Powerful Platform Research Articles

The rise and contestation of platform capitalism: Evidence from two food delivery blackouts in Malaysia

The vulnerability and inequality of on-demand gig workers around the world are epitomised by the insecure rights that arise from the legal implications of their status. They are the biggest victims of capital accumulation under platform capitalism, which has skilfully exploited this worker–employer relationship. The resistance of gig workers is essential to counter the powerful structural control structures of platform capitalism. However, theoretical developments in the ideology and resistance of the industrial relations processes that overshadow platform capitalism and empirical studies of them in non-Western contexts are underdeveloped. This study develops an analytical framework in the process of platform capitalism versus gig worker resistance and examines longitudinal resistance and changes and challenges to platform capitalism. A longitudinal analysis of food delivery boycotts for Malaysian p-hailing gig workers in 2022 and 2024 produced different results and complexities in terms of the robustness and continuity of this resistance. The study finds theoretical fluidity in the robustness of workers’ commodification processes under platform capitalism, the focus on organising motives and demands of resistance, and two routes of resistance to the powerful platform balance of power.

NHC‐Catalyzed [3+3] Cycloaddition of 2‐(acetoxymethyl)buta‐2,3‐dienoates with 1 C,3O‐bisnucleophiles

AbstractDiverse transformations of allenoates catalyzed by Lewis bases have emerged as a powerful platform for generating new chemical entities in organic synthesis. Herein, an N‐heterocyclic carbene (NHC) catalyzed [3+3] cyclization of 2‐(acetoxymethyl)buta‐2,3‐dienoates with 1 C,3O‐bisnucleophiles has been developed. This approach provides a facile method to synthesize highly functionalized 4H‐pyran derivatives with a broad substrate scope (31 examples, up to 83 % yield).

A Comparison of the Capture Width and Interaction Factors of WEC Arrays That Are Co-Located with Semi-Submersible-, Spar- and Barge-Supported Floating Offshore Wind Turbines

This research paper explores an approach to enhancing the economic viability of the heaving wave energy converters (WECs) of both cylinder-shaped and torus-shaped devices, by integrating them with four established, floating offshore wind turbines (FOWTs). Specifically, the approach focused on the wave power performance matrix. This integration of WECs and FOWTs not only offers the potential for shared construction and maintenance costs but also presents synergistic advantages in terms of power generation and platform stability. The study began by conducting a comprehensive review of the current State-of-the-Art in co-locating different types of WECs with various foundation platforms for FOWTs, taking into consideration the semi-submersible, spar and barge platforms commonly employed in the offshore wind industry. The research took a unified approach to investigate more and new WEC arrays, totaling 20 configurations across four distinct FOWTs. The scope of this study’s assumption primarily focused on the hydrodynamic wave power performance matrix, without the inclusion of aerodynamic loads. It then compared their outcomes to determine which array demonstrated superior wave energy under the key metrics of total absorbed power, capture width, and interaction factor. Additionally, the investigation could serve to reinforce the ongoing research and development efforts in the allocation of renewable energy resources.

Effect of forced lateral vibration on flow and heat transfer performance within an annular fuel element

The investigation into the thermo-hydraulic characteristics of fuel elements under forced vibration conditions is of paramount importance in the design and application of offshore nuclear power platforms. This study employs a mathematical model of fluid-solid coupling and applies the theory of multi-field synergy to numerically analyze the flow and heat transfer features in an annular fuel element with internal and external double-sided cooling under forced lateral vibration conditions. The synergistic relationship of each flow field parameter is scrutinized for vibration conditions with frequencies ranging from 0 to 10 Hz and amplitudes from 0.005 to 0.2 m. The results demonstrate that increased amplitude and frequency contribute to enhancing the homogeneity of the temperature and velocity field distributions. Notably, the field synergy angles α, β, ψ, and γ attain minimal values at the gaps (X = 8 mm, X = 25 mm). Furthermore, the variation of vibration frequency and amplitude decreases the mean synergistic angle ψ by 5.14 % and 7.9 % and increases the mean field synergistic angle θ by 23.18 % and 31.21 %, respectively. It indicates that the vibration parameters have the least effect on the synergistic angle ψ and the greatest effect on the synergistic angle θ.

