bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation of Time-Domain Thermo-Reflectance Experiments Using the Anisotropic Fourier Heat Conduction Equation and the Phonon Boltzmann Transport Equation
Authors: Saurav Siddharth , Mazumder Sandip
Published: September 2024

The anisotropic Fourier Heat Conduction Equation (FHCE) and the multidimensional phonon Boltzmann Transport Equation (BTE) were solved numerically in cylindrical coordinates and in time domain to simulate a Time Domain Thermo-Reflectance (TDTR) experimental silicon/aluminum substrate/transducer setup. The out-of-phase response of the probe laser was predicted at various beam offset distances for a pump laser pulse frequency of 80 MHz and modulation frequency of 10 MHz and compared against experimental measurements. The isotropic FHCE was also solved for comparison. Results show that the isotropic FHCE with bulk thermal conductivity of 145 W/m/K significantly underpredicts the out-of-phase temperature difference, particularly at smaller beam offsets. With an isotropic thermal conductivity of 105 W/m/K, the computed results match experimental data at smaller beam offsets well, but overpredicts the experimental data at larger beam offsets. An almost-perfect match is obtained by using an anisotropic thermal conductivity wherein the radial (in-plane) thermal conductivity is set to 90 W/m/K and the axial (through-plane) conductivity is set to 130 W/m/K. The multidimensional frequency and polarization dependent phonon BTE is next solved. The BTE results for the out-of-phase temperature difference match experimental observations well at small and intermediate beam offsets, but overpredicts the experimental data at larger beam offsets. FHCE results are fitted to the BTE predictions, and the extracted (best fit) thermal conductivity is found to be 105 W/m/K.
Assessment of Optimal Fin Structure and Shroud Size in Fan-Cooled Heat Sinks for Next-Generation EV Battery Chargers
Authors: Najafpour Sahand , Botting Chris , Bahrami Majid
Published: September 2024

As next-generation battery chargers become more compact yet offer higher power outputs, efficient cooling methods are crucial. Air-cooled heat sinks are gaining prominence due to the growing demand for high-performance EV battery chargers. This study delves into the impact of shroud size and optimal fin configuration in the axial fan impingement cooling technique. Experimental study is performed on the Delta-Q XV3300 battery charger, with four distinct configurations tested, reflective of current market trends: i) no shroud, ii) half-size shroud, iii) full shroud, and iv) a Delta-Q production shroud. Results indicate that the shroud size has negligible effect on the heat sink’s thermal performance, with shrouds directing airflow through the fin array, resulting in up to a 5% temperature decrease on the heat sink’s periphery, in contrast to the no-shroud scenario. Notably, the Delta-Q production shroud lagged in performance, primarily due to its integrated “fan guards.” Furthermore, a numerical model is developed to compare various fin arrangements under the fan, namely bare fin, pin fin, and vane-shaped designs—. Under assumptions of a level heatsink skyline and a uniform heat flux boundary condition, both pin fin and vane-shaped designs surpass the bare fin configuration in thermal efficiency by 7.3% and 5.1%, respectively. At the end, a new heatsink design is provided for enhancing the cooling efficiency, especially when a protective wall shields the connectors. The proposed design introduces an additional wall on the opposite side to curb excessive airflow escape. Additionally, integrating converging radial fins that gradually transition to parallel orientations reduces air circulation, thereby decreasing temperature variances by 7% to 25% across various heat-intensive regions, respectively.
Influence of Stirring in Seawater Freeze Desalination Inside a Cooled Jacketed Crystallizer
Authors: Zhang Hongtao , Savvopoulos Symeon , Islam Md Didarul , Janajreh Isam
Published: September 2024

This study investigates waste brine freeze desalination within a designed, cooled, jacketed crystallizer system. The study combines experimental findings with numerical simulation to interpret the feasibility of this approach. In the experimental phase, actual waste brine samples were collected from several seawater reverse osmosis (RO) units across the Arabian Gulf and analyzed for their ion composition. Furthermore, synthetic concentrated NaCl solution freezing inside the jacketed crystallizer by radial freezing from outer to center with stirring is carried out. The experimental results confirm that stirring enhances desalination efficiency, and it is found that 30 rpm’s efficiency outperforms 60 rpm. Moreover, a computational fluid dynamics (CFD) model of the crystallizer was also developed to understand heat and mass transfer during the freezing process under various conditions. The developed model captures the salinity growth trend, although discrepancies likely result from imperfect insulation at the top and bottom of the crystallizer. The results highlight the crucial role of stirring in homogenizing concentrated brine, effectively preventing the formation of highly concentrated layers at the freezing front. This research underscores the promise of seawater/waste brine freeze desalination as a sustainable and efficient solution for global freshwater scarcity.
Numerical Analysis Comparing the Thermal Performance of Two Solar Chimneys Combined With Thermal Energy Storage Made of Phase Change Materials Embedded in a Metal Foam
Authors: Buonomo Bernardo , Famoso Tommaso Antonio , Golia Maria Rita , Manca Oronzio , Nardini Sergio , Plomitallo Renato Elpidio
Published: September 2024

The two-dimensional numerical analysis of a solar chimney integrated with a phase change material (PCM) wall on a south face of building is the primary goal of this work. While the chimney has a converging channel with a vertical absorbing wall and an angled glass plate, the absorbing capacity wall employs PCM and metal foam.

