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Nanograined materials possess ultrahigh strength, while their processing and technological applications are constrained by inherent thermal and mechanical instability. Existing experiments show that the stability of Cu nanograins can be enhanced by performing a rapid heating pretreatment that reduces the grain boundary (GB) energy by changing the GB structure. The variation in the GB structure inevitably affects the migration mechanism of GBs. However, the effect of the pretreatment-induced variation in migration mechanisms on stability remains unclear. Here, the shear deformation of a series of ⟨ 100 ⟩ symmetrical tilt GBs after rapid heating pretreatment is systematically investigated by molecular dynamics simulations. The simulations of unheated GBs are also included for comparison. Our results show that the rapid heating pretreatment does not improve the mechanical stability of GBs with tilt angles larger than 36.87° but rather enhances the mechanical stability of those with tilt angles less than 36.87° by the transformation of migration behavior from the normal ⟨ 110 ⟩ mode to (i) a ⟨ 100 ⟩ mode; (ii) an inhomogeneous mixed one that reconciles the ⟨ 110 ⟩ and ⟨ 100 ⟩ modes; and (iii) an inhomogeneous ⟨ 110 ⟩ mode. The former leads to an increase in the critical shear stress that is required to initiate the migration, whereas the latter two result in a decrease in the migration distance. The variation in the GB migration mechanism is attributed to the change in the GB structure from an ordered kite structure to a disordered one. The research gives an atomic insight into the stabilizing mechanism of nanocrystalline materials with rapid heating pretreatment. [ABSTRACT FROM AUTHOR]

In sports practices, the intensity and type of forces exerted on the human body are totally different from everyday living. Harsh movements and impact loadings are very common in sports and sometimes cause severe injuries to both muscles and bones. In a specific case, in volleyball games, the lower arm of the player is continuously exposed to heavy impacts by the ball. The main part of the body enduring these impact loads are the two ulna and radius bones in the lower arm. Therefore, in this type of ball impacts it is important to investigate the effect of ball movement and condition on the stress-induced in bones. In the present study, using numerical finite element and generalized differential quadrature (GDQ) methods, stability conditions in the ulna and radius bones in volleyball players under several static and harmonic loading types are investigated. Furthermore, change in the ball mass in the standard range is also considered in analyses. The bone structure is modeled as a cylindrical shell with classical elasticity theory and for inhomogeneous material properties. The results obtained using the numerical method are presented with a focus on the state of stability of the both ulna and radius bones. [ABSTRACT FROM AUTHOR]

The accurate perception of external environment information through the robot foot is crucial for the mobile robot to evaluate its ability to traverse terrain. Adequate foot-end contact signals can provide robust support for robot motion control and decision-making processes. The shape and uncertain rotation of the wheel-legged robot foot end represent a significant challenge to sensing the robot foot-end contact state, which current foot-end sensing schemes cannot solve. This paper presents a sensing method for the tire stress field of wheel-legged robots. A finite element analysis was conducted to study the deformation characteristics of the foot-end tire under force. Based on this analysis, a heuristic contact position estimator was designed that utilizes symmetrical deformation characteristics. Strain sensors, arranged in an array, extract the deformation information on the inner surface of the tire at a frequency of 200 Hz. The contact position estimator reduces the dimensionality of the data and fits the eigenvalues to the estimated contact position. Using support vector regression, the force estimator utilizes the estimated contact position and sensor signal to estimate the normal reaction force, designated as FZ. The sensing system is capable of detecting the contact position on the wheel circumference (with a root mean square error of 1.150°), as well as the normal force of 160 N on the Z axis (with a root mean square error of 6.04%). To validate the efficacy of the sensor detection method, a series of randomized and repeated experiments were conducted on a self-constructed test platform. This novel approach offers a promising avenue for perceiving contact states in wheel-legged robots. [ABSTRACT FROM AUTHOR]

This study investigates the performance of a 4-MIX engine utilizing hydrogen combustion in pure oxygen, water injection, and the application of the early-intake valve closure (EIVC) Miller cycle. Transitioning from a standard petrol–oil mix to hydrogen fuel with pure oxygen combustion aims to reduce emissions. Performance comparisons between baseline and oxyhydrogen engines showed proportional growth in the energy input rate with increasing rotational speed. The oxyhydrogen engine exhibited smoother reductions in brake torque and thermal efficiency as rotational speed increased compared to the baseline, attributed to hydrogen's higher heating value. Water injection targeted cylinder and exhaust temperature reduction while maintaining a consistent injected mass. The results indicated a threshold of around 2.5 kg/h for the optimal water injection rate, beyond which positive effects on engine performance emerged. Investigation into the EIVC Miller cycle revealed improvements in brake torque, thermal efficiency, and brake specific fuel consumption as early-intake valve closure increased. Overall, the EIVC model exhibited superior energy efficiency, torque output, and thermal efficiency compared to alternative models, effectively addressing emissions and cylinder temperature concerns. [ABSTRACT FROM AUTHOR]

At present, the valence state (connectivity) of most covalent organic frameworks (COFs) building units is low, mostly trivalent and tetravalent, making only 18 types of topological structures of COFs materials. On the contrary, the valence states of MOFs building blocks vary from 3 to 24, making them have more than 2 000 topological structure types. If a higher valence COFs building block can be designed, it will greatly enrich its topological structure type and material number. To this end, a hexahedral boron-phosphorus unit (-B4 P4 O12-) and five linear organic linkers (phenyl, fluorophenyl, toluene, naphthalene, biphenyl) were selected, and five high-valent boron-phosphorus covalent organic frameworks (BP-COFs) with lta topology were theoretically designed by molecular mechanics methods. The results show that the five materials have structural characteristics that are conducive to hydrogen storage applications, such as low density (0.52 ~ 1.17 g⋅cm-3), large specific surface area (1 274.12 ~ 4 033. 95 m² ⋅g-1) and high porosity (0. 55% ~ 0.78%). The Grand Canonical Monte Carlo (GCMC) method was used to predict the physical adsorption properties of hydrogen molecules on five materials at 298 and 77 K, and the structure-activity relationship between material structure and hydrogen adsorption properties was analyzed. The results show that the five BP-COFs materials have strong hydrogen adsorption capacity. Especially at 77 K, BP-COF-10 and BP-COF-11 have the best performance in hydrogen storage performance. BP-COF-10 has the highest volumetric hydrogen storage capacity at 77 K, reaching 52.86 g⋅L-1. BP-COF-11 has a large accessible specific surface area and high porosity. It has a good hydrogen storage capacity at 77 K and a gravimetric hydrogen storage capacity of 9.90% at 5 000 kPa. With the increase of pressure, the hydrogen storage capacity of BP-COF-11 still maintains a good upward trend. BP-COF-7 has the largest hydrogen storage capacity at 298 K, and the hydrogen storage capacity reaches 4.83 g⋅L-1 at 5 000 kPa. This indicates that the designed material has good hydrogen storage potential. This study will provide a theoretical reference for the experimental development of new high-performance hydrogen storage materials. [ABSTRACT FROM AUTHOR]

For the problem of long modeling time and large workload of multiview bill of material (XBOM) reconstruction process in digital twin shop, this paper proposes a knowledge-driven XBOM reconstruction method for complex products. Through the research of knowledge base construction, the modeling and simulation analysis of XBOM reconstruction process in digital twin workshop are supported, so as to shorten the cycle and improve efficiency and quality. Taking the maintenance history data of the typical representative electric multiple unit (EMU) bogies in complex products as the research object, the bidirectional long short-term memory neural network with conditional random field (BiLSTM-CRF) algorithm is used to complete the entity recognition of maintenance BOM (WBOM) reconstructed parts. Finally, taking the XBOM reconstruction process of the bogie of an enterprise as an example, the XBOM reconstruction knowledge base interaction system of the EMU bogie is built. It verifies the feasibility of the method proposed in this paper, and provides knowledge support for the XBOM reconstruction process of complex products in the digital twin workshop. [ABSTRACT FROM AUTHOR]

