Transformative Technologies in Brain-Computer Interfaces-Innovations, Applications, and Challenges.

Malaria vector control technology has remained largely static for decades and there is a pressing need for innovative control tools and methodology to radically improve the quality and efficiency of current vector control practices. This report summarizes a workshop jointly organized by the Innovative Vector Control Consortium (IVCC) and the Armed Forces Pest Management Board (AFPMB) focused on public health pesticide application technology. Three main topics were discussed: the limitations with current tools and techniques used for indoor residual spraying (IRS), technology innovation to improve efficacy of IRS programmes, and truly disruptive application technology beyond IRS. The group identified several opportunities to improve application technology to include: insuring all IRS programmes are using constant flow valves and erosion resistant tips; introducing compression sprayer improvements that help minimize pesticide waste and human error; and moving beyond IRS by embracing the potential for new larval source management techniques and next generation technology such as unmanned “smart” spray systems. The meeting served to lay the foundation for broader collaboration between the IVCC and AFPMB and partners in industry, the World Health Organization, the Bill and Melinda Gates Foundation and others.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-015-0907-9) contains supplementary material, which is available to authorized users.

The growth of the Indonesian population has led to an increase in the demand for rice, which the country has yet to satisfy. Indonesia needs a comprehensive strategy that integrates meaningful efforts to increase its agricultural production. This study aims to review the examined trends in rice yield in Indonesia for 70 years after Indonesia’s independence (1945–2016) followed by the identification of the application technology and factors that contribute to increasing rice yields to forecast sustainable food security scenarios up to 2030. This article reviews the results of research on rice production technology in Indonesia from 1945 to 2016, and the outlook for 2030. This paper examines the main points of the Indonesian transformation of rice technology: improvement of rice varieties, integrated crop management, innovations in agricultural machinery, and the Integrated Cropping Calendar Information System (ICCIS). We found that transformation has helped Indonesia increased its rice yields from 3 t ha−1 prior to 1961 to 4.6 t ha−1 in 1985, stagnated in 1990, and increased again in 2017 to 5.46 t ha−1. The increase in yield was sustained by an increase in the harvested area owing to cropping index (CI) innovation. Food security and sustainable development remain the primary goals of Indonesia’s agricultural sector. The application of appropriate technologies and institutional innovations can assist Indonesia in achieving its food security. Therefore, the transformation of technological innovations will continue to be an essential driver of future agricultural growth, including greater use of crop varieties, machinery, and land/institutional reforms.

Proton exchange membrane fuel cells (PEMFC), distinguished by rapid refueling capability and zero tailpipe emissions, have emerged as a transformative energy conversion technology for automotive applications. Nevertheless, their widespread commercialization remains constrained by technical limitations mainly in operational longevity. Precise prognostics of performance degradation could enable real-time optimization of operation, thereby extending service life. This investigation proposes a hybrid prognostic framework integrating steady-state modeling with dynamic condition. First, a refined semi-empirical steady-state model was developed. Model parameters’ identification was achieved using grey wolf optimizer. Subsequently, dynamic durability testing data underwent systematic preprocessing through a correlation-based screening protocol. The processed dataset, comprising model-calculated reference outputs under dynamic conditions synchronized with filtered operational parameters, served as inputs for a recurrent neural network (RNN). Comparative analysis of multiple RNN variants revealed that the hybrid methodology achieved superior prediction fidelity, demonstrating a root mean square error of 0.6228%. Notably, the integration of steady-state physics could reduce the RNN structural complexity while maintaining equivalent prediction accuracy. This model-informed data fusion approach establishes a novel paradigm for PEMFC lifetime assessment. The proposed methodology provides automakers with a computationally efficient framework for durability prediction and control optimization in vehicular fuel cell systems.

