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This paper introduces the concept of vessel train, a new mode in maritime transport offering both environmental and economic advantages. The study provides a framework for analyzing the economic feasibility of vessel train in ocean shipping, focusing on four different scenarios to evaluate its impact on navigation speed and productivity for both round-trip and year-long operations. Using the container ship route from Yangshan Port to the Port of Piraeus as a case study, the research compares vessel train with traditional shipping methods by categorizing shipping costs. It also includes a sensitivity analysis considering factors like route length, frictional resistance reduction, and variations in the container freight index, fuel prices, and carbon tax rates. The findings indicate that vessel train can reduce transportation costs and fuel emissions. The paper concludes that vessel train could significantly contribute to a competitive and sustainable future in shipping.
The purpose of this study is to investigate whether spatial-temporal dependence models can improve the prediction performance of short-term freight volume forecasts in inland ports. To evaluate the effectiveness of spatial-temporal dependence forecasting, the basic time series forecasting models for use in our comparison were first built based on an autoregression integrated moving average model (ARIMA), a back-propagation neural network (BPNN), and support vector regression (SVR). Subsequently, combining a gradient boosting decision tree (GBDT) with SVR, an SVR- GBDT model for spatial-temporal dependence forecast was constructed. The SVR model was only used to build a spatial-temporal dependence forecasting model, which does not distinguish spatial and temporal information but instead takes them as data features. Taking inland ports in the Yangtze River as an example, the results indicated that the ports’ weekly freight volumes had a higher autocorrelation with the previous 1–3 weeks, and the Pearson correlation values of the ports’ weekly cargo volume were mainly located in the interval (0.2–0.5). In addition, the weekly freight volumes of the inland ports were higher depending on their past data, and the spatial-temporal dependence model improved the performance of the weekly freight volume forecasts for the inland river. This study may help to (1) reveal the significance of spatial correlation factors in ports’ short-term freight volume predictions, (2) develop prediction models for inland ports, and (3) improve the planning and operation of port entities.
The identification of the ship that contact with the buoy can provide evidence for accident accountability. To this aim, the paper develops a probabilistic analytics method to evaluate the ship-buoy contact risk for the striking ship identification at the coastal areas by combining buoy domain and bounding box models. The method makes use of Automatic Identification System (AIS) data and navigational buoy data. Firstly, an AIS-based probabilistic buoy domain model is adopted for the determination of the safety boundary of the buoy to detect potential striking ships with a higher contact probability. Then, the bounding boxes of the navigational buoy and the detected potential striking ships are developed to detect the real striking ship by analyzing the interaction be-tween the ship bounding box and the buoy bounding box. Finally, the probabilistic analytics method is demonstrated in the South China Sea and validated using historical ship-buoy contact records. Results indicated that, from a probabilistic perspective, the safety buoy domain (critical boundary) existed with diverse distances dynamically. The proposed method could assist the identification of striking ships while aiding the definition of the safety buoy domain for preventing ship-buoy contacts. As a result, it has the potential to support the development of ship-buoy contact risk management and assist surveillance operators and master on board by improving their cognitive abilities in dangerous traffic scenarios.
Ready-to-use therapeutic foods (RUTFs) are a key component of a life-saving treatment for young children who present with uncomplicated severe acute malnutrition in resource limited settings. Increasing recognition of the role of balanced dietary omega-6 and omega-3 polyunsaturated fatty acids (PUFA) in neurocognitive and immune development led two independent groups to evaluate RUTFs. Jones et al. (BMC Med 13:93, 2015), in a study in BMC Medicine, and Hsieh et al. (J Pediatr Gastroenterol Nutr 2015), in a study in the Journal of Pediatric Gastroenterology and Nutrition, reformulated RUTFs with altered PUFA content and looked at the effects on circulating omega-3 docosahexaenoic acid (DHA) status as a measure of overall omega-3 status. Supplemental oral administration of omega-3 DHA or reduction of RUTF omega-6 linoleic acid using high oleic peanuts improved DHA status, whereas increasing omega-3 alpha-linolenic acid in RUTF did not. The results of these two small studies are consistent with well-established effects in animal studies and highlight the need for basic and operational research to improve fat composition in support of omega-3-specific development in young children as RUTF use expands.
The grouted sleeve splice is a competitive splice in the prefabricated structure that plays a key role in ensuring the stability of the whole structure. Despite the large amounts of experiments performed, its force mechanism has rarely been explored. In this study, a novel method was developed to calculate the constitutive model of grouted sleeve splice, and a comprehensive understanding of the force mechanism was analyzed. Tensile tests of 24 specimens were conducted to explore the mechanical properties of the grouted sleeve splice. The results showed that the anchorage length of rebar with ultra-high-performance grout material can be shorter than that recommended in design standards. The anchorage length and eccentricity of rebars have a significant impact on the mechanical performance of the grouted sleeve splice, which deserves special attention in the structure design and construction. The non-anchorage section of the grouted sleeve splice offers little contribution to the bearing capacity. Based on the concept of equivalent section elastic moduli, a theoretical calculation method was established to reveal the stress–strain relationship of the grouted sleeve splice. The errors between the theoretical model and test results vary from 0.20% to 18.90%. This study provides new perspectives for theoretical research on the mechanism of grouted sleeve splice.
