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The term disaster resilience has not been well defined. The purpose of this article is to scrutinize the concept of disaster resilience in rescue workers.
A systematic search was conducted of the PsychInfo, PubMed, ISI Web of Science, MEDLINE, CINAHL, Embase, and Scopus databases using the key terms. The framework from Walker and Avant was used to analyze the concept of disaster resilience.
A total of 26 papers was included in this analysis. The attributes of disaster resilience have been identified from the literature as including personality, perceived control, self-efficacy, coping strategies, and social support. The antecedents of disaster resilience are disastrous events and preparedness for disaster. The consequences of disaster resilience are psychological well-being, posttraumatic growth, and enhanced work engagement.
This concept analysis presents a definition of the concept of disaster resilience that could contribute to the development of a standardized screening or assessment tool and tailored training programs to strengthen disaster resilience among those who are willing to be deployed to engage in disaster rescue work and those who have been involved in such work.
With the increasing demand for a personalized product and rapid market response, many companies expect to explore online user-generated content (UGC) for intelligent customer hearing and product redesign strategy. UGC has the advantages of being more unbiased than traditional interviews, yielding in-time response, and widely accessible with a sheer volume. From online resources, customers’ preferences toward various aspects of the product can be exploited by promising sentiment analysis methods. However, due to the complexity of language, state-of-the-art sentiment analysis methods are still not accurate for practice use in product redesign. To tackle this problem, we propose an integrated customer hearing and product redesign system, which combines the robust use of sentiment analysis for customer hearing and coordinated redesign mechanisms. Ontology and expert knowledges are involved to promote the accuracy. Specifically, a fuzzy product ontology that contains domain knowledges is first learned in a semi-supervised way. Then, UGC is exploited with a novel ontology-based fine-grained sentiment analysis approach. Extracted customer preference statistics are transformed into multilevels, for the automatic establishment of opportunity landscapes and house of quality table. Besides, customer preference statistics are interactively visualized, through which representative customer feedbacks are concurrently generated. Through a case study of smartphone, the effectiveness of the proposed system is validated, and applicable redesign strategies for a case product are provided. With this system, information including customer preferences, user experiences, using habits and conditions can be exploited together for reliable product redesign strategy elicitation.
For torpedo electronic components tested by functional verification, there are characteristics of a few samples and few failures. During service life, it is difficult to analyse and predict the changes in reliability. At present, management's observation of quality is mainly base on failure data, and it is difficult to make predictions about the moments without failure in service life. In this paper, according to the failure data, we consider such factors as performance degradation and detection and use the model of instantaneous failure rate to evaluate the reliability of the detection moments periodically, and predict the reliability of stages through the results of detection moments. The method proposed in this paper, on the one hand, considers the service experience, and on the other combines the detection data, to make the final evaluation result more credible. In addition, this paper predicts the changing trend of reliability between adjacent detection moments, which can provide a useful reference for quality management work.
To evaluate the management mode for the prevention and control of coronavirus 2019 (COVID-19) transmission utilized at a general hospital in Shenzhen, China, with the aim to maintain the normal operation of the hospital.
From January 2, 2020 to April 23, 2020, Hong Kong–Shenzhen Hospital, a tertiary hospital in Shenzhen, has operated a special response protocol named comprehensive pandemic prevention and control model, which mainly includes six aspects: 1) human resource management; 2) equipment management; 3) logistics management; 4) cleaning, disinfection and process reengineering; 5) environment layout; 6) and training and assessment. The detail of every aspect was described and its efficiency was evaluated.
A total of 198,802 patients were received. Of those, 10,821 were hospitalized; 26,767 were received by the emergency department and fever clinics; 288 patients were admitted for observation with fever; and 324 were admitted as suspected cases for isolation. Under the protocol of comprehensive pandemic prevention and control model, no case of hospital-acquired infection with COVID-19 occurred among the inpatients or staff.
The present comprehensive response model may be useful in large public health emergencies to ensure appropriate management and protect the health and life of individuals.
Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.
