| 1. |
- Hu, Yuning, et al.
(författare)
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Cooking methods affect the intake of per- and polyfluoroalkyl substances (PFASs) from grass carp
- 2020
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Ingår i: Ecotoxicology and Environmental Safety. - : Academia Press. - 0147-6513 .- 1090-2414. ; 203
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Tidskriftsartikel (refereegranskat)abstract
- Consumption of fish is one of the predominant sources of human exposure to per- and polyfluoroalkyl substances (PFASs). In this study, the effect of various cooking methods (boiling, steaming, grilling and frying) on the levels of PFASs in fish muscle and the intake of PFASs was explored by using grass carp collected from Tangxun Lake, Wuhan, China. Perfluorooctane sulfonate (PFOS) was the predominant PFASs in raw fish fillets, with the concentrations ranging from 59.6 to 136 ng/g ww, followed by perfluorobutane sulfonate (PFBS) (7.73-51.9 ng/g ww). The concentrations of long-chain PFASs in fish increased after cooking, while those of short-chain PFASs decreased. The amounts of PFASs in the cooked fish fillets decreased except PFOS. Short-chain PFASs, including PFBS and perfluoroheptanoic acid (PFHpA), were dominant in cooking juice. The highest amounts of PFBS in the juices were observed after boiling and frying, even higher than those in cooked fish fillets, suggesting that the release of short-chain PFASs to the cooking juices could not be neglected. Based on these results, the intake of short-chain PFASs amount through cooked fish fillets slightly decreased, but the intake of PFOS amount increased. However, consumption of cooking juice (fish soup) could increase the exposure risk of PFBS. Comprehensively considering the increase of PFOS and decrease of total PFASs, boiling may be the relatively better method to cook fish. As PFASs are ubiquitous and inevitable in aquatic food, it is thus important to choose appropriate cooking processes and dietary habits for reducing the intake of different PFASs from fish.
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| 2. |
- Joshi, Peter K, et al.
(författare)
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Directional dominance on stature and cognition in diverse human populations
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 523:7561, s. 459-462
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Tidskriftsartikel (refereegranskat)abstract
- Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
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| 3. |
- Liu, Lizheng, et al.
(författare)
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A FPGA-based Hardware Accelerator for Bayesian Confidence Propagation Neural Network
- 2020
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Ingår i: 2020 IEEE Nordic Circuits and Systems Conference, NORCAS 2020 - Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- The Bayesian Confidence Propagation Neural Network (BCPNN) has been applied in higher level of cognitive intelligence (e.g. working memory, associative memory). However, in the spike-based version of this learning rule the pre-, postsynaptic and coincident activity is traced in three low-passfiltering stages, the calculation processes of weight update are very computationally intensive. In this paper, a hardware architecture of the updating process for lazy update mode is proposed for updating 8 local synaptic state variables. The parallelism by decomposing the calculation steps of formulas based on the inherent data dependencies is optimized. The FPGA-based hardware accelerator of BCPNN is designed and implemented. The experimental results show the updating process on FPGA can be accomplished within 110 ns with a clock frequency of 200 MHz, the updating speed is greatly enhanced compared with the CPU test. The trade-off between performance, accuracy and resources on dedicated hardware is evaluated, and the impact of the module reuse on resource consumption and computing performance is evaluated.
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| 4. |
- Qu, Xueqi, et al.
(författare)
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Socio-emotional challenges and development of children left behind by migrant mothers.
- 2020
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Ingår i: Journal of global health. - : International Global Health Society. - 2047-2986 .- 2047-2978. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- With great economic development and rapid urbanization in China, left-behind children whose parents migrate to big cities for job has become a large special population which requires more attention. The present study aims to explore the specific influence of migrant mothers on early child development, especially on social-emotional problems.The data of this study was obtained from a cross-sectional study in 8 counties of central and western rural China. Development status of 1880 children aged <60 months were assessed by Ages & Stages Questionnaire-Chinese Edition (ASQ) and the Ages and Stages Questionnaire: Social Emotional-Chinese Edition (ASQ: SE). Multivariate logistic regressions were used to analyze the association between being left behand by migrant mothers and developmental problems in various domains, while adjusting socio-demographic, socio-economic and perinatal co-variates, and effect modification analysis were conducted to explore the effect of age, gender and birth order.Children left behind by migrant mothers were more likely to have overall suspected developmental delay (odds ratio (OR) = 1.24, 95% confidence interval (CI) = 1.13-1.35), developmental delay in personal social domain (OR = 1.55, 95% CI = 1.17-2.04) and socio-emotional delay compared with those living with their own mothers (OR = 1.49, 95% CI = 1.11-2.00) after adjusting for potential confounders. Additionally, girls increased the odds of social-emotional problems among children being left behind by migrating mother (P for interaction = 0.037).The study concluded that children left behind by migrant mothers were more likely to have suspected developmental delay compared with their peers living with mothers, especially on social emotional development. Future intervention is needed for this special population and should pay more attention to girls.