The thesis studies slag and iron flow in the blast furnace hearth and the complex hearth drainage phenomena by both experiments and numerical simulation. It also presents a mathematical model by which the asymptotic state of the hearth lining can be estimated. The main points of the work were to undertake a quantitative analysis to shed further light on blast furnace hearth drainage and the corresponding flow and behavior of the interfaces. A transparent Hele-Shaw (H-S) slot model was constructed and experiments were undertaken with it. To gain quantitative tapping information from the experimental model, an image analysis algorithm was developed to treat and refine the experimental results. The H-S model has inherent merits for the application of image analysis, such as low optical distortion. Based on the developed image analysis method, the role of the blast pressure, slag viscosity, and initial accumulated liquid amounts on the tapping duration and residual liquid ratios were examined. Some results were processed to dimensionless form to employ the findings in the practical BF system. In addition, the influence of the operational conditions on the tapping end state was studied. The evolution of liquid levels and volumes, liquid outflow rates and oil ratio, as well as interface angles was studied to characterize the hearth draining. Since it is not easy to use the H-S model to study certain factors, like the coke-free zone or bed permeability, a simulation model of the H-S was developed to mimic the experimental counterpart. This computational fluid dynamics (CFD)-based model was first validated by experimental data and then applied to analyze the evolution of key process variables. Even though the real furnace hearth experiences continuous inflows of iron and slag, the experiments and computational models developed in this thesis for the sake of simplicity only considered the drainage. To gain an understanding on how the hearth lining design and boundary conditions affect the inner profile of the hearth, an asymptotic erosion model was also developed. The model considers hot metal flow, heat transfer, lining erosion, and possible skull formation and can be used to estimate the durability of the hearth. A number of cases were studied to illustrate the applicability and versatility of the model.Denna doktorsavhandling studerar strömningen and järn och slagg i masugnens nedersta del, s.k. ställ, och den komplexa dräneringen av ugnen under tappning. Forskningen baserades på såväl experiment i liten skala som numerisk simulering. I arbetet utvecklades även en matematisk modell för ställväggens och -bottnens slutliga tillstånd för en specifik ställdesign samt drifttillstånd hos masugnen. Doktorsarbetets huvudsakliga avsikt var att undersöka förhållandena under tappning av masugn och att kvantifiera hur de två smälta faserna flödar ut ur ugnen. Speciell tonvikt sattes vid hur gränsskikten mellan fluiderna utvecklades under tappningen. En genomskinlig spaltmodell, av H-S-typ, byggdes och användes i arbetets experimentella delar. I laboratoriemodellen ersattes järn och slagg av vatten och olja, som inbördes visades ha sådana egenskaper att slutsatser om det verkliga systemet kunde dras på basis av experimenten. För att kunna behandla stora datamängder samt erhålla tillförlitlig information från spaltmodellens försök utvecklades en metodik för automatisk bildanalys, som via videosekvenser kan detektera fasernas gränsskikt och därför beskriva dessa numeriskt för vidarebehandling av informationen. Metoden möjliggjorde även en automatisk uppföljning av vätskevolymerna i H-S-modellen under experimenten, vilket implicit även gav utflödeshastigheterna av vatten och olja. På basis av metoden studerades inverkan av blästertryck, slaggviskositet och startvolymerna av järn och slagg i masugnsstället på tapptiden genom motsvarande försök i H-S-modellen, där resultaten för vatten och olja omformades med hjälp av dimensionslösa uttryck så att slutsatser beträffande de industriella förhållandena kunde dras. Försöken gjordes utan att tillföra vätskor, vilket betyder att endast dräneringen (utflödet) beaktades i experimenten. Med modellen studerades bl.a. hur omständigheterna påverkade de slutliga vätskemängderna, hur vätskenivåerna och –utflödet utvecklades samt hur, och i vilken omfattning, gränsskikten deformerades i närheten av tapphålet under tappningens gång. Arbetet klargjorde de faktorer som ha stor betydelse för tappningsförloppet, samt illustrerade även möjliga avvikande tillstånd som kan uppstå under vissa omständigheter. Blästertrycket befanns spela en avgörande roll vid dräneringen för både tappningshastigheterna och restvolymerna av smältorna då tappningen avslutats. Ett exempel ur avvikande tillstånd är tappningar som slutar fastän gränsskiktet mellan järn och slagg överlag befinner sig ovanom tapphålets nivå. Då det inte var enkelt att studera vissa parametrar med den experimentella modellen, såsom t.ex. bäddpermeabiliteten eller en möjlig flytning av koksbädden i masugnen, utvecklades även en numerisk modell på basis av strömningsmekanik (eng. computational fluid dynamics, CFD) för H-S-systemet. Den numeriska modellen efterliknar det experimentella systemet och kan användas för jämförelse samt för att analysera variabler vilkas värden inte kan ändras i laboratoriemiljö. Modellen befanns beskriva den experimentella modellen med acceptabel noggrannhet och utnyttjades därefter för att teoretiskt studera vissa faktorers inverkan på dräneringsförloppen. I