To identify the most efficient thermal performance, four configurations of the absorbing capacity wall — which serves as a latent thermal energy storage — are studied. The numerical study uses a transient assessment of a two-dimensional airflow model with the Boussinesq assumption and the k-ε turbulence model, where the chimney channel dimensions are given. The finite volume method in Ansys-Fluent is utilized for simulations.

The study examines the thermal and fluid dynamic performance of the phase change material absorbing wall at varying thicknesses. Simulations based on average days in June and December in Aversa, Italy, use aluminium foam-embedded paraffin wax with melting temperatures of 31°C and 42°C. Results include temperature distributions, air velocity, channel profiles, liquid fractions. Understanding the thermal differences between different PCM with metal foam and optimising the energy conversion system are the two main goals of the evaluation.
Inferring Flow Boiling Interfacial Shear Stress Using Physics Informed Neural Networks From Control Volume Models
Authors: Pirnstill Logan M. , Kharangate Chirag
Published: September 2024

Flow boiling has been identified as a promising method for heat acquisition in thermal management technologies. Common issues preventing flow boiling technology from being widely used are variable heat transfer characteristics as well as large pressure drops along the flow boiling channels. These complications arise from the phase change phenomenon and can be rather difficult to predict and characterize. A common approach to predict these phenomena are semi-empirical models, due to their simplicity and basis in well-established physics. These types of models employ a control volume approach where the conservation of mass, momentum, and energy are applied to solve for average quantities like mean vapor and liquid velocities. They are promising as they directly embed physics into solutions while also utilizing correlation-based methods to directly compute complex flow quantities like shear stress. As a result of utilizing correlations to fill in for hard to measure quantities, semi-empirical models act as a prelude to data driven methods in physical modelling. Physics informed neural networks (PINNs) are a recent advancement in the data-driven science and engineering field that also accurately model physics problems using data-driven techniques. In this paper we replace the semi-empirically derived interfacial shear stress term in the momentum equations, which often poorly predicts the interfacial shear stress, with an interfacial shear term informed by a PINN. In general, we find that the PINN is better at fitting the interfacial shear stress term than well-known correlations, with the added benefit of directly being able to include data into the modelling process. This paper demonstrates the effectiveness of data-driven solutions to differential equations for inferring complex flow quantities in under-determined systems, such as these semi-empirical models. Furthermore, applications of PINNs to flow boiling systems will aid in the advancement of thermal management technologies by improving model reliability and incorporation of experimental data directly into the computation process.
Heat Transfer Characteristics of Oscillating Electrohydrodynamic Liquid Flow
Authors: Castaneda Alexander J. , Yagoobi Jamal
Published: September 2024

The current trend in electronic systems sees them continue to develop at a remarkable pace and, thus, they become smaller, more complex, and require larger power densities to operate. Similarly, associated thermal management technologies that support them must continue to advance. The existing world of thermal management systems is typically comprised of heat pipes and loops to dissipate heat from electronics. These systems, despite their ability to transfer heat, are met with the challenge of overcoming mechanical deterioration and are often limited to being passive thermal management methods. Electrohydrodynamic (EHD) conduction pumping is an innovative, low power, and non-mechanical method to pump fluids for thermal management. In addition to these advantages, EHD is also simple in design and is controllable, as it can be integrated into complex and programmable scenarios for optimal thermal management. EHD conduction pumping in unidirectional flows has been successfully explored as a method of enhancing heat transfer and managing fluid flows in both space and terrestrial applications. By designing EHD conduction pumping to oscillate flows, a system is expected to experience further enhanced heat transfer than typical unidirectional pumping due to mixing. This study numerically investigates the concept of using EHD conduction pumping to oscillate a liquid flow to observe the effects on fluid flow behavior, using Novec 7100 as the working fluid. Based on the results, which include enhanced vorticity, and pulsating flow, it is expected that this technology can be used to enhance heat transport. The results of this simulation further support those found in previous experimental studies, and they continue to support the future of EHD conduction pumping as a technology to augment next generation cooling technologies.
Creating Fluid Flow Through Bubble Squeezing in Tapered Microgap
Authors: Shukla Maharshi Y. , Pal Divyprakash , Perez-Raya Isaac , Kandlikar Satish G.
Published: September 2024

