Theoretical and experimental investigations on rotary ultrasonic surface micro-machining of brittle materials.

Many brittle materials, such as single-crystal materials, amorphous materials, and ceramics, are widely used in many industries such as the energy industry, aerospace industry, and biomedical industry. In recent years, there is an increasing demand for high-precision micro-machining of these brittle materials to produce precision functional parts. Traditional ultra-precision micro-machining can lead to workpiece cracking, low machined surface quality, and reduced tool life. To reduce and further solve these problems, a new micro-machining process is needed. As one of the nontraditional machining processes, rotary ultrasonic machining is an effective method to reduce the issues generated by traditional machining processes of brittle materials. Therefore, rotary ultrasonic micro-machining (RUµM) is investigated to conduct the surface micro-machining of brittle materials. Due to the small diameter cutting tool (<500 µm) and high accuracy requirements, the impact of input parameters in the rotary ultrasonic surface micro-machining (RUSµM) process on tool deformation and cutting quality is extremely different from that in rotary ultrasonic surface machining (RUSM) with relatively large diameter cutting tool (∼10 mm). Up till now, there is still no investigation on the effects of ultrasonic vibration (UV) and input variables (such as tool rotation speed and depth of cut) on cutting force and machined surface quality in RUSµM of brittle materials. To fill this knowledge gap, rotary ultrasonic surface micro-machining of the silicon wafer (one of the most versatile brittle materials) was conducted in this study. The effects of ultrasonic vibration, tool rotation speed, and depth of cut on tool trajectory, material removal rate (MRR), cutting force, cutting surface quality, and residual stress were investigated. Results show that the ultrasonic vibration could reduce the cutting force, improve the cutting surface quality, and suppress the residual compressive stress, especially under conditions with high tool rotation speed.

Effect of lean manufacturing tools on sustainability: the case of Mexican maquiladoras.

The Mexican maquiladora industry is applying Lean Manufacturing Tools (LMT) in its production lines; however, few studies have investigated its relationship with sustainability (social, economic, and environmental). This paper presents a second-order structural equation model (SEM) relating 8 LMT integrated into three independent latent variables: continuous improvement (Kaizen and Gemba), supporting tools (Andon, visual management, and Poka-yoke), and machinery and equipment (total productive maintenance, overall equipment effectiveness, and Jidoka) that are related to social, economic, and environmental sustainability as dependent variables. The model is validated with information obtained from 249 companies using partial least squares. Findings show that the application of LMT in the Mexican maquiladora industry avoids the generation of waste and reprocessing. Likewise, the improvement of production processes reduces the waste emitted into the environment and reduces energy consumption. Also, when companies have environmental programs, the work environment is safe, and labor relations are improved, increasing morale and the commitment to work for the company, gaining economic and ecological benefits.

Corporate social responsibility and cross-border M&A: The moderating effect of institutional distance.

Drawing upon a dataset of cross-border mergers and acquisitions (M&A) events of Chinese enterprises from 2010 to 2017, this study investigates the impact of corporate social responsibility (CSR) on the completion of cross-border M&A with a focus on the moderating role of institutional distance. The results highlight the significance of CSR on the completion of cross-border M&A. The robustness tests including changing estimation model, new measurements, propensity score matching, and instrumental variable tests show that the main results are consistent. Second, both formal and informal institutional distance have positive moderating effects of CSR on the completion of cross-border M&A.

Xylanolytic Enzymes in Pulp and Paper Industry: New Technologies and Perspectives.

The pulp and paper industry discharges massive amount of wastewater containing hazardous organochlorine compounds released during different processing stages. Therefore, some cost-effective and nonpolluting practices such as enzymatic treatments are required for the potential mitigation of effluents released in the environment. Various xylanolytic enzymes such as xylanases, laccases, cellulases and hemicellulases are used to hydrolyse raw materials in the paper manufacturing industry. These enzymes are used either individually or in combination, which has the efficient potential to be considered for bio-deinking and bio-bleaching components. They are highly dynamic, renewable, and high in specificity for enhancing paper quality. The xylanase act on the xylan and cellulases act on the cellulose fibers, and thus increase the bleaching efficacy of paper. Similarly, hemicellulase enzyme like endo-xylanases, arabinofuranosidase and ß-D-xylosidases have been described as functional properties towards the biodegradation of biomass. In contrast, laccase enzymes act as multi-copper oxidoreductases, bleaching the paper by the oxidation and reduction process. Laccases possess low redox potential compared to other enzymes, which need some redox mediators to catalyze. The enzymatic process can be affected by various factors such as pH, temperature, metal ions, incubation periods, etc. These factors can either increase or decrease the efficiency of the enzymes. This review draws attention to the xylanolytic enzyme-based advanced technologies for pulp bleaching in the paper industry.

