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[EN] Agri-food production must increase while food waste needs to be reduced for improving the position of farmers. To do so it is necessary to sustainably manage agri-food supply chains beginning with the crop planning decisions. Although the centralized approach has usually been adopted for this purpose, it can lead to unfair solutions due to inequitable distribution of profits among farmers causing their unwillingness to collaborate in the implementation of decisions made. To solve this, in this paper a novel centralized multi-objective mathematical programming model is proposed to support the sustainable crop planning definition for a region that jointly optimize three objectives aligned to the sustainability aspects: supply chain profits maximization (economic objective), waste minimization (environmental objective) and unfairness among farmers minimization (social objective), being the last two objectives novel in the crop planning literature. It has also shown the conflicting nature of the three objectives finding trade-offs among them. Other novelties of this proposal are: (1) anticipation of operative decisions (such as harvest, transport, sale, clearance sale, waste and unmet demand) when defining the crop planning, (2) possibility of clearing the oversupply of crops as a means of increasing the farmers' profits and reducing waste, and (3) the modelling of a agri-food supply chain characterized by the lack of intermediaries between farmers and retailers, fostering the freshest product delivery and farmers' power position. The model is solved by applying the weighted sum method concluding that the crop waste generated along the chain and the unfairness among farmers can be considerably reduced by little decreasing the optimal SC profits., We acknowledge the support of the Project 691249, RUCAPS: "Enhancing and implementing knowledge based ICT solutions within high risk and uncertain conditions for agriculture production systems", funded by the European Union's research and innovation programme under the H2020 Marie Sklodowska-Curie Actions.

In the last decade, food and drink supply chain management has become an important part of global operations strategy. The global food and drink industries (FDIs) is establishing supply chain opera...

Ring-opening copolymerization (ROCOP) of epoxide/anhydride/CO2 for the synthesis of CO2-based copolymers is a promising process, because CO2 is an abundant, nontoxic, and low-cost monomer and has b...

Phosphazenes as organocatalysts for the synthesis of polymers have evolved to powerful tools, and their catalytic performances highly depend on the basicity and molecular structure (size and shape). Therefore, designing phosphazenes with tunable basicity and molecular structure is greatly promising for the development of organocatalysts with improved catalytic properties, for example, high activity and selectivity. In this contribution, 2,4,6-tris[tri(dimethylamino)iminophosphorane]-1,3,5-triazine (C

The agri-food supply chain (AFSC) is an extremely complex structure that comprises a series of events from farm-to-fork. Additionally, there is a wide range of information and material flows that require to be managed, which are seen as the knowledge flow in the AFSCs. It is expected that the use of knowledge governance mechanisms (KGMs) will help in enhancing AFSC performance. To examine the impact of KGMs on AFSC performance, a mixed methods research design was applied. First, semi-structured interviews were conducted to collect data. Then, themes were generated through thematic analysis. Afterwards, relationships between KGMs and AFSC performance were built by using total interpretive structural modelling (TISM). Finally, questionnaire-based structured interviews were undertaken to evaluate the empirical and theoretical findings further. The research results indicate that trust-, reciprocity-, market-, and contract-based KGMs have positive effects on product quality, efficiency, flexibility, responsiveness, and process quality of AFSC. Furthermore, market-based KGM, located in the lowest level in the TISM hierarchy, should be given additional focus due to its role as a key force driving the higher level of AFSC performance and other KGMs. The findings provide AFSC practitioners with useful guidance on how the relationships between KGMs and AFSC performance should be managed to improve the performance of AFSC.

The Wangshi Group faithfully records the Late Cretaceous palaeogeographic environment and tectonic evolution of the East Asian continental margin. Here, we reconstruct a four-stage evolution model ...

Static environment is a prerequisite for most existing vision-based SLAM (simultaneous localization and mapping) systems to work properly, which greatly limits the use of SLAM in real-world environments. The quality of the global point cloud map constructed by the SLAM system in a dynamic environment is related to the camera pose estimation and the removal of noise blocks in the local point cloud maps. Most dynamic SLAM systems mainly improve the accuracy of camera localization, but rarely study on noise blocks removal. In this paper, we proposed a novel semantic SLAM system with a more accurate point cloud map in dynamic environments. We obtained the masks and bounding boxes of the dynamic objects in the images by BlitzNet. The mask of a dynamic object was extended by analyzing the depth statistical information of the mask in the bounding box. The islands generated by the residual information of dynamic objects were removed by a morphological operation after geometric segmentation. With the bounding boxes, the images can be quickly divided into environment regions and dynamic regions, so the depth-stable matching points in the environment regions are used to construct epipolar constraints to locate the static matching points in the dynamic regions. In order to verify the preference of our proposed SLAM system, we conduct the experiments on the TUM RGB-D datasets. Compared with the state-of-the-art dynamic SLAM systems, the global point cloud map constructed by our system is the best.

Supported gold catalysts play a crucial role in the chemical industry; however, their poor on-stream stability because of the sintering of the gold nanoparticles restricts their practical application. The strong metal-support interaction (SMSI), an important concept in heterogeneous catalysis, may be applied to construct the structure of catalysts and, hence, improve their reactivity and stability. Here we report an ultrastable Au nanocatalyst after calcination at 800 °C, in which Au nanoparticles are encapsulated by a permeable TiOx thin layer induced by melamine under oxidative atmosphere. Owning to the formed TiOx overlayer, the resulting Au catalyst is resistant to sintering and exhibits excellent activity and stability for catalytic CO oxidation. Furthermore, this special strategy can be extended to colloidal Au nanoparticles supported on TiO2 and commercial gold catalyst denoted as RR2Ti, providing a universal way to engineer and develop highly stable supported Au catalysts with tunable activity., Sintering-resistant Au nanoparticles are highly desirable due to their low Tammann temperature. Here, the authors report an ultrastable titania-supported Au nanocatalyst through an encapsulation strategy under oxidative atmosphere.