The particle–particle (PP) model has a growing number of applications in plasma simulations, because of its high accuracy of solving Coulomb collisions. One of the main issues restricting the practical use of the PP model is its large computational cost, which is now becoming acceptable thanks to state-of-art parallel computing techniques. Another issue is the singularity that occurs when two particles are too close. The most effective approach of avoiding the singularity would be to simulate particles with only like charges plus a neutralizing field, such that the short-range collisions are equivalent to those of using unlike charges. In this paper, we introduce a way of adding the neutralizing field by using the analytical solution of the electric field in the domain filled with uniformly distributed charges, for applications with homogeneous and quasi-neutral plasmas under a reflective boundary condition. Two most common Cartesian domain geometries, cubic and spherical, are considered. The model is verified by comparing simulation results with an analytical solution of an electron–ion temperature relaxation problem, and a corresponding simulation using unlike charges. In addition, it is found that a PP simulation using like charges can achieve a significant speed-up of 100 compared with a corresponding simulation using unlike charges, due to the capability of using larger time steps while maintaining the same energy conservation.
We propose a novel Fabry–Pérot (FP) antenna consisting of a checkered polarization-conversion metasurface (PCM), corner-cut square patch antennas, and sandwiched compounds. The proposed antenna achieves low radar-cross-section (RCS), high gain, and wideband circular polarization (CP). The corner-cut square patch antennas facilitate high reflectivity, satisfactory transmission magnitude, and the desired phase difference. An embedded metal between two rings of substrate contributes to reducing cross-polarization, improving transmission efficiency, enhancing bandwidth, and reducing RCS. Following simulations, we fabricated a prototype of the proposed antenna and tested its performance. Measurements from the simulation and prototype tests were similar within a reasonable margin of error. Compared with alternative antennas, our proposed FP antenna offers high gain, wideband CP, low cost, a low RCS, and a lower profile.
Non-alcoholic fatty liver disease (NAFLD) was defined in 1980 and has the same histological characteristics as alcoholic liver disease except for alcohol consumption (1). After 40 years, the understanding of this disease is still imperfect. Without specific drugs available for treatment, the number of patients with NAFLD is increasing rapidly, and NAFLD currently affects more than one-quarter of the global population. The causes of NAFLD are mostly due to a sedentary lifestyle and excessive energy intake of fat and sugar (2). To ameliorate or avoid NAFLD, people commonly replace high-fat foods with high-carbohydrate foods (especially starchy carbohydrates) as a way to reduce caloric intake and reach satiety. However, studies that concentrate on the effect of carbohydrate intake on liver metabolism in patients with NAFLD are fewer, which is much less than the studies on fat intake. Besides, most of these studies are not systematic, which has made identification of the mechanism difficult. In this review, we collected and analysed data from studies on human and animal models, surprisingly, we found that carbohydrates and liver steatosis could be linked by inflammation. This review not only describes the effects of carbohydrates on NAFLD and body lipid metabolism but also analyses and predicts possible molecular pathways of carbohydrates on liver lipid synthesis that involve inflammation. Furthermore, the limitations of recent research and possible targets for regulating inflammation and lipogenesis are discussed. This review describes the effects of starchy carbohydrates, a nutrient signal, on NAFLD from the perspective of inflammation.
Video monitoring is an important means of ship traffic supervision. In practice, regulators often need to use an electronic chart platform to determine basic information concerning ships passing through a video feed. To enrich the information in the surveillance video and to effectively use multimodal maritime data, this paper proposes a novel ship multi-object tracking technology based on improved single shot multibox detector (SSD) and DeepSORT algorithms. In addition, a night contrast enhancement algorithm is used to enhance the ship identification performance in night scenes and a multimodal data fusion algorithm is used to incorporate the ship automatic identification system (AIS) information into the video display. The experimental results indicate that the ship information tracking accuracies in the day and night scenes are 78⋅2% and 70⋅4%, respectively. Our method can effectively help regulators to quickly obtain ship information from a video feed and improve the supervision of a waterway.
We present extensions to ChainQueen, an open source, fully differentiable material point method simulator for soft robotics. Previous work established ChainQueen as a powerful tool for inference, control, and co-design for soft robotics. We detail enhancements to ChainQueen, allowing for more efficient simulation and optimization and expressive co-optimization over material properties and geometric parameters. We package our simulator extensions in an easy-to-use, modular application programming interface (API) with predefined observation models, controllers, actuators, optimizers, and geometric processing tools, making it simple to prototype complex experiments in 50 lines or fewer. We demonstrate the power of our simulator extensions in over nine simulated experiments.
