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  • Revenue and employees of "Manufacture of fabricated metal pr…
    1939    

    NEWS

       |   24/03/2019    
    Revenue and employees of "Manufacture of fabricated metal pr…
    Industrial Goods  Steel products

    ▣ CATEGORY OF COMPANIES (NACE Rev.2) Forging, pressing, stamping and roll-forming of metal; powder metallurgy Machining Manufacture of central heating radiators and boilers Manufacture of cutlery Manufacture of cutlery, tools and general hardware Manufacture of doors and windows of metal Manufacture of fabricated metal products, except machinery and equipment Manufacture of fasteners and screw machine products Manufacture of light metal packaging Manufacture of locks and hinges Manufacture of metal structures and parts of structures Manufacture of other fabricated metal products Manufacture of other fabricated metal products n.e.c. Manufacture of other tanks, reservoirs and containers of metal Manufacture of steam generators, except central heating hot water boilers Manufacture of steel drums and similar containers Manufacture of structural metal products Manufacture of tanks, reservoirs and containers of metal Manufacture of tools Manufacture of weapons and ammunition Manufacture of wire products, chain and springs Treatment and coating of metals Treatment and coating of metals; machining

  • Revenue and employees of "Manufacture of computer, electroni…
    1918    

    NEWS

       |   24/03/2019    
    Revenue and employees of "Manufacture of computer, electroni…
    Plants & Machinery  AI, Robot, Industry 4.0

    ▣ CATEGORY OF COMPANIES (NACE Rev.2) Manufacture of communication equipment Manufacture of computer, electronic and optical products Manufacture of computers and peripheral equipment Manufacture of consumer electronics Manufacture of electronic components Manufacture of electronic components and boards Manufacture of instruments and appliances for measuring, testing and navigation Manufacture of instruments and appliances for measuring, testing and navigation; watches and clocks Manufacture of irradiation, electromedical and electrotherapeutic equipment Manufacture of loaded electronic boards Manufacture of magnetic and optical media Manufacture of optical instruments and photographic equipment Manufacture of watches and clocks

  • Revenue and employees of "Manufacture of chemical products" …
    2366    

    NEWS

       |   24/03/2019    
    Revenue and employees of "Manufacture of chemical products" …
    Plants & Machinery  Material handling

    ▣ CATEGORY OF COMPANIES (NACE Rev.2) Manufacture of basic chemicals, fertilizers and nitrogen compounds, plastics and synthetic rubber in primary forms Manufacture of chemicals and chemical products Manufacture of dyes and pigments Manufacture of essential oils Manufacture of explosives Manufacture of fertilizers and nitrogen compounds Manufacture of glues Manufacture of industrial gases Manufacture of man-made fibers Manufacture of other chemical products Manufacture of other chemical products n.e.c. Manufacture of other inorganic basic chemicals Manufacture of other organic basic chemicals Manufacture of paints, varnishes and similar coatings, printing ink and mastics Manufacture of perfumes and toilet preparations Manufacture of pesticides and other agrochemical products Manufacture of plastics in primary forms Manufacture of soap and detergents, cleaning and polishing preparations Manufacture of synthetic rubber in primary forms

  • Revenue and employees of "Manufacture of basic pharmaceutica…
    3122    

    NEWS

       |   24/03/2019    
    Revenue and employees of "Manufacture of basic pharmaceutica…
    Medical & Healthcare  Health supplement

    ▣ CATEGORY OF COMPANIES (NACE Rev.2) Manufacture of basic pharmaceutical products Manufacture of basic pharmaceutical products and pharmaceutical preparations Manufacture of pharmaceutical preparations

  • Revenue and employees of "Manufacture of basic metals" compa…
    2205    

    NEWS

       |   24/03/2019    
    Revenue and employees of "Manufacture of basic metals" compa…
    Industrial Goods  Manufacture of basic metals

    ▣ CATEGORY OF COMPANIES (NACE Rev.2) Aluminium production Casting of iron Casting of light metals Casting of metals Casting of other non-ferrous metals Casting of steel Cold drawing of bars Cold drawing of wire Cold forming or folding Cold rolling of narrow strip Copper production Lead, zinc and tin production Manufacture of basic iron and steel and of ferro-alloys Manufacture of basic metals Manufacture of basic precious and other non-ferrous metals Manufacture of other products of first processing of steel Manufacture of tubes, pipes, hollow profiles and related fittings, of steel Other non-ferrous metal production Precious metals production Processing of nuclear fuel

  • Revenue and employees of "Construction of buildings" compani…
    1673    

    NEWS

       |   24/03/2019    
    Revenue and employees of "Construction of buildings" compani…
    Building & Construction  Tools for building

    ▣ CATEGORY OF COMPANIES (NACE Rev.2) Construction of buildings Construction of residential and non-residential buildings Development of building projects

