bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of brief psychosocial support for patients with cancer and their relatives: a quasi-experimental evaluation of cancer counselling centres
Authors: Lingens Solveigh Paola , Schilling Georgia , Schulz Holger , Bleich Christiane
Published: March 2023

Objectives

The aim of this study was to evaluate the effectiveness of brief psychosocial support for patients with cancer and their relatives regarding their mental health.

Design

Quasi-experimental controlled trial with measurements at three time points (baseline, after 2 weeks and after 12 weeks).

Setting

The intervention group (IG) was recruited at two cancer counselling centres in Germany. The control group (CG) included patients with cancer or relatives who did not seek support.

Participants

In total, n=885 participants were recruited and n=459 were eligible for the analysis (IG, n=264; CG, n=195).

Intervention

One to two psychosocial support sessions (approximately hour) provided by a psycho-oncologist or social worker.

Primary and secondary outcome measures

The primary outcome was distress. The secondary outcomes were anxiety and depressive symptoms, well-being, cancer-specific and generic quality of life (QoL), self-efficacy and fatigue.

Results

The linear mixed model analysis showed significant differences between IG and CG at follow-up for distress (d=0.36), p=0.001), depressive (d=0.22), p=0.005) and anxiety symptoms (d=0.22), p=0.003), well-being (d=0.26, p=0.002), QoL (QoL mental; d=0.26, p=0.003), self-efficacy (d=0.21, p=0.011) and QoL (global; d=0.27, p=0.009). The changes were not significant for QoL (physical; d=0.04, p=0.618), cancer-specific QoL (symptoms; d=0.13, p=0.093), cancer-specific QoL (functional; d=0.08, p=0.274) and fatigue (d=0.04, p=0.643).

Conclusion

The results suggest that brief psychosocial support is associated with the improvement of mental health of patients with cancer and their relatives after 3 months.

Trial registration number

DRKS00015516.
Plasma inflammation for predicting phenotypic conversion and clinical progression of autosomal dominant frontotemporal lobar degeneration
Authors: Asken Breton M , Ljubenkov Peter A , Staffaroni Adam M , Casaletto Kaitlin B , Vandevrede Lawren , Cobigo Yann , Rojas-Rodriguez Julio C , Rankin Katherine P , Kornak John , Heuer Hilary , Shigenaga Judy , Appleby Brian S , Bozoki Andrea C , Domoto-Reilly Kimiko , Ghoshal Nupur , Huey Edward , Litvan Irene , Masdeu Joseph C , Mendez Mario F , Pascual Belen , Pressman Peter , Tartaglia Maria Carmela , Kremers Walter , Forsberg Leah K , Boeve Brad F , Boxer Adam L , Rosen Howie J , Kramer Joel H
Published: March 2023

Background

Measuring systemic inflammatory markers may improve clinical prognosis and help identify targetable pathways for treatment in patients with autosomal dominant forms of frontotemporal lobar degeneration (FTLD).

Methods

We measured plasma concentrations of IL-6, TNFα and YKL-40 in pathogenic variant carriers (MAPT, C9orf72, GRN) and non-carrier family members enrolled in the ARTFL-LEFFTDS Longitudinal Frontotemporal Lobar Degeneration consortium. We evaluated associations between baseline plasma inflammation and rate of clinical and neuroimaging changes (linear mixed effects models with standardised (z) outcomes). We compared inflammation between asymptomatic carriers who remained clinically normal (‘asymptomatic non-converters’) and those who became symptomatic (‘asymptomatic converters’) using area under the curve analyses. Discrimination accuracy was compared with that of plasma neurofilament light chain (NfL).

Results

We studied 394 participants (non-carriers=143,C9orf72=117,GRN=62,MAPT=72). InMAPT, higher TNFα was associated with faster functional decline (B=0.12 (0.02, 0.22), p=0.02) and temporal lobe atrophy. InC9orf72,higher TNFα was associated with faster functional decline (B=0.09 (0.03, 0.16), p=0.006) and cognitive decline (B=−0.16 (−0.22, −0.10), p<0.001), while higher IL-6 was associated with faster functional decline (B=0.12 (0.03, 0.21), p=0.01). TNFα was higher in asymptomatic converters than non-converters (β=0.29 (0.09, 0.48), p=0.004) and improved discriminability compared with plasma NfL alone (ΔR2=0.16, p=0.007; NfL: OR=1.4 (1.03, 1.9), p=0.03; TNFα: OR=7.7 (1.7, 31.7), p=0.007).

Conclusions

Systemic proinflammatory protein measurement, particularly TNFα, may improve clinical prognosis in autosomal dominant FTLD pathogenic variant carriers who are not yet exhibiting severe impairment. Integrating TNFα with markers of neuronal dysfunction like NfL could optimise detection of impending symptom conversion in asymptomatic pathogenic variant carriers and may help personalise therapeutic approaches.
Impact of COVID-19 pandemic on cardiovascular diseases hospitalisation, management and mortality in Switzerland
Authors: Maung Ko Ko , Marques-Vidal Pedro
Published: March 2023

Background

COVID-19 pandemic led to a reduction in hospital admissions and intervention for other diseases in many countries. We aimed to assess the effect of COVID-19 pandemic on cardiovascular disease (CVD) hospitalisations, management and mortality in Switzerland.

Methods

Swiss hospital discharge and mortality data for period 2017–2020. CVD hospitalisations, CVD interventions and CVD mortality were assessed before (2017–2019) and during (2020) the pandemic. Expected numbers of admissions, interventions and deaths for 2020 were computed using simple linear regression model.

