Se ha vuelto popular la posición de que si la ciencia no genera un producto que se venda bien, resulta un ejercicio inútil y desperdiciador. Queremos resultados sin esfuerzo.
Los icebergs son símbolo de lo mucho que se oculta detrás de lo poco que se ve. Su densidad es un poco menor que la del agua salada, por eso flotan –pero el 90 por ciento de su masa está sumergida–. Quienes quieren tener un pico sin su base deben saber que no es posible.
Recuerdo los icebergs cuando pienso en nuestras políticas de ciencia y tecnología. Se ha vuelto popular la posición de que la ciencia sirve meramente como instrumento para mejorar la competitividad y de que si no genera un producto que se venda bien, resulta un ejercicio inútil y desperdiciador. Queremos resultados sin esfuerzo.
Me han tratado de convencer de que eso es posible con el ejemplo de Steve Jobs, quien, sin grandes estudios, construyó un imperio tecnológico. Es cierto, él fue una persona muy ingeniosa, pero no se puede olvidar lo que hay debajo de la punta del iceberg.
¿Cuánta física del estado sólido y cuánta química de materiales hay detrás de una pantalla táctil?
¿De dónde salió la tecnología de transmisión inalámbrica de la información?
¿Serían posibles los mapas de Google y los GPS sin la teoría de la relatividad?
¿Cuánta matemática y cuánto diseño hay detrás de cualquier app de moda?
Es difícil profetizar, pero sí se puede decir con seguridad que las innovaciones tecnológicas revolucionarias surgirán en aquellos países que tienen una sólida capacidad científica.
La ciencia no solo sirve para la competitividad. Nos ayuda a entender el mundo y la vida, a generar bienestar y salud, a cuidar el medioambiente y a educar gente con pensamiento riguroso y capacidad para responder a problemas insospechados. Así mismo, la competitividad no es solo innovación. Esta última es apenas un factor entre otros, como el tipo de cambio, las tasas de interés, la productividad y el costo del trabajo, las leyes de protección, los recursos naturales, la cercanía y posibilidad de acceso a los mercados y más.
Pero nosotros insistimos en quedarnos con la punta del iceberg. El Plan Nacional de Desarrollo aprobó la fusión del sistema de Ciencia, Tecnología e Innovación con el de Competitividad. Definió la política de ciencia en apenas 12 renglones, en una ley de 68 páginas. Colciencias ni siquiera se menciona en ese único artículo (el 186) y aparece apenas tres veces nombrada en toda la ley, siempre dependiendo del Departamento Nacional de Planeación. Pienso que cuando Carlos Lleras fundó Colciencias y la denominó cabeza del sistema, no se refería a su posición en la jerarquía administrativa, sino a que contenía el cerebro.
Un amigo, miembro de un consejo de programa de C. y T., me relató una anécdota que viene al caso. A una reunión para evaluar la situación de la investigación vino un viceministro como delegado del Gobierno. Llegó tarde, habló y se fue. No averiguó quiénes eran los asistentes y se dirigió al consejo, compuesto por líderes académicos, investigadores y empresarios, como si se tratara de un comité interno de Colciencias. Les explicó que no hay que perder el tiempo en investigaciones sofisticadas, sino generar productos. Les recordó que esa institución debe estar al servicio de su cliente, que es... el Presidente (sí, lector, yo tampoco lo creí, y pedí que me lo repitieran). Terminó asegurando que Colombia tiene ya demasiados doctores y que no se justifica seguir fomentándolos con programas y becas.
Puede ser que creamos que podemos tener la punta de un iceberg sin su base porque ya tenemos una casita en el aire (la he oído por la radio, pero no la he visto en las ofertas inmobiliarias). Tal vez los edificios Space, en Medellín, fueron un primer experimento de esa política que dice que no vale la pena invertir en cimientos y columnas si lo que se vende son los acabados.
Google's Sundar Pichai talks about its advancements in deep
learning at the 2015 Google I/O conference in San Francisco on May 28.
Image Credit: Screenshot
Google today announced its advancements in deep learning, a type of artificial intelligence, for key processes like image recognition and speech recognition.