Experiments have shown that the ultrahigh strength of nanolayered metallic composites originates from their high-density interfaces of special characteristics. Hence, the modulation of interface structures becomes an effective route to enhance the mechanical performance of the nanolayered composites. One of the general ways to tune the interfacial feature is to introduce interlayers of several nanometers among constituent layers, such as amorphous (disordered) and crystalline (ordered) interlayers. Here, the deformation of a Cu/Ni layered composite with Ag interlayers of different thicknesses was simulated by molecular dynamics simulations. Our simulations show that the yield stress of 25 nm Cu/25 nm Ni nanolayered composites with Ag interlayers can be significantly enhanced, i.e., it can be 56.4% higher than that of their counterparts without interlayers. We also found that the yield strength of the new composites can be maximized by selecting an appropriate thickness for the Ag interlayer. The optimum interlayer thickness is 2.1 nm in tension and 4.2 nm for compression. It is revealed that the extra strength results from the alleviation of stress concentration by stimulating abundant interfacial dislocations at the Cu–Ag and Ag–Ni interfaces. These findings show that the introduction of additional interlayers is a new route to design stronger nanolayered metallic composites. [ABSTRACT FROM AUTHOR]

Nanolayered metallic composites have attracted intensive scientific interests due to their ultrahigh strength. However, the deformation incompatibility among the component layers with high mechanical contrast leads to extremely low tensile ductility in the nanolayered composites, which is a great setback for their engineering applications. Here, by molecular dynamics simulations, we show that a heterogeneous nanolayered design by combining 2.5 nm and 24 nm Cu/Ni bilayers in a composite in an appropriate way can promote the dislocation activity of the hard phase, i.e., the Ni layers. In the new heterogeneous structure, each 24 nm Cu or Ni layer is coated on both surfaces by one 2.5 nm Cu/Ni bilayer. The simulations show that the dislocations in the 24 nm Ni layers can nucleate and glide almost synchronously with those in the 24 nm Cu layers. The enhanced dislocation activities are attributed to the presence of the 2.5 nm Cu layer that can promote the dislocation nucleation and motion in the 24 nm Ni layer by forming more nodes in the dislocation network of the interface. [ABSTRACT FROM AUTHOR]

Diesel engines play a very significant role in the automotive industry, but the total emissions of diesel engines are more than 1.8 times that of petrol engines. It is therefore important for diesel engines to control emissions. Theoretically, the Miller cycle can be used to achieve NOx reductions by changing the effective compression ratio, while it has become increasingly popular in recent years with the increasing maturity of current turbocharging technology. Based on Ricardo WAVE software, this paper analyses the NOx emissions and engine performance of diesel engines by modelling and simulating their operation under different loads with two types of Miller cycles (EIVC and LIVC) at different degrees. Simulation of engines operating under different loads allows a more comprehensive study of the effects of the Miller cycle on the engine, and a specific analysis in the context of the actual engine operating environment. The result is that both versions of the Miller cycle are most effective in reducing NOx emissions at 10% load, showing a maximum reduction of 21% for EIVC and 37% for LIVC. However, as the Miller cycle decreases engine power, the paper further investigates the application of turbocharger systems in the EIVC Miller cycle, with results showing a 32% increase in brake power at 10% load and −25% EIVC Miller cycle degree. Both ethanol-fueled diesel-cycle and Miller cycle engines were also analyzed, and a reduction in NOx emissions was observed, as well as hydrogen engine performance and NOx emissions. [ABSTRACT FROM AUTHOR]

Aiming at low accuracy of recognition in complex leakage images of subway tunnels, this paper studied the application of image recognition algorithms in tunnel water-leakage disease, was using two kinds of neural networks: U-Net and PSP-Net. Based on the subway tunnel images, tunnel leakage disease sample data set was constructed, where 5000 subway tunnel disease image data and 4000 labeled images were included. This data set could be used for deep neural convolution network training. U-Net and PSP-Net deep learning frameworks were established, and the neural networks were trained by self-made data set. The accuracy of the prediction results from U-Net and PSP-Net was evaluated, and the performance of the two networks in the application of leakage disease identification was compared. U-Net had stronger coverage for the disease and quick detection, while PSP-net had higher accuracy fit to fine detection. [ABSTRACT FROM AUTHOR]

In this work, L -tryptophan was hyper-crosslinked on cellulose and several other matrices (such as silica gel and polystyrene) via a Friedel–Crafts alkylation reaction to produce a series of chiral hyper-crosslinked catalyst supports (HCP-Mt-(L)Trp). Transition metal catalysts (M) were then fixed on the resulting supports via coordination with the amino acid residues, generating heterogeneous chiral catalysts (HCP-Mt-(L)Trp-M). All the catalysts successfully catalyzed the asymmetric Henry reaction, and the influence of the matrix on the catalytic performance was investigated. It is found that the choice of matrix significantly affects the catalytic performance; matrices supported on cellulose show the best performance, and they led to good yields and enantioselectivity at both low and high temperatures (enantiomeric excesses up to 99% and yields of >80%). The catalysts can be readily recycled via filtration and show good recyclability. This work provides an effective strategy for the synthesis of highly efficient asymmetric catalysts with both high selectivity and ease of preparation. [ABSTRACT FROM AUTHOR]

Methanol/high reactivity fuel (HRF) dual fuel combustion cannot further extend methanol energy ratio (MER) at medium and low loads. Polyoxymethylene dimethyl ether (PODE) as a biofuel with high cetane number is well suited for HRF. This paper explored the effect of spark ignition (SI) on energy conversion and MER extension for methanol/PODE under medium and low loads. The results show that SI triggers the exothermic processes of SI and dual fuel spark-assisted compression ignition (D-SACI). SI raised MER from 30 %, 40 %, 46 % to 40 %, 60 %, 90 % for brake mean effective pressure (BMEP) of 0.2, 0.4, 0.6 MPa, respectively. SI and D-SACI combustion can partially or completely replace premixed compression ignition (CI). Diffusion combustion and one or more exothermic processes of SI, D-SACI and premixed CI make up two-stage or three-stage exotherm. D-SACI is easily triggered when spark timing approaches PODE injection timing, otherwise, SI exotherm is easily triggered; at BMEP of 0.6 MPa, the exothermic energy of premixed CI is gradually converted into the exothermic energy of D-SACI and SI as MER increases. By optimizing, maximum brake thermal efficiency for BMEP of 0.4 and 0.6 MPa are 37.75 % and 42.82 %, respectively, corresponding to the MER of 50 % and 80 %, respectively. • The effect of spark ignition (SI) on methanol/PODE combustion was studied. • SI made SI and dual fuel spark-assisted compression ignition (D-SACI) combustion. • SI and D-SACI partially or completely replaced premixed compression ignition. • SI raised methanol energy ratio and thermal efficiency of dual fuel combustion. [ABSTRACT FROM AUTHOR]

Vienna rectifiers are widely used, but they have problems of zero-crossing current distortion and midpoint potential imbalance. In this paper, an improved hybrid modulation strategy is proposed. According to the phase difference between the reference voltage vector and the input current vector, the dynamic current crossing distortion sector is divided at each phase current crossing, and the discontinuous pulse width modulation strategy is adopted in the sector to suppress the redundant small vector mutation and improve the current crossing distortion. To solve the problem of midpoint potential balance, a space vector modulation strategy is adopted outside the sector to control the midpoint potential balance by allocating the time of small vector action by voltage balance factor. Finally, the effectiveness of the proposed method is verified by simulation and experiment. [ABSTRACT FROM AUTHOR]

