bluuebunny/crossref_metadata_2025_split huggingface dataset:
EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks
Authors: Meng Lubin , Huang Jian , Zeng Zhigang , Jiang Xue , Yu Shan , Jung Tzyy-Ping , Lin Chin-Teng , Chavarriaga Ricardo , Wu Dongrui 
Published: January 2021

Abstract
Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to the wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial attacks, e.g., the attacker can add tiny adversarial perturbations to a test sample to fool the model, or poison the training data to insert a secret backdoor. Previous research has shown that adversarial attacks are also possible for EEG-based BCIs. However, only adversarial perturbations have been considered, and the approaches are theoretically sound but very difficult to implement in practice. This article proposes to use narrow period pulse for poisoning attack of EEG-based BCIs, which is more feasible in practice and has never been considered before. One can create dangerous backdoors in the machine learning model by injecting poisoning samples into the training set. Test samples with the backdoor key will then be classified into the target class specified by the attacker. What most distinguishes our approach from previous ones is that the backdoor key does not need to be synchronized with the EEG trials, making it very easy to implement. The effectiveness and robustness of the backdoor attack approach is demonstrated, highlighting a critical security concern for EEG-based BCIs.
Evaluating the impact of investing in the industry of clinical practice guidelines for health systems
Authors: Hassanien Amal 
Published: January 2021

Abstract
Rationale: This review has been conducted to facilitate evidence-informed policymaking and help healthcare policymakers in Saudi Arabia decide whether or not a sustainable investment in the CPG industry is socially and economically viable.Objectives: To investigate whether the clinical practice guidelines help to improve clinical practice and save costs.Methods: A literature review to evaluate the benefits of implementing clinical practice guidelines.Results: The clinical practice guidelines help improve clinical practice, but the evidence about their impact on saving costs is insufficient in the literature.Conclusion: Investing in CPGs industry seems socially and economically viable as there are many benefits health-care regulators, providers, and payers might gain. The unified national CPGs would enable health-care regulators to optimise the quality of care services, including by protecting patient safety and preventing malpractice, and to reduce the number of medical errors. While updating national unified clinical guidelines would represent a trustworthy peer-reviewed approach to health care and offer providers a reference for best practices in health care customised to the local context. Also, having a national reference for standardised medical practices would help healthcare payers improve value-based payments.
Feasibility and effectiveness of remotely supervised tDCS combined with computerized cognitive training for patients with stroke: A randomized sham-controlled study
Authors: Yoon Ju-Yul , Son Mi-Nam , Jo Yun-Ju , Kim Da-Sol , Kim Gi-Wook , Won Yu-Hui , Park Sung-Hee , Seo Jeong-Hwan , Kim Yun-Hee , Ko Myoung-Hwan 
Published: January 2021

Abstract
Background Cognitive impairment after stroke is an unfavorable factor for long-term functional independence. Transcranial direct current stimulation (tDCS) is a promising tool for improving cognitive function in patients with stroke. Home-based rehabilitation is increasingly required for patients with stroke, with greater benefits expected if supplemented with remotely supervised tDCS (RS-tDCS). We evaluated cognitive improvement and the feasibility of RS-tDCS in patients with chronic stroke. Methods Thirty chronic stroke patients with cognitive impairment (K-MoCA <26) received a computerized cognitive training package (ComcogTM, Neofact, Seoul, Korea), and were randomized into real RS-tDCS and sham RS-tDCS groups according to the application of tDCS. Participants were treated 5 days/week for 4 weeks. To ensure correct self-application of tDCS (Mindd Stim®, Ybrain Inc., Korea), patients and caregivers received training and were monitored. Several cognitive evaluations were performed. Rate of adherence to the appropriate RS-tDCS session was also investigated. Results Among the 30 participants, 2 chose to withdraw and 2 were excluded due to noncompliance. In the within-group comparison, unlike the sham group (n= 14), the real group (n=12) showed a significant improvement in K-MoCA (intra-p=0.004 vs. 0.132), particularly in patients with moderate cognitive impairment (K-MoCA: 10–17; intra-p=0.001 vs. 0.835, K-MoCA: 18-25; intra-p=0.060 vs. 0.064). However, in K-DRS2, Stoop and K-BNT, both groups showed significant improvement, but there was no group time interaction. In the Trail Making Test, Go/no Go, and Controlled Oral Word Association Test, both groups did not show statistically significant improvement. A total of 551 of the 560 sessions conducted by 28 people were successfully performed (adherence rate: 98.4%) and no serious adverse effects were detected. Conclusion RS-tDCS is a safe and feasible rehabilitation modality for post-stroke cognitive dysfunction. It has the potential to enhance the effect of home-based CT. RS-tDCS seems to be particularly effective in patients with relatively more severe cognitive impairment who are capable of home-based training. Trial registration: Clinical Research information Service (KCT0003427). Registered 26 June 2018, https://cris.nih.go.kr/cris/en/search/search_result_st01.jsp?seq=12363
Characterization and eradication of the high concentration infection source of oral segment of Candida by infection examination diagnosis system
Authors: Nonomura Yuusuke 
Published: January 2021