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| 5. |
- Wang, Deyu, et al.
(författare)
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FPGA-Based HPC for Associative Memory System
- 2024
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Ingår i: 29TH ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE, ASP-DAC 2024. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 52-57
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Konferensbidrag (refereegranskat)abstract
- Associative memory plays a crucial role in the cognitive capabilities of the human brain. The Bayesian Confidence Propagation Neural Network (BCPNN) is a cortex model capable of emulating brain-like cognitive capabilities, particularly associative memory. However, the existing GPU-based approach for BCPNN simulations faces challenges in terms of time overhead and power efficiency. In this paper, we propose a novel FPGA-based high performance computing (HPC) design for the BCPNN-based associative memory system. Our design endeavors to maximize the spatial and timing utilization of FPGA while adhering to the constraints of the available hardware resources. By incorporating optimization techniques including shared parallel computing units, hybrid-precision computing for a hybrid update mechanism, and the globally asynchronous and locally synchronous (GALS) strategy, we achieve a maximum network size of 150x10 and a peak working frequency of 100 MHz for the BCPNN-based associative memory system on the Xilinx Alveo U200 Card. The tradeoff between performance and hardware overhead of the design is explored and evaluated. Compared with the GPU counterpart, the FPGA-based implementation demonstrates significant improvements in both performance and energy efficiency, achieving a maximum latency reduction of 33.25x, and a power reduction of over 6.9x, all while maintaining the same network configuration.
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| 6. |
- Wang, Deyu, et al.
(författare)
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Memristor-Based In-Circuit Computation for Trace-Based STDP
- 2022
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Ingår i: 2022 Ieee International Conference On Artificial Intelligence Circuits And Systems (Aicas 2022). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Recently, memristors have been widely used to implement Spiking Neural Networks (SNNs), which is promising in edge computing scenarios. However, most memristor-based SNN implementations adopt simplified spike-timing-dependent plasticity (STDP) for the online learning process. It is challenging for memristor-based implementations to support the trace-based STDP learning rules that have been widely used in neuromorphic applications. This paper proposed a versatile memristor-based architecture to implement the synaptic-level trace-based STDP learning rules. Especially, the similarity between synaptic trace dynamics and the memristor nonlinearity is explored and exploited to emulate the trace variables of trace-based STDP. As two typical trace-based STDP learning rules, the pairwise STDP and the triplet STDP, are simulated on two typical nonlinear bipolar memristor devices. The simulation results show that the behavior of physical memristor devices can be well estimated (below 6% in terms of the relative root-mean-square error), and the memristor-based in-circuit computation for trace-based STDP learning rules can achieve a high correlation coefficient over 98%.
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| 7. |
- Zhou, Hong, et al.
(författare)
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Relationship between moderate to late preterm, diet types and developmental delay in less-developed rural China.
- 2022
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Ingår i: Nutritional neuroscience. - : Informa UK Limited. - 1476-8305 .- 1028-415X. ; 25:1, s. 70-79
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Forskningsöversikt (refereegranskat)abstract
- Aim: To measure the development of moderate to late preterm children by Ages and Stages Questionnaires (ASQ) and explore the relationship between moderate to late preterm, diet types and development delay in less-developed rural China.Methods: Data were collected from a cross-sectional community-based survey, which recruited 1748 children aged 1-59 months in eight counties of China. Caregivers of these children completed the Chinese version of ASQ-3 (ASQ-C) while physical examination and questionnaires on socio-demographic characteristics were conducted. Multivariate logistic regressions were used to analyze the association between moderate to late preterm and suspected developmental delay, as well as the association between diet types and suspected developmental delay. Consumption of certain food types was compared between moderate to late preterm and full-term children.Results: The prevalence of suspected overall developmental delay was 31.3% in the moderate to the late preterm group, compared with 21.6% in the full-term group. Moderate to late preterm birth was not associated with total suspected developmental delay and developmental delay in all the domains of ASQ, except for fine motor (OR = 2.43 95% C.I.: 1.04-5.56). The intake of vegetables and fruits had a protective influence on developmental delay in fine motor function, and moderate to late preterm children had lower relative consumption of fruits and vegetables than full-term children.Conclusion: Moderate to late preterm children in rural China showed an increased likelihood of developmental delay in fine motor function. Future interventions to improve the intake of vegetables and fruits in moderate to late preterm children are recommended.
