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Rigid robotic hands are generally fast, precise and capable of exerting large forces, whereas soft robotic hands are compliant, safe and adaptive to complex environments. It is valuable and challenging to develop soft-rigid robotic hands that have both types of capabilities. The paper aims to address the challenge through developing a paradigm to achieve the behaviors of soft and rigid robotic hands adaptively.

The design principle of a two-joint finger is proposed. A kinematic model and a stiffness enhancement method are proposed and discussed. The manufacturing process for the soft-rigid finger is presented. Experiments are carried out to validate the accuracy of the kinematic model and evaluate the performance of the flexible body of the finger. Finally, a robotic hand composed of two soft-rigid fingers is fabricated to demonstrate its grasping capacities.

The kinematic model can capture the desired distal deflection and comprehensive shape accurately. The stiffness enhancement method guarantees stable grasp of the robotic hand, without sacrificing its flexibility and adaptability. The robotic hand is lightweight and practical. It can exhibit different grasping capacities.

It can be applied in the field of industrial grasping, where the objects are varied in materials and geometry. The hand’s inherent characteristic removes the need to detect and react to slight variations in surface geometry and makes the control strategies simple.

This work proposes a novel robotic hand. It possesses three distinct characteristics, i.e. high compliance, exhibiting discrete or continuous kinematics adaptively, lightweight and practical structures.

The purpose of this paper is to investigate the effect of selective laser sintering (SLS) method on morphology and performance of polyamide 12.

Crystallization behavior is critical to the properties of semi-crystalline polymers. The crystallization condition of SLS process is much different from others. The morphology of polyamide 12 produced by SLS technology was investigated using scanning electron microscopy, polarized light microscopy, differential scanning calorimetry, X-ray diffraction and wide-angle X-ray diffraction.

Too low fill laser power brought about bad fusion of powders, while too high energy input resulted in bad performance due to chain scission of macromolecules. There were three types of crystal in the raw powder material, denoted as overgrowth crystal, ring-banded spherulite and normal spherulite.

In this work, SLS samples with different sintering parameters, as well as compression molding sample for the purpose of comparison, were made to study the morphology and crystal structure of sintered PA12 in detail.

The purpose of this paper is to bring up the concept of multi‐material electromagnetic band‐gap structure (EBGs) and develop a method for its fabrication. Meanwhile, its microwave properties were studied and compared with the traditional EBGs consisting of two kinds of material.

Stereolithography (SL) and gel casting were used to fabricate 3D multi‐material EBGs. Resin mold was designed and fabricated based on SL process, slurries loaded with 55vol per cent Al₂O₃ and 55vol per cent TiO₂, respectively, were prepared, and using gel casting, multilayer EBGs with diamond structure were fabricated. T/R method was used to obtain the characteristic parameter S₂₁ of the EBGs; meanwhile, characters of their band structure were studied based on plane wave expansion method.

The fabricated EBGs with a TiO₂‐resin‐air structure showed a band gap from 11.7 GHz to 16.0 GHz along <1, 1, 0> direction; the EBGs with a TiO₂‐resin‐Al₂O₃ structure showed a band gap from 11.4 GHz to 11.9 GHz along <1, 1, 0> direction. Both of them agreed well with the simulation result. Also, through the study of multi‐material EBGs' microwave properties, it could be seen that this structure was a good approach to adjust the band gap.

With the concept of multi‐material EBG structure brought up, multilayer 3D EBGs were designed and fabricated based on SL combined with gel casting. It could be seen that multi‐material EBGs was a good approach to adjust the band gap. Also, the fact that the testing result matched the simulation validates the feasibility of the process.

The purpose of this paper is to investigate the electrochemical corrosion behavior of type 444 stainless steel (SS) in synthetic tap water from 25°C to 80°C, i.e. the operation environment of the electric water heater.

The corrosion behavior was studied by using electrochemical measurements such as electrochemical impedance spectroscopy and polarization curve. The specimen surfaces were observed with scanning electron microscopy. The passive films were characterized with X-ray photoelectron spectroscopy.

In the typical tap water, 444 SS passivates spontaneously under different temperatures. The passive films formed at higher temperatures contain relatively less Cr-species and more Cl⁻ ions, resulting in lower polarization resistances. The stable pitting corrosion takes place in the potential region of oxygen evolution as the temperature increases to about 55°C. The critical Cl⁻ concentration of pitting corrosion reduces from about 160 mg L⁻¹ to 60 mg L⁻¹ with changing temperature from 25°C to 80°C.

