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Clearance exists in mechanical equipment, which aggravates the friction and wear in moving pairs and reduces the use accuracy of mechanism. So as to reduce the impact of clearance on industrial equipment, lubricating oil is usually added to the clearance of moving pair. The lubricating oil can effectively reduce the collision and vibration between components and reduce noise. Previous studies mainly concentrated on the research of dry clearance joints, but less on clearance lubrication. At the same time, there is little research on nonlinear characteristic of lubrication clearance. For the sake of studying the impact of lubrication clearance with multiple revolute joints on mechanical system, the dynamic response and nonlinear characteristic of planar six-bar linkage are analyzed. The movement model of lubrication clearance is developed, and lubrication force of lubrication clearance is modeled by modified Pinkus–Sternlicht model. Dynamical model of lubrication clearance of planar six-bar linkage is established by Lagrange multiplier method. The impacts of lubrication, viscosity coefficient, clearance value and driving speed on dynamic of mechanism with lubrication clearance are explored. By drawing bifurcation diagram, phase trajectory diagram and Poincare map, the nonlinear characteristic of mechanism with lubrication clearance is studied.

Recently designed passenger vehicles with heightened features are entering the market every year. One of them is the power window which enables the fast movement of window-panes. Not opening of window-pane in an emergency is responsible for the death of passengers in some cases. Deaths of children, the disabled or older person have been reported due to carbon monoxide(CO) poisoning. Simultaneously, they were allowed to stay inside a static, locked car in the absence of other assisting occupants. Fatal injuries have also been reported repeatedly due to the sinking of the vehicle in a water body. In this paper, the design of an automatic opening mechanism is discussed for a car window during such crises. In this system, the temperature sensor, Carbon-monoxide sensor and water pressure sensor are placed inside a car cabin to monitor the temperature range, CO levels and water pressure continuously. In case of high internal temperatures or raised carbon monoxide in the cabin due to incomplete fuel combustion or excessive heat or vehicle rested under the Sun for long, or if the vehicle is subjected to pressure by flowing or static water, the sensors send signals to the motor controlling power window to slide it down. It also sends a warning message to the registered mobile phone of the vehicle owner.

Data Envelopment Analysis (DEA) is a linear programming methodology for measuring the efficiency of Decision Making Units (DMUs) to improve organizational performance in the private and public sectors. However, if a new DMU needs to be known its efficiency score, the DEA analysis would have to be re-conducted, especially nowadays, datasets from many fields have been growing rapidly in the real world, which will need a huge amount of computation. Following the previous studies, this paper aims to establish a linkage between the DEA method and machine learning (ML) algorithms, and proposes an alternative way that combines DEA with ML (ML-DEA) algorithms to measure and predict the DEA efficiency of DMUs. Four ML-DEA algorithms are discussed, namely DEA-CCR model combined with back-propagation neural network (BPNN-DEA), with genetic algorithm (GA) integrated with back-propagation neural network (GANN-DEA), with support vector machines (SVM-DEA), and with improved support vector machines (ISVM-DEA), respectively. To illustrate the applicability of above models, the performance of Chinese manufacturing listed companies in 2016 is measured, predicted and compared with the DEA efficiency scores obtained by the DEA-CCR model. The empirical results show that the average accuracy of the predicted efficiency of DMUs is about 94%, and the comprehensive performance order of four ML-DEA algorithms ranked from good to poor is GANN-DEA, BPNN-DEA, ISVM-DEA, and SVM-DEA.

This paper aims to investigate whether oil volatility risks could diffuse through the linkage of industry returns and even further contribute to global crisis throughout the stock market. To highlight such sectoral financial interconnectedness which may serve as a key channel for oil volatility diffusion, we first apply the partial cross-quantilogram (PCQ) approach to detect the directional predictability between returns of 26 industries in China's stock market across different quantiles. We construct the corresponding network to provide a more comprehensive picture of such sectoral interconnection, which is shown to vary prominently under different market states and lag order specifications. Utilizing the spatial autoregressive (SAR) model for panel data, we further assess the possibility of the oil volatility risk diffusion by decomposing the aggregate effect of oil volatility shocks into direct shocks, and indirect shocks transmitting through the estimated network linkage of industries. The empirical results point to the significantly heterogeneous pattern of oil volatility risk diffusion among networks with different lag selections under various market states. Considering the financial linkage of industries within 5 traded days under extreme market states, there exist significant indirect effects contributing to larger oil volatility shocks on industry returns, which confirms risk contagion effects of monthly oil volatilities. It indicates that the network linkage of financial assets might be an important diffusion mechanism for oil volatility risks, which should not be neglected in the research of the oil-stock nexus.

The extant literature examines the impact of US uncertainty on international stock markets without paying much attention to the inherent spillovers between the US and the stock markets. This study investigates the role of US uncertainty in driving global stock market spillover from the US. To this end, we consider a wide range of stock markets around the world and three news-based uncertainties from the US, namely economic policy uncertainty (EPU), equity market uncertainty (EMU), and equity market volatility (EMV). We find that the US uncertainties significantly explain the spillovers from the US to global stock markets. This causality from US uncertainties depends upon certain country-characteristics. Specifically, the US uncertainties better explain the spillovers between the US and target countries when those countries have a higher degree of financial openness, trade linkage with the US, and vulnerable fiscal position. However, improved stock market development levels in the target countries mitigate their stock markets' vulnerability to US uncertainty shocks. The study offers potential insights and implications for investors and policymakers.