When it comes to accurately recognizing words in speech, Google now has just an 8 percent error rate. Compare that to 23 percent in 2013, Sundar Pichai, senior vice president of Android, Chrome, and Apps at Google, said at the company’s annual I/O developer conference in San Francisco.
Pichai boasted, “We have the best investments in machine learning over the past many years.” Indeed, Google has acquired several deep learning companies over the years, including DeepMind, DNNresearch, and Jetpac.
Deep learning involves ingesting lots of data to train systems called neural networks, and then feeding new data to those systems and receiving predictions in response.
The company’s current neural networks are now more than 30 layers deep, Pichai said.
Meanwhile, Baidu, Facebook, and Microsoft are also beefing up their deep learning capabilities. Earlier-stage companies like Flipboard, Pinterest, and Snapchat have also been doing research in the area — but none have the computing power that Google does. So Google’s achievements in real production apps are a pretty big deal.
To view all of VentureBeat’s Google I/O coverage, click here.
Abstract
The introduction of affordable, consumer-oriented 3-D printers is a milestone in the current “maker movement,” which has been heralded as the next industrial revolution. Combined with free and open sharing of detailed design blueprints and accessible development tools, rapid prototypes of complex products can now be assembled in one’s own garage—a game-changer reminiscent of the early days of personal computing. At the same time, 3-D printing has also allowed the scientific and engineering community to build the “little things” that help a lab get up and running much faster and easier than ever before.
Figures
Citation: Baden T, Chagas AM, Gage G, Marzullo T, Prieto-Godino LL, et al. (2015) Open Labware: 3-D Printing Your Own Lab Equipment. PLoS Biol 13(3): e1002086. doi:10.1371/journal.pbio.1002086
Funding: This work was supported by the Deutsche Forschungsgemeinschaft (DFG) (Werner Reichardt Centre for Integrative Neuroscience Tübingen, EXC 307 to TE and TB; BA 5283/1-1 to TB) and the U.S. National Institutes of Mental Health Small Business Innovation Research grant #R44 MH093334 to GG and TM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: Authors GG and TM are founders of Backyard Brains (www.backyardbrains.com), a company specializing in the design and distribution of Open Labware.
Abbreviations:: ABS, Acrylnitrile butadiene styrene; CNC, computer numerical control; DIY, Do It Yourself; EMG, Electromyogram; ERG, Electroretinogram; FOSSFA, Free Software and Open Source Foundation for Africa; GNU, “GNU is not Unix” (recursive acronym); GPIO, general-purpose input-output; IT, information technology; LED, Light Emitting Diode; NIH, National Institutes of Health; PCB, Printed Circuit Board; PLA, Polylactic acid; TReND, Teaching and Research in Natural Sciences for Development (in Africa); UV, Ultraviolet
Applications of 3-D printing technologies (Fig. 1A, Box 1) have become as diverse as the types of materials that can be used for printing. Replacement parts at the International Space Station may be printed in orbit from durable plastics or metals, while back on Earth the food industry is starting to explore the same basic technology to fold strings of chocolate into custom-shaped confectionary. Also, consumer-oriented laser-cutting technology makes it very easy to cut raw materials such as sheets of plywood, acrylic, or aluminum into complex shapes within seconds. The range of possibilities comes to light when those mechanical parts are combined with off-the-shelf electronics, low-cost microcontrollers like Arduino boards [1], and single-board computers such as a Beagleboard [2] or a Raspberry Pi [3]. After an initial investment of typically less than a thousand dollars (e.g., to set-up a 3-D printer), the only other materials needed to build virtually anything include a few hundred grams of plastic (approximately US$30/kg), cables, and basic electronic components [4,5].
