In a dynamic and rapidly changing world, customers’ often conflicting demands plus fluid economic requirements, often driven by geo-politics, have continued to evolve, out-striping the capability of existing production systems. With its inherent shortcomings, the traditional factory has proven to be incapable of addressing these modern-day manufacturing challenges. Recent advancements in Industry 4.0 have catalyzed the development of new manufacturing paradigms (or smart factory visions) under different monikers (e.g., Smart factory, Intelligent factory, Digital factory, Cloud-based factory etc.) would help fix these challenges. Due to a lack of consensus on a general nomenclature for these manufacturing paradigms, the term Future Factory (or Factory of the Future) is here used as a collective euphemism, without prejudice. The Future Factory constitutes a creative convergence of multiple technologies, techniques and capabilities that represent a significant change in current production capabilities, models, and practices. It is a data-driven manufacturing approach and system that harnesses intelligence from multiple information streams i.e., assets (including people), processes, and subsystems to help create new forms of production efficiency and flexibility. Serving both as a review monograph and reference companion, this paper details the meanings, characteristics, and technological underpinnings of the Future Factory. It also elucidates on the architectural models that guide the structured deployment of these modern factories with particular emphasis on three advanced communication technologies capable of speeding up advancements in the field. It not only highlights the relevance of communication between assets but also lays out mechanisms to achieve these interactions using the Administration shell. Finally, the paper also discusses the key enabling technologies that are typically embedded into bare bone factories to help improve their visibility, resilience, intelligence, and capacity, in addition to how these technologies are being deployed and to what effect. At the onset of the study, we were interested in developing a monograph which would serve as a comprehensive but concise review of general principles, fundamental concepts, major characteristics, key building blocks and implementation guidelines for the Future Factory within the overall context of the manufacturing ecosystem, in the age of Industry 4.0. Our hope is that this paper would enrich the extant literature on advanced manufacturing, help shape policy and research, and provide insights on how some of the identified pathways can be diffused into industry.

Background: Shared value creation in Base of the Pyramid (BoP) communities is a crucial process towards building sustainable societies. BoP communities in developing countries represent more than four billion people who live on low incomes with limited access to basic products and services. Current or emerging technologies offer promising solutions for organisations pursuing manufacturing opportunities in BoP communities. This study seeks to explore the literature on how BoP communities may become active participants in sustainably manufacturing products using micro-manufacturing factories. The research question posed is: What are the core concepts that need to be taken into consideration for creating shared value through micro-manufacturing factories in BoP communities? Method: A Systematised Literature review (SLR) was completed following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) method for data selection criteria and analysis. The SLR is used to explore the state of literature with regards to creating manufacturing shared value in BoP communities with the objective to identify study gaps and to explore shared value creation concepts. Results: Literature indicates BoP initiatives that have pursued to engage BoP communities through various innovation strategies. The findings of the review is organised under three strategic pillars: Capability building strategy, Implementation process, and Growth strategy. The capability building strategy defines the users’ intention to create shared value in BoP communities with Micro-manufacturing factories (MMF). It is followed by the implementation process which guides the users to create manufacturing shared value in BoP communities. This is followed by a growth strategy to scale for impact.

The Wolfram (W), Silicium (Si) and Molybdenum (Mo) doped Co-Cr biomedical alloy were fabricated by additive manufacturing method, which is part of powder metadology. The mixture of Wolfram (W), Silicium (Si), Chrome (Cr) and Cobalt (Co) alloy is known good wear and corrosion resistance among of biomedical applications. By addition of Molybdenum (Mo) into the structure of alloy, the structure become more stbale also increase the corrosion and wear resistance. In addition, the effects of secondary annealing process on the alloy were investigated. The microstructure of the produced alloy was analyzed by X-ray diffraction method XRD, Energy Dispersive X-Ray Analysis EDX and scanning electron microscope SEM. Moreover, Electrochemical corrosion test, micro hardness and density measurements were performed to investigate the mechanical properties of the alloy. As a result of the analyzes, the effects of Molydenum (Mo) doped and secondary annealing on the microstructure and mechanical properties of bioalloying were determined.

In this paper, we present an experimental procedure to enhance the dimensional accuracy of fabrication via Stereolithography (SLA) of features at the micro-scale. Using a custom benchmark part, deviations in feature dimensions (micro-pores diameters and depths) were detected and measured by confocal microscopy. Samples characterization and experimental observations allowed the identification of inaccuracy sources, mainly due to the laser beam scanning strategy and to the incomplete removal of uncured liquid resin in post-processing (i.e., IPA washing). As a technology baseline, the measured dimensional errors on pores diameters were up to -46%. A compensation method of the nominal laser spot diameter (85m) was defined and implemented resulting in relevant improvements in dimensional accuracy of 9.8% and 11.3% on full-open pores diameter and depth, respectively. Further investigation was performed on a customized test part to adjust the calibration procedure. The measurements revealed that the estimate of the laser beam spot size is 968m. Measurements on micro-pores having different sizes revealed that a constant compensation parameter (i.e., C=85, 96, 120m) is not fully effective at the micro-scale, where average errors still remain at -24%, -18.8%, and -16% for compensations equals to 85, 96 and 120m, respectively. A further experimental campaign allowed the identification of an effective nonlinear compensation law where the compensation parameter depends on the micro-feature size C= f (D). Results show a sharp improvement in dimensional accuracy on micro-pore fabrication, with errors consistently below +8.2%. The proposed compensation method can be extended for the fabrication of any micro-features without restrictions on the specific technology implementation. Concerning the inaccuracy introduced by the laser path, experimentation with a customized part allowed the optimization of the part orientation to reduce the errors and their differences along the X and Y machine axes.

An outbreak of occupational methanol poisoning occurred in small-scale 3rd tier factories of large-scale smartphone manufacturer, in the Republic of Korea, in 2016. To investigate the working environment and the health effect of the methanol exposure among co-workers of the methanol poisoning cases, we performed a cross sectional study on 155 workers at the five aluminum CNC cutting factories. Air and urinary methanol concentration were measured by gas chromatography, and health examination included symptoms, ophthalmological examinations and neurobehavioral tests. Multiple logistic regression analyses controlled for age and sex were conducted for revealing association of employment duration with symptoms. Air concentrations of methanol in factory A and E were ranged from 228.5 to 2220.0 ppm. Mean urinary methanol concentrations of the workers in each factory were from 3.5 mg/L up to 91.2 mg/L. The odds ratios for symptom of deteriorating vision and CNS increased, according to the employment duration, after adjusting for age and sex. Four cases with injured optic nerve and two cases with decreased neurobehavioral function were founded among co-workers of the victims. This study showed that the methanol exposure under poor environmental control not only produce eye and CNS symptoms but also affect neurobehavioral function and optic nerve.

Keywords: friction stir processing; additive manufacturing; wire; titanium alloy; material transfer; microstructure; microhardness

The use of additive manufacturing in fabricating composite components has been gaining traction in the past decade. However, some issues with mechanical perfor-mance still need to be resolved. The issue of material porosity remains a pertinent one that needs more understanding to be able to determine viable solutions. Different re-searchers have examined the subject of porosity issues in AM-fabricated CFRP compo-sites. However, more research to quantitatively determine the effects of fabrication temperatures at the micro-scale is still needed. This study employed micro CT scan analysis to quantitatively compare the effects of fabrication temperatures at 230°C, 250°C, 270°C, and 290°C for CF-PA and CF-ABS composites. This followed an SEM evaluation which was used to determine the effects of the temperatures on interlayer and intralayer porosity generation. The porosity volume was related to the mechanical properties results in which it was determined how deposition temperatures affect the porosity volumes. It was also determined that semicrystalline composites are generally more affected by fabrication temperatures than amorphous composites, with the rela-tionship between porosity and mechanical properties also established. The overall po-rosity volume from the interlayer and intralayer voids was also determined, with the interlayer voids found to play a more determinant role in influencing the mechanical properties.

This work presents the results of the experimental and theoretical study of the static pull-in of tilting actuation executed by a hybrid levitation micro-actuator (HLMA) based on the combination of inductive levitation and electrostatic actuation. A semi-analytical model to study such the pull-in phenomenon is developed, for the first time, as a result of using the qualitative technique based on the Lagrangian approach to analyze inductive contactless suspensions presented in work and a recent progress in the calculation of mutual inductance and force between two circular filaments. The obtained non-linear model, accounting for two degrees of freedom of the actuator, allows us to predict accurately the static pull-in displacement and voltage. The results of modelling were verified experimentally and agree well with measurements.

While laminar flow heat transfer and mixing in microfluidic geometries has been investigated experimentally, as has the effect of geometry-induced turbulence in microfluidic flow (it is well documented that turbulence increases convective heat transfer in macrofluidic flow), little literature exists investigating the effect of electrokinetically-induced turbulence on heat transfer at the micro scale. Using recently observed experimental data, this work employed computational fluid dynamics coupled with electromagnetic simulations to determine if electrokinetically-forced, low-Reynolds number turbulence could be observed in a rectangular microchannel with using Newtonian fluids. Analysis of the results was done via comparison to the experimental criteria defined for turbulent flow. This work shows that, even with a simplified simulation setup, computational fluid dynamics (CFD) software can produce results comparable to experimental observations of low-Reynolds turbulence in microchannels using Newtonian fluids. In addition to comparing simulated velocities and turbulent energies to experimental data this work also presents initial data on the effects of electrokinetic forcing on microfluidic flow based on entropy generation rates.

A pilot study on laser 3D printing of inorganic free-form micro-optics is experimentally validated. Ultrafast laser nanolithography is employed for structuring hybrid organic-inorganic material SZ2080TM followed by high-temperature calcination post-processing. The combination allows production of 3D architectures and the heat-treatment results in converting the material to inorganic substance. The produced miniature optical elements are characterized and their optical performance demonstrated. Finally, the concept is validated for manufacturing compound optical components such as stacked lenses. This is opening for new directions and applications of laser made microoptics under harsh conditions such as high intensity radiation, temperature, acidic environment, pressure variations, which include open space, astrophotonics, and remote sensing.

The current rapidly changing and highly competitive market has put companies under a great pressure not only to be successful, but also to sustain their success into the future. In addition, in recent years, companies have become more aware of the fact that it is no longer enough to take care of economic aspects, being crucial to also take care of environmental and social aspects in order to actually succeed and lead in the current and future markets. In this context, companies are urged to move towards more innovative manufacturing practices that maintain a healthy balance among economic, environmental and social performances, which are the three pillars of the sustainability performance. To give some insight into this issue, a Systematic Literature Review (SLR) is conducted in this paper regarding the current trends in the field, doing special focus on the link between lean-green manufacturing and the different sustainability aspects. The SLR concluded that lean and green implementations as stand-alone systems are usually not enough to ensure the required balance between the three pillars of sustainability, suggesting further combining them into a single approach. Researchers expect to achieve further improvements in the sustainability performance moving towards the next level of sustainability.

Micro-technology has played a substantial role in bioscience, biomedical and biotechnological research due to its core advantages in modern science and engineering. It has created unique development in various sectors of bio-research and upsurges the efficacy of research at the molecular level in recent years. Microfluidic technology makes it possible to manipulate sample volumes at the micro- and nano-level (called nanofluidics) with terrific control outside in vivo cellular microenvironment, enabling the reduction of discrepancies between in vivo and in vitro environments as well as reducing reaction time and cost. In this review, we discuss various effective integrations of microfluidic technologies into biotechnology and its paradigmatic significance in bio-research, supporting mechanical and chemical in vitro cellular micro-environment. Specific innovations relating to the application of microfluidics to advance microbial life, solitary and co-cultures along with a multiple-type cell culturing, cellular communications, cellular interactions and population dynamics are discussed.