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG [Abstract] Deployable bar structures are especially useful for emergency buildings. These structures require simplicity and ease of assembly and their performance can be improve by using reciprocal linkage at their bars ends. This reciprocal configuration determines singular constructive conditions that allow all types of cylindrical vaults. This article develops this new system, from a previously theoretical analysis to a test campaign that allows verifying the validity of the proposal. Comparing these results with those resulting from construction systems with straight scissor-like elements or imposed curvature, shows the adequacy of this new proposal, verifying the advantages of the reciprocal joints in cylindrical vaults configurations. This study is part of the research project “Deployable and modular constructions for situations of humanitarian catastrophe”, funded by the Ministry of Economy and Competitiveness of the Kingdom of Spain with reference BIA2016-79459-R. Funding for open access charge: Universidade da Coruña/CISUG

This paper examines the effects of HSR development on airport technical efficiency and the labor productivity at airports. Existing literature mainly focuses on the impacts of HSR on passenger traffic. In addition to passengers, HSR development may influence airports' other outputs such as cargo and flight movements together with various inputs. These inputs and outputs collectively determine airports' technical efficiency. With access to a dataset consisting of 46 Chinese airports and 16 Japanese airports from 2007 to 2015, the paper firstly adopts both the standard two-stage Data Envelopment Analysis (DEA) and double bootstrap methods to evaluate the impacts of HSR development on airports’ technical efficiency. We then evaluate the effects of HSR on airport labor productivity which is measured by both work-load units per employee and aircraft movements per employee. Our main findings indicate that HSR development relates to a decline in airport efficiency. Airports located in cities that have better connectivity or accessibility in the HSR network suffer more efficiency loss than the others. It is also observed that the locational advantage of HSR stations relative to airports is negatively associated with airport efficiency. By contrast, good intermodal linkage between the airport and its nearest HSR station is positively correlated with airport efficiency. Furthermore, the study reports different results between China and Japan with respect to the effects of HSR on labor productivity.

The development of IoT techniques and the automation enabled by trigger-action platforms have brought great convenience to human life. However, with time the proliferating IoT devices will eventually overwhelm such platforms. Specifically, the ever-increasing huge amount of linkage rules significantly challenge the response rate as well as the efficiency of conflict rule detection, which will lead to terrible user experience and disastrous security issues. In this work, we develop a rule engine system for large-scale trigger-action applications. The key insight is that the linkage rules can be executed independent from the central cloud platform, which only require edge-side gateways and an efficient addressing strategy. The platform-side maintains an global image consisting of mappings between rules and gateway addresses, while edge-side rule engine is designed based on an open source tool, i.e., Drools. The implemented RETE algorithm helps to carry out large-scale linkage rules. In addition, we design a lightweight yet effective conflict detection algorithm that categorizes those rules into several types to downgrade the computation complexity. Experiments prove that the system can reduce the resource consumption of the platform-side and remarkably enhance the response speed. Moreover, our system also achieve a high efficacy when detecting conflicts.

By combining linkage analysis and the multi-objective programming model, this study establishes a fresh analytical framework that embeds tourism-related sectors to identify the direction of change in the structure of the tourism industry for a low-carbon economy. In a demonstration of the analytical framework, it is applied to an empirical study of China. The main results reveal that most tourism-related sectors are not key emission sectors, and that significant heterogeneity exists in the economic and emission linkage characteristics of these tourism-related sectors. In the optimal scenario, increasing the output of tourism by using the optimal production structure reduces the emission intensity of tourism and offsets macroeconomic losses caused by emission constraints. In the optimisation of the industrial structure aimed at a low-carbon economy, the direction of change in output varies across tourism-related sectors. Therefore, it is essential to avoid promoting emission reductions indiscriminately across the tourism industry. Finally, the practicality and implications of the proposed analytical framework are illustrated.

The unpredictability of Indian Summer Monsoon (ISM) remains an area of major challenge for operational forecasters. The distribution of active and break days in a monsoon season, though of utmost importance is very difficult to predict. In this regard, the geostationary satellite observations from Indian National Satellite System-3D (INSAT-3D) satellite over the Indian region provide significant insights into the propagation of ISM. In this manuscript, the correlation of satellite derived cloud microphysical parameters (CMP) to the strength and development of the ISM is studied objectively for the years 2017 and 2018. In particular, the association of the CMP to the active and break spell has also been investigated. It is found that the Cloud Particle Effective radius (CER) and the Cloud Optical Thickness (COT) bears a maximum correlation of 0.67 and 0.65 with the daily average rainfall at 1 day lag. The histogram analysis with active/break conditions show that CER exhibit a bimodal distribution (~27 µm and ~36 µm) during an active spell, while in case of break phase, smaller cloud droplets ranging in size between 15 and 25 µm is prevalent. The findings of the study will contribute towards better understanding and prediction of active and break spells of ISM.

A huge amount of sensitive personal data is being collected by various online health monitoring applications. Although the data is anonymous, the personal trajectories (e.g., the chronological access records of small cells) could become the anchor of linkage attacks to re-identify the users. Focusing on trajectory privacy in online health monitoring, we propose the User Trajectory Model (UTM), a generic trajectory re-identification risk predicting model to reveal the underlying relationship between trajectory uniqueness and aggregated data (e.g., number of individuals covered by each small cell), and using the parameter combination of aggregated data to further mathematically derive the statistical characteristics of uniqueness (i.e., the expectation and the variance). Eventually, exhaustive simulations validate the effectiveness of the UTM in privacy risk evaluation, confirm our theoretical deductions and present counter-intuitive insights.

Small and medium-sized enterprises (SMEs) engaging in foreign operations have drawn significant research attention in recent years. One of the aspects linked to such operations is SMEs’ expansion to foreign markets, often relying on local intermediaries. These intermediaries provide the firms with valuable resources such as market knowledge and recognition and reduce foreign operations’ costs. Hence, they are often considered as strategic partners. The current study aims to expand the existing knowledge regarding the relationships between business to business SMEs and their intermediaries by exploring interaction orientation as an organizational cultural aspect and its linkage to the trust-conflicts balance. Based on a survey of 165 international venture managers, complemented by in-depth interviews with 16 senior export managers, we found that by incorporating interaction-orientation constructs into the relationship management, SMEs can enhance affective trust while mitigating conflicts. We also reveal that the impact of emotional and task conflicts on SMEs’ performance is mediated through calculative trust, indicating the benefits of balancing between relational and formal governance.