överensstämmelse med resultat som rapporterats i litteraturen fann man att utströmningen av vätskorna påverkades kraftigt av en koksfri zon i bädden som sträcker sig ända upp till tapphålet. I praktiken är masugnsställets dimensioner inte statiska utan förändras under driften p.g.a. slitage av de eldfasta ställmaterialen samt även av möjliga ansättningar av material på ställväggen och –bottnen. För att öka förståelsen för hur ställdesign samt driftsparametrar, såsom omständigheterna vid ställets gränser, påverkar förloppen utvecklades en matematisk modell som beskriver det asymptotiska sluttillståndet för ställinfodringen. Modellen, som är två-dimensionell och statisk, beaktar strömningen av järnsmältan, värmeöverföring från smältan via ställväggen och –bottnen till omgivningen, och estimerar samtidigt infodringens slitaget samt möjlig bildning av ansättningar. Den kan därför användas som ett verktyg för att teoretiskt studera hur ställdesign (geometri, materialval) samt driftomständigheter (produktionstakt, väggkylning, etc.) påverkar det förväntade fortfarighetstillståndet hos stället. Ett flertal intressanta fall studerades med modellen för att belysa dess användningsmöjligheter.
A hybrid Large Eddy Simulation (LES) - Reynolds-Averaged Navier-Stokes (RANS) method (HLR) has been applied to simulate an engine related selective catalytic reduction (SCR) system. Typical SCR systems utilize low pressure urea injection together with a mixer for vapor field homogenization. Simultaneously, it is also desirable to reduce spray-wall interaction to avoid urea crystallization. The present study considers an SCR system where a high pressure (150 bar) urea spray is injected towards hot exhaust gases in exhaust pipe. The system has been shown to work well in a previous experimental study but detailed characterization of the system is missing. The novelty of the present study rises from: 1) the creation of phase diagrams with single droplet simulations that predict the optimum operation regions for the SCR system, 2) validation of the HLR method in a high Reynolds number (Re=49,900) compressible pipe flow, 3) the use of HLR simulations in an engine SCR system for the first time, and 4) the detailed characterization of the present SCR system. As a result of the study, new non-dimensional timescale ratios are proposed to link the droplet size and liquid injection velocity to the exhaust pipe dimensions in future SCR systems.
Earthquakes worldwide highlight the seismic vulnerability of reinforced concrete (RC) bridge columns. RC bridges are likely to collapse or lose service function due to damage to the bridge columns from strong earthquakes. Rapid repair of RC bridge columns is of great significance for maintaining traffic lines for emergency rescue work after earthquakes. In this study, an improved rapid repair method was developed to restore the bearing capacity of a damaged precast column after earthquake damage. A cyclic loading test was performed to simulate the seismic loading. The original column and the repaired column were both tested. The test results showed that the bearing capacity of the repaired columns was increased by 8%, and the energy dissipation capacity was 53% higher than that of the original column. The ductility decreased because the test for the repaired specimen ended in advance. The initial stiffness of the repaired columns was reduced, but the stiffness was significantly developed in the later loading stage. The rapid repair method proposed in this study exhibited an excellent effect on restoring the seismic resistance of the damaged columns.
Grouted sleeve connections have been developed in various precast structures such as columns in buildings and bridges. When they are used in precast columns, the aspect ratio of the column is reduced owing to the shifted plastic hinge phenomenon. In contrast, short columns with aspect ratios of less than three are susceptible to shear failure under earthquakes. This study investigated the effect of UHPC (ultra-high-performance concrete) grouted sleeve connections on the seismic performance of precast columns. One cast-in-place column (CIP) and two precast columns (PCGS1 and PCGS2) with an original aspect ratio of 3.11 were manufactured. The two precast columns were designed with grouted sleeve connections at different positions, which were supposed to have lower actual aspect ratios according to the shifted plastic-hinging phenomenon. Cyclic loading tests were conducted on all the columns to study their seismic performance. The damage progression and seismic responses were analyzed experimentally. Shifted plastic hinging was theoretically calculated, and a numerical model was developed using OpenSees platform. From the acquired results, the precast column PCGS1, which was connected by grouted sleeve connections at the bottom, failed in shear failure. The other two columns failed in flexure-shear failure. The seismic performance of precast column PCGS1 was significantly reduced through a comparison of the hysteretic responses. A calculation method was proposed to obtain the critical height of the grouted sleeve connections, which helped the short columns avoid shear failure during earthquakes. The numerical analysis showed that the location of grouted sleeves had a negligible effect on seismic performance when placed above the critical height. The increase in the compression ratio and rebar strength positively affected the bearing capacity but negatively influenced the ductility.
