This study explores a handheld, battery-operated e-ink device displaying Google Scholar citation statistics. The StatCounter places academic metrics into the flow of daily life rather than a desktop context. The work draws on a first-person, longitudinal auto-ethnographic inquiry examining how constant access to scholarly metrics influences motivation, attention, reflection, and emotional responses across work and non-work settings. The ambient proximity and pervasive availability of scholarly metrics invites frequent micro-checks, short reflective pauses, but also introduces moments of second-guessing when numbers drop or stagnate. Carrying the device prompts new narratives about academic identity, including a sense of companionship during travel and periods away from the office. Over time, the presence of the device turns metrics from an occasional reference into an ambient background of scholarly life. The study contributes insight into how situated, embodied access to academic metrics reshapes their meaning, and frames opportunities for designing tools that engage with scholarly evaluation in reflective ways.
Advances in the next generation of mesoscopic electronics require an understanding of topological phases in inhomogeneous media and the principles that govern them. Motivated by the nature of motifs available in printable conducting inks, we introduce and study quantum transport in a minimal model that describes a bundle of one-dimensional metallic wires that are randomly interconnected by semiconducting chains. Each of these interconnects is represented by a Su-Schrieffer-Heeger chain, which can reside in either a trivial or a topological phase. Using a tight-binding approach, we show that such a system can transit from an insulating phase to a robust metallic phase as the interconnects undergo a transition from a trivial to a topological phase. In the latter, despite the random interconnectedness, the metal evades Anderson localization and exhibits a ballistic conductance that scales linearly with the number of wires. We show that this behavior originates from hopping renormalization in the wire network. The zero-energy modes of the topological interconnects act as effective random dimers, giving rise to an energy-dependent localization length that diverges as $\sim 1/E^2$. Our w
Although some of the human senses can nowadays be replaced by low-cost electronic sensors such as microphones and image sensors, a compact low-cost electronic nose (E-nose) remains elusive. In this work, an E-nose is presented that can capacitively detect volatile organic compounds (VOCs). The E-nose consists of an array of 1024 capacitive microelectrodes on a complementary metal-oxide-semiconductor (CMOS) chip, functionalized by inkjet printing. The pixels are coated with a UV-curable ink and metal-organic frameworks (MOFs: ZIF-8, MIL-101(Cr), MIL-140A) to create chemically diverse microdomains that generate gas-specific response patterns through adsorption-driven dielectric loading. ZIF-8 exhibits the highest response to 2-butanone, whereas the UV-curable layer responds most strongly to toluene; both show low cross-sensitivity to water vapor, enabling operation under humid conditions. After calibration in pure gases, reproducible responses to controlled binary mixtures of toluene and 2-butanone are observed. The device operates at low power, combines a large 1024-pixel array with CMOS integration, and offers application-specific functionalization by inkjet printing, providing bot
This paper presents a comprehensive analysis of the energy consumption characteristics of a Silicon (Si)-based Reconfigurable IoT (RIoT) node developed in the initial phase of the SUPERIOT project, focusing on key operating states, including Bluetooth Low Energy (BLE) communication, Narrow-Band Visible Light Communication (NBVLC), sensing, and E-ink display. Extensive measurements were conducted to establish a detailed energy profile, which serves as a benchmark for evaluating the effectiveness of subsequent optimizations and future node iterations. To minimize the energy consumption, multiple optimizations were implemented at both the software and hardware levels, achieving a reduction of over 60% in total energy usage through software modifications alone. Further improvements were realized by optimizing the E-ink display driving waveform and implementing a very low-power mode for non-communication activities. Based on the measured data, three measurement-based energy consumption models were developed to characterize the energy behavior of the node under: (i) normal, unoptimized operation, (ii) low-power, software-optimized operation, and (iii) very low-power, hardware-optimized o
Energy efficiency has emerged as a defining constraint in the evolution of sustainable Internet of Things (IoT) networks. This work moves beyond simulation-based or device-centric studies to deliver measurement-driven, network-level smart energy analysis. The proposed system enables end-to-end visibility of energy flows across distributed IoT infrastructures, uniting Bluetooth Low Energy (BLE) and Visible Light Communication (VLC) modes with environmental sensing and E-ink display subsystems under a unified profiling and prediction platform. Through automated, time-synchronized instrumentation, the framework captures fine-grained energy dynamics across both node and gateway layers. We developed a suite of tools that generate energy datasets for IoT ecosystems, addressing the scarcity of such data and enabling AI-based predictive and adaptive energy optimization. Validated within a network-level IoT testbed, the approach demonstrates robust performance under real operating conditions.
