complications (hypothyroidism, gestational diabetes mellitus, pregnancy-induced hypertension, polyhydramnios, oligohydramnios, premature rupture of membranes and postpartum hemorrhage), obstetric outcomes (preterm birth rate, cesarean section rate) and neonatal outcomes (birth-weight, body length, low-birth-weight rate, rate of congenital defects, neonatal mortality and admission to the neonatal intensive care unit).ResultsThere was no significant difference in the incidence of complications during pregnancy and delivery when compared between the vaccine group and control group in either univariate- or multivariate-models. The type of vaccine was not associated with the odds of adverse pregnancy outcome. Among the women with infertility treatment, the vaccinated group and the unvaccinated group had similar pregnancy outcomes.ConclusionWomen who received COVID-19 vaccination prior to conception had similar maternal and neonatal outcomes as women who were unvaccinated. Our findings indicate that COVID-19 vaccinations can be safely administered prior to pregnancy in women who are planning pregnancy or assisted reproductive treatment. During new waves of COVID-19 infection, women who are planning pregnancy should be vaccinated as soon as possible to avoid subsequent infections

VHF data transmission experiments using MBC equipment conducted during the period from JARE-43 to JARE-45

In order to study the ability of meteor burst communications (MBC) as a new medium of data collection networks in Antarctica, we have performed a series of VHF data transmission experiments. In the experiment during the period of JARE-43 (the 43rd Japanese Antarctic Research Expedition), a remote station at Zhongshan Station sent data packets to a master station at Syowa Station using a commercial MBC system. Together with meteor burst propagations, non-meteoric propagations were frequently observed during local nighttime. We found that they worked effectively for packet transmissions and greatly increased the data throughput. Overall data throughput obtained by this experiment was 0.63bps. In JARE-44, we added another remote station at Dome Fuji Station. Since the transmitted power from the master unit was split into two directions, data throughput from Zhongshan Station was reduced to 0.36bps. That from Dome Fuji Station was only 0.13bps. For the experiment in JARE-45, we replaced the commercial MBC system with a RANDOM (RAdio Network for Data Over Meteor) system developed by the authors. The experiment is being conducted between Syowa and Zhongshan Stations. The estimated data throughput during the period from April 1st, 2004 to August 31st, 2004 was 2.9bps