Establishment and application of highly efficient regeneration, genetic transformation and genome editing system for cucurbitacins biosynthesis in Hemsleya chinensis

Background Hemsleya Chinensis is a perennial plant in the Cucurbitaceae family containing antibacterial and anti-inflammatory compounds. The lack of genetic transformation systems makes it difficult to verify the functions of genes controlling important traits and conduct molecular breeding in H. chinensis.ResultsHighly efficient calli were induced on MS medium added 1.5 mg·L− 1 6-benzylaminopurine (6-BA) and 0.02 mg·L− 1 1-naphthylacetic acid (NAA) with high efficiency (> 95%). The frequency of shoot induction was increased to 90% with a plant growth regulator combination of 1.5 mg·L− 1 6-BA and 0.1 mg·L− 1 NAA. Our results also showed that 100% of shoot regeneration was achieved in a shoot regeneration medium. Additionally, more than 92% of kanamycin-resistant plants were confirmed. Furthermore, we achieved 42% genome editing efficiency by applying this transformation method to HcOSC6, a gene that catalyzes the formation of cucurbitadienol. HPLC analysis showed OE-HcOSC6 lines exhibited significantly higher cucurbitadienol levels than the genome-edited lines. Transcriptomic analysis revealed that some downstream genes related to cucurbitadienol biosynthesis, such as HcCYP87D20, HcCYP81Q58, and HcSDR34, were up-regulated in OE lines and down-regulated in mutants.ConclusionsHere, we established a process for regeneration, transformation, and genome editing of H. chinensis using stem segments. This provides valuable insight into the underlying molecular mechanisms of medicinal compound production. By combining high-efficiency tissue culture, transformation, and genome editing systems, we provide a powerful platform that supports functional research on molecular mechanisms of secondary metabolism.

Challenges and Prospects of DNA-Encoded Library Data Interpretation.

DNA-encoded library (DEL) technology is a powerful platform for the efficient identification of novel chemical matter in the early drug discovery process enabled by parallel screening of vast libraries of encoded small molecules through affinity selection and deep sequencing. While DEL selections provide rich data sets for computational drug discovery, the underlying technical factors influencing DEL data remain incompletely understood. This review systematically examines the key parameters affecting the chemical information in DEL data and their impact on hit triaging and machine learning integration. The need for rigorous data handling and interpretation is emphasized, with standardized methods being critical for the success of DEL-based approaches. Major challenges include the relationship between sequence counts and binding affinities, frequent hitters, and the influence of factors such as inhomogeneous library composition, DNA damage, and linkers on binding modes. Experimental artifacts, such as those caused by protein immobilization and screening matrix effects, further complicate data interpretation. Recent advancements in using machine learning to denoise DEL data and predict drug candidates are highlighted. This review offers practical guidance on adopting best practices for integrating robust methodologies, comprehensive data analysis, and computational tools to improve the accuracy and efficacy of DEL-driven hit discovery.

Decoding Nucleotide Repeat Expansion Diseases: Novel Insights from Drosophila melanogaster Studies