Analysis on the structure effect of marine fishery total factor productivity under high-quality development in China.

Improving total factor productivity (TFP) is the source of power for high-quality development. Industrial structure optimization is an important way to improve TFP. This paper constructed an econometric model of industry structure changes impacting on TFP in the marine fisheries and conducted an empirical test and analysis. The results showed that the industry rationalization, softening and processing coefficient of marine fishery had a significant "structural dividend" for improving its TFP; while the impact of industrial structure advancement and aquaculture-catching structure changes did not have "structural dividend", but it could be a combination of other factors to reduce these adverse effects.We believe that simply pursuing the advanced evolution of the industrial structure is not conducive to sustainable development of fishery. Under the pursuit of the rationalization of the marine fishery industry structure, by promoting the coordinated evolution of marine fisheries advancement, aquaculture-catching structure and other factors, the "structural dividend" effect can be enhanced and the fishery can achieve sustainable development. Finally, it proposed to promote the development of advancement and rationalization of marine fishery industry structure coordinately, adjust fishery science and technology transformation direction and key points, and accelerate the development of intensive processing industry by cross-border integration.

Spatial distribution evolution and accessibility of A-level scenic spots in Guangdong Province from the perspective of quantitative geography.

As a typical representative of tourism resources, the spatial distribution of A-level scenic spots has a profound impact on the layout of tourism industry. Scenic spot accessibility is also important for the development of tourism. However, the relationship of regional accessibility and spatial distribution of A-level scenic spots are understudied. The study used quantitative geography and geographic information system spatial analysis methods and analyzed the evolution of spatial distribution and regional accessibility of A-level scenic spots in Guangdong Province from 2001 to 2020. The results present the following: 1. Agglomeration distribution is the main distribution type of A-level scenic spots in Guangdong Province, and the spatial distribution is unbalanced. 2. From 2001 to 2020, the spatial distribution of A-level scenic spots in 21 prefecture-level cities of Guangdong Province has gradually developed from "wide gap" to "relatively reasonable." 3. Distribution density of A-level scenic spots in Guangdong Province has evolved into the main core area of high density. 4. Center of the gravity of A-level scenic spots in Guangdong Province developed from east to west during 2002-2007 and moved to the east after 2007. 5. Accessibility between A-level scenic spots and tourist source areas in Guangdong Province is good, with an evident aggregation phenomenon. This study reveals the spatial distribution evolution law and regional accessibility of A-level scenic spots, which is conducive to healthy, sustainable, and stable development of tourism in Guangdong Province.

Assessment of the pollution incident performance of water and sewerage companies in England.

Comparison of the severity, frequency and self-reporting of pollution incidents by water and sewerage companies is made difficult by differences in environmental and operational conditions. In England, the deterioration in pollution incident performance makes it important to investigate common trends that could be addressed to improve pollution management. This study presents the first external analysis of available national pollution incident data, obtained through Environmental Information Regulations 2004 requests to the English Environment Agency. The study aimed to assess and compare the pollution incident performance of water and sewerage companies in England. Results indicated that there were significant variations in numbers of pollution incidents reported and the severity of the impact on the water environment for different asset types (operational property). There were significant positive relationships between the self-reporting percentages and total numbers of reported pollution incidents per 10,000 km sewer length for pumping stations and sewage treatment works. These results indicate that in at least these asset types, an estimated 5% of pollution incidents could go unreported. Pollution events that go unreported can lead to more severe impacts to the water environment, so rapid and consistent reporting of incidents is crucial for limiting damage. The results have significance for the water industry internationally, because the issues presented here are not restricted to England. In the short-term, research should focus on investigating best practice and standardising reporting of pollution incidents, so that an accurate baseline of the number of pollution incidents occurring can be determined.

Skill-driven recommendations for job transition pathways.

