bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wearable magnetic induction-based approach toward 3D motion tracking
Authors: Golestani Negar , Moghaddam Mahta 
Published: September 2021

AbstractActivity recognition using wearable sensors has gained popularity due to its wide range of applications, including healthcare, rehabilitation, sports, and senior monitoring. Tracking the body movement in 3D space facilitates behavior recognition in different scenarios. Wearable systems have limited battery capacity, and many critical challenges have to be addressed to gain a trade-off among power consumption, computational complexity, minimizing the effects of environmental interference, and achieving higher tracking accuracy. This work presents a motion tracking system based on magnetic induction (MI) to tackle the challenges and limitations inherent in designing a wireless monitoring system. We integrated a realistic prototype of an MI sensor with machine learning techniques and investigated one-sensor and two-sensor configuration setups for motion reconstruction. This approach is successfully evaluated using measured and synthesized datasets generated by the analytical model of the MI system. The system has an average distance root-mean-squared error (RMSE) error of 3 cm compared to the ground-truth real-world measured data with Kinect.
Valence band structure and charge distribution in the layered lanthanide-doped CuCr0.99Ln0.01S2 (Ln = La, Ce) solid solutions
Authors: Korotaev E. V. , Syrokvashin M. M. , Filatova I. Yu , Kalinkin A. V. , Sotnikov A. V. 
Published: September 2021

AbstractThe comprehensive study of the electronic density distribution of CuCr0.99Ln0.01S2 (Ln = La, Ce) solid solutions was carried out using both X-ray photoelectron and emission spectroscopy. It was found that cationic substitution of chromium with lanthanum or cerium atoms does not significantly affect the atomic charges of the matrix elements (Cu, Cr, S) in the lanthanide-doped solid solutions. The copper atoms in the composition of CuCrS2-matrix and the lanthanide-doped solid solutions were found to be in the monovalent state. The chromium and lanthanide atoms were found to be in the trivalent state. This fact indicates the isovalent cationic substitution character. The sulfur atoms were found to be in the divalent state. The near-surface layers contain the additional oxidation forms of sulfur (S0, S4+, S6+) and copper (Cu2+) atoms. The detailed analysis of the valence band structure using DFT calculations has shown that partial DOS distribution character of the matrix elements is preserved after the cationic substitution. The experimental valence band spectra structure of CuCrS2-matrix and CuCr0.99Ln0.01S2 is determined by the occupied copper d-states contribution. The contribution of the lanthanide states in the valence band structure is lower in comparison with those for the matrix elements. The major contribution of the lanthanide states was found to be mainly localized near the conduction band bottom.
Real-world gait speed estimation, frailty and handgrip strength: a cohort-based study
Authors: Soltani Abolfazl , Abolhassani Nazanin , Marques-Vidal Pedro , Aminian Kamiar , Vollenweider Peter , Paraschiv-Ionescu Anisoara 
Published: September 2021

AbstractGait speed is a reliable outcome measure across multiple diagnoses, recognized as the 6th vital sign. The focus of the present study was on assessment of gait speed in long-term real-life settings with the aim to: (1) demonstrate feasibility in large cohort studies, using data recorded with a wrist-worn accelerometer device; (2) investigate whether the walking speed assessed in the real-world is consistent with expected trends, and associated with clinical scores such as frailty/handgrip strength. This cross-sectional study included n = 2809 participants (1508 women, 1301 men, [45–75] years old), monitored with a wrist-worn device for 13 consecutive days. Validated algorithms were used to detect the gait bouts and estimate speed. A set of metrics were derived from the statistical distribution of speed of gait bouts categorized by duration (short, medium, long). The estimated usual gait speed (1–1.6 m/s) appears consistent with normative values and expected trends with age, gender, BMI and physical activity levels. Speed metrics significantly improved detection of frailty: AUC increase from 0.763 (no speed metrics) to 0.798, 0.800 and 0.793 for the 95th percentile of individual’s gait speed for bout durations < 30, 30–120 and > 120 s, respectively (all p < 0.001). Similarly, speed metrics also improved the prediction of handgrip strength: AUC increase from 0.669 (no speed metrics) to 0.696, 0.696 and 0.691 for the 95th percentile of individual’s gait speed for bout durations < 30, 30–120 and > 120 s, respectively (all p < 0.001). Forward stepwise regression showed that the 95th percentile speed of gait bouts with medium duration (30–120 s) to be the best predictor for both conditions. The study provides evidence that real-world gait speed can be estimated using a wrist-worn wearable system, and can be used as reliable indicator of age-related functional decline.
Factors associated with the difference between the incidence and case-fatality ratio of coronavirus disease 2019 by country
Authors: Kim Jeehyun , Hong Kwan , Yum Sujin , Gómez Gómez Raquel Elizabeth , Jang Jieun , Park Sun Hee , Choe Young June , Ryu Sukhyun , Park Dae Won , Lee Young Seok , Lee Heeyoung , Kim Dong Hyun , Kim Dong-Hyun , Chun Byung Chul 
Published: September 2021