This research investigates the heterogeneous dynamic impacts of rural-urban migration and industrial agglomeration on the environmental degradation across regional development levels of Chinese provinces. An aggregated data set of 31 provinces, along with three provincial-scale panels, are used from 2005 through 2018. The long-run parameter estimates are obtained employing dynamic common correlated effects mean group technique (DCCEMGT), while the heterogeneous Granger non-causality Dumitrescu-Hurlin test is employed for causal directions. The core results are as follows. Firstly, a unidirectional positive linkage is revealed from industrial agglomeration and rural-urban migration to energy utilization. These linkages showed heterogeneity across the development levels—the most substantial impacts are discovered in highly developed regions (eastern provinces), while the least substantial are found in low developed regions (western provinces). Secondly, the combined impacts of linear and non-linear parameters of both industrial agglomeration and rural-urban migration confirmed environmental Kuznets curves (EKCs) in models with the tertiary sector. However, in the model with the secondary sector, only EKC based on rural-urban migration is verified. Finally, rural-urban migration mitigated the environmental degradation more substantially in the model with tertiary sector-based industrial agglomeration. It suggests that rural to urban migration contributes less to the environmental emissions through the economy's service sector.

In this study, we identify two typical donation strategies, i.e., the fire-suppressing approach and the proactive approach, for window-dressing environmental misconduct. For a sample of 2582 small Chinese companies, we find that pollution fines are positively associated with corporate charitable donations, implying that firms use charitable donations as a fire-suppressing method to address the negative impact of environmental misconduct. We also found a positive relationship between pollutant emissions and corporate charitable donations, which supports the hypothesis that firms use a proactive approach (i.e., more consistent charitable donations) to reduce the negative impact of environmental misconduct. The relationship between pollution fines and corporate charitable donations is positively moderated by advertising expenses, suggesting that small and medium-size enterprises (SMEs) with higher branding expenses are more likely to take a fire-suppressing approach. Politically connected SMEs are more likely to take a proactive approach whereas SMEs without political connections are more likely to take a fire-suppressing approach.

This article reviews how objects can serve as indicators of one's identity and signals of important life events. Objects carry both personal and social meaning, and ownership or usage increases the linkage between the object and the self. Owned objects are valued more due to their linkage with the (positively viewed) self. Similarly, self-views can assimilate to the associations of the owned or used object. We rely on the insights of consistency theories (e.g. Balance Theory) to provide a unifying umbrella for the literature, and we review how the acquisition and abandonment of objects can shape self-views, affect task performance, and serve as inward and outward signals of group membership.

In the crowdsourcing task allocation scheme, there is an emerging and realistic co-opetition phenomenon. To availably solve the crowdsourcing task allocation problem with co-opetition, this paper designs a two-stage co-opetition model by constructing novel three-way decision (TWD), including a competition-optimization model and a negotiation-cooperation model. Unlike the other studies, the two-stage co-opetition model with TWD can not only protect the profits of the task candidates, but also optimize the overall benefits. Specifically speaking, in the competition-optimization model, we construct an optimization model based on the data envelopment analysis (DEA) method in advance, which maximizes the personal benefit. By integrating information system and the loss function matrix, we consider the linkage of evaluation information and risk information and then improve the original TWD to make an initial allocation. In the negotiation-cooperation model, considering that the relationship among the candidates may influence the task performance, the fuzzy measure is introduced to describe a broader partnership. Meanwhile, we also design two different schemes to coordinate and optimize the best task allocations based on the initial allocation. In order to choose the best scheme, the selection strategy between schemes is further investigated under the guidance of the utility and the loss. Finally, we give an example of a medical supply chain crowdsourcing problem to illustrate and verify our proposed approach.

The integral shrouded blisk provides better performance with minimum weight, but its semi-open structure presents problems for its production. Manufacturing processes of these components require a removal of about 70%-90% of material from their blanks. Multi-axis electrical discharge machining (EDM) is commonly used for these processes, but its poor efficiency cannot meet the requirements of mass production. Strong flushing assisted high-current discharge is able to improve the machining efficiency. In this paper, this method was applied to manufacture the integral shrouded blisk. An electrode design method was proposed. Taking the largest revolving entity inside the flow channel as the base geometry, this laminated arc-shaped hollow electrode meets the requirements such as high pressure flushing, tool wear compensation, and easy to be made. A 4-axis linkage machining tool path with planetary motion was proposed. Taking an integral guide vane ring as an example, it has been experimentally verified that the time consumption for each channel using this method was reduced to a half of the ordinary EDM method, while the finished surface quality remains same.

Motivated by the risen linkage between events and Bitcoin return, this paper first defines Bitcoin-related events (BREs) based on the change points analysis and then divides these events into two categories. Furthermore, we model the impact of BREs on the Bitcoin market activities, using an event study methodology and a GARCH-X model. Empirical results show that the shock directions of Bitcoin-related events on Bitcoin price are heavily correlative with types of events. Additionally, there is a significant positive influence of domestic events on reaction volatility, whereas the foreign events impose their influences on both the expectations of market reactions and volatility.