[Display omitted] • Three different N-configurations of BiOBr/N-CQDs (BNCs) were successfully synthesized. • The degradation rate of BNC-eda for carbamazepine was 5 times higher than that of BiOBr. • The electron-hole pair separation was greatly enhanced by pyrrole N-doped CQDs. • The content of pyrrole N in BNCs was linearly and positively correlated with the k. In the realm of persistent pharmaceutical contaminants photodegradation, N-doped carbon quantum dots (N-CQDs) modified bismuth-based photocatalysts have recently received a lot of interest. However, an in-depth understanding of the effect of both N chemical state and N chemical configuration on the photocatalytic activity was still lacking. Herein, three graphite/pyrrole N-doped CQDs with different contents were prepared by hydrothermal method to modify BiOBr (BNCs), respectively. The degradation kinetics of carbamazepine (CBZ) by BNC-eda (doped with 100 % pyrrole N, k = 0.363 min−1) was higher than that of BNC-trp (doped with 62 % pyrrole N and 38 % graphitic N, k = 0.099 min−1) and BNC-ur (doped with 58 % pyrrole N and 42 % graphitic N, k = 0.072 min−1) under visible-light irradiation. More importantly, the k of BNCs degrading CBZ showed a linear positive relationship with the percentage content of pyrrole-N in the corresponding N-CQDs with r2 = 0.9999. The characterization results showed that doping with pyrrole N rather than graphite N could be responsible for the increase in visible light absorption, the promotion of electron-hole separation and the generation of more superoxide radicals (•O 2 –) and singlet oxygen (1O 2) in BNCs. Toxicity Estimation Software Tool program showed that the BNC-eda exhibited CBZ toxicity reduction performance. Overall, this study offered a useful method for designing excellent N-CQDs modified Bi-based photocatalysts for the treatment of pharmaceutical wastewater. [ABSTRACT FROM AUTHOR]

By using aromatic amino acid as the starting material, a novel chiral catalyst support, porous hypercrosslinked amino acid polymer was synthesized, the recyclable asymmetric metal supported by it catalyzed efficient asymmetric reaction with high ee% (up to 99%). [Display omitted] • Synthesis of a new chiral catalyst support, porous hypercrosslinked amino acid (HCP-AA). • A new heterogeneous asymmetric catalyst. • High enantioselectivity of HCP-AA-Rh for asymmetric hydrosilylation of ketones and olefins (ee% up to 99%). • HCP-AA-Rh can be easily recycled and well maintain the catalytic performance after recycle. The application of asymmetric catalysis in industrial processes is limited by the high cost of chiral ligands and the difficulty associated with recovering precious metal catalysts. Here, based on a FeCl 3 -catalyzed Friedel–Crafts alkylation reaction, an aromatic amino acid was crosslinked with 4,4′-bis(chloromethyl)-1,1′-biphenyl to produce a novel porous chiral catalyst support, hypercrosslinked amino acid polymer (HCP-AA). Subsequently, metal catalysts were loaded on HCP-AA through the coordination of the metal ion with amino acid residues to generate heterogeneous asymmetric catalysts, HCP-AA-M. The resulting catalysts were characterized by scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy. The HCP-AA-M samples were employed to catalyze the heterogeneous asymmetric reaction, and they achieved high enantioselectivities (up to 99% ee). Meanwhile, the catalysts could be readily recovered through filtration, and they exhibited good recycling performances. The results suggested that the utilization of inexpensive amino acids as raw materials for producing porous chiral supports for recyclable high-performance asymmetric catalysts is an effective strategy. [ABSTRACT FROM AUTHOR]

This study aimed to find a distributed renewable power system with hydrogen generation and storage to meet the current Isle of Rum's energy demands. Five different systems (Case 2–6) were evaluated compared to the current power system (Case 1), with the inclusion of a hydrogen generation and storage subsystem acting as an energy storage medium in Case 3, 4, 5 and 6. Case 2 exhibited a 96.2% reduction in diesel consumption. Case 3 and 4 achieved a fully renewable generation mix through the addition of a hydrogen subsystem comprised of a 28 kW PEM electrolyser, 120 kg compressed storage and modified gen-set. Case 5 and 6 also achieved a fully renewable generation mix, meeting the domestic heating and full heating demands of the island respectively through the integration of heat pumps. Economic analysis showed that Case 2 exhibited the lowest cost, with a LCOE of £3.02/kWh, a 43% reduction from Case 1. Both Case 3 and Case 4 also had a lower LCOE than Case 1 of £5.02/kWh and £4.37/kWh respectively. This shows that the hydrogen subsystem designed can be an economically viable option despite its currently high CAPEX. Both Case 5 and 6 had the highest CAPEX of all systems, due to the additional generation technology required to meet the additional heating demand. However, they achieved the lowest LCOE at £1.86/kWh and £0.76/kWh, due to the high efficiency exhibited by the heat pumps used for the heating load. [ABSTRACT FROM AUTHOR]

Referring Expression Comprehension (REC) is a task that involves grounding a specific object in an image based on a given referring query in the form of bounding boxes. Existing fully-supervised or weakly-supervised REC methods rely on either manually annotated regional coordinates or query texts. In this paper, we propose an unsupervised training paradigm for the REC task that does not require any manual annotated data. Specifically, we introduce a V isual-Semantic-Parsing-based U nsupervised R eferring E xpression C omprehension framework (VUREC), which leverages a Visual Semantic Parser (VSP) as its core module to recognize the rich semantic information in images and construct pseudo-region-query pairs as the training supervision for REC. The VSP comprises a Scene Graph Parser (SGP) and a Visual Concept Detector (VCD) that can detect the locations, categories, attributes of objects, and visual relationships among them in images. Furthermore, we present a Referring Expression Reasoning (RER) model that utilizes a Multi-Modal Cascade Attention Decoder (MCAD) for fine-grained multi-modality fusion and regresses the four coordinates of the referential object directly. The experimental results on three benchmark datasets of Refcoco, Refcoco+ and Refcocog demonstrate the effectiveness of our proposed method. • Recognize the rich semantics contained in images. • Construct pseudo region-query pairs as training data. • Present a fine-grained multi-modality fusion decoder for REC. [ABSTRACT FROM AUTHOR]

We introduce a framework to efficiently capture and identify the defects on the subway tunnel surfaces. Specifically, we design a high-speed multi-camera-synchronous acquisition system for scanning the tunnel surfaces and capturing the cracks from images. We propose an Improved Cascade Region-Based Convolutional Neural Network (R-CNN) method to locate and classify defects, with the crack being refined by image processing algorithms. The methodology is tested by on-site experiments carried out in an operational subway. The mAP value reaches 0.827, with a specific AP value of 0.625 and a newly proposed measure identification rate of 0.942 for crack objects. Notably, by training on bounding box labels, our overall algorithm exhibits the lowest Error Rate (ER) and the highest Intersection over Union (IoU) across all test images, surpassing the performance of classical semantic segmentation networks trained on pixel-level labels. [ABSTRACT FROM AUTHOR]

• The tension of Cu/Nb nanolayered composites is simulated by atomic simulations. • The normal sample with ordinary interfaces is subject to severe strain localization. • The addition of amorphous interfacial layer gives an enhanced strain delocalization. • Strong strain delocalization is further gained by composition gradient in interface. • The delocalization results from nanotwinning and vortex flow of interfacial layers. Nanostructured metals and alloys possess ultrahigh strength but suffer from severe shear instability (strain localization). Recent experiments have shown that the strength and strain delocalization capability of some novel nanostructured alloys and nanolayered composites can be enhanced simultaneously by introducing nanoscale amorphous interfacial layers. However, the study on the underlying mechanism is still in an embryonic stage due to the ignorance of the complicated elemental composition of the interfacial layers, especially the compositional gradient along the interface thickness. Here, the atomic mechanisms of the tensile deformation of Cu/Nb nanolayered composites with amorphous interfacial layers are systematically investigated by molecular dynamics simulations. Depending on whether the composition of the interfacial layers is invariable or has a gradient distribution along the interface thickness, these samples are classified as amorphous or gradient samples, respectively. The simulations of normal Cu/Nb nanolayered composites with ordinary incoherent Cu‒Nb interfaces are also included for comparison, the results of which show that strain localization occurs due to the inhomogeneous plastic deformation between soft and hard grains in the Cu and Nb layers. The strain localization is inhibited in the amorphous samples mainly through the activation of deformation twinning in the Cu and Nb layers that produces a co-deformation between grains. Intriguingly, the gradient arrangement of the elemental composition of the amorphous interfacial layers gives a further stronger strain delocalization by further promoting the co-deformation between grains through stimulating more nanotwins in Cu layers and hindering twin growth in Nb layers, and by producing a much more uniform von Mises strain distribution in the interfacial layers. In addition, a better strain delocalization capability can be obtained when the thickness of the interfacial layers is closer to that of the crystalline ones in the amorphous sample or the range of gradient composition is larger in the gradient one. [ABSTRACT FROM AUTHOR]