With the development of advanced communication systems, paralleled with recent efforts to adopt lightweight, low-carbon footprint materials, there is an urgent demand for green electromagnetic interference (EMI) shielding materials. However, this is challenged by the shielding effectiveness of bio-based EMI and their capacity to eliminate radiation pollution while meeting the demands of diverse application environments. Learning from the strategies used by epiphytes, we introduce a highly efficient and multi-functional bio-based EMI shielding eco-material. We developed 3D hybrid network structures incorporating coordination-driven silver nanoparticles to achieve excellent shielding effectiveness, ∼30.8 dB, while simultaneously meeting mechanical demands, multi-functionality, water resistance, flame retardancy, and antibacterial properties. Overall, this work provides a novel but practical pathway to implement bio-based materials conferred with EMI protection, applicable in next-generation electronics.
Abstract Multiple kernel learning (MKL) has been intensively studied during the past decade. It optimally combines the multiple channels of each sample to improve classification performance. However, existing MKL algorithms cannot effectively handle the situation where some channels of the samples are missing, which is not uncommon in practical applications. This paper proposes three absent MKL (AMKL) algorithms to address this issue. Different from existing approaches where missing channels are firstly imputed and then a standard MKL algorithm is deployed on the imputed data, our algorithms directly classify each sample based on its observed channels, without performing imputation. Specifically, we define a margin for each sample in its own relevant space, a space corresponding to the observed channels of that sample. The proposed AMKL algorithms then maximize the minimum of all sample-based margins, and this leads to a difficult optimization problem. We first provide two two-step iterative algorithms to approximately solve this problem. After that, we show that this problem can be reformulated as a convex one by applying the representer theorem. This makes it readily be solved via existing convex optimization packages. In addition, we provide a generalization error bound to justify the proposed AMKL algorithms from a theoretical perspective. Extensive experiments are conducted on nine UCI and six MKL benchmark datasets to compare the proposed algorithms with existing imputation-based methods. As demonstrated, our algorithms achieve superior performance and the improvement is more significant with the increase of missing ratio.
Visual attention and visual working memory (VWM) are two major cognitive functions in humans, and they have much in common. A growing body of research has investigated the effect of emotional information on visual attention and VWM. Interestingly, contradictory findings have supported both a negative bias and a positive bias toward emotional faces (e.g., angry faces or happy faces) in the attention and VWM fields. We found that the classical paradigms—that is, the visual search paradigm in attention and the change detection paradigm in VWM—are considerably similar. The settings of these paradigms could therefore be responsible for the contradictory results. In this paper, we compare previous controversial results from behavioral and neuroscience studies using these two paradigms. We suggest three possible contributing factors that have significant impacts on the contradictory conclusions regarding different emotional bias effects; these factors are stimulus choice, experimental setting, and cognitive process. We also propose new research directions and guidelines for future studies.
Abstract Three di-nuclear DyIII complexes [Dy2(H2L)2(tfa)]·Cl·3DMF (1), [Dy2(H2L)2(MeO)(SCN)]·MeOH (2) and [Dy2(H2L)2(MeOH)Cl]·Cl·2MeOH (3) were synthesized and structurally and magnetically characterized. The Dy1/Dy2 centers in these complexes are all nine-coordinate with spherical capped square antiprism (local C4v symmetry) environments. All complexes display single-molecule magnet (SMM) behavior under zero applied dc field with their properties dependent on the nature of the magnetic interactions between the DyIII ions. Ab initio calculations substantiate that all DyIII ions show a weakly axial crystal-field environment with the exception of one of the DyIII ions in complex 2. The ground Kramers doublets show modest amounts of quantum tunneling of magnetization that gets blocked by the interaction between the DyIII ions, leading to a thermally activated slow relaxation of magnetization. The interaction between the ions is ferromagnetic and mostly originates from the dipolar interaction. However, anti-ferromagnetic intermolecular interaction plays an important role and in the case of complex 2 it is sufficiently strong to mask the ferromagnetic intramolecular interaction.
Abstract Predicted intensified climate warming will likely alter the ecosystem net carbon (C) uptake of the Qinghai–Tibetan Plateau (QTP). Variations in C sink–source responses to climate warming have been linked to water availability; however, the mechanisms by which net C uptake responds to soil water content in saturated swamp meadow ecosystems remain unclear. To explore how soil moisture and other environmental drivers modulate net C uptake in the QTP, field measurements were conducted using the eddy covariance technique in 2014, 2015, 2017, and 2018. The alpine swamp meadow presented in this study was a persistent and strong C sink of CO2 (−168.0 ± 62.5 g C m−2 yr−1, average ± standard deviation) across the entire 4-year study period. A random forest machine-learning analysis suggested that the diurnal and seasonal variations of net ecosystem exchange (NEE) and gross primary productivity (GPP) were regulated by temperature and net radiation. Ecosystem respiration (Re), however, was found mainly regulated by the variability of soil water content (SWC) at different temporal aggregations, followed by temperature, the second contributing driver. We further explored how Re is controlled by nearly saturated soil moisture and temperature comparing two different periods featuring almost identical temperatures and significant differences on SWC and vice versa. Our data suggest that, despite the relatively abundant water supply, periods with a substantial decrease in SWC or increase in temperature produced higher Re and therefore weakened the C sink strength. Our results reveal that nearly saturated soil conditions during the growing seasons can help maintain lower ecosystem respiration rates and thus enhance the overall C sequestration capacity in this alpine swamp meadow. We argue that soil respiration and subsequent ecosystem C sink magnitude in alpine swamp meadows could likely be affected by future changes in soil hydrological conditions caused by permafrost degradation or accelerated thawing–freezing cycling due to climate warming.
