bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of ferroptosis-related subtypes, characteristics of TME infiltration and development of prognostic models in gastric cancer
Authors: ling rui , TANG XIANG , LIU NA , YU YUNPENG , SU YUTING , ZHOU YUEPENG , CHEN DEYU 
Published: February 2022

Abstract
Purpose: Ferroptosis is a new type of cell death in morphology, biochemistry and genetics, and is closely related to the occurrence, development, prognosis and treatment of tumors. However, the potential role of ferroptosis-related genes (FRGs) in the tumor microenvironment (TME) is indistinct. Methods: We described and evaluated the expression pattern of FRGs in gastric cancer (GC) samples from the fields of genetics and transcription. Subsequently, we identified two different molecular subtypes and found the changes in multilayer FRGs. Then, we constructed an FRG-score to predict overall survival (OS) and verified its predictive ability in GC patients. Therefore, we constructed a high-precision nomogram to improve the clinical applicability of the FRG-score. Results: The changes in multilayer FRGs are related to the clinicopathological characteristics, prognosis and TME cell infiltration characteristics of patients. Low FRG-score, due to its high microsatellite instability (MSI-H), high mutation burden and immune activation, indicates the possible advantage of OS. In addition, the FRG-score was closely correlated with the cancer stem cell (CSC) index and chemotherapeutic drug sensitivity. Conclusions: Our generalized analysis of FRGs in gastric cancer shows their potential role in the TME, clinicopathological characteristics and prognosis.
Phytochemical analysis, antiproliferative and apoptosis-inducing properties of Persicaria strigosa Nakai
Authors: Swargiary Ananta , Roy Mritunjay Kumar , Boro Harmonjit , Verma Akalesh Kumar 
Published: February 2022

Abstract
Persicaria strigosa is an important medicinal plant having several ethnomedicinal values. The present study investigates the phytochemical contents, antiproliferative, and apoptosis-inducing properties of P. strigosa. The phytocompounds were identified by the GC-MS technique. Antiproliferative and apoptosis-inducing properties were conducted in DL cells. In-silico molecular docking, drug-likeness, and ADMET was carried out to study the binding affinity and drug-likeness of the compounds. The study revealed a dose-dependent antiproliferative activity of P. strigosa. Ethyl acetate extract showed the strongest activity compared to other extracts. Plant extract-treated cells showed morphological features of apoptotic cells. GC-MS analysis identified 12 compounds from the ethyl acetate extract. Compound C2, C5, C6, C7, and C12 showed the best binding affinity with the anti-apoptotic proteins. The phytocompounds were predicted to possess drug-likeness property and a good ADMET profile. The findings, thus, suggest that the Persicaria strigosa extract could be a potential source of anticancer agents.
Efficacy and predictor of anti-TNFα agents in patients with intestinal Behçet's disease
Authors: Miyazaki Haruka , Watanabe Daisuke , Okamoto Norihiro , Tokunaga Eri , Ku Yuna , Takenaka Haruka , Hoshi Namiko , Ooi Makoto , Kodama Yuzo 
Published: February 2022