We demonstrated that the dimeric 1-tert-butyl-2,2,4,4,4-pentakis(dimethylamino)-2Λ5, 4Λ5-catenadi(phosphazene) supported on polystyrene (PS-t-BuP2) was an efficient and recyclable catalyst for the ring-opening polymerization (ROP) of δ-valerolactone (δ-VL). The heterogeneous catalyst PS-t-BuP2 could be recycled and reused for five consecutive cycles without significant decrease of catalytic activity. The monomer conversions maintained between 79% and 85% for five cycles. Using BnOH as initiator, the produced polyvalerolactones (PVLs) had controlled molecular weights (MWs) and narrow MW distributions (Đ), and the products were free of catalyst by simple filtration. The 1H NMR and MALDI-TOF characterizations of the obtained PVLs clearly indicated the presence of the initiator residue at the chain end.

Recycling of construction and demolition wastes (C&DWs) can not only address environmental pollution problems but can also produce abundant profits. Using repeatedly recycled coarse aggregate (RCA) to prepare structural concrete is an important means for addressing the economic, environmental, and social problems caused by the shortage of natural aggregate resources. In this study, the durability of three generations of 100% repeatedly recycled aggregate concrete (RAC) was investigated to evaluate the effect of using RCA from various recycling cycles. The first-generation RCA was purchased, while the second and third generations of RCA were prepared in the laboratory, based on the principle of equal carbonization depth. All the aggregates were crushed and sieved to eliminate the difference in size distribution between the RAC mixes in each cycle. The results show that the qualities of the RCA that affect the durability of concrete deteriorate with increasing number of recycling cycles. Durability metrics of the RAC (freeze-thaw resistance, chloride ion permeability coefficient, and carbonization depth) decrease gradually with increasing number of recycling cycles. However, the RCA in each cycle could meet the requirements for structural concrete aggregates, and concrete utilizing RCA can be designed as structural concrete with a life span of at least 50 y.

The optical manipulation of tiny objects is significant to understand and to explore the unknown in the microworld, which has found many applications in materials science and life science. Physically speaking, these technologies arise from direct or indirect optomechanical coupling to convert incident optical energy to mechanical energy of target objects, while their efficiency and functionalities are determined by the coupling behavior. Traditional optical tweezers stem from direct light-to-matter momentum transfer, and the generation of an optical gradient force requires high optical power and rigorous optics. As a comparison, the opto-thermophoretic manipulation techniques proposed recently originate from high-efficiency opto-thermomechanical coupling and feature low optical power. Through rational design of the light-generated temperature gradient and exploring the mechanical response of diverse targets to the temperature gradient, a variety of opto-thermophoretic techniques were developed, which exhibit broad applicability to a wide range of target objects from colloid materials to biological cells to biomolecules. In this review, we will discuss the underlying mechanism of thermophoresis in different liquid environments, the cutting-edge technological innovation, and their applications in colloidal science and life science. We also provide a brief outlook on the existing challenges and anticipate their future development.

Remote manipulation of a micromachine under an external magnetic field is significant in a variety of applications. However, magnetic manipulation requires that either the target objects or the fluids should be ferromagnetic or superparamagnetic. To extend the applicability, we propose a versatile optical printing technique termed femtosecond laser-directed bubble microprinting (FsLDBM) for on-demand magnetic encoding. Harnessing Marangoni convection, evaporation flow, and capillary force for long-distance delivery, near-field attraction, and printing, respectively, FsLDBM is capable of printing nanomaterials on the solid-state substrate made of arbitrary materials. As a proof-of-concept, we actuate a 3D polymer microturbine under a rotating magnetic field by implementing γ-Fe2O3 nanomagnets on its blade. Moreover, we demonstrate the magnetic encoding on a living daphnia and versatile manipulation of the hybrid daphnia. With its general applicability, the FsLDBM approach provides opportunities for magnetic control of general microstructures in a variety of applications, such as smart microbots and biological microsurgery.

Knowledge has long been recognised as a valuable asset to individuals, organisations and economy, subsequently knowledge management (KM) has been a well-established area of research. Existing research has developed various classification schemes for knowledge, and a great number of KM process and lifecycle models have been proposed over the last few decades. In particular, knowledge transfer and sharing has received great attention. However, majority of existing work has focused on knowledge sharing within the same organisation or community where people have a shared sense of identity, values and some common practice, hence knowledge process and learning is within relatively homogeneous groups. There is inadequate research to address the issue of knowledge boundaries and approaches to knowledge mobilisation spanning across knowledge boundaries. The knowledge boundaries can erect significant barriers to knowledge sharing and flowing especially in value chain context where there are a great number of players from different domains, with varied level of knowledge, having different and possibly conflicting interests - participating in knowledge sharing activities. This paper will explore how such knowledge boundaries can be identified and how knowledge gaps among different value chain players can be closed by using appropriate boundary-crossing mechanisms. A multi-perspective knowledge mobilisation framework is proposed. Example applications of the knowledge mobilisation framework in agri-food value chain will be illustrated, based on the most recent developments from an EU collaborative project, RUC-APS (standing for Risk and Uncertain Conditions in Agriculture Production Systems), which is funded by European Commission’s Horizon 2020 RISE programme., Laboratorio de Investigación y Formación en Informática Avanzada

[EN] Crop-based Agri-food Supply Chains (AFSCs) are complex systems that face multiple sources of uncertainty that can cause a significant imbalance between supply and demand in terms of product varieties, quantities, qualities, customer requirements, times and prices, all of which greatly complicate their management. Poor management of these sources of uncertainty in these AFSCs can have negative impact on quality, safety, and sustainability by reducing the logistic efficiency and increasing the waste. Therefore, it becomes crucial to develop models in order to deal with the key sources of uncertainty. For this purpose, it is necessary to precisely understand and define the problem under study. Even, the characterisation process of this domains is also a difficult and time-consuming task, especially when the right directions and standards are not in place. In this chapter, a Conceptual Framework is proposed that systematically collects those aspects that are relevant for an adequate crop-based AFSC management under uncertainty., Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015

Wireless sensor networks, as a multi-hop self-organized network system formed by wireless communication, are vulnerable to malware diffusion by breaking the data confidentiality and service availability, owing to their low configuration and weak defense mechanism. To reveal the rules of malware diffusion in the really deployed wireless sensor networks, we propose a model called Malware Diffusion Based on Cellular Automaton to describe the dynamics of malware diffusion based on cellular automaton. According to the model, we first analyze and obtain the differential equations, which can reflect the various state dynamics of sensor nodes with cellular automaton. Then, we attain the equilibrium points of the model Malware Diffusion Based on Cellular Automaton to determine the threshold for whether malware will diffuse or die out in wireless sensor networks. Furthermore, we compute the basic regeneration number of the model Malware Diffusion Based on Cellular Automaton using the next-generation matrix and prove the stability of the equilibrium points. Finally, via experimental simulation, we verify the effectiveness of the model Malware Diffusion Based on Cellular Automaton, which can provide administrators with the theoretical guidance on suppressing malware diffusion in wireless sensor networks.