A taper microgap is a wedge-shaped cavity placed over a heater surface for enhancing pool and flow boiling heat transfer. Extensive experimental, numerical, and theoretical investigations show that the tapered microgap augments vapor bubbles and liquid movement to enhance critical heat flux and heat transfer coefficient. The current work studies the effect of bubble squeezing with simulated air flow where a bubble grows near the diverging end of a 5° tapered microgap. The bubbles are air-injected at flowrates of 3, 15, and 30 ml/min, and their movement is studied numerically and validated experimentally using a newly developed Arduino Mega 2560-based electromechanical test bench. Qualitative experimental testing validates the numerical method and finds air-injected bubbles leaving from the diverging end of the tapered microgap while drawing working fluid in its wake. In an actual heat transfer system equipped with a tapered microgap, the drawn working fluid will create a flow-like macroconvective current over the heater surface that enhances heat transfer. Results from the current study can be used to expedite tapered microgap development.
Impact of Clean Energy on the Carbon Emission Structure of the Power Grid in China
Authors: Li Xingsheng , Li Wei , Dong Yahong , Sherif S. A.
Published: September 2024

Achieving carbon neutrality is being accelerated by the gradual replacement of traditional high-emission power generation systems with wind and solar energy systems. This development will curb the emission of greenhouse gases (GHGs). This step is especially important in the power transmission and distribution (T&D) network. The purpose of this study is to investigate GHG emissions in the T&D network based on life cycle assessment (LCA). A life cycle carbon assessment (LCCA) model of the T&D network is developed and presented. The inventory of a typical T&D system is presented and the GHG emissions intensity of that system is calculated. It is found that the intensity of GHG emissions of a typical T&D system in China is around 66 gCO2 eq/kWh in 2012. This amount has decreased to around 32 gCO2 eq/kWh in 2022, with the emissions structure remaining mostly unchanged. Electricity loss due to the transmission in a typical T&D network has been found to be responsible for the majority of GHG emissions. A prediction of the timing of carbon neutrality indicates that T&D GHG emissions will account for at least 16% of the total GHG emissions in the power grid in China by the year 2060. This is because solar and wind energy will account for most of the electricity generated.
Thermal Tensegrity
Authors: Conneely Grace E. , Kinzel Gary L. , Juliano Thomas J. , Kinzel Edward C.
Published: September 2024

Several practical problems require high thermal resistance and minimum compliance. An example is a high-temperature computer-controlled stage for additive manufacturing, which must be heated and precisely positioned. In this case, the heat transfer from the build plate must be limited to minimize the heating of the computer-controlled stage. The simplest option, supporting the build plate using low thermal conductivity risers, introduces a tradeoff between the heat transfer to the stage and the mechanical stiffness of the system. We explore an alternative using the concept of tensegrity, a term coined by Buckminster Fuller for structures that are separated only by members in tension. Other objects can be loaded under compression or bending. Because the tensile members can be very slender (for example stainless steel cabling) the overall thermal resistance can be reduced while increasing the mechanical stiffness. We present a solution to a specific problem including practical fabrication considerations and design for manufacturability. We then generalize the design of tensegrity structures to high-temperature thermal applications. Besides the additive manufacturing system, the concept of thermal tensegrity has applications to furnace or kiln design and even connecting high-temperature aircraft skins to structural elements.
Water Depth and Surface Area Extension Correlation Effect on Single Basin Solar Still
Authors: Phillips Agboola
Published: September 2024

This work examines the effect of 4kg, 6kg, 8kg, and 10kg water depth on the efficiency of a passive (single basin solar still) coupled with surface area extension (Fins). Three different configurations of the system were designed and fabricated as follows: SBSS, SBSS4, and SBSS8.

These configurations were studied concurrently while data on the water vapors temperature, absorber plate temperature, covered glass temperature, Ambient temperature, solar irradiation, and daily water production were collected. The empirical findings show that in terms of daily productivity, the SBSS8 performed best with 3.7 kg/m2/day with a water depth of 6kg while SBSS produced the least with 2.3 kg/m2/day with a water depth of 8kg.
A novel GFP-based strategy to quantitate cellular spatial associations in HSV-1 viral pathogenesis
Authors: Arya Deepak , Jaggi Ujjaldeep , Wang Shaohui , Tormanen Kati , Che Mingtian , Mahov Simeon , Jin Ling , Ghiasi Homayon
Published: September 2024

Periodic reactivation of herpes simplex virus type 1 (HSV-1) triggers immune responses that result in corneal scarring (CS), known as herpes stromal keratitis (HSK). Despite considerable research, fully understanding HSK and eliminating it remains challenging due to a lack of comprehensive analysis of HSV-1-infected immune cells in both corneas and trigeminal ganglia (TG). We engineered a recombinant HSV-1 expressing green fluorescent protein (GFP) in the virulent McKrae virus strain that does not require corneal scarification for efficient virus replication (GFP-McKrae). Next-generation sequencing (NGS) analysis, along with
in vitro
and
in vivo
assays, showed that GFP-McKrae virus was similar to WT-McKrae virus. Furthermore, corneal cells infected with GFP-McKrae were quantitatively analyzed using image mass cytometry (IMC). The single-cell reconstruction data generated cellular maps of corneas based on the expression of 25 immune cell markers in GFP-McKrae-infected mice. Corneas from mock control mice showed the presence of T cells and macrophages, whereas corneas from GFP-McKrae-infected mice on days 3 and 5 post-infection (PI) exhibited increased immune cells. Notably, on day 3 PI, increased GFP expression was observed in closely situated clusters of DCs, macrophages, and epithelial cells. By day 5 PI, macrophages and T cells became prominent. Finally, immunostaining methods detected HSV-1 or GFP and gD proteins in latently infected TG. This study presents a valuable strategy for identifying cellular spatial associations in viral pathogenesis and holds promise for future therapeutic applications.