Abstract
Purpose: Candida albicans (CA) is a major pathogenic fungus that causes a critical infection and life-threatening disease. Currently, during the treatment of COVID-19 (in ICU), invasive Candidiasis and Candida colonization should be prevented to avoid the increase, in mortality, in SAPSII, and in length of stay. Our aim was to characterize and analyze the infection of Candida albicans (CA) for eradication. Methods: We characterized and analyzed the infection source and infection field which are carrier field, diffusion field, and spread field, by using a new infection examination (diagnostic) system (IEDS) comprising a new dental formula (measurement analysis) medium (DFM) with time, space, and phase, and the simultaneous relative differential equations (C4RDE).Results: This study showed that CA was not an endogenous microorganism, but a fungus that infected teeth causing dental caries that was successfully eradicated from all teeth of 353 Japanese patients (oral cavity segment). [In the first examination, the percentages of people with CA (+) was 40.5% (the DMFT: 62.8%) and CA(-) was 56.4% (the DMFT: 47.1%). The difference in DMFT was 15.7% (P<0.01)] (DMFT is decayed, missing, and filled tooth index).Conclusion: Eradication of the infection source (IS) of the oral segment(s) and breaking the infection chain (IC) by IE(D)S will dramatically reduce the threat to the living body by pathogenic microorganisms. And, our methods help to eradicate the infection source (IS), prevent critical infection, and reduce mortality. The IEDS is a powerful tool that can be applied for any microbial infection easily. It is possible for the dentists to characterize CA by IEDS and eradicate CA from the oral cavity. Moreover, CA must consider the phase of the space-time of infection source, infection field, receptor field, resistance field, adhesive colony, fixed colony and infection chain. Moreover, CA must consider the phase of microorganisms. If they are neglected, the statistical research or the medical treatment etc., the study cannot obtain the correct result.
Hexagonal Resonator Loaded Star Shaped Polarization Insensitive Compact Broadband Zero Indexed Nano-Meta Absorber for Optical Region Applications: A Numerical Approach
Authors: Samsuzzaman Md , Hossain Ismail , Hoque Ahasanul , Islam Mohammad Tariqul , Almutairi Ali F. 
Published: January 2021

Abstract
Broadband response metamaterial absorber (MMA) remains a challenge among researchers. A nanostructured new Zero Indexed Metamaterial (ZIM) absorber is presented in this study, which is constructed with a hexagonal shape resonator for the optical region applications. The design consists of a resonator and dielectric layers made with tungsten and quartz (Fused), respectively. The proposed absorbent exhibits average absorption of more than 0.8972 (89.72%) within the visible wavelength of 450-600 nm and almost perfect absorption 0.99 (99%) at 458.54 nm. Based on computational analysis, the proposed absorber can be characterized as Zero Indexed Metamaterial. The developments of ZIM absorbers have demonstrated plasmonic resonance characteristics and a perfect impedance match. The incidence obliquity in typically the range of 0°–90° both in TE and TM mode with maximum absorbance is more than 0.8972 (~89.72%) and up to 35° angular stability, which is suitable for solar cell applications, like exploiting solar energy. The proposed structure prototype is designed and simulated by a study of microwave technology numerical computer simulation (CST) tools. Finite integration technique (FIT) and finite element method (FEM) is performed to data analysis in CST software, and HFSS also helps validate the numerical data of the proposed ZIM absorber. The proposed MMA design is appropriate for substantial amounts of absorption, wide-angle stability, absolute invisible layers, magnetic resonance imaging (MRI), color images, and thermal imaging applications.
A population survey on behavioural insights on COVID-19 in Sri Lanka: A quantitative analysis on perceptions, behaviours, opinions, trust and affect to inform pandemic outbreak response
Authors: Ginige Pabasari , Silva S.K.S.T. , Bandara T.P. , Weerasinghe W.M.P.C. , Thennakoon T.M.P.D.M. 
Published: January 2021

