Advocacy and Use of Advocates as a Quick Win in Scaling Up Biofortification in Nigeria: The Case of Building Nutritious Food Basket (BNFB) Project

The Building Nutritious Food Baskets (BNFB) Project explored advocacy and the use of advocates as a model strategy for scaling up biofortification in Nigeria during its three-year implementation. In addition to its direct advocacy efforts, the BNFB project identified and selected key personnel across disciplines, gender and sectors, based on some selected criteria, as Advocates to support the scaling up of biofortification by raise of investments, resource mobilization, the inclusion of biofortification in relevant policy documents, strategies and plans of action. To realize these, the selected 32 Advocates were empowered to mainstream biofortification into their existing and/or potential programs/projects, as well as create awareness and demand for biofortified crops within their spheres of influence. Training and retreats were organized for the Advocates to strengthen their capacities in advocacy and promotion of biofortification and biofortified crops, while a social platform was launched to share opportunities, experiences and address issues around biofortification within the Advocates. As a result of these efforts, biofortification was included in three key national policies, strategies/plans of actions with resource allocation, and investments, over USD3 million were raised for biofortification. The Federal Government of Nigeria and some external governments became committed to biofortification programs while biofortified crops were mainstreamed in at least two national programs in Nigeria. Biofortified crops were included in the Home-Grown School Feeding Program of two states. The use of Advocates proved to be a resultful strategy in the biofortification scaling up model of BNFB as the advocates, upon being trained, looked out within their sectors and disciplines to mainstream biofortification into their programs. They gave timely information on potential opportunities to follow up with in influencing favorable policies;they mobilized resources nationally, regionally and locally;they facilitated wider coverage of biofortification within a short time. However, the influence of the Advocates was limited to their number and locations;thus, for a quick win in Nigeria, there is a need to raise advocates in all the 36 states of the country while giving equal priority to national and state level advocacy. As a lesson, to engender adoption of biofortification, participation/leveraging on existing programs in advocacy works faster and easier than starting afresh in Nigeria.

Scaling up impact of malaria control programmes: a tale of events in Sub-Saharan Africa and People’s Republic of China

This review aims at providing synthetic information with scientific evidence on the trends in the malaria events from 1960 to 2011,with the hope that it will help policy makers to take informed decisions on public health issues and intervention designs on malaria control towards elimination in both Sub-Sahara Africa and in the People’s Republic of China by highlighting the achievements,progress and challenges in research on moving malaria from epidemic status towards elimination.Our findings showed that since 1960,malaria control programmes in most countries have been disjointed and not harmonized.Interestingly,during the last decade,the causal factors of the unprecedented and substantial decline in malaria morbidity and mortality rates in most vulnerable groups in these endemic areas are multifaceted,including not only the spread of malaria and its related effects but also political and financial willingness,commitment and funding by governments and international donors.The benefits of scaling up the impact of malaria coverage interventions,improvement of health system approaches and sustained commitment of stakeholders are highlighted,although considerable efforts are still necessary in Sub-Sahara Africa.Furthermore,novel integrated control strategies aiming at moving malaria from epidemic status to control towards elimination,require solid research priorities both for sustainability of the most efficient existing tools and intervention coverage,and in gaining more insights in the understanding of the epidemiology,pathogenesis,vector dynamics,and socioeconomic aspects of the disease.In conclusion,political commitment and financial investment of stakeholders in sustaining the scaling up impact of malaria control interventions,networking between African and Chinese scientists,and their Western partners are urgently needed in upholding the recent gains,and in translating lessons learnt from the Chinese malaria control achievements and successes into practical interventions in malaria endemic countries in Africa and elsewhere.

Coupling Research on the Process of Transfer of Surplus Labor Forces and Scaling-up of Farmland

On the basis of giving an overview of efficiency research on transformation of land from fragmentation to scale economy, by using the concept of coupling in physics, this paper expounds the behavior basis of transfer of surplus rural labor forces in China and transformation of land from fragmentation to scaling up, and analyzes behaviors of all parties and equilibrium outcomes in the three stages concerning the transformation of agricultural land from fragmentation to scaling up as follows. At the first stage of coupling, after multitudinous rural surplus labor forces emerge, the farmers begin to go to city seeking jobs. In this period, the amalgamation of land management has not occurred and the single farmer's land has not yet concentrated. The total land area of single farmer has not yet increased and the total amount of farmers has not yet decreased. At the second stage of coupling, driven by living standards and income, multitudinous rural surplus labor forces begin to live in the city permanently in fact, and the scale management of rural land begins to arise. Foreign funded enterprises begin to enter agriculture, and the industrialization management of agriculture is equipped with the most fundamental conditions due to the occurrence of scaling up of land. At the third stage of coupling, the transfer of rural surplus labor forces basically ends. The property rights of agricultural land or the management forms also, in a large measure, concentrate. The obstacles to agricultural scaling-up management are solved fundamentally, and the income gap between urban areas and rural areas is narrowed. Urban-rural population migration is no longer the main form of China's population migration. This stage has not yet been realized in China and it is the future state of villages. Finally, through the two cases researched by the predecessors, we verify the research results of the preceding two stages, which provides reliable reference for transformation of China's agricultural land management, and policy formulation of transfer of surplus labor forces.