Fig 1. Examples of open 3-D printed laboratory tools.A1, Components for laboratory tools, such as the base for a micromanipulator [18] shown here, can be rapidly prototyped using 3-D printing. A2, The printed parts can be easily combined with an off-the-shelf continuous rotation servo-motor (bottom) to motorize the main axis. B1, A 3-D printable micropipette [8], designed in OpenSCAD [19], shown in full (left) and cross-section (right). B2, The pipette consists of the printed parts (blue), two biro fillings with the spring, an off-the-shelf piece of tubing to fit the tip, and one screw used as a spacer. B3, Assembly is complete with a laboratory glove or balloon spanned between the two main printed parts and sealed with tape to create an airtight bottom chamber continuous with the pipette tip. Accuracy is ±2–10 μl depending on printer precision, and total capacity of the system is easily adjusted using two variables listed in the source code, or accessed via the “Customizer” plugin on the thingiverse link [8]. See also the first table.
Box 1. Glossary Open source
A collective license that defines terms of free availability and redistribution of published source material. Terms include free and unrestricted distribution, as well as full access to source code/blueprints/circuit board designs and derived works. For details, see http://opensource.org.
Maker movement
Technology-oriented extension of the traditional “Do-it-Yourself (DIY)” movement, typically denoting specific pursuits in electronics, CNC (computer numerical control) tools such as mills and laser cutters, as well as 3-D printing and related technologies.
3-D printing
Technology to generate three-dimensional objects from raw materials based on computer models. Most consumer-oriented 3-D printers print in plastic by locally melting a strand of raw material at the tip (“hot-end”) and “drawing” a 3-D object in layers. Plastic materials include Acrylnitrile butadiene styrene (ABS) and Polylactic acid (PLA). Many variations of 3-D printers exist, including those based on laser-polymerization or fusion of resins or powdered raw materials (e.g., metal or ceramic printers).
Arduino boards
Inexpensive and consumer-oriented microcontroller boards built around simple processors. These boards offer a variety of interfaces (serial ports, I2C and CAN bus, etc.), μs-timers, and multiple general-purpose input-output (GPIO) pins suitable for running simple, time-precise programs to control custom-built electronics.
Single board computers
Inexpensive single-board computers capable of running a mature operating system with graphical-user interface, such as Linux. Like microcontroller boards, they offer a variety of hardware interfaces and GPIO pins to control custom-built electronics.
It therefore comes as no surprise that these technologies are also routinely used by research scientists and, especially, educators aiming to customize existing lab equipment or even build sophisticated lab equipment from scratch for a mere fraction of what commercial alternatives cost [6]. Designs for such “Open Labware” include simple mechanical adaptors [7], micropipettes (Fig. 1B) [8], and an egg-whisk–based centrifuge [9] as well as more sophisticated equipment such as an extracellular amplifier for neurophysiological experiments [10], a thermocycler for PCR [11], or a two-photon microscope [12]. At the same time, conceptually related approaches are also being pursued in chemistry [13–15] and material sciences [16,17]. See also Table 1.
Table 1. Open Labware designs for a biology lab. doi:10.1371/journal.pbio.1002086.t001
A Culture of SharingMost makers share their designs under an open source license together with detailed assembly instructions in online repositories [20–22] such as the National Institutes of Health (NIH) 3-D print exchange [23] or in peer-reviewed journals [10,17,24–29]. As a result, anyone can freely use and modify them. This open culture, which has transformed the world of software engineering over the past decades, offers several advantages over traditional product design. First, designs are not only free, but are directly shaped by people who will actually use the final product. Second, building your own experimental equipment yields a much deeper understanding of the principles underlying its design and a better awareness of its limits. Third, manufacturing is immediate and local—thus empowering laboratories and schools located in difficult-to-reach places. Fourth, the open source movement is a global phenomenon, connecting people worldwide, often to recruit talented builders and coders from outside the traditional scientific establishment. Still, there are drawbacks. For example, a commercial solution may be preferred if the time and cost of in-house development exceeds the benefits of control and instrument knowledge. Nevertheless, and perhaps counter-intuitively, some open designs are published by commercial companies that offer the parts as well as the assembled product with technical support for a fee, while maintaining the source material online under an open source license. Consumers can more freely balance cost against time to build, while companies gain in customer relations and product feedback.
