bluuebunny/crossref_metadata_2025 huggingface dataset:
Una experiencia de escolarización en el contexto rural en la Puna Argentina
Authors:   IRES-UNCa CONICET, Tapia María Gabriela , Melandez Cecilia Evangelina ,   IRES-UNCa CONICET, Yuni José Alberto ,   IRES-UNCa CONICET
Published: December 2022

El propósito de este artículo es examinar los retos que enfrenta la escuela secundaria, ligada desde su origen a mandatos y formatos modernos, para su expansión hacia contextos rurales, en el marco de una creciente fragmentación del sistema educativo. El análisis propuesto se realiza a partir de la experiencia de escolarización de una joven de la región puneña argentina. El enfoque de investigación adoptado es el cualitativo la perspectiva la etnografía. Los resultados evidencian que,en el caso en estudio, la escolarización enfrenta retos y alberga posibilidades vinculadas a brindar conocimientos útiles para las comunidades rurales en la región, distanciándose de los propósitos de la escuela secundaria común, pero a la vez el acceso a la educación y los bienes que aporta la escuela representan la puerta de acceso a otros derechos, no solo para la estudiante sino también para su familia.
Cálculo de probabilidades en tablas de contingencia por estudiantes chilenos de primer año medio
Authors:   Universidad de Los Lagos, Calderón Torres Daniela , García-García Jaime I. ,   Universidad de Los Lagos, Fernández Coronado Nicolás ,   Universidad de Los Lagos, Hernández Arredondo Elizabeth ,   Universidad de Los Lagos
Published: December 2022

La enseñanza de la probabilidad ha tomado un papel importante y necesario en la formación de los estudiantes, puesto que en la cotidianidad se presentan situaciones en las cuales es fundamental entender afirmaciones probabilísticas, o bien, calcular la probabilidad de eventos para la toma de decisiones. El presente estudio tiene por objetivo evaluar el manejo de tablas de contingencia 2x2, respecto al cálculo de probabilidades, por 25 estudiantes chilenos de primer año medio (14-15 años), antes y después de una experiencia de aprendizaje. El estudio es de tipo cualitativo, descriptivo-exploratorio, donde se describen y comparan las respuestas de los participantes en seis ítems relacionados con el cálculo de probabilidades simples, conjuntas y condicionales. En general, los resultados indican una mejora en el cálculo de probabilidades por parte de los participantes, mediante el uso de la regla de Laplace y la regla de tres como estrategias de solución; sin embargo, persisten algunos conflictos semióticos, por ejemplo, la confusión entre una probabilidad conjunta con una condicional, o viceversa, después de la experiencia de aprendizaje.
Atherosclerosis: From the Disruption of Mitochondrial Membrane
Potential to the Potential Interventional Strategies
Authors: Xia Dexiang , Chen Yanmei , Luo Guifang , Wei Dangheng
Published: December 2022

Atherosclerosis (AS) is the major factor of cardiovascular disease (CVD) and
is characterized by a progressive and chronic inflammatory process in the arterial wall.
Recent studies have shown that disruption of the mitochondrial membrane potential
(deltapsi (m)) directly affects the electron transport chain (ETC), which in turn
leads to oxidative stress, and furthermore, its alteration leads to apoptosis and activation
of the NLRP3 inflammasome, thereby promoting the development of AS. Here, this review
describes how deltapsi (m) contributes to the development of AS by mediating
oxidative stress, apoptosis, and NLRP3 inflammasome activation, and potential AS intervention
strategies by targeting oxidative stress, apoptosis, and NLRP3 inflammasome activation
induced by deltapsi (m).
Understanding and Targeting the Epigenetic Regulation to Overcome
EGFR-TKIs Resistance in Human Cancer
Authors: Sun Lan , Gao Lingyue , Zhao Yingxi , Wang Yuqing , Xu Qianhui , Zheng Yiru , Chen Jiali , Wang He , Wang Lihui
Published: December 2022

Background:

The occurrence and progression of cancer are the results of the dysregulation
of genetics and epigenetics. Epigenetic regulation can reversibly affect gene transcription activity
without changing DNA structure. Covalent modification of histones is crucial in the epigenetic
regulation of gene expression. Furthermore, epidermal growth factor receptor (EGFR) significantly
affects cell tumorigenesis, proliferation, antitumor drug resistance, etc. Overexpression of
EGFR promotes cancer development. Therefore, EGFR-targeted drugs have become the focus of
tumor therapy. With the advent of epidermal growth factor receptor tyrosine kinase inhibitors
(EGFR-TKIs), EGFR-TKIs resistance, which occurs about half a year to a year, has become an
obstacle in cancer treatment.