IMPORTANCE

The goal of this study was to establish quantitative approaches to analyze immune cell markers in HSV-1-infected intact corneas and trigeminal ganglia from primary and latently infected mice. This allowed us to define spatial and temporal interactions between specific immune cells and their potential roles in virus replication and latency. To accomplish this important goal, we took advantage of the utility of GFP-McKrae virus as a valuable research tool while also highlighting its potential to uncover previously unrecognized cell types that play pivotal roles in HSV-1 replication and latency. Such insights will pave the way for developing targeted therapeutic approaches to tackle HSV-1 infections more effectively.
Identification of reactive
Borrelia burgdorferi
peptides associated with Lyme disease
Authors: Tokarz Rafal , Guo Cheng , Sanchez-Vicente Santiago , Horn Elizabeth , Eschman Aleah , Turk Siu Ping , Lipkin W. Ian , Marques Adriana
Published: September 2024

Borrelia burgdorferi,
the agent of Lyme disease, is estimated to cause >400,000 annual infections in the United States. Serology is the primary laboratory method to support the diagnosis of Lyme disease, but current methods have intrinsic limitations that require alternative approaches or targets. We used a high-density peptide array that contains >90,000 short overlapping peptides to catalog immunoreactive linear epitopes from >60 primary antigens of
B. burgdorferi
. We then pursued a machine learning approach to identify immunoreactive peptide panels that provide optimal Lyme disease serodiagnosis and can differentiate antibody responses at various stages of disease. We examined 226 serum samples from the Lyme Biobank and the National Institutes of Health, which included sera from 110 individuals diagnosed with Lyme disease, 31 probable cases from symptomatic individuals, and 85 healthy controls. Cases were grouped based on disease stage and presentation and included individuals with early localized, early disseminated, and late Lyme disease. We identified a peptide panel originating from 14 different epitopes that differentiated cases versus controls, whereas another peptide panel built from 12 unique epitopes differentiated subjects with various disease manifestations. Our method demonstrated an improvement in
B. burgdorferi
antibody detection over the current two-tiered testing approach and confirmed the key diagnostic role of VlsE and FlaB antigens at all stages of Lyme disease. We also uncovered epitopes that triggered a temporal antibody response that was useful for differentiation of early and late disease. Our findings can be used to streamline serologic targets and improve antibody-based diagnosis of Lyme disease.

IMPORTANCE

Serology is the primary method of Lyme disease diagnosis, but this approach has limitations, particularly early in disease. Currently employed antibody detection assays can be improved by the identification of alternative immunodominant epitopes and the selection of optimal diagnostic targets. We employed high-density peptide arrays that enabled precise epitope mapping for a wide range of
B. burgdorferi
antigens. In combination with machine learning, this approach facilitated the selection of serologic targets early in disease and the identification of serological indicators associated with different manifestations of Lyme disease. This study provides insights into differential antibody responses during infection and outlines a new approach for improved serologic diagnosis of Lyme disease.
Draft genome sequences of three
Planktothrix rubescens
strains cultivated from a eutrophic lake in Norwalk, Ohio (USA)
Authors: Wagner Ryan S. , Bullerjahn George S.
Published: September 2024

Draft genomes were generated for three filamentous toxin-producing cyanobacterial strains cultivated from aquatic sources in Ohio sequenced by NovaSeq S4. Here, we report the classification and genome statistics of
Planktothrix rubescens
PR221, PR222, and PR223.
Supplemental Material: Body-size reductions in dacryoconarid tentaculitoids during Late Devonian warming
Authors: Prow-Fleischer Ashley N. , al. et
Published: September 2024

Figure S1: Log-transformed adult volume distributions for each sampled interval. Figure S2: Log-transformed initial chamber volume distributions for each sampled bed. Figure S3: Evolutionary trajectory modeling. Figure S4: Family-level stratigraphic trends in mean log-transformed initial chamber volumes (A), adult volumes (B), and adult to initial chamber ratio (C). Figure S5: Geochemical proxy data for nutrient availability (A–C) and redox conditions (D–E) relevant interval spanning the upper West River Formation through the punctata zonation of the lower Rhinestreet Formation from Akzo core 9455.
British Society of Gastroenterology Endoscopic Retrograde Cholangiopancreatography (ERCP) Quality Improvement Programme: minimum service standards and good practice statements
Authors: Everett Simon M , Ahmed Wafaa , Dobson Christina , Haworth Emily , Jarvis Mark , Kluettgens Bettina , Oates Beverly C , Oppong Kofi W , Rees Colin , Scarisbrick Lindsey , Sharp Linda , Wadhwani Sharan , Penman Ian D
Published: September 2024