Quality Control and the Evolution of Open Labware Designs
The flagship of the open source movement, the operation system GNU/Linux [30], is perhaps the best example for the potential of open designs. First available in the 1990s, today it is one of the most widely used system on supercomputers, servers, and mobile phones (Android) and increases its share of home users every year. Critically, Linux is fully open source—anyone can freely access its entire source code, change it, and distribute modifications. Its success flows from the idea that “given enough eyeballs all bugs are shallow” [31]. In other words, a distributed network of collaborators helps to identify and rectify bugs in the system as they arise. Open Labware works the same way: release of a design sparks feedback and refinements from the community. Although Open Labware’s contributor base is still relatively small, feedback can nonetheless markedly improve product design and expand potential applications over time. For example, free online sharing of the designs for a manually controlled 3-D printed micromanipulator (Fig. 2A) [18] provided the starting point for a high-precision motorized version (Fig. 2B) [32]. Subsequently, and in combination with open designs for smartphone lens-adapters offering portable options for field-microscopy [33], both designs led to the “Raspberry Pi-scope” [34]—a self-standing histology microscope based on a Raspberry Pi, equipped with a high-resolution camera module, a low-cost acrylic lens, and the manipulator body to accurately position the sample (Fig. 2C). One next step in this evolution may be to add low-cost fluorescence capability through the addition of a ultraviolet light-emitting diode (UV-LED) and the appropriate filters, perhaps inspired by materials used in the less than US$1 fluorescence-capable Foldscope [24]. Without free-and-open sharing of the complete source materials at all stages of development, this evolution would not have been possible. With educators and researchers increasingly integrating Open Labware approaches into their projects, designs are expected to continuously improve and diversify.
Fig 2. Evolution of an Open Labware design.
A, A 3-D printable micromanipulator with a slanted Z-axis [18], here shown amidst commercial alternatives, initially served as the basis for a motorized version with “real” Z axis [32] (B). B1,2, the three axes are driven by continuous-rotation micro-servos, controlled by an Arduino fitted with a Joystick-shield and a 9V battery. B3, The motorized manipulator offers sufficient precision to target individual hairs on the head of a fruitfly (±5–20 μm during movements, depending on printer precision; <1 μm drift min-1 when stationary). Scale bar 1 mm. C1, The same manipulator build was then converted into a microscope-stage to permit accurate placement and focus of histology samples [34]. The optics are provided by an off-the-shelf, low-power acrylic lens positioned directly above a Raspberry Pi camera module [3]. C2, Image taken with the microscope, showing a slice of mouse brain (hippocampus) stained for cytochrome oxidase C. Scale bar 500 μm.
doi:10.1371/journal.pbio.1002086.g002
Online Resources for Learning and Problem Solving
Although most Open Labware designs are published with detailed assembly instructions aimed at the non-specialist, a basic understanding of concepts in physics, electronics, and computer programming is certainly helpful. Luckily, freely available online resources facilitate self-learning (Table 2). In addition, many makers hone their skills directly at the workbench, simply by attempting to recreate or modify existing designs. Expert community help can be rapidly found in online forums such as Stack Overflow [35], returning to the idea that many eyes lead to rapid problem-solving. In addition, online aggregators gather and summarize information on specific topics, serving as a hub for both information seekers and distributors. Some of them are curated in a centralized manner [36], while others follow the distributed wiki principle [37].
Table 2. Open resources for self-taught learning of programming, electronics, and basic physics. doi:10.1371/journal.pbio.1002086.t002
Application in a Resource-Challenged Context
If a commercial alternative is available, it is usually the compromise between time and money spent that determines whether to build or purchase equipment. While Open Labware designs may benefit any research or education setting [38], one obvious foothold for their possibilities lies in economically deprived schools and universities in the developing world. Here, the introduction of Open Labware may make the crucial difference between having some usable equipment to work with and having none at all. Several benefits of an open model come to light: low cost, local manufacture, and the possibility to customize according to local demands or availability of parts. In sub-Saharan Africa, only a few bases and organizations that offer training in “maker” skills or general promotion of open source principles operate. These include the Free Software and Open Source Foundation for Africa (FOSSFA [39]), Fundi bots [40], as well as a few physical spaces such as FabLabs [41] and Maker- [42] and Hackerspaces [43] scattered mostly around the major cities. In addition, companies selling easily transportable 3-D printers and supplies are rapidly establishing their foothold on the African continent, such that local sourcing of the required hardware is no longer an insurmountable obstacle. However, on the whole, Open Labware possibilities remain poorly established in this context, as attested in a survey taken by 89 biomedical researchers from 12 sub-Saharan African countries in August 2014 (Fig. 3). When asked about their software competency, most respondents indicated that while they are comfortable with “basic” IT usage (defined as using office packages or navigating the web), few were routine users of standard open analysis packages such as R [44], octave [45], or other Python [46] based packages, and programming skills were even less prevalent (Fig. 3A). Awareness and competency in the use of open hardware approaches were even less developed: over 90% of respondents (83/89) had never used 3-D printing or any form of single-board computers or microcontrollers (Fig. 3B).
