Using Graphs to Perform Effective Sensor-Based Human Activity Recognition in Smart Homes.

There has been a resurgence of applications focused on human activity recognition (HAR) in smart homes, especially in the field of ambient intelligence and assisted-living technologies. However, such applications present numerous significant challenges to any automated analysis system operating in the real world, such as variability, sparsity, and noise in sensor measurements. Although state-of-the-art HAR systems have made considerable strides in addressing some of these challenges, they suffer from a practical limitation: they require successful pre-segmentation of continuous sensor data streams prior to automated recognition, i.e., they assume that an oracle is present during deployment, and that it is capable of identifying time windows of interest across discrete sensor events. To overcome this limitation, we propose a novel graph-guided neural network approach that performs activity recognition by learning explicit co-firing relationships between sensors. We accomplish this by learning a more expressive graph structure representing the sensor network in a smart home in a data-driven manner. Our approach maps discrete input sensor measurements to a feature space through the application of attention mechanisms and hierarchical pooling of node embeddings. We demonstrate the effectiveness of our proposed approach by conducting several experiments on CASAS datasets, showing that the resulting graph-guided neural network outperforms the state-of-the-art method for HAR in smart homes across multiple datasets and by large margins. These results are promising because they push HAR for smart homes closer to real-world applications.

Developing a Personalized Meal Recommendation System for Chinese Older Adults: Observational Cohort Study.

BACKGROUND: China's older population is facing serious health challenges, including malnutrition and multiple chronic conditions. There is a critical need for tailored food recommendation systems. Knowledge graph-based food recommendations offer considerable promise in delivering personalized nutritional support. However, the integration of disease-based nutritional principles and preference-related requirements needs to be optimized in current recommendation processes. OBJECTIVE: This study aims to develop a knowledge graph-based personalized meal recommendation system for community-dwelling older adults and to conduct preliminary effectiveness testing. METHODS: We developed ElCombo, a personalized meal recommendation system driven by user profiles and food knowledge graphs. User profiles were established from a survey of 96 community-dwelling older adults. Food knowledge graphs were supported by data from websites of Chinese cuisine recipes and eating history, consisting of 5 entity classes: dishes, ingredients, category of ingredients, nutrients, and diseases, along with their attributes and interrelations. A personalized meal recommendation algorithm was then developed to synthesize this information to generate packaged meals as outputs, considering disease-related nutritional constraints and personal dietary preferences. Furthermore, a validation study using a real-world data set collected from 96 community-dwelling older adults was conducted to assess ElCombo's effectiveness in modifying their dietary habits over a 1-month intervention, using simulated data for impact analysis. RESULTS: Our recommendation system, ElCombo, was evaluated by comparing the dietary diversity and diet quality of its recommended meals with those of the autonomous choices of 96 eligible community-dwelling older adults. Participants were grouped based on whether they had a recorded eating history, with 34 (35%) having and 62 (65%) lacking such data. Simulation experiments based on retrospective data over a 30-day evaluation revealed that ElCombo's meal recommendations consistently had significantly higher diet quality and dietary diversity compared to the older adults' own selections (P<.001). In addition, case studies of 2 older adults, 1 with and 1 without prior eating records, showcased ElCombo's ability to fulfill complex nutritional requirements associated with multiple morbidities, personalized to each individual's health profile and dietary requirements. CONCLUSIONS: ElCombo has shown enhanced potential for improving dietary quality and diversity among community-dwelling older adults in simulation tests. The evaluation metrics suggest that the food choices supported by the personalized meal recommendation system surpass autonomous selections. Future research will focus on validating and refining ElCombo's performance in real-world settings, emphasizing the robust management of complex health data. The system's scalability and adaptability pinpoint its potential for making a meaningful impact on the nutritional health of older adults.

Activation of ERK/NF-kB Pathways Contributes to the Inflammatory Response in Epithelial Cells and Macrophages Following Manganese Exposure.