Highlights • Different crystal facets are exposed with adding different capping agents. • (2 0 0) crystal facet shows the best chemical adsorption characteristic and activity. • The order of low-temperature SCR activity corresponds with that of NH 3 - and NO-TPD. Abstract The low-temperature selective catalytic reduction (SCR) of NO x by ammonia is an efficient purification technique to eliminate NO x from stationary combustion sources. In this paper, the different exposed crystal facets of α-MnO 2 catalyst were controllably synthesized by using of capping agents of PVP, P123, HAc and CTAB. It was found that all α-MnO 2 catalyst prepared using various capping agents are with the same nanorods morphology but different exposed crystal facets. The structure-activity relationship of the catalyst was investigated and the exposed crystal facets showed strong effects of on its activity of SCR for deNO x. The α-MnO 2 catalyst with exposed (2 0 0) facets has the highest surface acidity, strongest NH 3 and NO adsorption and therefore the best low-temperature SCR activity, with 98% NO conversion at 160 °C. [ABSTRACT FROM AUTHOR]

The response to Nigeria's energy inadequacies and waste management issues is projected in this research to be achieved with hydrogen and methane co-produced from pretreated (PT) rice straw (RS) in a three-stage digestion process. This study also demonstrated a novel pretreatment (PTM) agent to improve biological energy recovery from RS. The objectives were accomplished using acidogenic and methanogenic procedures in batch, semi-continuous and continuous systems after pretreating RS with chemical/potash extract (PE) followed by a biological agent. At the same time, the energy assessments were done using data from the laboratory study and the literature. The research findings indicated that at the acidogenesis stage, specific hydrogen yield was insignificant when chemical agents and PE were employed alone. However, the daily H 2 production increased when the PT RS residues were enzymatically hydrolysed with NaOH-PT (114 NmL H 2 g−1 TS d−1) and PE-PT (103 NmL H 2 g−1 TS d−1) RS substrates having the highest values at steady states and raw RS producing the least (30 NmL H 2 g−1 TS d−1). In the methanogenesis phase, chemical/ PE PTM followed by enzymatic hydrolysis of RS improved the daily specific methane production by 18%, 31.7% and 41.5% for HCl, PE and NaOH-PT RS residues. The methane production efficiency was 80% for NaOH, 75% for PE, and 68% for HCl RS PT samples, while the raw RS was 48%. The total output energy expressed in electricity and thermal production using combined cooling, heat, and power (CCHP) showed that NaOH and PE-PT RS digesters gave the highest electricity (892.43 and 852.00 KWh elect. tonne-1 TS) and thermal (1194.10 and 1140 KWh therm. tonne-1 TS) yield respectively. Similarly, the cooling fluid in KWh cool produced per tonne of TS RS was 835.57, 798.00 and 741.66 for NaOH, PE and HCl PT RS samples. Finally, whereas the Firmicutes, especially the Clostridium , Ruminococcus and Thermoanaerobacterium, were the dominant microbial community in acidogenic digestates, the Euryarchaeota typified by Methanobacterium , Methanosarcina and Methanosaeta were the principal phyla for most methanogenic reactors. [Display omitted] • Co-production of H 2 and CH 2 from PT rice straw in a novel 3-stage digestion process. • Improving rice straw energy recovery via innovative potash extract pretreatment. • Daily H 2 and CH 4 yield from RS improved with chemical/PE and enzyme pretreatment. • NaOH and PE-PT RS digesters generated the highest electricity, thermal, and cooling fluid in CCHP. • Firmicutes and Euryarchaeota dominated acidogenic and methanogenic reactors, respectively. [ABSTRACT FROM AUTHOR]

We propose a new hybrid model algorithm that addresses the challenges of recognizing multiple objects. Specifically, objects are recognized from massive, large-scale, and complex tunnel images without repeated parameter adjustments and high-cost annotation datasets. Our algorithm utilizes a multi-scale, fusion-based encoder–decoder segmentation model to classify objects from high-resolution images of the tunnel surfaces. To enhance the accuracy of crack identification from complex backgrounds, we incorporate the Expanded Threshold Search (ETS) algorithm and the Local Window Extraction (LWE) algorithm. The acquisition device and the algorithm, implementing the multi-object dataset, have successfully tested, whereby it recognizes five objects and attains the highest Intersection over Union (39.3% for the crack object, 65.6% for the leakage object, and 75.7% for the rest). [Display omitted] • An image acquisition device is designed for tunnel. • A multi-object dataset of complex subway tunnel images is efficiently built. • An efficient and accurate hybrid model is proposed. • Comprehensive experimental results are provided. [ABSTRACT FROM AUTHOR]

The objective of the study has been to determine the river discharge by measuring the river flow velocity using two different measurement methods together with the area method and compare the accuracy of the results. Two river flow velocity measurement methods were used, the floating method and the use of current meter. In floating method a floating object was used to determine the water flow velocity on the surface by allow a float to move a distance of 1 m along the river and record the time it takes to travel that distance in seconds. Ten readings were taken and manually recorded and the flow velocity was determined by taking the distance travel by the float (1 m) divide by the time taken by the float (in seconds). On the other hand, the current meter method measure directly the average flow velocity across the river depth, twenty readings were taken and recorded manually and the average velocity were calculated. The use of current meter display flow velocity directly without the need of calculations. The result shows that both methods produce very close value, but the floating method have displayed higher value of around + 2% than current meter method which is a good value, despite the fact that floating method measures the surface velocity and the use of calculation. Many literature highlighted the accuracy of flow velocity measurement using current meter due to the fact that it measures the average velocity across the river, but from the findings when the floating method flow velocity measurement is properly applied it will produce as accurate results as the current meter with a fraction of cost in terms of instrument cost and expertise requirement in measurements. The floating method flow velocity measurement method could be applicable as alternative to current meter in micro hydropower projects river flow measurements in rural areas of developing countries with limited funding and local expertise. [ABSTRACT FROM AUTHOR]

The free-piston engine generator (FPEG) is a linear energy conversion device with the objective of utilisation within a hybrid-electric automotive vehicle power system. In this research, the piston dynamic characteristics of an FPEG is compared with that of a conventional engine (CE) of the same size, and the difference in the valve timing is compared for both port scavenging type and valve scavenging type, with the exhaust valve closing timing is selected as the parameter. A zero-dimensional simulation model is developed in Ricardo WAVE software (2016.1), with the piston dynamics obtained from the simulation model in Matlab/SIMULINK (R2017a). For the CE and FEPG using scavenging ports, in order to improve its power output to the same level as that of a CE, the inlet gas pressure is suggested to be improved to above 1.2 bar, approximately 0.2 bar higher than that used for a CE. If a CE cylinder with exhaust valves is adopted or referred to during the development of an FPEG prototype, the exhaust valve is suggested to be closed earlier to improve its power output, and a higher intake pressure is also suggested if its output power is expected to be the same or higher than that of a CE. [ABSTRACT FROM AUTHOR]