AbstractCoronavirus disease (COVID-19) has been spreading all over the world; however, its incidence and case-fatality ratio differ greatly between countries and between continents. We investigated factors associated with international variation in COVID-19 incidence and case-fatality ratio (CFR) across 107 northern hemisphere countries, using publicly available COVID-19 outcome data as of 14 September 2020. We included country-specific geographic, demographic, socio-economic features, global health security index (GHSI), healthcare capacity, and major health behavior indexes in multivariate models to explain this variation. Multiple linear regression highlighted that incidence was associated with ethnic region (p < 0.05), global health security index 4 (GHSI4) (beta coefficient [β] 0.50, 95% Confidence Interval [CI] 0.14–0.87), population density (β 0.35, 95% CI 0.10–0.60), and water safety level (β 0.51, 95% CI 0.19–0.84). The CFR was associated with ethnic region (p < 0.05), GHSI4 (β 0.53, 95% CI 0.14–0.92), proportion of population over 65 (β 0.71, 95% CI 0.19–1.24), international tourism receipt level (β − 0.23, 95% CI − 0.43 to − 0.03), and the number of physicians (β − 0.37, 95% CI − 0.69 to − 0.06). Ethnic region was the most influential factor for both COVID-19 incidence (partial $${R}^{2}$$

R

2

= 0.545) and CFR (partial $${R}^{2}$$

R

2

= 0.372), even after adjusting for various confounding factors.
Predicting medication adherence using ensemble learning and deep learning models with large scale healthcare data
Authors: Gu Yingqi , Zalkikar Akshay , Liu Mingming , Kelly Lara , Hall Amy , Daly Kieran , Ward Tomas 
Published: September 2021

AbstractClinical studies from WHO have demonstrated that only 50–70% of patients adhere properly to prescribed drug therapy. Such adherence failure can impact therapeutic efficacy for the patients in question and compromises data quality around the population-level efficacy of the drug for the indications targeted. In this study, we applied various ensemble learning and deep learning models to predict medication adherence among patients. Our contribution to this endeavour involves targeting the problem of adherence prediction for a particularly challenging class of patients who self-administer injectable medication at home. Our prediction pipeline, based on event history, comprises a connected sharps bin which aims to help patients better manage their condition and improve outcomes. In other words, the efficiency of interventions can be significantly improved by prioritizing the patients who are most likely to be non-adherent. The collected data comprising a rich event feature set may be exploited for the purposes of predicting the status of the next adherence state for individual patients. This paper reports on how this concept can be realized through an investigation using a wide range of ensemble learning and deep learning models on a real-world dataset collected from such a system. The dataset investigated comprises 342,174 historic injection disposal records collected over the course of more than 5 years. A comprehensive comparison of different models is given in this paper. Moreover, we demonstrate that the selected best performer, long short-term memory (LSTM), generalizes well by deploying it in a true future testing dataset. The proposed end-to-end pipeline is capable of predicting patient failure in adhering to their therapeutic regimen with 77.35 % accuracy (Specificity: 78.28 %, Sensitivity: 76.42%, Precision: 77.87%,F1 score: 0.7714, ROC AUC: 0.8390).
Proteomic characterization of primary and metastatic prostate cancer reveals reduced proteinase activity in aggressive tumors
Authors: Li Qing Kay , Chen Jing , Hu Yingwei , Höti Naseruddin , Lih Tung-Shing Mamie , Thomas Stefani N. , Chen Li , Roy Sujayita , Meeker Alan , Shah Punit , Chen Lijun , Bova G. Steven , Zhang Bai , Zhang Hui 
Published: September 2021