The present work studies the concept of productivity in shipbuilding and how it should be measured. The existing metrics, shipbuilding process and shipyard organization were studies in order to choose the most adequate metrics which would allow the measuring of a shipyard productivity in a systematic and holistic way. This is achieved by gathering the man-hours spent in each ship organized by cost centre and using Compensated Gross Tonnages as the measure of output from the shipyard. Data was gathered for thirty ships built in the same European yard organized by cost centre. From the data collected it was found that the ratio of hours spent in outfitting to the hours spent in structures is proportional to the complexity of the ship. There was also opportunity to study the work reduction resulting from building ships in series and the shares of labour for ships series and across ship types.

The controllability and consistency in the fabrication of micro-textures on large-scale remains a challenge for existing production processes. Mask electrolyte jet machining (MEJM) is an alternative to Jet-ECM for controllable and high-throughput surface microfabrication with more consistency of dimensional tolerances. This hybrid configuration combines the high-throughput of masked-ECM and the adjustable flow-field of jet-ECM. In this work, a duckbill jet nozzle was introduced to make MEJM more capable of batch micro-structuring. A multiphysics model was built to simulate the distribution of electrochemical reaction ions, the cur- rent density distribution and the evolution of the shape of the machined cavity. Experimental investigations are presented showing the influence of the machining voltage and nozzle moving speed on the micro cavity. Several 35 ×35 micro cavity arrays with a diameter of 24.92 − 11.73 µm and depth of 15.86 − 7.24 µm are generated on 304 stainless steel.

We report a 92 channel RF channelizer based on a 48.9 GHz integrated micro-comb that operates via soliton crystals, together with a passive high-Q ring resonator that acts as a periodic filter with an optical 3dB bandwidth of 121.4 MHz. We obtain an instant RF bandwidth of 8.08 GHz and 17.55 GHz achieved through temperature tuning. These results represent a major advance to achieving fully integrated photonic RF spectrum channelizers with reduced low complexity, size, and high performance for digital-compatible signal detection and broadband analog signal processing.

The steady streaming (SS) phenomenon is gaining increased attention in the microfluidics community, because it can generate net mass flow from the zero-mean vibration. We developed numerical simulation and experimental measurement tools to analyze this vibration induced flow, which has been challenging due to its unsteady nature. Validity of these analysis methods is confirmed by comparing the three-dimensional (3D) flow field induced around a cylindrical micropillar under circular vibration. In the numerical modeling, we directly solved the flow in the Lagrangian frame so that the substrate with a micropillar becomes stationary, and the result was converted to the Eulerian frame to compare them with the experimental results. The present approach enables to avoid the introduction of moving boundary or small perturbation approximation. The flow field obtained by the micro particle image velocimetry (PIV) measurement supported the three-dimensionality observed in the numerical results, which could be important for controlling the mass transport and manipulating particulate objects in the microfluidic systems.

Digital technologies have been present in manufacturing and industry for a long time, and today they represent the basis for the application of the Industry 4.0 model in practice. The transformation marked by the Industry 4.0 model is based on the application of a large number of models of communication technologies, solutions for connecting entities (machines, parts, ...) in the factory within Internet of Things (IoT), as well as the possibility of big data analysis (BDA) throught the artificial intelligence tools (AI/ML). These technologies provide great opportunities to create more flexible and profitable manufacturing processes based on data, and using the Internet. As more and more factories and their equipment are IoT enabled, the volume of data will only grow, hence the application of digital technologies is inevitable. To truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into cognitive manufacturing, which is the base model of smart manufacturing. This paper provides an overview of the development of the concept of digital manufacturing, from different aspects, with examples of application in real manufacturing. The goal is to create a good practice of digital manufacturing with the elements of Industry 4.0, as a basis for the development and application of the smart manufacturing (SM) model.

The development of organ-on-chip and biological scaffolds is currently requiring simpler methods to microstructure biocompatible materials in three dimensions, fabricate structural and functional elements in biomaterials or modify the physicochemical properties of desired substrates. Aiming at addressing this need, a low-power CD-DVD-Blu-ray laser pickup head was mounted on a programmable three-axis micro-displacement system in order to modify the surface of polymeric materials in a local fashion. Thanks to a specially-designed method using a strongly absorbing additive coating the materials of interest, it has been possible to establish and precisely control processes useful in microtechnology for biomedical applications. The system was upgraded with blu-ray laser for additive manufacturing and ablation on a single platform. In this work, we present the application of these fabrication techniques to the development of biomimetic cellular culture platforms thanks to the simple integration of several features typically achieved with traditional, less cost-effective microtechnology methods in one step or through replica-molding. Our straightforward approach indeed enables great control of local laser microablation or polymerization for true on-demand biomimetic micropatterned designs in transparent polymers and hydrogels and is allowing integration of microfluidics, microelectronics, surface microstructuring and transfer of superficial protein micropatterns on a variety of biocompatible materials.

Hybrid machine tools combining additive and subtractive processes have arisen as a solution to the increasing manufacture requirements, boosting the potentials of both technologies, while compensating and minimizing their limitations. Nevertheless, the idea of hybrid machines is relatively new and there is a notable lack of knowledge in the field. Therefore, in the present paper, an insight into the advancements of hybrid machines is given, identifying their real capabilities, together with the latest developments from an industrial context. In addition, the current situation and future perspectives of hybrid machines from the point of view of process planning, monitoring and inspection are discussed. Finally, the challenges that must be overcome and the opportunities that the hybrid machines will provide in the forthcoming years are presented.

To improve the measurement accuracy of wood density and study the linear correlation between the drill feed resistance and wood density, a new micro drill instrument that can can simultaneously measure the rotation resistance and feed resistance of the drill needle was designed. The test wood samples included hardwood, softwood and conifer. The absolute dry density of each wood sample was measured. The drill resistance data was tested by using self-developed micro drill instrument and Resistogaph 650-SC. 4 linear models between drill resistance and the absolute dry density of wood . The results showed that: the statistical indicators of each model of the self-made micro drill resistance in-strument were better than the corresponding indicators of Resistogaph 650-SC; the coefficient of determination of the linear regression model between the feed resistance of the self-made micro drill resistance instrument and the absolute dry density of wood was 0.946; the statistical indicators of model including rotation resistance and feed resistance, were better than those of the model only including rotation resistance. Therefor, the design proposed in the article is reasonable, and increasing the feed resistance can improve the measurement accuracy of the micro drill resistance instrument for measuring wood density.

Additive manufacturing (AM) provides opportunities to design objects differently than traditional manufacturing methods allow, but only if designers understand the possibilities AM presents. In this study, we examined whether an AM workshop combined with an idea generation session could inspire engineering professionals to use AM solutions to solve current technical problems they face. All subjects were employees at an organization that will be referred to as Company X, a multinational commercial organization based in North America. During the study, we collected ideas for 24 projects generated before and after a training workshop focused on design for AM. In the workshop, we provided three hours of instruction about design for two metal-based AM processes. The participants’ ideas were assessed using four specific metrics: (1) cost, (2) time,(3) completeness of solution, and (4) quality, which was a function of feasibility, usefulness, and novelty. Using these data, we explored whether the workshop was effective in inspiring the participants to use AM methods and techniques from AM research in their concept generation and whether participants’ AM solutions showed improvement in cost, implementation time, and quality over non-AM designs generated before the workshop.

Traditional metals such as stainless steel, titanium and cobalt chrome are used in biomedical applications (implants, scaffolds etc.) but suffer from issues such as osseointegration and compatibility with existing bone. One way to improve traditional biomaterials is to incorporate ceramics with these metals so that their mechanical properties can be similar to cortical bones. Tricalcium phosphate is such a ceramic with properties so that it can be used in human body. This research explores the use of binder jetting based additive manufacturing process to create a novel biocomposite made of cobalt chrome and tricalcium phosphate. Experiments were conducted and processing parameters were varied to study their effect on the printing of this biocomposite. Layer thickness, binder saturation and drying time affected the dimensional tolerance and the density of the green samples. This effect is important to understand so that the material can be optimized for use in specific applications.

As China put forward its “carbon emissions peak and carbon neutrality” goals, how to achieve carbon reduction had become a key for China’s goal. The manufacturing industry is an important source of carbon dioxide emissions. For a manufacturing country like China, adjustments in various aspects of the industry would have a huge impact on carbon emissions. As an important reform of contemporary production mode, the process of production automation in China will inevitably affect China's carbon emissions. Therefore, the analysis of the impact of production automation on carbon dioxide emissions was an important basis for judging the future carbon reduction in China. Refer to the traditional study of carbon Kuznets curve, this paper analyzed the impact of average wage on production automation and the role of production automation in the carbon Kuznets curve(CKC). This paper proposed that production automation plays a mediating role in the process of carbon emissions, and gives a verification model of the mediating role. By analyzing the relationship between average wage and production automation process, the U-shaped curve relationship between them was verified. By examining the relationship between carbon dioxide emission data and production automation industry in China, we verified that production automation plays a partial mediating role in the change of carbon Kuznets curve. Combined with the analysis of the two parts, this paper believed that with the continuous development of China's intelligent manufacturing industry, China's carbon reduction prospects were more optimistic, and there was a good industrial foundation to achieve the “carbon peaking and carbon neutrality” goals. Finally, this paper proposes policy suggestions as increase research investment in production automation, help promote the application of production automation, encourage the research and application development of low-carbon technology, especially encourage modular design, so as to give full play to the role of production automation in the process of carbon neutrality in China.

Control as a Service (CaaS) is an emerging paradigm where low-level control of a device is moved from a local controller to the Cloud, and provided to the device as an on-demand service. Among its many benefits, CaaS gives the device access to advanced control algorithms which may not be executable on a local controller due to computational limitations. As a step toward 3D printer CaaS, this paper demonstrates the control of a 3D printer by streaming low-level stepper motor commands (as opposed to high-level G-codes) directly from the Cloud to the printer. The printer is located at the University of Michigan, Ann Arbor, while its stepper motor commands are calculated using an advanced motion control algorithm running on Google Cloud computers in South Carolina and Australia. The stepper motor commands are sent over the Internet using the user datagram protocol (UDP) and buffered to mitigate transmission delays; checks are included to ensure accuracy and completeness of the transmitted data. All but one part printed using the cloud-based controller in both locations were hitch free (i.e., no pauses due to excessive transmission delays). Moreover, using the cloud-based controller, the parts printed up to 54% faster than using a standard local controller, without loss of accuracy.

In this work modeling and analysis of an integrated opto-fluidic sensor, with a focus on achievement of single mode optical confinement and continuous flow of micro particles in the microfluidic channel for Lab-on-a Chip (LOC) sensing application is presented. This sensor consists of integrated optical waveguides, microfluidic channel among other integrated optical components. A continuous flow of micro particles in a narrow fluidic channel is achieved by maintaining the two sealed chambers at different temperatures and by maintaining a constant pressure of 1Pa at the centroid of narrow fluidic channel geometry. The analysis of silicon on insulator (SOI) integrated optical waveguide at an infrared wavelength of 1550nm for single mode sensing operation is presented. The optical loss is found to be 0.0005719dB/cm with an effective index of 2.2963. The model presented in this work can be effectively used to detect the nature of micro particles and continuous monitoring of pathological parameters for sensing applications.