Abstract
Background Behçet's disease (BD) is a recurrent multisystem inflammatory disease. Anti-tumor necrosis factor (TNF) α agents have been used to treat patients with intestinal BD with severe disease activity or those who are resistant to conventional treatments; however, the long-term efficacy of anti-TNFα agents in intestinal BD remains unclear. In the present study, we investigated the clinical outcomes and predictors of discontinuation of anti-TNFα agents in patients with intestinal BD.Methods We reviewed the medical records of patients with intestinal BD who received first-line anti-TNFα agents between January 2009 and June 2020. The primary outcome was the percentage of patients who continued anti-TNFα therapy for 48 weeks. Secondary outcomes included the percentage of patients who achieved marked improvement, complete remission, and mucosal healing, as well as predictors of discontinuation of anti-TNFα agents.Results A total of 29 patients were included in the study. Twenty-two (75.9%) patients continued anti-TNFα therapy for 48 weeks. The percentage of patients who achieved marked improvement, complete remission, and mucosal healing at week 48 was 48.3%, 37.9%, and 48.3%, respectively. At week 96, 11 (37.9%) patients achieved marked improvement, complete remission, and mucosal healing. A higher C-reactive protein level (CRP; ≥1 mg/dL) at baseline was a predictor of discontinuation of anti-TNFα agents.Conclusions The 48-week continuation rate of anti-TNFα agents was 75.9% in bio-naïve patients with intestinal BD. However, a higher baseline CRP level (≥1 mg/dL) was associated with discontinuation of anti-TNFα agents.
Integrating a GIS-based approach and a SWAT model to identify potential suitable sites for rainwater harvesting in Rwanda
Authors: Umugwaneza Adeline , Chen Xi , Liu Tie , Mind'je Richard , Uwineza Aline , Kayumba Patient Mindje , Uwamahoro Solange , Umuhoza Jeanine , Gasirabo Aboubakar , Maniraho Albert Poponi 
Published: February 2022

AbstractThe increasing demand for water results in the overexploitation of water resources. This situation calls for more effective water management alternatives including rainwater harvesting (RWH) systems. Due to the lack of biophysical data and infrastructure, the identification of suitable sites for various RWH systems is a challenging issue. However, integrating geospatial analysis and modeling approaches has become a promising tool to identify suitable sites for RWH. Thus, this study aimed at identifying suitable sites for RWH in the Nyabugogo catchment located in Rwanda by integrating a geo-information-based multi-criteria decision-making (MCDM) and SWAT (Soil and Water Assessment Tool) model. Moreover, the sediment yield was compared to the soil erosion evaluated using the Revised Universal Soil Loss Equation (RUSLE) owing to the lack of sediment concentration measured data. The results revealed that about 4.8 and 16.35% of the study area are classified as highly suitable and suitable areas for RWH, respectively. Around 6% of the study area (98.5 km2) was found to be suitable for farm ponds, whereas 1.6% (26.1 km2) suitable for check dams, and 25.9% (423 km2) suitable for bench terraces. Among 50 proposed sites for the RWH structures, 29 are located in the most suitable area for RWH. The results implicated that the surface runoff, sediment yield, and topography are essential factors in identifying the suitability of RWH areas. It is concluded that the integrated geospatial and MCDM techniques provide a useful and efficient method for planning RWH at a basin scale in the study area.
Monitoring indigenous microalgae using derivative spectrophotometry and comparison with M. aeruginosa and C. vulgaris
Authors: Singh Jaitegh , Örmeci Banu 
Published: February 2022

Abstract
Derivative spectrophotometry was investigated as a monitoring tool for indigenous microalgae in surface waters. Absorbance spectra of indigenous microalgae were studied at low, medium and high range concentrations and were compared to the absorbance spectra of pure strains of M. aeruginosa and C. vulgaris to understand the differences in their absorbance fingerprints and the applicability of this method for real-time monitoring. Method Detection Limit (MDL) of the indigenous microalgae sample from its absorbance spectra was found to be 158,693 cells/mL. First derivative spectrophotometry was effective in detecting mixed indigenous microalgae at medium and high concentrations; however, it failed to differentiate between noise and signal at low concentrations. Subsequently, Savitzky-Golay algorithm was applied to improve the sensitivity and specificity of detection. The Savitzky-Golay first derivative of absorbance resulted in distinctive peaks and spectra fingerprints, indicating it can be used not only to monitor but also to identify various species of microalgae in water bodies. The Savitzky-Golay first derivative of absorbance also resulted in the lowest detection limits (60,170 cells/mL). Derivative spectrophotometry, along with mathematical and statistical tools, can be used for real-time detection and monitoring of mixed indigenous microalgae in surface waters.
Los sistemas de conceptualización y la semántica cognitiva. La polisemia y la metáfora conceptual
Authors: Escobar Zapata Emérita 
Published: February 2022