AbstractProstate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. In order to improve patient outcomes, it is critical to clinically separate aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with aggressive PCa, it is still challenging to separate AG from NAG. To better understand the functional consequences of PCa progression and the unique features of the AG subtype, we studied the proteomic signatures of primary AG, NAG and metastatic PCa. 39 PCa and 10 benign prostate controls in a discovery cohort and 57 PCa in a validation cohort were analyzed using a data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using a validation cohort; and was also compared with a TCGA mRNA expression dataset and confirmed by immunohistochemistry (IHC) using PCa tissue microarray (TMA). 4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed reduced expressions of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates and the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using an independently-collected tumor cohort, correlated with a TCGA mRNA dataset, and confirmed by immunohistochemical stains of PCa tumor microarray (TMA). Our study is the first large-scale proteomics analysis of PCa tissue using a DIA SWATH-MS platform. It provides not only an interrogative proteomic signature of PCa subtypes, but also indicates the critical roles played by certain proteinases during tumor progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in PCa and for the development of a clinical assay to distinguish aggressive from indolent PCa.
Transcriptome analysis reveals the molecular mechanisms of response to an emergent yellow-flower disease in green Chinese prickly ash (Zanthoxylum schinifolium)
Authors: Xu Fan , Meng Qian , Suo Xiaodong , Xie Yonghong , Cheng Yueqing , Luo Ming 
Published: September 2021

AbstractChinese prickly ash (Zanthoxylum) is extensively used as spice and traditional medicine in eastern Asian countries. Recently, an emergent yellow-flower disease (YFD) break out in green Chinese prickly ash (Zanthoxylum schinifolium, Qinghuajiao in Chinese) at Chongqing municipality, and then leads to a sharp reduction in the yield of Qinghuajiao, and thus results in great economic losses for farmers. To address the molecular response for the emergent YFD of Qinghuajiao, we analyzed the transcriptome of 12 samples including the leaves and inflorescences of asymptomatic and symptomatic plants from three different towns at Chongqing by high-throughput RNA-Seq technique. A total of 126,550 genes and 229,643 transcripts were obtained, and 21,054 unigenes were expressed in all 12 samples. There were 56 and 164 different expressed genes (DEGs) for the AL_vs_SL (asymptomatic leaf vs symptomatic leaf) and AF_vs_SF (asymptomatic flower vs symptomatic flower) groups, respectively. The results of KEGG analysis showed that the “phenylpropanoid biosynthesis” pathway that related to plant–pathogen interaction were found in AL_vs_SL and AF_vs_SF groups, and the “Plant–pathogen interaction” found in AF_vs_SF group, implying that this Qinghuajiao YFD might cause by plant pathogen. Interestingly, we detected 33 common unigenes for the 2 groups, and almost these unigenes were up-regulated in the symptomatic plants. Moreover, most of which were homologs to virus RNA, the components of viruses, implying that this YFD was related to virus. Our results provided a primary molecular basis for the prevention and treatment of YFD of Qinghuajiao trees.
RETRACTED ARTICLE: Pharmacist-driven antimicrobial stewardship program in a long-term care facility by assessment of appropriateness
Authors: Cantudo-Cuenca María Rosa , Jimenez-Morales Alberto , Martínez-de la Plata Juan Enrique 
Published: September 2021