The pitting corrosion probability was assessed through the statistical analysis of tap water quality. The results are useful for the application of 444 SS as well as the design of electric water heater.

This paper shows the variation of polarization resistance, pitting potential, passive film composition and critical pitting chloride concentration with the temperature of tap water. It is of great significance for the development and application of SS in tap water environments.

Mining user-concerned actionable and interpretable hot topics will help management departments fully grasp the latest events and make timely decisions. Existing topic models primarily integrate word embedding and matrix decomposition, which only generates keyword-based hot topics with weak interpretability, making it difficult to meet the specific needs of users. Mining phrase-based hot topics with syntactic dependency structure have been proven to model structure information effectively. A key challenge lies in the effective integration of the above information into the hot topic mining process.

This paper proposes the nonnegative matrix factorization (NMF)-based hot topic mining method, semantics syntax-assisted hot topic model (SSAHM), which combines semantic association and syntactic dependency structure. First, a semantic–syntactic component association matrix is constructed. Then, the matrix is used as a constraint condition to be incorporated into the block coordinate descent (BCD)-based matrix decomposition process. Finally, a hot topic information-driven phrase extraction algorithm is applied to describe hot topics.

The efficacy of the developed model is demonstrated on two real-world datasets, and the effects of dependency structure information on different topics are compared. The qualitative examples further explain the application of the method in real scenarios.

Most prior research focuses on keyword-based hot topics. Thus, the literature is advanced by mining phrase-based hot topics with syntactic dependency structure, which can effectively analyze the semantics. The development of syntactic dependency structure considering the combination of word order and part-of-speech (POS) is a step forward as word order, and POS are only separately utilized in the prior literature. Ignoring this synergy may miss important information, such as grammatical structure coherence and logical relations between syntactic components.

This study aims to evaluate the effectiveness of different prefabricated construction (PC) policies using a case study in Wuhan, considering the local context.

The effectiveness of PC policies is falling behind expectations. The main reason lies in an insufficient understanding of the policy impacts. An agent-based model was built by choosing the residential sector in a typical large city of Wuhan, China, as the study case. Different cost reduction scenarios were introduced for investigating the PC policy effectiveness. The proposed model and simulation approach can be used for other cities and generalized to the whole Chinese PC industry with the potential to include more local policies and corresponding data.

Simulation results show that carbon emission reduction will be between 60,000 and 80,000 tons with policy incentives, nearly double that of the no policy intervention scenario. The target of 30% PC in all new buildings by 2026 in China is achievable with the subsidy policies of linear cost reduction, or cost reduction conforms to the learning curve.

Simulation results of three kinds of policy show that subsidy policy optimization is necessary regarding reducing the level of subsidy needed. The carbon credit policy is not essential since it has little influence on PC development. Implementing the project procurement restriction policy is not recommended if the scale of development of PC is more important than achieving the development target.

This study can help the government and developers make better policy and strategic decisions on PC development and boost the sustainability transition of the construction industry.

The purpose of this study is to estimate different data models on house prices using statistical models and the variables which are controlled by real estate policy.

This study used several statistical techniques, such as Vector auto-regression (VAR), Johansen co-integration and variance decomposition, which aim to assess the significant effect of macroeconomic factors on Chinese house prices.

The results show that land supply and other variables have negative effects on house prices. The results also indicate that financial mortgages for real estate have positive effects on house prices and the area of vacant houses as well as the area of housing sold.

This study only covers three cities in China because of limitations of data for other cities.

This study proposes policy suggestions according to the empirical results obtained.

Reverse logistics (RL), an inseparable aspect of supply chain management, returns used products to recovery processes with the aim of reducing waste generation. Enterprises, however, seem reluctant to apply RL due to various types of risks which are perceived as posing an economic threat to businesses. This paper draws on a synthesis of supply chain and risk management literature to identify and cluster RL risk factors and to recommend risk mitigation strategies for reducing the negative impact of risks on RL implementation.

The authors identify and cluster risk factors in RL by using risk management theory. Experts in RL and supply chain risk management validated the risk factors via a questionnaire. An unsupervised data mining method, self-organising map, is utilised to cluster RL risk factors into homogeneous categories.

A total of 41 risk factors in the context of RL were identified and clustered into three different groups: strategic, tactical and operational. Risk mitigation strategies are recommended to mitigate the RL risk factors by drawing on supply chain risk management approaches.

This paper studies risks in RL and recommends risk management strategies to control and mitigate risk factors to implement RL successfully.