Organic small-molecule-based photothermal agents such as cyanine dyes have received increasing attention in developing novel cancer therapies with potential clinical utility but suffer from poor stability, low photothermal efficiency, and limited accumulation at tumor sites in molecular forms. Self-assembly of small-molecule dyes into supramolecular assemblies may address these concerns by controlling the molecular organization of dye monomers to form structures of a higher order. Among them, H-aggregates of dyes favor face-to-face contacts with strongly overlapping areas, which always have a negative connotation to exhibit low or no fluorescence in most cases but may emanate energy in nonradiative forms such as heat for photothermal cancer therapy applications. Here, the synergistic self-assembly of cyanine dyes into H-aggregates is developed as a new supramolecular strategy to fabricate small-molecule-based photothermal nanomaterials. Compared to the free cyanine dyes, the H-aggregates assembled from pyrene or tetraphenylethene (TPE) conjugating cyanine exhibit the expected absorption spectral blue shift and fluorescence self-quenching but unique photothermal properties. Remarkably, the obtained H-aggregates are saucer-shaped nanoparticles that exhibit passive tumor-targeting properties to induce imaging-guided photothermal tumor ablation under irradiation. This supramolecular strategy presented herein may open up new opportunities for constructing next-generation small-molecule-based self-assembly nanomaterials for PTT cancer therapy in clinics.

Phosphazenes have attracted considerable attention in the field of ring-opening polymerization (ROP) of cyclic esters. However, the application of phosphazenes as catalyst is subject to a trade-off between activity and selectivity (chain propagation versus transesterification/back-biting reaction, e.g., controlled polymerization). Despite extensive research efforts, the development of a new catalytic system having concurrent high activity and selectivity remains a great challenge. In this work, we report that the binary organocatalytic system comprised of cyclic trimeric phosphazene base (CTPB) and ureas shows both of high activity and selectivity for the ROP of e-caprolactone (e-CL) and δ-valerolactone (δ-VL) in the presence of alcohol as initiator. It is found that the introduction of ureas would significantly increase the catalytic selectivity during ROP without sacrificing the catalytic activity of CTPB. Moreover, the polymerizations catalyzed by the title catalytic system exhibit immortal characteristics and thus thousands equivalent of monomer could be converted to polymer efficiently with desired MWs and microstructures. Linear diblock copolymer AB and star copolymers (AB)3 with three identical diblock arms could be readily synthesized by sequential copolymerization using different alcohols as initiators.

Degradable long-chain aliphatic polyesters are promising alternatives to polyolefins. The ring-opening polymerization (ROP) of ω-pentadecalactone (PDL) enables the synthesis of aliphatic polyesters with melting temperature close to low-density polyethylene (LDPE). However, this ROP reaction is of great challenge because of low ring strain of the PDL monomer. The occurrence of intra- and intermolecular transesterification reactions during ROP made it difficult to prepare well-defined block copolyesters for advanced properties. In this context, cyclic trimeric phosphazene base (CTPB) in combination with benzyl alcohol (BnOH) was proved to be an efficient initiator system for ROP of PDL, showing an excellent polymerization rate (TOF up to 600 h–1) at 80 °C. Well-defined diblock copolyesters, i.e., PPDL-b-PLLA, can be easily synthesized by sequential addition of PDL and l-lactide (L-LA). In contrast, sequential addition of PDL and e-caprolactone (CL) or δ-valerolactone (VL) only led to the random copolyesters...

Polysiloxanes containing phenyl functional groups are a class of promising polymer materials with enhanced low-temperature flexibility, high-temperature stability and great damping properties. In this context, organic cyclic trimeric phosphazene bases (CTPBs) have been proved to be highly efficient for the ring-opening polymerization (ROP) of octamethylcyclotetrasiloxane (D4) and the copolymerization of D4 with octaphenylcyclotetrasiloxane (P4) under mild conditions. The polymerizations are fast and the resulting polymers have high molecular weights (Mn up to 1353 kg mol−1). The molecular structures of the obtained copolysiloxanes were characterized by 1H NMR and 29Si NMR, which demonstrate that as high as 64 mol% diphenyl siloxane units can be incorporated within the copolysiloxane chain. Remarkably, copolysiloxanes with different contents of the diphenyl siloxane group are found free of T-branches and Q-branches based on the 29Si NMR analysis, indicating a good controlled ROP by the current organocatalytic system. DSC analysis shows no crystallization exotherm or melting endotherm in the range of −70 °C to 50 °C for all the copolysiloxanes, confirming that incorporation of diphenyl groups successfully suppresses the undesirable crystallization of polydimethylsiloxane. Moreover, the thermal stability of copolysiloxanes was evaluated by TGA, showing dramatically enhanced thermal stability with the increment of the diphenyl siloxane content.

The chemosynthesis of bio-renewable poly(γ-butyrolactone) (PγBL) with a high molecular weight via ring opening polymerization (ROP) of non-strained γ-butyrolactone (γBL) remains a big challenge although several catalysts have been developed in the past two years. In this contribution, we reported the efficient ROP of γBL using a strong base/urea binary synergistic catalytic system. Either an alkaline alkoxide or organophosphazene superbase was used as a strong base in this study. The base/urea binary catalyst showed high catalytic activity and high selectivity for ring opening relative to transesterification toward the ROP of γBL, and the organophosphazene superbase in combination with urea showed better catalytic activity compared to an alkaline alkoxide/urea system. The effects of bases, ureas, and reaction conditions on monomer conversions and resultant molecular weights of PγBL were systematically investigated. A PγBL homopolymer with a high molecular weight up to 35.0 kDa was synthesized using a combination of a cyclic trimeric phosphazene superbase (CTPB) and suitable ureas with electron-donating substituents. The thermal stabilities of PγBL improved dramatically with an increase in its molecular weight. The obtained PγBL exhibited unprecedented superior mechanical properties with an elongation at break of 858 ± 79%, which paves the way for its practical applications.