Having garnered significant attention in the scientific community over the past decade, Wire Arc Directed Energy Deposition (arc-DED) technology is at the heart of this investigation into additive manufacturing parameters. Singularly focused on invar as the selected material, the primary objective revolves around devising an indirect cord height measurement approach. This innovative methodology involves the seamless integration of internal signals and sensors, enabling the derivation of crucial measurements sans the requirement for direct physical interaction or conventional measurement methodologies. Through the course of this research, meticulous alteration of deposition parameters is undertaken to thoroughly scrutinize their influence on the ultimate cord dimensions. The fusion of cutting-edge manufacturing techniques with advanced sensor technology constitutes the essence of this endeavor, offering substantial potential to augment precision and efficiency in additive manufacturing processes. Remarkably cost-effective, this solution circumvents the need for intricate measurements and significantly contributes to the proper layer-by-layer growth process.

The solved research problem is oriented to the implementation of advanced methods of component design and their sophisticated use in the ever-advancing additive manufacturing. Based on the stated objectives, the research was divided into several parts. Initially, the methods and principles of design in additive manufacturing were evaluated and investigated, from which the intent was subsequently defined and the DfAM method in the component design and development process was determined. The given design method, namely topology optimization (TO), was applied to multiple development and production cycles of additive manufacturing parts to validate the research conclusions. In this paper, the procedure for a specific part or component assembly is shown. By evaluating the developed design procedure using the TO method included in the design process, the conclusions are positive in terms of both time savings and properties of the designed part such as strength and weight parameters. The given findings need to be further developed by implementing on specific product lines for increasing the efficiency of the developed design methodology.

This article explores the important role of traditional shipyards in the global maritime industry, covering aspects of construction, repair, and maintenance. With the advent of faster manufacturing techniques, traditional shipyards face important challenges such as planning errors, coordination problems, delivery delays, and underutilization of technology, which results in high costs, reduced productivity, and prolonged projects. The application of Manufacturing Cycle Efficiency (MCE) emerged as an important solution to significantly increase production efficiency. MCE empowers shipyards to deal effectively with waste, bottlenecks, and disruptions, thereby increasing performance, competitiveness, and profitability. Using a comprehensive approach that uses both qualitative and quantitative methods, including field surveys, and in-depth interviews in the traditional shipyards industry, this research identifies Non-Value-Added (NVA) processes, conducts process mapping, and calculates MCE. The findings reported in this article underscore the significant wastage in the production process, indicating an urgent need for improvement, given the current average MCE value of 67.08%, indicating considerable room for improvement. This article provides innovative perspectives on optimizing the traditional shipyards industry through production cycle efficiencies while offering actionable recommendations. Key focus areas include integrating management systems, adopting advanced technologies, and implementing sustainable strategies to improve MCE, especially by reducing non-value-added time wastage, such as inspection and storage. By implementing strategies that optimize production, minimize waste, and overcome the challenges of global competition, this research contributes to improving MCE. In conclusion, this study is an invaluable guide for industry stakeholders, enabling them to enhance their competitiveness and adapt effectively to a dynamic business environment.

Additive manufacturing has already been established as a highly versatile manufacturing technique with demonstrated potential to completely transform conventional manufacturing in the future. The objective of this paper is to review the latest progress and challenges associated with the fabrication of multi-material parts using additive manufacturing technologies. Various manufacturing processes and materials used to produce functional components were investigated and summarized. The latest applications of multi-material additive manufacturing (MMAM) in automotive, aerospace, biomedical and dentistry field were demonstrated. Investigation on the current challenges were also carried out to predict the future direction of MMAM processes. It is concluded that the further research and development needed in the design of multi-material interfaces, manufacturing processes and material compatibility of MMAM parts are necessary.

The use of flexible sensors has tripled over the last decade due to the increased demand in various fields including health monitoring, food packaging, electronic skins and soft robotics. Flexible sensors have the ability to be bent and stretched during use and can still maintain their electrical and mechanical properties. This gives them an advantage over rigid sensors that lose their sensitivity when subject to bending. Advancements in 3D printing have enabled the development of tailored flexible sensors. Various additive manufacturing methods are being used to develop these sensors including inkjet printing, aerosol jet printing, fused deposition modelling, direct ink writing, selective laser melting and others. Hydrogels have gained much attention in the literature due to their self-healing and shape transforming. Self-healing enables the sensor to recover from damages such as cracks and cuts incurred during use and this enables the sensor to have a longer operating life and stability. Various polymers are used as substrates on which the sensing conductive material is placed. Polymers including polydimethylsiloxane (PDMS), polyvinyl acetate (PVA), and Kapton are extensively used in flexible sensors. The most widely used nanomaterials in flexible sensors are carbon and silver, however, other nanomaterials such as iron, copper, manganese dioxide and gold are also used to provide controlled levels of conductivity or other functional properties.

As the additive manufacturing industry grows, it is compounding the global plastic waste problem. Distributed recycling and additive manufacturing (DRAM) offers an economic solution to this challenge, but it has been relegated to either small-volume 3D printers (limiting waste recycling throughput) or expensive industrial machines (limiting accessibility and lateral scaling). To overcome these challenges, this paper provides proof-of-concept for a novel open-source hybrid 3D printer that combines a low-cost hanging printer design with a compression screw-based end-effector that allows direct extrusion of recycled plastic waste in large expandable printing volumes. Mechanical testing of the resultant prints from 100% waste plastic, however, showed that combining challenges of non-uniform feedstocks and a heavy printhead for a hangprinter reduced the strength of the parts compared to fused filament fabrication. The preliminary results are technologically promising, however, and provide opportunities to improve on the open source design to help process the volumes of waste plastic needed for DRAM to address the negative environmental impacts of global plastic use.

Rapidly providing a definitive diagnostic test that can be used broadly by healthcare providers and members of the public in the setting of a disease emergency is critical to limit pathogen spread, develop and deploy medical countermeasures, and mitigate the social and economic harms of a serious epidemic or pandemic. There is extraordinary expertise within and outside of government working on these issues, and major accomplishments have been made to accelerate test development, expand laboratory testing capacity, and establish widespread point-of-care testing. Still, the United States does not have a plan to rapidly respond, to develop, manufacture, or deploy at national scale diagnostic testing in the earliest days of a new infectious disease crisis. Nor does the nation have a plan to sustain testing capacity at high volume over the course ofan enduring epidemic or pandemic. To address this gap, we are proposing a National Diagnostics Action Plan that describes the steps that are urgently needed to prepare for future infectious disease emergencies, as well as the actions we must take at the first signs of such events. These recommendations require substantial collaboration between the US government (USG) and the private sector to solve a series of challenges now, as well as to prepare for the massive and rapid scale-up of laboratory and point-of-care test development and testing capacity in future emergencies. The recommendations include establishing pre-event contracts; ensuring rapid access to clinical samples; creating a permanent public-private testing coordinating body to allow for rapid information sharing and improved cooperation among the USG, test developers, and clinical laboratories; and accelerating testing rollout at the beginning of an event—andthus, the effective public health management of a disease crisis. These recommendations were informed by extensive discussion with people who managed the COVID-19 and monkeypox responses, review of past reports written on diagnostic challenges, and the experiences of the authors.

(1) In recent ten years, with the fast development of digital and engineering manufacturing technology, additive manufacturing has already been more and more widely used in the field of dentistry, from the first personalized surgical guides to the latest personalized restoration crowns and root implants. (2) Especially, the bioprinting of teeth and tissue is of great potential to realize organ regeneration and finally improve the life quality. (3) In this review paper, we firstly presented the workflow of additive manufacturing technology. Then we summarized main applications and recent research progresses of additive manufacturing in dentistry. (4) Lastly, we sketched out some challenges and future directions of additive manufacturing technology in dentistry.

In the production of green parts from powder, there is unavoidable slight deviation in the die filling, even when high-quality powders are used. The quantity of powder in the die varies and thus affects the weight of the compact. This filling variation results in variation of the pressing force, and thus influences the part geometry. The development of the DORST Netshape® System was conceived as an autonomous manufacturing system in order to compensate for these effects. Based on the Dorst Industry 4.0 innovations for part weight measuring immediately after pressing in combination with a laser dimension measuring system, this technology package attempts to reach enhanced precision and consistency in production. The paper presents results from various trials that show the capability of this new system, designed to improve the quality of pressed parts.

This paper presents the results of the investigation of composite sinters W-TiB2 which were used as an electrode in the process of electro-spark deposition (ESD) and the examination of the deposited layers. The scope of the study includes detailed characteristics of powder mixtures, composite sinters made using the spark plasma sintering method (SPS) and layers deposited in the electro-spark process. The ESD process, using the W+30 vol.% TiB2 electrode, was carried out using an automated device. The substrates were made of copper and aluminium. The topography analysis of the surfaces of the composite layer and the evaluation of their wear resistance properties are also presented. The analysis of the results of research showed the possibility to obtain, using the SPS method, composite materials of good quality, which can be used as electrodes in the ESD process. The obtained layers had increased wear resistance in relation to the substrate material.

We present progress in fast, high-resolution imaging, material classification, and fault detection using hyperspectral X-ray measurements. Classical X-ray CT approaches rely on data from many projection angles, resulting in long acquisition and reconstruction times. Additionally, conventional CT cannot distinguish between materials with similar densities. However, in additive manufacturing, the majority of materials used are known a priori. This knowledge allows to vastly reduce the data collected and increase the accuracy of fault detection. In this context, we propose an imaging method for non-destructive testing of materials based on the combination of spectral X-ray CT and discrete tomography. We explore the use of spectral X-ray attenuation models and measurements to recover the characteristic functions of materials in heterogeneous media with piece-wise uniform composition. We show by means of numerical simulation that using spectral measurements from a small number of angles, our approach can alleviate the typical deterioration of spatial resolution and the appearance of streaking artifacts.

Fatigue remains a challenge especially for high end metal AM parts and materials. From a design perspective, the fatigue limit of an AM solution can be improved upon by optimizing the manufacturing process for a certain material and part. In addition, improved accuracy of design methodologies aids in capturing the features critical for fatigue and quantifies their significance to desired part lifetime as well as providing a basis for their avoidance. In current work we present an overall concept merging thermomechanical process and powder bed solidification modeling to micromechanical analysis of fatigue of the resulting material microstructure. Material features critical to fatigue, particularly surface roughness, internal defects such as porosity and cracks and on the other hand inclusions, can be assessed directly on the basis of AM part microstructure with respect to the resulting fatigue limit. Case analyses consist of maraging steel and nickel alloys. The overall scheme provides a basis for optimization of metal AM solutions against fatigue and multiscale modeling founded basis for fatigue design.

Quality assurance has been one of the major challenges in laser-based additive manufacturing (AM) processes. This study proposes a novel process modeling methodology for layer-wise in-situ quality monitoring based on image series analysis. An image-based autoregressive (AR) model has been proposed based on the image registration function between consecutively observed thermal images. Image registration is used to extract melt pool location and orientation change between consecutive images, which contains sensing stability information. Subsequently, a Gaussian process model is used to characterize the spatial correlation within the error matrix. Finally, the extracted features from the aforementioned processes are jointly used for layer-wise quality monitoring. A case study of a thin wall fabrication by a Directed Laser Deposition (DLD) process is used to demonstrate the effectiveness of the proposed methodology.

Additive Manufacturing (AM) simplifies the fabrication of complex geometries. Its scope has rapidly expanded from the fabrication of pre-production visualization models to the manufacturing of end use parts driving the need for better part quality assurance in the additively manufactured parts. Machine learning (ML) is one of the promising techniques that can be used to achieve this goal. Current research in this field includes the use of supervised and unsupervised ML algorithms for quality control and prediction of mechanical properties of AM parts. This paper explores the applications of supervised learning algorithms - Support Vector Machines and Random Forests. Support vector machines provide high accuracy in classifying the data and is used to decide whether the final parts have the desired properties. Random Forests consist of an ensemble of decision trees capable of both classification and regression. This paper reviews the implementation of both algorithms and analyzes the research carried out on their applications in AM.