Abstract
Background The COVID-19 pandemic outbreak is placing insurmountable challenges and burden on health systems and authorities demanding responses with effective and appropriate policies and interventions. Wrong decision making, lack of foresightedness and preparation in the acute and transition phases can threaten the gains collectively achieved. Understanding the behaviours, perceptions and feelings of the population is imperative in management decisions. Not much evidence is available on such behavioural insights to inform the COVID-19 response in countries. This study is expected to contribute to the evidence-informed understanding on effective management of the outbreak.Methods This was a cross sectional observational study with entirely voluntary online participation. The study protocol and the questionnaire, originally prepared by a WHO collaboration, were adjusted to match the local setting and resource availability. The study explored 14 variables including perceptions, trust and behaviours in relation to COVID-19. Data was collected during the first wave of COVID-19 in early May 2020 and statistically analysed to see the associations and comparisons between chosen variables.Results N = 1001 with 65.63% from the age range 18–29 years and 65% from the non -health care worker category. Basic or postgraduate degree holders were 64.7%. Participants were from 23 out of the 25 districts in SL with 34.07% from high-risk districts. They were in general, knowledgeable (e.g., > 95% correctly identified common symptoms of COVID19) and majority (99.5%) reported conforming to the health recommendations. They trusted government health bodies including hospitals (90.8%) but majority (63.8%) had poor confidence in media in the ability to manage the outbreak. Stigma around COVID-19 was not a concern for the majority of 78.9%. Participants less than 30 years believed in conspiracies around COVID-19 more than older counterparts.Conclusion The perceptions, affect and behaviour of the study population gives insights on information dissemination, gaps in health message delivery, alternative approaches in responding and policy making helping to improve the pandemic response.
Correlation of histologic chorioamnionitis and intra-partum leukocytosis
Authors: Heyman Taryn , Sayyed Farah Al , Lederman Sanford , Zhang Peilin 
Published: January 2021

Abstract
Background Histologic chorioamnionitis (HCA) is the most common placental lesion measuring maternal/fetal responses to intraamniotic bacterial infection. Study design We reviewed 1400 placentas referred for placental examination and explored the relationship of HCA with clinical information and with total white cells (WBC), differentials, and whether maternal admission WBC and differentials predict HCA.Results The frequency of HCA of the 1400 placentas was 38.8% (543 of 1400), and funisitis 16.9% (237 of 1400). Abnormal white blood count (total WBC >10.3) within this population was 41.1% with abnormal neutrophil differential of 39.1% and lymphopenia of 33.9%. There is an association between HCA and elevated WBC, neutrophil differentials, and preterm delivery 32 weeks or earlier. The predictive value of WBC, differentials and gestational age was 59% using ROC analysis.Conclusion Prediction of HCA using WBC and differential is suboptimal. Molecular solution to HCA is required to identify patients at risk for maternal/fetal complications.
Identification of tRNA-Derived Small RNAs and their Potential Roles in the Hippocampus of Nicotine Exposure Rats
Authors: Shao Jiali , Fei Yanxia , Su Chen , Zou Wangyuan , Yang Jinfeng 
Published: January 2021