Results

Compared with 2017–2019, 2020 was characterised by a reduction of CVD admissions in age groups 65–84 and ≥85 by approximately 3700 and 1700 cases, respectively, and by an increase in the percentage of admissions with a Charlson index >8. The total number of CVD-related deaths decreased from 21 042 in 2017 to 19 901 in 2019, and increased to 20 511 in 2020, with an estimated excess of 1139 deaths. This increase was due to out-of-hospital deaths (+1342), while the number of in-hospital deaths decreased from 5030 in 2019 to 4796 in 2020, which concerned mostly subjects aged ≥85 years. The total number of admissions with cardiovascular interventions increased from 55 181 in 2017 to 57 864 in 2019, and decreased in 2020, with an estimated reduction of 4414 admissions; percutaneous transluminal coronary angioplasty (PTCA) was the exception, as the number and percentage of emergency admissions with PTCA increased. The preventive measures applied against COVID-19 inverted the seasonal pattern of CVD admissions, the highest number of admissions being found in summer and the lowest in winter.

Conclusion

The COVID-19 pandemic led to a reduction in CVD hospital admissions, planned CVD interventions, an increase in total and out-of-hospital CVD deaths and a change in seasonal patterns.
Sexual and reproductive health in Britain during the first year of the COVID-19 pandemic: cross-sectional population survey (Natsal-COVID-Wave 2) and national surveillance data
Authors: Mitchell Kirstin R , Willis Malachi , Dema Emily , Baxter Andrew J , Connolly Anne , Riddell Julie , Bosó Pérez Raquel , Clifton Soazig , Gibbs Jo , Tanton Clare , Geary Rebecca , Ratna Natasha , Mohammed Hamish , Unemo Magnus , Bonell Christopher , Copas Andrew , Sonnenberg Pam , Mercer Catherine H , Field Nigel
Published: March 2023

Objectives

To assess sexual behaviour, and sexual and reproductive health (SRH) outcomes, after 1 year of the COVID-19 pandemic in Britain.

Methods

6658 participants aged 18–59 and resident in Britain completed a cross-sectional web-panel survey (Natsal-COVID-Wave 2, March-April 2021), 1 year after the first lockdown. Natsal-COVID-2 follows the Natsal-COVID-Wave 1 survey (July-August 2020) which captured impacts in the initial months. Quota-based sampling and weighting resulted in a quasi-representative population sample. Data were contextualised with reference to the most recent probability sample population data (Natsal-3; collected 2010–12; 15 162 participants aged 16–74) and national surveillance data on recorded sexually transmitted infection (STI) testing, conceptions, and abortions in England/Wales (2010–2020). The main outcomes were: sexual behaviour; SRH service use; pregnancy, abortion and fertility management; sexual dissatisfaction, distress and difficulties.

Results

In the year from the first lockdown, over two-thirds of participants reported one or more sexual partners (women 71.8%; men 69.9%), while fewer than 20.0% reported a new partner (women 10.4%; men 16.8%). Median occasions of sex per month was two. Compared with 2010–12 (Natsal-3), we found less sexual risk behaviour (lower reporting of multiple partners, new partners, and new condomless partners), including among younger participants and those reporting same-sex behaviour. One in 10 women reported a pregnancy; pregnancies were fewer than in 2010–12 and less likely to be scored as unplanned. 19.3% of women and 22.8% of men were distressed or worried about their sex life, significantly more than in 2010–12. Compared with surveillance trends from 2010 to 2019, we found lower than expected use of STI-related services and HIV testing, lower levels of chlamydia testing, and fewer conceptions and abortions.

Conclusions

Our findings are consistent with significant changes in sexual behaviour, SRH, and service uptake in the year following the first lockdown in Britain. These data are foundational to SRH recovery and policy planning.
Bottom quark and tau lepton masses in a toy $$\textrm{SU}(6)$$ model
Authors: Chen Ning , Mao Ying-nan , Teng Zhaolong
Published: March 2023

We study a toy $$\textrm{SU}(6)$$

SU
(
6
)

model with the symmetry breaking pattern of the extended 331 symmetry of $$\textrm{SU}(3)_c \otimes \textrm{SU}(3)_W \otimes \textrm{U}(1)_X$$

SU

(
3
)

c

⊗
SU

(
3
)

W

⊗
U

(
1
)

X

. A “fermion-Higgs mismatching” symmetry breaking pattern is proposed for more realistic model building. Within such symmetry breaking pattern, only one Higgs doublet develops vacuum expectation value for the spontaneous electroweak symmetry breaking, and gives tree-level top quark mass. A natural VEV splittings in the 331 breaking Higgs fields gives tree-level masses to both bottom quark and tau lepton. The $$125\,\textrm{GeV}$$

125

GeV

SM-like Higgs boson discovered at the LHC can have Yukawa couplings to bottom quark and tau lepton as in the SM prediction, and this suggests the 331 symmetry breaking scale to be $$\sim {{{\mathcal {O}}}}(10)\,\textrm{TeV}$$

∼
O
(
10
)

TeV

.
f(Q, T) gravity, its covariant formulation, energy conservation and phase-space analysis
Authors: Loo Tee-How , Solanki Raja , De Avik , Sahoo P. K.
Published: March 2023

