bluuebunny/crossref_metadata_2025 huggingface dataset:
Common design and data elements reported in active mechanical thrombectomy trials focusing on distal medium vessel occlusions and minor strokes: a systematic review
Authors: Bilgin Cem , Bolsegui Marisabel L , Ghozy Sherief , Hassankhani Amir , Kobeissi Hassan , Jabal Mohamed Sobhi , Gupta Rishabh , De Rubeis Gianluca , Kadirvel Ramanathan , Brinjikji Waleed , Saba Luca , Kallmes David F
Published: January 2024

Background

Distal medium vessel occlusions (DMVOs) and minor strokes represent emerging frontiers in mechanical thrombectomy (MT). Although several randomized clinical trials (RCTs) are underway, the design characteristics of these trials and the specific questions they aim to address have not been extensively explored. This current study sought to investigate the design and data elements reported in active prospective DMVO and minor stroke studies.

Methods

The ClinicalTrials.gov database was searched for ongoing prospective studies assessing the role of MT in patients with DMVOs or minor strokes. The Nested Knowledge AutoLit platform was utilized to categorize reported outcomes and inclusion/exclusion criteria. Frequencies of reported data elements were extracted from study protocols.

Results

A total of 10 (8 DMVO and 2 minor stroke) studies enrolling 3520 patients were included. All DMVO studies employ different criteria regarding target occlusion locations. Five DMVO studies use stent retrievers as the first-line thrombectomy technique (62.5%, 5/8), while three studies allow any MT techniques, generally at the operator’s discretion. Four DMVO studies permit intravenous thrombolysis (IVT) utilization in both intervention and control arms (50%, 4/8). The DISTALS trial excludes patients receiving IVT, while the DUSK trial and Tigertriever registry only enroll patients who are ineligible for IVT or for whom IVT failed to achieve reperfusion. DMVO studies exhibit notable heterogeneity in symptom onset duration thresholds for inclusion (<6 hours: 2 studies; <12 hours: 2 studies; <24 hours: 3 studies). Minor stroke trials employ similar inclusion criteria and outcome measures except for symptom duration thresholds for inclusion (8 hours for ENDOLOW and 23 hours for MOSTE).

Conclusions

There is considerable heterogeneity among active DMVO trials regarding potential target DMVO locations and time thresholds for inclusion based on the last known well time. Furthermore, our review indicates that the utility of aspiration thrombectomy in DMVOs and the advantages of MT without IVT over IVT alone will remain largely unexplored even after completion of active DMVO trials.
HEALTH SYSTEM PERFORMANCE, DISASTER RESPONSE AND POLITICAL IDENTITIES DURING THE COVID-19 PANDEMIC: THEORETICAL AND EMPIRICAL EVIDENCE
Authors: HO SZU-HSIEN , OKAFOR LUKE , YAN ERIC
Published: January 2024

In this paper, we developed a model to assess the government’s disaster response during the COVID-19 pandemic, exploring variations across jurisdictions dominated by different political identities in the United States. The model defines an individual’s payoff as a positive function of his/her income and the government’s disaster response. The individual is more prone to wear a mask if the government is more responsive to the disaster during the pandemic, and there can be a lower income loss for the individual during the pandemic when he/she has higher compliance to the government’s order of face mask. Utilizing this model, we derive the government’s disaster response to be positively correlated with the impact of COVID-19 deaths on masking behavior and negatively correlated with the change of the death toll relative to income. This allows us to evaluate the unobserved disaster response of the government explicitly using regression results. We compare the government’s disaster response across jurisdictions dominated by different political identities in the United States. The results highlight a more resilient disaster response in Democratic states, translating into superior health system performance compared to their Republican counterparts. These findings emphasize the crucial role of policies designed to strengthen disaster response, especially in addressing collective action problems such as those posed by the COVID-19 pandemic and climate crises.
Formation of solitons for the modified nonlinear Schrödinger equation
Authors: Akram Ghazala , Sadaf Maasoomah , Arshed Saima , Raza Muhammad Zubair , Alzaidi Ahmed S. M.
Published: January 2024

The study of modified nonlinear Schrödinger equation plays a significant role in the description of wave propagation through optical waveguides and rogue waves in ocean. The main aim of this work is to obtain solitons as well as other types of exact wave solutions to the modified nonlinear Schrödinger equation. The accurate traveling wave solutions are obtained using the [Formula: see text]-exponential expansion method and the modified auxiliary equation method. Consequently, soliton solutions and periodic wave solutions have been retrieved. The graphical illustrations of the results are provided for suitable values of the parameters involved in the solutions to explain the dynamical nature of the considered equation.
A Latency-Aware End-Edge Cooperative Insulator Detection Method with High Energy Efficiency and Accuracy
Authors: Qiang Wei
Published: January 2024