Objective:

The objective of this study is to discuss the ways to overcome EGFR-TKIs resistance in
a variety of tumors.

Methods:

The combination therapy of epigenetic drugs and other drugs is used.

Results:

The combination of the two drugs can overcome the resistance of EGFR-TKIs and prolong
the survival of patients.

Conclusion:

This article depicts the concepts of epigenetics and the mechanism of EGFR-TKIs
resistance and then illustrates the relationship between epigenetic mechanisms and EGFR-TKIs
resistance. Finally, it discusses the clinical research and the latest patents for using epigenetic
drugs to reverse EGFR-TKIs resistance in human cancer. In the future, more novel targets may be
discovered for overcoming resistance to EGFR-TKIs, not just on histone deacetylases (HDACs).
The dosing course and mode of administration of the combination therapy containing epigenetic
drugs need further study. This review provides new ideas for using epigenetic agents to overcome
EGFR-TKIs resistance.
In vivo Antihyperglycemic and Antidyslipidemic Effects of L-Tartaric
Acid
Authors: Eddouks Mohamed , Amssayef Ayoub
Published: December 2022

Aims:

The aim of the study was to investigate the antihyperglycemic effect of L-Tartaric acid.

Background:

L-Tartaric acid is a natural product with possible beneficial effects on health.

Objective:

The goal of this work was to evaluate the antihyperglycemic and antidyslipidemic effects of L-Tartaric acid (L-TA) in rats.

Materials and methods:

In the first model, the effects of L-TA (10 and 40 mg/kg) on diabetes conditions induced by streptozotocin (STZ) in rats were investigated. In the second model, the effects of L-TA (40 and 80 mg/kg) on dyslipidemia induced by tyloxapol (Triton WR-1339) in rats were assessed.

Results:

L-TA (40 mg/kg) had improved all studied parameters. L-TA at 40 mg/kg was able to significantly reduce glycaemia, improve oral glucose tolerance (OGT), increase glycogen content in liver and extensor digitorum longus (EDL) muscle, and ameliorate the lipidic profile and atherogenic indices in STZ-diabetic rats.

Conclusion:

L-Tartaric acid was able to exhibit antihyperglycemic and antidyslipidemic effects in STZ-induced diabetic rats. Moreover, the antidyslipidemic effect of L-Tartaric acid was confirmed in tyloxapol-induced hyperlipidemic rats.
Pattern of Thyroid Cancer and its Associated Factors among Thyroid Patients Underwent Thyroidectomy at Jimma Medical Center, Southwest Ethiopia; A Four Years Retrospective Review
Authors: Mulatu Bilisuma , Michael Yadene , Alemu Seifu , Demissie Wondu Reta
Published: December 2022

Background:

Thyroid cancer is the most common malignant disease of endocrine system and its incidence is rapidly increasing globally (about three to four times higher among females and accounts the sixth most common malignancy diagnosed in women). Among the four major types of thyroid cancer, papillary thyroid cancer (PTC) accounts 85-90% from all thyroid cases, followed by follicular thyroid cancer (FTC) which accounts for 5-10% of cases.

Objective:

The present study aimed to assess the pathologic patterns of thyroid disease at Jimma medical center (JMC).

Materials and Methods:

A retrospective data of 260 patients who underwent thyroid surgery from 2015 to 2019 were included in the study and the status of the disease (clinical manifestations, laboratory/pathology findings (thyroid function tests (TFTs) and biopsy) were reviewed from patient cards. The pattern of thyroid cancer was discriminated based on histo-pathological biopsy results. Descriptive and analytical statistics were applied to express the finding and reported by tables, figures and narration. Cross tabulation and logistic regression was applied to determine the association between thyroid CA and its predictors. A p-value of <0.05 was declared as statistically significant.