Job security can never be taken for granted, especially in times of rapid, widespread and unexpected social and economic change. These changes can force workers to transition to new jobs. This may be because new technologies emerge or production is moved abroad. Perhaps it is a global crisis, such as COVID-19, which shutters industries and displaces labor en masse. Regardless of the impetus, people are faced with the challenge of moving between jobs to find new work. Successful transitions typically occur when workers leverage their existing skills in the new occupation. Here, we propose a novel method to measure the similarity between occupations using their underlying skills. We then build a recommender system for identifying optimal transition pathways between occupations using job advertisements (ads) data and a longitudinal household survey. Our results show that not only can we accurately predict occupational transitions (Accuracy = 76%), but we account for the asymmetric difficulties of moving between jobs (it is easier to move in one direction than the other). We also build an early warning indicator for new technology adoption (showcasing Artificial Intelligence), a major driver of rising job transitions. By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19). They can be leveraged by policy-makers, educators, and job seekers who are forced to confront the often distressing challenges of finding new jobs.

Elephant bones for the Middle Pleistocene toolmaker.

The use of bone as raw material for implements is documented since the Early Pleistocene. Throughout the Early and Middle Pleistocene bone tool shaping was done by percussion flaking, the same technique used for knapping stone artifacts, although bone shaping was rare compared to stone tool flaking. Until recently the generally accepted idea was that early bone technology was essentially immediate and expedient, based on single-stage operations, using available bone fragments of large to medium size animals. Only Upper Paleolithic bone tools would involve several stages of manufacture with clear evidence of primary flaking or breaking of bone to produce the kind of fragments required for different kinds of tools. Our technological and taphonomic analysis of the bone assemblage of Castel di Guido, a Middle Pleistocene site in Italy, now dated by 40Ar/39Ar to about 400 ka, shows that this general idea is inexact. In spite of the fact that the number of bone bifaces at the site had been largely overestimated in previous publications, the number of verified, human-made bone tools is 98. This is the highest number of flaked bone tools made by pre-modern hominids published so far. Moreover the Castel di Guido bone assemblage is characterized by systematic production of standardized blanks (elephant diaphysis fragments) and clear diversity of tool types. Bone smoothers and intermediate pieces prove that some features of Aurignacian technology have roots that go beyond the late Mousterian, back to the Middle Pleistocene. Clearly the Castel di Guido hominids had done the first step in the process of increasing complexity of bone technology. We discuss the reasons why this innovation was not developed. The analysis of the lithic industry is done for comparison with the bone industry.

Recommending blue ocean technologies for subcontractors: A framework based on business reports of prime contractors and patents.

Subcontractors depend heavily on their prime contractor and thus find it very risky to enter a new business on their own. This study proposes a framework for these subcontractors to develop blue ocean technologies related to their prime contractor. First, the primary technologies predicted to be promising are extracted from the business reports of the prime contractor. Sub-technologies are then selected through a patent-based search using keywords and International Patent Classification codes of the primary technologies. From them, blue ocean technologies are proposed by optimizing the weighted mean of the min-max normalized market value, degree of competition in the technology market, and subcontractors' potential technological capabilities for each sub-technology. This study shows that subcontractors can enhance their technology competitiveness by finding a low-risk blue ocean technology. Our empirical research on the subcontractors of a semiconductor firm identified technological patent fields for them to pursue. From our framework, subcontractors can identify blue ocean technologies by considering their prime contractor's future industrial areas and technologies of interest as well as their own technological capabilities. Furthermore, the prime contractors can gain the synergy effect of technology expansion through cooperation.

Efficient energy and completion time for dependent task computation offloading algorithm in industry 4.0.

Rapid technological development has revolutionized the industrial sector. Internet of Things (IoT) started to appear in many fields, such as health care and smart cities. A few years later, IoT was supported by industry, leading to what is called Industry 4.0. In this paper, a cloud-assisted fog-networking architecture is implemented in an IoT environment with a three-layer network. An efficient energy and completion time for dependent task computation offloading (ET-DTCO) algorithm is proposed, and it considers two quality-of-service (QoS) parameters: efficient energy and completion time offloading for dependent tasks in Industry 4.0. The proposed solution employs the Firefly algorithm to optimize the process of the selection-offloading computing mode and determine the optimal solution for performing tasks locally or offloaded to a fog or cloud considering the task dependency. Moreover, the proposed algorithm is compared with existing techniques. Simulation results proved that the proposed ET-DTCO algorithm outperforms other offloading algorithms in minimizing energy consumption and completion time while enhancing the overall efficiency of the system.