A prerequisite to ensure the stability of the power supply system is suitable functioning of transmission line equipment. However, the increasing deployment of transmission lines in modern power systems has introduced significant challenges to line inspection. While deep learning-based image detection techniques have shown promise in improving the efficiency and accuracy of insulator detection, they often require substantial computational resources and energy. This limitation hinders the consistent guarantee of accuracy and real-time performance on resource-constrained drones. To address this issue, this paper investigates the co-optimization problem of energy consumption and analytic accuracy in insulator image detection on unmanned aerial vehicles (UAVs). We propose a latency-aware end-edge cooperative insulator detection task offloading scheme with high energy efficiency and accuracy that aims to achieve optimal performance. Initially, we conducted an experimental analysis to examine the influence of input image resolution on the accuracy and latency of the CNN-based insulation detection model. Subsequently, we develop a model that takes into account the latency, analytic accuracy and energy consumption for image detection task offloading. Finally, we formalized a nonlinear integer optimization problem and designed a particle swarm optimization (PSO)-based task offloading scheme to optimize task accuracy and energy consumption while adhering to latency constraints. Extensive experiments validated the effectiveness of the proposed end-edge cooperative insulator detection method in optimizing accuracy and energy consumption.
Battery Thermal Management System for Electric Vehicle (EV)/Hybrid EV (HEV) with the Incorporation of POA-FSO Strategy
Authors: Justin Raj P. , Vasan Prabhu V. , Krishna Kumar V.
Published: January 2024

A hybrid technique is proposed for electric vehicles (EVs) or hybrid electric vehicles (HEVs) with a battery thermal management system (BTMS). The proposed hybrid method is the combined execution of the Pelican Optimization Algorithm (POA) and Firebug Swarm Optimization (FSO). The hunting behavior of pelicans is improved with the help of the FSO technique; hence, it is named the POA-FSO strategy. Here, a battery of 36 lithium-ion (Li-ion) cells is considered. The proposed method of analyzing battery thermal performance analyzed factors like heat flux from the battery cell to the passage spacing size, cooling air and the cooling air’s mass flow rate (MFR). The BTMS performance is studied under maximum battery unit temperature, pressure drop and temperature uniformity. The proposed method enhances the coolant passage spacing and decreases the temperature difference in the battery cells. The proposed approach is executed on the MATLAB platform, and its performance is compared with existing approaches. From the results, it is concluded that the MFR maximizes, and a nonuniform distribution of the MFR of the passage occurs. By using the proposed approach, the maximal temperature change of cooling air among the passages is 2.0[Formula: see text]K, the maximal temperature change between the battery cells is 7.5[Formula: see text]K and a pressure drop of 228.03[Formula: see text]Pa is obtained.
Dehornoy’s class and Sylows for set-theoretical solutions of the Yang–Baxter equation
Authors: Feingesicht Edouard
Published: January 2024

We explain how the germ of the structure group of a cycle set decomposes as a product of its Sylow-subgroups, and how this process can be reversed to construct cycle sets from ones with coprime classes. We study Dehornoy’s class associated to a cycle set, and conjecture a bound that we prove in a specific case. We combine the use of braces and a monomial representation, in particular to answer a question by Dehornoy on retrieving the Garside structure without a theorem of Rump, while also retrieving said theorem.
Directed partial orders on complex numbers and quaternions
Authors: Ma Jingjing
Published: January 2024

Let [Formula: see text] be an integral domain that is algebraic over [Formula: see text]. It is shown that each directed maximal partial order on [Formula: see text] is an Archimedean total order. Let [Formula: see text] be a subfield of [Formula: see text] and [Formula: see text] be the complex field over [Formula: see text]. As a consequence of the above result, if [Formula: see text] is algebraic over [Formula: see text], then [Formula: see text] does not have a directed partial order making it a partially ordered ring. In particular, [Formula: see text] cannot be a lattice-ordered ring. The result is proved for certain partially ordered algebras of quaternions as well.
Genoprotective Potency of Vit C on Zinc Oxide (ZnO) and Iron Oxide (Fe2O3) Nanoparticle-Mediated Toxicity, an In Vitro Study
Authors: Karimi Arezoo , Modanloo Mona , Barghi Nasrin Ghassemi , Shokrzadeh Mohammad
Published: January 2024

Introduction: The potential of zinc oxide (ZnO) and iron oxide (Fe2O[Formula: see text] nanoparticles (NPs) to induce toxic effects, especially genotoxicity, has been demonstrated in previous studies and is in part related to the ability of NPs to produce ROS. The use of antioxidants is an effective method to reduce NP-induced genotoxicity. The aim of this study was to determine the protective role of vitamin C as a potent antioxidant in ZnO-and Fe2O3 NP-induced genotoxicity in the HGF-1 cell line.

Methods: Different concentrations of ZnO and Fe2O3 NPs (50[Formula: see text][Formula: see text]g, 100[Formula: see text][Formula: see text]g, and 150[Formula: see text][Formula: see text]g/mL) were used to achieve the best concentration for further evaluation. HGF-1 cells were incubated with different concentrations of vitamin C 24[Formula: see text]h before the NPs. The cells were then exposed to ZnO and Fe2O3 NPs at a concentration of 100[Formula: see text][Formula: see text]g/mL for 1[Formula: see text]h. The possible genoprotective effects of vitamin C were determined using a comet assay.

Results: The results of this study showed that all concentrations of vitamin C could reduce the DNA damage induced by ZnO and Fe2O3 NPs.