The presence of a soil seedbank facilitates the persistence of annual weed species in arable fields. Soil weed seedbank is replenished by many sources, but the largest one is the seeds produced by uncontrolled late-season weed escapes. The estimation of weed seed production potential from late-season escapes may allow farmers to make appropriate management decisions to minimize seedbank replenishment. The objective of this research was to evaluate the feasibility of using unmanned aerial vehicle–based RGB and multispectral imagery for estimating seed rain potential in late-season weed escapes in crop fields. Three case studies were used to capture images of weed escapes before crop harvest: common waterhemp [Amaranthus tuberculatus (Moq.) Sauer] in soybean [Glycine max (L.) Merr.], Palmer amaranth [Amaranthus palmeri (S.) Watson] in cotton (Gossypium hirsutum L.), and johnsongrass [Sorghum halepense (L.) Pers.] in soybean. Randomly selected quadrats with different density gradients of weed escapes were sampled at the time of crop maturity. High-resolution RGB and multispectral images of the experimental area were collected using drones immediately before ground sample collection. Normalized difference vegetation index (NDVI), excess green index (ExG), and canopy volume estimates derived from canopy height models were used to obtain weed biological measurements (biomass and seed production). Among the indices investigated, NDVI and ExG had very strong correlations (0.71 to 0.97) with weed biomass. No specific remote sensing variable was ideal across the three cases examined here, suggesting that a generalized remote sensing approach may not offer robust estimations and case-specific applications are imperative. Nonetheless, drone imagery is a powerful tool for estimating seed production from uncontrolled weed escapes and assisting with management decision making.
In this paper, a special 6-PUS parallel manipulator (PM) is utilized as a shaking table. Unlike the existing results about 6-PUS PMs, we make the actuator direction collinear with the linkage direction at neutral position. With respect to the application background, a further analysis of the special PM is carried out from the perspective of motion/force transmissibility, natural frequency and acceleration capability. Specially, the complete dynamics model is established based on the Kane method. Then, generalized transmission indices based on the screw theory are utilized to reflect its motion ability, and a model of natural frequency is proposed with the axial stiffness of linkages considered. Finally, the effect of the angle between the actuator direction and the linkage direction α on various performances is analyzed, and other results are included to illustrate its feasibility and usability.
The coexistence of underweight (UW) and overweight (OW)/obese (OB) at the population level is known to affect iron deficiency (ID) anaemia (IDA), but how the weight status affects erythropoiesis during pregnancy is less clear at a population scale. This study investigated associations between the pre-pregnancy BMI (pBMI) and erythropoiesis-related nutritional deficiencies.
Anthropometry, blood biochemistry and 24-h dietary recall data were collected during prenatal care visits. The weight status was defined based on the pBMI. Mild nutrition deficiency-related erythropoiesis was defined if individuals had an ID, folate depletion or a vitamin B12 deficiency.
The Nationwide Nutrition and Health Survey in Taiwan (Pregnant NAHSIT 2017–2019).
We included 1456 women aged 20 to 45 years with singleton pregnancies.
Among these pregnant women, 9·6 % were UW, and 29·2 % were either OW (15·8 %) or OB (13·4 %). A U-shaped association between the pBMI and IDA was observed, with decreased odds (OR; 95 % CI) for OW subjects (0·6; 95 % CI (0·4, 0·9)) but increased odds for UW (1·2; 95 % CI (0·8, 2·0)) and OB subjects (1·2; 95 % CI (0·8, 1·8)). The pBMI was positively correlated with the prevalence of a mild nutritional deficiency. Compared to normal weight, OB pregnant women had 3·4-fold (3·4; 95 % CI (1·4, 8·1)) higher odds for multiple mild nutritional deficiencies, while UW individuals had lowest odds (0·3; 95 % CI (0·1, 1·2)). A dietary analysis showed negative relationships of pBMI with energy, carbohydrates, protein, Fe and folate intakes, but positive relationship with fat intakes.
The pre-pregnancy weight status can possibly serve as a good nutritional screening tool for preventing IDA during pregnancy.
In nature, competing species often achieve coexistence through niche differentiation. We examined this phenomenon for Pachycrepoideus vindemmiae and Spalangia endius (Hymenoptera: Pteromalidae), two species of pupal parasitoids that are considered biological control agents of house fly, Musca domestica (Diptera: Muscidae). We examined the ability of each species, alone and in combination, to locate host pupae buried at different depths (0, 1, 2, 4, and 6 cm) in three types of substrate (sand, dry wheat bran, and spent fly diet). We then evaluated the competitiveness of each species by allowing first one species, then the other species, to parasitise host individuals within time periods ranging from less than 2 hours to 96 hours of each other. Spalangia endius exhibited greater ability than did P. vindemmiae to locate host pupae buried at depths below one centimetre. Conversely, P. vindemmiae exhibited a greater competitive ability, being more likely to emerge from pupae co-parasitised by S. endius, regardless of oviposition interval or sequence. Our findings suggest that these two parasitoid species coexist through niche differentiation. Our findings also indicate that to increase the effectiveness of biological control, the environmental conditions and risk of interspecific competition should be considered when selecting parasitoid species for release.