AbstractAntimicrobials are the most frequently prescribed drugs in long-term care facilities (LTCF). Antibiotic stewardship programs (ASP) are coordinated interventions promoting the responsible use of antibiotics to improve patient outcomes and reduce antibiotic resistant bacterias. The objectives are to evaluate the effectiveness of a pharmacist-led ASP in a LTCF, to characterise antibiotic therapy and assess the appropriateness of antibiotic prescriptions. A prospective quasi-experimental study to implement an ASP in a LTCF. Antibiotic prescriptions for suspected infections initiated in any setting for LTCF residents were included. We assessed appropriateness and prospective audits and feedback of each inappropriate antimicrobial prescription were carried out. Associations of variables with appropriate antibiotic prescribing were estimated using logistic regression. A total of 416 antibiotic prescriptions were included. The mean consumption of antibiotics was reduced from 63.2 defined daily doses per 1000 residents-days (DRD) in the preintervention period to 22.8 in the intervention period (− 63.8%), with a signifcant drop in fluoroquinolones (81.4%). Overall, 46.6% of antibiotic prescriptions were judged inappropriate, mainly because of a use not recommended in treatment guidelines (63.2%). Multivariable analysis showed that empirical therapy, some classes of antibiotics (cephalosporins, fluoroquinolones, fosfomycin calcium, macrolides) and prescription initiation in the emergency department were independent predictors of antimicrobial inappropriateness. Pharmacist-led ASP in a LTCF has being effective in reducing consumption of antibiotics by improving appropriateness of treatment decisions. However, ASP should include interventions in the emergency department because of the high inappropriate use in this setting.
Visibility matters during wayfinding in the vertical
Authors: Gath-Morad Michal , Thrash Tyler , Schicker Julia , Hölscher Christoph , Helbing Dirk , Aguilar Melgar Leonel Enrique 
Published: September 2021

AbstractVisibility is the degree to which different parts of the environment can be observed from a given vantage point. In the absence of previous familiarity or signage, the visibility of key elements in a multilevel environment (e.g., the entrance, exit, or the destination itself) becomes a primary input to make wayfinding decisions and avoid getting lost. Previous research has focused on memory-based wayfinding and mental representation of 3D space, but few studies have investigated the direct effects of visibility on wayfinding. Moreover, to our knowledge, there are no studies that have explicitly observed the interaction between visibility and wayfinding under uncertainty in a multilevel environment. To bridge this gap, we studied how the visibility of destinations, as well as the continuity of sight-lines along the vertical dimension, affects unaided and goal-directed wayfinding behavior in a multilevel desktop Virtual Reality (VR) study. We obtained results from a total of 69 participants. Each participant performed a total of 24 wayfinding trials in a multilevel environment. Results showcase a significant and nonlinear correlation between the visibility of destinations and wayfinding behavioral characteristics. Specifically, once the destination was in sight, regardless of whether it was highly or barely visible, participants made an instantaneous decision to switch floors and move up towards the destination. In contrast, if the destination was out-of-sight, participants performed ‘visual exploration’, indicated by an increase in vertical head movements and greater time taken to switch floors. To demonstrate the direct applicability of this fundamental wayfinding behavioral pattern, we formalize these results by modeling a visibility-based cognitive agent. Our results show that by modeling the transition between exploration and exploitation as a function of visibility, cognitive agents were able to replicate human wayfinding patterns observed in the desktop VR study. This simple demonstration shows the potential of extending our main findings concerning the nonlinear relationship between visibility and wayfinding to inform the modeling of human cognition.
Identification of the phase composition of solid microparticles in the nasal mucosa of patients with chronic hypertrophic rhinitis using Raman microspectroscopy
Authors: Čabanová Kristina , Motyka Oldřich , Bielniková Hana , Čábalová Lenka , Handlos Petr , Zabiegaj Dominika , Zeleník Karol , Dvořáčková Jana , Komínek Pavel , Heviánková Silvie , Havlíček Miroslav , Kukutschová Jana 
Published: September 2021