The ecosystem and human society are nowadays greatly threatened by oily wastewater or spilled oils. To address these severe issues, considerably advanced methods, such as those using polymer membranes and polymer-coated meshes with special wettability, have been developed to achieve efficient oil/water separation. However, a single superhydrophobic- or superhydrophilic-based membrane or mesh can only allow either oil or water to pass through, which restricts their applications. Besides, these artificial materials and their fabricating processes may also involve hazardous substances and enormous energy consumption. Therefore, powerful and green oil/water separation approaches are still urgently needed. Herein, we report that the natural lotus leaf with Janus wettability can be a potential candidate for efficient oil/water separation after simple punching by a needle. The proposed approach has the advantages of easily obtained and low-cost natural origin materials and a simple fabrication process and shows potential applicability for building a greener world.
Abstract The first oligopyrrolic Cu(II)-based metallocage featuring two antiferromagnetically coupled dimeric cupric tetracarboxylate units linked by a single molecule of water was assembled successfully using a nonlinear pyridine–pyrrolate ligand. Broken symmetry density functional theory (BS-DFT) calculations show that the exchange couplings between Cu(II) ions in the Cu2 unit and over the water bridge are −298 and −0.13 cm−1, respectively.
Abstract Magnetoelectric (ME) multiferroic materials have unique advantages in low-power and high-density information storage, because they can simultaneously display ferroelectricity and ferromagnetism. However, research on how to construct air-stable high-performance ME single-molecule magnets (SMMs) is nonexistent. Herein, by introducing homochirality while reducing molecular symmetry, two double-decker Dy(III) enantiomers adopting the polar space group P21 and exhibiting excellent thermal stability were obtained. They displayed zero field SMM behavior with an anisotropy barrier (Ueff) of ca. 100 cm−1. This work establishes a rational chemical design strategy for crystallizing SMMs in polar space groups and elucidates the direction for future research, that is, engineering small-size high-performance SMMs.
Abstract The advances of sensing and computing technologies pave the way to develop novel applications and services for wearable devices. For example, wearable devices measure heart rate, which accurately reflects the intensity of physical exercise. Therefore, heart rate prediction from wearable devices benefits users with optimization of the training process. Conventionally, Cloud collects user data from wearable devices and conducts inference. However, this paradigm introduces significant privacy concerns. Federated learning is an emerging paradigm that enhances user privacy by remaining the majority of personal data on users’ devices. In this paper, we propose a statistically sound, Bayesian inference federated learning for heart rate prediction with autoregression with exogenous variable (ARX) model. The proposed privacy-preserving method achieves accurate and robust heart rate prediction. To validate our method, we conduct extensive experiments with real-world outdoor running exercise data collected from wearable devices.
Abstract To solve the problem of environmental pollution, Distiller’s dried grains (DDGS), a biomass, is used as a clean reducing agent for the leaching process of pyrolusite. Experimental results have shown that the leaching rate of manganese can reach 92.1% with the optimized conditions including a sulfuric acid concentration of 3.5 mol/L, a DDGS to pyrolusite ratio of 0.4, a liquid–solid ratio of 3 mL/g, a temperature of 363K, a time of 3 h, and a rotation speed of 400 rpm. This article explored the mechanism of the entire leaching process: the crude fiber in DDGS is hydrolyzed into reducing sugars, and the MnO2 in pyrolusite undergoes an oxidation–reduction reaction to generate Mn2+ and studied the kinetics of the leaching process following the unreacted shrinkage nuclear reaction model controlled by the surface chemical reaction (\(1-(1-X)^{1/3}=\text{kt}\)). The equation of leaching kinetics is \(1−1-\text{X}^{\frac{1}{3}} = 3738.06 \cdot [\text{H}_{2}\text{SO}_{4}]^{0.57} \cdot \left[\frac{L}{S}\right]^{0.78} \cdot \left[\frac{DDGS}{\text{pyrolusite}}\right]^{0.25} \cdot [rpm]^{0.09} \cdot \exp(-48.448/(RT)\) This work provides a green and effective leaching process for the leaching of pyrolusite.