Drosophila melanogaster usage has provided substantial insights into the pathogenesis of several nucleotide repeat expansion diseases (NREDs), a group of genetic diseases characterized by the abnormal expansion of DNA repeats. Leveraging the genetic simplicity and manipulability of Drosophila, researchers have successfully modeled close to 15 NREDs such as Huntington’s disease (HD), several spinocerebellar ataxias (SCA), and myotonic dystrophies type 1 and 2 (DM1/DM2). These models have been instrumental in characterizing the principal associated molecular mechanisms: protein aggregation, RNA toxicity, and protein function loss, thus recapitulating key features of human disease. Used in chemical and genetic screenings, they also enable us to identify promising small molecules and genetic modifiers that mitigate the toxic effects of expanded repeats. This review summarizes the close to 150 studies performed in this area during the last seven years. The relevant highlights are the achievement of the first fly-based models for some NREDs, the incorporation of new technologies such as CRISPR for developing or evaluating transgenic flies containing repeat expanded motifs, and the evaluation of less understood toxic mechanisms in NREDs such as RAN translation. Overall, Drosophila melanogaster remains a powerful platform for research in NREDs.

Multi-residue analytical method development and dietary exposure risk assessment of 345 pesticides in mango by LC-Q-TOF/MS

Mango is attracting increasing global attention for its superior flavor and nutritional benefits. However, the use of pesticides has resulted in a threat to its quality, safety, and human health due to their inevitable residue. There is an urgent need for advanced technologies that can efficiently and sensitively analyze a wide range of pesticides. In this study, a high-throughput screening and quantification method for 345 pesticides in mango was established by applying a modified QuEChERS method combined with liquid chromatography-quadrupole-time-of-flight mass spectrometry (LC-Q-TOF/MS). A response surface methodology (RSM) optimized the critical parameters for extracting various pesticides in 1% acetic acid-acetonitrile (v/v) using MgSO4, PSA, C18, and GCB as the adsorbents. The proposed method was successfully validated and applied to the quantitative detection of pesticide residues in 73 mango samples from Hainan. The study found pesticide residues in 95.9% of mango samples, of which 3 samples had residue concentrations in excess of the Chinese maximum residue limit. A total of 24 pesticides were detected, with detection percentages ranging from 1.4% (Thiabendazole) to 41.1% (Pyraclostrobin). Considering the possible health risks related to pesticide residues, risk assessment of human exposure to pesticides via intake of mango was evaluated. The acute and chronic dietary exposure risks related to pesticide residues in mango were accepted. In conclusion, this study provides a powerful platform for monitoring multiple pesticides in mango. First, it can promote the rational use of pesticides, and second, it can help consumers to assess the risk of dietary exposure to pesticide residues.

Small scale laboratory monotonic and cyclic pull out testing on grout and resin encapsulated cable bolts

Axial studies on cable bolts can be conducted using various scale testing apparatuses. Large scale testing, while providing a powerful platform for testing, is expensive and time consuming. This study presents details of a small scale pull out testing campaign on cable bolts and investigates the results achieved. Six popular types of cable bolts were studied using an anti rotation apparatus while encapsulated in cementitious grout and resin. The resin samples were tested under both monotonic and cyclic loading patterns. The results showed that grouted bulbed cables require higher displacement to reach their maximum load capacity which is lost at failure, while plain cables tend to hold lower loads for a longer time. Resin samples provided strain softening behaviour with low capacities, particularly in absence of cable indentation or bulbs. Cyclic loading tended to adversely affect the post peak behaviour of the resin samples, especially in the bulbed cables. Failed samples inspected after the testing suggested a non-uniform damage profile along the cable with extensive damage at the exit point transitioning into almost no damage at the entry point.

Enhancing IoT data acquisition efficiency via FPGA-based implementation with OpenCL framework