Liziping Tunnel is located in the southwestern mountainous area of China. The majority of the support structures in the tunnel have failed shortly after construction completion. The goals of this study are to reveal the failure cause of the given support structure, and to develop a quantitative analysis method to optimize scheme of support design. According to the parallel model, the deformation-load relation function of combined support structure (CSS) of anchor bolt-spray are derived from the bearing arch mechanism. Through numerical simulations, the ground reaction curve (GRC) of country rock is obtained, along with the longitudinal deformation profile (LDP) reflecting influences of both installed supports structure and construction technology. The stability factors of the installed support structure under various envisaged construction schemes are estimated by using the convergence-confinement method (CCM). The results indicate that it is possible to avoid the failure of the given support structure if the construction technology is slightly adjusted during construction. Derived from the above research, the empirical method based on the rock mass classification is expanded to be a quantitative analysis approach and can consider more contributing factors than ever, through embedding the convergence-confinement algorithm into the empirical design method of support scheme and with the help of simulation computation technology.

Porous organic polymers (POPs) have been considered as prominent adsorbents for volatile iodine. So far, both crystalline and amorphous POPs have accomplished excellent iodine capture capability. Considering the difficulty and challenges in preparing perfect crystalline POPs, more explorations into developing versatile amorphous POPs are needed. Herein, amorphous POPs based on the Schiff-base reaction were designed and synthesized for volatile iodine removal. Four amorphous POPs products named as NDB-H, NDB-S, ADB-HS, and ADB-S obtained under different solvothermal conditions were investigated in terms of their morphologies, porosity, and their iodine enrichment performance in detail. It is noteworthy that excellent efficiency for removing iodine vapor was acquired for NDB-S (≈425 wt %), ADB-HS (≈345 wt %), and ADB-S (≈342 wt %). Remarkably, NDB-H exhibited an iodine capture capacity up to ≈443 wt %. Excellent reusability was obtained as well. Amorphous NDB-H has accomplished an extremely high iodine capture performance, illustrating the great chance to exploit versatile amorphous POPs for iodine enrichment and removal based on Schiff-base chemistry.

Phosphazene base is an important organocatalyst in polymer chemistry owing to its high activity and versatility. In this contribution, we demonstrate that cyclic trimeric phosphazene base (CTPB) can catalyze stereoselective ring-opening polymerization (ROP) of rac-lactide (rac-LA) to produce isotactic stereoblock PLA (Pi up to 0.93). The polymerizations are highly controlled, as evidenced by linear relationship between molecular weights (MW) and monomer conversions and the narrow dispersity (Đ = Mw/Mn) of the resulted polymers with high fidelity of end groups. The investigations on polymerization parameters show that the tacticity of produced PLA depends on the polymerization temperatures and solvents, while the kinetic studies reveal a faster rate for ROP of l-LA as compared to rac-LA under same conditions. Based on these results, the chain end control mechanism is proposed to explain the production of isotactic stereoblock PLA from rac-LA by an achiral catalyst.

The purpose of this paper is to investigate the role of trade credit and quantity discount in supply chain coordination when the sales effort effect on market demand is considered. In this paper, we consider a two-echelon supply chain consisting of a single retailer ordering a single product from a single manufacturer. Market demand is stochastic and is influenced by retailer sales effort. We formulate an analytical model based on a single trade credit and find that the single trade credit cannot achieve the perfect coordination of the supply chain. Then, we develop a hybrid quantitative analytical model for supply chain coordination by coherently integrating incentives of trade credit and quantity discount with sales effort effects. The results demonstrate that, providing that the discount rate satisfies certain conditions, the proposed hybrid model combining trade credit and quantity discount will be able to effectively coordinate the supply chain by motivating retailers to exert their sales effort and increase product order quantity. Furthermore, the hybrid quantitative analytical model can provide great flexibility in coordinating the supply chain to achieve an optimal situation through the adjustment of relevant parameters to resolve conflict of interests from different supply chain members. Numerical examples are provided to demonstrate the effectiveness of the hybrid model.

The Common Land Model (CoLM) has been updated to a new version, but the lake scheme in CoLM (CoLM-Lake) has never been evaluated. This paper introduces the structure and physical processes of CoLM-Lake, and evaluates its simulation performance through the observations from 10 lakes over different regions. It also discusses the sensitivities of simulated results to some important parameters in the model. Results show that CoLM-Lake performs very well over the three shallow lakes (Kossenblatter, Taihu and Sparkling Lake) where the model accurately captures the magnitudes and seasonal variations of lake surface temperature, turbulent fluxes, and vertical thermal structure. The freeze-thaw cycle of Sparkling Lake is reproduced at a reasonable level as well. Also, CoLM-Lake show acceptable performance in simulating vertical structures and their variations for deep lakes, although the vertical mixing strength remains underestimated. The biases of surface temperatures in the Great Lakes of North America are relatively larger, but the magnitudes and seasonal variations in temperature fall within a reasonable range. In general, CoLM-Lake is suitable for the simulation of lake physical processes on the global scale. The simulated results have strong sensitivities to some parameters with values that have large uncertainties. The surface roughness lengths determine the amounts of turbulent fluxes which are emitted into the atmosphere, and thus affecting the simulated lake surface temperature. Although the surface roughness based on the dynamic diagnosis of lake properties in the model has made the simulated turbulent fluxes very accurate, the further adjustment of surface roughness can improve the realism of the simulated turbulent fluxes and temperature on lake surface. Lake depth, optical extinction coefficient and thermal diffusivity affect the simulated lake thermal structure from different angles. Lake depth determines the amount of water in vertical mixing; optical extinction coefficient determines the distribution of solar radiation at different lake depths; and thermal diffusivity determines the simulated vertical mixing strength that a lake can achieve. Either a larger lake depth, a smaller extinction coefficient, or a larger thermal diffusivity enables a lake to transfer and store more heat internally, thereby increasing lake thermal inertia, reducing daily and seasonal variations of lake water temperatures, and causing late freeze-up dates in winter. Therefore, the biases of simulated lake thermal structure can be corrected by adjusting the above three parameters. Note that lake depth and optical extinction coefficient are lake inherent attributes, and thus it is important to collect high-resolution and high-precision data for these two parameters in the future. The modification of thermal diffusivity should focus on increasing simulated vertical mixing strength for deep lakes, while the relatively accurate simulation for shallow lakes should be maintained, and thus more complex processes in deep lakes need to be considered in the model than simply multiplying the background thermal diffusivity of entire lake. The temperature at which lake water reaches maximum density is affected by lake salinity, and adjusting this temperature also improves simulated results. Hence, the effects of lake salinity on lake water physical properties should be considered in the development of future lake schemes. As three-dimensional lake schemes become more sophisticated, it is increasingly important to couple them into regional and global climate models. However, the description of important processes such as lake vertical mixing, phase change and snow hydrology are still too simple in one-dimensional schemes, and thus the upper limit of accuracy that one-dimensional schemes can achieve in deep lake simulations remains unclear, and the necessity of coupling the three-dimensional schemes with climate models is under dispute. If one-dimensional schemes are found to have better performance in simulating the characteristics of deep lakes, then the large amount of computational resources that need to be consumed to run three-dimensional models can be saved. Therefore, developing one-dimensional lake schemes at current stage is extremely important.