Nowadays, increasing the penetration of renewable heat technologies is an important approach to minimise global primary energy use and reduce CO2 emissions for a sustainable future. Thermoelectric heat pumps, which have some unique characteristics in comparison with conventional vapour compression heat pumps, can be integrated with solar thermal energy storage to form a promising renewable heat technology. However, currently, a reliable numerical model for TeHPs suitable for building energy simulation is lacking and the benefits achievable for a TeHP thanks to the integration with heat storage are unclear. To solve these issues, in this work, an experimental apparatus consisting of a water-to-air TeHP unit with a heat storage tank is modelled and tested for the first time, under the scenarios with thermal energy storage and without thermal energy storage, respectively. The results found that the developed numerical model could well predict the output performance of the TeHP unit, with deviations within 12%. Additionally, the output performance of the TeHP unit when combined with a heat storage tank is better than that of the TeHP unit without heat storage, in terms of the maximum temperature achieved in the testing box, the temperature response speed of the testing box, and the coefficient of performance (COP) of the TeHP unit. This work not only paves the way for the following building-integrated simulations of TeHP units, but also provides guidance for the design of the integrated systems that include TeHPs and thermal energy storage. [ABSTRACT FROM AUTHOR]

Free-piston engine is a kind of linear internal combustion engine, and shows advantages on simple mechanical structure, low frictional losses, high thermal efficiency and operational flexibility. In this research, an experimental test rig of a dual-piston air-driven free-piston linear expander (FPLE) is established using the FPE concept. A linear generator is used to convert the mechanical work of the pistons into electricity during the expansion process. The piston dynamics, the output voltage of the generator, and the expander operation frequency, as well as the system energy conversion efficiency are identified. It is observed that the piston displacement profile is similar with a sinusoidal wave. The piston is found to run at relative high speed during the middle stroke, and peak velocity is usually achieved when the piston approaches the middle stroke. The output voltage of the generator is sensitive with the piston velocity. With higher driven pressure, the expander frequency is higher. The energy conversion efficiency increases with higher driven pressure and can reach up to 55% with a driven pressure of 3.75 bar. This research presents a fundamental analysis of a FPLE prototype, which can be used as a guidance for the future design of this FPLE type. [ABSTRACT FROM AUTHOR]

In this paper, we establish a model to analyze the light scattering properties of material surface considering the specific morphology information based on small element scattering hypothesis and analysis of receiving flux components. Aluminum micro-structure material is chosen as an example, its surface scattering characteristics are simulated and analyzed using this model. Results show that the scattering distribution on the surface of the material is mainly dependent on the information of the surface topography, when the size and distance of the surface of the material do not cause obvious diffraction effect, and the incident light energy is not enough to cause obvious Compton effect. The research of this paper can provide an effective method for the study of scattering characteristics of new materials and new surface structure, which is the theoretical foundation of the complex scattering analysis and the target detection based on the light scattering characteristics. [ABSTRACT FROM AUTHOR]

Laser conduction limited heating finds wide application in surface processing industry. Modeling of the laser heating can give an insight into the physical processes. In this paper, repetitive long pulse laser heating of solid materials is considered, and an analytical solution for two-dimensional modeling of the temperature distribution is obtained using the method of separation of variables combining with Laplace transformation. It is found that the results obtained from the analytical solution agree well with the existing finite element method. Temperature distributions for different radial locations, axial locations, duty cycles and repetitive frequencies are calculated, and effects of these parameters on temperature distributions are analyzed. The results of this study can give some theoretical basis for revealing the mechanism of laser heating and provide some guidance for experiments of repetitive long pulse laser heating materials in the next work. [ABSTRACT FROM AUTHOR]

• Synthesis of a novel U (VI) adsorbent HCP-Phenylalaninol (HCP-PAO), a porous hypercrosslinked aminol. • The hypercrosslinked product is simple to synthesize and shows porosity, large surface area and good thermodynamic stability properties. • HCP-PAO shows efficient U (VI) adsorption performance (Q e = 369.5 mg/g, pH = 7) and long service life. • HCP-PAO shows good selective toward uranium at simulated seawater. Uranium mining from seawater has sparked a lot of research curiosity. Here, we synthesized a porous hypercrosslinked phenylalaninol (HCP-PAO) for U (VI) adsorption from water, in which phenylalaninol bearing amino and hydroxyl groups was used as the monomer, and biphenyl dichlorobenzyl (BCMP) was used as the external crosslinker. The resulting porous adsorbent has a surface area of 562.6 m2/g and a pore volume of 0.41 cm3·g−1. The pore size distribution is focused around 3–4 nm, indicating that it is a typical mesoporous polymer. The adsorbent had the most promising adsorption performance at pH = 7, reaching adsorption saturation in a 100-ppm uranium-doped solution for 2 h (adsorption capacity of 369.5 mg/g). HCP-PAO was particularly sensitive to uranium in complicated settings (56.3 % removal rate), and the adsorption mechanism closely resembled the Langmuir model and the pseudo-second-order model well. The practically consistent adsorption capacity of the HCP-PAO after five adsorption/resolution studies indicated its high recyclability. The mechanism of uranium extraction by HCP-PAO is the synergistic coordination of –NH 2 and –OH with U (VI). HCP-PAO had an adsorption capacity higher than 100 mg/g at pH = 8 which is close to the pH of natural seawater, and showed good selectivity for U (VI) in simulated seawater experiments (removal rate over 55 %). Our research suggests that the novel hypercrosslinked product HCP-PAO can be applied as an adsorbent to efficiently capture U (VI) from water, and also it has great potential in seawater uranium extraction as well as expanding the research concept of porous uranium adsorbent. [ABSTRACT FROM AUTHOR]

This paper presents an optimised resorption cogeneration using mass and heat recovery to improve the performance of a novel resorption cogeneration fist proposed by Wang et al. This system combines ammonia-resorption technology and expansion machine into one loop, which is able to generate refrigeration and electricity from low-grade heat sources such as solar energy and industrial waste heat. Two sets of resorption cycle are designed to overcome the intermittent performance of the chemisorption and produce continuous/simultaneous refrigeration and electricity. In this paper, twelve resorption working pairs of salt complex candidates are analysed by the first law analysis using Engineering Equation Solver (EES). The optimal resorption working pairs from the twelve candidates under the driven temperature from 100 °C to 300 °C are identified. By applying heat/mass recovery, the coefficient of performance (COP) improvement is increased by 38% when the high temperature salt (HTS) is NiCl 2 and by 35% when the HTS is MnCl 2 . On the other hand, the energy efficiency of electricity has also been improved from 8% to 12% with the help of heat/mass recovery. The second law analysis has also been applied to investigate the exergy utilisation and identify the key components/processes. The highest second law efficiency is achieved as high as 41% by the resorption working pair BaCl 2 –MnCl 2 under the heat source temperature at 110 °C. [ABSTRACT FROM AUTHOR]

To study concrete members' safety and residual life after fire damage, this study takes concrete beams as the research object. Then, it predicts the residual energy of concrete beams after fire by investigating their temperature field after the fire and deriving the required data for studying the corresponding residual life. This study first establishes the temperature field model of concrete beams under fire by using the finite element software ABAQUS, selects the ISO-834 standard warming curve as the fire condition, and obtains the thermodynamic parameters and calculation formulas of concrete and steel reinforcement from a large number of experiments and examples, to provide reliable materials for the temperature field simulation, reliability analysis, and residual life prediction by using the finite element software ABAQUS afterward. The results obtained from the temperature field simulation are used to calculate the probability of failure using the Monte Carlo method calculation program prepared by MATLAB software in conjunction with the equation of limit state to derive the results of the residual life of the concrete member. When the concrete beam with a definite strength of C40 and a thickness of the protective layer of 35 mm undergoes a fire for 2 hours, the residual life of the concrete beam is 13 years and 7 years, respectively, under the requirements of the general building and the use of the essential building components. They are about 13 years and 7 years, respectively. To verify the reasonableness of the derived equations, confirmed cases are used to demonstrate the feasibility. Finally, by analyzing the results of reliability and remaining life under different working conditions, it can be concluded that the concrete grade and the thickness of the concrete protective layer have a significant effect on the remaining life of concrete beams after the fire, regardless of the requirements of general or essential building components. [ABSTRACT FROM AUTHOR]