Producing complex shaped tungsten carbide cobalt (WC-Co) tools by classical technologies is difficult and often impossible due to their high hardness and brittle fracture behavior. Additive Manufacturing (AM) is a suitable technology for creating complex structures and simultaneously shortening expensive machining processes. Binder Jetting (BJ) is an innovative AM technology that offers several advantages over laser-based processes, for example low manufacturing costs and high build-up rates. Binders with nanoparticle additives have already proven to be effective in in- creasing the packing density of the powder bed and improving the sintering properties. Addition- ally, they offer the possibility of selectively changing the material composition in the part. This paper presents a concept for the use of nanoparticles to generate gradients in the green compact, which leads to a cobalt gradient in the part after sintering. The possibility of introducing particles locally into complex structures allows local modification of the material properties.

Understanding the equilibrium saturation level is crucial to Binder Jetting (BJ). Saturation level influences dimensional accuracy, print time, green strength, and final material properties. Improved understanding of the saturation level can reduce development time for new materials and improve existing processes in BJ. Attempts have been made to predict saturation levels of parts with simple calculations from droplet primitives and capillary pressure. There is, however, limited experimental validation for these methods and they do not include the impact of drop velocity and droplet spacing. This study incorporates the influences of drop velocity and droplet spacing on the saturation level of the part. Drop primitives of varying droplet velocity and droplet spacing were compared. Results show that velocity impacts the feasible parameter space.

Powder Bed Fusion (PBF) is a type of Additive Manufacturing (AM) technology that builds parts in a layer-by-layer fashion out of a bed of metal powder via the selective melting action of a laser or electron beam heat source. The technology has become widespread, however the demand is growing for closed loop process monitoring and control in PBF systems to replace the open loop architectures that exist today. This paper demonstrates the simulated efficacy of applying closed-loop state estimation to the problem of monitoring temperature fields within parts during the PBF build process. A simplified LTI model of PBF thermal physics with the properties of stability, controllability and observability is presented. An Ensemble Kalman Filter is applied to the model. The accuracy of this filters’ predictions are assessed in simulation studies of the temperature evolution of various test parts when subjected to simulated laser heat input. The significant result of this study is that the filter supplied predictions that were about 2.5x more accurate than the open loop model in these simulation studies.

One of the main benefits of binder jetting is the ability to print quickly compared to other metal additive manufacturing methods. Demand for higher throughput continues to increase, but the effects of faster print speeds on part outcomes are not yet clearly understood. MIM powders are used to achieve optimal density and surface finish. Printing at slower speeds results in densities near 98% and average surface roughness values as low as 4 μm (Ra), in the as-sintered condition. In this study, spread speeds were varied in order to understand the effect of print speed on surface roughness. 316L D90 -22 μm powder was used to print with 3 different spread speeds, 2 different layer thicknesses, and 2 different printhead droplet sizes. The surface finish and density were quantified for the sintered parts that were oriented at 0, 22.5, and 45 degrees with respect to the Z- direction.

Construction of Pontoons is based on multiple elements, dimensions and weight. The study has addressed about how the industry of the floating reinforcement concrete precast (pontoons) installs in the factory with the combinations of utility, electricity services, and Internet service. The pontoon bridges are successfully installed in the road for transport or sea for shops. The installation process for pontoons is successfully attempted in a balanced situation above surface of the sea to the resistant of floating precast (pontoons) to any ambient effects such as weather conditions, the movement of the waves or any others effects. The findings elaborate that it is not just a military solution. Pontoon installation can significantly serve for civil purposes.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

This study presents the manufacturing process driven development of an interlocking metasurface mechanism (ILM) for Fused Filament Fabrication (FFF) with a focus on open-source accessibility. The presented ILM is designed to enable strong contact between to planar surfaces. The mechanism consists of spring elements and locking pins which snap together when forced into contact. The mechanism is designed to optimize mechanical properties, functionality and printability with common FFF printers. The mechanisms is printed from thermoplastic polyurethane (TPU) filament which was selected for its flexibility, crucial for spring element performance and tolerances of the fabrication method. To characterize the designed mechanism a tensile test is carried out to assess the holding force of the ILM. The force-displacement profiles are analyzed and categorized into distinct phases, highlighting the interplay between spring deformation, sliding, and disengagement. The results show variations in holding forces attributed to geometric and material-related factors. The testing results are compared and discussed to a numerical simulation carried out with a frictionless approach with a nonlinear Neo–Hookean material law. The study underscores the importance of meticulous parameter control in 3D printing for consistent and reliable performance of interlocking metasurface mechanisms. The investigation leads to a scalable model of a ILM element pair with a distinct three-phase snapping characteristics ensuring reliable holding capabilities.

Additive manufactured interlocking structures often face challenges in achieving suitable joinability due to thermal deformation. This issue becomes particularly interesting when fabricating structures that require high density but not fully connected layers, such as soft-magnetic materials. This study focuses on systematical investigation of the deformation as a function of finger thickness and building direction in model interlocking structure. In the perpendicular direction to the build plate, the distortions of joint part were significantly reduced due to lower thermal stress. In addition, the effect of laser power and scan speed on interlocking structure are systematically discussed. Additionally, through stress and thermal simulations of additive manufacturing process, it was confirmed that the compensated model can enhance the joinability of interlocking structures. These findings contribute to the development of optimal design for additive manufactured parts of soft magnetic materials such as stators in electric motor components, which needs insulations and density.

This paper presents a systematic approach to developing big data analytics for manufacturing process-relevant decision-making activities from the perspective of smart manufacturing. The proposed analytics consists of five integrated system components: 1) data preparation system, 2) data exploration system, 3) data visualization system, 4) data analysis system, and 5) knowledge extraction system. The functional requirements of the integrated systems are elucidated. In addition, JAVA- and spreadsheet-based systems are developed to realize the proposed integrated system components. Finally, the efficacy of the analytics is demonstrated using a case study where the goal is to determine the optimal material removal conditions of a dry electrical discharge machining operation. The analytics identified the variables (among voltage, current, pulse-off time, gas pressure, and rotational speed) that effectively maximize the material removal rate. It also identified the variables that do not contribute to the optimization process. The analytics also quantified the underlying uncertainty. In synopsis, the proposed approach results in transparent, big-data-inequality-free, and less resource-dependent data analytics, which is desirable for small and medium enterprises—the actual sites where machining is carried out.

The paper presents the conceptualization and realization of a novel platform for additive manu-facturing, an industrial robot arm-based system for additive manufacturing applications. Tradi-tional 3D printers, especially those employing fused deposition modelling (FDM) processes, are restricted to depositing material in a single toolpath plane (e.g. x-y plane). The focus of this study was to explore the feasibility of integrating commercial off the shelf (COTS) additive manufac-turing technologies with a six degree of freedom industrial robot arm to yield a 3D additive manufacturing system with the capability to perform free-form six degree of freedom fused deposition modelling. The present paper presents the development of a platform from stage 0, i.e. materials to its use, and finally a printed product with the developed extruder.

Grape dehydration is practiced widely in the food industry with large yields of sultanas produced globally. This paper proposes an investigation into grape microstructure changes as it is dried by imaging specimens at intervals during dehydration at two temperatures using scanning electron microscopy. Detailed images of the microstructure were obtained, and a unique image processing algorithm was developed to quantitatively analyse the properties of this microstructure. Two main methods were developed to obtain the complex boundaries of cells present in the grape tissue in over 36 SEM images. Segmentation of the binary image using an adapted watershed function obtained the most consistent and accurate morphological shape. This was compared to a secondary method which used Canny’s edge detection function, morphological closing and skeletonizing to outlines the cellular microstructure. MATLAB was utilised to convert these boundaries into measurable areas so that quantitative data on average cell area, perimeter and cell axis lengths was acquired. It was found that over drying time cell area and perimeter reduced as expected. Some variability in the data was clear due to only single samples being analysed for each temperature and time combination. The development of automatic image processing techniques will enable quantitative data to be extracted from these images. Trends in cell perimeter, diameter and shape will be used to demonstrate relationships between morphological structure, drying temperature, and duration.

With the increased emphasis on competition in academic settings, anxiety is becoming more common, which inevitably has some impact on students’ learning process and result. This study aimed to explore how competition-induced anxiety influences the subjective cognitive load (SCL), attention level and test score. Meanwhile, we investigated the mediating role of the behavioral inhibition system/behavioral activation system (BIS/BAS) in those processes. A total of 101 college students were recruited in Study 1 to learn five micro-lectures from massive open online courses (MOOC) under with and without competitive conditions. The results showed that participants’ state anxiety (SA) scores were higher after the experiment, participants in the competition condition had higher test scores, and the relationship between SA/ trait anxiety (TA) and SCL could be mediated by the BIS. To obtain more objective data on learning processes (attention levels), we conducted Study 2, which collected behavioral and EEG data from 42 college students during the online learning. The results showed that the competition group had higher SA, lower attention levels, and worse test scores, and the relationship between SA/TA and attention levels could be mediated through the BIS. The present study not only expands previous research by finding that BIS functioning plays an important role in the effects of anxiety on cognitive load and attention, but also offers implications for using competitive strategies to motivate students according to their aptitude.

In our day-to-day life, Lie detection has a significant concern. We human beings are very much inaccurate while detecting the liars and We believe in what we are told. Lie detection is important in today’s life, because Concealing the information or faking it can sometimes take you to huge problems. In any areas like airport management[2], criminal investigations, counterterrorism, etc this concept has great importance. It is an evergreen challenging and changing topic. This paper presents the common technique which was followed up till now and why it was not considered effective and a review of Robust solutions to detection of deception. People generally do not[3] always believe on what someone says but also try to visualize their facial expressions. While in Robust solution these facial micro-expressions are identified, which are tiny, natural expressions seen on the individual’s face, when they try to conceal or suppress emotions. In addition, the article also provides the year-wise assessment and analysis of research articles published in the area of Lie detection from 2011 to 2022. In the end, our proposed framework for lie detection system is also presented. This paper cover up current issues as well as challenges that could be helpful to resolve in future research works. The review paper closes up by supporting future directions.

Abstract: Microstructural and mechanical properties of the eutectic Sn58Bi and micro-alloyed Sn57.6Bi0.4Ag solder alloys were compared. With the addition of Ag micro-alloy, the tensile strength was improved and this is attributed to a combination of microstructure refinement and an Ag3Sn precipitation hardening mechanism. However, ductility is slightly deteriorated due to the brittle nature of the Ag3Sn intermetallic compounds (IMCs). Additionally, a board level reliability study of Ag micro-alloyed Sn58Bi solder joints produced utilising a surface-mount technology (SMT) process, were assessed under accelerated temperature cycling (ATC) conditions. Results reveal that micro-alloyed Sn57.6Bi0.4Ag has a higher characteristic lifetime with a narrower failure distribution. This enhanced reliability corresponds with improved bulk mechanical properties. It is postulated that Ag3Sn IMCs are located at the Sn-Bi phase boundaries and suppress the solder microstructure from coarsening during the temperature cycling, hereby extending the time to failure.

The tissue micro environment or milieu consists of a highly dynamic population of cellular and non-cellular components which constitute a complex regulatory network aimed at maintaining the organ homeostasis. In the modern medicine the discovery of miRNAs is undoubtedly a promising field of research and they are essential in orchestrating immune system logic and their release in the gut micro milieu can directly affect bacterial gene expression. Here, we briefly review the role of microRNAs, focuses on their role on immune system components in physiological and pathophysiological gut micro milieu.