Large-scale Internet of Things (IoT) applications, such as asset tracking and remote sensing, demand multi-year battery lifetimes to minimize maintenance and operational costs. Traditional wireless protocols often employ duty cycling, introducing a tradeoff between latency and idle consumption - both unsuitable for event-driven and ultra-low power systems. A promising approach to address these issues is the integration of always-on wake-up radios (WuRs). They provide asynchronous, ultra-low power communication to overcome these constraints. This paper presents WakeMod, an open-source wake-up transceiver module for the 868MHz ISM band. Designed for easy integration and ultra-low power consumption, it leverages the -75dBm sensitive FH101RF WuR. WakeMod achieves a low idle power consumption of 6.9uW while maintaining responsiveness with a sensitivity of -72.6dBm. Reception of a wake-up call is possible from up to 130m of distance with a -2.1dBi antenna, consuming 17.7uJ with a latency below 54.3ms. WakeMod's capabilities have further been demonstrated in an e-ink price tag application, achieving 7.17uW idle consumption and enabling an estimated 8-year battery life with daily updates o
Assessing resection margins is central to pathological specimen evaluation and has profound implications for patient outcomes. Current practice employs physical inking, which is applied variably, and cautery artifacts can obscure the true margin on histological sections. We present a virtual inking network (VIN) that autonomously localizes the surgical cut surface on whole-slide images, reducing reliance on inks and standardizing margin-focused review. VIN uses a frozen foundation model as the feature extractor and a compact two-layer multilayer perceptron trained for patch-level classification of cautery-consistent features. The dataset comprised 120 hematoxylin and eosin (H&E) stained slides from 12 human tonsil tissue blocks, resulting in ~2 TB of uncompressed raw image data, where a board-certified pathologist provided boundary annotations. In blind testing with 20 slides from previously unseen blocks, VIN produced coherent margin overlays that qualitatively aligned with expert annotations across serial sections. Quantitatively, region-level accuracy was ~73.3% across the test set, with errors largely confined to limited areas that did not disrupt continuity of the whole-sl
This paper presents the design and initial assessment of a novel device that uses generative AI to facilitate creative ideation, inspiration, and reflective thought. Inspired by magnetic poetry, which was originally designed to help overcome writer's block, the device allows participants to compose short poetic texts from a limited vocabulary by physically placing words on the device's surface. Upon composing the text, the system employs a large language model (LLM) to generate a response, displayed on an e-ink screen. We explored various strategies for internally sequencing prompts to foster creative thinking, including analogy, allegorical interpretations, and ideation. We installed the device in our research laboratory for two weeks and held a focus group at the conclusion to evaluate the design. The design choice to limit interactions with the LLM to poetic text, coupled with the tactile experience of assembling the poem, fostered a deeper and more enjoyable engagement with the LLM compared to traditional chatbot or screen-based interactions. This approach gives users the opportunity to reflect on the AI-generated responses in a manner conducive to creative thought.