Efficiently predicting the flow field and load in aerodynamic shape optimisation remains a highly challenging and relevant task. Deep learning methods have been of particular interest for such problems, due to their success in solving inverse problems in other fields. In the present study, U-net-based deep neural network (DNN) models are trained with high-fidelity datasets to infer flow fields, and then employed as surrogate models to carry out the shape optimisation problem, i.e. to find a minimal drag profile with a fixed cross-sectional area subjected to a two-dimensional steady laminar flow. A level-set method as well as Bézier curve method are used to parameterise the shape, while trained neural networks in conjunction with automatic differentiation are utilised to calculate the gradient flow in the optimisation framework. The optimised shapes and drag force values calculated from the flow fields predicted by the DNN models agree well with reference data obtained via a Navier–Stokes solver and from the literature, which demonstrates that the DNN models are capable not only of predicting flow field but also yielding satisfactory aerodynamic forces. This is particularly promising as the DNNs were not specifically trained to infer aerodynamic forces. In conjunction with a fast runtime, the DNN-based optimisation framework shows promise for general aerodynamic design problems.
Flavonoids are a group of phenolic secondary metabolites in plants that have important physiological, ecological and economic value. In this study, using the desert plant Artemisia sphaerocephala Krasch. as the sample material, the content and components of the total flavonoids in its seeds at seven different developmental stages were determined. In addition, the genes involved in flavonoid metabolism were identified by full-length transcriptome sequencing (third-generation sequencing technology based on PacBio RS II). Their expression levels were analysed by RNA-seq short reading sequencing, to reveal the patterns and regulation mechanisms of flavonoid accumulation during seed development. The key results were as follows: the content of total flavonoids in mature seeds was 15.05 mg g−1, including five subclasses: flavonols, chalcones, flavones, flavanones and proanthocyanidins, among which flavonols accounted for 45.78%. The period of rapid accumulation of flavonoids was 40–70 d following anthesis. The high expression of phenylalanine ammonia-lyase (PAL), 4-coumarate-CoA ligase (4CL) and UDP-glucose:flavonoids 3-o-glucosyltransferase (UF3GT) promoted the accumulation of total flavonoids, while the high expression of flavonoids 3′-hydroxylase (F3′H) and flavonols synthase (FLS) made flavanols the main component. Transcription factors such as the MYB-bHLH-WDR (MBW) complex and Selenium-binding protein (SBP) directly regulated the structural genes of flavonoid metabolism, while C2H2-type zinc finger (C2H2), Zinc-finger transcription factor (GATA), Dehydration-responsive element binding (DREB), Global Transcription factor Group E protein (GTE), Trihelix DNA-binding factors (Trihelix) and Phytochrome-interacting factor (PIF) indirectly promoted the synthesis of flavonoids through hormones such as brassinoidsteroids (BRs) and abscisic acid (ABA). These results provided valuable resources for the application of related genes in genetics and breeding.
To present the clinical characteristics and dynamic changes in laboratory parameters of the COVID-19 in Guangzhou, and explore the probable early warning indicators of disease progressing.
We enrolled all the patients diagnosed as COVID-19 in the Guangzhou No. 8 People’s Hospital. The patients’ demographic, and epidemiologic data were collected, including chief complaints, lab results and imaging examination.
The characteristics of the patients in Guangzhou are different from that in Wuhan. They were younger in age, female dominated, not commonly combined with other disease. 75% of patients suffered fever on admission, followed by cough occurring in 62% patients. By comparing the mild/normal and severe/critical patients, male, aged, combined with hypertension, abnormal in blood routine result, raised creatine kinase, glutamic oxaloacetic transaminase, lactate dehydrogenase, CRP, procalcitonin, D-dimer, fibrinogen, APTT, and positive in proteinuria can be candidate of early warning indicators to severe disease.
The patients in outside epidemic areas showed different characteristics from that in Wuhan. The abnormal laboratory parameters were markedly changed in 4 weeks after admission, and also shown different between the mild and severe patients. The highest specificity and sensitivity potential early warning indicators of severe disease need more evidence to confirm.