Exogenous dietary advanced glycation endproducts (AGEs) have been suggested to increase health risk. Oral use tobacco products are used as substitute for cigarette smoking due to their “reduced risk” and no second-hand smoke. They may increase AGEs intake due to their oral form of use. However, research on AGEs in oral use tobacco products is limited. A HPLC-MS/MS method was developed to survey free and total Ne-Carboxymethyllysine (CML) and Ne-Carboxyethyllysine (CEL) levels in different oral use tobacco products in this work. HPLC conditions, such as HPLC column and mobile phase additive were optimized. With the optimized conditions, analytical method performance for three types of oral use tobacco matrix (i.e. CRP2, gum and dissolvable tobacco product) was characterized. CML and CEL showed higher recovery in all three sample matrix, and the recovery of CML and CEL was in the range of 88.7%-120%, 90.0%-110%, respectively. The developed method showed good intra-day and inter-day precision with RSDs for both free and total CML (or CEL) of less than 9.7%. Limit of detections (LODs) of CML and CEL were 0.36 and 0.25 ng/mL, respectively. Sample analysis for 21 oral use tobacco products was conducted with the developed method. As for oral use tobacco products, total CML and CEL was much more than those of their free state, indicating that CML and CEL exist mainly protein adducts. In addition, the content of CML was higher than that of CEL for both free and total state. Oral use tobacco products I (i.e. dry snuff, moist snuff, suns and chew) had the highest CML (i.e. 44.89–608.69 µg/g) and CEL (i.e. 15.98–77.70 µg/g) levels, compared with oral use tobacco products II (i.e. gum) with the least CML (i.e. 0.7–0.8 µg/g) and CEL (i.e. 0.14–0.18 µg/g) levels. It mainly depended on the composition and processing technology of oral use tobacco products. Both total CML and CEL showed linear relationship with lysine and total amino acid (i.e. R > 0.77). However, there was no linear relationship between total CML (or CEL) and total reducing carbohydrates (i.e. R

Making the right decisions for food supply chain is extremely important towards achieving sustainability in agricultural businesses. This paper explores that knowledge sharing to support food supply chain decisions to achieve lean performance (i.e. to reduce/eliminate non-value-adding activities, or “waste” in lean term). The focus of the paper is on defining new knowledge networks and mobilisation approaches to address the network and community nature of current supply chains. Based on critical analysis of the state-of-the-art in the topic area, a knowledge network and mobilisation framework for lean supply chain management has been developed. The framework has then been evaluated using a case study from the food supply chain. Analytic Hierarchy Process (AHP) has been used to incorporate expert's view on the defined knowledge networks and mobilisation approaches with respect to their contribution to achieving various lean performance objectives. The results from the work have a number of implications for current knowledge management and supply chain management in theory and in practice.

A new superbase, cyclic trimeric phosphazene base (CTPB), was prepared with high yield and purity. In the presence of alcohol, the CTPB can serve as highly efficient organocatalyst for ring-opening polymerization (ROP) of "non-polymerizable" γ-butyrolactone to offer well-defined poly(γ-butyrolactone) with high conversions (up to 98%) at -60 °C. The produced polymers have high molecular weights (up to 22.9 kg·mol-1) and low polydensity distributions (1.27-1.50). NMR analysis of initiation process and the structural analysis of resulted polymers by MALDI-TOF suggest an activating initiator mechanism that is responsive for linear polymer as only product with designed BnO/H chain ends.

Purpose Knowledge management is crucial for enterprise resource planning (ERP) systems implementation in real industrial environments, but this is a highly demanding task. The purpose of this paper is to examine the effectiveness of knowledge identification, categorisation and prioritisation that contributes to achieving ERP implementation success. Design/methodology/approach This study adopts a mixed methods approach; a qualitative phase to identify and categorise knowledge types and sub-types; conducting in-depth interviews with ERP clients and implementation partners; plus a quantitative phase to prioritise knowledge types and sub-types based on their contribution to achieving ERP success for business performance improvement. An analytic hierarchy process-based questionnaire was used to collect empirical data for the quantitative phase. Findings This study has been able to identify, categorise and rank various types of ERP-related knowledge based on in-depth interviews and survey responses from both ERP clients and implementation partners. In total, 4 knowledge types and 21 sub-types were ranked based on their contribution to achieving ERP success; 4 variables of information quality, systems quality, individual impact and organisational impact were used to measure ERP success. Originality/value The empirical findings demonstrate exactly what kinds of knowledge need to be managed, enabling knowledge prioritisation when a client organisation or an implementation partner steps into an ERP implementation, in a real industrial environment.

In stability reliability analysis of complicated geotechnical structure, the analytical expression of limit state function (LSF) is often highly non-linear, implicit or indefinable. This results in the classical second-order reliability method (SORM) not to be applied directly. The present study is devoted to eliminating this dilemma. Firstly, universal solving methods of partial derivatives of LSF to its basic random variables are derived using finite difference principle. Secondly, the universal methods supplement SORM to substitute for Newton–Leibniz derivation method; then, an improved algorithm of SORM is developed in conjunction with Breitung’s notion. Thirdly, reliability evaluation of three examples with explicit/implicit LSF are carried out, an available constant quantity of step length coefficient is sought out in the independent standard normal space (u-space) through theoretical inference and trial. Fourthly, an extensive SORM (ESORM) that does not resort to any abstruse mathematic the...