In the present article we analyze the matter-geometry coupled f(Q, T) theory of gravity. We offer the fully covariant formulation of the theory, with which we construct the correct energy balance equation and employ it to conduct a dynamical system analysis in a spatially flat Friedmann–Lemaître–Robertson–Walker spacetime. We consider three different functional forms of the f(Q, T) function, specifically, $$f(Q,T)=\alpha Q+ \beta T$$

f
(
Q
,
T
)
=
α
Q
+
β
T

, $$f(Q,T)=\alpha Q+ \beta T^2$$

f

(
Q
,
T
)

=
α
Q
+
β

T
2

, and $$f(Q,T)=Q+ \alpha Q^2+ \beta T$$

f

(
Q
,
T
)

=
Q
+
α

Q
2

+
β
T

. We attempt to investigate the physical capabilities of these models to describe various cosmological epochs. We calculate Friedmann-like equations in each case and introduce some phase space variables to simplify the equations in more concise forms. We observe that the linear model $$f(Q,T)=\alpha Q+ \beta T$$

f
(
Q
,
T
)
=
α
Q
+
β
T

with $$\beta =0$$

β
=
0

is completely equivalent to the GR case without cosmological constant $$\Lambda $$
Λ
. Further, we find that the model $$f(Q,T)=\alpha Q+ \beta T^2$$

f

(
Q
,
T
)

=
α
Q
+
β

T
2

with $$\beta \ne 0$$

β
≠
0

successfully depicts the observed transition from decelerated phase to an accelerated phase of the universe. Lastly, we find that the model $$f(Q,T)= Q+ \alpha Q^2+ \beta T$$

f

(
Q
,
T
)

=
Q
+
α

Q
2

+
β
T

with $$\alpha \ne 0$$

α
≠
0

represents an accelerated de-Sitter epoch for the constraints $$\beta < -1$$

β
<
-
1

or $$ \beta \ge 0$$

β
≥
0

.
Spherically symmetric distributions with an invariant and vanishing complexity factor by means of the extended geometric deformation
Authors: León P. , Las Heras C.
Published: March 2023

In this work, we will analyze the complexity factor, proposed by L. Herrera, of spherically symmetric static distribution through the gravitational decoupling method. Specifically, we will consider both spatial and temporal deformations of the metric function, and we will impose conditions over the complexity factor to close the system of equations. In particular, we found that the regularity at the center of both the seed and final solutions led to important restrictions on the deformation of the spatial metric components. These are particularly restrictive for the MGD method. In this case, we show that if the seed solution is regular at $$r=0,$$

r
=
0
,

the final solution with invariant complexity factor will be singular at this point unless $$f=0.$$

f
=
0
.

We also show that solutions with the same temporal components will, in general, lead to the same solutions with vanishing complexity factor in the MGD approach. Finally, we will construct realistic models using different seed solutions such as Tolman IV and FS (Finch–Skeas).
THE EFFECT OF CORPORATE FRUGALITY ON CRISIS PREPAREDNESS: THE MEDIATING ROLE OF ENTREPRENEURIAL ORIENTATION
Authors: AL ISSA HUSSEIN-ELHAKIM , THAI MAI THI THANH , OMAR MOHAMMED MISPAH SAID , FRNANA FAROUK MAHMUD
Published: March 2023

This study explores relationships between Corporate Frugality (CF), Entrepreneurial Orientation (EO) and Crisis Preparedness (CP). CP was proposed as the surrogate measure for firm performance during actual crises. EO is also examined as a potential mediator in the CF-CP association. The hypotheses were tested using partial least squares structural equation modeling with data collected from randomly selected small businesses operating in the Tripolitania region of northwestern Libya during the current economic instability caused by civil unrest. Further, COVID-19 pandemic cases had significantly risen among the population at the time of the study. The findings show that CF can be instrumental in responding to market crisis requirements, while innovativeness only results in better CP and partially mediates the CF-CP association. These findings validate the CF construct, but entrepreneurs must cautiously proceed when exercising EO in response to crises. Furthermore, the study casts new light on how the association between EO dimensions and performance can differ across contexts. Building on the resource-based view and pecking order theory and integrating them with contingency theory, this study is the first to explore the effect of EO and its dimensions as the mediator between CF and CP.
Human Parsing with Joint Learning for Dynamic mmWave Radar Point Cloud
Authors: Wang Shuai , Cao Dongjiang , Liu Ruofeng , Jiang Wenchao , Yao Tianshun , Lu Chris Xiaoxuan
Published: March 2023

Human sensing and understanding is a key requirement for many intelligent systems, such as smart monitoring, human-computer interaction, and activity analysis, etc. In this paper, we present mmParse, the first human parsing design for dynamic point cloud from commercial millimeter-wave radar devices. mmParse proposes an end-to-end neural network design that addresses the inherent challenges in parsing mmWave point cloud (e.g., sparsity and specular reflection). First, we design a novel multi-task learning approach, in which an auxiliary task can guide the network to understand human structural features. Secondly, we introduce a multi-task feature fusion method that incorporates both intra-task and inter-task attention to aggregate spatio-temporal features of the subject from a global view. Through extensive experiments in both indoor and outdoor environments, we demonstrate that our proposed system is able to achieve ~ 92% accuracy and ~ 84% IoU accuracy. We also show that the predicted semantic labels can increase the performance of two downstream tasks (pose estimation and action recognition) by ~ 18% and ~ 6% respectively.
Using Wearable Sensors to Measure Interpersonal Synchrony in Actors and Audience Members During a Live Theatre Performance
Authors: Sun Yanke , Greaves Dwaynica A. , Orgs Guido , de C. Hamilton Antonia F. , Day Sally , Ward Jamie A.
Published: March 2023