In 2014, the British Society of Gastroenterology (BSG) published a standards framework outlining key performance indicators for ERCP practitioners and services. In the last 10 years there have been numerous changes to clinical practice yet there remains considerable variation in service delivery in the UK. In 2021 the BSG commissioned an ERCP endoscopy quality improvement project (EQIP) comprising members from all relevant stakeholding groups. This document draws from the results of a national survey of ERCP practitioners and units performed in 2022/23 supported by detailed stakeholder interviews. These results informed a draft document and series of statements that were revised at 2 group meetings and through several iterations. Each statement was included only after achieving 100% consensus from all participants. This service specification has set out 70 consensus statements covering the patient journey from booking to discharge and follow up, the members of the ERCP team, requirements for continued professional development and clinical governance, equipment and facilities and network provision and MDT working. This document describes the key components of a high quality and safe ERCP Service, seen from the patient’s perspective. It provides a detailed template for service delivery that should now be implemented by ERCP practitioners and units through the UK and should be used by ERCP providers and commissioners to benchmark services and guide continuous quality improvement.
Characterizing Teacher Support of Debugging with Physical Computing: Debugging Pedagogies in Practice
Authors: Hennessy Elliott Colin , Nixon Jessie , Gendrau Chakarov Alexandra , Bush Jeffrey B. , Schneider Michael J. , Recker Mimi
Published: September 2024

Objectives
. Physical computing systems are increasingly being integrated into secondary school science and STEM instruction, yet little is known about how teachers, especially those with little background and experience in computing, help students during the inevitable debugging moments that arise. In this article, we describe a framework, comprising two dimensions, for characterizing how teachers support students as they debug a physical computing system called the Data Sensor Hub (DASH). The DASH enables students to program sensors to measure, analyze, and visualize data as they engage in science inquiry activities.

Participants
. Five secondary school teachers implemented an inquiry-oriented instructional unit designed to introduce students to working with the DASH as a tool for scientific inquiry.

Study Method
. Findings drew on video analysis of the teachers’ classroom implementations of the unit. A review of the data corpus led to the selection of 23 moments where the teachers supported an individual or small groups of students engaged in debugging. These moments were analyzed using a grounded perspective based on Interaction Analysis to characterize the teachers’ varied interactional approaches.

Findings
. Our analysis revealed how teachers’ moves during debugging moments fell along two dimensions. The first dimension characterizes teachers’ positioning during the debugging interactions, ranging from a positioning for teacher understanding to a positioning for student understanding of the bug. The second dimension characterizes the inquiry orientation of the teachers’ questions and guidance, ranging from focusing on the debugging process to focusing on the product—or fixing the bug. Further, teachers’ moves often fell along different points on these dimensions given nuances in the instructional context.

Conclusions
. The framework offers a first step toward characterizing teachers’ debugging pedagogy as they support students during debugging moments. It also calls attention to how teachers do not necessarily need to be programming experts to effectively help students learn independent and generalizable debugging strategies. Further, it illustrates the variety of expertise that teachers can bring to debugging moments to support students learning to debug. Finally, the framework provides implications for the design of professional learning and supports for teachers as they increasingly are asked to support students in computing—and debugging—activities across a range of disciplines.
SmartDampener: An Open Source Platform for Sport Analytics in Tennis
Authors: Liu Runze , Lu Taiting , Yuan Shengming , Zhou Hao , Gowda Mahanth
Published: September 2024