Abstract
Nicotine use is highly prevalent and brings a huge burden on individuals, society, health-care systems and economic development. The existing mechanisms underlying nicotine’ actions can’t illuminate all basic and clinical problems thoroughly. Transfer RNA-derived small RNAs (tsRNAs) is a novel class of small non-coding RNAs (sncRNAs), possessing potential regulatory functions in various diseases. However, the roles of tsRNAs in nicotine exposure have not been determined yet. In this study, firstly we established nicotine exposure model by subcutaneously injecting (sc.) with 0.5mg/kg of nicotine twice daily for 14 consecutive days, and conducted some behavioral observations (the pain threshold and body weight gains). Secondly, we identified the differentially expressed profiles of tsRNAs in rat hippocampus on saline or nicotine delivery conditions by using ncRNA-Seq, and then predicted the promising functions of the putative genes of the tsRNAs by bioinformatic method. The results shown that there were 26 differentially expressed tsRNAs (7 up-regulated and 19 down-regulated tsRNAs) (Fold change > 1.5; P < 0.05), of which the tRF-5 was the most common type. Eight tsRNAs were selected to validate the sequencing result by RT-qPCR. Then, based on the sequencing and RT-qPCR data, five candidate tsRNAs (tRF-1-T28-His-GTG-1, tRF-5c-Glu-CTC-1, tRF-5c-Glu-CTC-3, tRF-5c-Gly-GCC-2-M2, tRF-5c-Glu-TTC-4) were finally selected for further bioinformatic analysis. The GO and KEGG pathway enrichment analysis suggested that the five candidate tsRNAs might play regulatory roles through the cholinergic synapse pathways, dopaminergic synapse pathways, etc. In conclusion, our results indicated that tsRNAs were dysregulated in the rat hippocampus after nicotine exposure, and among them, tRF-5c-Glu-CTC-1 was the most promising one, which might lay a novel foundation for further research into nicotine’ actions.
Factors affecting retention in the Doctors to the Barrios Program (Philippines) from 2012 to 2019: A Mixed Methods Study
Authors: Flores Erika Louise Lapitan , Manahan Edric Matthew Rivera , Lacanilao Miguel Paulo Bernardo , Ladaw Isabella Ma. Beatriz Tinio , Mallillin Mico Martin Baligod , Mappatao Nikolai Thadeus Quinto , Leonardia Juan Alfonso , Pepito Veincent Christian Filipino 
Published: January 2021

Abstract
BACKGROUND: To address the maldistribution of healthcare providers and the shortage of physicians in geographically isolated and disadvantaged areas of the Philippines, the Doctors to the Barrios (DTTB) program was established in 1993. However, as of 2011, only 18% of the DTTBs chose to stay in their assigned municipalities after their two-year deployment, termed retention. This study aims to identify the individual, local, work, national, and international factors affecting the retention of DTTBs in their assigned communities after their two-year deployment.
METHODS: A descriptive, mixed-methods design was used. For the quantitative part, the modified and updated Stayers Questionnaire was given to all current DTTBs present in a Continuing Medical Education session in the Development Academy of the Philippines. Descriptive statistics were then presented. For the qualitative part, individual, semi-structured key informant interviews were conducted in-person or via phone with current and alumni DTTBs from 2012 to 2019. Proceedings of the interviews were transcribed, translated, and analyzed thematically.

RESULTS: 102 current DTTBs participated in the quantitative part of our study, while 10 current and former DTTBs participated in the interviews. Demographic factors and location, personal beliefs, well-being, friends and family dynamics, and perceptions about work were the individual factors identified to affect retention. Social working conditions, career development, and infrastructure, medical equipment, and supplies were among the work factors identified to affect retention. Geography, living conditions, local social needs, and technology were among the local factors identified to affect retention. Compensation, the recently signed Universal Healthcare Law, and Safety and Security were identified as national factors that could affect retention. International factors did not seem to discourage DTTBs from staying in their communities.

CONCLUSIONS: A host of individual, work-related, local, national, and international factors influence the DTTB’s decision to be retained in different, complex, interconnected, and dynamic ways. We also identified implementation issues in the DTTB program and suggested interventions to encourage retention.
Martensite Variant Identification For Shape Memory Alloys By Using Graph Neural Networks
Authors: Tseng YI-Ming , Wang Pei-Te , Chen Nan-Yow , Yang An-Cheng , Tsou Nien-Ti 
Published: January 2021

Abstract
Detailed microstructure evolution in shape memory alloys (SMAs) is typically studied by molecular dynamics (MD) simulations. However, the conventional post-processing tools for atomistic calculations, such as CNA and PTM, fail to identify distinct crystal variants and to reveal twin alignments in SMAs. In the current work, a powerful and efficient post-processing tool based on GraphSAGE neural network is developed, which can identify multiple phases in martensitic transformation, including the orthorhombic, monoclinic and R phases. Where the network was trained by the results of sets of temperatureand stress-induced martensitic transformation MD calculations. The accuracy and generality were also verified by the application to the cases which did not appear in the training dataset, such as unrecoverable nanoindentation process. The proposed method is rapid, accurate, and is ready to be integrated with any visualization tool for MD simulations. The outcome of the current work is expected to accelerate the pace of atomistic studies on SMAs and related materials.
An App Developed for Predicting Nurse Intention to Quit the Job (NIQJ) Using the Artificial Neural Networks(ANN) in Microsoft Excel: Population-Based Questionnaire Study
Authors: Jen Tung-Hui , Chien Tsair-Wei , Yeh Yu-Tsen , Lee Huan-Fang 
Published: January 2021