Titanium micro-scale topography results in excellent osteoconductivity and bone-implant integration. However, the biological effects of sub-micron topography are unknown. We compared osteoblastic phenotypes and in vivo bone and implant integration abilities between titanium surfaces with micro- (1–5 µm) and sub-micro-scale (0.1–0.5 µm) topographies and machined titanium. Average roughness was 12.5 ± 0.65 nm, 123 ± 6.15 nm, and 24 ± 1.2 nm for machined, micro-rough, and sub-micro-rough surfaces, respectively. The micro-rough surface showed the fewest cells attaching during the initial stage and the lowest proliferation. Calcium deposition and expression of osteoblastic genes were highest on the sub-micro-rough surface and lowest on the machined surface. Bone-to-implant integration was strongest for the micro-rough surface, consistent with it having the greatest ability to retain cells in vitro. Thus, the biological effects of titanium surfaces are not necessarily proportional to the degree of roughness in osteoblastic cultures or in vivo. Sub-micro-rough titanium ameliorates the disadvantage of micro-rough titanium by restoring cell attachment and proliferation and enhances the rate of osteoblastic differentiation over that of micro-rough titanium; however, bone integration and the ability to retain cells are compromised due to its lower interfacial mechanical locking compared to that of micro-rough titanium.

The deployment of a manufacturing execution system (MES) holds promising potential in facilitating the accumulation of a substantial amount of inspection data. Low quality levels in discrete manufacturing environments are the result of multi-factor coupling and failure to find quality issues in a timely manner within manufacturing settings may trigger the propagation of defects downstream. Currently, most of the inspection quality methods are direct measurement followed by manual judgment. The integration of deep learning methods provides a feasible way to identify defects in a timely manner, thus improving the acceptance rate of factories. This paper focuses on the design of a data-driven quality prediction and control model around discrete manufacturing characteristics, and use fuzzy theory to evaluate the quality level of production stages. Building Multivariate Long and short-term memory learning hidden quality representations to extract predictions from multi-level inspection data in manufacturing systems. Finally, by validating the data of actual produced water dispensers according to three evaluation indexes, RMSE, MAE, MAPE, the results show that Multivariate Long and short-term memory has better prediction performance.

This report describes the collection of a large dataset (6930 measurement) on dimensional error in the fused deposition modeling (FDM) additive manufacturing process for full-density parts. Three different print orientations were studied, as well as seven raster angles (0°, 15°, 30°, 45°, 60°, 75°, and 90°) for the rectilinear infill pattern. All measurements were replicated ten times on ten different samples to ensure a comprehensive dataset. Eleven polymer materials were considered: acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), high-temperature PLA, wood-composite PLA, carbon-fiber-composite PLA, copper-composite PLA, aluminum-composite PLA, high-impact polystyrene (HIPS), polyethylene terephthalate glycol-enhanced (PETG), polycarbonate, and synthetic polyamide (nylon). The samples were ASTM-standard impact testing samples, since this geometry allows the measurement of error on three different scales; the nominal dimensions were 3.25mm thick, 63.5mm long, and 12.7mm wide. This dataset is intended to give engineers and product designers a benchmark for judging the accuracy and repeatability of the FDM process for use in manufacturing of end-user products.

The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models based on equations describing the physical laws of the machining processes; however additional efforts are needed to overcome the gap between scientific research and the real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep-knowledge and models” that aid machine designers, production engineers or machinists to get the best of the machine-tools. This article proposes a methodology to reduce problems in machining by means of a simulation utility, which uses the main variables of the system&process as input data, and generates results that help in the proper decision-making and machining planification. Direct benefits can be found in a) the fixture/clamping optimal design, b) the machine tool configuration, c) the definition of chatter-free optimum cutting conditions and d) the right programming of cutting toolpaths at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies and are explained in the paper.

The next future using machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy and reliability. Nowadays, distortion and vibration problems are easily solved for the most common cases by sing models based on equations describing the physical laws dominating the machining process; however additional efforts are needed to overcome the gap between scientific research and the real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep knowledge and models” that aid the machine designer, the production engineer, or machinists to get the best of their machines. This article proposes a systematic methodology to reduce problems in machining by means of a simulation utility, which recognizes, collects and uses the main variables of the system/process as input data, and generates objective results that help in the proper decision-making. Direct benefits by such an application are found in a) the fixture/clamping optimal design, b) the machine tool configuration, c) the definition of chatter free optimum cutting conditions and the right programming of cutting tool path at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies.

In recent years, in addition to the commonly known wire-based processes of Directed Energy Deposition using lasers, a process variant using the electron beam has also developed to industrial market maturity. The process offers particular potential for processing highly conductive, reflective or oxidation-prone materials. However, for industrial usage there is a lack of comprehensive data on performance, process limits and possible applications. The present study deals with this problem using the example of the high-strength aluminum bronze CuAl8Ni6. Multi-stage test welds are used to determine the physically possible process limits and draw conclusions about the suitability of the parameters for additive manufacturing. For this purpose, optimal ranges for energy input, possible welding speeds and the scalability of the process were investigated. Finally, additive test specimens in the form of cylinders and walls are produced and the hardness profile, microstructure and mechanical properties are investigated. It is found that the material CuAl8Ni6 can be well processed by wire electron beam additive manufacturing. The microstructure is similar to a cast structure, the hardness profile over the height of the specimens is constant and the tensile strength and elongation at fracture values achieved correspond to the specification of the raw material.

In recent years, additive manufacturing of products made from 5000 series alloys has grown in popularity for marine and automotive applications. In this work, we compare of mechanical properties characteristics of aluminum alloy 5056 material produced by wire-arc additive technology and rolling. We carried out tension tests under quasi-static loading and impact toughness tests under impact loading. The results show that upon similar ultimate tensile strength and ductility, material after additive manufacturing demonstrates decreased resistance against dynamic loading than material manufactured by the typical method of casting and rolling. This decrease in properties was explained through macro- and microstructure analysis.

There is an intense need to optimize agrivoltaic systems. This article describes the invention of a new testing system: the parametric open source cold-frame agrivoltaic system (POSCAS). POSCAS is an adapted gardening cold-frame used in cold climates as it acts as a small greenhouse for agricultural production. POSCAS is designed to test partially transparent solar photovoltaic (PV) modules targeting the agrivoltaic market. It can both function as a traditional cold frame, but it can also be automated to function as a full-service greenhouse. The integrated PV module roof can be used to power the controls or it can be attached to a microinverter to produce power. POSCAS can be placed in an experimental array for testing, agricultural and power production. It can be easily adapted for any type of partially transparent PV module. An array of POSCAS systems al-lows for testing agrivoltaic impacts from the percent transparency of the modules by varying the thickness of a thin film PV material or the density of silicon-based cells, and various forms of optical enhancement, anti-reflection coatings and solar light spectral shifting materials in the back sheet. All agrivoltaic variables can be customized to identify ideal PV designs for a given agricultural crop.

Background: This study aimed to assess the impact of a nutrition-care bundle on growth and neurodevelopmental outcomes of micro-preterm infants born in a level III neonatal intensive care unit (NICU) by two years corrected age. Methods: A nutrition-care bundle emphasizing the prompt initiation of parenteral nutrition at birth, initiation of enteral feeds within 6 hours after birth, and early addition of human milk fortifiers was implemented in 2015 for infants born <26 weeks gestation. This before-and-after study evaluated growth and neurodevelopmental outcomes in infants born between 2012-2013 (before-nutrition-bundle BNB) and 2016-2017 (after-nutrition-bundle ANB). Results: A total of 145 infants were included in the study. Infants in the ANB group (n=73) were smaller (birthweight and gestational age), and there were more male infants and multiples included compared to the BNB group (n=72). Enteral feeds and fortifiers started earlier in the ANB group. Growth velocity and weight-z-score changes were similar in both groups during NICU stay and post-discharge. Systemic steroid use, but not cohort, was linked to lower Bayley scores across all domains. Conclusions: Implementing a nutrition-care bundle was not consistently associated with improved weight-gain and neurodevelopmental outcomes in the micro-preterm infant population, likely due to ongoing high-quality nutritional care by the clinical team.

It was for long time believed that lidar systems based on the use of high-repetition micro-pulse lasers could be effectively used to only stimulate atmospheric elastic backscatter echoes, and thus only exploited in elastic backscatter lidar systems. Their application to stimulate rotational and roto-vibrational Raman echoes, and consequently their exploitation in atmospheric thermodynamic profiling, was considered not feasible based on the technical specifications possessed by these laser sources until a few years ago. However, recent technological advances in the design and development of micro-pulse lasers, presently achieving high UV average powers (1-5 W) and small divergences (0.3-0.5 mrad), in combination with the use of large aperture telescopes (0.3-0.4 m diameter primary mirrors), allow to presently develop micro-pulse laser-based Raman lidars capable to measure the vertical profiles of atmospheric thermodynamic parameters, namely water vapour and temperature, both in daytime and nighttime. This paper is aimed at demonstrating the feasibility of these measurements and at illustrating and discussing the high achievable performance level, with a specific focus on water vapour profile measurements. The technical solutions identified in the design of the lidar system and their technological implementation within the experimental setup of the lidar prototype are also carefully illustrated and discussed.

Mass transfer is often the rate determining step for solid-liquid chemical reactions. Decrease of the concentration boundary layer thickness is essential to intensify the chemical reaction. Because the concentration boundary layer exists in the velocity boundary layer, force imposition in the concentration boundary layer by superimposing an electrical current and a magnetic field was proposed. Through, flow can be directly excited in the concentration boundary layer. The previous result indicates that by superimposing a DC current and a gradient magnetic field, the development of the concentration boundary layer was suppressed, because of a macro-scale flow excitation in the whole vessel. And by superimposing the gradient magnetic field with a modulate current, the development of the concentration boundary layer was further suppressed. This is because of the macro-scale flow enhancement and the excitation of a micro-scale flow near the solid-liquid interface. However, the mechanism for the micro-scale flow excitation has not been clarified. To clarify this, a uniform magnetic field was superimposed with the DC current or the modulate current. By this means, only the micro-scale flow was excited near the anode surface. The results found that the non-unform electromagnetic force distribution is the main reason for the micro-scale flow excitation.

As the scarcity of potable water increases, recycling of treated wastewater is increasing. Small-scale, decentralized treatment can be implemented to serve local populations by keeping water within their boundaries and within reach for reuse, particularly in less dense, non-urban communities. Availability of cellular networks and high-speed internet connectivity, along with significant reduction in cost, allows ongoing monitoring of decentralized treatment systems at a central location. In this paper a decentralized treatment system using micro nanobubble aeration, moving media and membranes is able to produce reusable water with low energy consumption, thereby allowing the use of solar energy in places with unreliable electrical supply. The treatment system, which uses no external chemicals, is able to operate unattended and deliver clear, disinfected water with non-detect suspended solids, BOD5 less than 10 mg/L and nutrients below 5 mg/L.

Along with the popularity of the Internet, people are exposed to more and more ways of micro-videos, and a huge amount of micro-video data has emerged. micro-videos have gradually become the Internet content preferred by the public, and a large number of micro-video apps have also emerged, such as Tiktok and Kwai. Intelligent classification and mining of micro-videos can greatly enhance user experience, improve business operation efficiency and enhance user experience. Through deep intelligent analysis and mining of micro-videos, important information in micro-videos can be extracted to provide an important basis for beautifying videos, content appreciation, video recommendation, content search, etc. In the past, content understanding for short videos often used human work annotation, but in recent years, with the great success of deep convolutional neural networks in image recognition, short video content understanding based on this method has gradually developed. Nowadays, most recognition algorithms extract the feature representation of each frame independently and then fuse them. However, while extracting the feature representation, some low-level semantic features are lost, which makes the algorithm unable to accurately distinguish the category of the video. At present, the algorithm of micro-video recognition based on deep learning has surpassed the iDT algorithm, making these traditional methods fade out of people’s view. In this paper according to the micro-video classification task, a new network model is proposed to concatenate features of each modality into the overall features of various modalities through the network, and then fuse the various modal features with the attention mechanism to obtain the whole micro-video features, which will be used for classification. In order to verify the effectiveness of the algorithm proposed in this paper, experiments are conducted in the public dataset, and it is shown the effectiveness of our model.