Discussion: In conclusion, vitamin C could be considered a potent genoprotective agent against ZnO- and Fe2O3 NP-induced genotoxicity.
Improving a Conventional Connection of Beam-to-Weak Axis of H-shaped Column to Modify Load Path in Panel Zone
Authors: Mirghaderi Seyed Rasoul , Taheri Ghazaleh , Ebrahimi Samira
Published: January 2024

This study aims to propose an improvement to the conventional connection of beam-to-weak axis of H-shaped columns with in-plane load paths and to compare the improved connection with the conventional one. The conventional connection detail consists of continuity plates and face plates, while the improved connection detail, in addition to the previous components, has a plate perpendicular to the column web (middle panel zone) acting as a panel zone. A numerical study using ABAQUS was conducted, and the study results showed that the most appropriate value for the middle panel zone thickness is equal to the column flange thickness, and it should be designed for 30% of the force demand induced by the beam bending moments. Furthermore, the study findings indicated that the proposed connection resulted in an average of 59.5% decrease in the force demands induced to the panel zone in comparison with the conventional connection. In addition, it was observed that the force demand on the face plate experienced the most decrease due to reducing the out-of-plane performance of the face plate in the improved connection models. Moreover, the results showed that the improved connection models experienced lower levels of von Mises stress, approximately 35.7% less than the conventional connection models.
Study on Nonlinear Acoustic Waves in Stepped Acoustic Resonators
Authors: Yu Yanan , Chen Qi , He Wen , Zhou Jie
Published: January 2024

The problem of investigating the nonlinear acoustic waves in stepped acoustic resonators is treated theoretically. A perturbation scheme that combines the method of multi-scale expansion yields a set of coupled nonlinear ordinary differential equations for deriving an analytical model to describe the resonant oscillations. The nonlinear sound pressure in stepped resonator is predicted with accuracy up to the second-order terms of a small-amplitude parameter [Formula: see text]. The pressure amplitudes and waveforms at the closed end of stepped resonators with different size parameters are investigated by the derived analytical model and qualitatively compared with the measured results in experiment. The qualitative comparison of calculated and measured results shows good agreement. The results suggest that the sound pressure generated in stepped resonators with different size parameters may be very different. Not all stepped resonators can generate high-amplitude and low-distortion standing waves. The derived analytical model can be used to qualitatively study the nonlinear acoustic waves in stepped acoustic resonators and design suitable tube dimensions for resonant macrosonic synthesis.
Hierarchical Decision-Making Framework for Multi-UAV Task Assignment via Enhanced Pigeon-Inspired Optimization
Authors: Chen Weike , Hai Xingshuo , Hu Yanming , Feng Qiang , Wang Zili
Published: January 2024

Effective task assignment decisions are paramount for ensuring reliable task execution in multi-UAV systems. However, in the development of feasible plans, challenges stemming from extensive and prolonged task requirements are encountered. This paper establishes a decision-making framework for multiple unmanned aerial vehicles (multi-UAV) based on the well-known pigeon-inspired optimization (PIO) algorithm. By addressing the problem from a hierarchical structural perspective, the initial stage involves minimizing the global objective of the flight distance cost after obtaining the entire task distribution and task requirements, utilizing the global optimization capability of the classical PIO algorithm to allocate feasible task spaces for each UAV. In the second stage, building upon the decisions made in the preceding stage, each UAV is abstracted as an agent maximizing its own task execution benefits. An improved version of the PIO algorithm modified with a sine-cosine search mechanism is proposed, enabling the acquisition of the optimal task execution sequence. Simulation experiments involving two different scales of UAVs validate the effectiveness of the proposed methodology. Moreover, dynamic events such as UAV damage and task changes are considered in the simulation to validate the efficacy of the two-stage framework.
Conversational Localization
Authors: Sheshadri Smitha , Hara Kotaro
Published: January 2024

We propose a novel sensorless approach to indoor localization by leveraging natural language conversations with users, which we call conversational localization. To show the feasibility of conversational localization, we develop a proof-of-concept system that guides users to describe their surroundings in a chat and estimates their position based on the information they provide. We devised a modular architecture for our system with four modules. First, we construct an entity database with available image-based floor maps. Second, we enable the dynamic identification and scoring of information provided by users through our utterance processing module. Then, we implement a conversational agent that can intelligently strategize and guide the interaction to elicit localizationally valuable information from users. Finally, we employ visibility catchment area and line-of-sight heuristics to generate spatial estimates for the user's location. We conduct two user studies in designing and testing the system. We collect 800 natural language descriptions of unfamiliar indoor spaces in an online crowdsourcing study to learn the feasibility of extracting localizationally useful entities from user utterances. We then conduct a field study with 10 participants at 10 locations to evaluate the feasibility and performance of conversational localization. The results show that conversational localization can achieve within-10 meter localization accuracy at eight out of the ten study sites, showing the technique's utility for classes of indoor location-based services.
ClearSpeech
Authors: Ma Dong , Dang Ting , Ding Ming , Balan Rajesh
Published: January 2024