  • Revenue and employees of "Civil engineering" companies in EU
    1624    

    NEWS

       |   24/03/2019    
    Revenue and employees of "Civil engineering" companies in EU
    Building & Construction  Tools for building

    ▣ CATEGORY OF COMPANIES (NACE Rev.2) Civil engineering Construction of bridges and tunnels Construction of other civil engineering projects Construction of other civil engineering projects n.e.c. Construction of railways and underground railways Construction of roads and motorways Construction of roads and railways Construction of utility projects Construction of utility projects for electricity and telecommunications Construction of utility projects for fluids Construction of water projects

  • Machine learning tracks moving cells
    2282    

    NEWS

       |   18/03/2019    
    Machine learning tracks moving cells
    Plants & Machinery  AI, Robot, Industry 4.0

    Both developing babies and elderly adults share a common characteristic: the many cells making up their bodies are always on the move. As we humans commute to work, cells migrate through the body to get their jobs done. Biologists have long struggled to quantify the movement and changing morphology of cells through time, but now, scientists at the Okinawa Institute of Science and Technology Graduate University (OIST) have devised an elegant tool to do just that. Using machine learning, the researchers designed a software to analyze microscopic snapshots of migrating cells. They named the software Usiigaci, a Ryukyuan word that refers to tracing the outlines of objects, as the innovative tool detects the changing outlines of individual cells. Usiigaci, described in a paper published March 13, 2019 in SoftwareX, is now available online for anyone to use, along with a video tutorial explaining the software. In the womb, a baby’s cells migrate to precise locations so that each arm, leg, and organ grows in its proper place. Our immune cells race through the body to mend wounds after injury. Cancerous cells metastasize by traveling through the body, spreading tumors to new tissues. To test the efficacy of new medicines, drug developers track the movement of cells before and after treatment. The Usiigaci software finds applications in all these areas of study and more. “This is an all-in-one solution to get us from raw images to quantitative data on cell migration,” said Hsieh-Fu Tsai, first author of the study. Tsai is a graduate student and a Japan Society for the Promotion of Science (JSPS) DC1 research fellow in the OIST Micro/Bio/Nanofluidics Unit, led by Prof. Amy Shen. “Our software is at least 100 times faster than manual methods, which are currently the gold-standard for these types of experiments because computers are not yet powerful enough.” “We’re hoping this software can become quite useful for the scientific community,” said Prof. Amy Shen, principal investigator of the unit and senior author of the study. “For any biological study or drug screening that requires you to track cellular responses to different stimuli, you can use this software.” Usiigaci in Action The Micro/Bio/Nanofluidics Unit has devised a machine learning software to segment, track, and analyze the movement of migrating cells. Named Usiigaci, a Ryukyuan word that means “tracing,” the software significantly outperforms existing programs and has many applications across biology and medicine. Machine Learning Makes Usiigaci Adaptable In order to observe cells under the microscope, scientists often steep them in dye or tweak their genes to make them glow in eye-popping colors. But coloring cells alters their movement, which in turn skews the experimental results. Some scientists attempt to study cell migration without the help of fluorescent tags, using so-called “label-free” methods, but end up running into a different problem; Label-free cells blend into the background of microscopic images, making them incredibly difficult to analyze with existing computer software. Usiigaci hops this hurdle by allowing scientists to train the software over time. Biologists act as teachers, providing the software new images to study so that it can come to recognize one cell from the next. A fast learner, the program quickly adapts to new sets of data and can easily track the movement of single cells, even if they’re crammed together like commuters on the Tokyo metro. “Most software...cannot tell cells in high-density apart; basically, they’re segmenting into a glob,” said Tsai. “With our software, we can segment correctly even if cells are touching. We can actually do single-cell tracking throughout the entire experiment.” Usiigaci is currently the fastest software capable of tracking the movement of label-free cells at single-cell resolution on a personal laptop. Prof. Amy Shen (left) and Hsieh-Fu Tsai of the Micro/Bio/Nanofluidics Unit stand beside the microscope that they use to capture images of migrating cells. As an initial step to pursue his thesis project, Tsai designed a software, called Usiigaci, to analyze these images and quantify the movement and changing morphology of cells through time. Software Mimics the Human Brain The researchers designed Usiigaci to process images as if it were a simplified human brain. The strategy enables the software to trace the outlines of individual cells, monitor their movement moment to moment, and transform that information into crunchable numbers. The program is built around a machine learning infrastructure known as a “convolutional neural network.” roughly based on how brain cells work together to process incoming information from the outside world. When our eyes capture light from the environment, they call on neurons to analyze those signals and figure out what we’re looking at and where it is in space. The neurons first sketch out the scene in broad strokes then pass the information on to the next set of cells, progressively rendering the image in more and more detail. Neural networks work similarly, except each “neuron” is a collection of code rather than a physical cell. This design grants Usiigaci its accuracy and adaptability. Looking forward, the researchers aim to develop neural networks to identify different components within cells, rather than just their outlines. With these tools in hand, scientists could easily assess whether a cell is healthy or diseased, young or old, derived from one genetic lineage or another. Like Usiigaci, these programs would have utility in fundamental biology, biotechnology research and beyond.