According to the vibration characteristics of the organ of Corti (OC), seven hypotheses are made to simplify the structure of the model, and a mechanical OC model is established. Using the variational principle, a displacement analytical expression is solved under a certain pressure. The results are in good agreement with experimental data, showing the validity of the formula. Combined with the damage caused by noise in clinic, it is found that the hardening of outer hair cells and outer stereocilia can lead to loss of hearing and generation of threshold shift. In addition, the results show that high frequency resonance occurs at the bottom of the basilar membrane (BM), and low frequency resonance occurs at the top of the BM. This confirms the frequency selective characteristics of the BM. Further, using this formula can avoid interference of the envi- ronment and the technical level of the test personnel, and can evaluate performance of the OC objectively.

Agri-food supply chains (AFSCs) are becoming more complex in structure, and thus more susceptible to different vulnerabilities and risks. Therefore, to enhance performance, we need to manage the risks in AFSCs effectively and efficiently. This study analyses various AFSC risks using a multi-method approach, including thematic analysis, total interpretive structural modelling (TISM) and fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis. Based on the empirical data collected from experienced AFSC practitioners and following thematic analysis, eight categories of risk and 16 risk factors were identified as important. Furthermore, the interrelationships among the identified risks were built using TISM. Finally, the identified risks were classified into various categories according to their dependence and driving power using fuzzy MICMAC analysis. The research results indicate that the weather-related and political risks have the highest driving power and are located at the lowest level in the TISM hierarchy. These risks have a high tendency to disturb the whole flow of AFSC and so should be managed effectively. This study advances existing literature on identifying risk factors, defining interrelations between different AFSC risks, and determining the key risks. The risk analysis results can help AFSC practitioners in AFSC to identify, categorise and analyse the risks.

Part 13: Digital Transformation in Food and Agribusiness; International audience; Simulations help to understand and predict the behaviour of complex phenomena's, likewise distributed socio-technical systems or how stakeholders interacts in complex domains. Such domains are normally based on networked based interaction, where information, product and decision flows comes in to play, especially under the well-known supply chains structures. Although tools exist to simulate supply chains, they do not adequately support multiple stakeholders to collaboratively create and explore a variety of decision-making scenarios. Hence, in order to provide a preliminary understanding on how these interaction affects stakeholders decision-making, this research presents an study, analysis and proposal development of robust platform to collaboratively build and simulate communication among supply chain. Since realistic supply chain behaviours are complex, a multi-agent approach was selected in order to represent such complexities in a standardised manner. The platform provides agent behaviours for common agent patterns. It provides extension hotspots to implement more specific agent behaviour for expert users (that requires programming). Therefore, as key contribution, technical aspects of the platform are presented, and also the role of multi-level supply chain scenario simulation is discussed and analysed, especially under de context of digital supply chain transformation in the agri-food context. Finally, we discuss lessons learned from early tests with the reference implementation of the platform.

© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. Knowledge retention (k-retention) is vital for various enterprise resource planning (ERP) implementations in small and medium-sized enterprises (SMEs), though it is a highly demanding and challenging task. The aim of this paper is to investigate different types of approaches to k-retention and factors influencing k-retention in SMEs. Our study adopts a grounded theory approach with cases based on 12 ERP implementations in UK SMEs. We analyze our data using thematic analysis. The findings reveal specific elements that support the k-retention of ERP package knowledge and business process knowledge. These elements are: k-retention tools, documentation, human capital and the understanding of k-retention challenges. In addition to insights from these aspects, our study reveals two additional factors (project management and organizational culture) that influence ERP package k-retention and business process k-retention. Based on these findings, we develop an ERP k-retention (EKR) framework that can be utilized by SMEs which are considering implementing ERP systems, to facilitate knowledge retention during implementation.

An agri-food value chain (VC) represents a set of activities aimed at delivering highly valuable products to the market. Due to the diversity of actors in the agri-food VCs ́ accumulated knowledge is typically situated within the boundaries of each entity of the VC. Hence, the question is how to improve knowledge sharing in agri-food VC, or more specifically how can knowledge flow and mobilize among different actors in the VC. To answer this question, we present a decision support system (DSS) for evaluation of knowledge sharing crossing boundaries in agri-food VC. The proposed DSS is developed through two phases: (i) identification of the most common knowledge boundaries by using machine learning and ontology technologies; (ii) transformation of the obtained ontology into a DSS for the evaluation of existing knowledge boundaries. In particular, the developed DSS helps in identifying, evaluating and providing directions for improvement of the knowledge sharing crossing boundaries in agri-food VC. We apply the DSS to evaluate three real VCs: a tomato VC in Argentina, a Chinese leaf VC in China and a brassica VC in the UK. The comparative analysis across the three varied case studies and their evaluation with the proposed DSS lead to more insights into knowledge-based decisions that a particular VC needs to address to improve its knowledge flow, in particular, to obtain insights in the transparency and interoperability of data and knowledge crossing boundaries in agri-food VCs., Laboratorio de Investigación y Formación en Informática Avanzada

Agri-food value chain is an area of significant importance because of providing sustainable, affordable, safety and sufficient food, feed, fibre and fuel to consumers, it is critical to ensure these value chains running smoothly and successfully by applying advanced internet technologies. Blockchain technology is a new digital technological approach underpinned by the Industry 4.0 to ensuring data integrity and preventing tampering and single point failure through offering fault-tolerance, immutability, trust, transparency and full traceability of the stored transaction records to all agri-food value chain partners. This paper used systematic literature network analysis to review the state-of-the-art blockchain technology including its recent advances, main applications in agri-food value chain and challenges from a holistic perspective. The findings suggest that blockchain technology together with advanced information and communication technology and internet of things have been adopted for the improvement of agri-food value chain management in four main aspects: traceability, information security, manufacturing and sustainable water management. Six challenges have been identified including storage capacity and scalability, privacy leakage, high cost and regulation problem, throughput and latency issue, and lack of skills. Based on the critical analysis of literature, research gaps and future research directions are proposed in this paper regarding the applications and challenges of blockchain technology in agri-food value chain management. This study makes contributions to the extant literature in the field of agri-food value chain management by discovering the potential of blockchain technology and its implications for agri-food value chain performance improvements such as food safety, food quality and food traceability.