Results:

From the total sample of 260 patients underwent thyroid surgery, majority of them were females 219(84.2%), belong to age interval of 31-40 years (34.6%), dwellers of Oromia region (91.2%) and Jimma zone (83.8%). Colloid goiter was the most prevalent pattern of thyroid disease (74.6%) followed by follicular CA (4.2%), papillary CA (1.9%) and medullary CA (0.77%) while biopsy results of 48(18.46%) patients were not known. In general, about 194(91.5%) of the thyroid lesion was identified as benign type and malignancy accounts for 18(8.5%) from the total conducted biopsy results of 212 patients. Five variables (marital status, family history of the disease, nodularity, surface and border of the thyroid mass) were the predictors of thyroid malignancy in univariate and finally, two variables (thyroid tissue with surface (rough) and border (irregular)) were identified as the predictors of thyroid malignancy in multivariate [1.9(95%CI; 1.17 to 5.8) P=0.012 and 2.5(95%CI; 1.13 to 16.16) P<0.001] respectively.

Conclusion and Recommendation:

The burden of malignancy was higher and alarming among thyroid diseases and warrants early screening and management.
Association between Diabetes and Rheumatoid Arthritis: A Systematic Literature Review
Authors: Okais Jad , Fayad Fouad , Baddoura Rafic , Tabesh Ouidade Aitisha , Aouad Krystel , Ghoubar Marcelle , Sunna Nancy , Mysler Eduardo
Published: December 2022

Objective:

To examine the risk of diabetes mellitus (DM) in patients with rheumatoid arthritis (RA) and whether the risk is related to conventional risk factors, RA disease activity, and treatment.

Methods:

A systematic literature review (SLR) query was conducted using specified MeSH terms, searching PubMed and EMBASE databases from inception to March 2020. Both cohort or case-control design studies assessing the incidence or prevalence of DM in RA patients were included.

Results:

Of the 1948 articles, 43 peer-reviewed observational studies were selected. A high degree of heterogeneity in study design and reporting was observed, precluding final conclusions.

Based on the studies included, it was observed that DM prevalence ranged between 1% and 20% in RA patients, which was similar to controls (1–29%). The cumulative incidence of DM in RA patients ranged between 1.3% and 11.7% over different time frames. DM incidence rates in patients with RA per 1000 person-years ranged from 5.2 to 16.7.

RA patients may be at higher risk of DM, particularly among those receiving glucocorticoids (GC), while patients on hydroxychloroquine and biological disease-modifying anti-rheumatic treatments (DMARDs) may be at lower risk.

Conclusion:

DM incidence may be increased in patients with RA as a result of more concomitant traditional risk factors and GC exposure. It is unclear whether biologics may have a true protective effect or provide a GC-sparing effect. High-quality studies in large cohorts of RA patients with appropriate adjustment for covariates are warranted to fully investigate the interplay between DM and RA.
Review of Progress and Prospects in Research on Enzymatic and Non-
Enzymatic Biofuel Cells; Specific Emphasis on 2D Nanomaterials
Authors: Geetha Mithra , Sadasivuni Kishor Kumar , Al-Ejji Maryam , Sivadas Nandagopal , Baig Moghal Zubair Khalid , Promi Tamanna Jannat , Ahmad Sumayya Ali , Alabed Sara , Hijazi Dima Anwar , Alsaedi Fatimatulzahraa , Al-Shaibah Faozia Nasser
Published: December 2022

Energy generation from renewable sources and effective management are two critical challenges for sustainable development. Biofuel Cells (BFCs) provide an elegant solution by com-bining these two tasks. BFCs are defined by the catalyst used in the fuel cell and can directly gener-ate electricity from biological substances. Various nontoxic chemical fuels, such as glucose, lactate, urate, alcohol, amines, starch, and fructose, can be used in BFCs and have specific components to oxide fuels. Widely available fuel sources and moderate operational conditions make them promise in renewable energy generation, remote device power sources, etc. Enzymatic biofuel cells (EBFCs) use enzymes as a catalyst to oxidize the fuel rather than precious metals. The shortcoming of the EBFCs system leads to integrated miniaturization issues, lower power density, poor operational sta-bility, lower voltage output, lower energy density, inadequate durability, instability in the long-term application, and incomplete fuel oxidation. This necessitates the development of non-enzymatic bio-fuel cells (NEBFCs). The review paper extensively studies NEBFCs and its various synthetic strat-egies and catalytic characteristics. This paper reviews the use of nanocomposites as biocatalysts in biofuel cells and the principle of biofuel cells as well as their construction elements. This review briefly presents recent technologies developed to improve the biocatalytic properties, biocompatibil-ity, biodegradability, implantability, and mechanical flexibility of BFCs.
Analysis of Sparse Signal Sequences under Compressive Sampling Techniques
for Different Measurement Matrices
Authors: Devendrappa Deepak M. , Palani Karthik , Ananth Deepak N.
Published: December 2022