Studying social interaction in real-world settings is of increasing importance to social cognitive researchers. Theatre provides an ideal opportunity to study rich face-to-face interactions in a controlled, yet natural setting. Here we collaborated with Flute Theatre to investigate interpersonal synchrony between actors-actors, actors-audience and audience-audience within a live theatrical setting. Our 28 participants consisted of 6 actors and 22 audience members, with 5 of these audience members being audience participants in the show. The performance was a compilation of acting, popular science talks and demonstrations, and an audience participation period. Interpersonal synchrony was measured using inertial measurement unit (IMU) wearable accelerometers worn on the heads of participants, whilst audio-visual data recorded everything that occurred on the stage. Participants also completed post-show self-report questionnaires on their engagement with the overall scientists and actors performance. Cross Wavelet Transform (XWT) and Wavelet Coherence Transform (WCT) analysis were conducted to extract synchrony at different frequencies, pairing with audio-visual data. Findings revealed that XWT and WCT analysis are useful methods in extracting the multiple types of synchronous activity that occurs when people perform or watch a live performance together. We also found that audience members with higher ratings on questionnaire items such as the strength of their emotional response to the performance, or how empowered they felt by the performance, showed a high degree of interpersonal synchrony with actors during the acting segments of performance. We further found that audience members rated the scientists performance higher than the actors performance on questions related to their emotional response to the performance as well as, how uplifted, empowered, and connected to social issues they felt. This shows the types of potent connections audience members can have with live performances. Additionally, our findings highlight the importance of the performance context for audience engagement, in our case a theatre performance as part of public engagement with science rather than a stand-alone theatre performance. In sum we conclude that interdisciplinary real-world paradigms are an important and understudied route to understanding in-person social interactions.
VoiceListener
Authors: Wang Lei , Chen Meng , Lu Li , Ba Zhongjie , Lin Feng , Ren Kui
Published: March 2023

Recently, voice leakage gradually raises more significant concerns of users, due to its underlying sensitive and private information when providing intelligent services. Existing studies demonstrate the feasibility of applying learning-based solutions on built-in sensor measurements to recover voices. However, due to the privacy concerns, large-scale voices-sensor measurements samples for model training are not publicly available, leading to significant efforts in data collection for such an attack. In this paper, we propose a training-free and universal eavesdropping attack on built-in speakers, VoiceListener, which releases the data collection efforts and is able to adapt to various voices, platforms, and domains. In particular, VoiceListener develops an aliasing-corrected super resolution mechanism, including an aliasing-based pitch estimation and an aliasing-corrected voice recovering, to convert the undersampled narrow-band sensor measurements to wide-band voices. Extensive experiments demonstrate that our proposed VoiceListener could accurately recover the voices from undersampled sensor measurements and is robust to different voices, platforms and domains, realizing the universal eavesdropping attack.
ForceSticker
Authors: Gupta Agrim , Park Daegue , Bashar Shayaun , Girerd Cedric , Bhat Nagarjun , Mundhra Siddhi , Morimoto Tania K. , Bharadia Dinesh
Published: March 2023

Any two objects in contact with each other exert a force that could be simply due to gravity or mechanical contact, such as any ubiquitous object exerting weight on a platform or the contact between two bones at our knee joints. The most ideal way of capturing these contact forces is to have a flexible force sensor which can conform well to the contact surface. Further, the sensor should be thin enough to not affect the contact physics between the two objects. In this paper, we showcase the design of such thin, flexible sticker-like force sensors dubbed as 'ForceStickers', ushering into a new era of miniaturized force sensors. ForceSticker achieves this miniaturization by creating new class of capacitive force sensors which avoid both batteries, as well as wires. The wireless and batteryless readout is enabled via hybrid analog-digital backscatter, by piggybacking analog sensor data onto a digitally identified RFID link. Hence, ForceSticker finds natural applications in space and battery-constraint in-vivo usecases, like force-sensor backed orthopaedic implants, surgical robots. Further, ForceSticker finds applications in ubiquiti-constraint scenarios. For example, these force-stickers enable cheap, digitally readable barcodes that can provide weight information, with possible usecases in warehouse integrity checks. To meet these varied application scenarios, we showcase the general framework behind design of ForceSticker. With ForceSticker framework, we design 4mm*2mm sensor prototypes, with two different polymer layers of ecoflex and neoprene rubber, having force ranges of 0-6N and 0-40N respectively, with readout errors of 0.25, 1.6 N error each (<5% of max. force). Further, we stress test ForceSticker by >10,000 force applications without significant error degradation. We also showcase two case-studies onto the possible applications of ForceSticker: sensing forces from a toy knee-joint model and integrity checks of warehouse packaging.
AI-to-Human Actuation
Authors: Cho Sungjae , Kim Yoonsu , Jang Jaewoong , Hwang Inseok
Published: March 2023