In this paper, a transmission-type graphene plasmonic modulator by introducing off-resonant Au structure is theoretically and experimentally investigated. It is found that the modulation efficiency and bandwidth could be dramatically enhanced compared with bare graphene plasmonic structure. The validity of this proposed method is verified both in the 1D and 2D graphene plasmonic structures: ribbons and holes. This work will open up a new path to design the high-efficiency modulators, switches, and multispectral detectors.
The prevalence of ideal cardiovascular health (CVH) among adults in the United States is low and decreases with age. Our objective was to identify specific age windows when the loss of CVH accelerates, to ascertain preventive opportunities for intervention. Data were pooled from 5 longitudinal cohorts (Project Heartbeat!, Cardiovascular Risk in Young Finns Study, The Bogalusa Heart Study, Coronary Artery Risk Development in Young Adults, Special Turku Coronary Risk Factor Intervention Project) from the United States and Finland from 1973 to 2012. Individuals with clinical CVH factors (i.e., body mass index, blood pressure, cholesterol, blood glucose) measured from ages 8 to 55 years were included. These factors were categorized and summed into a clinical CVH score ranging from 0 (worst) to 8 (best). Adjusted, segmented, linear mixed models were used to estimate the change in CVH over time. Among the 18,343 participants, 9,461 (52%) were female and 12,346 (67%) were White. The baseline mean (standard deviation) clinical CVH score was 6.9 (1.2) at an average age of 17.6 (8.1) years. Two inflection points were estimated: at 16.9 years (95% confidence interval: 16.4, 17.4) and at 37.2 years (95% confidence interval: 32.4, 41.9). Late adolescence and early middle age appear to be influential periods during which the loss of CVH accelerates.
Abstract The threat of 3D masks to face recognition systems is increasingly serious and has been widely concerned by researchers. To facilitate the study of the algorithms, a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask) has been collected. Specifically, it consists of a total amount of 54,600 videos which are recorded from 75 subjects with 225 realistic masks under 7 new kinds of sensors [21]. Based on this dataset and Protocol 3 which evaluates both the discrimination and generalization ability of the algorithm under the open set scenarios, we organized a 3D High-Fidelity Mask Face Presentation Attack Detection Challenge to boost the research of 3D mask-based attack detection. It attracted 195 teams for the development phase with a total of 18 teams qualifying for the final round. All the results were verified and re-run by the organizing team, and the results were used for the final ranking. This paper presents an overview of the challenge, including the introduction of the dataset used, the definition of the protocol, the calculation of the evaluation criteria, and the summary and publication of the competition results. Finally, we focus on introducing and analyzing the top ranking algorithms, the conclusion summary, and the research ideas for mask attack detection provided by this competition.
Introduction: Minimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the “Dynamic COVID-zero” strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures. Methods: Informed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks. Results: Under the transmission scenario (R0=5.49), this study estimated the cumulative case incidence of Changchun City, Jilin Province as 3,233 (95% confidence interval: 1,480, 4,986) before a lockdown on March 14, 2022, which is close to the 3,168 cases reported in real life by March 16, 2022. In a total of 367 prefectures (cities), 127 (35%) had high exportation risks according to the simulation and could transmit the disease to 50% of all other regions within a period from 17 to 94days. The average time until a new infection arrives in a location in 1 of the 367 prefectures (cities) ranged from 26 to 101 days. Conclusions: Estimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 — especially when new variants emerge.
Abstract Face presentation attack detection (PAD) is essential to secure face recognition systems primarily from high-fidelity mask attacks. Most existing 3D mask PAD benchmarks suffer from several drawbacks: 1) a limited number of mask identities, types of sensors, and a total number of videos; 2) low-fidelity quality of facial masks. Basic deep models and remote photoplethysmography (rPPG) methods achieved acceptable performance on these benchmarks but still far from the needs of practical scenarios. To bridge the gap to real-world applications, we introduce a large-scale High- Fidelity Mask dataset, namely HiFiMask. Specifically, a total amount of 54,600 videos are recorded from 75 subjects with 225 realistic masks by 7 new kinds of sensors. Along with the dataset, we propose a novel C ontrastive C ontext-aware L earning (CCL) framework. CCL is a new training methodology for supervised PAD tasks, which is able to learn by leveraging rich contexts accurately (e.g., subjects, mask material and lighting) among pairs of live faces and high-fidelity mask attacks. Extensive experimental evaluations on HiFiMask and three additional 3D mask datasets demonstrate the effectiveness of our method. The codes and dataset will be released soon.