Fibrous supercapacitors with high energy/power densities are important energy supply systems for smart wearable devices. Kinds of yarn-cathodes were fabricated, however, high performance anode materials have not been developed to match with the reported cathodes. Additionally, the (volumetric/area) capacitance of yarn-supercapacitors are often limited by less active material deposition, as the yarn is not resistant to high temperature, and the metal conductive-layer is not corrosion resistant. So, a high mass-loading anode with high volumetric performance has not been fabricated. In this study, we report a novel kind of Fe2O3 nanowires arrays on Ni-coated textiles anodes to solve this problem. The nickel layer deposited on the low-cost polyester yarn was applied as high-conductivity current collector, and vertically aligned Fe2O3 nanowires grown on the nickel layer with high mass loading were used as high performance active materials (Fe2O3//Ni//Yarn). It is worth noting that the Fe2O3//Ni//Yarn-based anodes exhibit a high specific capacitance of 54.2 F cm−3 at a scan rate of 10 mv s−1, furthermore, a symmetrical all-solid-state yarn-supercapacitor based on the above electrodes show a capacitance of 969 mF cm−3 at 10 mv s−1. This work provide a good choice of yarn-anodes to match with the reported high performance cathodes for further yarn-supercapacitor designs.

Transpiration represents more than 30% of the global land–atmosphere water exchange but is highly uncertain. Plant hydraulics was ignored in traditional land surface modeling, but recently plant hydraulics has been found to play an essential role in transpiration simulation. A new physical-based representation of plant hydraulic schemes (PHS) was recently developed and implemented in the Common Land Model (CoLM). However, it is unclear to what extent PHS can reduce these uncertainties. Here, we evaluated the PHS against measurements obtained at 81 FLUXNET sites. The transpiration of each site was estimated using an empirical evapotranspiration partitioning approach. The metric scores defined by the International Land Model Benchmarking Project (ILAMB) were used to evaluate the model performance and compare it with that of the CoLM default scheme (soil moisture stress (SMS)). The bias score of transpiration in PHS was higher than SMS for most sites, and more significant improvements were found in semi-arid and arid sites where transpiration was limited by soil moisture. The hydraulic redistribution in PHS optimized the soil water supply and thus improved the transpiration estimates. In humid sites, no significant improvement in seasonal or interannual variability of transpiration was simulated by PHS, which can be explained by the insensitivity of transpiration demand coupled to the photosynthesis response to precipitation. In arid and semi-arid sites, seasonal or interannual variability of transpiration was better captured by PHS than SMS, which was interpreted by the improved drought sensitivity for transpiration. Arid land is widespread and is expected to expand due to climate change, thus there is an urgent need to couple PHS in land surface models.

Land-surface heterogeneity occurs on many scales, but its inclusion remains an unsolved problem in land-surface and atmospheric boundary-layer schemes for weather and climate models. We investigate the propagation of land-surface heterogeneity in a convective boundary layer using an atmosphere and land-surface coupled large-eddy model. Simulations are made for land surfaces of different heterogeneity scales and a uniform land surface. A multi-scale analysis is carried out and it is found that while domain-and-time averaged fluxes and state variables are not sensitive to land-surface heterogeneity, atmospheric patterns are. Close to the surface, atmospheric patterns are dominated by land-surface forced patterns; away from the surface, “eigen” patterns dominate and forced patterns reemerge for large averaging times. While small-scale land-surface features are more rapidly destroyed by turbulence, large-scale features can persist over hundreds of meters.

A method was developed for the determination of nine volatile N-nitrosamines in tobacco and smokeless tobacco products. The targets are N-nitrosodimethylamine, N-nitrosopyrrolidine, N-nitrosopiperidine, N-nitrosomorpholine, N-nitrosoethylmethylamine, N-nitrosodiethylamine, N-nitrosodipropylamine, N-nitrosobuylmethylmine, and N-nitrosodibutylamine. The samples were treated by dispersive solid-phase extraction using 1 g of primary secondary amine and 0.5 g of carbon and then analyzed by gas chromatography with tandem mass spectrometry with an electron impact ion source. The recoveries for the targets ranged from 84 to 118%, with

The Triassic-Jurassic stratigraphy in the Yanshan fold-thrust belt is dominated by nonmarine deposits, and the division of this stratigraphy remains controversial among geologists. Age results from biostratigraphic and isotope chronological studies are inconsistent, especially for the Dengzhangzi and Guojiadian Basins in the eastern part of the Yanshan belt. We present four new detrital zircon U–Pb isotope datasets for the Triassic-Jurassic stratigraphic units and one for the Permian unit in the basins. The geochronological results show that the andesitic breccia in the Permian strata was deposited at ca. 273.78 ± 1.68 Ma, the Laohugou Formation was deposited in the Anisian-Ladinian Stage, the andesitic lava in the Shuiquangou Formation erupted at ca. 238.56 ± 0.91 Ma, and the conglomerate in the Guojiadian Formation was deposited from ca. 170 ± 5 to 163.0 ± 2.2 Ma. Field observations and facies analyses demonstrate that the Laohugou, Shuiquangou and Dengzhangzi Formations predominantly consist of subaqueous debris flow deposits, subaerial fluvial deposits, and fan delta deposits while the Guojiadian Formation is generally composed of fluvial and subaerial mass-flow deposits that formed in braided channels. Here, we propose a more precise and comprehensive Triassic-Jurassic stratigraphic division scheme based on age constraints and facies analysis. With this new stratigraphic sequence, we compare the Mesozoic stratigraphic units in the study area with those in other basins in the Yanshan fold-thrust belt in terms of the lithological associations, regional unconformities and zircon U-Pb dating results. This comparison indicates that the Indosinian and Yanshanian movements exerted a far-reaching influence on the development and evolution of the Dengzhangzi and Guojiadian Basins in the study area, forming several important regional unconformities and syntectonic conglomeratic units. These new age data on the stratigraphy are of fundamental significance for understanding the Mesozoic tectonic evolution of Yanshan.