The increasing demand for real-time data processing in Internet of Things (IoT) applications necessitates the development of efficient and flexible data acquisition systems capable of receiving and processing data from various sensor types. In conjunction with OpenCL, field-programmable gate arrays (FPGAs) have recently emerged as powerful platforms for accelerating data-intensive tasks. This study explored the implementation of an FPGA for data acquisition using OpenCL, aiming to design and implement an efficient data acquisition system tailored for IoT applications. Utilizing OpenCL for FPGA-based data acquisition offers several advantages that contribute to system efficiency, particularly in hardware interfaces between FPGA and external devices used in IoT applications. OpenCL abstracts the complexity of the FPGA hardware interface to external DDR memory for storing temporary data and a communication interface to the host CPU for transferring the collected data and enabling remote access, enabling developers to focus on algorithm design and functionality. To enable data reading from an external analog-to-digital converter (ADC) chip for IoT applications, we developed a component module that utilizes the Avalon-streaming interface and can stream the data to the OpenCL kernel. An experiment was conducted to demonstrate the performance of our proposed design. According to the findings of the experiments, a data acquisition implementation based on an FPGA and OpenCL can simultaneously read analog signals via a multichannel ADC. The proposed design provides a foundation for designing efficient data acquisition solutions, addressing the increasing needs of FPGA-based data acquisition in various IoT environments.

A SIMBA CoMICs Initiative to Cocreating and Disseminating Evidence-Based, Peer-Reviewed Short Videos on Social Media: Mixed Methods Prospective Study.

Social media is a powerful platform for disseminating health information, yet it is often riddled with misinformation. Further, few guidelines exist for producing reliable, peer-reviewed content. This study describes a framework for creating and disseminating evidence-based videos on polycystic ovary syndrome (PCOS) and thyroid conditions to improve health literacy and tackle misinformation. The study aims to evaluate the creation, dissemination, and impact of evidence-based, peer-reviewed short videos on PCOS and thyroid disorders across social media. It also explores the experiences of content creators and assesses audience engagement. This mixed methods prospective study was conducted between December 2022 and May 2023 and comprised five phases: (1) script generation, (2) video creation, (3) cross-platform publication, (4) process evaluation, and (5) impact evaluation. The SIMBA-CoMICs (Simulation via Instant Messaging for Bedside Application-Combined Medical Information Cines) initiative provides a structured process where medical concepts are simplified and converted to visually engaging videos. The initiative recruited medical students interested in making visually appealing and scientifically accurate videos for social media. The students were then guided to create video scripts based on frequently searched PCOS- and thyroid-related topics. Once experts confirmed the accuracy of the scripts, the medical students produced the videos. The videos were checked by clinical experts and experts with lived experience to ensure clarity and engagement. The SIMBA-CoMICs team then guided the students in editing these videos to fit platform requirements before posting them on TikTok, Instagram, YouTube, and Twitter. Engagement metrics were tracked over 2 months. Content creators were interviewed, and thematic analysis was performed to explore their experiences. The 20 videos received 718 likes, 120 shares, and 54,686 views across all platforms, with TikTok (19,458 views) and Twitter (19,678 views) being the most popular. Engagement increased significantly, with follower growth ranging from 5% on Twitter to 89% on TikTok. Thematic analysis of interviews with 8 out of 38 participants revealed 4 key themes: views on social media, advice for using social media, reasons for participating, and reflections on the project. Content creators highlighted the advantages of social media, such as large outreach (12 references), convenience (10 references), and accessibility to opportunities (7 references). Participants appreciated the nonrestrictive participation criteria, convenience (8 references), and the ability to record from home using prewritten scripts (6 references). Further recommendations to improve the content creation experience included awareness of audience demographics (9 references), sharing content on multiple platforms (5 references), and collaborating with organizations (3 references). This study demonstrates the effectiveness of the SIMBA CoMICs initiative in training medical students to create accurate medical information on PCOS and thyroid disorders for social media dissemination. The model offers a scalable solution to combat misinformation and improve health literacy.