• A novel hybrid model of broad-deep networks is proposed for data augmentation. • The highly similar features can be merged to generate new augmented features. • The method solves the problem of insufficient authenticity of EEG generated by GAN. Decades after data augmentation was first proposed in brain-computer interface (BCI), the authenticity and performance still do not meet rational requirements, which is directly related to the fact that the augmentation methods do not provide real electroencephalograph (EEG) trials. Here we show how to generate a numerous authentic EEG from the original calibrated EEG by using a novel hybrid model of broad-deep networks, which eliminates the lack of authenticity of data generated by GAN and other methods. First, we design an EEG evoked experiment with a complex boundary avoidance task to collect the EEG of different subjects. This experiment can effectively highlight the differences of EEG features of different subjects that makes the results more reliable when using our novel hybrid model to measure the similarity. A new hybrid model of broad-deep networks is proposed to measure the similarity of different subjects in this study. And the EEG features of the two subjects with the highest similarity are combined to generate an augmented feature set. On the condition of satisfying the authenticity of EEG, the augmented feature set is significantly better than the original feature set in data dimension and quality. Finally, we verify the classification effect of the augmented feature set, and the results show that the proposed method can effectively generate real EEG data and improve the classification performance to a high reliability level for complex boundary avoidance tasks under limited EEG conditions. In addition, we observe the obvious advantages of this model over traditional deep learning methods in terms of training time and memory overhead. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the incidence and clinical characteristics of chronic subdural haematoma (CSDH) evolving from traumatic subdual hydroma (TSH). Methods: The clinical characteristics of 44 patients with CSDH evolving from TSH were analysed retrospectively and the relevant literature was reviewed. Results: In 22.6% of patients, TSH evolved into CSDH. The time required for this evolution was 14-100 days after injury. All patients were cured with haematoma drainage. Conclusions: TSH is one possible origin of CSDH. The clinical characteristics of TSH evolving into CSDH include polarization of patient age and chronic small effusion. The injuries usually occur during deceleration and are accompanied by mild cerebral damage. [ABSTRACT FROM AUTHOR]

Background and aims: The aim of this study was to determine Zn/Cd accumulation ability and cellular distribution in Sedum plumbizincicola from a mine area. Methods: Spatial localization of S, Cl, K, Ca, Ti, Mn, Fe, Ni, Cu, Zn and Cd in frozen-hydrated sections of S. plumbizincicola was quantitatively determined using cryo-micro-PIXE. Results: The shoots of S. plumbizincicola hyperaccumulated up to 1,470 mg kg of Cd and 14,600 mg kg of Zn (dry weight) in field-grown plants. Micro-PIXE analyse shows that in roots Zn was concentrated in the cortex. In stems Zn was preferentially accumulated in the epidermis (5,090 mg kg wet weight) and in vascular bundles and neighbouring parenchyma cells. Interestingly, some vascular bundles of the stem were depleted in Zn. Taking tissue area into account, 22.1, 46.2 and 31.8 % of total Zn and 17.1, 71.6 and 11.3 % of total Cd in the stem were present in the epidermis, cortex and central cylinder, respectively. In the leaves, 81.3 % of total Cd and 55.2 % of total Zn were distributed in the mesophyll. Conclusions: The parenchyma cells, e.g. cortex in stem and mesophyll in leaf, play more important roles in Cd storage and detoxification than Zn in S. plumbizincicola. [ABSTRACT FROM AUTHOR]

Localization of Hg in root tissues of vetiver grass(Chrysopogon zizanioides)was investigated by micro-Proton Induced X-ray Emission (PIXE) spectrometry to gain a better understanding of Hg uptake and its translocation to the aerial plant parts. Tillers ofC. zizanioideswere grown in a hydroponic culture for 3 weeks under controlled conditions and then exposed to Hg for 10 days with or without the addition of the chelators (NH4)2S2O3or KI. These treatments were used to study the effects of these chelators on localization of Hg in the root tissues to allow better understanding of Hg uptake during its assisted-phytoextraction. Qualitative elemental micro-PIXE analysis revealed that Hg was mainly localized in the root epidermis and exodermis, tissues containing suberin in all Hg treatments. Hg at trace levels was localized in the vascular bundle when plants were treated with a mercury solution only. However, higher Hg concentrations were found when the solution also contained (NH4)2S2O3or KI. This finding is consistent with the observed increase in Hg translocation to the aerial parts of the plants in the case of chemically induced Hg phytoextraction. [ABSTRACT FROM AUTHOR]

Highlights: [•] An adsorption cogeneration was proposed and simulated for cooling and electricity. [•] A dynamic model was built and studied to demonstrate the variability of the system. [•] A dynamic model included the complex coupling of thermodynamic and chemical kinetic. [•] Mutual constrains between main components and optimisation methods were discussed. [•] The highest theoretical COP and exergy efficiency of cogeneration is 0.57 and 0.62. [ABSTRACT FROM AUTHOR]

In this paper, validated simulations using Ricardo WAVE have been performed to investigate the effect of the Miller cycle and low-carbon fuels on the performance (power, torque, BTE and BSFC) and emissions of a diesel engine. The results show that the increased Miller cycle effect (larger deviation of the advanced or retarded intake valve closing from the standard intake valve closing time) will decrease NOx, CO and HC emissions, and slightly improve brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) with slight loss in engine performance and increase in soot emissions. An engine running B0 (diesel with 0% Biodiesel in the blend) with a −18% Miller cycle effect has a reduction in NOx of 9% and CO of 4.3% with a decrease of 1.6% in power at the rated engine speed. Using low carbon fuels drastically reduces emissions with reduced BTE and increased BSFC. When used in conjunction, the Miller cycle and low-carbon fuels have an improved effect on both performance and emissions. The optimal results demonstrate that using B60 (60% Biodiesel in the blend) and a −8% Miller effect contributes to a 1.5% improvement in power, 1.2% in BTE, 13.3% in NOx, 38.5% in CO, 8.9% in HC, and 33.0% in soot at a cost of 6.0% increase in BSFC. The results show that it is an easy way to reduce NOx, CO, HC and soot emissions and increase the BTE of the engine by combining Miller cycle and low-carbon fuels. [ABSTRACT FROM AUTHOR]

Abstract: Based on Perceptual Control Theory, we study the problem of unified modeling for incompatible approaches of Cyber–Physical Systems (CPSs). Inspired by the effective organization of living systems structure accommodating heterogeneous information processing and environmental interaction, we propose Perceptual Control Architecture of CPSs, and take Traffic Incident Management systems as the modeling research carrier. Throughout the structure of Traffic Incident Management systems, the hierarchical negative feedback is constituted by perceptual and behavioral loops to ensure a mechanism of intelligence behavior. The internal representation is categorized into two intelligent spaces: physical-reflex space and cyber-virtual space. In physical-reflex space, the sensing-actuation mapping of objective world is built, through four levels of distributed traffic infrastructure. In cyber-virtual space, subjective decision using Bayesian reasoning network is defined by three levels: principles, interrelated factors and situation assessment. Through evaluation of field operation in Dalian, the Traffic Incident Management under the developed architecture shows a considerable reduction in response time as well as assessment inaccuracy. The test results explicated the effectiveness of the architecture on integrating complex Cyber–Physical functions. Besides transportation systems, the modeling approach could be a well-defined unified architecture applied to other CPSs. [Copyright &y& Elsevier]