In this paper, we introduce SmartDampener, an open-source tennis analytics platform that redefines the traditional understanding of vibration dampeners. Traditional vibration dampeners favored by both amateur and professional tennis players are utilized primarily to diminish vibration transmission and enhance racket stability. However, our platform uniquely merges wireless sensing technologies into a device that resembles a conventional vibration dampener, thereby offering a range of tennis performance metrics including ball speed, impact location, and stroke type. The design of SmartDampener adheres to the familiar form of this accessory, ensuring that (i) it is readily accepted by users and robust under real-play conditions such as ball-hitting, (ii) it has minimal impact on player performance, (iii) it is capable of providing a wide range of analytical insights, and (iv) it is extensible to other sports. Existing computer vision systems for tennis sensing such as Hawk-eye and PlaySight, rely on hardware that costs millions of US dollars to deploy with complex setup procedures and is susceptible to lighting environment. Wearable devices and other tennis sensing accessories, such as Zepp Tennis sensor and TennisEye, using intrusive mounting locations, hinder user experience and impede player performance. In contrast, SmartDampener, a low-cost and compact tennis sensing device, notable for its socially accepted, lightweight and scalable design, seamlessly melds into the form of a vibration dampener. SmartDampener exploits opportunities in SoC and form factor design of conventional dampeners to integrate the sensing units and micro-controllers on a two-layer flexible PCB, that is bent and enclosed inside a dampener case made of 3D printing TPU material, while maintaining the vibration dampening feature and further being enhanced by its extended battery life and the inclusion of wireless communication features. The overall cost is $9.42, with a dimension of 21.4 mm × 27.5 mm × 9.7 mm (W × L × H) and a weight of 6.1 g and 5.8 hours of battery life. In proof of SmartDampener's performance in tennis analytics, we present various tennis analytic applications that exploit the capability of SmartDampener in capturing the correlations across string vibration, and racket motion, including the estimation of ball speed with a median error of 3.59 mph, estimation of ball impact location with accuracy of 3.03 cm, and classification of six tennis strokes with accuracy of 96.75%. Finally, extensive usability studies with 15 tennis players indicate high levels of social acceptance of form factor design for the SmartDampener dampener in comparison with alternative form factors, as well as its capability of sensing and analyzing tennis stroke in an accurate and robust manner. We believe this platform will enable exciting applications in other sports like badminton, fitness tracking, and injury prevention.
View-agnostic Human Exercise Cataloging with Single MmWave Radar
Authors: Liu Alan , Lin Yu-Tai , Sundaresan Karthikeyan
Published: September 2024

Advances in mmWave-based sensing have enabled a privacy-friendly approach to pose and gesture recognition. Yet, providing robustness with the sparsity of reflected signals has been a long-standing challenge towards its practical deployment, constraining subjects to often face the radar. We present RF-HAC- a first-of-its-kind system that brings robust, automated and real-time human activity cataloging to practice by not only classifying exercises performed by subjects in their natural environments and poses, but also tracking the corresponding number of exercise repetitions. RF-HAC's unique approach (i) brings the diversity of multiple radars to scalably train a novel, self-supervised, pose-agnostic transformer-based exercise classifier directly on 3D RF point clouds with minimal manual effort and be deployed on a single radar; and (ii) leverages the underlying doppler behavior of exercises to design a robust self-similarity based segmentation algorithm for counting the repetitions in unstructured RF point clouds. Evaluations on a comprehensive set of challenging exercises in both seen and unseen environments/subjects highlight RF-HAC's robustness with high accuracy (over 90%) and readiness for real-time, practical deployments over prior art.
Self-Supervised Representation Learning and Temporal-Spectral Feature Fusion for Bed Occupancy Detection
Authors: Song Yingjian , Pitafi Zaid Farooq , Dou Fei , Sun Jin , Zhang Xiang , Phillips Bradley G. , Song WenZhan
Published: September 2024

In automated sleep monitoring systems, bed occupancy detection is the foundation or the first step before other downstream tasks, such as inferring sleep activities and vital signs. The existing methods do not generalize well to real-world environments due to single environment settings and rely on threshold-based approaches. Manually selecting thresholds requires observing a large amount of data and may not yield optimal results. In contrast, acquiring extensive labeled sensory data poses significant challenges regarding cost and time. Hence, developing models capable of generalizing across diverse environments with limited data is imperative. This paper introduces SeismoDot, which consists of a self-supervised learning module and a spectral-temporal feature fusion module for bed occupancy detection. Unlike conventional methods that require separate pre-training and fine-tuning, our self-supervised learning module is co-optimized with the primary target task, which directs learned representations toward a task-relevant embedding space while expanding the feature space. The proposed feature fusion module enables the simultaneous exploitation of temporal and spectral features, enhancing the diversity of information from both domains. By combining these techniques, SeismoDot expands the diversity of embedding space for both the temporal and spectral domains to enhance its generalizability across different environments. SeismoDot not only achieves high accuracy (98.49%) and F1 scores (98.08%) across 13 diverse environments, but it also maintains high performance (97.01% accuracy and 96.54% F1 score) even when trained with just 20% (4 days) of the total data. This demonstrates its exceptional ability to generalize across various environmental settings, even with limited data availability.
EasyAsk: An In-App Contextual Tutorial Search Assistant for Older Adults with Voice and Touch Inputs
Authors: Gao Weiwei , Du Kexin , Luo Yujia , Shi Weinan , Yu Chun , Shi Yuanchun
Published: September 2024

An easily accessible tutorial is crucial for older adults to use mobile applications (apps) on smartphones. However, older adults often struggle to search for tutorials independently and efficiently. Through a formative study, we investigated the demands of older adults in seeking assistance and identified patterns of older adults' behaviors and verbal questions when seeking help for smartphone-related issues.

