The DIY 3D printing community has passion and dedication for making solid objects from digital models. Recently, we have noticed electronics projects integrated with 3D printed enclosures, brackets, and sculptures, so each Thursday we celebrate and highlight these bold pioneers! Have you considered building a 3D project around an Arduino or other microcontroller? How about printing a bracket to mount your Raspberry Pi to the back of your HD monitor? And don't forget the countless LED projects that are possible when you are modeling your projects in 3D!

It just got a little easier to create soft robots that adapt to the world around them. Rice University researchers have developed a 3D printing technique (they call it "4D") for material that automatically changes to an alternate shape when subjected to an electric current, changes in temperature or simple stress. The team produced a liquid crystal polymer'ink' with two exclusive sets of molecular links -- one with the originally printed shape, and another by manipulating the material. In this case, scientists just had to heat or cool the material to flip it between a flat surface and a bumpy one, among other changes. The challenge was to craft a polymer mix that could be printed in a catalyst bath without losing its shape, Rice said.

Here at Crendon Insurance Ltd we often cover topics on 3D printing and artificial intelligence. Reporting on the progress of the 3D printing industry and how it is modernising many sectors including manufacturing, construction and automotive has taken our interest for some years now. Whilst in addition, over more recent months, we have begun highlighting the expansion of AI (artificial intelligence) and how it too, is changing the way in which humans will engage with products of the future. Over the last few years, 3D printing has demonstrated as real'gamechanger' in the world of manufacturing. Offering the ability to produce several copies of the same component at a much lower cost, cutting out the middle man to save transportation cost and time and allowing new and innovative entrepreneurs to realise their designs more independently by installing much lower cost 3D printers on-site, has provided just some of the benefits to the growth of the 3D printing industry.

Industry 4.0, or the fourth industrial revolution, has called for a merger between automated solutions and smarter, more effective operations through the application of real-time data collection. Essentially, IoT and data-based technologies will feed real-time content into an AI platform, which will then use machine learning algorithms to analyze and extract actionable insights. Beyond that, the data solutions may support additional power systems by controlling robots or informing various processes to influence output. In other words, machine learning and AI allow for a degree of autonomy in the field like never seen before. While they are incredibly promising technologies, they're still relatively new to the industry, which means manufacturers are looking for fresh and innovative ways to apply them.

An object can be replicated by creating its 3D model and then using a 3D printer. Another important application can be found in manufacturing industries for inspection purposes. Minute cracks, faults or problems can be detected easily by comparing the reconstructed 3D model with the known model. Simultaneous Localization and Mapping (SLAM): SLAM is a technique used to create map of the surrounding environment. It is very useful in robotics and self-driving cars.

Dimensionality reduction is the process of expressing high-dimensional data in a reduced number of dimensions such that each one contains the most amount of information. Dimensionality reduction may be used for visualization of high-dimensional data or to speed up machine learning models by removing low-information or correlated features. Principal Component Analysis, or PCA, is a popular method of reducing the dimensionality of data by drawing several orthogonal (perpendicular) vectors in the feature space to represent the reduced number of dimensions. The variable number represents the number of dimensions the reduced data will have. In the case of visualization, for example, it would be two dimensions.

The popular show'Black Mirror' may be on hold due to the pandemic spreading across the globe, but fans of the dystopian world can create a part of the sci-fi series on their own. A Stanford student built a robot dog similar to that used in the episode titled'Metalhead' that hunts and kills humans in an apocalyptic setting. The miniature version, called the Stanford Pupper, was developed using a 3D printer, a PlayStation controller and other common pieces - and the team has shared all the details for the public to use. It has 12 degrees of freedom, meaning it can goes backwards, forwards, side-to-side and also features a'sneaky mode' that mimics the movement of a real canine creeping on the floor. A Stanford student built a robot dog similar to that used in the episode titled'Metalhead' that hunts and kills humans in an apocalyptic setting.

An injured hornbill that was found in Thailand with part of its beak snapped off can now eat again after vets fitted it with a replacement made using a 3D printer. The adult bird -- dubbed'Coco' -- was found sprawled on the ground with a broken wing and its lower bill missing in Kanchanaburi, western Thailand, on April 18. Wildlife officers are unsure how Coco was injured, but believe that she may have been shot or attacked by hunters or poachers and then left for dead in the forest. Although veterinarians were able to give urgent care and stabilise the bird, they were sadly unable to find its missing bill in order to reattach it. Realising it would be impossible for Coco to eat without her signature long bill, they scanned her body and used 3D printing technology to create plastic replacements.

Increasing the penetration of variable generation has a substantial effect on the operational reliability of power systems. The higher level of uncertainty that stems from this variability makes it more difficult to determine whether a given operating condition will be secure or insecure. Data-driven techniques provide a promising way to identify security rules that can be embedded in economic dispatch model to keep power system operating states secure. This paper proposes using a sparse weighted oblique decision tree to learn accurate, understandable, and embeddable security rules that are linear and can be extracted as sparse matrices using a recursive algorithm. These matrices can then be easily embedded as security constraints in power system economic dispatch calculations using the Big-M method. Tests on several large datasets with high renewable energy penetration demonstrate the effectiveness of the proposed method. In particular, the sparse weighted oblique decision tree outperforms the state-of-art weighted oblique decision tree while keeping the security rules simple. When embedded in the economic dispatch, these rules significantly increase the percentage of secure states and reduce the average solution time.

Increased Integration of Different Solutions to Provide Improved Performance 5.2.3.3 Rapid Industrial Growth in Emerging Economies 5.2.4 Challenges 5.2.4.1 Threats Related to Cybersecurity 5.2.4.2 Complexity in Implementation of Smart Manufacturing Technology Systems 5.2.4.3 Lack of Awareness About Benefits of Adopting Information and Enabling Technologies 5.2.4.4 Lack of Skilled Workforce 5.3 Industrial Wearable Devices Trends in Smart Manufacturing 5.3.1 By Device 5.3.1.1