Abstract During the storm recovery phase on 27 August 2018, the China Seismo-Electromagnetic Satellite (CSES) detected Pc1 wave activities in both the Northern Hemisphere and Southern Hemisphere in the high-latitude, post-midnight ionosphere with a central frequency of about 2 Hz. Meanwhile, the typical Pc1 waves were simultaneously observed for several hours by the Sodankylä Geophysical Observatory (SGO) stations on the ground. In this paper, we study the propagation characteristics and possible source regions of those waves. Firstly, we find that the Pc1 waves observed by the satellites exhibited mixed polarisation, and the wave normal is almost parallel with the background magnetic field. The field-aligned Poynting fluxes point downwards in both hemispheres, implying that the satellites are close to the wave injection regions in the ionosphere at about L=3. Furthermore, we also find that the estimated position of the plasmapause calculated by models is almost at L=3. Therefore, we suggest that the possible sources of waves are near the plasmapause, which is consistent with previous studies in that the outward expansion of the plasmasphere into the ring current during the recovery phase of geomagnetic storms may generate electromagnetic ion cyclotron (EMIC) waves, and these EMIC waves propagate northwards and southwards along the background magnetic field to the ionosphere at about L=3. Additionally, the ground station data show that Pc1 wave power attenuates with increasing distance from L=3, supporting the idea that the CSES observes the wave activities near the injection region. The observations are unique in that the Pc1 waves are observed in the ionosphere in nearly conjugate regions where transverse Alfvén waves propagate down into the ionosphere.
Magnetoelectric coupling at room temperature in multiferroic materials, such as BiFeO3, is one of the leading candidates to develop low-power spintronics and emerging memory technologies. Although extensive research activity has been devoted recently to exploring the physical properties, especially focusing on ferroelectricity and antiferromagnetism in chemically modified BiFeO3, a concrete understanding of the magnetoelectric coupling is yet to be fulfilled. We have discovered that La substitutions at the Bi-site lead to a progressive increase in the degeneracy of the potential energy landscape of the BiFeO3 system exemplified by a rotation of the polar axis away from the < 111 > (pc) towards the < 112 > (pc) discretion. This is accompanied by corresponding rotation of the antiferromagnetic axis as well, thus maintaining the right-handed vectorial relationship between ferroelectric polarization, antiferromagnetic vector and the Dzyaloshinskii-Moriya vector. As a consequence, La-BiFeO3 films exhibit a magnetoelectric coupling that is distinctly different from the undoped BiFeO3 films. BiFeO3 has a wide application but the impact of rare-earth substitution for the evolution of the coupling mechanism is unknown. Here, the authors reveal the correlation between ferroelectricity, antiferromagnetism, a weak ferromagnetic moment, and their switching pathways in La-substituted BiFeO3.
Secondary aerosol formation in the aging process of primary emission is the main reason for haze pollution in eastern China. Pollution evolution with photochemical age was studied for the first time at a comprehensive field observation station during winter in Beijing. The photochemical age was used as an estimate of the timescale attributed to the aging process and was estimated from the ratio of toluene to benzene in this study. A low photochemical age indicates a fresh emission. The photochemical age of air masses during new particle formation (NPF) days was lower than that on haze days. In general, the strongest NPF events, along with a peak of the formation rate of 1.5 nm (J1.5) and 3 nm particles (J3), were observed when the photochemical age was between 12 and 24 h while rarely took place with photochemical ages less than 12 h. When photochemical age was larger than 48 h, haze occurred and NPF was suppressed. The sources and sinks of nanoparticles had distinct relation with the photochemical age. Our results show that the condensation sink (CS) showed a valley with photochemical ages ranging from 12 to 24 h, while H2SO4 concentration showed no obvious trend with the photochemical age. The high concentrations of precursor vapours within an air mass lead to persistent nucleation with photochemical age ranging from 12 to 48 h in winter. Coincidently, the fast increase of PM2.5 mass was also observed during this range of photochemical age. Noteworthy, CS increased with the photochemical age on NPF days only, which is the likely reason for the observation that the PM2.5 mass increased faster with photochemical age on NPF days compared with other days. The evolution of particles with the photochemical age provides new insights into understanding how particles originating from NPF transform to haze pollution.
Gaseous hydrochloric (HCl) and hydrobromic acid (HBr) are vital halogen species that play essential roles in tropospheric physicochemical processes. Yet, the majority of the current studies on these halogen species were conducted in marine or coastal areas. Detection and source identification of HCl and HBr in inland urban areas remain scarce, thus limiting the full understanding of halogen chemistry and potential atmospheric impacts in the environments with limited influence from the marine sources. Here, both gaseous HCl and HBr were concurrently measured in urban Beijing, China, during winter and early spring of 2019. We observed significant HCl and HBr concentrations ranging from a minimum value at 1gg108 molecules cm-3 (4gppt) and 4gg107 molecules cm-3 (1gppt) up to 6gg109 molecules cm-3 (222gppt) and 1gg109 molecules cm-3 (37gppt), respectively. The HCl and HBr concentrations are enhanced along with the increase of atmospheric temperature, UVB and levels of gaseous HNO3. Based on the air mass analysis and high correlations of HCl and HBr with the burning indicators (HCN and HCNO), gaseous HCl and HBr are found to be related to anthropogenic burning aerosols. The gas-particle partitioning may also play a dominant role in the elevated daytime HCl and HBr. During the daytime, the reactions of HCl and HBr with OH radicals lead to significant production of atomic Cl and Br, up to 2gg104 molecules cm-3gs-1 and 8gg104 moleculesgcm-3gs-1, respectively. The production rate of atomic Br (via HBrg+gOH) is 2-3 times higher than that of atomic Cl (via HClg+gOH), highlighting the potential importance of bromine chemistry in the urban area. On polluted days, the production rates of atomic Cl and Br are faster than those on clean days. Furthermore, our observations of elevated HCl and HBr may suggest an important recycling pathway of halogen species in inland megacities and may provide a plausible explanation for the widespread halogen chemistry, which could affect the atmospheric oxidation in China.