Imagine a near-future smart home. Home-embedded visual AI sensors continuously monitor the resident, inferring her activities and internal states that enable higher-level services. Here, as home-embedded sensors passively monitor a free person, good inferences happen randomly. The inferences' confidence highly depends on how congruent her momentary conditions are to the conditions favored by the AI models, e.g., front-facing or unobstructed. We envision new strategies of AI-to-Human Actuation (AHA) that empower the sensory AIs with proactive actuation so that they induce the person's conditions to be more favorable to the AIs. In this light, we explore the initial feasibility and efficacy of AHA in the context of home-embedded visual AIs. We build a taxonomy of actuations that could be issued to home residents to benefit visual AIs. We deploy AHA in an actual home rich in sensors and interactive devices. With 20 participants, we comprehensively study their experiences with proactive actuation blended with their usual home routines. We also demonstrate the substantially improved inferences of the actuation-empowered AIs over the passive sensing baseline. This paper sets forth an initial step towards interweaving human-targeted AIs and proactive actuation to yield more chances for high-confidence inferences without sophisticating the model, in order to improve robustness against unfavorable conditions.
From 2D to 3D
Authors: Yi Xin , Liang Chen , Chen Haozhan , Song Jiuxu , Yu Chun , Li Hewu , Shi Yuanchun
Published: March 2023

Mid-air text entry on virtual keyboards suffers from the lack of tactile feedback, which brings challenges to both tap detection and input prediction. In this paper, we explored the feasibility of single-finger typing on virtual QWERTY keyboards in mid-air. We first conducted a study to examine users' 3D typing behavior on different sizes of virtual keyboards. Results showed that the participants perceived the vertical projection of the lowest point on the keyboard during a tap as the target location and inferring taps based on the intersection between the finger and the keyboard was not applicable. Aiming at this challenge, we derived a novel input prediction algorithm that took the uncertainty in tap detection into a calculation as probability, and performed probabilistic decoding that could tolerate false detection. We analyzed the performance of the algorithm through a full-factorial simulation. Results showed that the SVM-based probabilistic touch detection together with a 2D elastic probabilistic decoding algorithm (elasticity = 2) could achieve the optimal top-5 accuracy of 94.2%. In the evaluation user study, the participants reached a single-finger typing speed of 26.1 WPM with 3.2% uncorrected word-level error rate, which was significantly better than both tap-based and gesture-based baseline techniques. Also, the proposed technique received the highest preference score from the users, proving its usability in real text entry tasks.
mSilent
Authors: Zeng Shang , Wan Haoran , Shi Shuyu , Wang Wei
Published: March 2023

Silent speech recognition (SSR) allows users to speak to the device without making a sound, avoiding being overheard or disturbing others. Compared to the video-based approach, wireless signal-based SSR can work when the user is wearing a mask and has fewer privacy concerns. However, previous wireless-based systems are still far from well-studied, e.g. they are only evaluated in corpus with highly limited size, making them only feasible for interaction with dozens of deterministic commands. In this paper, we present mSilent, a millimeter-wave (mmWave) based SSR system that can work in the general corpus containing thousands of daily conversation sentences. With the strong recognition capability, mSilent not only supports the more complex interaction with assistants, but also enables more general applications in daily life such as communication and input. To extract fine-grained articulatory features, we build a signal processing pipeline that uses a clustering-selection algorithm to separate articulatory gestures and generates a multi-scale detrended spectrogram (MSDS). To handle the complexity of the general corpus, we design an end-to-end deep neural network that consists of a multi-branch convolutional front-end and a Transformer-based sequence-to-sequence back-end. We collect a general corpus dataset of 1,000 daily conversation sentences that contains 21K samples of bi-modality data (mmWave and video). Our evaluation shows that mSilent achieves a 9.5% average word error rate (WER) at a distance of 1.5m, which is comparable to the performance of the state-of-the-art video-based approach. We also explore deploying mSilent in two typical scenarios of text entry and in-car assistant, and the less than 6% average WER demonstrates the potential of mSilent in general daily applications.
Individualized Tracking of Neurocognitive-State-Dependent Eye-Movement Features Using Mobile Devices
Authors: Lai Hsin-Yu , Sodini Charles G. , Sze Vivienne , Heldt Thomas
Published: March 2023

With current clinical techniques, it is difficult to assess a patient's neurodegenerative disease (e.g., Alzheimer's) state accurately and frequently. The most widely used tests are qualitative or only performed intermittently, motivating the need for quantitative, accurate, and unobtrusive metrics to track disease progression. Clinical studies have shown that saccade latency (an eye movement measure of reaction time) and error rate (the proportion of eye movements in the wrong direction) may be significantly affected by neurocognitive diseases. Nevertheless, how these features change over time as a disease progresses is underdeveloped due to the constrained recording setup.

In this work, our goal is to first understand how these features change over time in healthy individuals. To do so, we used a mobile app to frequently and accurately measure these features outside of the clinical environment from 80 healthy participants. We analyzed their longitudinal characteristics and designed an individualized longitudinal model using a Gaussian process. With a system that can measure eye-movement features on a much finer timescale in a broader population, we acquired a better understanding of eye-movement features from healthy individuals and provided research directions in understanding whether eye-movement features can be used to track neurocognitive states.
Auto-Gait
Authors: Rahman Wasifur , Hasan Masum , Islam Md Saiful , Olubajo Titilayo , Thaker Jeet , Abdelkader Abdel-Rahman , Yang Phillip , Paulson Henry , Oz Gulin , Durr Alexandra , Klockgether Thomas , Ashizawa Tetsuo , Investigators Readisca , Hoque Ehsan
Published: March 2023