Fig 3. Open Labware at universities in sub-Saharan Africa.
An online survey was taken by 89 biomedical researchers (MSc. to
Professor) at universities in 12 different sub-Saharan African countries
in August 2014. Researchers rated their own competency and awareness in
aspects of software and hardware usage. A, Software competency rated on
a scale of 1 (low) to 10 (high) in “basic usage such as navigating
office software or the internet,” “usage of open analysis packages such
as R [44], octave [45],
or similar,” and “programming, e.g., using C++, python, or any other
mainstream language.” B, Hardware awareness for possibilities in “3-D
printing” (top) and “single board computers/microcontrollers such as
Raspberry Pi, Arduino, Beagleboard, or similar” rated in four
categories: (i) “I have never heard of this,” (ii) “I have heard of it
but I have no access,” (iii) “I have tried using this at least once,”
(iv) “I am a competent/routine user.”doi:10.1371/journal.pbio.1002086.g003
As part of ongoing efforts to promote scientific education and research in the developing world, we introduced the many possibilities of Open Labware to schools and universities in sub-Saharan Africa (TReND in Africa [47]) and Latin America (Backyard Brains [48]). Different formats were used, ranging from three-week intensive neuroscience summer schools aimed at university graduates in Uganda and Tanzania (four events), to multiday MakerSpace workshops aimed at school students and their teachers in Chile and Mexico (12 events), to outreach events and lectures held at scientific conferences, schools, and public spaces on four continents (more than 100 events). Here, we present some experiences and success stories from this work.
In-Depth Exposure during Multiday Training Events
The longer events, such as the three-week neuroscience summer schools in Africa or the multiday MakerSpace workshops in Latin America, afforded participants the opportunity to get hands-on experience using, assembling, and contributing to the development of Open Labware designs. One popular activity was to assemble existing designs (such as a spikerbox, Fig. 4A [10,49]) from off-the-shelf parts. This required participants to study the circuit diagram, note the identity and polarity of simple electronic components such as chips and capacitors and to solder them in place on the printed circuit board (PCB) (Fig. 4B). The assembled amplifiers were subsequently used to perform classic neurophysiological experiments such as recording of action potentials from the locust [50] or cricket [51,52] extensor tibiae (Fig. 4C). Although initially daunting especially for the many participants without previous contact with any form of electrical engineering, the experience tended to be very motivating across ages and cultures. In particular, it contributed to take away the fear of experimenting with simple electronic circuits or opening up and attempting to modify or repair existing electronic tools in their daily environment. The low cost of required parts also allowed participants to build their own gear, rather than that of their school or university, making them more invested in its success and maintenance. Critically, building equipment from scratch often resulted in a high level of mechanistic understanding and a curiosity to “play” with the finished product to see if it can be improved or modified to better suit a particular purpose. For example, one undergraduate student linked an electromyogram (EMG)-amplifier to an off-the-shelf “robotic limb” [53] via an Arduino microcontroller [1] to remotely control grasping movements by contracting their forearm muscles (Fig. 4D). Clearly, introduction of low-cost and open source electronics and mechanical parts has the potential to open up vast possibilities to resourceful people anywhere in the world, independent of financial means or educational background.
Fig 4. Hands-on exposure to Open Labware in the developing world.