AbstractSolid particles, predominantly in micron and submicron sizes, have repeatedly been observed as a threat to a human health unique compared to the other textures of the same materials. In this work, the hypothesis the solid metal-based particles play a role in the pathogenesis of chronic hypertrophic rhinitis was investigated in patients who had not responded positively to medication. In the group of 40 randomly selected patients indicated for surgical mucotomy, the presence of solid micro- and submicron particles present in their nasal mucosa was assessed. For comparison, a set of 13 reference samples from patients without diagnosed chronic hypertrophic rhinitis was evaluated. The analysis was performed using Raman microspectroscopy. The advantage of this method is the direct identification of compounds. The main detected compounds in the mucosa samples of patients with chronic hypertrophic rhinitis were TiO2, carbon-based compounds, CaCO3, Ca(Fe, Mg, Mn)(CO3)2 MgCO3, Fe2O3, BaSO4, FeCO3 and compounds of Al and Si, all of which may pose a health risk to a living organism. In the reference samples, only TiO2 and amorphous carbon were found. In the control group mucosa, a significantly lower presence of most of the assessed compounds was found despite the longer time they had to accumulate them due to their higher mean age. Identification and characterisation of such chemicals compounds in a living organism could contribute to the overall picture of the health of the individual and lead to a better understanding of the possible causes not only in the chronic hypertrophic rhinitis, but also in other mucosal and idiopathic diseases.
Dizziness in Parkinson’s disease patients is associated with vestibular function
Authors: Park Jeong-Ho , Kang Suk Yun 
Published: September 2021

AbstractDizziness is common in Parkinson’s disease (PD) patients. It is known that orthostatic hypotension (OH) is the main cause of such dizziness, but even without OH, quite a few PD patients complain of dizziness in the clinic. It can be regarded as non-specific because most of these patients have no neurological abnormalities. We hypothesized that this type of dizziness would be associated with vestibular function, although included patients did not have clinically confirmed vestibulopathy. We studied 84 patients without OH among 121 PD patients. Their clinical features and function were compared between patients with and without dizziness. Hoehn and Yahr stage (H&Y stage), the Unified Parkinson's Disease Rating Scale (UPDRS) part III, the Korean version of the Mini-Mental State Examination (K-MMSE), education years, disease duration, total levodopa equivalent daily dose (LEDD), the presence of dizziness, the dizziness severity, and orthostatic hypotension were tested. Vestibular evoked myogenic potentials (VEMPs) were used to characterize vestibular function. Ocular (oVEMPs) and cervical (cVEMPs) were recorded. oVEMPs in the right side showed significantly reduced potentials (p = 0.016) in PD patients with dizziness, but cVEMPs did not (all ps > 0.2). Bilateral absent oVEMP responses were more common in PD patients with dizziness (p = 0.022), but the frequencies of bilateral absent cVEMP responses were not different between the dizzy and non-dizzy groups (p = 0.898). Dizziness in PD patients without orthostatic hypotension may be associated with vestibular hypofunction. Our results provide evidence that can aid clinicians when making a treatment plan for patients with dizziness. i.e., strategies to enhance reduced vestibular function may be helpful, but this suggestion remains to be evaluated.
Effect of 2.5D haptic feedback on virtual object perception via a stylus
Authors: Kim Gyuwon , Hwang Donghyun , Park Jaeyoung 
Published: September 2021

AbstractAs touch screen technologies advanced, a digital stylus has become one of the essential accessories for a smart device. However, most of the digital styluses so far provide limited tactile feedback to a user. Therefore we focused on the limitation and noted the potential that a digital stylus may offer the sensation of realistic interaction with virtual environments on a touch screen using a 2.5D haptic system. Thus, we developed a haptic stylus with SMA (Shape Memory Alloy) and a 2.5D haptic rendering algorithm to provide lateral skin-stretch feedback to mimic the interaction force between fingertip and a stylus probing over a bumpy surface. We conducted two psychophysical experiments to evaluate the effect of 2.5D haptic feedback on the perception of virtual object geometry. Experiment 1 investigated the human perception of virtual bump size felt via the proposed lateral skin-stretch stylus and a vibrotactile stylus as reference. Experiment 2 tested the participants’ ability to count the number of virtual bumps rendered via the two types of haptic styluses. The results of Experiment 1 indicate that the participants felt the size of virtual bumps rendered with lateral skin-stretch stylus significantly sensitively than the vibrotactile stylus. Similarly, the participants counted the number of virtual bumps rendered with the lateral skin-stretch stylus significantly better than with the vibrotactile stylus. A common result of the two experiments is a significantly longer mean trial time for the skin-stretch stylus than the vibrotactile stylus.