Wireless earbuds have been gaining increasing popularity and using them to make phone calls or issue voice commands requires the earbud microphones to pick up human speech. When the speaker is in a noisy environment, speech quality degrades significantly and requires speech enhancement (SE). In this paper, we present ClearSpeech, a novel deep-learning-based SE system designed for wireless earbuds. Specifically, by jointly using the earbud's in-ear and out-ear microphones, we devised a suite of techniques to effectively fuse the two signals and enhance the magnitude and phase of the speech spectrogram. We built an earbud prototype to evaluate ClearSpeech under various settings with data collected from 20 subjects. Our results suggest that ClearSpeech can improve the SE performance significantly compared to conventional approaches using the out-ear microphone only. We also show that ClearSpeech can process user speech in real-time on smartphones.
Scribe
Authors: Bai Yang , Shahid Irtaza , Takawale Harshvardhan , Roy Nirupam
Published: January 2024

This paper presents the design and implementation of Scribe, a comprehensive voice processing and handwriting interface for voice assistants. Distinct from prior works, Scribe is a precise tracking interface that can co-exist with the voice interface on low sampling rate voice assistants. Scribe can be used for 3D free-form drawing, writing, and motion tracking for gaming. Taking handwriting as a specific application, it can also capture natural strokes and the individualized style of writing while occupying only a single frequency. The core technique includes an accurate acoustic ranging method called Cross Frequency Continuous Wave (CFCW) sonar, enabling voice assistants to use ultrasound as a ranging signal while using the regular microphone system of voice assistants as a receiver. We also design a new optimization algorithm that only requires a single frequency for time difference of arrival. Scribe prototype achieves 73 μm of median error for 1D ranging and 1.4 mm of median error in 3D tracking of an acoustic beacon using the microphone array used in voice assistants. Our implementation of an in-air handwriting interface achieves 94.1% accuracy with automatic handwriting-to-text software, similar to writing on paper (96.6%). At the same time, the error rate of voice-based user authentication only increases from 6.26% to 8.28%.
Powered by AI
Authors: Figueiredo Mayara Costa , Ankrah Elizabeth , Powell Jacquelyn E. , Epstein Daniel A. , Chen Yunan
Published: January 2024

Recently, there has been a proliferation of personal health applications describing to use Artificial Intelligence (AI) to assist health consumers in making health decisions based on their data and algorithmic outputs. However, it is still unclear how such descriptions influence individuals' perceptions of such apps and their recommendations. We therefore investigate how current AI descriptions influence individuals' attitudes towards algorithmic recommendations in fertility self-tracking through a simulated study using three versions of a fertility app. We found that participants preferred AI descriptions with explanation, which they perceived as more accurate and trustworthy. Nevertheless, they were unwilling to rely on these apps for high-stakes goals because of the potential consequences of a failure. We then discuss the importance of health goals for AI acceptance, how literacy and assumptions influence perceptions of AI descriptions and explanations, and the limitations of transparency in the context of algorithmic decision-making for personal health.
Spatial-Temporal Masked Autoencoder for Multi-Device Wearable Human Activity Recognition
Authors: Miao Shenghuan , Chen Ling , Hu Rong
Published: January 2024

The widespread adoption of wearable devices has led to a surge in the development of multi-device wearable human activity recognition (WHAR) systems. Nevertheless, the performance of traditional supervised learning-based methods to WHAR is limited by the challenge of collecting ample annotated wearable data. To overcome this limitation, self-supervised learning (SSL) has emerged as a promising solution by first training a competent feature extractor on a substantial quantity of unlabeled data, followed by refining a minimal classifier with a small amount of labeled data. Despite the promise of SSL in WHAR, the majority of studies have not considered missing device scenarios in multi-device WHAR. To bridge this gap, we propose a multi-device SSL WHAR method termed Spatial-Temporal Masked Autoencoder (STMAE). STMAE captures discriminative activity representations by utilizing the asymmetrical encoder-decoder structure and two-stage spatial-temporal masking strategy, which can exploit the spatial-temporal correlations in multi-device data to improve the performance of SSL WHAR, especially on missing device scenarios. Experiments on four real-world datasets demonstrate the efficacy of STMAE in various practical scenarios.
MIRROR
Authors: Kang Dong-Sig , Baek Eunsu , Son Sungwook , Lee Youngki , Gong Taesik , Kim Hyung-Sin
Published: January 2024

We present MIRROR, an on-device video virtual try-on (VTO) system that provides realistic, private, and rapid experiences in mobile clothes shopping. Despite recent advancements in generative adversarial networks (GANs) for VTO, designing MIRROR involves two challenges: (1) data discrepancy due to restricted training data that miss various poses, body sizes, and backgrounds and (2) local computation overhead that uses up 24% of battery for converting only a single video. To alleviate the problems, we propose a generalizable VTO GAN that not only discerns intricate human body semantics but also captures domain-invariant features without requiring additional training data. In addition, we craft lightweight, reliable clothes/pose-tracking that generates refined pixel-wise warping flow without neural-net computation. As a holistic system, MIRROR integrates the new VTO GAN and tracking method with meticulous pre/post-processing, operating in two distinct phases (on/offline). Our results on Android smartphones and real-world user videos show that compared to a cutting-edge VTO GAN, MIRROR achieves 6.5× better accuracy with 20.1× faster video conversion and 16.9× less energy consumption.
BodyTouch
Authors: Cheng Wen-Wei , Chan Liwei
Published: January 2024