Many patients with neurological disorders, such as Ataxia, do not have easy access to neurologists, -especially those living in remote localities and developing/underdeveloped countries. Ataxia is a degenerative disease of the nervous system that surfaces as difficulty with motor control, such as walking imbalance. Previous studies have attempted automatic diagnosis of Ataxia with the help of wearable biomarkers, Kinect, and other sensors. These sensors, while accurate, do not scale efficiently well to naturalistic deployment settings. In this study, we propose a method for identifying ataxic symptoms by analyzing videos of participants walking down a hallway, captured with a standard monocular camera. In a collaboration with 11 medical sites located in 8 different states across the United States, we collected a dataset of 155 videos along with their severity rating from 89 participants (24 controls and 65 diagnosed with or are pre-manifest spinocerebellar ataxias). The participants performed the gait task of the Scale for the Assessment and Rating of Ataxia (SARA). We develop a computer vision pipeline to detect, track, and separate the participants from their surroundings and construct several features from their body pose coordinates to capture gait characteristics such as step width, step length, swing, stability, speed, etc. Our system is able to identify and track a patient in complex scenarios. For example, if there are multiple people present in the video or an interruption from a passerby. Our Ataxia risk-prediction model achieves 83.06% accuracy and an 80.23% F1 score. Similarly, our Ataxia severity-assessment model achieves a mean absolute error (MAE) score of 0.6225 and a Pearson's correlation coefficient score of 0.7268. Our model competitively performed when evaluated on data from medical sites not used during training. Through feature importance analysis, we found that our models associate wider steps, decreased walking speed, and increased instability with greater Ataxia severity, which is consistent with previously established clinical knowledge. Furthermore, we are releasing the models and the body-pose coordinate dataset to the research community - the largest dataset on ataxic gait (to our knowledge). Our models could contribute to improving health access by enabling remote Ataxia assessment in non-clinical settings without requiring any sensors or special cameras. Our dataset will help the computer science community to analyze different characteristics of Ataxia and to develop better algorithms for diagnosing other movement disorders.
BabyNutri
Authors: Hu Haiyan , Huang Qianyi , Zhang Qian
Published: March 2023

The physical and physiological development of infants and toddlers requires the proper amount of macronutrient intake, making it an essential problem to estimate the macronutrient in baby food. Nevertheless, existing solutions are either too expensive or poor performing, preventing the widespread use of automatic baby nutrient intake logging. To narrow this gap, this paper proposes a cost-effective and portable baby food macronutrient estimation system, BabyNutri. BabyNutri exploits a novel spectral reconstruction algorithm to reconstruct high-dimensional informative spectra from low-dimensional spectra, which are available from low-cost spectrometers. We propose a denoising autoencoder for the reconstruction process, by which BabyNutri can reconstruct a 160-dimensional spectrum from a 5-dimensional spectrum. Since the high-dimensional spectrum is rich in light absorption features of macronutrients, it can achieve more accurate macronutrient estimation. In addition, considering that baby food contains complex ingredients, we also design a CNN nutrition estimation model with good generalization performance over various types of baby food. Our extensive experiments over 88 types of baby food show that the spectral reconstruction error of BabyNutri is only 5.91%, reducing 33% than the state-of-the-art baseline with the same time complexity. In addition, the nutrient estimation performance of BabyNutri not only obviously outperforms state-of-the-art and cost-effective solutions but also is highly correlated with the professional spectrometer, with the correlation coefficients of 0.81, 0.88, 0.82 for protein, fat, and carbohydrate, respectively. However the price of our system is only one percent of the commercial solution. We also validate that BabyNutri is robust regarding various factors, e.g., ambient light, food volume, and even unseen baby food samples.
RF-CM
Authors: Wang Xuan , Liu Tong , Feng Chao , Fang Dingyi , Chen Xiaojiang
Published: March 2023

Radio-Frequency (RF) based human activity recognition (HAR) enables many attractive applications such as smart home, health monitoring, and virtual reality (VR). Among multiple RF sensors, mmWave radar is emerging as a new trend due to its fine-grained sensing capability. However, laborious data collection and labeling processes are required when employing a radar-based sensing system in a new environment. To this end, we propose RF-CM, a general cross-modal human activity recognition framework. The key enabler is to leverage the knowledge learned from a massive WiFi dataset to build a radar-based HAR system with limited radar samples. It can significantly reduce the overhead of training data collection. In addition, RF-CM can work well regardless of the deployment setups of WiFi and mmWave radar, such as performing environments, users' characteristics, and device deployment. RF-CM achieves this by first capturing the activity-related variation patterns through data processing schemes. It then employs a convolution neural network-based feature extraction module to extract the high-dimensional features to be fed into the activity recognition module. Finally, RF-CM takes the generalization knowledge from WiFi networks as guide labels to supervise the training of the radar model, thus enabling a few-shot radar-based HAR system. We evaluate RF-CM by applying it to two HAR applications, fine-grained American sign language recognition (WiFi-cross-radar) and coarse-grained gesture recognition (WiFi-cross-RFID). The accuracy improvement of over 10% in both applications demonstrates the effectiveness of RF-CM. This cross-modal ability allows RF-CM to support more cross-modal applications.
MoCaPose
Authors: Zhou Bo , Geissler Daniel , Faulhaber Marc , Gleiss Clara Elisabeth , Zahn Esther Friederike , Ray Lala Shakti Swarup , Gamarra David , Rey Vitor Fortes , Suh Sungho , Bian Sizhen , Joost Gesche , Lukowicz Paul
Published: March 2023