Probe-based dual-chip digital loop-mediated isothermal amplification for the simultaneous detection of Staphylococcus aureus and Salmonella enteritidis in livestock and aquatic products

Staphylococcus aureus and Salmonella are common pathogens causing foodborne diseases, posing a serious threat to food safety. Accurate detection of foodborne pathogens is particularly critical. This study developed a probe-based dual-chip digital loop-mediated isothermal amplification (cdLAMP) technique that enables the simultaneous detection of Staphylococcus aureus and Salmonella in food samples. The chip contains 20,000 wells, each with a micro-reaction unit volume of approximately 1 nL. The dual-detection is achieved through the dual-color fluorescence channel equipped on the imaging analyzer. Compared with qPCR, the cdLAMP demonstrates superior sensitivity. In the detection of pure cultures and spiked food samples, the detection limit of two foodborne pathogens is 2 CFU/mL. In the detection of field samples, it is capable of detecting single colonies of both pathogens. The dynamic detection range spans 5 logs. In conclusion, the probe-based cdLAMP technique emerges as a user-friendly tool for detecting foodborne pathogens, providing a powerful platform for food safety testing.

In situ monitoring of CO2$$ {}_2 $$ sorption on polyethylenimine dynamics through broadband dielectric spectroscopy

AbstractChemical reactions between carbon dioxide (CO) and amine have been extensively characterized, however, their influence on the dynamics of polyamines remains largely unexplored. In this work, we compare the dynamics of polyethylenimine (PEI) before and after CO absorption through broadband dielectric spectroscopy (BDS). The molecular processes of bulk PEI are very different from those of thin film PEI, highlighting an interesting interface and nano‐confinement effect. Detailed analyses show CO absorption slows down the PEI dynamics, which is consistent with an elevated glass transition temperature of PEI upon CO absorption from differential scanning calorimetry measurements. Further in situ kinetic measurements demonstrate nonmonotonic changes in relaxation times or dielectric amplitudes of some relaxation processes during CO sorption or desorption, suggesting an intriguing interplay between CO chemisorption and the dynamics of PEI. These results demonstrate that BDS is a powerful platform to resolve the temporal dynamics changes of polyamines for CO capture.

Competing excitation quenching and charge exchange in ultracold Li-Ba+ collisions

Abstract Hybrid atom-ion systems are a rich and powerful platform for studying chemical reactions, as they feature both excellent control over the electronic state preparation and readout as well as a versatile tunability over the scattering energy, ranging from the few-partial wave regime to the quantum regime. In this work, we make use of these excellent control knobs, and present a joint experimental and theoretical study of the collisions of a single 138Ba+ ion prepared in the 5d 2D3/2,5/2 metastable states with a ground state 6Li gas near quantum degeneracy. We show that in contrast to previously reported atom-ion mixtures, several non-radiative processes, including charge exchange, excitation exchange and quenching, compete with each other due to the inherent complexity of the ion-atom molecular structure. We present a full quantum model based on high-level electronic structure calculations involving spin-orbit couplings. Results are in excellent agreement with observations, highlighting the strong coupling between the internal angular momenta and the mechanical rotation of the colliding pair, which is relevant in any other hybrid system composed of an alkali-metal atom and an alkaline-earth ion.

Enhancing Customer Engagement in Insurance Companies Using Salesforce Journey Builder: Tracking Customer Journeys Through Email Open and Ad Clicks

In the competitive insurance industry, understanding and engaging customers throughout their journey is crucial for retaining existing clients and acquiring new ones. Salesforce Marketing Cloud's Journey Builder provides a powerful platform for designing and automating personalized customer experiences. This paper explores how insurance companies can leverage Journey Builder to track and analyze customer interactions such as email opens, and ad clicks. Detailed explanations of journey flows, including the use of Apex code for integrations, are provided. Key Performance Indicators (KPIs) essential for measuring the success of these customer journeys are highlighted. An illustrative example is included to demonstrate the practical application of Journey Builder in enhancing customer engagement within the insurance sector. Keywords: Salesforce Journey Builder, Insurance Industry, Customer Engagement, Marketing Cloud, Apex Code, Customer Journey Tracking, Email Opens, Ad Clicks, KPIs

Optical manipulation of spin states in ultracold magnetic atoms via an inner-shell hz transition