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| 8. |
- Eivazi, Hamidreza, et al.
(författare)
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Physics-informed deep-learning applications to experimental fluid mechanics
- 2024
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Ingår i: Measurement science and technology. - : IOP Publishing. - 0957-0233 .- 1361-6501. ; 35:7
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Tidskriftsartikel (refereegranskat)abstract
- High-resolution reconstruction of flow-field data from low-resolution and noisy measurements is of interest due to the prevalence of such problems in experimental fluid mechanics, where the measurement data are in general sparse, incomplete and noisy. Deep-learning approaches have been shown suitable for such super-resolution tasks. However, a high number of high-resolution examples is needed, which may not be available for many cases. Moreover, the obtained predictions may lack in complying with the physical principles, e.g. mass and momentum conservation. Physics-informed deep learning provides frameworks for integrating data and physical laws for learning. In this study, we apply physics-informed neural networks (PINNs) for super-resolution of flow-field data both in time and space from a limited set of noisy measurements without having any high-resolution reference data. Our objective is to obtain a continuous solution of the problem, providing a physically-consistent prediction at any point in the solution domain. We demonstrate the applicability of PINNs for the super-resolution of flow-field data in time and space through three canonical cases: Burgers' equation, two-dimensional vortex shedding behind a circular cylinder and the minimal turbulent channel flow. The robustness of the models is also investigated by adding synthetic Gaussian noise. Furthermore, we show the capabilities of PINNs to improve the resolution and reduce the noise in a real experimental dataset consisting of hot-wire-anemometry measurements. Our results show the adequate capabilities of PINNs in the context of data augmentation for experiments in fluid mechanics.
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| 9. |
- Jiang, Yuning, 1993-, et al.
(författare)
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A Semantic Framework With Humans in the Loop for Vulnerability-Assessment in Cyber-Physical Production Systems
- 2020
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Ingår i: Risks and Security of Internet and Systems. - Cham : Springer. - 9783030415679 - 9783030415686 ; , s. 128-143
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Konferensbidrag (refereegranskat)abstract
- Criticalmanufacturingprocessesinsmartnetworkedsystems such as Cyber-Physical Production Systems (CPPSs) typically require guaranteed quality-of-service performances, which is supported by cyber- security management. Currently, most existing vulnerability-assessment techniques mostly rely on only the security department due to limited communication between di↵erent working groups. This poses a limitation to the security management of CPPSs, as malicious operations may use new exploits that occur between successive analysis milestones or across departmental managerial boundaries. Thus, it is important to study and analyse CPPS networks’ security, in terms of vulnerability analysis that accounts for humans in the production process loop, to prevent potential threats to infiltrate through cross-layer gaps and to reduce the magnitude of their impact. We propose a semantic framework that supports the col- laboration between di↵erent actors in the production process, to improve situation awareness for cyberthreats prevention. Stakeholders with dif- ferent expertise are contributing to vulnerability assessment, which can be further combined with attack-scenario analysis to provide more prac- tical analysis. In doing so, we show through a case study evaluation how our proposed framework leverages crucial relationships between vulner- abilities, threats and attacks, in order to narrow further the risk-window induced by discoverable vulnerabilities.
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| 10. |
- Jiang, Yuning, 1993-, et al.
(författare)
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Leveraging Digital Twin Technology for Enhanced Cybersecurity in Cyber–Physical Production Systems
- 2024
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Ingår i: Future Internet. - : MDPI. - 1999-5903. ; 16:4
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Tidskriftsartikel (refereegranskat)abstract
- The convergence of cyber and physical systems through cyber–physical systems (CPSs) has been integrated into cyber–physical production systems (CPPSs), leading to a paradigm shift toward intelligent manufacturing. Despite the transformative benefits that CPPS provides, its increased connectivity exposes manufacturers to cyber-attacks through exploitable vulnerabilities. This paper presents a novel approach to CPPS security protection by leveraging digital twin (DT) technology to develop a comprehensive security model. This model enhances asset visibility and supports prioritization in mitigating vulnerable components through DT-based virtual tuning, providing quantitative assessment results for effective mitigation. Our proposed DT security model also serves as an advanced simulation environment, facilitating the evaluation of CPPS vulnerabilities across diverse attack scenarios without disrupting physical operations. The practicality and effectiveness of our approach are illustrated through its application in a human–robot collaborative assembly system, demonstrating the potential of DT technology.
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