For the past half century, silicon has served as the primary material platform for integrated circuit technology. However, the recent proliferation of nontraditional electronics, such as wearables, ...embedded systems, and low‐power portable devices, has led to increasingly complex mechanical and electrical performance requirements. Among emerging electronic materials, single‐walled carbon nanotubes (SWCNTs) are promising candidates for next‐generation computing as a result of their superlative electrical, optical, and mechanical properties. Moreover, their chirality‐dependent properties enable a wide range of emerging electronic applications including sub‐10 nm complementary field‐effect transistors, optoelectronic integrated circuits, and enantiomer‐recognition sensors. Here, recent progress in SWCNT‐based computing devices is reviewed, with an emphasis on the relationship between chirality enrichment and electronic functionality. In particular, after highlighting chirality‐dependent SWCNT properties and chirality enrichment methods, the range of computing applications that have been demonstrated using chirality‐enriched SWCNTs are summarized. By identifying remaining challenges and opportunities, this work provides a roadmap for next‐generation SWCNT‐based computing.
Recent progress in computing devices based on carbon nanotubes is reviewed, with an emphasis on the relationship between chirality enrichment and electronic functionality. A range of chirality‐dependent electronic applications is explored including monolithic logic‐memory, optoelectronic integrated circuits, neuromorphic devices, and enantiomer‐recognition sensors. By identifying remaining challenges and opportunities, a roadmap for next‐generation carbon nanotube computing is provided.
The objective of this study is to identify and analyze the scientific literature with a bibliometric analysis to find the main topics, authors, sources, most cited articles, and countries in the ...literature on virtual reality in education. Another aim is to understand the conceptual, intellectual, and social structure of the literature on the subject and identify the knowledge base of the use of VR in education and whether it is commonly used and integrated into teaching–learning processes. To do this, articles indexed in the Main Collections of the Web of Science, Scopus and Lens were analyzed for the period 2010 to 2021. The research results are presented in two parts: the first is a quantitative analysis that provides an overview of virtual reality (VR) technology used in the educational field, with tables, graphs, and maps, highlighting the main performance indicators for the production of articles and their citation. The results obtained found a total of 718 articles of which the following were analyzed 273 published articles. The second stage consisted of an inductive type of analysis that found six major groups in the cited articles, which are instruction and learning using VR, VR learning environments, use of VR in different fields of knowledge, learning processes using VR applications or games, learning processes employing simulation, and topics published during the Covid-19 pandemic. Another important aspect to mention is that VR is used in many different areas of education, but until the beginning of the pandemic the use of this so-called “disruptive process” came mainly from students, Institutions were reluctant and slow to accept and include VR in the teaching–learning processes.
This paper addresses to some of the latest contributions on the application of Finite Control Set Model Predictive Control (FCS-MPC) in Power Electronics. In FCS-MPC , the switching states are ...directly applied to the power converter, without the need of an additional modulation stage. The paper shows how the use of FCS-MPC provides a simple and efficient computational realization for different control objectives in Power Electronics. Some applications of this technology in drives, active filters, power conditioning, distributed generation and renewable energy are covered. Finally, attention is paid to the discussion of new trends in this technology and to the identification of open questions and future research topics.
Spiking neural networks exploit spatiotemporal processing, spiking sparsity, and high interneuron bandwidth to maximize the energy efficiency of neuromorphic computing. While conventional ...silicon-based technology can be used in this context, the resulting neuron-synapse circuits require multiple transistors and complicated layouts that limit integration density. Here, we demonstrate unprecedented electrostatic control of dual-gated Gaussian heterojunction transistors for simplified spiking neuron implementation. These devices employ wafer-scale mixed-dimensional van der Waals heterojunctions consisting of chemical vapor deposited monolayer molybdenum disulfide and solution-processed semiconducting single-walled carbon nanotubes to emulate the spike-generating ion channels in biological neurons. Circuits based on these dual-gated Gaussian devices enable a variety of biological spiking responses including phasic spiking, delayed spiking, and tonic bursting. In addition to neuromorphic computing, the tunable Gaussian response has significant implications for a range of other applications including telecommunications, computer vision, and natural language processing.
The ubiquity of nanoparticles, sourced from both natural environments and human activities, presents critical challenges for public health. While offering significant potential for innovative ...biomedical applications—especially in enhancing drug transport across the blood–brain barrier—these particles also introduce possible hazards due to inadvertent exposure. This concise review explores the paradoxical nature of nanoparticles, emphasizing their promising applications in healthcare juxtaposed with their potential neurotoxic consequences. Through a detailed examination, we delineate the pathways through which nanoparticles can reach the brain and the subsequent health implications. There is growing evidence of a disturbing association between nanoparticle exposure and the onset of neurodegenerative conditions, highlighting the imperative for comprehensive research and strategic interventions. Gaining a deep understanding of these mechanisms and enacting protective policies are crucial steps toward reducing the health threats of nanoparticles, thereby maximizing their therapeutic advantages.