Introduction::

A more modern, extremely applicable method for signal acquisition is
compression sensing. It permits effective data sampling at a rate that is significantly lower than what
the Nyquist theorem suggests. Compressive sensing has a number of benefits, including a muchreduced
demand for sensory devices, a smaller memory storage need, a greater data transfer rate,
and significantly lower power usage. Compressive sensing has been employed in a variety of applications
because of all these benefits. Neuro-signal acquisition is a domain in which compressive
sensing has applications in the medical industry.

Methods::

The novel methods discussed in this article are FFT-based CoSaMP (FFTCoSaMP),
DCT-based CoSaMP(DCTCoSaMP) and DWT-based CoSaMP (DWTCoSaMP) based on sparse
signal sequences / dictionaries by means of Transform Techniques, where CoSaMP stands for Compressive
Sampling Matching Pursuit with respect to Objective Quality Assessment Algorithms like
PSNR, SSIM and RMSE, where CoSaMP stands for Compressive Sampling Matching Pursuit.

Results:

DWTCoSaMP is giving the PSNR values of 40.26 db, for DCTCoSaMP and FFTCoSaMP,
PSNR is 36.76 db and 34.76 db. For DWTCoSaMP, SSIM value is 0.8164, and for DCTCoSaMP
and FTCoSaMP, SSIM 0.719 and 0.5625 respectively. Finally, for DWTCoSaMP, RMSE value is
0.442, and for DCTCoSaMP and FFTCoSaMP, SSIM 0.44 and 0.4425, respectively.

Conclusion::

Among Compressed sampling techniques DWTCoSaMP, DCTCoSaMP and FFTCoSaMP
discussed in this paper, DWTCoSaMP reveals the best results.
Why Public Sector projects fail or succeed in Pakistan- A model for evaluating impact of HR management practices on Project Success
Authors: Hussain Muhammad Rizwan
Published: December 2022

Employees are the most important assets of an organization. As quality human resources become scarce, companies need to pay more heed to the satisfaction and motivation of their employees. If employees are motivated towards work, then it is likely to yield better results. This study will examine the role of Human resource management (HRM) practices upon New product development (NPD). NPD involves technical, marketing, and financial risks organizations undertake for developing new products and services. Effective project planning and control are valuable for decision-making. The analysis of the impact of HRM practices on NPD, project success, and organizational benefit is based on data collected using a cross-sectional design via a survey questionnaire. The questionnaire consisted of items related to HR practices, New product development, Project Success, and Organizational benefits adapted from previous studies. Respondents working in 10 large-scale public sector projects executed by National Database & Registration Authority, Pakistan were selected for the study. Therefore, the results of the study can be generalized to similar projects executed by the public sector in Pakistan. From the findings of data analysis, it has been concluded that there is a significant association between HR practices and project success, but no significant relationship has been established between new product development and organizational benefit. Therefore, it can be concluded that HR management practices have a significant impact on public sector project success in the case of Pakistan.
The influence of occupational safety and health on work engagement
Authors: Andreine Refrelza El Nisaa , Kusmaryani Rosita Endang , Purwaniningtyas Dyah Ayu
Published: December 2022

This study is conducted based on the phenomenon of low work engagement in companies, the possible one is due to lack of application Occupational Safety and Health (OSH). This paper aims to determine the effect of Occupational Safety and Health (OSH) on work engagement on employees. This research uses a quantitative approach to the type of ex post facto.The sampling technique in this research is purposive sampling and the samples in this research is employee of PT Telkom Access Pugeran Yogyakarta branch, with the scale of 96 employees, 67 male employees and 29 female employees. The instruments of this research used two psychological scales, namely OSH scale and work engagement scale. Analyzed data by using descriptive analysis and simple linear regression analysis. The results of the regression analysis score are 0,000 0,05, it can be concluded that there is a positive influence of Occupational Safety and Health (OSH) on work engagement. The coefficient determination or R Square is 0,498 or 49,8%, meaning that 49,8% of employees work engagement is influenced by OSH, while the remaining 50,2% is influenced by other factors not examined in this study.
Revealing the Roles of Part-of-Speech Taggers in Alzheimer Disease Detection: Scientific Discovery Using One-Intervention Causal Explanation
Authors: Wen Bingyang , Wang Ning , Subbalakshmi Koduvayur , Chandramouli Rajarathnam
Published: December 2022