Researchers and practitioners have been interested in solving real-world problems through clustering. The clustering of nodes in networks with unipartite or bipartite structure is important to explore real-world complex networks present in nature and society. Bipartite networks form an important class of complex networks because they reveal the heterogeneity of nodes in a network. However, most extant clustering methods focus only on unipartite networks. In this work, a novel constrained agglomerative clustering method applicable to unipartite and bipartite networks has been proposed. Initially, the topology of a network is modeled according to set-theoretic principles. Subsequently, the concepts related to rough set theory and relative linkage are used to cluster the set of nodes. The utility and effectiveness of the proposed approach are demonstrated through offline experiments on unipartite and bipartite networks. A comparison against ten state-of-the-art similarity measures over two different partitional clustering algorithms reveals the effectiveness of the proposed relative linkage measure. Moreover, a comparative analysis with state-of-the-art network clustering methods reveals the viability of the proposed rough set-based constrained agglomerative clustering algorithm. Finally, the proposed method has been applied for the detection of cohesive subgroups of banks in a real bipartite network formed by mapping credit relationships between Indian firms and banks.

This work analyzed the dynamic interactive causal links among urban agglomeration, economic performance, carbon emissions, and health expenditures across developmental disparities in China. To this end, this work developed a health expenditures-augmented growth model to introduce health expenditures and carbon emissions as a shift factor of total factor productivity. A block of simultaneous equations is developed based on the health expenditures-augmented growth modeling framework. The System-variant/Difference-variant Generalized Method of Moments is employed to estimate the block of simultaneous equations in order to deal with the potential endogeneity of the variables used. Based on empirical results, the core findings are as follows: first, a Pendroni cointegration-based long-run stable association is verified. Second, the urban agglomeration exhibited a bidirectional positive causal linkage with the gross domestic product (GDP) growth and health expenditures growth. Third, the health expenditures growth demonstrated a bidirectional positive causal linkage with carbon emissions growth and GDP growth. Fourth, a unidirectional mixed causal linkage—positive (negative) for linear form (squared form) of urban agglomeration—existed from urban agglomeration to carbon emissions growth. Fifth, there is a negative causal linkage operating from carbon emissions growth to GDP growth. However, there is mixed causal linkage—positive for a linear form of GDP growth, and negative for the squared form of GDP—operating from GDP growth to carbon emissions growth. These findings exhibited consistency in the type of causal linkages across the developmental disparities and hence showed robustness. Nevertheless, the findings showed disparities in the degree of impact across the developmental disparities. In this regard, the strength of causal linkage is the largest (moderate/lowest) for highly (moderately/least) developed regions of China. Based on empirical results, inferences are extracted and discussed.

Sustainable consumption and production (SCP) is a key to envisioning the desirable linkage between consumers and producers for transforming the mass production paradigm. The authors have proposed a method for designing scenarios to describe visions and pathways for SCP. This paper proposes a method for quantifying scenarios using expert workshops to clarify effective SCP measures. That is, we develop a simplified model to help workshop participants execute iterative cycles of changing parameter values and evaluate the environmental effects of SCP measures. In a case study, a scenario for Vietnam was quantified to extract conditions for halving CO2 emissions in 2050.

The term prosthesis is usually used in analogy with Biomechanics. The motion of the body is provided by the bones, joints that form the basic linkage mechanism along with the activity of the muscle. The prime motive of biomechanics is to study about these linkages, their ranges of motion and their degree of freedom. In medicine, a body part which is missing, is been replaced by an artificial device or an extension, namely prosthesis. It is a part of Biomechanics, which deals with the usage of mechanical devices to assist human muscle, skeleton and nervous system in enhancing motor control lost due to trauma, defect or a disease. This paper aims to provide an improved system for lower limb prosthetic users through a better sleeve design. Braided designs with variations are created and analysed. The results suggest that the braided pattern shall be implemented in sleeve design with slight modifications.

The intention of this research is to design a new Novel Routing and Hybrid based Clustering Scheme (NRHCS) for VANETs. The vehicle link counts, and vehicle displacement is employed under various concepts like cluster formation, adding and deleting cluster, cluster head election and re-clustering are carried out. During cluster arrangement, the vehicles with comparatively improved extent of linkage preliminarily arrange as support which is chosen as the head. The management then takes part in cluster head selection and effective re-cluster with the aid of combined comparative displacement of vehicles using cluster head. The proposed technique processes the information dissemination in the VANET necessitate smart and vibrant decisions centered on the contexts to operate on dense and sparse instances to ensure that information transfer is possible for motor flexibility.

This paper summarizes the work done in the context of an industrial research project in collaboration between the Italian Institute of Technology and the company Fameccanica Data Spa. This paper introduces the design of a six bar linkage mechanism, actuated by a single motor, for re-orienting and aligning objects. The main application consists of grasping empty bottles lying flat on an input conveyor, rotating, aligning and placing them in upright position on another conveyor. The breakthrough aspect of the general and scalable design introduced lays in a system of kinematic equations whose solutions correspond to the linkage lengths. Such lengths define a six-bar-linkage able to re-orient and align vertically a generic object. Finally, this paper presents the mechanism prototype created for such industrial application for performing tests in an operational environment at high speed.

The usages of linkage mechanisms in diverse applications, including manufacturing, are extensively appreciated. The synthesis of mechanisms for given motion and path generation has becomemore significant. The data of the kinematics of machines, thus, is a very important aspect of modern-day manufacturing. From conventional perception, kinematics' knowledge prevents many realistic mechanisms like pin deformation, joint clearances, and manufacturing inexactitudes, which cannot be overlooked. This study aims to explain the different design optimization processes and the analysis of flexible four-bar linkages for achieving a better solution. This study could be an essential step for setting the appropriate resources and optimizing the four-bar mechanism design to reduce the deviation from the desired output. The high-speed rotation of the mechanism may cause vibration and deformation in the system. So, different methods may be applied for improved four-bar mechanisms. This study provides us withprobable to resolve such conditions as precise load values regarding other vibrating elements. Like MATLAB, ADAMS, and ANSYS, the soft-computing method has been formulated to strengthen the researcher's analysis ability. These software packages may provide the improved design data in the form of displacement, deformation, and vibration frequency of the four-bar Mechanisms.