We demonstrate a photonic RF integrator based on an integrated soliton crystal micro-comb source. By multicasting and progressively delaying the input RF signal using a transversal structure, the input RF signal is integrated discretely. Up to 81 wavelengths are provided by the microcomb source, which enable a large integration time window of ~6.8 ns, together with a time resolution as fast as ~84 ps. We perform signal integration of a diverse range of input RF signals including Gaussian pulses with varying time widths, dual pulses with varying time intervals and a square waveform. The experimental results show good agreement with theory. These results verify our microcomb-based integrator as a competitive approach for RF signal integration with high performance and potentially lower cost and footprint.

Under the background that the international technological innovation environment VUCA has been intensifying and the innovation situation of Chinese manufacturing enterprises has been impacted, the innovation dilemma faced by enterprises has attracted increasing attention, while the innovation dilemma is also one of the important factors affecting the operation efficiency of enterprises. Based on the micro-data of China’s A-share manufacturing listed enterprises, this paper empirically analyzes the impact of innovation dilemmas faced by enterprises on operational efficiency (innovation dilemmas are measured by the difference when actual innovation performance is lower than expected innovation performance). The results show that the innovation dilemma of manufacturing enterprises significantly inhibits the operational efficiency of manufacturing enterprises by reducing their risk tolerance, development ability expectation and profitability. After using a series of tests, such as instrumental variable method, propensity score matching method, DID (Differences-in-Differences) and changing variable measure method, the conclusion is still robust. In addition, the inhibitory effect of innovation dilemma on enterprise operation efficiency is more obvious for private enterprises, small and medium-sized enterprises, enterprises in the ascend or decline phase, high-tech enterprises and enterprises in the eastern region. Therefore, the government should strengthen the policy support for the manufacturing enterprises in the innovation dilemma, help the enterprises to overcome the innovation bottleneck. Manufacturing enterprises themselves should enhance their innovation capabilities and strive to get rid of the innovation dilemma in order to maintain a stable footing in the fierce market competition and improve the high-quality development of China’s manufacturing industry.

Additive manufacturing, commonly referred to as 3D printing, is an exciting and versatile manufacturing technology that is gaining traction and interest in both academic and industrial settings. Polymeric materials are essential components in a majority of the “inks” used across the various 3D printing technologies. As the environmental ramifications of sole or primary reliance on petrochemicals as a resource for industrial polymers continue to manifest themselves at a global scale, a transition to more sustainable bioderived alternatives could offer solutions. In particular, cellulose is promising due to its global abundance, biodegradability, excellent thermal and mechanical properties, and ability to be chemically modified to suit various applications. Thus far, cellulose has typically been incorporated in additive manufacturing applications as a substrate, filler, or reinforcement for other materials. However, due to its versatility and desirable properties, the exploration of all-cellulose 3D printing materials and associated methodologies is increasing. This review will discuss the progress and status of all-cellulose 3D printing approaches, associated challenges, and their potential as a key player in a more sustainable industrial future.

In the realm of smart manufacturing, equipment plays a pivotal role, impacting the efficiency and quality of production. Ensuring equipment availability and optimal performance is crucial, necessitating effective maintenance strategies. This paper addresses the complexities of smart device maintenance, which often involves collaboration between multiple entities like device owners, manufacturers, suppliers, and external maintenance services. To enhance this cooperative maintenance, we propose a novel maintenance system based on permissioned blockchain technology, offering superior security and reliability compared to conventional cloud-based platforms. Our contributions include developing an integrated maintenance system framework for smart manufacturing, which facilitates interactions among diverse stakeholders. Additionally, we have developed a prototype of this maintenance system, serving as a practical model for real-world application. Our research primarily demonstrates the practicality and advantages of using permissioned blockchain for maintenance systems in the manufacturing sector, paving the way for more secure, efficient, and collaborative maintenance practices.

The paper delves into an extensive exploration of the integration of the circular economy paradigm within the realm of additive manufacturing (AM). The objective is to comprehensively investigate existing methodologies for structuring the symbiotic relationship between circular economy and additive manufacturing, while meticulously analyzing the current research gap concerning the implementation of circular economy principles in additive manufacturing practices. A thorough review focusing on the sustainability of additive manufacturing within the circular economy framework was conducted. This review aims to recognize and delineate pertinent aspects related to post-use material valuation in AM, recyclability of materials, and the environmental footprint associated with these processes. Emphasis was placed on the significance of examining circular economy facets concerning additive manufacturing processes to establish a holistic understanding. The overarching goal of this review is to augment knowledge regarding the potential advantages and benefits derived from the seamless integration of circular economy principles within AM. By elucidating the activities essential to attain compliance with the Sustainable Development Goals, this study endeavors to illuminate the pathway toward promoting sustainable development through the harmonious marriage of additive manufacturing and the circular economy.

The rapid market changes and strong product individualization create the need for great flexibility of manufacturing management on new foundations, such as the Industry 4.0 model. Digital manufacturing is the basis for Industry 4.0, that have the following dimensions: (i) digital manufacturing based on advanced digital-oriented technologies, (ii) smart products (advanced manufacturing mode and new characteristics), and (iii) smart supply - chain (procurement of raw materials and delivery of finished products). Bidirectional exchange of information in collaborative manufacturing, using it exchange also for digital platforms of design of the innovative products. In this paper we are showing developed model of one Serbian digital factory model for Quality 4.0 (Q 4.0) , especially in workshop as a part of ERP/MES model.

Sustainability is the core concern of every business; The exploration of avenues to maintain sustainability while staying competitive with high level of productivity remains a vital endeavor. Production flexibility is a key area that can enhance the sustainability of manufacturing industries as it can ensure product availability, scalability, agility/fault tolerance as well as disaster recovery potentials. Technological advancements have provided avenues where companies can enhance virtually all aspects of their operations for efficiency, effectiveness, and productivity. This paper uses both quantitative and qualitative research approach to identify the capability requirements for smart and effective production management and subsequent analysis is done using Multi-Criteria Decision-Making methodology to identify and rank various industry 4.0 technologies and concepts that can provide these smart capabilities in in manufacturing industries to aid the businesses to achieve sustainability with production flexibility. The paper identifies over 12 smart capabilities and 9 Industry 4.0 Technologies which are applicable to production management. It also compares results from the analytics of historical I4.0 implementation as discussed in literatures with the current state as deduces from survey feedbacks from various manufacturing industries.

Over the last decade, a significant literature has emerged that advocates the potential of different Additive manufacturing (AM) technologies and printable polymeric materials. Nevertheless, large scale printing and complex geometric shapes, with curvatures and non-planar layer deposition, are a challenging process for the traditional gantry-based machine. The 3 degrees of freedom cartesian configuration restricted their capability to planar layered printing and restricted part dimensions. To date, many researchers have used industrial robots to overcomes this limitation. This review gives the reader a good overview of the FDM technique due to its scalability, cost efficiency and a wide range of material printability. A strong emphasis is laid on the PLA and PLA-based composites as promising materials for the FDM process applications. The second part of this paper links the successful use of these materials in the traditional printing process to large scale printing using the robot-based FDM process. This survey presents representative setups for robot-based AM and works that have been used these setups for non-planar material deposition. Finally, we conclude this paper by identifying opportunities for realizing new functional capabilities by exploiting robot-based AM, and we also present the future trends in this area.

This study explores the potential to reach a circular economy for post-consumer recycled polyethylene terephthalate (rPET) packaging and bottles by using it as a distributed recycling for additive manufacturing (DRAM) feedstock. Specifically, rPET is processed using only an open source toolchain with fused particle fabrication (FPF) or fused granular fabrication (FGF) processing. In this study, first the impact of granulation, sifting and heating (and their combination) is quantified on the shape and size distribution of the rPET flakes. Then feeding studies were performed to see if they could be printed through an external feeder or needed to be direct printed with a hopper using two Gigabot X machines, one with extended part cooling and one without. Print settings were optimized based on thermal characterization and for the latter which was shown to print rPET directly from shredded water bottles mechanical testing is performed. The results showed that geometry was important for extended feeding tubes and direct printed using a hopper. Further there is a wide disparity in the physical properties of rPET from water bottles depending on source and the history of the material. Future work is needed to enable water bottles to be used as a widespread DRAM feedstock.

Abstract: Due to sever land degradation throughout Ethiopia, the government has been implementing massive soil and water conservation works at the watershed scale since 2010 to conserve soil and water resources. However, most of the rivers in Ethiopia carry huge amount of sediment in the rainy season and streams dried up in the dry period. Planned research was conducted on two paired micro-catchments of Mt.Yewel with the main objective of evaluating the impact of soil and water conservation measures on base flow modification. Stream flow and rainfall data were collected from 22/11/2020 to 8/11/2022 on both micro-catchments at their outlets and center respectively. Base flow separation was done using Sp. Hydro base flow separation tool and SPSS Ver.21 statistical software was employed for data analysis. Flow duration curve (FDC) for both watersheds were developed. The FDC indicated that the base flow from treated micro-catchment is higher and sustained in the dry season while it is low and un-sustained in untreated micro-catchment. From statistical analysis, there is a significant difference in base flow enhancement between the treated and untreated micro-catchment (P<0.001). Hence, catchment treatment contributed to improve groundwater recharge and sustain base flow in the dry season by reducing surface runoff during rainy season.

Abstract: Due to sever land degradation throughout Ethiopia, the government has been implementing massive soil and water conservation works at the watershed scale since 2010 to conserve soil and water resources. However, most of the rivers in Ethiopia carry huge amount of sediment in rainy season and streams dried up in the dry period. Planned research was conducted on two paired micro-catchments Mt.Yewel with the main objective of evaluating the impact of soil and water conservation measures on base flow modification. Stream flow and rainfall data were collected from 22/11/2020 to 8/11/2022 on both micro-catchments at their outlets and center respectively. Base flow separation was done using Sp. Hydro base flow separation tool and SPSS Ver.21 statistical software was employed for data analysis. Flow duration curve (FDC) for both watersheds were developed. The FDC indicated that the base flow from treated micro-catchment ishigher and sustained in the dry season while it is low and un-sustained in untreated micro-catchment. From statistical analysis, there is a significant difference in base flow enhancement between the treated and untreated micro-catchment (P<0.001). Hence, catchment treatment contributed to improve groundwater recharge and sustain base flow in the dry season by reduce surface runoff during rainy season.

Evaluating soil quality across various altitudinal gradients, both with and without vegetative cover, is crucial for the proper functioning of soil and optimal crop growth, thereby contributing to the sustainability of agroecosystems. Although the altitudinal gradient significantly influences soil quality, the ability to predict this quality, expressed through an index, in soils with and without vegetative cover, is still insufficiently explored. This study aimed to assess soil quality in the Jun Jun micro-watershed, located in the Tungurahua region, Ecuador. To achieve this objective, three categories of altitudinal gradients were selected: less than 2800 meters above sea level (masl), between 2800 and 2900 masl, and greater than 2900 masl. A total of 24 soil samples were collected in the mentioned gradients, considering both areas with and without vegetative cover. The indicators used included chemical and biological parameters such as soil organic carbon (OC), earthworm density (WD), earthworm biomass (WB), organic matter (OM), pH, total nitrogen (TN), and organic carbon (OC). The results revealed that in areas with altitudinal gradients below 2800 masl, soil quality index values were higher compared to other altitudes. In vegetated areas, a decrease in index values was observed as the altitudinal gradient increased, indicating a deterioration in soil quality with altitude. These findings are significant in providing a quantitative assessment of the effects of altitudinal gradient and vegetative cover influence on soil quality.