Different types of metals, including manganese (Mn), are constantly encountered in various environmental matrices due to natural and anthropogenic activities. They induce a sustained inflammatory response in various organs, which is considered to be an important priming event in the pathogenesis of several diseases. Mn-induced neuroinflammation and subsequent neurodegeneration are well recognized. However, emerging data suggest that occupationally and environmentally relevant levels may affect various organs, including the lungs. Therefore, the present study was carried out to investigate the effects of Mn (as Mn2+) exposure on the inflammatory response in human normal bronchial (BEAS-2B) and adenocarcinoma alveolar basal (A549) epithelial cells, as well as in murine macrophages (J774). Mn2+ exposure significantly induced mRNA and protein expression of various pro-inflammatory mediators (cytokines and chemokines) in all cells compared to corresponding vehicle controls. Furthermore, Mn2+ treatment also led to increased phosphorylation of extracellular-signal-regulated kinase (ERK)1/2 and nuclear factor-kappa B (NF-kB) p65 in both epithelial cells and macrophages. As expected, cells treated with inhibitors of ERK1/2 (PD98059) and NF-kB p65 (IMD0354) effectively mitigated the expression of various pro-inflammatory mediators induced by Mn2+, suggesting that ERK/NF-kB pathways have a critical role in the Mn2+-induced inflammatory response. Further, in vivo studies are required to confirm these in vitro findings to support clinical translation.

Study on chromatin regulation patterns of expression vectors in the PhiC31 integration site.

The PhiC31 integration system allows for targeted and efficient transgene integration and expression by recognizing pseudo attP sites in mammalian cells and integrating the exogenous genes into the open chromatin regions of active chromatin. In order to investigate the regulatory patterns of efficient gene expression in the open chromatin region of PhiC31 integration, this study utilized Ubiquitous Chromatin Opening Element (UCOE) and activating RNA (saRNA) to modulate the chromatin structure in the promoter region of the PhiC31 integration vector. The study analysed the effects of DNA methylation and nucleosome occupancy changes in the integrated promoter on gene expression levels. The results showed that for the OCT4 promoter with moderate CG density, DNA methylation had a smaller impact on expression compared to changes in nucleosome positioning near the transcription start site, which was crucial for enhancing downstream gene expression. On the other hand, for the SOX2 promoter with high CG density, increased methylation in the CpG island upstream of the transcription start site played a key role in affecting high expression, but the positioning and clustering of nucleosomes also had an important influence. In conclusion, analysing the DNA methylation patterns, nucleosome positioning, and quantity distribution of different promoters can determine whether the PhiC31 integration site possesses the potential to further enhance expression or overcome transgene silencing effects by utilizing chromatin regulatory elements.

Understanding the pivotal role of ubiquitous Yellow River suspend sediment in efficiently degrading metronidazole pollutants in water environments.

Sulfite-based advanced oxidation technology has received considerable attention for its application in organic pollutants elimination. However, the potential of natural sediments as effective catalysts for sulfite activation has been overlooked. This study investigates a novel process utilizing suspended sediment/sulfite (SS/S(IV)) for degradation of metronidazole (MNZ). Our results demonstrate that MNZ degradation efficiency can reach to 93.1 % within 90 min with 12.0 g SS and 2.0 mM sulfite. The influencing environmental factors, including initial pH, SS dosage, S(IV) concentration, temperature, and co-existing substances were systematically investigated. Quenching experiments and electron paramagnetic resonance analyses results indicate that SO3•- is the primary active substance responsible for MNZ degradation, with involvement of SO4•-, SO5•-, and •OH. X-ray photoelectron spectroscopy and Mössbauer spectra reveal that Fe (III)-silicates play a crucial role in activating S(IV). Furthermore, analysis of degradation intermediates and pathways of MNZ is conducted using liquid chromatography with mass spectrometry (LC -MS). The toxicity of MNZ and its intermediates were also systematically evaluated by the T.E.ST. program and wheat seeds germination test. This study offers valuable insight into the activation of sulfite by natural sediments and could contribute to the development of SS-based advanced oxidation processes (AOPs) for the in-situ remediation of antibiotics-contaminated water environments.

Cyber-agricultural systems for crop breeding and sustainable production.