Text-to-image generation has recently witnessed remarkable achievements. We introduce a text-conditional image diffusion model, termed RAPHAEL, to generate highly artistic images, which accurately portray the text prompts, encompassing multiple nouns, adjectives, and verbs. This is achieved by stacking tens of mixture-of-experts (MoEs) layers, i.e., space-MoE and time-MoE layers, enabling billions of diffusion paths (routes) from the network input to the output. Each path intuitively functions as a "painter" for depicting a particular textual concept onto a specified image region at a diffusion timestep. Comprehensive experiments reveal that RAPHAEL outperforms recent cutting-edge models, such as Stable Diffusion, ERNIE-ViLG 2.0, DeepFloyd, and DALL-E 2, in terms of both image quality and aesthetic appeal. Firstly, RAPHAEL exhibits superior performance in switching images across diverse styles, such as Japanese comics, realism, cyberpunk, and ink illustration. Secondly, a single model with three billion parameters, trained on 1,000 A100 GPUs for two months, achieves a state-of-the-art zero-shot FID score of 6.61 on the COCO dataset. Furthermore, RAPHAEL significantly surpasses its
Stabilization and dispersion of electrical charge by colloids in non-polar media, such as nano-particles or inverse micelles, is significant for a variety of chemical and technological applications, ranging from drug delivery to e-ink. Many applications require knowledge about concentrations near the solid|liquid interface and the bulk, particularly in media where colloids exhibit spontaneous charging properties. By modification of the mean field equations to include the finite size effects that are typical in concentrated electrolytes along with disproportionation kinetics, and by considering high potentials, it is possible to evaluate the width of the condensed double layers near planar electrodes and the bulk concentrations of colloids at steady state. These quantities also provide an estimate of the minimum initial colloid concentration that is required to support electroneutrality in the dispersion bulk, and thus provide insights into the quasi-steady state currents that have been observed in inverse micellar media.
Indoor light is known to be a new energy source to power uW low consumption wireless sensor networks (WSNs). For wireless electronic devices that consume tens of mW, it is still challenging to harvest this amount of power in a low light indoor environment. The challenge comes from the fact that the irradiance is low, as well the fact that the source is a multi-spectral direct, reflective, and scattered mix of artificial and natural light, with intensity and composition varying in time. This article describes a method providing an evaluation of the potentially harvestable energy in real light environments. Measurements of indoor light spectral composition in real condition and optoelectrical characteristics of photovoltaic converters in a controlled environment are base on the method s calculation model. Real harvester prototypes based on GaAs commercial photovoltaic cells and power management integrated circuit, powering a commercial wireless e-ink display, have been conceived to compare with the model calculations. For two days of experimentation, model calculations achieve a mean absolute percentage error (MAPE) of 2 percents and 6 percents for Day 1 and Day 2, respectively. A me
Scientists have found that staple-shaped particles can tangle together to create a material that is both strong and flexible。 Unlike conventional materials, these particles can be locked into a sturdy structure or rapidly unraveled using vibrations。 The unusual behavior could open the door to recyclable buildings, reconfigurable structures, and eve
A surprisingly simple fuel modification could help tackle one of diesel engines’ biggest problems: pollution。 Researchers reviewing studies from around the world found that mixing small amounts of water into diesel fuel can dramatically reduce harmful emissions, including nitrogen oxides and soot, while maintaining or even improving engine efficien
A strange gamma-ray glow at the center of the Milky Way has long sparked debate over whether it comes from hidden neutron stars or elusive dark matter。 By applying machine learning to more than a million simulated observations, researchers included photon energy data for the first time and reached a different conclusion than many earlier studies
Two newly confirmed "super-puff" planets are so diffuse that they are less dense than cotton candy, despite being about the size of Jupiter。 Their rare orbital relationship and enormous, lightweight atmospheres could provide valuable clues about how some of the strangest planets in the galaxy come to exist
Researchers found that a Chinese sodium-ion battery performs far better than expected, with production quality and design features comparable to Tesla’s batteries。 If engineers can improve cold-weather charging and energy density, sodium could become a cheaper and more abundant alternative to lithium for EVs and large-scale energy storage
It only works for a few divisions thanks to a lot of added materials
“We will own nothing, it's truly sad
A rare meteorite has revealed evidence of a massive lost world that once orbited the young Sun before being destroyed in a catastrophic collision。 The discovery suggests some early planets formed from dramatically different materials than Earth and Mars, rewriting part of the solar system’s origin story