This paper presents a study on the touch precision of an eye-free, body-based interface using on-body and near-body touch methods with and without skin contact. We evaluate user touch accuracy on four different button layouts. These layouts progressively increase the number of buttons between adjacent body joints, resulting in 12, 20, 28, and 36 touch buttons distributed across the body. Our study indicates that the on-body method achieved an accuracy beyond 95% for the 12- and 20-button layouts, whereas the near-body method only for the 12-button layout. Investigating user touch patterns, we applied SVM classifiers, which boost both the on-body and near-body methods to support up to the 28-button layouts by learning individual touch patterns. However, using generalized touch patterns did not significantly improve accuracy for more complex layouts, highlighting considerable differences in individual touch habits. When evaluating user experience metrics such as workload perception, confidence, convenience, and willingness-to-use, users consistently favored the 20-button layout regardless of the touch technique used. Remarkably, the 20-button layout, when applied to on-body touch methods, does not necessitate personal touch patterns, showcasing an optimal balance of practicality, effectiveness, and user experience without the need for trained models. In contrast, the near-body touch targeting the 20-button layout needs a personalized model; otherwise, the 12-button layout offers the best immediate practicality.
PyroSense
Authors: Zeng Huaili , Li Gen , Li Tianxing
Published: January 2024

We present PyroSense, the first-of-its-kind system that enables fine-grained 3D posture reconstruction using ubiquitous COTS passive infrared sensor (PIR sensor). PyroSense senses heat signals generated by the human body and airflow due to body movement to reconstruct the corresponding human postures in real time. PyroSense greatly advances the prior PIR-based sensing design by improving the sensitivity of COTS PIR sensor to body movement, increasing spatial resolution without additional deployment overhead, and designing intellectual algorithms to adapt to diverse environmental factors. We build a low-cost PyroSense prototype using off-the-shelf hardware components. The experimental findings indicate that PyroSense not only attains a classification accuracy of 99.46% across 15 classes, but it also registers a mean joint distance error of less than 16 cm for 14 body joints for posture reconstruction in challenging environments.
SDE
Authors: Xue Meng , Zeng Yuyang , Gu Shengkang , Zhang Qian , Tian Bowei , Chen Changzheng
Published: January 2024

Early screening for dry eye disease (DED) is crucial to identify and provide timely intervention to high-risk susceptible populations. Currently, clinical methods for diagnosing DED include the tear break-up time test, meibomian gland analysis, tear osmolarity test, and tear river height test, which require in-hospital detection. Unfortunately, there is no convenient way to screen for DED yet. In this paper, we propose SDE, a contactless, convenient, and ubiquitous DED screening system based on RF signals. To extract biomarkers for early screening of DED from RF signals, we construct frame chirps variance and extract fine-grained spontaneous blinking action. SDE is carefully designed to remove interference in RF signals and refine the characterization of biomarkers that denote the symptoms of DED. To endow SDE with the ability to adapt to new users, we develop a deep learning-based model of unsupervised domain adaptation to remove the influence of different users and environments in local and global two-level feature spaces. We conduct extensive experiments to evaluate SDE with 54 volunteers in 4 scenes. The experimental results confirm that SDE can accurately screen for DED in a new user in real environments such as eye examination rooms, clinics, offices, and homes.
Reading Between the Heat
Authors: Xiao Yi , Sharma Harshit , Zhang Zhongyang , Bergen-Cico Dessa , Rahman Tauhidur , Salekin Asif
Published: January 2024

Stress impacts our physical and mental health as well as our social life. A passive and contactless indoor stress monitoring system can unlock numerous important applications such as workplace productivity assessment, smart homes, and personalized mental health monitoring. While the thermal signatures from a user's body captured by a thermal camera can provide important information about the "fight-flight" response of the sympathetic and parasympathetic nervous system, relying solely on thermal imaging for training a stress prediction model often lead to overfitting and consequently a suboptimal performance. This paper addresses this challenge by introducing ThermaStrain, a novel co-teaching framework that achieves high-stress prediction performance by transferring knowledge from the wearable modality to the contactless thermal modality. During training, ThermaStrain incorporates a wearable electrodermal activity (EDA) sensor to generate stress-indicative representations from thermal videos, emulating stress-indicative representations from a wearable EDA sensor. During testing, only thermal sensing is used, and stress-indicative patterns from thermal data and emulated EDA representations are extracted to improve stress assessment. The study collected a comprehensive dataset with thermal video and EDA data under various stress conditions and distances. ThermaStrain achieves an F1 score of 0.8293 in binary stress classification, outperforming the thermal-only baseline approach by over 9%. Extensive evaluations highlight ThermaStrain's effectiveness in recognizing stress-indicative attributes, its adaptability across distances and stress scenarios, real-time executability on edge platforms, its applicability to multi-individual sensing, ability to function on limited visibility and unfamiliar conditions, and the advantages of its co-teaching approach. These evaluations validate ThermaStrain's fidelity and its potential for enhancing stress assessment.
KeyStub
Authors: Nolan John , Qian Kun , Zhang Xinyu
Published: January 2024