The cyber-agricultural system (CAS) represents an overarching framework of agriculture that leverages recent advances in ubiquitous sensing, artificial intelligence, smart actuators, and scalable cyberinfrastructure (CI) in both breeding and production agriculture. We discuss the recent progress and perspective of the three fundamental components of CAS - sensing, modeling, and actuation - and the emerging concept of agricultural digital twins (DTs). We also discuss how scalable CI is becoming a key enabler of smart agriculture. In this review we shed light on the significance of CAS in revolutionizing crop breeding and production by enhancing efficiency, productivity, sustainability, and resilience to changing climate. Finally, we identify underexplored and promising future directions for CAS research and development.

WiCHORD+: A Scalable, Sustainable, and P2P Chord-Based Ecosystem for Smart Agriculture Applications.

In the evolving landscape of Industry 4.0, the convergence of peer-to-peer (P2P) systems, LoRa-enabled wireless sensor networks (WSNs), and distributed hash tables (DHTs) represents a major advancement that enhances sustainability in the modern agriculture framework and its applications. In this study, we propose a P2P Chord-based ecosystem for sustainable and smart agriculture applications, inspired by the inner workings of the Chord protocol. The node-centric approach of WiCHORD+ is a standout feature, streamlining operations in WSNs and leading to more energy-efficient and straightforward system interactions. Instead of traditional key-centric methods, WiCHORD+ is a node-centric protocol that is compatible with the inherent characteristics of WSNs. This unique design integrates seamlessly with distributed hash tables (DHTs), providing an efficient mechanism to locate nodes and ensure robust data retrieval while reducing energy consumption. Additionally, by utilizing the MAC address of each node in data routing, WiCHORD+ offers a more direct and efficient data lookup mechanism, essential for the timely and energy-efficient operation of WSNs. While the increasing dependence of smart agriculture on cloud computing environments for data storage and machine learning techniques for real-time prediction and analytics continues, frameworks like the proposed WiCHORD+ appear promising for future IoT applications due to their compatibility with modern devices and peripherals. Ultimately, the proposed approach aims to effectively incorporate LoRa, WSNs, DHTs, cloud computing, and machine learning, by providing practical solutions to the ongoing challenges in the current smart agriculture landscape and IoT applications.

Marinomonas transparens sp. nov. and Marinomonas sargassi sp. nov., isolated from marine alga.

Two Gram-stain-negative, rod-shaped, non-spore-forming, strictly aerobic, motile bacteria with a single polar flagellum, designated strains C1424T and C2222T, were isolated from marine alga collected from the sea shore at Yantai, PR China. Strain C1424T grew at 4-37 °C and in the presence of 1-9 % (w/v) NaCl, while strain C2222T grew at 4-32 °C with 1-6 % (w/v) NaCl. Phylogenetic analysis based on 16S rRNA gene sequences and concatenated amino acid sequences of 120 ubiquitous single-copy proteins showed that both strains C1424T and C2222T belonged to the genus Marinomonas, showing highest 16S rRNA gene sequence similarities to the type strains of Marinomonas primoryensis (98.1 %) and Marinomonas dokdonensis (98.1 %), respectively. The major fatty acids of the two strains were C18 : 1 ω6c and/or C18 : 1 ω7c, C16 : 1 ω6c and/or C16 : 1 ω7c and C16 : 0, their predominant polar lipids were phosphatidylethanolamine and phosphatidylglycerol, and their sole respiratory quinone was Q8. On the basis of polyphasic analyses, strains C1424T and C2222T are considered to represent two novel species within the genus Marinomonas, for which the names Marinomonas transparens sp. nov. and Marinomonas sargassi sp. nov. are proposed. The type strains are C1424T (=KCTC 72119T=MCCC 1K03601T) and C2222T (=KCTC 72120T=MCCC 1K03602T), respectively.

Histochemistry and transcriptomics of mucins and peritrophic membrane (PM) proteins along the midgut of a beetle with incomplete PM and their complementary function.