El propósito central de la presente investigación es estudiar el fenómeno de la polisemia y la metáfora conceptual, partiendo de la hipótesis planteada por Evans2 (2014) 2015, quien sostiene que los «significados» que están asociados con las palabras1 son de naturaleza proteica, es decir, flexibles, abiertos y altamente dependientes del contexto en el que están incrustados. Asimismo, se pretende demostrar que el significado de las unidades lingüísticas es altamente motivado, corporeizado, y que el lenguaje humano refleja estructuras conceptuales basadas en el carácter experiencial, sociocultural
A Combined Feature Screening Approach of Random Forest and Filterbased
Methods for Ultra-high Dimensional Data
Authors: Zhou Lifeng , Wang Hong 
Published: February 2022

Background:
Various feature (variable) screening approaches have been proposed in the past
decade to mitigate the impact of ultra-high dimensionality in classification and regression problems, including
filter based methods such as sure independence screening, and wrapper based methods such as
random forest. However, the former type of methods rely heavily on strong modelling assumptions
while the latter ones requires an adequate sample size to make the data speak for themselves. These requirements
can seldom be met in biochemical studies in cases where we have only access to ultra-high
dimensional data with a complex structure and a small number of observations.

Objective:
In this research, we want to investigate the possibility of combining both filter based screening
methods and random forest based screening methods in the regression context.

Method:
We have combined four state-of-art filter approaches, namely, sure independence screening
(SIS), robust rank correlation based screening (RRCS), high dimensional ordinary least squares projection
(HOLP) and a model free sure independence screening procedure based on the distance correlation
(DCSIS) from the statistical community with a random forest based Boruta screening method from the
machine learning community for regression problems.

Result:
Among all the combined methods, RF-DCSIS performs better than the other methods in terms
of screening accuracy and prediction capability on the simulated scenarios and real benchmark datasets.

Conclusion:
By empirical study from both extensive simulation and real data, we have shown that both
filter based screening and random forest based screening have their pros and cons, while a combination
of both may lead to a better feature screening result and prediction capability.
Computational Approach on Acoustic and Flow Performances of a Combined
Resistive and Reactive Muffler
Authors: Sinaga Farlian Rizky , Ubaidillah U. , Yahya Iwan , Choi Seung-Bok , Aziz Siti Aishah Abdul , Yunus Nurul Azhani 
Published: February 2022

Aim:
The internal combustion engine (ICE) based vehicles must follow strict regulations regarding
noise levels, especially in the racing competition. The noise level is typically gauged as per two
different scenarios: stationary engine revolution and maximum achievable revolution. One cannot reach
the required noise level by deploying just reactive or resistive muffler type separately. This research recommends
a novel mix of reactive and resistive mufflers in a single package solution. For assessing the
noise level, three different types of mufflers are devised and studied by means of a computational approach.
The new exhaust design in this study becomes a novelty of the proposed article. In analyzing the
acoustic capability of the muffler, up to now it has not been able to dampen in various frequency ranges.

Method:
In this paper, the author wants to perform a computational analysis of 3 muffler models that
combine several methods of attenuation that are effective at different specific frequency ranges with
different configurations in order to obtain a good combined attenuation capability in various frequency
ranges. Muffler 1 uses simple reactive and dissipative techniques like standard mufflers, while muffler 2
combines the dissipative technique with a Helmholtz resonator acting as the reactive part. Muffler 3 has a
multi-chamber system that uses a combination of several advanced techniques. The three mufflers are
evaluated on the basis of their capacity to decrease noise level. This noise level is assessed by considering
both transmission and insertion loss through mathematical calculations in the frequency range of 200
Hz to 6400 Hz with the help of pressure acoustic, frequency domain (ACPR) simulation. Apart from
noise evaluation, this study also examines flow parameters to estimate the pressure drop for the proposed
muffler.

Result:
Comsol simulation provided both insertion loss (IL) and transmission loss (TL) with different
trends. Muffler 3 had broadband response compared to its counterparts. Verifiying the finite element
simulation results, electroacoustic models of each muffler were simulated using Matlab Simulink to get
frequency response. Both finite element and electroacoustic modeling results have a good agreement.
Pressure distribution of each model was also evaluated in terms of isosurface total pressure.