The proliferation of the Internet of Things is calling for new modalities that enable human interaction with smart objects. Recent research has explored RFID tags as passive sensors to detect finger touch. However, existing approaches either rely on custom-built RFID readers or are limited to pre-trained finger-swiping gestures. In this paper, we introduce KeyStub, which can discriminate multiple discrete keystrokes on an RFID tag. KeyStub interfaces with commodity RFID ICs with multiple microwave-band resonant stubs as keys. Each stub's geometry is designed to create a predefined impedance mismatch to the RFID IC upon a keystroke, which in turn translates into a known amplitude and phase shift, remotely detectable by an RFID reader. KeyStub combines two ICs' signals through a single common-mode antenna and performs differential detection to evade the need for calibration and ensure reliability in heavy multi-path environments. Our experiments using a commercial-off-the-shelf RFID reader and ICs show that up to 8 buttons can be detected and decoded with accuracy greater than 95%. KeyStub points towards a novel way of using resonant stubs to augment RF antenna structures, thus enabling new passive wireless interaction modalities.
Deep Heterogeneous Contrastive Hyper-Graph Learning for In-the-Wild Context-Aware Human Activity Recognition
Authors: Ge Wen , Mou Guanyi , Agu Emmanuel O. , Lee Kyumin
Published: January 2024

Human Activity Recognition (HAR) is a challenging, multi-label classification problem as activities may co-occur and sensor signals corresponding to the same activity may vary in different contexts (e.g., different device placements). This paper proposes a Deep Heterogeneous Contrastive Hyper-Graph Learning (DHC-HGL) framework that captures heterogenous Context-Aware HAR (CA-HAR) hypergraph properties in a message-passing and neighborhood-aggregation fashion. Prior work only explored homogeneous or shallow-node-heterogeneous graphs. DHC-HGL handles heterogeneous CA-HAR data by innovatively 1) Constructing three different types of sub-hypergraphs that are each passed through different custom HyperGraph Convolution (HGC) layers designed to handle edge-heterogeneity and 2) Adopting a contrastive loss function to ensure node-heterogeneity. In rigorous evaluation on two CA-HAR datasets, DHC-HGL significantly outperformed state-of-the-art baselines by 5.8% to 16.7% on Matthews Correlation Coefficient (MCC) and 3.0% to 8.4% on Macro F1 scores. UMAP visualizations of learned CA-HAR node embeddings are also presented to enhance model explainability. Our code is publicly available1 to encourage further research.
Designing Data Visualisations for Self-Compassion in Personal Informatics
Authors: Loerakker Meagan B. , Niess Jasmin , Bentvelzen Marit , Woźniak Paweł W.
Published: January 2024

Wearable personal trackers offer exciting opportunities to contribute to one's well-being, but they also can foster negative experiences. It remains a challenge to understand how we can design personal informatics experiences that help users frame their data in a positive manner and foster self-compassion. To explore this, we conducted a study where we compared different visualisations for user-generated screen time data. We examined positive, neutral and negative framings of the data and whether or not a point of reference was provided in a visualisation. The results show that framing techniques have a significant effect on reflection, rumination and self-compassion. We contribute insights into what design features of data representations can support positive experiences in personal informatics.
FSS-Tag
Authors: Chang Liqiong , Yang Xiaofeng , Liu Ruyue , Xie Guodong , Wang Fuwei , Wang Ju
Published: January 2024

Material sensing is crucial in many emerging applications, such as waste classification and hazardous material detection. Although existing Radio Frequency (RF) signal based systems achieved great success, they have limited identification accuracy when either RF signals can not penetrate through a target or a target has different outer and inner materials.

This paper introduces a Frequency Selective Surface (FSS) tag based high accuracy material identification system, namely FSS-Tag, which utilises both the penetrating signals and the coupling effect. Specifically, we design and attach a FSS tag to a target, and use frequency responses of the tag for material sensing, since different target materials have different frequency responses. The key advantage of our system is that, when RF signals pass through a target with the FSS tag, the penetrating signal responds more to the inner material, and the coupling effect (between the target and the tag) reflects more about the outer material; thus, one can achieve a higher sensing accuracy. The challenge lies in how to find optimal tag design parameters so that the frequency response of different target materials can be clearly distinguished. We address this challenge by establishing a tag parameter optimization model.