Abstract
Background: Studies in the past have identified factors related to the nursing staff’s intention to leave the unit, institution, and profession. However, none has successfully predicted the nurse's intention to quit the job (NIQJ). Whether NIQJ can be predicted be predicted is an interesting topic in healthcare management. A model to predict the NIQJ for novice nurses in hospitals should be investigated and developed in this mobile computer age. Objective: The aim of this study is to build a model to develop an app for automatic prediction and classification of NIQJ using a smaller number of items to help assess NIQJ and take necessary actions before nurses quit the job.Methods: We recruited 1104 novice nurses working in six medical centers in Taiwan to complete 100-item questionnaires related to NIQJ in October 2018. The k-mean was used to divide nurses into two classes (i.e., NIQJ and Non- NIQJ) based on five- NIQJ items regarding leave intention. Feature variables were chosen from 100 relevant items. Two models, including artificial neural network (ANN) and convolutional neural network (CNN), were compared across four scenarios made up by two training sets (n=1104 and n=804B) and their corresponding testing (n=300a) sets to verify the model accuracy (e.g., sensitivity, specificity, area under the receiver operating characteristic curve, AUC) and stability and generalization (e.g., using the training set to predict the testing set). An app predicting NIQJ was then developed involving the model's estimated parameters as a website assessment.Results: We observed that (1) 24 feature variables extracted from this study in ANN model yielded a higher AUC of 0.82 (95% CI 0.80-0.84) based on the total 1104 cases, (2) the ANN performed better than CNN on both accuracy, stability and generalization, and (3) an ready and available app for predicting NIQJ was successfully developed in this study.Conclusions: The 24-item ANN model with the 53 parameters estimated by the ANN for improving the accuracy of NIQJ has been developed with the use of Excel (Microsoft Corp). The app would help team leader and HR department to pick up nurse’s NIQJ before actions are taken, allowing them to make plans accordingly.
Outcomes of Patients Falling from Heights in the Level-I Trauma Center: A 10-Year Multi-Center Study
Authors: Wang Pei-Hsiu , Huang Chun-Hsiang , Chen I-Chung , Huang Edward Pei-Chuan , Lien Wan-Ching , Huang Chien-Hua 
Published: January 2021

Abstract
Background: Falls from height and fall-related injuries are global healthcare challenges. Falls cause a significant proportion of urban trauma with high mortality rates, being the leading cause of accidental deaths. This study aims to investigate the outcomes of patients after free falls in the level 1 trauma centers in Taiwan.Methods: This retrospective cohort study was conducted at the emergency departments of the National Taiwan University Hospital, and its two branches, the Hsin-Chu branch and the Yun-Lin branch between January 2010 and September 2020. Adult patients with free falls higher than one story were enrolled. Clinical data were obtained from electronic medical records. Odds ratios (OR) were computed with 95% confidence intervals (CIs) for significant parameters for mortality in the logistic regression models.Results: A total of 371 patients were enrolled and 101 patients suffered from out-of-hospital cardiac arrests (OHCAs). The mortality rate was 98% and 11% in patients with and without OHCA and the majority of deaths occurred within one day of the fall. Falling heights were significantly (OR, 1.14, 95% CIs, 1.10-1.19) related to OHCAs. Among the patients without cardiac arrests on arrival, a higher injury severity score (ISS) was significantly (OR, 1.10, 95% CIs, 1.07-1.14) related to deaths. Serious head/neck (OR, 5.19, 95% CI, 2.21-12.19) and chest injury (OR, 2.39, 95% CIs, 1.10-5.17) were significantly fatal injuries. Conclusion: Patients with falls-related OHCA had poor outcomes and higher falling height was significantly related to cardiac arrests. A higher ISS was related to death during admission. A better understanding of the characteristics allows for resource allocation for patients with free-fall trauma.