China is the world's largest oil importer, and therefore the correlations between stock indices and highly volatile oil prices deserve close examination when investing in China's gradually liberalizing stock market. Another concern for international investors is whether safe-haven assets can reduce portfolio risks for investment in China. The paper makes two main contributions. First, we develop a novel method of examining a multivariate dependence structure by combining wavelet analysis with the vine copula model. Second, we apply the proposed methodology to study the correlations between China's liberalizing stock market, petroleum, and safe-haven assets at different frequencies. We find that the multidimensional dependence of these assets has been altered as a result of the 2008 global financial crisis. Moreover, the vine structures exhibit dependence patterns that vary over time horizons, indicating that the multidimensional dependence is sensitive to time scales.

Rigid origami is a branch of origami with great potential in engineering applications to deal with rigid-panel folding. One of the challenges is to compactly fold flat a polyhedron made from rigid facets with a single degree of freedom. In this paper, we present a new method to design origami cubes with three fundamental characteristics: rigid foldability, flat foldability and one degree of freedom (DOF). A total of four cases of crease patterns that enable origami cubes with distinct folding performances have been proposed, which covers all possible layouts of the diagonal creases on the square facets of origami cubes. The folding utilises spherical linkages formed by intersecting creases, and based on the kinematic equivalence between the rigid origami and the spherical linkages, the corresponding spherical linkage loops are introduced and analysed to reveal the motion properties of the origami cubes. The newly found method can be readily utilized to design deployable structures for various engineering applications including cube-shaped cartons, small satellites, containers, etc.

The paper empirically examines the impact of foreign direct investment spillovers on the performance of Vietnamese manufacturing firms from 2007 to 2015, and the role exerted by absorptive capacity on this relationship. Importantly, it is expected that the thresholds of absorptive capacity of the domestic firms exist, and the benefits which local firms enjoy can vary subject to the thresholds. This paper applies a threshold fixed effect model with panel data in Vietnam to show several findings. Firstly, the domestic firms can benefit from spillovers via the horizontal channel and backward linkage. Secondly, absorptive capacity is a vital factor in linking horizontal spillovers to local firms. Finally, the paper finds that there are thresholds of absorptive capacity in the case of Vietnam.

Design of a myoelectric prosthetic hand that satisfies the expectations of those who unfortunately lost a hand is discussed in this paper. That is to perform and look as close as a human hand, and to have a proprioceptive feedback in order to improve their quality of life. Linkage mechanisms are designed to replicate the trajectory of the human hand. Distinct seven grip patterns enable the prosthetic hand to manipulate different amputee needs. Kinematics and dynamics analysis are performed to estimate the required input motor torques, and to determine the hand force capabilities. The user controls the hand with the electromyography signal coming from the arm. The feedback system is then designed to reduce the relying of prosthetic users on visual or audible feedback. This system is divided into four separate categories: force sensing, feeling the temperature, motion sensing, and the final feedback allows the user to monitor and control the hand via an android application. Tests show that the suggested prosthetic hand is able to perform the required grip patterns correctly, and the hand can handle different objects in a wide range.

The evaluation of data obtained from responses given to questionnaires in humanities and social sciences, such as management, linguistics, etc. is a complex task with the necessity of dealing with the inherent subjectivity and vagueness in such data. In this paper, a method based on fuzzy signatures (FSigs), suitable for analyzing questionnaires with hierarchically connected (partially) vague responses is proposed, and its applicability will be demonstrated by a real life problem; the partial analysis of an ongoing research examining employee behavior in various companies. The linkage of the factors hidden in the data bases obtained from the answers to the questionnaires, containing various factors interconnected in a more or less tight way, are represented by a hierarchical FSig system, allowing further evaluation and the discovery of emerging connections and deeper patterns among the responses, thus extending the idea of the original FSig model towards a more general, fuzzy-fuzzy signature approach. The method proposed here is a combination of some statistical elements with the Fuzzy Signature model, and it also uses Kohonen-maps in order to discover deeper structural components in the data pool. As FSigs are suitable to express hierarchically structured connections among vague and imprecise features of the individual data, the statistical analysis helps reveal the degrees of redundancies and the closeness of connectedness of the individual elements within the responses, and thus enable the construction of a relevant FSig tree graph for the data on hand, while further expert domain knowledge helps with determining the proper fuzzy aggregations in the intermediate nodes of the FSigs. The case study presented is based on data obtained from North Lithuanian companies. The results of the case study focusing on the analysis of the connection between OCB and CWB, and other factors, disclose some interesting and, partly unexpected, results. They indicate a strong and unambiguous relationship between career satisfaction and OCB, which is not very surprising. However, it is found that there is no relationship with gender, age, and actual position in the company, which are generally supposed to be determining factors. These results may be further validated by expert knowledge, and thus the new combined method for evaluating structured multicomponent data and internal dependencies is adequate.

One objective of the efficiency measurement of multi-division systems is to find the least efficient divisions such that making improvements to them will increase the efficiency of the system most effectively. To accomplish this task, it is desirable to find the relationship between the system and division efficiencies. This issue has been addressed for the radial efficiency measures. This paper explores the relationship for a non-radial efficiency measure known as the slacks-based measure. The idea is to transform the network system into an equivalent one that is composed of a series of subsystems with parallel structures. Based on the property that the system efficiency is the product of the division efficiencies adjusted by the linkage efficiencies for series systems and is a linear combination of the division efficiencies for parallel systems, the system efficiency can be decomposed into a function of the division and linkage efficiencies. The decomposition of the slacks-based efficiency measure works not only for the technology of constant returns to scale, but also for the case of variable returns to scale. In addition, the proposed model produces suitable efficiency scores for weakly efficient units and for those using weakly efficient units as the target to calculate efficiencies, which makes it possible to obtain reliable rankings for the assessed units.