Lanthanides, like erbium and dysprosium, have emerged as powerful platforms for quantum-gas research due to their diverse properties, including a significant large spin manifold in their absolute ground state. However, effectively exploiting the spin richness necessitates precise manipulation of spin populations, a challenge yet to be fully addressed in this class of atomic species. In this work, we present an all-optical method for deterministically controlling the spin composition of a dipolar bosonic erbium gas, based on a clocklike transition in the telecom window at 1299nm. The atoms can be prepared in just a few tens of microseconds in any spin-state composition using a sequence of Rabi-pulse pairs, selectively coupling Zeeman sublevels of the ground state with those of the long-lived clocklike state. Finally, we demonstrate that this transition can also be used to create spin-selective light shifts, thus fully suppressing spin-exchange collisions. These experimental results unlock exciting possibilities for implementing advanced spin models in isolated, clean, and fully controllable lattice systems. Published by the American Physical Society 2024

Framework and policy recommendations for the design of metaverse platforms in support of Saudi Vision 2030

Purpose This paper suggests a framework that describes the critical features and design elements that should be considered when creating a metaverse platform. This metaverse framework will assist in achieving the goals of Saudi Vision 2030, specifically in making the applied technology transformation goal a reality. In addition, this paper offers valuable recommendations and insights for policymakers to guarantee the actualization of the digital transformation associated with the metaverse in Saudi Vision 2030. Design/methodology/approach This research plans to address the gaps by conducting a thorough literature review to examine the characteristics and design elements of the latest metaverse platforms. It proposes a suggested framework that discusses the distinctive features that should be considered when creating any metaverse platform. In addition, the research provides policymakers with important recommendations and insights to ensure effective contribution to the digital transformation goals of Saudi Vision 2030, thereby supporting the scientific development of the metaverse platform Findings After a deep review of the literature, this paper proposes a conceptual framework as described in Figure 1, which identifies the most important design features and elements that need to be considered when building a metaverse platform, which will be a critical component of the digital infrastructure. These design elements include immersive engineering, accessibility, privacy, security, interoperability, digital assets and regulations. They are essential to developing a powerful metaverse platform that has all the features of this virtual reality environment. Immersive engineering concepts in the metaverse world aim to improve user experience by creating more realistic, interactive and engaging virtual environments. Research limitations/implications The findings of this study provide valuable insights into the development and implementation of metaverse platforms in Saudi Arabia by proposing a suggested framework that discusses the distinctive features that should be considered when creating metaverse platform and provides policymakers with some important recommendations and insights to ensure that effectively contributes to the realization of digital transformation, which is the one of Saudi Vision 2030. This paper carries several implications. First, this paper has an impact on future technology research, as it presented the most important design elements and advanced technologies for implementing metaverse platforms. In addition, it sheds the light on the limitations faced by Saudi Arabia metaverse platforms. Second, this research also has an impact on public policy in Saudi Arabia. This paper presented the most important recommendations that need to be taken into consideration when applying metaverse in Saudi Arabia [see section Recommendation]. Finally, it is seen that the presence of the metaverse not only facilitates but also supports digital transformation and the application of new technology. This research also has an indirect impact on society and the economy, as it is delineating the enhancements within these environments following the metaverse’s adoption, as elucidated in section Discussion. Social implications Metaverse platforms have societal impacts such as social engagement, entertainment, education, accessibility and cultural promotion. They can enhance inclusivity, improve well-being, showcase cultural heritage and boost tourism-related industries. Originality/value Proposed framework for metaverse platforms: The research proposes a suggested framework that outlines the distinctive features necessary for creating metaverse platforms. This framework is based on a thorough literature review and aims to guide the development of metaverse platforms that can support the objectives of Saudi Vision 2030. Policy recommendations: The study offers important recommendations and insights for policymakers. These recommendations are designed to ensure that policymakers can effectively contribute to the realization of the digital transformation goals of Saudi Vision 2030, particularly in the context of applied technology transformation.