Background

Recently, rich computational methods that use deep learning or machine learning have been developed using linguistic biomarkers for the diagnosis of early-stage Alzheimer disease (AD). Moreover, some qualitative and quantitative studies have indicated that certain part-of-speech (PoS) features or tags could be good indicators of AD. However, there has not been a systematic attempt to discover the underlying relationships between PoS features and AD. Moreover, there has not been any attempt to quantify the relative importance of PoS features in detecting AD.

Objective

Our goal was to disclose the underlying relationship between PoS features and AD, understand whether PoS features are useful in AD diagnosis, and explore which PoS features play a vital role in the diagnosis.

Methods

The DementiaBank, containing 1049 transcripts from 208 patients with AD and 243 transcripts from 104 older control individuals, was used. A total of 27 PoS features were extracted from each record. Then, the relationship between AD and each of the PoS features was explored. A transformer-based deep learning model for AD prediction using PoS features was trained. Then, a global explainable artificial intelligence method was proposed and used to discover which PoS features were the most important in AD diagnosis using the transformer-based predictor. A global (model-level) feature importance measure was derived as a summary from the local (example-level) feature importance metric, which was obtained using the proposed causally aware counterfactual explanation method. The unique feature of this method is that it considers causal relations among PoS features and can, hence, preclude counterfactuals that are improbable and result in more reliable explanations.

Results

The deep learning–based AD predictor achieved an accuracy of 92.2% and an F1-score of 0.955 when distinguishing patients with AD from healthy controls. The proposed explanation method identified 12 PoS features as being important for distinguishing patients with AD from healthy controls. Of these 12 features, 3 (25%) have been identified by other researchers in previous works in psychology and natural language processing. The remaining 75% (9/12) of PoS features have not been previously identified. We believe that this is an interesting finding that can be used in creating tests that might aid in the diagnosis of AD. Note that although our method is focused on PoS features, it should be possible to extend it to more types of features, perhaps even those derived from other biomarkers, such as syntactic features.

Conclusions

The high classification accuracy of the proposed deep learner indicates that PoS features are strong clues in AD diagnosis. There are 12 PoS features that are strongly tied to AD, and because language is a noninvasive and potentially cheap method for detecting AD, this work shows some promising directions in this field.
The Prevalence, Features, Influencing Factors, and Solutions for COVID-19 Vaccine Misinformation: Systematic Review
Authors: Zhao Sihong , Hu Simeng , Zhou Xiaoyu , Song Suhang , Wang Qian , Zheng Hongqiu , Zhang Ying , Hou Zhiyuan
Published: December 2022

Background

During the COVID-19 pandemic, infodemic spread even more rapidly than the pandemic itself. The COVID-19 vaccine hesitancy has been prevalent worldwide and hindered pandemic exiting strategies. Misinformation around COVID-19 vaccines is a vital contributor to vaccine hesitancy. However, no evidence systematically summarized COVID-19 vaccine misinformation.

Objective

This review aims to synthesize the global evidence on misinformation related to COVID-19 vaccines, including its prevalence, features, influencing factors, impacts, and solutions for combating misinformation.

Methods

We performed a systematic review by searching 5 peer-reviewed databases (PubMed, Embase, Web of Science, Scopus, and EBSCO). We included original articles that investigated misinformation related to COVID-19 vaccines and were published in English from January 1, 2020, to August 18, 2022. We excluded publications that did not cover or focus on COVID-19 vaccine misinformation. The Appraisal tool for Cross-Sectional Studies, version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2), and Critical Appraisal Skills Programme Checklist were used to assess the study quality. The review was guided by PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and registered with PROSPERO (CRD42021288929).