RD internationalization, domestic technology alliance, and innovation in emerging market.

Although R&D internationalization plays an important role in enterprises' globalization, few studies explore the mechanism of R&D internationalization and emerging market companies' innovation, or the relationship between R&D internationalization, domestic technology alliances and absorptive capacity. How does the R&D internationalization of emerging market enterprises affect the innovation of those enterprises? Under fierce market competition, do absorption capacity and domestic technology alliances have a significant impact on enterprise innovation? From the perspective of the knowledge-based view, this paper studies 185 enterprises undergoing R&D internationalization in China from 2012 to 2017, using high-dimensional Poisson fixed effects model, we use instrumental (HDFE IV) estimation to explain the impact of R&D internationalization on the innovation of the parent company and the mechanism behind it. The study finds that R&D internationalization positively promotes the parent company's innovation, and domestic technology alliances and absorptive capacity play a partial mediator role in R&D internationalization. In the face of fierce market competition, domestic technical alliances play a significant role in promoting enterprise innovation, while absorptive capacity plays a negative role in promoting enterprise innovation with the moderating effect of market competition.

Analysis of carbon emission performance and regional differences in China's eight economic regions: Based on the super-efficiency SBM model and the Theil index.

China's carbon emission performance has significant regional heterogeneity. Identified the sources of carbon emission performance differences and the influence of various driving factors in China's eight economic regions accurately is the premise for realizing China's carbon emission reduction goals. Based on the provincial panel data from 2005 to 2017, the super-efficiency SBM model and Malmquist model are constructed in this paper to measure regional carbon emission performance's static and dynamic changes. After that, the Theil index is used to distinguish the impact of inter-regional and intra-regional differences on different regions' carbon emissions performance. Finally, by introducing the Tobit model, the effect of various driving factors on carbon emission performance differences is analyzed quantitatively. The results show that: (1) There are significant differences in different regions' carbon emission performance, but the overall carbon emission performance presents an upward fluctuation trend. Malmquist index decomposition results show substantial differences in technology progress index and technology efficiency index in different regions, leading to significant carbon emission performance differences. (2) Overall, inter-regional differences contribute the most to the overall carbon emission performance, up to more than 80%. Among them, the inter-regional and intra-regional differences in ERMRYR contributed significantly. (3) Through Tobit regression analysis, it is found that residents' living standards, urbanization level, ecological development degree, and industrial structure positively affect carbon emission performance. On the contrary, energy intensity presents an apparent negative correlation on carbon emission performance. Therefore, to improve the carbon emission performance, we should put forward targeted suggestions according to the characteristics of different regional development stages, regional carbon emission differences, and influencing driving factors.

Application of a simulation model to the prognosis of material loss in wood processing.

The article discusses the influence of a sample size on the credibility of a simulation model created for the estimation of material loss in the production of a middle layer of a wooden floorboard. The study was conducted in a production company operating in the wood processing industry. Geometric characteristics of input material were captured and used to derive statistical distributions, which were then included in the simulation model. The conducted experiments indicated that the quality of the simulation model was significantly affected by the quality and quantity of the sample, on the basis of which the stochastic model is estimated. It was shown that small sample for wood processing data was insufficient to capture process variability. On the other hand, excessive sample size (80 or more observations) for the material with high natural geometric variability, involves taking into account outliers, which may lower the overall prognostic quality of the simulation model. Based on the conducted simulation experiments, the recommended sample size which allows development of a reliable model for estimation of material loss in the analyzed manufacturing process, ranges from 40 to 60 measurements.

Multi-energy conversion based on game theory in the industrial interconnection.

The multi-energy conversion system (MCS) plays an important role in improving the utilization of energy resources and realizing the energy transition. With the application of the new generation of information technologies, the new MCS can realize real-time information interaction, multi-energy collaboration, and real-time demand response, in which energy suppliers can intelligently motivate consumers' energy use behavior. In this paper, an MCS coupled with a cloud platform is proposed to address information explosion and data security issues. Due to the development of Internet technology, the increasing energy data, and the serious energy coupling, it is difficult for traditional optimization methods to deal with the interaction between participants of the MCS. Therefore, the non-cooperative game is used to formulate the interactions between participants with the aim of maximizing the energy suppliers' profit and minimizing the customers' cost. It is proved that the game model is an ordinary game with one Nash equilibrium. The simulation was performed with a gradient projection algorithm and the results show that the proposed MCS improves energy utilization efficiency through energy conversion while ensuring consumer satisfaction, and benefits both the customers and suppliers by reducing the energy consumption cost and the peak load demand, which effectively improve the supply quality and enrich the energy consumption patterns.