Surface lurking and interfacial ion release strategy for fabricating a superhydrophobic coating with scaling inhibition

The design and manufacture of anti-scaling surface is a prospective way to prevent scaling in oil field.In this work,a novel superhydrophobic Cu^(2+)-loaded and DTPMPA-modified anodized copper oxide(S-Cu^(2+)/D-ACO)coating was fabricated by modification of 1H,1H,2H,2H-perfluorodecyltriethoxysilane.The valid storing of scale inhibitors at the coating surface and the interfacial release of Cu^(2+)ions contribute to enhancing the anti-scaling of the S-Cu^(2+)/D-ACO coating.The water contact angle of the S-Cu^(2+)/D-ACO coating is 163.03°and exhibits superhydrophobicity,which makes it difficult for CaCO_(3)to deposit at the surface of the coating.DTPMPA will steadily lurk into the inner space,and Cu^(2+)will be loaded at the interface in the form of the DTPMPA:Cu^(2+)chelate.During the deposition of CaCO_(3),the dynamic release of DTPMPA can be realized by transferring DTPMPA:Cu^(2+)to DTPMPA:Ca^(2+).Interestingly,the released Cu^(2+)hinders the active growth of CaCO_(3).After 48 h of scaling,the mass of CaCO_(3)scale at the S-Cu^(2+)/D-ACO coating surface is only 44.1%that of the anodized copper oxide coating.The excellent anti-scaling performance of the S-Cu^(2+)/D-ACO coating is determined by the synergistic effect of the DTPMPA lurking and dynamic release,as well as the Cu^(2+)inhibition at the interface of superhydrophobic coating and against CaCO_(3)deposition.This research provides a new exploration for designing and fabricating anti-scaling superhydrophobic surface for oil field development.

可视化编程语言中small-screen与scaling-up问题解决方法探讨

由于目前可视化编程语言的设计工具主要集中于将其语素和数据应用二维图形对象来表示的范例来实现,针对其随之产生的sm all-screen与scaling-up问题,提出了一种在二维可视化编程环境下进行解决的方案。可以证明在解决实际问题中效果明显。

Scaling Region in Desynchronous Coupled Chaotic Maps

The largest Lyapunov exponent and the Lyapunov spectrum of a coupled map lattice are studied when the system state is desynchronous chaos. In the large system size limit a scaling region is found in the parameter space where the largest Lyapunov exponent is independent of the system size and the coupling strength. Some scaling relation between the Lyapunov spectrum distributions for different coupling strengths is found when the coupling strengths are taken in the scaling parameter region. The existence of the scaling domain and the scaling relation of Lyapunov spectra there are heuristically explained.

Call for papers: Special Issue on “Novel technologies for sustainable monitoring of polar environment upscaling from in situ observations to aerial and space-borne remote sensing”

Polar regions have received increasing scientific research attentions,in great part,due to its dramatic changes of temperature in recent decades.Satellite remote sensing data provides consistent,regional and large scales patterns of polar oceans and sea ice that are essential for polar climate modelling and operational service.One the other hand,acquiring in situ observations data is hampered by harsh environmental conditions.These ground truths are critical for remote sensing algorithms and numerical models’validation,and therefore,play important roles to improve the quality of polar weather and climate forecast and enhance better understanding of advances in polar science.

Exploring the mechanisms of calcium carbonate deposition on various substrates with implications for effective anti-scaling material selection

The unexpected scaling phenomena have resulted in significant damages to the oil and gas industries,leading to issues such as heat exchanger failures and pipeline clogging.It is of practical and fundamental importance to understand the scaling mechanisms and develop efficient anti-scaling strategies.However,the underlying surface interaction mechanisms of scalants(e.g.,calcite)with various substrates are still not fully understood.In this work,the colloidal probe atomic force microscopy(AFM)technique has been applied to directly quantify the surface forces between calcite particles and different metallic substrates,including carbon steel(CR1018),low alloy steel(4140),stainless steel(SS304)and tungsten carbide,under different water chemistries(i.e.,salinity and pH).Measured force profiles revealed that the attractive van der Waals(VDW)interaction contributed to the attachment of the calcium carbonate particles on substrate surfaces,while the repulsive electric double layer(EDL)interactions could inhibit the attachment behaviors.High salinity and acidic p H conditions of aqueous solutions could weaken the EDL repulsion and promote the attachment behavior.The adhesion of calcite particles with CR1018 and4140 substrates was much stronger than that with SS304 and tungsten carbide substrates.The bulk scaling tests in aqueous solutions from an industrial oil production process showed that much more severe scaling behaviors of calcite was detected on CR1018 and 4140 than those on SS304 and tungsten carbide,which agreed with surface force measurement results.Besides,high salinity and acidic p H can significantly enhance the scaling phenomena.This work provides fundamental insights into the scaling mechanisms of calcite at the nanoscale with practical implications for the selection of suitable antiscaling materials in petroleum industries.