A, Each student assembled a spikerbox [10,49],
an amplifier for neurophysiological experiments, from its off-the-shelf
components. B, Students at a workshop in Dar es Salaam, Tanzania. C,
The assembled amplifiers were subsequently used to perform simple
neurophysiological experiments [51]. Image credit for panels B and C: Horst Schneider. D, One student set up
a spikerbox via an Arduino to trigger closure of a “gripper-hand,” a
low-cost robotic limb, through contractions of their forearm muscles. doi:10.1371/journal.pbio.1002086.g004
During the three-week neuroscience summer schools in Uganda and Tanzania [54] we introduced participants to 3-D printed lab tools such as pipettes [8], manipulators [18,32], and microscope adapters [55] and compared the usefulness of self-built versus commercially available solutions for different types of experiments. For example, although printed pipettes [8] offer lower precision than commercially available ones (±2–10 μl, depending on printer precision) they are nonetheless adequate for many “low precision” tasks such as distributing diluted antibody solutions to different samples or applying mounting media for immunohistochemistry. Similarly, we used different versions of 3-D printed micromanipulators [18,32] to position reference electrodes during neurophysiological experiments, e.g., for Calliphora tangential cell recordings [56], but maintained the recording tungsten electrode on a more stable commercial manipulator. For some types of recordings, such as Drosophila electroretinograms (ERGs) [57], the printed manipulators were adequate to hold both electrodes, and the magnification gained by attaching a low-power acrylic lens to a webcam or smartphone easily sufficed for their accurate placement. We also provided access to pre-installed Raspberry Pi computers [3] running a range of open analysis and office software packages and provided basic training in their use. Hands-on exposure allowed students to judge for themselves which designs would be useful in their own research and teaching activities. In a subsequent survey, students rated the usefulness of every open design described above as at least nine out of ten on average (n = 33). We believe that the introduction of Open Labware possibilities to the African university system may be a highly effective measure towards fostering excellence in research and education on the continent.
Motivating More High School Graduates to Pursue a Career in Science
One pervasive issue in building a sustainable research infrastructure and scientific culture in resource-challenged countries is a perceived limit on career choices afforded by higher education. Traditionally, three disciplines—medicine, civil engineering, or law—are considered the best choices for reliable income, with few individuals enrolling in a natural science subject and fewer still ending up in active research [58,59]. To encourage students to consider a career in science, we (TReND and Backyard Brains) have participated in more than a hundred science outreach events around (Neuro)science, engaging more than 10,000 students, parents, and teachers. In several science camps (“ChileVA! [60]”), we gave two-hour lectures to high school students about the brain and how to record from neurons and muscles. The students not only “tolerated” this unusually long-format science lecture without breaks, but swarmed the demonstration booth afterwards. Clearly, low-cost and portable equipment offers the possibility to perform science demonstrations anywhere, independent of local infrastructure.
In TReND’s African activities, student-alumni of our summer workshops have taken over local science outreach by organizing into regional teams to visit schools and universities in their respective home countries [61]. Many of these young scientists come from similar backgrounds as the students they engage, allowing them to act as powerful role models. Thus, students attending a school that cannot afford the equipment or infrastructure to perform live experiments during science classes are exposed to local scientists with a similar background, handling equipment they know how to build from affordable, local resources. The experience can be very powerful and inspire them to pursue a similar career, as well as offering local teachers ideas to use in future science classes. This approach of “teaching the teachers” also means that the impact of educating a few students at a high level has the potential to trickle-down and achieve a wide impact in the long term.
Policy Recommendations
Clearly, the use and design of Open Labware designs can be a powerful ingredient to foster scientific research, education, and public science engagement. Their evolution spans several disciplines, from computer sciences and mechanical engineering to electronics and biology—thus connecting experts and the wider public across fields and sparking creativity in people of all ages. Their low cost, adaptability and robustness renders designs suitable for a broad range of applications in both teaching and research. Below we present some suggestions for policy implementations to optimize available possibilities.
Integrate more aspects of design and use of Open Labware into traditional science curricula, ideally at an early age.
Establish more hands-on training courses in basic hardware design and programming skills for established scientists and educators.
Establish infrastructural support to afford more students and educators easy and direct access to 3-D printing and related technologies. With 3-D printers starting at a few hundred dollars and their price steadily falling, schools and university departments should not be barred from investing in their own model because of economic reasons.