Real-world experiments show that FSS-Tag achieves more than 91% accuracy on identifying eight common materials, and improves the accuracy by up to 38% and 8% compared with the state of the art (SOTA) penetrating signal based method TagScan and the SOTA coupling effect based method Tagtag.
Bi-directional Block Encoding for Reversible Data Hiding over Encrypted Images
Authors: Liu Xingyu , Hua Zhongyun , Yi Shuang , Zhang Yushu , Zhou Yicong
Published: January 2024

Reversible data hiding over encrypted images (RDH-EI) technology is a viable solution for privacy-preserving cloud storage, as it enables the reversible embedding of additional data into images while maintaining image confidentiality. Since the data hiders, e.g., cloud servers, are willing to embed as much data as possible for storage, management, or other processing purposes, a large embedding capacity is desirable in an RDH-EI scheme. In this article, we introduce a novel bi-directional block encoding (BDBE) method, which, for the first time, encodes the distances of values in a binary sequence from both ends. This approach allows for encoding images with smaller sizes compared to traditional and state-of-the-art encoding methods. Leveraging the BDBE technique, we propose a high-capacity RDH-EI scheme. In this scheme, the content owner initially predicts the image pixels and then employs BDBE to encode the prediction errors, creating space for data embedding. The resulting encoded data are subsequently encrypted using a secure stream cipher, such as the Advanced Encryption Standard, before being transmitted to a data hider. The data hider can embed confidential information within the encrypted image for the purposes of storage, management, or other processing. Upon receiving the data, an authorized receiver can accurately recover the original image and the embedded data without any loss. Experimental results demonstrate that our RDH-EI scheme achieves a significantly larger embedding capacity compared to several state-of-the-art schemes.
“The Spanish Cathedral”, a Prototype of Mobile Application for the Access to the Religious Cultural Heritage of Gothic Hispanic Cathedrals
Authors: Barbosa Jennifer Carolina Cruz , Zymla Herbert González
Published: January 2024

After an in-depth examination of the communication strategies, digital offerings, and audio guides currently employed by various Spanish cathedrals constructed during the 12th and 15th centuries, it was detected that there was a need to gradually build and improve an integral and unified tool that serves as a reference for the learning of the artistic elements that characterize the mentioned constructions. This will contribute to both the promotion of the cathedral —understood as an ensemble— and its communication with the public.

This article introduces the conceptualization and design of the mobile application “La Catedral Hispana”, a high-fidelity prototype that seeks to promote Spanish cathedrals with Gothic elements in their construction. This prototype encompasses two areas of study for its task: the research of Gothic architecture in cathedrals and the principles of user experience (interaction design, information architecture, and interface development), for the correct development of the sample, using the Figma software for its design and implementation.

The objectives lay not only in providing a tool that facilitates access and shares academic information, but also in establishing relationships among the diverse Spanish cathedrals by means of their common features. The Spanish Cathedral is a proposal for promoting the democratization of cultural information, the learning of the value of heritage, and the development of a new solid and accessible communication channel that enables the target audience to both value and recognize one of the most important types of constructions as a part of Spanish identity.
The Alternative Model of Personality Disorders: Assessment, Convergent and Discriminant Validity, and a Look to the Future
Authors: García Luis F. , Gutiérrez Fernando , García Oscar , Aluja Anton
Published: January 2024

The Alternative Model of Personality Disorders (AMPD) is a dimensional, empirically based diagnostic system developed to overcome the serious limitations of traditional categories. We review the mounting evidence on its convergent and discriminant validity, with an incursion into the less-studied ICD-11 system. In the literature, the AMPD's Pathological Trait Model (Criterion B) shows excellent convergence with normal personality traits, and it could be useful as an organizing framework for mental disorders. In contrast, Personality Functioning (Criterion A) cannot be distinguished from personality traits, lacks both discriminant and incremental validity, and has a shaky theoretical background. We offer some suggestions with a view to the future. These include removing Criterion A, using the real-life consequences of traits as indicators of severity, delving into the dynamic mechanisms underlying traits, and furthering the integration of currently disengaged psychological paradigms that can shape a sounder clinical science.
Scalable Processes for Culturing Meat Using Edible Scaffolds
Authors: Kawecki N. Stephanie , Chen Kathleen K. , Smith Corinne S. , Xie Qingwen , Cohen Julian M. , Rowat Amy C.
Published: January 2024

There is increasing consumer demand for alternative animal protein products that are delicious and sustainably produced to address concerns about the impacts of mass-produced meat on human and planetary health. Cultured meat has the potential to provide a source of nutritious dietary protein that both is palatable and has reduced environmental impact. However, strategies to support the production of cultured meats at the scale required for food consumption will be critical. In this review, we discuss the current challenges and opportunities of using edible scaffolds for scaling up the production of cultured meat. We provide an overview of different types of edible scaffolds, scaffold fabrication techniques, and common scaffold materials. Finally, we highlight potential advantages of using edible scaffolds to advance cultured meat production by accelerating cell growth and differentiation, providing structure to build complex 3D tissues, and enhancing the nutritional and sensory properties of cultured meat.
Cerebrovascular adaptations to habitual resistance exercise with aging
Authors: Allison Elric Y. , Al-Khazraji Baraa K.
Published: January 2024