Engineered Multifunctional BioHJzyme via Tuning D‐Band Center for Postoperative Infected Wound Regeneration of Tumor Resection

AbstractThe catalytic therapy for abundant •OH, 1O2, and •O2− provides an efficient tactic and methodology for rapid tumor/bacteria killing, whereas the limitation is focused on the catalytic efficiency owing to the in‐built energy band of catalytic materials. Thus, d‐band center tuning BioHJzyme is devised, which is composed of zinc tellurate/manganese dioxide anchored by glucose oxidase (GOx) with anti‐tumor and anti‐bacteria properties for postoperative infected wound regeneration of tumor. The GOx depletes glucose to produce H2O2, intercepting the glucose metabolism. The D‐BioHJzyme can catalyze the produced H2O2 to highly lethal •OH with POD‐mimetic activity owing to the tunned d‐band center strategy decreasing the adsorption energy of the intermediate in the catalytical process, while the oxygen originated from H2O2 and Mn2+ can be catalyzed into 1O2. The GPx‐mimetic activity of it can impair the antioxidant system of tumor. In vivo studies show that the BioHJzyme exhibits robust abilities against bacteria and tumors by •OH/1O2 production and promotes the apoptosis owing the Te. Besides, the BioHJzyme can accelerate cutaneous regeneration by M1/M2 regulation and the angiogenesis/collagen deposition. This work enlightens a powerful platform for the remedy of postoperative infected wound regeneration of tumor resection using an engineered BioHJzyme.

Boosting Light-Matter Interactions in Plasmonic Nanogaps.

Plasmonic nanogaps in strongly coupled metal nanostructures can confine light to nanoscale regions, leading to huge electric field enhancement. This unique capability makes plasmonic nanogaps powerful platforms for boosting light-matter interactions, thereby enabling the rapid development of novel phenomena and applications. This review traces the progress of nanogap systems characterized by well-defined morphologies, controllable optical responses, and a focus on achieving extreme performance. The properties of plasmonic gap modes in far-field resonance and near-field enhancement are explored and a detailed comparative analysis of nanogap fabrication techniques down to sub-nanometer scales is provided, including bottom-up, top-down, and their combined approaches. Additionally, recent advancements and applications across various frontier research areas are highlighted, including surface-enhanced spectroscopy, plasmon-exciton strong coupling, nonlinear optics, optoelectronic devices, and other applications beyond photonics. Finally, the challenges and promising emerging directions in the field are discussed, such as light-driven atomic effects, molecular optomechanics, and alternative new materials.

Boolean Computation in Single-Transistor Neuron.

Brain neurons exhibit far more sophisticated and powerful information-processing capabilities than the simple integrators commonly modeled in neuromorphic computing. A biological neuron can in fact efficiently perform Boolean algebra, including linear nonseparable operations. Traditional logic circuits require more than a dozen transistors combined as NOT, AND, and OR gates to implement XOR. Lacking biological competency, artificial neural networks require multilayered solutions to exercise XOR operation. Here, it is shown that a single-transistor neuron, harnessing the intrinsic ambipolarity of graphene and ionic filamentary dynamics, can enable in situ reconfigurable multiple Boolean operations from linear separable to linear nonseparable in an ultra-compact design. By leveraging the spatiotemporal integration of inputs, bio-realistic spiking-dependent Boolean computation is fully realized, rivaling the efficiency of a human brain. Furthermore, a soft-XOR-based neural network via algorithm-hardware co-design, showcasing substantial performance improvement, is demonstrated. These results demonstrate how the artificial neuron, in the ultra-compact form of a single transistor, may function as a powerful platform for Boolean operations. These findings are anticipated to be a starting point for implementing more sophisticated computations at the individual transistor neuron level, leading to super-scalable neural networks for resource-efficient brain-inspired information processing.