Provide incentives for companies to invest in an open model of product design. This move promises to spark a new generation of open companies in more direct dialogue with the end user, towards better, individually tailored, and more affordable product design.
Container with all files mentioned in the article that are currently hosted on thingiverse (www.thingiverse.com).
S1 Data. Thingiverse files.
Container with all files mentioned in the article that are currently hosted on thingiverse (www.thingiverse.com).
doi:10.1371/journal.pbio.1002086.s001
(ZIP)
Acknowledgments
We thank the students and voluntary instructors of the many lectures and workshops mentioned in the manuscript, as well as the TReND outreach team, headed by Mahmoud Bukar Maina and Yunusa Mohammed Garba, for their ongoing efforts in promoting science education in Africa. We thank all sponsors of workshops, most notably including the International Brain Research Organization (IBRO), The Company of Biologists, and the Cambridge Alborada Fund.
ORIGINAL:PLOS
Tom Baden,
Andre Maia Chagas,
Greg Gage,
Timothy Marzullo,
Lucia L. Prieto-Godino,
Thomas Euler
March 20, 2015
DOI: 10.1371/journal.pbio.1002086
Everyone’s least favorite rodent has been tasked with cleaning up the lethal leftovers of war. Land mines kill thousands every year, but these rats have been trained to save lives by sniffing out the scent of explosives. The group responsible for training the rodents is APOPO – which stands for Anti-Persoonsmijnen Ontmijnende Product Ontwikkeling in Dutch, or Anti-Personnel Landmines Detection Product Development in English.
Using positive reinforcement that is respectful to the animals, these African pouched rats are taught to identify explosives and then alert their handler.
They’re perfect for the job – they’re highly intelligent and have a keen sense of smell. They are small enough not to trigger mines, yet large enough to be easily identifiable in the field. No rat has been killed in a minefield.
They can clear two hundred square meters in just 20 minutes. It would take humans with metal detectors five days to cover the same area.
Since 2000, they have found over 9,000 buried land mines and bombs all across Tanzania and Mozambique. They’ve also found thousands of small arms and ammunitions stashed in the ground.
The rats normally live for up to eight years, but are retired when they turn six. They live out the rest of their days as hero’s, munching on avocados, apples and bananas, and being loved on by their handlers.
1. Socialization. Once the rats open their eyes at the age of four weeks, they are socialized to interact with people and get used to the various stimuli of our world.
2-3 Click training and scent conditioning. The click sound is
established as a conditioned reinforcer associated with a food reward.
Once the rat learns that click means food, it will now have to search
for the target scent, TNT, to earn this reward.
4. TNT scent discrimination. The rat is offered a choice between
various scents placed beneath 3 sniffer holes. Only when it pauzes above
the target scent, the click and food treat will teach the rat this was
the correct response.
5. Soil floor search - The rat will continue its search
for the target scent, but now it is hidden in a sandbox. The rat learns
to walk in lanes and return to its trainer for some banana after each
correct indication.
6. Field training. For the first time, the rats enter a real field
with deactivated landmines. They will first detect surface laid mines on
a small surface to, and move gradually to deeper mines in larger areas.
7. Blind test and accreditation - In this final test the rats will have to earn their ticket to the countries of operation. They are rigorously tested with higher requirements compared to the International Mine Action Standards (IMAS).
An experiment showing that oil droplets can be propelled across a fluid bath by the waves they generate has prompted physicists to reconsider the idea that something similar allows particles to behave like waves.
Owen Maroney worries that physicists have spent the better part of a century engaging in fraud.
Ever since they invented quantum theory in the early 1900s, explains Maroney, who is himself a physicist at the University of Oxford, UK, they have been talking about how strange it is — how it allows particles and atoms to move in many directions at once, for example, or to spin clockwise and anticlockwise simultaneously. But talk is not proof, says Maroney. “If we tell the public that quantum theory is weird, we better go out and test that's actually true,” he says. “Otherwise we're not doing science, we're just explaining some funny squiggles on a blackboard.”