We present MoCaPose, a novel wearable motion capturing (MoCap) approach to continuously track the wearer's upper body's dynamic poses through multi-channel capacitive sensing integrated in fashionable, loose-fitting jackets. Unlike conventional wearable IMU MoCap based on inverse dynamics, MoCaPose decouples the sensor position from the pose system. MoCaPose uses a deep regressor to continuously predict the 3D upper body joints coordinates from 16-channel textile capacitive sensors, unbound by specific applications. The concept is implemented through two prototyping iterations to first solve the technical challenges, then establish the textile integration through fashion-technology co-design towards a design-centric smart garment. A 38-hour dataset of synchronized video and capacitive data from 21 participants was recorded for validation. The motion tracking result was validated on multiple levels from statistics (R2 ~ 0.91) and motion tracking metrics (MP JPE ~ 86mm) to the usability in pose and motion recognition (0.9 F1 for 10-class classification with unsupervised class discovery). The design guidelines impose few technical constraints, allowing the wearable system to be design-centric and usecase-specific. Overall, MoCaPose demonstrates that textile-based capacitive sensing with its unique advantages, can be a promising alternative for wearable motion tracking and other relevant wearable motion recognition applications.
IoTBeholder
Authors: Zou Qingsong , Li Qing , Li Ruoyu , Huang Yucheng , Tyson Gareth , Xiao Jingyu , Jiang Yong
Published: March 2023

With the deployment of a growing number of smart home IoT devices, privacy leakage has become a growing concern. Prior work on privacy-invasive device localization, classification, and activity identification have proven the existence of various privacy leakage risks in smart home environments. However, they only demonstrate limited threats in real world due to many impractical assumptions, such as having privileged access to the user's home network. In this paper, we identify a new end-to-end attack surface using IoTBeholder, a system that performs device localization, classification, and user activity identification. IoTBeholder can be easily run and replicated on commercial off-the-shelf (COTS) devices such as mobile phones or personal computers, enabling attackers to infer user's habitual behaviors from smart home Wi-Fi traffic alone. We set up a testbed with 23 IoT devices for evaluation in the real world. The result shows that IoTBeholder has good device classification and device activity identification performance. In addition, IoTBeholder can infer the users' habitual behaviors and automation rules with high accuracy and interpretability. It can even accurately predict the users' future actions, highlighting a significant threat to user privacy that IoT vendors and users should highly concern.
A User-Centric Evaluation of Smart Home Resolution Approaches for Conflicts Between Routines
Authors: Zaidi Ali , Yang Rui , Koshy Vinay , Cobb Camille , Gupta Indranil , Karahalios Karrie
Published: March 2023

With the increasing adoption of smart home devices, users rely on device automation to control their homes. This automation commonly comes in the form of smart home routines, an abstraction available via major vendors. Yet, questions remain about how a system should best handle conflicts in which different routines access the same devices simultaneously. In particular---among the myriad ways a smart home system could handle conflicts, which of them are currently utilized by existing systems, and which ones result in the highest user satisfaction? We investigate the first question via a survey of existing literature and find a set of conditions, modifications, and system strategies related to handling conflicts. We answer the second question via a scenario-based Mechanical-Turk survey of users interested in owning smart home devices and current smart home device owners (N=197). We find that: (i) there is no context-agnostic strategy that always results in high user satisfaction, and (ii) users' personal values frequently form the basis for shaping their expectations of how routines should execute.
The SARS-CoV-2 E protein induces Toll-like receptor 2-mediated neonatal lung injury in a model of COVID-19 viremia that is rescued by the glucocorticoid ciclesonide
Authors: Menden Heather L. , Mabry Sherry M. , Venkatraman Aparna , Xia Sheng , DeFranco Donald B. , Yu Wei , Sampath Venkatesh
Published: March 2023

We reveal that the envelope protein of SARS-CoV-2 mediates acute lung injury (ALI) and alveolar remodeling through Toll-like receptor activation, which is rescued by the glucocorticoid, ciclesonide.
Numerical Simulation on Enhanced Heat Transfer and Flow Characteristics in Direct-Contact Heat Exchanger: A Novel Kenics Static Mixer
Authors: Zhao Shuang , Zhang Xia , Wang Hua , Zhang Hao , Huang Junwei
Published: March 2023

In this paper, a novel Kenics static mixer applied in a direct-contact heat exchanger (DCHE) was proposed in order to enhance the heat transfer efficiency. The computational fluid dynamics (CFD) simulation method was adopted to investigate the effect of the continuous phase and dispersed phase on direct-contact heat transfer (DCHT) in the Kenics static mixer. The perforation index (PI) was introduced to depict the performance of the Kenics static mixer, and the effect of different numbers of openings at three initial heat transfer temperature differences (at the inlet of the continuous and dispersed phases) was studied. The simulation results showed that under the same working conditions, a larger initial temperature difference would result in greater differences in the fluid uniformity index (UI), turbulence intensity, and time evolution of a gaseous working substance. The increase of hole numbers and decrease of hole diameters can optimize the DCHT. Under three initial temperature differences, the heat transfer efficiency for the 6-hole and 9-hole Kenics DCHEs was about 20% higher than the Kenics DCHE without holes.
Risk Assessment of Dyslipidemias, Hyperglycemia, Hyperuricemia, and Hypertension Utilizing Self-Reported Body Silhouettes
Authors: Blachman-Braun Ruben , Talavera Juan O. , Pérez-Rodríguez Marcela , Roy-García Ivonne , Rivas-Ruiz Rodolfo , Huitrón-Bravo Gerardo , Salmerón Jorge
Published: March 2023