The midgut of Zabrotes subfasciatus (Coleoptera) and other insects may have regions lacking a peritrophic membrane (matrix, PM) and covered with a jelly-like material known as peritrophic gel. This work was undertaken to test the hypothesis that the peritrophic gel is a vertebrate-like mucus. By histochemistry we identified mucins along the whole midgut, which contrasts with the known occurrence of PM only at the posterior midgut. We also analyzed the expression of the genes coding for mucus-forming mucins (Mf-mucins), peritrophins, chitin synthases and chitin deacetylases along the midgut and carcass (insect without midgut) by RNA-seq. Mf-mucins were identified as proteins with high O-glycosylation and multiple tandem repeats of Pro/Thr/Ser residues. Peritrophins were separated into PM proteins, cuticular proteins analogous to peritrophins (CPAPs) and ubiquitous-chitin-binding domain-(CBD)-containing proteins (UCBPs). PM proteins have at least 3, CPAP one or 3, and UCBPs have a varied number of CBDs. PM proteins are more expressed at midgut, CPAP at the carcass, and UCBP at both. The results showed that most PM proteins are mainly expressed at the posterior midgut, together with midgut chitin synthase and chitin deacetylase, and in agreement with the presence of PM only at the posterior midgut by visual inspection. The excretion of most midgut chitinase is avoided, suggesting that the shortened PM is functional. Mf-mucins are expressed along the whole midgut, probably forming the extracellular mucus layer observed by histochemistry. Thus, the lack of PM at anterior and middle midgut causes the exposure of a mucus, which may correspond to the previously described peritrophic gel. The putative functional interplay of mucus and PM is discussed. The major role of mucus is proposed to be tissue protection and of PM to enhancing digestive efficiency by allowing enzyme recycling.

The Dosing of Mobile-Based Just-in-Time Adaptive Self-Management Prompts for Caregivers: Preliminary Findings From a Pilot Microrandomized Study.

BACKGROUND: Caregivers of people with chronic illnesses often face negative stress-related health outcomes and are unavailable for traditional face-to-face interventions due to the intensity and constraints of their caregiver role. Just-in-time adaptive interventions (JITAIs) have emerged as a design framework that is particularly suited for interventional mobile health studies that deliver in-the-moment prompts that aim to promote healthy behavioral and psychological changes while minimizing user burden and expense. While JITAIs have the potential to improve caregivers' health-related quality of life (HRQOL), their effectiveness for caregivers remains poorly understood. OBJECTIVE: The primary objective of this study is to evaluate the dose-response relationship of a fully automated JITAI-based self-management intervention involving personalized mobile app notifications targeted at decreasing the level of caregiver strain, anxiety, and depression. The secondary objective is to investigate whether the effectiveness of this mobile health intervention was moderated by the caregiver group. We also explored whether the effectiveness of this intervention was moderated by (1) previous HRQOL measures, (2) the number of weeks in the study, (3) step count, and (4) minutes of sleep. METHODS: We examined 36 caregivers from 3 disease groups (10 from spinal cord injury, 11 from Huntington disease, and 25 from allogeneic hematopoietic cell transplantation) in the intervention arm of a larger randomized controlled trial (subjects in the other arm received no prompts from the mobile app) designed to examine the acceptability and feasibility of this intensive type of trial design. A series of multivariate linear models implementing a weighted and centered least squares estimator were used to assess the JITAI efficacy and effect. RESULTS: We found preliminary support for a positive dose-response relationship between the number of administered JITAI messages and JITAI efficacy in improving caregiver strain, anxiety, and depression; while most of these associations did not meet conventional levels of significance, there was a significant association between high-frequency JITAI and caregiver strain. Specifically, administering 5-6 messages per week as opposed to no messages resulted in a significant decrease in the HRQOL score of caregiver strain with an estimate of -6.31 (95% CI -11.76 to -0.12; P=.046). In addition, we found that the caregiver groups and the participants' levels of depression in the previous week moderated JITAI efficacy. CONCLUSIONS: This study provides preliminary evidence to support the effectiveness of the self-management JITAI and offers practical guidance for designing future personalized JITAI strategies for diverse caregiver groups. TRIAL REGISTRATION: ClinicalTrials.gov NCT04556591; https://clinicaltrials.gov/ct2/show/NCT04556591.

Securing Group Patient Communication in 6G-Aided Dynamic Ubiquitous Healthcare with Real-Time Mobile DNA Sequencing.