The domestication and subsequent global dispersal of livestock are crucial events in human history, but the migratory episodes during the history of livestock remain poorly documented. Here, we first developed a set of 493 novel ovine SNPs of the male-specific region of Y chromosome (MSY) by genome mapping. We then conducted a comprehensive genomic analysis of Y chromosome, mitochondrial DNA, and wholegenome sequence variations in a large number of 595 rams representing 118 domestic populations across the world. We detected four different paternal lineages of domestic sheep and resolved, at the global level, their paternal origins and differentiation. In Northern European breeds, several of which have retained primitive traits (e.g., a small body size and short or thin tails), and fat-tailed sheep, we found an overrepresentation of MSY lineages y-HC and y-HB, respectively. Using an approximate Bayesian computation approach, we reconstruct the demographic expansions associated with the segregation of primitive and fat-tailed phenotypes. These results together with archaeological evidence and historical data suggested the first expansion of early domestic hair sheep and the later expansion of fat-tailed sheep occurred 11,800–9,000 years BP and 5,300–1,700 years BP, respectively. These findings provide important insights into the history of migration and pastoralism of sheep across the Old World, which was associated with different breeding goals during the Neolithic agricultural revolution.
Domestic sheep and their wild relatives harbor substantial genetic variants that can form the backbone of molecular breeding, but their genome landscapes remain understudied. Here, we present a comprehensive genome resource for wild ovine species, landraces and improved breeds of domestic sheep, comprising high-coverage (∼16.10×) whole genomes of 810 samples from 7 wild species and 158 diverse domestic populations. We detected, in total, ∼121.2 million single nucleotide polymorphisms, ∼61 million of which are novel. Some display significant (P < 0.001) differences in frequency between wild and domestic species, or are private to continent-wide or individual sheep populations. Retained or introgressed wild gene variants in domestic populations have contributed to local adaptation, such as the variation in the HBB associated with plateau adaptation. We identified novel and previously reported targets of selection on morphological and agronomic traits such as stature, horn, tail configuration, and wool fineness. We explored the genetic basis of wool fineness and unveiled a novel mutation (chr25: T7,068,586C) in the 3′-UTR of IRF2BP2 as plausible causal variant for fleece fiber diameter. We reconstructed prehistorical migrations from the Near Eastern domestication center to South-and-Southeast Asia and found two main waves of migrations across the Eurasian Steppe and the Iranian Plateau in the Early and Late Bronze Ages. Our findings refine our understanding of genome variation as shaped by continental migrations, introgression, adaptation, and selection of sheep.
Understanding the genetic changes underlying phenotypic variation in sheep (Ovis aries) may facilitate our efforts towards further improvement. Here, we report the deep resequencing of 248 sheep including the wild ancestor (O. orientalis), landraces, and improved breeds. We explored the sheep variome and selection signatures. We detected genomic regions harboring genes associated with distinct morphological and agronomic traits, which may be past and potential future targets of domestication, breeding, and selection. Furthermore, we found non-synonymous mutations in a set of plausible candidate genes and significant differences in their allele frequency distributions across breeds. We identified PDGFD as a likely causal gene for fat deposition in the tails of sheep through transcriptome, RT-PCR, qPCR, and Western blot analyses. Our results provide insights into the demographic history of sheep and a valuable genomic resource for future genetic studies and improved genome-assisted breeding of sheep and other domestic animals.
Sulfur trioxide (SO3) is a crucial compound for atmospheric sulfuric acid (H2SO4) formation, acid rain formation, and other atmospheric physicochemical processes. During the daytime, SO3is mainly produced from the photo-oxidation of SO2by OH radicals. However, the sources of SO3during the early morning and night, when OH radicals are scarce, are not fully understood. We report results from two field measurements in urban Beijing during winter and summer 2019, using a nitrate-CI-APi-LTOF (chemical ionization-Atmospheric pressure interface-long-Time-of-flight) mass spectrometer to detect atmospheric SO3and H2SO4. Our results show the level of SO3was higher during the winter than during the summer, with high SO3levels observed especially during the early morning (05:00 to 08:30) and night (18:00 to 05:00 the next day). On the basis of analysis of SO2, NOx, black carbon, traffic flow, and atmospheric ions, we suggest SO3could be formed from the catalytic oxidation of SO2on the surface of traffic-related black carbon. This previously unidentified SO3source results in significant H2SO4formation in the early morning and thus promotes sub-2.5 nm particle formation. These findings will help in understanding urban SO3and formulating policies to mitigate secondary particle formation in Chinese megacities.