Motivated by the increasing need of optimised micro-devices for droplets production in medical and biological applications, this paper introduces an integrated approach for the study of the liquid-liquid droplet creation in flow-focusing micro cross-junctions. The micro-junction considered is characterised by a restriction of the channels cross-sections in the junction, which has the function of focusing the flow in the region of the droplet formation. The problem is studied numerically in OpenFOAM environment and validated by the comparison with experimental results obtained by high-speed camera images and micro-PIV measurements. The analysis of the forces acting on the dispersed phase during the droplet formation and the diameter of the droplets obtained numerically are considered for the development of a model of the droplet breakup under the squeezing regime. On the basis of energy balancing during the breakup, a relation between interfacial tension, the size of the cross-sections in the junction, and the time interval needed for droplet creation is obtained, which yields a novel correlation between the dimensionless length of the droplet and the dimensionless flow rate. This correlation is general and can be used to predict the droplet diameters produced by similar micro-junctions with different aspect ratios and extended to different geometries of flow-focusing micro-junctions.

A recent study reported that micro-osteoperforations (MOPs) accelerated tooth movement by activating alveolar bone remodeling. However, very little is known about the relationship between MOPs and external apical root resorption during orthodontic treatment. In this study, in order to investigate the mechanism which MOPs accelerate tooth movement without exacerbating the progression of root resorption, we measured the volume of resorbed root, and performed the immunostaining for the terminal deoxynucleotidyl transferase (TdT)-mediated dUTP-biotin nick-end-labelling method (TUNEL) exposed MOPs during rat experimental tooth movement. Male Wistar rats (11 week old) were divided into 3 groups: 10-g orthodontic force (optimal force) applied to the maxillary first molar (optimal force: OF group), 50-g orthodontic force application (heavy force: HF group) and 10-g force application plus 3 small perforations of the cortical plate (OF+MOPs group). On days 1, 4, 7, 10 and 14 after force application, the tooth movement and root volume were investigated by micro-computed tomography. Furthermore, the expression levels of apoptotic cells in pressure sides of periodontal ligament (PDL) and surround hard tissues were determined by TUNEL staining. The OF+MOP group exhibited a 1.8-fold increase in tooth movement on days 7, 10 and 14 compared with the OF group. On days 14, the HF group had a higher volume of root loss than the OF and OF+MOP groups. On the same day, the number of TUNEL-positive cells in the HF group increased at the root (cementum) site whereas that in the OF group increased at the alveolar bone site. Furthermore, that in the OF + MOP group increased at the alveolar bone site compared with the OF group. These results suggest that MOPs accelerate orthodontic tooth movement without exacerbating the progression of root resorption.

This research was aimed to apply probiotics in aquaculture to improve fish health and growth performances of Nile tilapia. Fingerlings with a mean initial body weight of 11.43±1.27 and mean initial body length of 6.2±0.84 were stocked in 12 happas. Fish were fed four times daily with four different diets having 30% crude protein at 5% of their body weight and reared for two months. The four diets were control diet, diets treated with Saccharomyces cervisiae, Lactobacillus fermentum and their combinations at a dosage of (1.5×108CFU/ml). Growth performance and gut pathogenic microbial of fish were investigated. Accordingly results indicated that the highest performance interims of body weight gain (33.43±1.65g), daily growth rate (0.51±0.05g), feed conversion ratio (1.89±0.10), and protein efficiency ratio (1.78±0.09) was achieved in fish fed with L. fermentum whereas, the lowest performance (19.83±2.23, 0.33±0.04, 3.52±0.39, and 0.97±0.11) respectively was achieved in fish fed with control diet. Salmonella, Shigella, E. coli and, Proteus were detected in gut of fish. In conclusion, the present study confirmed that Nile tilapia fed with probiotics Lac-tobacillus fermentum and Saccharomyces cerevisiae based diets improved growth and health of Nile tilapia reared under pond culture condition.

Both the use of plastic and its decomposition products lead to the distribution of plastic all over the earth and finally to the uptake by all kind of living beings including humans. Still, it is widely unknown what risks harbor the widespread uptake of plastics for human health, espe-cially regarding contributing factors like size, shape and surface composition. We assessed the uptake of polymethylmethacrylate (PMMA)-nano- and microbeads for HEK293-, A549- and MRC5 cells. Via confocal microscopy, we localized multiple PMMA-beads inside the cytosol of cells. Uptake of PMMA-beads did not alter cell growth and cell division, implying no short-term toxicity towards human cells. Further, we used a cAMP response element binding protein (CREB)-mediated reporter assay to assess whether internalized PMMA-nanobeads alter cell-signaling pathways. In contrast to the in vitro transcription, where the addition of PMMA-nanobeads abolished the transcription, no changes regarding CREB-mediated cell sig-naling are given in HEK293-cells. Our data led to the assumption that PMMA-nano-and mi-crobeads are internalized via endocytosis and end up as lysosomes within the cells cytosol. Therefore, we concluded differences regarding the surface composition of the PMMA-nanobeads mainly affect its potential to alter cell signaling. These findings emphasize the key role the sur-face composition plays regarding microplastic and its risks for human health.

This study aims to formulate binary cementitious systems containing silica fume (SF) and micro quartz (MQ) to improve cementitious concrete's durability and mechanical properties. In this investigation, we examined the effects of different essential variables, such as the level of SF and MQ replacement and the ratio of the water-binder (w/b). In this study, the w/b ratios were 0.25, 0.3, 0.35, and 0.4. Replacement levels for SF were 8, 10, and 12%, while replacement levels for MQ were 5, 8, 10, 15, 25, and 35%. The porosity and permeability decreased with an increase in replacement levels, regardless of the type of fine material used or the amount of replacement. Meanwhile, the strength increased markedly with SF replacement, reaching its maximum MQ of 25% at the SF level. The strength of the SF mixing was the highest in all mixes, and it remained the highest until 15% of MQ was replaced. The ultrafine size of MQ particles contributes to the improvement of compressive strength, porosity, and permeability in a similar way to SF particles, despite their high crystalline structure. Furthermore, in this study, analysis of variance (ANOVA) was employed to verify the influence of each variable on the studied response.

Abstract: Autophagy has a dual role in gliomagenesis in a microRNA-modulated environment. We investigated the potential relevance of autophagy in glioma development and survival by exploring the association of autophagy-associated genes and microRNAs in low- and high-grade gliomas. Real-time PCR (qPCR) was used to determine the expression of genes and microRNAs in 50 fresh glioma tissues while Formalin-fixed paraf-fin-embedded tissues of the same patients were used for immunohistochemistry. The Mann-Whitney U-test test, Spearman correlation test, and Kaplan-Meier survival analysis were performed to evaluate the expression, association, and overall survival in patients respectively. The expression of LC3, AKT, and miR-21 was increased in high-grade glioma compared to low-grade glioma while ULK2 expression was decreased in high-grade glioma. A strong positive correlation was observed for ULK2 with UVRAG, PTEN, miR-7, and miR-100, while the moderate correlation with mTOR, Beclin1, miR-30, miR-204, miR-374, miR-21 and miR-126 in low-grade glioma, while a moderate positive correlation between ULK2 and PI3K, PTEN, ULK1, VPS34, mTOR, Beclin1, UVRAG, AKT and miR-374, and between AKT and ULK1, VPS34, UVRAG, and miR-7 in high-grade gliomas. The low ULK2 and LC3 expression group was significantly associated with better overall survival in gliomas while miR-21 overexpression showed a poor prognosis in glioma patients. Therefore, miR-21, ULK2, and LC3 may serve as prognostic biomarkers for survival outcomes in glioblastoma.

Broadband noise reduction over the low-mid frequency range in the building and transportation sectors requires compact lightweight sound absorbers of typical sub-wavelength size. The use of multi-layered closely-spaced (micro-)perforated membranes or panels, if suitably optimized, contribute to these objectives. However, their elasticity or modal behaviors often impede the final acoustical performance of the partition. The objective of this study is to get insights into the vibrational effects induced by elastic limp membranes or panels volumetric modes on the optimized sound absorption properties of acoustic fishnets and functionally-graded partitions (FGP). Cost-efficient global optimization of the partition total frequency-averaged dissipation is achieved from simulated annealing with vibrational effects included through an impedance translation method. Critical coupling analysis reveals how the membranes or panels vibrations redistribute the locations of the Hole-Cavity resonances as well as their cross-coupling with the panels first volumetric mode. It is found that elastic limp micro-perforated membranes broaden the first pass-band of acoustic fishnets while smoothing out the dissipation ripples over the FGP optimiza-tion bandwidth. Moreover, the resonance frequency of the first panels mode sets an upper limit to the broadband optimization of FGPs, up to which high dissipation, low reflection and low trans-mission can be achieved.

Magnesium ions play an important immune-regulatory role during bone repair. For this study, we prepared micro-nano bioactive glass containing magnesium, which can release magnesium, silicon, and calcium ions and has a positive impact on osteogenic differentiation and vascular regeneration. In this study, MgMNBG was compounded and combined with PLGA and PCL for 3D printing. Afterwards, the physicochemical properties and bone repair performance of the scaffolds were evaluated through in vitro and in vivo experiments. We also investigated the effects of MgMNBG on osteogenic differentiation, immune regulation, and vascular regeneration. The results showed that MgMNBG can inhibit inflammation and promote osteogenesis and angiogenesis by regulating macrophages. PLGA/PCL/MgMNBG scaffolds have good osteogenic and angiogenic effects, and the composite scaffolds have excellent bone repair performance and potential application value.

Aluminum alloy (Al6061) sheet micro-hole processing is extensively used in smartphones, tablet PC, and smart wearable devices. The micro-hole processing is commonly performed using laser, micro drilling, microstamping, micro discharge, and chemical etching technologies. Micro-stamping technology is characterized by precision and rapid processing, but the precision positioning of the punch head and lower die is one of the major difficulties in micro-hole stamping, especially in manufacturing array micro-holes. This study used stamping without die technology. This technology uses an array punch head to punch the lower die holes on the base, then performs array micro-hole stamping. The experimental results show that a micro-hole array with 37 micro-holes were successfully manufactured and can be reproduced many times. Tapered array micro-holes with a high aspect ratio can be manufactured using this stamping without die technology; the micro-hole depth can be 260μm, the inlet diameter is 116μm, and the outlet diameter is 25μm. This study has successfully developed the feasibility of array micro-hole stamping technology.

This study evaluated the efficacy of experimental TEGDMA-functionalized dicalcium phosphate dihydrate (T-DCPD) filler-based resin-based composites (RBC) in preventing caries lesions around the restoration margins (secondary caries”, SC). Standardized Class-II cavities were made in sound molars having the cervical margin in dentin. Cavities were filled with a commercial resin-modified glass-ionomer cement (RMGIC) or experimental RBCs containing a BisGMA-TEGDMA resin blend and one of the following inorganic fractions: 60 wt.% Ba glass (RBC-0); 40 wt.% Ba glass, 20 wt.% T-DCPD (RBC-20); 20 wt.% Ba glass, 40 wt.% T-DCPD (RBC-40). An open-system bioreactor produced S. mutans biofilm-driven SC. Specimens were scanned using micro-CT to evaluate demineralization depths. Scanning Electron Microscopy and Energy-dispersive X-ray Spectroscopy characterized the specimens’ surfaces, while antimicrobial activity, buffering effect, and ion uptake by the biofilms were also evaluated. ANOVA and Tukey’s test were applied at p<0.05. RBC-0 and RBC-20 showed SC development in dentin, while RBC-40 and RMGIC significantly reduced the lesion depth at the restoration margin (p<0.0001). Initial enamel demineralization could be observed only around RBC-0 and RBC-20 restorations. A direct antibiofilm activity could explain SC reduction by RMGIC, while a buffering effect on biofilm’s acidogenicity explained the behavior of RBC-40. Experimental RBC with CaP-releasing functionalized T-DCPD filler could prevent SC with the same efficacy as F-releasing materials.