Conclusion:
It is demonstrated that the proposed muffler having a multi-chamber setup provides the best
performances showing both superior and consistent noise reduction throughout the 200-6400 Hz frequency
range and good airflow that does not create backpressure due to noise suppression efforts.
K-Nearest Neighbor (K-NN) algorithm with Euclidean and Manhattan in classification of student graduation
Authors: Hidayati Nur , Hermawan Arief 
Published: February 2022

K-Nearest Neighbor (K-NN) algorithm is a classification algorithm that has been proven to solve various classification problems. Two approaches that can be used in this algorithm are K-NN with Euclidean and K-NN with Manhattan. The research aims to apply the K-NN algorithm with Euclidean and K-NN with Manhattan to classify the accuracy of graduation. Student graduation is determined by the variables of gender, major, number of first-semester credits, number of second-semester credits, number of third-semester credits, grade point on the first semester, grade point on the second semester, grade point on the third semester, and age. These variables determine the accuracy of student graduation, timely or untimely. The implementation of the K-NN algorithm is carried out using Rapidminer software. The results were obtained after testing 380 training data and 163 testing data. The best accuracy system was achieved at K=7 with a value of 85.28%. The two algorithmic approaches did not affect the accuracy of the results. Furthermore, the addition of the value of K did not completely affect the accuracy.
Design and First Impressions of a Small Private Online Course in Clinical Workplace Learning: Questionnaire and Interview Study
Authors: Hamoen Esther C , De Jong Peter G M , Van Blankenstein Floris M , Reinders Marlies E J 
Published: February 2022

Background
Clinical workplace learning takes place in a dynamic and complex learning environment that is designated as a site for patient care and education. Challenges in clinical training can be overcome by implementing blended learning, as it offers flexible learning programs suitable for student-centered learning, web-based collaboration, and peer learning.

Objective
The aim of this study is to evaluate the Small Private Online Course (SPOC) by interns’ first impressions and satisfaction measures (N=20) on using the SPOC. This study describes the design process of a SPOC from a theoretical and practical perspective and how it has been integrated into a clinical internship in internal medicine.

Methods
The design of the SPOC was based on general theoretical principles that learning should be constructive, contextual, collaborative, and self-regulated, and the self-determination theory to stimulate intrinsic motivation. Interns’ impressions and level of satisfaction were evaluated with a web-based questionnaire and group interview.

Results
Interns thought the web-based learning environment to be a useful and accessible alternative to improve knowledge and skills. Peer learning and web-based collaboration through peer interaction was perceived as less effective, as student feedback was felt inferior to teacher feedback. The interns would prefer more flexibility within the course, which could improve self-regulated learning and autonomy.

Conclusions
The evaluation shows that the SPOC is a useful and accessible addition to the clinical learning environment, providing an alternative opportunity to improve knowledge and skills. Further research is needed to improve web-based collaboration and interaction in our course.
An E–Mental Health Solution to Prevent and Manage Posttraumatic Stress Injuries Among First Responders in Alberta: Protocol for the Implementation and Evaluation of Text Messaging Services (Text4PTSI and Text4Wellbeing)
Authors: Obuobi-Donkor Gloria , Eboreime Ejemai , Bond Jennifer , Phung Natalie , Eyben Scarlett , Hayward Jake , Zhang Yanbo , MacMaster Frank , Clelland Steven , Greiner Russell , Jones Chelsea , Cao Bo , Brémault-Phillips Suzette , Wells Kristopher , Li Xin-Min , Hilario Carla , Greenshaw Andrew J , Agyapong Vincent Israel Opoku 
Published: February 2022

Background
First responders are confronted with traumatic events in their work that has a substantial toll on their psychological health and may contribute to or result in posttraumatic stress injuries (PTSIs) for many responders. Persons with a PTSI usually seek management therapies. Evidence indicates that digital delivery of these therapies is an innovative, efficient, and effective way to improve PTSI symptoms as an adjunct to in-person delivery.