The maintenance of many subpopulations is an important technique employed in evolutionary methods. However, the use of a multi-population approach has its drawbacks. Among all, it requires spending high amounts of available resources. Therefore, the methods that dynamically manage the number of subpopulations gain an increasing interest due to their capability of adjusting the subpopulation number to their current state. They are shown to be capable of reaching excellent results. In this paper, we identify the Long-Way-To-Stuck effect and show it on the base of the practical, NP-complete problem. Such a phenomenon occurs when a randomly initialized population of an evolutionary method must be processed through many iterations before it is incapable of improving the best-found solution. If so, then a large amount of computational resources must be spent on subpopulation initialization, which may turn multi-population methods ineffective. Therefore, in this paper, we propose the Linkage Learning-Driven Subpopulation Initialization (LLDSI) that limits the costs of subpopulation initialization and significantly improves the effectiveness methods dynamically managing the subpopulation number.

The objective of this paper is to identify the sectors of the Indian economy that are able to generate different types of skilled employment (both directly and indirectly) through an estimation of their employment linkage effects with respect to varying levels of skills, using the Input–Output technique. The contribution of this paper lies in its redefining ‘skill’ by combining three types of education - general, vocational and technical – for arriving at four types of skilled employment categories—low, low-medium, medium-high and high skilled. The paper incorporates these four types of skilled employment into an Input–Output framework, using the World Input–Output Database for estimating the forward and backward employment linkages with respect to four different skill types for India for 2004–05 and 2011–12. The estimation of these employment linkage effects is critical for identifying the key employment-generating sectors of the Indian economy characterized by varying levels of skill. Moreover, a comparison of these linkage effects for two time-periods at varying levels of skill across sectors helps understand changing nature of employment structure over time, and how it varies across sectors.

This study aims to shed light on the co-movement of sovereign credit risk and economic risk in Turkey using the Toda–Yamamoto causality, Gradual Shift causality, and Wavelet Coherence tests. The study answers the following questions, which, to the best of our knowledge, have not been investigated in the literature: (i) Is there any causal linkage between sovereign credit risk and economic risk?; and (ii) If yes, why? Our findings reveal that (i) economic risk caused sovereign credit risk in 1997 and 2002; and (ii) between 2001 and 2012, sovereign credit risk caused economic risk at different scales. The Toda–Yamamoto causality and Gradual Shift causality tests confirm that, in Turkey, changes in sovereign credit risk significantly lead to changes in economic risk, indicating the importance of sovereign credit risk for predicting economic risk.

In this study, basic linear lumped elements such as springs and dashpots are used in nested linkage mechanisms in order to simulate the mechanical behavior of visco-hyperelastic materials. The proposed mechanism model containing two nested linkages can show initial softening followed by hardening response under quasi-static loading, which is commonly displayed by hyperelastic materials. Hence, material nonlinearity is simulated by geometric nonlinearity of the linkage mechanism. The mechanism also displays relaxation, hysteresis, and dynamic stiffness responses of viscoelastic materials with the help of dashpot elements. Visco-hyperelastic material behavior is closely approximated by the proposed mechanism model for the four different test scenarios, i.e., quasi-static loading, ramp-and-hold loading, hysteresis, and dynamic stiffness tests. It is shown that nonlinearity and frequency dependency of visco-hyperelastic materials is successfully captured.

We investigate the application of the Ordered Weighted Averaging (OWA) data fusion operator in agglomerative hierarchical clustering. The examined setting generalises the well-known single, complete and average linkage schemes. It allows to embody expert knowledge in the cluster merge process and to provide a much wider range of possible linkages. We analyse various families of weighting functions on numerous benchmark data sets in order to assess their influence on the resulting cluster structure. Moreover, we inspect the correction for the inequality of cluster size distribution – similar to the one in the Genie algorithm. Our results demonstrate that by robustifying the procedure with the Genie correction, we can obtain a significant performance boost in terms of clustering quality. This is particularly beneficial in the case of the linkages based on the closest distances between clusters, including the single linkage and its “smoothed” counterparts. To explain this behaviour, we propose a new linkage process called three-stage OWA which yields further improvements. This way we confirm the intuition that hierarchical cluster analysis should rather take into account a few nearest neighbours of each point, instead of trying to adapt to their non-local neighbourhood.

We analyze the relationship between forecaster disagreement and macroeconomic uncertainty in the Euro area using data from the European Central Bank’s Survey of Professional Forecasters for the period 1999Q1–2018Q4 and find that disagreement is generally a poor proxy for uncertainty. However, the strength of this link varies with the dispersion statistic employed, the choice of either the point forecasts or the histogram means for calculating disagreement, the outcome variable considered and the forecast horizon. In contrast, distributional assumptions do not appear to be very influential. The relationship is weaker in subsamples before and after the outbreak of the Great Recession. Accounting for the forecasters’ entry to and exit from the survey has little impact on the results. We also show that survey-based uncertainty is associated with overall policy uncertainty, whereas forecaster disagreement is related more closely to the expected fluctuations on financial markets.

This empirical study is a new addition to the existing body of knowledge, which estimates the influence of industrialisation and urbanisation on carbon dioxide emissions in the APEC countries with a new panel estimation technique, the Dynamic Unrelated Seemingly Regression (DSUR). The data covering the years 1990 to 2014 have been used for analysis. Empirical findings of the current study reveal that industrialisation degrades the environment through releasing carbon dioxide to the air. Beside this, it is also observed that the energy intensity, urbanisation, and economic growth enhance the level of environmental pollution via CO2 emissions. Moreover, unidirectional causality is found between industrialisation and CO2 emission. For dynamic analysis, a time series analysis is also performed. Finally, policy recommendations regarding R & D are suggested for the industrial and energy sectors.