Objective. Self-reported body silhouette is an anthropometric instrument that has been utilized as a screening tool for underweight, overweight, obesity, and other abnormal anthropometric variables. Herein, we analyzed the risk associated with the self-reported body silhouette in the scope of dyslipidemias, hyperglycemia, hyperuricemia, and hypertension. Methods. Adult participants of the Health Workers Cohort Study enrolled between March 2004 and April 2006 were included. Then, risk analysis was performed considering dyslipidemias as serum triglycerides, high total cholesterol, high LDL-C, low HDL-C, hyperglycemia, hyperuricemia, and hypertension. Results. A total of 2,297 males and 5,003 females were analyzed. The median ages of the studied population was 39 (30–49) and 41 (31–50) years for males and females, respectively. Overall, there is a stepwise increase in the risk of presenting dyslipidemias, hyperglycemia, hyperuricemia, and hypertension as the self-reported body silhouette number increases, this tendency was observed in both males and females. Conclusion. Self-reported body silhouette is a useful risk assessment tool for dyslipidemias, hyperglycemia, hyperuricemia, and hypertension in Mexican adults. Applications of questioners containing this silhouette might be considered a valuable public health instrument due to their low cost, relative simplicity, and absence of specialized equipment, training, or respondent knowledge.
Multipoint Deformation Safety Monitoring Model for Concrete Arch Dams Based on Bayesian Model Selection and Averaging
Authors: Cheng Lin , Chen Jiamin , Ma Chunhui , Yang Jie , Xu Xiaoyan , Yuan Shuai
Published: March 2023

The deformation properties of concrete arch dams are affected by the synergistic effects of multiple factors, featuring strong, multidimensional spatialtemporal evolution and distribution characteristics. This paper proposes a zoned safety monitoring model for arch dam deformation based on spatialtemporal similarity and model optimization to evaluate the deformation safety state of arch dam structures. First, zoned clustering of the deformation monitoring points at different locations of an arch dam was performed using a panel data multi-index clustering method to determine the deformation laws at different positions of the dam. Next, multipoint comprehensive displacements of the deformation properties of each zone were extracted using principal component analysis to extract the uniform deformation law of the monitoring point in each zone. Finally, we adopted Bayesian model selection (BMS) and Bayesian model averaging (BMA) for the regression model set, considering the uncertainty of the model. The engineering case study showed that BMA yielded robust and effective prediction results for the deformation of the arch dam. The analysis of the zoned deformation mechanism indicated that the deformation of the arch dam followed the general rule. The temperature component of the arch dam was mainly reflected in the middle with a hysteresis effect, and the time-dependent component was evident in both sides of the dam shoulder. The arch dam deformation safety monitoring model proposed in this study has strong robustness and interpretability, which can provide valuable technical support for analyzing the evolution of arch dam deformation properties.
Experimental Study of Awash Soil under Static and Cyclic Shear Loading
Authors: Arficho Tigistu Abu , Ashango Argaw Asha
Published: March 2023

The dynamic soil properties (shear modulus and damping ratio) are of great importance for the analysis and design of geotechnical structures subjected to dynamic loads such as earthquake. Cyclic simple shear tests were conducted to study the variation of shear modulus and damping ratio with a different number of factors for strain amplitudes of 0.01%, 0.1%, 1%, 2.5%, and 5% and for a frequency of 1 Hz at an axial stress of 150 kPa, 275 kPa, and 400 kPa. The result shows that the damping ratio decreases with an increase in confining pressure at different cyclic shear strains. The shear modulus increases with an increase in the void ratio at different cyclic shear strains. The damping ratio increases with a decrease in soil plasticity. The obtained values of shear modules were in the ranges of 0.292 MPa to 15.998 MPa and the damping ratio values from 0.146% to 30.851%. In concluding the major influencing factors that affect the dynamic properties of soils are confining pressure, void ratio, shear strain amplitude, and soil plasticity.
RNA Sequencing Reveals the Differentially Expressed circRNAs between Stable and Unstable Carotid Atherosclerotic Plaques
Authors: Lin Xueguang , Deng Ying , Ye Lujuan , Chen Bo , Tong Jindong , Shi Weijun , Wang Bo , Yu Bo , Tang Jingdong
Published: March 2023

Objective. This study aimed to identify circular RNA profiles (circRNAs) via high-throughput RNA sequencing and distinguish the differentially expressed (DE) circRNAs between stable and unstable plaques. Methods. RNA sequencing was performed on unstable and stable carotid plaque samples obtained from patients with carotid artery stenosis. DE circRNAs were screened, and six DE circRNAs were verified using quantitative real-time PCR (qRT-PCR). Functional evaluation of the DE circRNAs was conducted via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Results. We screened 344 DE circRNAs in unstable plaques, consisting of 342 upregulated and 2 downregulated circRNAs. GO analysis showed that the host genes of the upregulated circRNAs were related to ER to Golgi transport vesicle membrane, endocytic vesicle membrane, and Ran GTPase binding. KEGG analysis revealed that the host genes of the upregulated circRNAs were primarily associated with protein processing in endoplasmic reticulum, lysine degradation, homologous recombination, epithelial cell signaling in Helicobacter pylori infection, and yersinia infection. The results of qRT-PCR verified three upregulated DE circRNAs and two downregulated DE circRNAs in unstable plaques. Conclusion. Hsa-circ-0001523, hsa-circ-0008950, hsa-circ-0000571, hsa-circ-0001946, and hsa-circ-0000745 may be involved in regulating the stability of atherosclerotic plaques and serves as a therapeutic target for unstable plaques.