The differential diagnosis between patients with essential tremor (ET) and those with Parkinson's disease (PD) whose main manifestation is tremor may be difficult unless using complex neuroimaging ...techniques such as 123I-FP-CIT SPECT. We considered that using smartphone's accelerometer to stablish a diagnostic test based on time-frequency differences between PD an ET could support the clinical diagnosis.
The study was carried out in 17 patients with PD, 16 patients with ET, 12 healthy volunteers and 7 patients with tremor of undecided diagnosis (TUD), who were re-evaluated one year after the first visit to reach the definite diagnosis. The smartphone was placed over the hand dorsum to record epochs of 30 s at rest and 30 s during arm stretching. We generated frequency power spectra and calculated receiver operating characteristics curves (ROC) curves of total spectral power, to establish a threshold to separate subjects with and without tremor. In patients with PD and ET, we found that the ROC curve of relative energy was the feature discriminating better between the two groups. This threshold was then used to classify the TUD patients.
We could correctly classify 49 out of 52 subjects in the category with/without tremor (97.96% sensitivity and 83.3% specificity) and 27 out of 32 patients in the category PD/ET (84.38% discrimination accuracy). Among TUD patients, 2 of 2 PD and 2 of 4 ET were correctly classified, and one patient having PD plus ET was classified as PD.
Based on the analysis of smartphone accelerometer recordings, we found several kinematic features in the analysis of tremor that distinguished first between healthy subjects and patients and, ultimately, between PD and ET patients. The proposed method can give immediate results for the clinician to gain valuable information for the diagnosis of tremor. This can be useful in environments where more sophisticated diagnostic techniques are unavailable.
Luminescent nanomaterials have shown promise for thermal sensing in bio‐applications, yet little is known of the role of organic coatings such as supported lipid bilayers on the thermal conductivity ...between the nanomaterial and its environment. Additionally, since the supported lipid bilayer mimics the cell membrane, its thermal properties are fundamentally important to understand the spatial variations of temperature and heat transfer across membranes. Herein, a new approach is described that enables direct measurement of these thermal properties using a LiYF4:Er3+/Yb3+ upconverting nanoparticle encapsulated within a conformal supported lipid bilayer and dispersed in water as a temperature probe yielding the temperature gradient across the bilayer. The thermal conductivity of the lipid bilayer is measured as a function of the temperature, being 0.20 ± 0.02 W m−1 K−1 at 300 K. For the uncapped nanoparticles dispersed in water, the temperature dependence of the thermal conductivity is also measured in the 300–314 K range as 0.63–0.69 ± 0.11 W m−1 K−1. Using a lumped elements model, the directional heat transfer is calculated at each of the system interfaces, namely, nanoparticle–bilayer and bilayer–nanofluid, opening a new avenue to understand the membrane biophysical properties as well as the thermal properties of organic and polymer coatings.
The thermal properties of organic coatings on inorganic nanoparticles, for example biomimetic lipid bilayers, play a key role in their application as intracellular temperature probes. Measuring the core temperature using upconversion thermometry enables direct determination of the bilayer thermal conductivity, opening avenues for studying fundamental membrane biophysical and thermal properties of organic and polymer coatings for a multitude of nanomaterials.
Group 2 innate lymphoid cells (ILC2s) regulate inflammation and immunity in mammalian tissues
. Although ILC2s are found in cancers of these tissues
, their roles in cancer immunity and immunotherapy ...are unclear. Here we show that ILC2s infiltrate pancreatic ductal adenocarcinomas (PDACs) to activate tissue-specific tumour immunity. Interleukin-33 (IL33) activates tumour ILC2s (TILC2s) and CD8
T cells in orthotopic pancreatic tumours but not heterotopic skin tumours in mice to restrict pancreas-specific tumour growth. Resting and activated TILC2s express the inhibitory checkpoint receptor PD-1. Antibody-mediated PD-1 blockade relieves ILC2 cell-intrinsic PD-1 inhibition to expand TILC2s, augment anti-tumour immunity, and enhance tumour control, identifying activated TILC2s as targets of anti-PD-1 immunotherapy. Finally, both PD-1
TILC2s and PD-1
T cells are present in most human PDACs. Our results identify ILC2s as anti-cancer immune cells for PDAC immunotherapy. More broadly, ILC2s emerge as tissue-specific enhancers of cancer immunity that amplify the efficacy of anti-PD-1 immunotherapy. As ILC2s and T cells co-exist in human cancers and share stimulatory and inhibitory pathways, immunotherapeutic strategies to collectively target anti-cancer ILC2s and T cells may be broadly applicable.
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