In most existing SLAM (Simultaneous localization and mapping) methods, it is always assumed that the scene is static. Lots of errors would occur when the camera enters a highly dynamic environment. In this paper, we present an efficient and robust visual SLAM system which associates dynamic feature points detection with semantic segmentation. We obtain the stable feature points by the proposed depth constraint. Combined with the semantic information provided by BlitzNet, every image in the sequence is divided into environment region and potential dynamic region. Then, using the fundamental matrix obtained from the environment region to construct epipolar line constraint, dynamic feature points in the potential dynamic region can be identified effectively. We estimate the motion of the camera using the stable static feature points obtained by the joint constraints. In the process of constructing environment map, moving objects are removed while static objects are retained in the map with their semantic information. The proposed system is evaluated both on TUM RGB-D dataset and in real scenes. The results demonstrate that the proposed system can obtain high-accuracy camera moving trajectory in dynamic environment, and eliminate the smear effects in the constructed semantic point cloud map effectively.

Intelligentization of car navigation is an inevitable trend. Visual navigation has the advantages of high precision in short distances and low cost. This paper proposes a fuzzy control reversing system based on visual information. We obtain the trajectory of the rear camera by constructing reversing model of the car. YOLO (You Only Look Once) is used to detect pedestrians and cars appearing in the camera field of view and segment the detected images during the reversing process. The dynamic feature points are removed effectively by the proposed environmental statistical information analysis method. Using visual information to construct constraints to improve the traditional fuzzy control reversing system can provide drivers with accurate driving assistance information and effectively reduce the probability of accidents such as collisions. The experimental results show that the proposed method is effective and feasible.

Self-compacting concrete (SCC) widely used in tunnel structure is prone to spalling when it is subjected to the fire disaster. The fire-resistant materials coated on the surface of concrete are considered as an effective way to prevent concrete from being destroyed in a fire accident. However, current these coatings are difficult to withstand a high temperature, for example, tunnel fire temperature, and a longer-term fire. In this paper, a 40 mm thickness of SiO2 aerogel cement paste (ACP) coating was prepared to investigate the protective effect for SCC in a simulated tunnel fire with the maximum temperature of 1100 °C for 2.5 h. The mechanical properties, thermal conductivity and fire resistance of SiO2 ACP, and the compressive strength of SCC with or without ACP coating in the simulated tunnel fire were tested. The results showed that ACP exhibited excellent mechanical and durable performances and low thermal conductivity. The 40 mm thickness of ACP has a strong thermal insulation capacity and can effectively withstand tunnel fire up to 2.5 h. The SCC samples under the protection of ACP did not undergo compressive strength degradation and destruction of microstructure. The interfacial temperature of ACP and SCC was much lower than the critical value (380 °C) in a 2.5 h tunnel fire. Therefore, ACP can provide a good choice for protection of SCC in a tunnel fire with a high temperature and long time.

A strategy on amperometric detection for CZE of phenol carbamates as model analytes with a facile in-line thermal hydrolysis was presented, in which a thermal hydrolysis, subsequent CZE separation and final column-end amperometric detection were accomplished in an intact capillary. Key parameters of hydrolysis dynamics of carbamates and electrochemical detection of the hydrolysates were studied, as well as electrophoretic conditions. Under the optimal conditions, the capillary was utilized as chambers for in situ hydrolysis, CZE separation, and electrochemical detection. The successive separation of hydrolysates of five carbamates (propoxur, carbofuran, 3-OH-carbofuran, carbaryl and bendiocarb) were achieved within 17 min. Applied to vegetable samples, the recoveries of carbamates fortified at 0.02 and 0.05 mg/kg were ranging in 88-107.2 and 86.3-107.3%, respectively. The success in the implementation of such a scheme resulted in a simple instrument as compared with those current analytical methods with post-column derivization or pre-column hydrolysis, or online enrichment in chip, respectively. This protocol might possess a potential utility for the sensitive amperometric detection of phenol carbamates.

Ring-opening polymerization (ROP) of cyclic esters/lactones by efficient catalysts is a powerful method for synthesis of biodegradable and biocompatible polyesters with well-defined structures. To develop catalytic systems that are fast, selective and controlled is a persistent effort of chemists. In this contribution, we report a binary urea/alkoxide catalytic system that could catalyze ROP of rac-LA in a fast (over 90% conversion within 1-2 minutes), stereoselective (Pi up to 0.93) and controlled manner, indicated by narrow MW distributions, linear relationship between the monomer conversions and Mns, end-group fidelity and chain extension experiments. Remarkably, the catalytic system described here is simple, easily prepared, and structurally tunable and thus has versatile catalytic performances.

Atmosphere–land interactions simulated by an LES model are evaluated from the perspective of heterogeneity propagation by comparison with airborne measurements. It is found that the footprints of surface heterogeneity, though as 2D patterns can be dissipated quickly due to turbulent mixing, as1D projections can persist and propagate to the top of the atmospheric boundary layer. Direct comparison and length scale analysis show that the simulated heterogeneity patterns are comparable to the observation. The results highlight the model’s capability in simulating the complex effects of surface heterogeneity on atmosphere–land interactions.

Supramolecular nanomedicines, which use supramolecular design to improve the precision and effectiveness of pharmaceutical practice and optimize pharmacokinetic profiles, have gathered momentum to battle cancer and other incurable diseases, for which traditional small-molecular and macromolecular drugs are less effective. However, the lack of clinical approval of supramolecular assembly-based medicine underscores the challenges facing this field. A 2D nanodisc-based supramolecular structure is formed by a non-ionic heptamethine cyanine (Cy7) dye, which generates fluorescence self-quenching but unique photothermal and photoacoustic properties. These Cy7-based supramolecular nanodiscs exhibit passive tumor-targeting properties to not only visualize the tumor by near-infrared fluorescence imaging and photoacoustic tomography but also induce photothermal tumor ablation under irradiation. Due to the nature of organic small molecule, they induce undetectable acute toxicity in mice and can be eliminated by the liver without extrahepatic metabolism. These findings suggest that the self-assembling cyanine discs represent a new paradigm in drug delivery as single-component supramolecular nanomedicines that are self-delivering and self-formulating, and provide a platform technology for synergistic clinical cancer imaging and therapy.