It is this sentiment that has led Maroney and others to develop a new series of experiments to uncover the nature of the wavefunction — the mysterious entity that lies at the heart of quantum weirdness. On paper, the wavefunction is simply a mathematical object that physicists denote with the Greek letter psi (Ψ) — one of Maroney's funny squiggles — and use to describe a particle's quantum behaviour.
Quantum Harmonic Oscillator Animation.Comparison of classical and quantum harmonic oscillator conceptions for a single spinless particle. The two processes differ greatly. The classical process (A–B) is represented as the motion of a particle along a trajectory. The quantum process (C–H) has no such trajectory. Rather, it is represented as a wave. Panels (C–F) show four different standing wave solutions of the Schrödinger equation. Panels (G–H) further show two different wave functions that are solutions of the Schrödinger equation but not standing waves. Wikipedia
Built with our patented solid oxide fuel cell technology, Bloom's Energy Server® is a new class of distributed power generator, producing clean, reliable, affordable electricity at the customer site.
Fuel cells are devices that convert fuel into electricity through a clean electro-chemical process rather than dirty combustion. They are like batteries except that they always run.
Our particular type of fuel cell technology is different than legacy "hydrogen" fuel cells in three main ways:
Low cost materials – our cells use a common sand-like powder instead of precious metals like platinum or corrosive materials like acids.
High electrical efficiency – we can convert fuel into electricity at nearly twice the rate of some legacy technologies
Fuel flexibility – our systems are capable of using either renewable or fossil fuels
Each Bloom Energy Server provides 200kW of power, enough to meet the baseload needs of 160 average homes or an office building... day and night, in roughly the footprint of a standard parking space. For more power simply add more energy servers.
Each Energy Server consists of thousands of Bloom's fuel cells. Each cell is a flat solid ceramic square made from a common sand-like "powder."
Each Bloom Energy fuel cell is capable of producing about 25W... enough to power a light bulb. For more power, the cells are sandwiched, along with metal interconnect plates into a fuel cell "stack". A few stacks, together about the size of a loaf of bread, is enough to power an average home.
In an Energy Server, multiple stacks are aggregated together into a "power module", and then multiple power modules, along with a common fuel input and electrical output are assembled as a complete system.
For more power, multiple Energy Server systems can be deployed side by side.
In addition to Bloom's unmatched performance, this modular architecture offers...
easy and fast deployment
inherent redundancy for fault tolerance
high availability (one power module can be serviced while all others continue to operate)
mobility
Solid Oxide Fuel Cells
Fuel cells were invented over a century ago and have been used in practically every NASA mission since the 1960's, but until now, they have not gained widespread adoption because of their inherently high costs.
Legacy fuel cell technologies like
proton exchange membranes (PEMs),
phosphoric acid fuel cells (PAFCs), and
molten carbonate fuel cells (MCFCs),
have all required expensive precious metals, corrosive acids, or hard to contain molten materials. Combined with performance that has been only marginally better than alternatives, they have not been able to deliver a strong enough economic value proposition to overcome the status quo.
Some makers of legacy fuel cell technologies have tried to overcome these limitations by offering combined heat and power (CHP) schemes to take advantage of their wasted heat. While CHP does improve the economic value proposition, it only really does so in environments with exactly the right ratios of heat and power requirements on a 24/7/365 basis. Everywhere else the cost, complexity, and customization of CHP tends to outweigh the benefits.
For decades, experts have agreed that solid oxide fuel cells (SOFCs) hold the greatest potential of any fuel cell technology. With low cost ceramic materials, and extremely high electrical efficiencies, SOFCs can deliver attractive economics without relying on CHP. But until now, there were significant technical challenges inhibiting the commercialization of this promising new technology. SOFCs operate at extremely high temperature (typically above 800°C). This high temperature gives them extremely high electrical efficiencies, and fuel flexibility, both of which contribute to better economics, but it also creates engineering challenges.
Bloom has solved these engineering challenges. With breakthroughs in materials science, and revolutionary new design, Bloom's SOFC technology is a cost effective, all-electric solution.
Over a century in the making, fuel cells are finally clean, reliable, and most importantly, affordable.