The harvesting of fresh kiwifruit is a labor-intensive operation that accounts for more than 25% of annual production costs. Mechanized harvesting technologies are thus being developed to reduce labor requirements for harvesting kiwifruit. To improve the efficiency of a harvesting robot for picking kiwifruit, we designed an end-effector, which we report herein along with the results of tests to verify its operation. By using the established method of automated picking discussed in the literature and which is based on the characteristics of kiwifruit, we propose an automated method to pick kiwifruit that consists of separating the fruit from its stem on the tree. This method is experimentally verified by using it to pick clustered kiwifruit in a scaffolding canopy cultivation. In the experiment, the end-effector approaches a fruit from below and then envelops and grabs it with two bionic fingers. The fingers are then bent to separate the fruit from its stem. The grabbing, picking, and unloading processes are integrated, with automated picking and unloading performed using a connecting rod linkage following a trajectory model. The trajectory was analyzed and validated by using a simulation implemented in the software Automatic Dynamic Analysis of Mechanical Systems (ADAMS). In addition, a prototype of an end-effector was constructed, and its bionic fingers were equipped with fiber sensors to detect the best position for grabbing the kiwifruit and pressure sensors to ensure that the damage threshold was respected while picking. Tolerances for size and shape were incorporated by following a trajectory groove from grabbing and picking to unloading. The end-effector separates clustered kiwifruit and automatically grabs individual fruits. It takes on average 4–5 s to pick a single fruit, with a successful picking rate of 94.2% in an orchard test featuring 240 samples. This study shows the grabbing–picking–unloading robotic end-effector has significant potential to facilitate the harvesting of kiwifruit. Keywords: Kiwifruit, End-effector, Harvesting robot, Trajectory model, Simulation analysis

This paper investigates the time-varying relationship between German output and employment growth, in particular their decoupling in recent years. We estimate a correlated unobserved components model that allows for persistent and cyclical time variation in the employment-GDP linkage as well as an additional employment component beyond the one linked to GDP. Controlling for the latter yields a more precise classification of what is a jobless recovery or a labour hoarding recession. We find that the comovement of employment and GDP has loosened permanently since the Great Recession while the comovement with other variables than GDP has become tighter. The decoupling goes hand in hand with the change of the sectoral composition of the economy, especially the rise of the service sector. Beyond that, high labour market tightness and at the same time high labour supply carried recent employment growth. The industry mix, wages and working time had a smaller influence.

We illustrate an on-going work on the crossroad of mechanical linkages, dynamic geometry and automated reasoning. In particular, we exemplify how some automated reasoning tools (ART) based on symbolic computation and recently implemented in GeoGebra, can be used for linkage exploration. For instance, when considering linkages for generating specific algebraic curves, such as Peaucellier's construction of a straight line, we will show how these ART can help towards the verification (automatic proving) of the correctness of the linkage construction, as well as for finding (automatic discovery) a suitable modification on a given linkage for achieving a desired movement.

This paper contributes to the literature on backward linkages—the degree of localization in input usage, focusing on the potential interdependence between foreign and domestic producer firms. Drawing on Irish sectoral data during 2000–2013, our main objective is to empirically examine how foreign and domestic producer firms' backward linkages might dynamically influence each other, and the extent to which they respond to export intensity and productivity levels from the two groups of firms. We find an interesting asymmetric interdependence pattern: (1) domestic firms' backward linkages are not impacted by the backward linkages of foreign firms; (2) more robust backward linkages of domestic firms can potentially induce more backward linkages from foreign firms; and (3) domestic firms' productivity shocks could generate a dynamic crossover impact on foreign firms' backward linkage status, but similar shocks originating from foreign firms generate little crossover impact on domestic firms’ backward linkage status. Our result on interdependent local linkages points to a potentially important role for domestic-to-domestic backward linkage formation in promoting foreign-to-domestic backward linkages.

Motivated by the high importance of the tolerance specification, numerous partially automated approaches have emerged. However, since these approaches require an extensive geometry definition, they are not applicable for an early definition of the tolerance concept and its evaluation by Robust Design aspects. Motivated by this lack, this paper presents a novel ontology-based approach combining knowledge from the product design and tolerancing domains to enable an automated tolerance specification of product concepts. This close linkage enables a more precise specification and bridges the gap to the subsequent final specification in accordance with current GPS standards. Finally, this novel approach is demonstrated by means of a crank drive mechanism.

Crop damage during the intra-row weed eradiation is one of the biggest challenges in intercultural agricultural operations. Several available mechanical systems provide effective weeding but result in excess crop damage. On the other hand, chemical based systems have been raising serious environmental and food concerns. This study presents development of a cost-effective mechatronic prototype for intra-row weeding operation. The primary focus was on incurring minimal crop damage. The system integrates time of flight and inductive sensing into fuzzy logic algorithm for electronic control of a four-bar linkage mechanism (FBLM). The crank of FBLM was connected to the vertical rotary weed control shaft with weeding blades. The crop sensing triggers the electronic control to laterally shift the control shaft away from crop, proportional to the forward speed and soil conditions. The developed algorithm incorporates varied conditions of soil, forward speed, and plant spacing to calculate dynamic lateral shift speed (SRPM). The prototype was evaluated to determine the relationships between the operating conditions and electronic control parameters. Moreover, the plant damage was assessed under varied conditions of plant spacing, forward speeds, soil cone index, operational depth and electronic control parameters. The derived SRPM was established as the ultimate governing factor for avoiding crop damage that varied significantly with electronic response time and soil strength (P 65%) and crop damage (

New technical systems are created on the basis of existing systems by different extent of taken over and newly developed and/or adapted subsystems and their linkage. Various approaches aim to characterize these different forms of technical adaptation and to make them formally measurable. The calculation of variation shares according to the model of the PGE is based on the determination of variation types with the help of the C&C²-A modelling of subsystems and the associated reference system element as well as the subsystem structure. Both can generally be selected variably. This contribution investigates the influence of these two parameters on the retrospective analysis of variation shares, using a test bench probe and an actuator in a tooling machine as examples. Variation shares are calculated for different levels of detail of the underlying C&C²-A modelling and subsystem structures with different numbers of subsystems. Observed effects regarding the identification of the variation type of a subsystem as well as regarding the calculation of variation shares for the whole system are discussed. A major conclusion of the investigation is that retrospective analyses of variation shares depend strongly on the two investigated parameters and are mostly not unambiguous.