Abstract: This study examined the performance and emission characteristics of a household size trigeneration based on a diesel engine generator fuelled with hydrogen comparing to that of single generation, cogeneration using ECLIPSE simulation software. In single generation simulation, the engine genset is used to produce electricity only and the heat from the engine is rejected to the atmosphere. In cogeneration and trigeneration, in addition to the electricity generated from the genset, the waste heat rejected from the hot exhaust gases and engine cooling system, is captured for domestic hot water supply using heat exchangers and hot water tank; and a part of the waste heat is used to drive absorption cooling in trigeneration. Comparisons have been made for the simulated results of these three modes of operation for hydrogen and diesel. The results prove that hydrogen is a potential energy vector in the future which is a key to meeting upcoming stringent greenhouse gases emissions. The study show that hydrogen has very good prospects to achieve a better or equal performance to conventional diesel fuel in terms of energetic performance, and a near zero carbon emission, depending on the life cycle analysis of the way the hydrogen is produced. The results also show enormous potential fuel savings and massive reductions in greenhouse gas emissions per unit of useful energy outputs with cogeneration and trigeneration compared with that of single generation. [Copyright &y& Elsevier]

Abstract: An experimental study of the performances and emissions of a diesel engine is carried out using two different biodiesels derived from Chinese pistache oil and jatropha oil compared with pure diesel. The results show that the diesel engine works well and the power outputs are stable running with the two selected biodiesels at different loads and speeds. The brake thermal efficiencies of the engine run by the biodiesels are comparable to that run by pure diesel, with some increases of fuel consumptions. It is found that the emissions are reduced to some extent when using the biodiesels. Carbon monoxide (CO) emissions are reduced when the engine run at engine high loads, so are the hydrocarbon (HC) emissions. Nitrogen oxides (NOx) emissions are also reduced at different engine loads. Smoke emissions from the engine fuelled by the biodiesels are lowered significantly than that fuelled by diesel. It is also found that the engine performance and emissions run by Chinese pistache are very similar to that run by jatropha biodiesel. [Copyright &y& Elsevier]

Abstract: The performance and the efficiency of a trigeneration system fueling with pure diesel and with raw jatropha oil are investigated using the ECLIPSE software. The study is based on a diesel engine generating set. The genset is used for electrical power generation only, acting as a single generation. The trigeneration system consists of the genset, a waste heat recovery system and an absorption refrigerator. The genset is used to generate electricity; the waste heat system is used to collect the waste heat from the cooling system and the exhaust from the engine, to supply heating/hot water; and the absorption refrigerator is used to supply cooling/refrigeration, which is driven by the waste heat from the engine instead of electricity. A comparison of the thermal efficiencies and the CO2 emissions of trigeneration with single generation and cogeneration (combined heat and power — CHP) is carried out. The results from the study show that the thermal efficiency of trigeneration is higher than that of single generation; the CO2 emissions of trigeneration are lower than that of single generation. The results also show the performance differences between the trigeneration and single generation; and the differences between trigeneration and cogeneration. [Copyright &y& Elsevier]

Abstract: A technical investigation of an innovative trigeneration integrated with absorption enhanced reforming (AER) of lignite and biomass is carried out using the ECLIPSE process simulator. The system includes an internal combustion engine, an AER gasifier, a waste heat recovery and storage unit and an absorption refrigerator. The whole system is operated in the following sequence: The AER gasifier is used to generate hydrogen using lignite and biomass; the hydrogen generated is used to run the engine which drives a generator to produce electricity. Additionally, the heat recovery unit collects waste heat from the engine and is used to supply hot water and space heating. Furthermore, the waste heat is used to operate the absorption refrigerator. The electricity, heat and cooling can be used to meet the energy requirements for the households in a village, a resident building or a commercial building, or a supermarket. Within the study, the effects of lignite mixed with three different types of biomass (straw, willow and switch grass) on the system performance are investigated and the results are compared. The results show that it is feasible to use an AER system to reform the low quality fuels lignite and biomass to generate a cleaner fuel – hydrogen to replace fossil fuels (diesel or natural gas) and to fuel an engine based trigeneration system; the system works with high efficiencies and with a potential of carbon capture from the sorbent-regeneration process that would benefit the environment. [Copyright &y& Elsevier]

• The dual-mode soft sensor is intrinsically embedded in different soft robots. • The dual-mode soft sensor can sense pressure and temperature simultaneously without mutual interference. • The soft robots can recognize size, weight, temperature variation and hardness of the contact object. • This work provides a new approach to integrate soft robots and soft sensors. [Display omitted] Soft sensing is indispensable for precisely manipulate and recognize objects in soft robotics. However, it is a challenge to better integrate soft robots with soft sensors because the sensing performances of soft sensors will be induced by mechanical stress and deformation to change and degrade. Herein, we propose a new design of intrinsically embedded pressure-temperature dual-mode soft sensors in soft robots to sense external stimuli. The soft sensor consists of a skin-inspired structure, the chief material prepared is equivalent to that of the soft robot, with high sensitivity, excellent repeatability and robustness. It can perceive the pressure and temperature of objects simultaneously and independently without mutual interference. Furthermore, we demonstrated that the soft sensor integrates with different soft robots to recognize the size, weight, temperature variation and hardness of the contact object. This work provides a new approach to integrate soft robots and soft sensors, which has great potential in vast robot-human and robot-environment applications. [ABSTRACT FROM AUTHOR]

Simple Summary: Excessive fat deposit is one of the major problems in finishing Ningxiang pigs, and adversely affects the breeding. The study aimed to investigate the effects of diet with betaine supplementation (basal diet + 0.2% betaine) on the growth performance, slaughter performance, meat quality and the genes expression related to fat deposition in finishing Ningxiang pigs. The results indicated that diet with betaine supplementation decreased back fat thickness and fat percentage, and increased the lean meat percentage as well. In addition, it reduced the fat deposition by regulating the genes expression. These findings provided a reference for breeding Ningxiang pigs. The present study was conducted to investigate the effects of diet with betaine supplementation on the growth performance, carcass quality and fat deposition in finishing Ningxiang pigs. A total of 24 Ningxiang pigs (43.6 ± 5.34 kg of average body weight) was randomly divided into two groups, with 6 replicates per treatment and 2 pigs per replicate. The treatments included a control group (basal diet) and a test group (basal diet + 0.2% betaine). The whole trial lasted 81 days. At the end of the experiment, one pig (close to the average body weight of all experimental pigs) per replicate was slaughtered to determine the carcass traits, meat quality and the mRNA expression levels of genes relate to fat deposition (one pig per replicate was randomly selected and fasted for 12 h, n = 6). Results indicated that growth performance was not changed with betaine supplementation. However, dietary with betaine supplementation decreased back fat thickness and fat percentage, and increased the lean meat percentage as well (p < 0.05). In addition, diet with betaine supplementation reduced drip loss, water loss, cooking loss, shear force and b × 24 h value of meat (p < 0.05). There was no difference in total moisture, ether extract and crude protein of longissimus thoracis between the control and test group. Dietary with betaine supplementation decreased ether extract and total cholesterol (p < 0.05) in liver. Dietary with betaine supplementation upregulated the mRNA expression levels of adipose triglyceride lipase (ATGL) and sirtuin 1 (Sirt1), while downregulated the mRNA expression levels of fatty acid synthase (FAS) and acetyl CoA carboxylase (ACC) in subcutaneous fat of back (p < 0.05). Besides, dietary with betaine supplementation upregulated the fatty acid binding protein 4 (FABP4) mRNA expression of longissimus thoracis in finishing Ningxiang pigs (p < 0.05). These results showed that diet supplemented with betaine could improve the slaughtering performance and meat quality, and regulate the genes expression to affect the fat deposition in finishing Ningxiang pigs. [ABSTRACT FROM AUTHOR]

Abstract: A conceptual analysis of the mechanism of the Miller cycle for reducing NO x emissions is presented. Two versions of selected Miller cycle (1 and 2) were designed and realized on a Rover “K” series 16-valve twin-camshaft petrol engine. The test results showed that the application of the Miller cycle could reduce the NO x emissions from the petrol engine. For Miller cycle 1, the least reduction rate of NO x emission was 8% with an engine-power-loss of 1% at the engine’s full-load, compared with that of standard Otto cycle. For Miller cycle 2, the least reduction rate of NO x emission was 46% with an engine-power-loss of 13% at the engine’s full-load, compared with that of standard Otto cycle. [Copyright &y& Elsevier]