Objective
This project aims to implement and provide accessible, convenient, and economical SMS text messaging services, known as Text4PTSI and Text4Wellbeing, to first responders in Alberta, Canada; to prevent and improve the symptoms of PTSI among first responders; and to improve their overall quality of life. We will evaluate posttraumatic symptoms and the impact of Text4PTSI and Text4Wellbeing on stress, anxiety, and depression in relation to the correspondents’ demographic backgrounds.

Methods
First responders who subscribe to Text4PTSI or Text4Wellbeing receive daily supportive and psychoeducational SMS text messages for 6 months. The SMS text messages are preprogrammed into an online software program that delivers messages to subscribers. Baseline and follow-up data are collected through online questionnaires using validated scales at enrollment, 6 weeks, 12 weeks, and 24 weeks (end point). In-depth interviews will be conducted to assess satisfaction with the text-based intervention.

Results
We hypothesize that participants who enroll in this program will have improved PTSI symptoms; increased or improved quality of life; and significant reduction in associated stress, depression, and anxiety symptoms, among other psychological concerns. Improvement will be determined in comparison to established baseline parameters.

Conclusions
This research will be beneficial for practitioners and will inform policy-making and decision-making regarding psychological interventions for PTSI. Lessons from this study will inform the scale-up of the intervention, a cost-effective, zero contact therapeutic option to manage PTSI.

International Registered Report Identifier (IRRID)
PRR1-10.2196/30680
Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis
Authors: Jang Hyeju , Rempel Emily , Roe Ian , Adu Prince , Carenini Giuseppe , Janjua Naveed Zafar 
Published: February 2022

Background
The development and approval of COVID-19 vaccines have generated optimism for the end of the COVID-19 pandemic and a return to normalcy. However, vaccine hesitancy, often fueled by misinformation, poses a major barrier to achieving herd immunity.

Objective
We aim to investigate Twitter users’ attitudes toward COVID-19 vaccination in Canada after vaccine rollout.

Methods
We applied a weakly supervised aspect-based sentiment analysis (ABSA) technique, which involves the human-in-the-loop system, on COVID-19 vaccination–related tweets in Canada. Automatically generated aspect and opinion terms were manually corrected by public health experts to ensure the accuracy of the terms and make them more domain-specific. Then, based on these manually corrected terms, the system inferred sentiments toward the aspects. We observed sentiments toward key aspects related to COVID-19 vaccination, and investigated how sentiments toward “vaccination” changed over time. In addition, we analyzed the most retweeted or liked tweets by observing most frequent nouns and sentiments toward key aspects.

Results
After applying the ABSA system, we obtained 170 aspect terms (eg, “immunity” and “pfizer”) and 6775 opinion terms (eg, “trustworthy” for the positive sentiment and “jeopardize” for the negative sentiment). While manually verifying or editing these terms, our public health experts selected 20 key aspects related to COVID-19 vaccination for analysis. The sentiment analysis results for the 20 key aspects revealed negative sentiments related to “vaccine distribution,” “side effects,” “allergy,” “reactions,” and “anti-vaxxer,” and positive sentiments related to “vaccine campaign,” “vaccine candidates,” and “immune response.” These results indicate that the Twitter users express concerns about the safety of vaccines but still consider vaccines as the option to end the pandemic. In addition, compared to the sentiment of the remaining tweets, the most retweeted or liked tweets showed more positive sentiment overall toward key aspects (P<.001), especially vaccines (P<.001) and vaccination (P=.009). Further investigation of the most retweeted or liked tweets revealed two opposing trends in Twitter users who showed negative sentiments toward vaccines: the “anti-vaxxer” population that used negative sentiments as a means to discourage vaccination and the “Covid Zero” population that used negative sentiments to encourage vaccinations while critiquing the public health response.

Conclusions
Our study examined public sentiments toward COVID-19 vaccination on tweets over an extended period in Canada. Our findings could inform public health agencies to design and implement interventions to promote vaccination.