Traditionally water, energy and food (WEF) resources are governed in many countries by separate sets of laws, rules and institutions. However, recent studies have increasingly underlined the WEF nexus approach as a framework for coherent, holistic and integrated implementation of the Sustainable Development Goals (SDGs) to address fragmentations and ensure cleaner and efficient production methods in each sector. This article examines the legal and governance aspects of integrating and implementing the WEF nexus in practice. Various legal and institutional challenges that arise with a nexus approach, such as incompatibility of WEF nexus aims, limited rule linkages, institutional limitations and resource constraints are examined in order to identify the ways in which an integrative legal framework on WEF can help close these gaps. The study suggests that enhanced levels of legislation and rule linkage; elaboration of common and shared principles by institutional actors in WEF domains; as well knowledge, expertise and information sharing on WEF-related decision making are significant steps towards advancing systemic and integrated governance of WEF resources.

From past few years, there has been a rising trend of using composite materials for suspension system of vehicles as it reduces overall weight to a great extent. Also, they are unaffected by chemicals and corrosion. Watt’s linkage is an assembly of a bell crank and two horizontal rods of equal length. It is a mechanical linkage in which the bell crank is pivoted to axle at its centre traces vertical line, allowing axle to move vertically. The assembly is connected to the chassis of the vehicle with help of the horizontal rods, which constraints the lateral movement of body of vehicle and locates the axle under the vehicle. Low alloy steels are commonly used material for manufacturing the linkages in suspension system. In this paper, the Watt’s linkage components are designed and assembled in PTC Creo 3.0 and the finite element analysis of Watt’s linkage for two materials, namely, AISI 4142 steel and Carbon Fibre Reinforced Polymer (CFRP) is carried out. The results for total deformation and equivalent stress are produced using ANSYS Workbench 2019 R2 for dynamic loading. The maximum total deformation for 4142 steel is 0.31891 mm and for CFRP is 2.6298 mm.

Important advances have been made to define the multiple impact pathways relating mineral resource use to the area of protection (AoP) natural resources in life cycle assessment (LCA). Yet, the link between stakeholders’ interests and the aspects relevant to resource use as addressed by existing impact assessment methods has so far only marginally been explored. This article proposes to go beyond the case-specific determination of stake­ holders’ interests (and the associated selection of impact assessment method) by defining multiple groups of different values based on cultural perspectives, in order to determine the corresponding relevant impact path­ ways and assessment methods. Relying on the Cultural Theory and related potential development scenarios, we identify socio-economicobjectives and resource management strategies that fit the egalitarian, individualist and hierarchist perspec­ tives. Our analysis reveals that different aspects of resource use may be most relevant to assess for each perspective since they pursue different socio-economic objectives. Egalitarians are expected to prioritize the long-term availability of geological stocks for future generations by keeping extraction flows to a minimum to reach global sufficiency, and individualists, to safeguard their short-term accessibility to resources by managing their supply risk. Hierarchists are likely to aim to maximize the value obtained from resources globally, and could thus focus on addressing dissipative flows. Building on this analysis, we provide a proposal for a more holistic assessment of the impact pathways linked to mineral resource use using existing LCIA methods, and identify ways forward for method developments to come. French agency for ecological transition (ADEME) French geological survey (BRGM)

The linkage between travel and the built environment has received extensive research attention over the past decades. However, the existing studies normally evaluate the built environment effect on travel from an individual-based perspective, neglecting the influence of intra-household interactions. We argue that individuals’ travel behavior is derived from the allocation of household tasks and resources (e.g., household vehicles) and the travel behaviors of household members are interdependent. This suggests that the built environment may impact one member’s travel behavior indirectly through its influence on others members’ travel choices. Thus, examining the travel impact of the built environment needs to consider intra-household interactions. This paper proposes to analyze the land use-travel relationship from a household perspective. We simultaneously examine the effects of the built environments of residential and work locations on married couples’ travel behaviors, considering the interrelations between their travels and controlling for both partners’ travel attitudes. The empirical study in Beijing, China indicates that the built environment effect on travel is different between partners. Two work environment factors influence the partners’ driving behaviors in opposite directions. Moreover, the wife’s travel behavior mediates the association between the built environment and the husband’s travel behavior. These findings highlight the importance of understanding the land use impact on travel behavior from the household perspective.

The linkage between economic growth and carbon dioxide (CO2) emissions has been quantified from both a theoretical perspective and an empirical perspective. However, these studies did not address the role of governance in environmental quality explicitly. Therefore, the current study examines the behavior of governance in CO2 emissions within the framework of the Environmental Kuznets Curve hypothesis for panel data from 1996 to 2017 for BRICS countries. The study employs Westerlund panel cointegration for investigation of cointegration among study’s variables. The long-run panel data estimation methods those eliminate dependencies across countries, heteroscedasticity, and spatial and serial dependency issues are used. To summarize the finding, governance has negative and statistically significant effects on CO2 emissions, help to form the Environmental Kuznets Curve hypothesis and reduces CO2 emissions in the BRICS countries. The newly developed results recommend the importance of governance in the clean environment and suggestions are directed accordingly