Lithium-ion batteries (LIBs) have arguably represented one of the most transformative technologies for electrochemical energy storage and conversion applications over the past 3+ decades. Since the inception of the concept in the 1970s, the LIBs have served a wide swath of electrochemical energy storage and conversion fields covering consumer to industrial applications. Continual improvements of the materials/chemistry have resulted in high energy densities unimaginable a mere 10 years ago.Further economic integration of LIBs continues to suffer from a major bottleneck: large-scale LIB manufacturing still relies upon slurry-based production methods to produce electrodes.[1] Regardless of the electrode chemistries Just the electrode drying process (and subsequent solvent evaporation/recovery) is a major expenditure with respect to footprint (+80 m long drying ovens), environmental conditioning, and energy costs. The realization of higher pack energy densities is severely constrained by the current manufacturing process; cathodes are too thin. They are constrained by the wet slurry casting/drying processes to ~100 µm thick. Even so-called “low capacity”, economically low-cost cathode materials such as lithium iron phosphate (LFP + carbon coating, ~170 mAh g-1 theoretical capacity) would become extremely attractive at +250 µm thicknesses.[2] Indeed, the capability to increase LFP cathode layer thicknesses to these levels presents an immediate opportunity to realize areal current densities well exceeding 6 mAh cm-2.INTECELLS, Inc., a Michigan-based, VC-backed startup, proposes that a solution to this bottleneck is to leverage cold plasma-based[3] deposition for electrode layer fabrication. Nitrogen gas-based cold plasma-powder coating (CPC, conducted in open air environments at room temperature and atmospheric pressure) allows for the solvent-free deposition of electrode layers beyond 200 µm. Plasma processing is not a pyrolytic process: neither the raw electrode powders nor the substrates are subjected to high temperatures that result in adverse chemical and/or structural changes to the starting materials. Significantly, CPC is essentially a solid-state process. Ergo, solvents and polymeric binders are no longer required. With respect to LFP, only conductive additives must be incorporated into the coating.An important advantage of cold plasma processing is the inherent property of modifying the surface energies of materials. Indeed, this has been the main thrust of CP technologies in Europe and Asia over the past several decades: to prepare a variety of targeted surfaces for bonding, increased hydrophilicity, and solvent-free surface cleaning. When this phenomenon is applied to LIB electrode materials, not only can dense, ultrathick electrode layers be deposited in a single step, but the very nature of plasma processing modifies the surface energy of the electrode particles. The deposited electrode layers exhibit an enhanced degree of hydrophilicity; thoroughly wetting the electrode layer becomes very simplified. In short, the deposition of electrode layers via CPC collapses several traditional manufacturing steps (slurry mixing, coating, drying/recovery, and calendering) into one step, and concomitantly reduces the cell filling/wetting step to a matter of minutes sans vacuum.This presentation will introduce the key concepts behind CPC-deposition of LIB electrode materials. Plasma-driven effects on the electrode layers such as enhanced surface energies, layer thicknesses, and densities will be discussed. Analysis of the electrode layers by techniques such as SEM, STEM, XPS, and others, will be leveraged to explore the compositions and qualities of the electrodes. Preliminary electrochemical evaluations (e.g., coin cell-level) will be presented to exhibit the effects of continuous process development and improvements. The CPC process represents an entirely new scalable manufacturing technique by which to realize performance goals necessary to further market penetration of LIBs into a variety of fields. The reduced plant footprints and material costs offered by CPC has the potential to re-define LIB manufacturing in the global marketplace. Acknowledgements The authors acknowledge Dr. Kai Sun and the University of Michigan College of Engineering for financial support at the Michigan Center for Materials Characterization for use of the instruments and staff assistance.

Functional ultrasound localization microscopy (fULM) is a new technique that combines the principles of ULM and functional ultrasound (fUS) to achieve brain-wide and micrometer-scale mapping of brain neural activities based on neurovascular coupling. The unique combination of high imaging spatial resolution, large imaging field-of-view, and deep imaging depth of penetration makes fULM a potentially transformative technology for numerous neuroscience applications where activities from both global neural networks and local neurocircuits need to be recorded simultaneously and continuously. At present, however, fULM suffers from many technical and pragmatic challenges, including low sensitivity and specificity to neural activities, the need of long data acquisition with continuous infusion of microbubbles and repeated simulations, and the lack of viable 3D imaging solutions that are essential for neuroscience research. In this presentation, I will first introduce the principles and technical challenges of fULM, followed by recent advances achieved by our group including (1) enhanced microbubble localization, tracking, and other post-processing techniques to boost fULM’s sensitivity to neural activities; (2) 3D fULM based on 2D matrix arrays that are compatible with mainstream 256-channel ultrasound systems; and (3) an awake fULM imaging platform for mice and rats that allows whole-brain, microscopic-scale recording of functional neural activities in awake animals.

Design and Research of Application Technology Transformation System Based on Data Mining