Informed by the findings from the formative study, we designed EasyAsk, an app-independent method to make tutorial search accessible for older adults. This method was implemented as an Android app. Using EasyAsk, older adults can obtain interactive tutorials through voice and touch whenever they encounter problems using smartphones. To power the method, EasyAsk uses a large language model to process the voice text and contextual information provided by older adults, and another large language model to search for the tutorial. Our user experiment, involving 18 older participants, demonstrated that EasyAsk helped users obtain tutorials correctly in 98.94% of cases, making tutorial search accessible and natural.
RDGait: A mmWave Based Gait User Recognition System for Complex Indoor Environments Using Single-chip Radar
Authors: Wang Dequan , Zhang Xinran , Wang Kai , Wang Lingyu , Fan Xiaoran , Zhang Yanyong
Published: September 2024

In this paper, we aim to study millimeter-wave-based gait recognition in complex indoor environments, focusing on dealing with multipath ghosts and supporting rapid deployment to new environments. We design a ghost detection algorithm based on velocity change patterns. This algorithm relies solely on velocity estimation, requiring no environmental priors or multipath modeling. Hence, it is suitable for single-chip millimeter-wave radar with low angular resolution and can be conveniently deployed in new indoor settings. In addition, we build a gait recognition network based on an attention-based Recurrent Neural Network (RNN) to extract spatiotemporal-velocity features from RD heatmaps.

We have evaluated RDGait in two scenarios: a corridor scenario and a crowded office scenario, with 125 volunteers of different genders and ages ranging from 6 to 63. RDGait achieves a user recognition accuracy exceeding 95% among 125 candidates in both scenarios. We have further deployed RDGait in two additional scenarios using the pretrain-finetune approach. With minimal user registration data, RDGait could achieve satisfactory (> 90%) recognition accuracy in these new environments considering different radar placements, heights, and number of co-existing users.
Predicting Signal Reception Information from GNSS Satellites in Indoor Environments without Site Survey: Towards Opportunistic Indoor Positioning Based on GNSS Fingerprinting
Authors: Zhou Heng , Maekawa Takuya
Published: September 2024

While traditional GPS localization is impractical in certain indoor environments, GPS satellites offer a valuable source of indoor contextual information, particularly around window-side areas where signals are more accessible. This study introduces a new method that predicts GPS signal reception information in a target indoor environment without the need for actual data collection in the target environment. By predicting the strengths of GPS signals that are expected to be measured at various indoor positions, we can construct a GPS signal reception map of a target environment, which functions similarly to a Wi-Fi fingerprinting map surrounding window-side areas, offering a new dimension in indoor positioning systems. For instance, it aids in the correction of accumulated errors in pedestrian dead reckoning (PDR) systems. Our proposed method leverages easily accessible inputs, including satellite location data, indoor floorplan image of the target floor, and 3D mapping of the surrounding buildings, to predict signal reception at each position in the target environment. We developed a specialized neural network, named multi-scale branch fusion network (MSBF-Net), designed to process and integrate data of varying scales, such as the floorplan image of the target environment and 3D map of the surrounding area obtained from Google Earth, with a specific focus on understanding the line-of-sight (LOS) and multi-path effects caused by internal obstacles and surrounding buildings. This advanced capability enables the network to effectively interpret complex signal interactions within urban environments, enhancing its predictive accuracy for GPS signal reception. The effectiveness of our method was rigorously evaluated using real-world environments. In addition, we employed our method to implement opportunistic GPS fingerprint-based indoor positioning, where position estimates are provided when a strong signal is observed from at least one satellite. Surprisingly, the positioning method achieved a positioning error of only 2.8 meters when a smartphone is close to window-side areas even though the method does not rely on labeled training data collected in a target environment and signal infrastructures installed in the target environment.
Parent and Educator Concerns on the Pedagogical Use of AI-Equipped Social Robots
Authors: Perella-Holfeld Francisco , Sallam Samar , Petrie Julia , Gomez Randy , Irani Pourang , Sakamoto Yumiko
Published: September 2024

Social robots equipped with conversational artificial intelligence are becoming increasingly common in educational settings. However, the long-term consequences of such uses remain relatively unknown due to their novelty. To ensure children's safe use of social robots, and proper adoption of the technology, it is crucial to scrutinize potential concerns regarding their usage. This exploration will provide insights to inform the design and development of this technology. Thus, this study investigated parents' and educators' perceptions of social robot use by children in the home and school settings. Our main objectives are to; 1) explore whether the types and/or levels of concern are tied to the role that individuals take (i.e., parents vs. educators); 2) explore if the levels of concern vary based on the gender and age of the potential child user; and 3) compile a catalogue of parents' and educators' concerns, both from the literature and those that are overlooked, surrounding children's use of SRs for learning. To address those inquiries, a cross-national online survey study was conducted with parents and educator participants (N = 396). Overall, participants indicated high levels of concern but recognized the potential in responsibly applying such technology for educational purposes.
Edge-Light: Exploiting Luminescent Solar Concentrators for Ambient Light Communication
Authors: Tapia Miguel A. Chávez , Rodríguez Diego Palma , Zamalloa Marco Zúñiga
Published: September 2024