Generating highly active oxide-phosphide heterostructure through interfacial engineering to break the energy scaling relation toward urea-assisted natural seawater electrolysis

Urea-assisted natural seawater electrolysis is an emerging technology that is effective for grid-scale carbon-neutral hydrogen mass production yet challenging.Circumventing scaling relations is an effective strategy to break through the bottleneck of natural seawater splitting.Herein,by DFT calculation,we demonstrated that the interface boundaries between Ni_(2)P and MoO_(2) play an essential role in the selfrelaxation of the Ni-O interfacial bond,effectively modulating a coordination number of intermediates to control independently their adsorption-free energy,thus circumventing the adsorption-energy scaling relation.Following this conceptual model,a well-defined 3D F-doped Ni_(2)P-MoO_(2) heterostructure microrod array was rationally designed via an interfacial engineering strategy toward urea-assisted natural seawater electrolysis.As a result,the F-Ni_(2)P-MoO_(2) exhibits eminently active and durable bifunctional catalysts for both HER and OER in acid,alkaline,and alkaline sea water-based electrolytes.By in-situ analysis,we found that a thin amorphous layer of NiOOH,which is evolved from the Ni_(2)P during anodic reaction,is real catalytic active sites for the OER and UOR processes.Remarkable,such electrode-assembled urea-assisted natural seawater electrolyzer requires low voltages of 1.29 and 1.75 V to drive 10 and600 mA cm^(-2)and demonstrates superior durability by operating continuously for 100 h at 100 mA cm^(-2),beyond commercial Pt/C||RuO_(2) and most previous reports.

Scaling Laws Behind Penetrative Turbulence:History and Perspectives

An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions.Past theoretical,numerical,and experimental studies on penetrative convection are reviewed,along with field studies providing insights into turbulence modeling.The physical factors that initiate penetrative convection,including internal heat sources,nonlinear constitutive relationships,centrifugal forces and other complicated factors are summarized.Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented,e.g.,the variational approach and quasilinear approach,which derive scaling laws embedded in penetrative turbulence.Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions.To better the model of penetrative turbulence towards a practical situation,new directions,e.g.,penetrative convection in spheres,and radiation-forced convection,are proposed.

Size-dependent vibration and buckling of porous functionally graded microplates based on modified couple stress theory in thermal environments by considering a dual power-law distribution of scale effects

In this study,the thermodynamic behaviors of the intrinsic frequency and buckling temperature of rectangular plates of functionally graded materials(FGMs)are explored based on the modified couple stress theory(MCST)and the novel dual powerlaw scale distribution theory.The effects of linear,homogeneous,and non-homogeneous temperature fields on the frequency and buckling temperature of FGM microplates are evaluated in detail.The results show that the porosity greatly affects the mechanical properties of FGM plates,reducing their frequency and flexural temperature compared with non-porous plates.Different temperature profiles alter plate frequencies and buckling temperatures.The presence and pattern of scale effect parameters are also shown to be crucial for the mechanical response of FGM plates.The present research aims to provide precise guidelines for the micro-electro-mechanical system(MEMS)fabrication by elucidating the complex interplay between thermal,material,and structural factors that affect the performance of FGM plates in advanced applications.

Integer multiple quantum image scaling based on NEQR and bicubic interpolation

As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.

Direct scaling of residual displacements for bilinear and pinching oscillators

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

Universal Scaling Laws in Quantum-Probabilistic Machine Learning by Tensor Network: Toward Interpreting Representation and Generalization Powers

The interpretation of representations and generalization powers has been a long-standing challenge in the fields of machine learning(ML)and artificial intelligence.This study contributes to understanding the emergence of universal scaling laws in quantum-probabilistic ML.We consider the generative tensor network(GTN)in the form of a matrix-product state as an example and show that with an untrained GTN(such as a random TN state),the negative logarithmic likelihood(NLL)L generally increases linearly with the number of features M,that is,L≃kM+const.This is a consequence of the so-called“catastrophe of orthogonality,”which states that quantum many-body states tend to become exponentially orthogonal to each other as M increases.This study reveals that,while gaining information through training,the linear-scaling law is suppressed by a negative quadratic correction,leading to L≃βM−αM^(2)+const.The scaling coefficients exhibit logarithmic relationships with the number of training samples and quantum channelsχ.The emergence of a quadratic correction term in the NLL for the testing(training)set can be regarded as evidence of the generalization(representation)power of the GTN.Over-parameterization can be identified by the deviation in the values ofαbetween the training and testing sets while increasingχ.We further investigate how orthogonality in the quantum-feature map relates to the satisfaction of quantum-probabilistic interpretation and the representation and generalization powers of the GTN.Unveiling universal scaling laws in quantum-probabilistic ML would be a valuable step toward establishing a white-box ML scheme interpreted within the quantum-probabilistic framework.