This research was carried out with the objective of analyzing the principles of social and solidarity economy in the community funds of the rural sector of Pichincha, Ecuador. Small organizations promote microcredits for local, social and economic development, representing an alternative to those managed by traditional banks. The research was descriptive, non-experimental field research. The population analyzed consisted of 220 community funds, and the size of the representative sample was 49 community organizations that practice solidarity finance. The data were collected through online questionnaires using a Likert scale, and the validity of this approach was judged by experts; the reliability of the instrument obtained was 0.95 using the Cronbach’s alpha method. The results highlight that in these organizations, the following traits prevail: associativity, self-management and organization. However, autonomy and solidarity have a negative valuation, which shows that strategies must be rethought to achieve the empowerment of the financial service. This will allow them to be sustainable and to expand with more benefits that promulgate financial activity and promote structures in rural community networks that promote local development and strengthen deficient principles as a basis for generating a greater benefit to the partners.

Excitation of the acoustic field leading to the Blaha effect affects the plasticity of the material significantly in ultrasonic vibration-assisted forming. In a micro-forming field, the effects are more significant in the deformation in surface of materials [1]-[3], in which reduction of the surface roughness based on the increasing of plastic deformation of surface asperity was effective [4]. On the other hand, the effect on deformation behavior of the bulk region indicted reduction in the yield stress of materials, and not only acoustic effect [5], but also impact effect is found to generate a large amount of dislocation and produce plastic deformation [6][7]. However, the effect on the bulk is more significant as that on the surface. Differences in the effect on the surface and the bulk are not clarified. In this study, the mechanism of the deformation in the surface of the material with ultrasonic vibration assistance is investigated and compared with that in the bulk. Forging tests using a newly developed ultrasonic vibrator were carried out on pure Cu foils with various process conditions. The longitudinal vibration frequency of the ultrasonic transducer is 60∓2kHz, and the vibration amplitude is in an adjustable range of 0~10μm. Forging test was carried out at different initial stress, specimen size and amplitude. The difference in acoustic softening and impact effects on the surface and the bulk was discussed.

The rapid growth of the Information and Communications Technology (ICT) sector requires additional infrastructure, such as more micro-datacenters and telecom stations, to support the higher internet speeds and low latency requirements of 5G net-works. The increased power requirements of the new ICT technologies necessitate the proposal of new power supplies in an attempt to retain the increase in energy demand and running costs. This work provides an in-depth theoretical analysis on the losses of the individual stages of commercially available PSU and proposes a new multicell PSU, Buck-PFC converter, which offers a higher overall efficiency at varying load levels. The theoretical results are verified using simulation results, via PSIM Thermal Module, and using experimental data. The results indicate that multi-cell structures can improve the overall PSU ef-ficiency by 1.2% at 50% rated power and more than 2.1% at full power. Finally, taking into consideration the economic implica-tions of this study, it is shown that the proposed multicell structure may increase the PSU costs by 10.78% but the payback pe-riod is in the order of just 3.3 years.

Substantial research is required to ensure that micro-mobility ride sharing provides a better fulfillment of user needs. This study proposes a novel crowdsourcing model for the ride-sharing system where light vehicles such as scooters and bikes are crowdsourced. The proposed model consists of three entities: suppliers, customers, and a management party responsible for receiving, renting, booking, and demand matching with offered resources. It can allow suppliers to define the location of their private e-scooters/e-bikes and the period of time they are available for rent. Using a dataset of over 9 million e-scooter trips in Austin, Texas, we ran an agent-based simulation six times using three maximum battery ranges (i.e., 35, 45, and 60 km) and different numbers of e-scooters (e.g., 50 and 100) at each origin. Computational results show that the proposed model is promising and might be advantageous to shift the charging and maintenance efforts to a crowd of suppliers.

Minerals play many important functions in plant and animal metabolism. Therefore, we investigated the concentration of Se and other minerals and their relationships in soils and fodder plants in Kosovo. Seventy-three samples of each soil and fodder plants (grass, maize, and wheat) from 30 farms were collected. Both soil and plant samples, after processing and digestion, were analyzed for mineral concentration by ICP-MS. Mineral concentrations in soil and fodder crops, and the best predicting/explanatory models for micro minerals concentration, achieved by stepwise linear regression, are presented. Results showed very low concentration of Se in most of the soil and all fodder samples. In addition, the concentration of Co, Zn and Fe was not sufficient to satisfy requirements for all categories of farm animals. Plant Se concentration showed a positive relationship with Se concentration in soils. Plant Zn, Mo, Mn, Fe and Pb, in general, showed no significant relationship with their concentration in soil, while plant Co and Cd showed positive relationship only in maize, and Cu in wheat grain. Among the soil properties, pH had the highest effect on the concentrations of Co, Mo, Mn, Cd and Pb in fodder crops.

A phosphate/molybdate and cerium-modified phosphate/molybdate conversion coatings were deposited on a carbon steel surface and their protective and self-healing abilities were evaluated. Surface morphology and inner structure of the coatings were examined using FE-SEM-FIB and TEM techniques, chemical composition and element distribution depth profiles in conversion layers were determined using EDX measurements, whereas XPS was applied for the analysis of Mo and Ce oxidation states. Voltammetric measurements and EIS were performed to assess the corrosion behavior of the samples. The higher protective and stronger self-healing abilities were found for phosphate/molybdate/cerium conversion coating deposited in a sulphate-containing solution. This was attributed to higher values of both: total cerium and Ce(IV) content in the conversion layer as well as to lower number of structural defects in the coating. It was demonstrated that the micro-structural characteristics of protective coatings are also important in determining self-healing abilities.

Biological micro-dissection has a wide range of applications in the field of molecular pathology. The current laser-assisted dissection technology is expensive, and laser radiation can lead to sample contamination. As an economical and pollution-free micro-dissection method, piezoelectric ultrasonic micro-dissection has a wide application prospect. However, the performance of the current piezoelectric ultrasonic micro-dissection technology is unsatisfactory. In this paper, a novel piezoelectric ultrasonic micro-dissection device based on a flexure mechanism is proposed in order to solve the problems of low dissecting precision and excessive wear of the dissecting needle caused by the harmful lateral vibration of the current piezoelectric ultrasonic micro-dissection device. By analyzing the flexibility of flexure hinge, the type of flexure beam and the optimal design parameters are determined. Through comparing the harmonic response simulation analysis of the micro-dissection device based on a flexure mechanism and the traditional micro-dissection device without the flexure mechanism, the newly designed micro-dissection device achieves the best vibration effect when the driving frequency is 28kHz, compared with the traditional micro-dissection device, the lateral vibration suppression effect is improved by 68%. Then, based on the 3D printing technology, a prototype of a novel micro-dissection device was produced, and its performance was tested. It was found that the flexure mechanism did indeed suppress the lateral vibration of the needle tip. Finally, the experiments of 5μm thick paraffin-embedded rat liver sections were carried out, and the effects of different dissecting parameters on the dissecting effect were analyzed, and the optimal dissecting parameters were obtained. By comparing the dissecting effects of the tissue sample and the wear condition of the needle tip between the novel micro-dissection device and the traditional micro-dissection device under their optimal dissecting parameters, it is proved that the suppression of harmful lateral vibration not only significantly improves the dissecting effect, but also improves the service life and durability of the dissecting needle, which is beneficial to reduce the equipment costs.

The flipped classroom is gaining prominence as an active learning pedagogy to engage a new generation of students. However, all courses do not lend themselves to a fully flipped design and instructors are often reluctant to flip lectures. In this study, I experimented with a “partial” flipped classroom design in a first-year undergraduate economics course. In this partial flipped format, traditional lectures were substituted with micro-lectures and the remaining class time was devoted to activities like quizzes, group work and student presentations. The full lectures were panopto recorded and put up on the e-learning site, Blackboard. This format enabled me to combine the benefits of a traditional lecture with a flipped classroom design. In order to evaluate the effectiveness of the partial flipped classroom format, I compared the final exam scores of students in the partial flipped classroom with those in the control group, which followed a traditional lecture-based approach. The key results from the analysis revealed that students in the partial flipped classroom performed better in the final exams vis-à-vis students in the traditional classroom format. Furthermore, the partial flipped classroom format was associated with lower odds of students failing in the module. This format also resulted in better student engagement, more flexibility and enhanced student-tutor interaction within the classroom.

The Neotropical region is one of the most diverse regions of the globe in terms of macro-organismic species. Regarding the microbial world, however, little is known about the diversity and biogeography patterns of micro-organisms in the Neotropics. In this context, the study of several microbial taxonomic groups is still missing and/or incomplete, such as the protists. Our goal here was to summarize the available information of Neotropical protists, focusing on molecular data from environmental continental samples, to explore what these data evidence on their ecology and biogeography. For this, we reviewed the findings from all articles that focused on or included the terrestrial protists using metabarcoding approach and identified the gaps and future perspectives in this research field. We found that Neotropical protists diversity patterns seem to be, at least in part, congruent with that of macro-organisms and, different than plants and bacteria, just weakly explained by environmental variables. We argue that studies with standardized protocols including different biomes are necessary to fully characterize the ecology and biogeography on Neotropical protists. Furthermore, dismember evolutionary lineages and functional guilds of protists are important to better understand the relationship between diversity, dispersal abilities and functionality of particular taxa of protists in their habitats.

The evolution of metals micro/nano-structure upon severe plastic deformation (SPD) is still far to be theoretically explained, while experimental datasets are persistently growing for several decades. Major problem associated with understanding of SPD is related to a fact that the latter is a synergetic product of several competing physical effects which alter the material micro/nano-structure. In attempt to find deformational boundaries, where predominantly one mechanism determines the micro/nano-structure, in this paper we propose a continuous piecewise model for the analysis of experiments on material hardness vs strain of SPD processed materials. The novelty of this approach lies in its ability to find, as free-fitting parameters, the strain breakpoints which separate different micro/nano-structure modes generated upon SPD process. The model is applied to analyse experimental data for polycrystalline samples of pure iron and two distinctive strain breakpoints are revealed with good accuracies. This finding is in a good agreement with our earlier results on TEM microscopy studies on pure iron polycrystals after SPD treatment.

This study evaluated the mechanical strengths of three types of orthodontic micro-implants by analyzing their structural configurations. Thirty micro-implants of three types (diameter 1.5 mm, Types A, B, C) were assessed. All micro-implants were manually driven into artificial bones at an 8-mm depth. The insertion torque (IT), pullout strength (PS), and gripping volume (GV) of each type were measured. Intergroup comparisons and intragroup correlation were investigated by statistical analysis. Type B had the greatest inner–outer diameter ratio (0.67), and Type A had the smallest (0.53). The IT of Type A (5.26 Ncm) was significantly (p = 0.038) lower than that of Type C (8.8 Ncm). There was no significant difference in the pullout strength (p = 0.868). The GV of Type A (9.7 mm3) was significant (p < 0.01) greater than Type C (8.4 mm3). Type C was significant (p < 0.01) greater than Type B (7.2 mm3). Spearman’s rho rank correlation test showed that PS of Type B was correlated significantly with GV. In conclusion, the design of thread and its GV were the important factors on the mechanical strengths of micro-implant.