Does Environmental Regulation Affect Export Quality? Theory and Evidence from China.

Most studies focus on the empirical investigation of the relationship between environment and trade, but they lack a systematic theoretical framework. To fill this gap, this study constructs an analytical framework of export competitiveness from the perspective of product quality, and reveals the theoretical mechanism of environmental regulation affecting export quality. We empirically examine the impact of environmental regulation on the export quality of China's manufacturing industry, as well as its possible mechanism. Our findings show that environmental regulation can significantly promote the export quality upgrading of the manufacturing industry and that process and product productivity are two possible channels through which such regulation affects export quality, although their mediating effects are in opposite directions. The mediating effect of product productivity is greater than that of process productivity, indicating that environmental regulation mainly has an innovation offset effect on China's manufacturing industry. For pollution-intensive industries, environmental regulation plays a significant promoting role through the channel of product productivity, but, for clean industries, environmental regulation has an inhibitory effect through the channel of process productivity. These findings provide important enlightenment for the coordinated development of China's ecological civilization and trade power.

Industrial Applications of Ionic Liquids.

Since their conception, ionic liquids (ILs) have been investigated for an extensive range of applications including in solvent chemistry, catalysis, and electrochemistry. This is due to their designation as designer solvents, whereby the physiochemical properties of an IL can be tuned for specific applications. This has led to significant research activity both by academia and industry from the 1990s, accelerating research in many fields and leading to the filing of numerous patents. However, while ILs have received great interest in the patent literature, only a limited number of processes are known to have been commercialised. This review aims to provide a perspective on the successful commercialisation of IL-based processes, to date, and the advantages and disadvantages associated with the use of ILs in industry.

Theoretical study of industrial scale closed-loop recycling counter-current chromatography separations.

Industrial separation technologies can be improved and greatly simplified by using the methods of counter-current chromatography (CCC). We have previously proposed the use of currently available solvent extraction equipment (a series of multistage columns, a cascade of centrifugal mixer-settler extractors) as large-scale CCC devices. For industrial separations, the application of closed-loop recycling counter-current chromatography (CLR CCC) methods seems to be the most promising. To improve the performance of the CLR CCC separations, semi-continuous three-stage processes (1 - continuous loading of the mixture solution over a definite time; 2 - separation of solutes in recycling closed-loop; 3 - elution of the fractions of the separated solutes with the mobile phase) can be used. The purpose of this study is to present a simple and easy to use mathematical model allowing the simulation and design of various options for implementing such separation processes and analyze the influence of its main parameters on separation efficiency.

Strategies in genotoxicology: Acceptance of innovative scientific methods in a regulatory context and from an industrial perspective.

The tests used and the general principles behind test strategies are now often over 30 years old. It may be time by now, given that our knowledge of genetic toxicology has improved and that we also technically are better able to investigate DNA damage making use of modern molecular biological techniques, to start thinking on a new test strategy. In the present paper, it is discussed that the time is there to consider a new approach for genotoxicity assessment of substances. A fit for all test strategy was discussed making use of the most recent technological methods and techniques. It was also indicated that in silico tools should be more accepted by regulatory institutes/bodies as supporting information to better conclude which tests should be required for each separate substance to demonstrate its genotoxic potency. Next to that there should be a good rationale for performing in vivo studies. Finally, the need for germ cell genotoxicity testing, essential when classification and labeling of substances is mandatory, was discussed. It was suggested to change the GHS for genotoxicity classification and labelling from in vivo tests in germ cells into in vivo tests in somatic cells. Quantitative genotoxicology was also discussed. It appeared that we are currently at a transition, where the science developing to justify carrying out human health risk assessments based on genetic toxicology data sets supported by mechanistic data and exposure data. However, implementation will take time, and acceptance will be supported through the development of numerous case studies. Major remaining questions are: is genetic damage a relevant endpoint in itself, or should the risk assessment be carried out on the apical endpoint of cancer and which genotoxic endpoint should be used to derive the point of departure (PoD) for the human exposure limit?