Resistance training (RT) is associated with improved metabolism, bone density, muscular strength, and lower risk of osteoporosis, sarcopenia, and cardiovascular disease. Although RT imparts many physiological benefits, cerebrovascular adaptations to chronic RT are not well defined. Participation in RT is associated with greater resting peripheral arterial diameters, improved endothelial function, and general cardiovascular health, whereas simultaneously linked to reductions in central arterial compliance. Rapid blood pressure fluctuations during resistance exercise, combined with reduced arterial compliance, could lead to cerebral microvasculature damage and subsequent cerebral hypoperfusion. Reductions in cerebral blood flow (CBF) accompany normal aging, where chronic reductions in CBF are associated with changes in brain structure and function, and increased risk of neurodegeneration. It remains unclear whether reductions in arterial compliance with RT relate to subclinical cerebrovascular pathology, or if such adaptations require interpretation in the context of RT specifically. The purpose of this narrative review is to synthesize literature pertaining to cerebrovascular adaptations to RT at different stages of the life span. This review also aims to identify gaps in the current understanding of the long-term impacts of RT on cerebral hemodynamics and provide a mechanistic rationale for these adaptations as they relate to aging, cerebral vasculature, and overall brain health.
Changes in Corneal Higher-Order Aberrations and Ocular Biometric Measurements after Phacoemulsification Combined with Goniosynechialysis in Primary Angle Closure/Glaucoma Patients
Authors: Xia Jiali , Guo Siqi , Hu Fei , Fan Liqi , Yu Ling , Ye Jian
Published: January 2024

Purpose. To compare corneal higher-order aberrations (HOAs), refractive error, and ocular biological parameters before and after phacoemulsification combined with goniosynechialysis (Phaco-GSL) in primary angle closure/glaucoma (PAC/PACG) patients with different axial lengths (ALs). Methods. In this prospective study, cataract patients diagnosed with PAC/PACG were categorized into two groups based on their ALs: the short AL group (AL ≤ 22.5 mm) and the normal AL group (22.5 < AL ≤ 24.5 mm). The pre- and postsurgery measurements of intraocular pressure (IOP) and best-corrected visual acuity (BCVA) were conducted at 1 day, 1 week, 1 month, 3 months, 6 months, and 12 months. Additionally, the assessments included corneal HOAs, the number of antiglaucoma medications, visual field parameters, manifest refraction, and other ocular biological parameters before surgery and at the final follow-up. Results. Prior to surgery, the two groups exhibited no significant differences, except for AL, curvature value, and Z (4, 0) of the posterior corneal surface (all P<0.01). Following surgery, BCVA improved, and IOP decreased significantly in both groups (P<0.01). Both anterior and total corneal HOAs, along with Z (3, −3), increased in the two groups (all P<0.05), with the normal AL group exhibiting a significantly greater increase in total cornea Z (3, −3) than the short AL group (P=0.047). The normal AL group also exhibited a slight tendency towards hyperopia (P<0.01). Significant changes were observed in the visual field index and mean deviation in both groups (P<0.05). Conclusions. Phaco-GSL resulted in an increased corneal HOAs, particularly trefoil, with variations based on the patient’s AL. Patients with normal ALs tended to shift towards hyperopia after surgery.
Research on Demagnetization Fault Diagnosis Method of Mine Cutting Permanent Magnet Synchronous Motor
Authors: Ye Guo , Lu Yanbin , Ju Jinyong , Sheng Lianchao
Published: January 2024

To give timely and accurate diagnosis in the early stage of demagnetization failure for effective control and treatment, based on wavelet packet analysis, principal component analysis (PCA) dimensionality reduction, and least squares support vector machine(LSSVM), the extraction of features and the classification of demagnetization faults are completed. Since it is difficult to collect real data sets of demagnetization faults in practice, a two-dimensional finite element simulation model of permanent magnet synchronous motor (PMSM) under uniform demagnetization and partial demagnetization faults is established based on the Maxwell simulation platform. The wavelet packet analysis is used to extract the demagnetization feature of the A-phase current of the PMSM. Based on PCA dimensionality reduction, the dimensionality reduction of fault features is realized. The LSSVM is used to identify the fault and complete the fault classification. The simulation results show that the method has a high classification accuracy rate for demagnetization faults.
PHS: A Pulse Sequence Method Based on Hyperbolic Frequency Modulation for Speed Measurement
Authors: Ping Tao , Song Caixia , Qi Zhiguo , Xu Pengmin
Published: January 2024

The channel in the marine environment is a time-varying and space-varying channel. Pulse-truncated continuous wave (PCW) speed measurement is often used in sonar, but the instability effect of PCW signal in the channel limits the effectiveness of speed measurement. Hyperbolic frequency modulation (HFM) signal is insensitive to Doppler; therefore, HFM signals are widely used in ranging and velocity measurement of sonar and radar. However, due to the filtering effect of the marine environment, the HFM signal of a single frequency band may cause excessive transmission loss, and the echo energy may be too weak to detect the target. Based on the analysis of the influence of speed on the distance measurement of HFM signal, a pulse sequence method based on HFM for speed measurement (PHS) is proposed, which uses HFM signals of different frequency bands and pulse widths in the pulse sequence to perform speed measurement. Extensive simulation results show that PHS method not only guarantees the speed measurement but also makes full use of the energy of the HFM sequence to improve the accuracy of the distance measurement. And PHS method is valuable to the practical application of engineering.