Complete Universal Scaling in First-Order Phase Transitions

Phase transitions and critical phenomena are among the most intriguing phenomena in nature and society.They are classified into first-order phase transitions(FOPTs)and continuous ones.While the latter shows marvelous phenomena of scaling and universality,whether the former behaves similarly is a long-standing controversial issue.Here we definitely demonstrate complete universal scaling in field driven FOPTs for Langevin equations in both zero and two spatial dimensions by rescaling all parameters and subtracting nonuniversal contributions with singular dimensions from an effective temperature and a special field according to an effective theory.This offers a perspective different from the usual nucleation and growth but conforming to continuous phase transitions to study FOPTs.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.

Effect of Y on Oxidation Behavior of Directionally Solidified Ni-Based Single-Crystal Superalloy

The effect of yttrium(Y)addition on the oxidation behavior of a Ni-based directionally solidified single-crystal superalloy is investigated in this study.Isothermal oxidation tests for samples with different levels of Y addition are conducted at 1100℃ in air.The Y content of the samples is determined by the actual pickup amount obtained from an Inductively Coupled Plasma-Atomic Emission Spectrometry test.It is discovered that the addition of Y increases the oxide resistance by the scale of an adhesive double-layer oxide,which is composed of Al_(2)O_(3) and spinel Ni(Cr,Al)_(2)O_(4).With 70 ppm of Y addition,the oxidation mass gain decreases from 12.6 g/m^(2) for the alloy without Y addition to 5.3 g/m^(2),and the oxidation rate decreases significantly.In addition,the internal nitride disappears after Y doping because of an increase in oxidation scale adherence and a decrease in oxidation products.In this study,the alloy with 660 ppm Y addition demonstrates the best oxidation resistance.

基于分数阶傅里叶变换和图像加权熵的chirp scaling算法

针对传统的基于傅里叶变换和匹配滤波实现的chirp scaling(CS)成像算法中多普勒参数随斜距变化以及成像分辨率低的问题,提出利用分数阶傅里叶变换(FRFT)对CS成像算法进行优化。首先建立斜视合成孔径雷达(SAR)回波信号模型,理论推导利用FRFT代替匹配滤波进行信号压缩。针对方位向最优旋转角的搜索问题,对得到的图像基于加权最小熵建立代价函数,利用动量法的梯度下降优化算法进行迭代计算,最终得到分辨率更高的SAR图像。为验证算法的有效性,分别在点目标仿真数据和实测SAR数据集上进行实验。结果表明,与传统CS成像算法相比,该算法的成像结果成像主瓣宽度更窄、旁瓣更低、成像更加清晰。

Comparative study of aeroacoustic performance of 1/8 and 1/1 pantographs coupled with cavity

The technology of pantograph sinking in the cavity is generally adopted in the new generation of high-speed trains in China for aerodynamic noise reduction in this region. This study takes a high-speed train with a 4-car formation and a pantograph as the research object and compares the aerodynamic acoustic performance of two scale models, 1/8 and 1/1, using large eddy simulation and Ffowcs Williams–Hawkings integral equation. It is found that there is no direct scale similarity between their aeroacoustic performance. The 1/1 model airflow is separated at the leading edge of the panhead and reattached to the panhead, and its vortex shedding Strouhal number(St) is 0.17. However, the 1/8 model airflow is separated directly at the leading edge of the panhead, and its St is 0.13. The cavity's vortex shedding frequency is in agreement with that calculated by the Rooster empirical formula. The two scale models exhibit some similar characteristics in distribution of sound source energy, but the energy distribution of the 1/8 model is more concentrated in the middle and lower regions. The contribution rates of their middle and lower regions to the radiated noise in the two models are 27.3% and 87.2%, respectively. The peak frequencies of the radiated noise from the 1/1 model are 307 and 571 Hz. The 307 Hz is consistent with the frequency of panhead vortex shedding, and the 571 Hz is more likely to be the result of the superposition of various components. In contrast, the peak frequencies of the radiated noise from the 1/8 scale model are 280 and 1970 Hz. The 280 Hz comes from the shear layer oscillation between the cavity and the bottom frame, and the 1970 Hz is close to the frequency at which the panhead vortex sheds. This shows that the scaled model results need to be corrected before applying to the full-scale model.