(1) Background: With an advanced technique, third-generation sequencing (TGS) provides services with long deoxyribonucleic acid (DNA) reads and super short sequencing time. It enables onsite mobile DNA sequencing solutions for enabling ubiquitous healthcare (U-healthcare) services with modern mobile technology and smart entities in the internet of living things (IoLT). Due to some strict requirements, 6G technology can efficiently facilitate communications in a truly intelligent U-healthcare IoLT system. (2) Research problems: conventional single user-server architecture is not able to enable group conversations where "multiple patients-server" communication or "patient-patient" communication in the group is required. The communications are carried out via the open Internet, which is not a trusted channel. Since heath data and medical information are very sensitive, security and privacy concerns in the communication systems have become extremely important. (3) Purpose: the author aims to propose a dynamic group-based patient-authenticated key distribution protocol for 6G-aided U-healthcare services enabled by mobile DNA sequencing. In the protocol, an authenticated common session key is distributed by the server to the patients. Using the key, patients in a healthcare group are allowed to securely connect with the service provider or with each other for specific purposes of communication. (4) Results: the group key distribution process is protected by a secure three-factor authentication mechanism along with an efficient sequencing-device-based single sign-on (SD-SSO) solution. Based on traceable information stored in the server database, the proposed approach can provide patient-centered services which are available on multiple mobile devices. Security robustness of the proposed protocol is proven by well-known verification tools and a detailed semantic discussion. Performance evaluation shows that the protocol provides more functionality and incurs a reasonable overhead in comparison with the existing works.

Multi-user conflict resolution mechanisms for smart home environments.

Context-awareness is a pervasive computing enabling technology that allows context-aware applications to respond to multiple contexts such as activity, location, temperature, and so on. When many users attempt to access the same context-aware application, user conflicts may emerge. This issue is emphasized, and a conflict resolution approach is presented to address it. Although there are other conflict resolution approaches in the literature, the one presented here is unique in that it considers the users' special cases such as their sickness, examinations, and so on when resolving conflicts. The proposed approach is helpful when several users with different special cases try to access the same context-aware application. To demonstrate the usefulness of the proposed approach, a conflict manager is integrated with the UbiREAL simulated context-aware home environment. The integrated conflict manager resolves conflicts by taking users special cases into account and employing either automated, mediated, or hybrid conflict resolution approaches. The evaluation of the proposed approach demonstrates that users are satisfied with it and that it is critical and essential to employ users' special cases in detecting and resolving users conflicts.

An indoor location-based hospital Porter management system and trace analysis.

Porters play an important role in supporting hospital operations. Their responsibilities include transporting patients and medical equipment between wards and departments. They also need to deliver specimens, drugs, and patients' notes to the correct place at the right time. Therefore, maintaining a trustworthy and reliable porter team is crucial for hospitals to ensure the quality of patient care and smooth the flow of daily operations. However, most existing porter systems lack detailed information about the porter movement process. For example, the location of porters is not transparent to the dispatch center. Thus, the dispatcher does not know if porters are spending all their time providing services. The invisibility makes it difficult for hospitals to assess and improve the efficiency of porter operations. In this work, we first developed an indoor location-based porter management system (LOPS) on top of the infrastructure of indoor positioning services in the hospital National Taiwan University Hospital YunLin Branch. The LOPS provides real-time location information of porters for the dispatcher to prioritize tasks and manage assignments. We then conducted a 5-month field trial to collect porters' traces. Finally, a series of quantitative analyses were performed to assess the efficiency of porter operations, such as the movement distribution of porters in different time periods and areas, workload distribution among porters, and possible bottlenecks of delivering services. Based on the analysis results, recommendations were given to improve the efficiency of the porter team.

Ubiquitous conservative interaction patterns between post-spliced introns and their mRNAs revealed by genome-wide interspecies comparison.