Abstract: Low bioavailability of mercury (Hg) in soil is a restricting factor in phytoextraction of Hg-contaminated soil. Iodide is known to mobilize Hg in soil and, therefore, the aim of this study was to investigate the possibility to use iodide to increase phytoextraction of Hg. The sensitivity of willow to iodide was investigated in both hydroponics with 0–10 mM KI and in soil with 0.2 and 1 mM KI addition. The capacity to accumulate HgI2 was compared with that of Hg(NO3)2 in hydroponics. Soil extractions with 0–2 mM KI were used to study mobilization of Hg in aged Hg-spiked soil. Additions of KI (0.2–1 mM) were used in pot tests with aged Hg-spiked soil as well as in field trials in an industrial Hg-contaminated soil to study whether iodide addition increased the accumulation of Hg from contaminated soil and the translocation of Hg to the shoots. The total Hg contents in plants, soils and extracts were analyzed by CVAAS. The results showed that too high KI concentration was toxic to plants. Moreover, KI was toxic to plants at lower concentrations in hydroponics than in soil additions. KI (85 μM) in hydroponics gave 50% growth decrease in terms of dry weight of shoot biomass, whereas 0.2 mM KI in soil addition could be tolerated by the plant without growth disturbance. Willow accumulated Hg from HgI2 solution slower than that from Hg(NO3)2 solution. KI mobilized Hg in contaminated soil and thereby increased the bioavailability of Hg in soil. Up to 1 mM KI addition increased the Hg concentrations to about 5, 3 and 8 times, respectively, in the leaves, branches and roots. However, the Hg translocation to the shoots did not show an increase with KI addition. Only less than 1% of the total Hg accumulated in the plant was distributed in the shoots. We may conclude that iodide addition enhances the phytoextraction of Hg, however, the translocation of Hg to the shoots is still too low and therefore it will not be realistic to use this method for phytoextraction of Hg-contaminated soil in practice. [Copyright &y& Elsevier]

This study investigated the effect of willow ( Salix viminalis × S. schwerinii) on soil characteristics, including changes in Hg fractionation in the soil solid phase, and Hg accumulation and distribution in pot-grown plants cultivated for 32 and 76 days in aged Hg-contaminated soil (30 mg Hg kg−1DW). Changes in soil pH and organic carbon content as well as in Hg fractionation were monitored in both rhizospheric soil and in soil without plants. Mercury fractionation was performed by a 5-step sequential soil extraction procedure. Organic carbon content increased while pH decreased in the rhizospheric soil. Both chemically defined exchangeable Hg (0.1) and Hg bound to humic and fulvic acids (1.1) decreased in the rhizospheric soil, whereas plant accumulation of Hg increased with cultivation time. The sum of the decrease of these two soil Hg fractions after 76 days of cultivation was approximately equal to the amount of Hg accumulated in plants. Furthermore, the major Hg fractions (Hg bound to residual organic matter (53), sulphides (43), and the residual fraction (2.5)) remained stable. Neither whole plant accumulation of Hg from the soil, approximately 0.2 of total Hg in soil after 76 days cultivation, nor the fraction of total plant Hg in the shoots, which accounted for about 3 of the total plant Hg pool regardless of the cultivation time, were high. The overall results suggest that plants might be suitable for phytostabilization of aged Hg-contaminated soil, where root systems trap bioavailable Hg and help to control both leaching of Hg and re-entrainment of Hg-containing particulates from a contaminated site. [ABSTRACT FROM AUTHOR]

This paper focuses on the investigation and optimisation of the Miller cycle, methanol, ethanol and turbocharging when applied to a high-performance gasoline engine. These technologies have been applied both individually and concurrently to test for potential compounding effects. Improvements have been targeted with regards to both emission output and performance. Also assessed is the capability of the engine to operate when exclusively powered by biofuels. This has been carried out numerically using the 1D gas dynamics tool 'WAVE', a 1D Navier–Stokes equation solver. These technologies have been implemented within the McLaren M838T 3.8L twin-turbo engine. The Miller cycle early intake valve close (EIVC) improved peak efficiency by 0.17% and increased power output at low and medium loads by 11%. Reductions of 6% for both NOx and CO were also found at rated speed. The biofuels achieved NOx and CO reductions of 60% and 96% respectively, alongside an efficiency increase of 2.5%. Exclusive biofuel use was found to be feasible with a minimum 35% power penalty. Applied cooperatively, the Miller cycle and biofuels were not detrimental to each other, compounding effects of a further 0.05% efficiency and 2% NOx improvements were achieved. [ABSTRACT FROM AUTHOR]

With the rise of the concept of carbon neutrality, carbon-free fuel ammonia has attracted widespread attention from internal combustion engine researchers. Ammonia/diesel dual fuel mode can effectively overcome the ignition difficulty of ammonia in the engine and is an effective measure to promote ammonia combustion. Based on a single-cylinder engine, diesel-ignited ammonia combustion experiments were conducted under conditions of 1200 rpm and 30 % load to systematically study the impact of ammonia energy ratio (AER), pilot injection ratio/timing on the combustion and emission characteristics of the ammonia/diesel dual fuel engine. This study finds that the pilot injection improves the upper limit of AER, reduces the cyclic coefficient of variation (COV). The rapid combustion fraction has been defined to understand the dual fuel combustion process. With the AER increases, the rapid combustion fraction of the single injection increases while the trends of the pilot injection strategy are the opposite. Both NOx emissions of the pilot injection strategies decrease while CO emissions increase. The reduction of NOx emissions may be caused by a decline in in-cylinder temperature. At a 35 % AER,Medium-low pilot injection ratios can increase the indicated mean effective pressure (IMEP), which is because as the pilot injection ratio exceeds 35 %, the growth rate in the effective expansion efficiency (EEE) is lower than that of heat transfer loss. When the pilot injection ratio is 35 %, the highest IMEP is achieved, CO and NOx emissions are cut down by 23 % and 20 %, respectively, compared to the single injection. [Display omitted] • Detailed investigation on ammonia/diesel dual fuel mode under low engine load. • Pilot injection strategy reduces the cyclic coefficient of variation. • The rapid combustion fraction has been defined to help understand the combustion process. • The highest IMEP is achieved while CO and NOx reduce by 23 % and 20 % with pilot injection. [ABSTRACT FROM AUTHOR]

• Synergistic path planning of multi-UAVs among sailing vessels for the air pollution inspection. • Develop a dynamic multi-objective TSP model. • A heuristic algorithm based on improved PSO is proposed to determine the path reprogramming time in dynamic environment by judging and cutting the "minimal loop". • Experimental results show that our proposed method can efficiently solve the problem. The phenomena of the COVID-19 outbreak and the Arctic Iceberg melting over the past two years make us reconsider the impact our way of life has on the environment and the responsibility of business toward minimizing and potentially eliminating emissions. Increasing ship traffic in ports leads to the growing emission of air pollutants, which influences the air quality and public health in the surrounding areas. The International Maritime Organization (IMO) has adopted relevant regulations (e.g., Annex VI of IMO's pollution prevention treaty (MARPOL) and mandatory energy-efficiency measures) to address ship emissions. To ensure the effective implementation of such regulations and measures, air emission detection and monitoring has become crucial. In this paper, a dynamic multitarget path planning model is developed to realize multi-UAVs (Unmanned Aerial Vehicles) performing synergistic detection of ship emissions in ports. A path planning algorithm under a dynamic environment is developed to establish the model. This algorithm incorporates a Tabu table into particle swarm optimization (PSO) to improve its optimization ability, and it obtains the initial detection route of each UAV based on a "minimum ring" method. This paper describes a multi-UAVs synergistic algorithm to formulate the path reprogramming time in a dynamic environment by judging and cutting the "minimum ring". This finding proves the improved efficiency of air pollution detection by UAVs. It provides useful insights for maritime and port authorities to detect ship emissions in practice and to ensure ship emission reduction for better air quality in the postpandemic era. [ABSTRACT FROM AUTHOR]