A recent advance in embedded Internet of Things (IoT) exploits ambient light for wireless communication. This new paradigm enables highly efficient links via simple light modulation, but the design space has a fundamental constraint: in most State of the Art (SoA) studies, the link can only follow the propagation direction of ambient light. Consider, for example, a swarm of drones and ground robots that want to communicate with sunlight. Drone-to-robot communication could be possible because sunlight travels downwards from the air (drone) to the ground (robot), allowing drones to modulate light to send information to robots beneath them. Robot-to-robot communication, however, is not possible because sunlight does not travel sideways (parallel to the ground). To allow 'lateral communication' with ambient light, we propose using Luminescent Solar Concentrators (LSC). These optical components receive ambient light on their surface and re-direct part of the spectra towards their edges. Considering this optical property of LSC, our work has three main contributions. First, we benchmark various optical properties of LSC to assess their performance for ambient light communication. Second, we combine LSC with liquid crystal (LC) shutters to form lateral links with ambient light. Third, we test our links indoors and outdoors with artificial and natural ambient light, by enhancing two robots with our LSC transceivers and showing that they can exchange basic commands and coordinate tasks by communicating only with sunlight.
ChatIoT: Zero-code Generation of Trigger-action Based IoT Programs
Authors: Gao Yi , Xiao Kaijie , Li Fu , Xu Weifeng , Huang Jiaming , Dong Wei
Published: September 2024

Trigger-Action Program (TAP) is a simple but powerful format to realize intelligent IoT applications, especially in home automation scenarios. Existing trace-driven approaches and in-situ programming approaches depend on either customized interaction commands or well-labeled datasets, resulting in limited applicable scenarios. In this paper, we propose ChatIoT, a zero-code TAP generation system based on large language models (LLMs). With a novel context-aware compressive prompting scheme, ChatIoT is able to automatically generate TAPs from user requests in a token-efficient manner and deploy them to the TAP runtime. Further, for those TAP requests including unknown sensing abilities, ChatIoT can also generate new AI models with knowledge distillation by multimodal LLMs, with a novel model customization method based on deep reinforcement learning. We implemented ChatIoT and evaluated its performance extensively. Results show that ChatIoT can reduce token consumption by 26.1-84.9% and improve TAP generation accuracy by 4.2-65.5% compared to state-of-the-art approaches in multiple settings. We also conducted a real user study, and ChatIoT can achieve 91.57% TAP generation accuracy.
airTac: A Contactless Digital Tactile Receptor for Detecting Material and Roughness via Terahertz Sensing
Authors: Zhang Zhan , Song Denghui , Zhou Anfu , Ma Huadong
Published: September 2024

Tactile sensing is an indispensable capability for humans or intelligent devices to engage in complex physical interactions. Mainstream tactile sensors are contact-based, which show limitation in measuring deformable objects and demanding high maintenance effort. As a complementary solution, a new paradigm of contactless tactile sensing is attracting much interest. While promising, they can only identify coarse-grained single tactile perception properties, either material type or surface roughness. In this paper, we propose airTac, which includes a novel contactless digital tactile receptor model, capable of simultaneously extracting these two basic tactile properties in a fine-grained resolution, by harnessing the massive bandwidth of terahertz(THz) frequency band. airTac is designed based on our key finding: while the impact of material type and surface roughness on THz signal intertwine with each other, they are actually separable, i.e., roughness manifests a certain pattern in distorting relative high-frequency components of the whole THz spectrum. Therefore, we custom-design a bio-inspired deep neural network model to decouple the intertwined THz signal, and distill the tactile perception properties embedded underlying the signal. We prototype airTac using a THz time domain spectroscopy, and perform extensive evaluation over 9 different daily material types with 39 different surface roughness. airTac achieves a material identification accuracy of 97.43% and a roughness classification accuracy of 91.46%, which demonstrates that airTac can identify common materials in daily life and exceed a fingertip spatial resolution of 1mm.
SpaceBeat: Identity-aware Multi-person Vital Signs Monitoring Using Commodity WiFi
Authors: Li Bofan , Ren Yili , Wang Yichao , Yang Jie
Published: September 2024

Vital signs monitoring has gained increasing attention due to its ability to indicate various human health and well-being conditions. The development of WiFi sensing technologies has made it possible to monitor vital signs using ubiquitous WiFi signals and devices. However, most existing approaches are dedicated to single-person scenarios. A few WiFi sensing approaches can achieve multi-person vital signs monitoring, whereas they are not identity-aware and sensitive to interferences in the environment. In this paper, we propose SpaceBeat, an identity-aware and interference-robust multi-person vital sign monitoring system using commodity WiFi. In particular, our system separates multiple people and locates each person in the spatial domain by leveraging multiple antennas. We analyze the change of signals at the location of each person to achieve identity-aware vital signs monitoring. We also design a contrastive principal component analysis-contrastive learning framework to mitigate interferences caused by other moving people. We evaluate SpaceBeat in various challenging environments, including interference scenarios, non-line-of-sight scenarios, different distances, etc. Our system achieves an average accuracy of 99.1% for breathing monitoring and 97.9% for heartbeat monitoring.