Introns, as important vectors of biological functions, can influence many stages of mRNA metabolism. However, in recent research, post-spliced introns are rarely considered. In this study, the optimal matched regions between introns and their mRNAs in nine model organism genomes were investigated with improved Smith-Waterman local alignment software. Our results showed that the distributions of mRNA optimal matched frequencies were highly consistent or universal. There are optimal matched frequency peaks in the UTR regions, which are obvious, especially in the 3'-UTR. The matched frequencies are relatively low in the CDS regions of the mRNA. The distributions of the optimal matched frequencies around the functional sites are also remarkably changed. The centers of the GC content distributions for different sequences are different. The matched rate distributions are highly consistent and are located mainly between 60% and 80%. The most probable value of the optimal matched segments is about 20 bp for lower eukaryotes and 30 bp for higher eukaryotes. These results show that there are abundant functional units in the introns, and these functional units are correlated structurally with all kinds of sequences of mRNA. The interaction between the post-spliced introns and their corresponding mRNAs may play a key role in gene expression.

On the Unknown Proteins of Eukaryotic Proteomes.

To study unknown proteins on a large scale, a reference system has been set up for the three better studied eukaryotic kingdoms, built with 36 proteomes as taxonomically diverse as possible. Proteins from 362 other eukaryotic proteomes with no known homologue in this set were then analyzed, focusing noteworthy on singletons, that is, on such proteins with no known homologue in their own proteome. Consistently, for a given species, no more than 12% of the singletons thus found are known at the protein level, according to Uniprot. In addition, since they rely on the information found in the alignment of homologous sequences, predictions of AlphaFold2 for their tridimensional structure are poor. In the case of metazoan species, the number of singletons rarely exceeds 1000 for the species the closest to the reference system (divergence times below 75 Myr). Interestingly, in the cases of viridiplantae and fungi, larger amounts of singletons are found for such species, as if the timescale on which singletons are added to proteomes were different in metazoa and in other eukaryotic kingdoms. In order to confirm this phenomenon, further studies of proteomes closer to those of the reference system are, however, needed.

Implementation of ubiquitous chromatin opening elements as artificial integration sites for CRISPR/Cas9-mediated knock-in in mammalian cells.

CRISPR/Cas9-mediated targeted gene integration (TI) has been used to generate recombinant mammalian cell lines with predictable transgene expression. Identifying genomic hot spots that render high and stable transgene expression and knock-in (KI) efficiency is critical for fully implementing TI-mediated cell line development (CLD); however, such identification is cumbersome. In this study, we developed an artificial KI construct that can be used as a hot spot at different genomic loci. The ubiquitous chromatin opening element (UCOE) was employed because of its ability to open chromatin and enable stable and site-independent transgene expression. UCOE KI cassettes were randomly integrated into CHO-K1 and HEK293T cells, followed by TI of enhanced green fluorescent protein (EGFP) onto the artificial UCOE KI site. The CHO-K1 random pool harboring 5'2.2A2UCOE-CMV displayed a significant increase in EGFP expression level and KI efficiency compared with that of the control without UCOE. In addition, 5'2.2A2UCOE-CMV showed improved Cas9 accessibility in the HEK293T genome, leading to an increase in indel frequency and homology-independent KI. Overall, this assessment revealed the potential of UCOE KI constructs as artificial integration sites in streamlining the screening of high-production targeted integrants by mitigating the selection of genomic hot spots.

Domain Adaptation Methods for Lab-to-Field Human Context Recognition.

Human context recognition (HCR) using sensor data is a crucial task in Context-Aware (CA) applications in domains such as healthcare and security. Supervised machine learning HCR models are trained using smartphone HCR datasets that are scripted or gathered in-the-wild. Scripted datasets are most accurate because of their consistent visit patterns. Supervised machine learning HCR models perform well on scripted datasets but poorly on realistic data. In-the-wild datasets are more realistic, but cause HCR models to perform worse due to data imbalance, missing or incorrect labels, and a wide variety of phone placements and device types. Lab-to-field approaches learn a robust data representation from a scripted, high-fidelity dataset, which is then used for enhancing performance on a noisy, in-the-wild dataset with similar labels. This research introduces Triplet-based Domain Adaptation for Context REcognition (Triple-DARE), a lab-to-field neural network method that combines three unique loss functions to enhance intra-class compactness and inter-class separation within the embedding space of multi-labeled datasets: (1) domain alignment loss in order to learn domain-invariant embeddings; (2) classification loss to preserve task-discriminative features; and (3) joint fusion triplet loss. Rigorous evaluations showed that Triple-DARE achieved 6.3% and 4.5% higher F1-score and classification, respectively, than state-of-the-art HCR baselines and outperformed non-adaptive HCR models by 44.6% and 10.7%, respectively.