  • Imaging: A peek into lymph nodes
    3017    

    NEWS

       |   18/03/2019    
    Imaging: A peek into lymph nodes
    Medical & Healthcare  Medical Test Services

    The vast majority of cancer deaths occur due to the spread of cancer from one organ to another, which can happen either through the blood or the lymphatic system. However, it can be tricky to detect this early enough. Researchers at Tohoku University have developed a new method that would allow doctors to detect cancers in the lymph nodes while they are still small, before they travel to other parts of the body. This can greatly increase the chances of a successful treatment. There aren't many imaging techniques that can detect tumors in lymph nodes before they grow too large, especially in smaller nodes. Biopsies of lymph nodes is a possible option, but it can often give false negative results. So the team wanted to come up with a new method that would accurately detect the earliest stages of a cancer moving to another part of the body, using a technique called x-ray microcomputed tomography (micro-CT) (imaging supplies in the catalogue of MEDICA 2018). The team tested their new method on mice with breast cancer cells inserted into their lymph nodes. They injected a contrast agent at a slow, steady pace into the lymph nodes upstream of those carrying the cancer cells. As the contrast agent made its way through the lymphatic system, the researchers were able to map out its movement using micro-CT. Initially, the researchers did not observe any change in the flow of the contrast agent. However, after 28 days of injecting the cancer cells into the lymph nodes, they had divided and grown to a point where they blocked the flow of the contrast agent, creating empty pockets in the scan that did not have any contrast agent. By comparing the shape of the lymph node and the areas that contained the contrast agent, the researchers were able to get a clear picture of the presence of cancer cells there. Next, the researchers would like to hone in on better contrast agents that would offer a clearer, more precise picture of how cancer cells are moving around the lymphatic system. In the future, this technique could be an effective way to detect tumors early before they spread around the body, saving many lives and adding one more tool that doctors can turn to in their fight against cancer.

  • Using 3D models to reduce side effects of radiotherapy
    3248    

    NEWS

       |   15/03/2019    
    Using 3D models to reduce side effects of radiotherapy
    Medical & Healthcare  Medical Test Services

    The debilitating side effects of radiotherapy could soon be a thing of the past thanks to a breakthrough by University of South Australia (UniSA) and Harvard University researchers. UniSA biomedical engineer Professor Benjamin Thierry is leading an international study using organ-on-a-chip technology to develop 3D models to test the effects of different levels and types of radiation. A microfluidic cell culture chip closely mimics the structure and function of small blood vessels within a disposable device the size of a glass slide, allowing researchers and clinicians to investigate the impact of radiotherapy on the body’s tissues. To date, scientists have relied on testing radiotherapy on cells in a two-dimensional environment on a slide. Professor Thierry, from UniSA’s Future Industries Institute (FII) and the ARC Centre of Excellence in Convergent Bio-Nano Science and Technology (CBNS), says the organ-on-a-chip technology could reduce the need for animal studies and irrelevant invitro work, both of which have major limitations. “An important finding of the study is that endothelial cells grown in the standard 2D culture are significantly more radiosensitive than cells in the 3D vascular network. This is significant because we need to balance the effect of radiation on tumour tissues while preserving healthy ones,” Prof Thierry says. The findings, published in Advanced Materials Technologies, will allow researchers to fully investigate how radiation impacts on blood vessels and – soon – all other sensitive organs. “The human microvasculature (blood vessel systems within organs) is particularly sensitive to radiotherapy and the model used in this study could potentially lead to more effective therapies with fewer side effects for cancer patients,” Prof Thierry says. More than half of all cancer patients receive radiotherapy at least once in the course of their treatment. While it cures many cancers, the side effects can be brutal and sometimes lead to acute organ failure and long-term cardiovascular disease. Prof Thierry’s team, including UniSA FII colleague Dr Chih-Tsung Yang and PhD student Zhaobin Guo, are working in close collaboration with the Royal Adelaide Hospital and Harvard University’s Dana-Farber Cancer Institute with the support of the Australian National Fabrication Facility. “Better understanding the effect of radiotherapy on blood vessels within organs – and more generally on healthy tissues – is important, especially where extremely high doses and types of radiation are used,” Dr Yang says. The researchers’ next step is to develop body-on-chip models that mimic the key organs relevant to a specific cancer type.