Corrigendum: SemNet: Learning semantic attributes for human activity recognition with deep belief networks.

[This corrects the article DOI: 10.3389/fdata.2022.879389.].

SenseFi: A library and benchmark on deep-learning-empowered WiFi human sensing.

Over the recent years, WiFi sensing has been rapidly developed for privacy-preserving, ubiquitous human-sensing applications, enabled by signal processing and deep-learning methods. However, a comprehensive public benchmark for deep learning in WiFi sensing, similar to that available for visual recognition, does not yet exist. In this article, we review recent progress in topics ranging from WiFi hardware platforms to sensing algorithms and propose a new library with a comprehensive benchmark, SenseFi. On this basis, we evaluate various deep-learning models in terms of distinct sensing tasks, WiFi platforms, recognition accuracy, model size, computational complexity, and feature transferability. Extensive experiments are performed whose results provide valuable insights into model design, learning strategy, and training techniques for real-world applications. In summary, SenseFi is a comprehensive benchmark with an open-source library for deep learning in WiFi sensing research that offers researchers a convenient tool to validate learning-based WiFi-sensing methods on multiple datasets and platforms.

Feasibility and Acceptability of an Internet of Things-Enabled Sedentary Behavior Intervention: Mixed Methods Study.

BACKGROUND: Encouraging office workers to break up prolonged sedentary behavior (SB) at work with regular microbreaks can be beneficial yet challenging. The Internet of Things (IoT) offers great promise for delivering more subtle and hence acceptable behavior change interventions in the workplace. We previously developed an IoT-enabled SB intervention, called WorkMyWay, by applying a combination of theory-informed and human-centered design approaches. According to the Medical Research Council's framework for developing and evaluating complex interventions such as WorkMyWay, process evaluation in the feasibility phase can help establish the viability of novel modes of delivery and identify facilitators and barriers to successful delivery. OBJECTIVE: This study aims to evaluate the feasibility and acceptability of the WorkMyWay intervention and its technological delivery system. METHODS: A mixed methods approach was adopted. A sample of 15 office workers were recruited to use WorkMyWay during work hours for 6 weeks. Questionnaires were administered before and after the intervention period to assess self-report occupational sitting and physical activity (OSPA) and psychosocial variables theoretically aligned with prolonged occupational SB (eg, intention, perceived behavioral control, prospective memory and retrospective memory of breaks, and automaticity of regular break behaviors). Behavioral and interactional data were obtained through the system database to determine adherence, quality of delivery, compliance, and objective OSPA. Semistructured interviews were conducted at the end of the study, and a thematic analysis was performed on interview transcripts. RESULTS: All 15 participants completed the study (attrition=0%) and on average used the system for 25 tracking days (out of a possible 30 days; adherence=83%). Although no significant change was observed in either objective or self-report OSPA, postintervention improvements were significant in the automaticity of regular break behaviors (t14=2.606; P=.02), retrospective memory of breaks (t14=7.926; P<.001), and prospective memory of breaks (t14=-2.661; P=.02). The qualitative analysis identified 6 themes, which lent support to the high acceptability of WorkMyWay, though delivery was compromised by issues concerning Bluetooth connectivity and factors related to user behaviors. Fixing technical issues, tailoring to individual differences, soliciting organizational supports, and harnessing interpersonal influences could facilitate delivery and enhance acceptance. CONCLUSIONS: It is acceptable and feasible to deliver an SB intervention with an IoT system that involves a wearable activity tracking device, an app, and a digitally augmented everyday object (eg, cup). More industrial design and technological development work on WorkMyWay is warranted to improve delivery. Future research should seek to establish the broad acceptability of similar IoT-enabled interventions while expanding the range of digitally augmented objects as the modes of delivery to meet diverse needs.