Results

Of the 8864 studies identified, 91 observational studies and 11 interventional studies met the inclusion criteria. Misinformation around COVID-19 vaccines covered conspiracy, concerns on vaccine safety and efficacy, no need for vaccines, morality, liberty, and humor. Conspiracy and safety concerns were the most prevalent misinformation. There was a great variation in misinformation prevalence, noted among 2.5%-55.4% in the general population and 6.0%-96.7% in the antivaccine/vaccine hesitant groups from survey-based studies, and in 0.1%-41.3% on general online data and 0.5%-56% on antivaccine/vaccine hesitant data from internet-based studies. Younger age, lower education and economic status, right-wing and conservative ideology, and having psychological problems enhanced beliefs in misinformation. The content, format, and source of misinformation influenced its spread. A 5-step framework was proposed to address vaccine-related misinformation, including identifying misinformation, regulating producers and distributors, cutting production and distribution, supporting target audiences, and disseminating trustworthy information. The debunking messages/videos were found to be effective in several experimental studies.

Conclusions

Our review provides comprehensive and up-to-date evidence on COVID-19 vaccine misinformation and helps responses to vaccine infodemic in future pandemics.

Trial Registration

PROSPERO CRD42021288929; https://tinyurl.com/2prejtfa
Understanding Why Many People Experiencing Homelessness Reported Migrating to a Small Canadian City: Machine Learning Approach With Augmented Data (Preprint)
Authors: Liyanage Chandreen Ravihari , Mago Vijay , Schiff Rebecca , Ranta Ken , Park Aaron , Lovato-Day Kristyn , Agnor Elise , Gokani Ravi
Published: December 2022

BACKGROUND

Over the past years, homelessness has become a substantial issue around the globe. The largest social services organization in Thunder Bay, Ontario, Canada, has observed that a majority of the people experiencing homelessness in the city were from outside of the city or province. Thus, to improve programming and resource allocation for people experiencing homelessness in the city, including shelter use, it was important to investigate the trends associated with homelessness and migration.

OBJECTIVE

This study aimed to address 3 research questions related to homelessness and migration in Thunder Bay: What factors predict whether a person who migrated to the city and is experiencing homelessness stays or leaves shelters? If an individual stays, how long are they likely to stay? What factors predict stay duration?

METHODS

We collected the required data from 2 sources: a survey conducted with people experiencing homelessness at 3 homeless shelters in Thunder Bay and the database of a homeless information management system. The records of 110 migrants were used for the analysis. Two feature selection techniques were used to address the first and third research questions, and 8 machine learning models were used to address the second research question. In addition, data augmentation was performed to improve the size of the data set and to resolve the class imbalance problem. The area under the receiver operating characteristic curve value and cross-validation accuracy were used to measure the models’ performances while avoiding possible model overfitting.

RESULTS

Factors predicting an individual’s stay duration included home or previous district, highest educational qualification, recent receipt of mental health support, migrating to visit family or friends, and finding employment upon arrival. For research question 2, among the classification models developed for predicting the stay duration of migrants, the random forest and gradient boosting tree models presented better results with area under the receiver operating characteristic curve values of 0.91 and 0.93, respectively. Finally, home district, band membership, status card, previous district, and recent support for drug and/or alcohol use were recognized as the factors predicting stay duration.

CONCLUSIONS

Applying machine learning enables researchers to make predictions related to migrants’ homelessness and investigate how various factors become determinants of the predictions. We hope that the findings of this study will aid future policy making and resource allocation to better serve people experiencing homelessness. However, further improvements in the data set size and interpretation of the identified factors in decision-making are required.
How do medical professionals make sense (or not) of artificial intelligence? A social-media-based computational grounded theory study (Preprint)
Authors: Weber Sebastian , Godefroid Marie , Knop Michael , Plattfaut Ralf , Niehaves Bjoern
Published: December 2022

BACKGROUND

Artificial intelligence (AI) holds tremendous potential for healthcare, as has been demonstrated across various use cases ranging from automated triage to assisted diagnosis. However, the limitations of AI must also be carefully considered in a fact-based debate on optimal use scenarios. In light of the prominent discussion around trust issues with AI, it is important to assess how and what physicians think about the topic in order to avoid general resistance to technology among medical practitioners.

OBJECTIVE

The aim of the present study was to identify key themes in medical professionals’ discussions of AI and to examine these themes for existent perceptions of AI.

METHODS

Using a computational grounded theory approach, 181 Reddit threads in the medical subreddits of r/medicine, r/radiology, r/surgery, and r/psychiatry were analyzed in order to identify key themes. We combined a quantitative, unsupervised machine learning approach for detecting thematic clusters with a qualitative data analysis for gaining a deeper understanding of the perceptions that medical professionals have of AI.

RESULTS

Three relevant key themes – (1) the perceived consequences of AI, (2) perceptions of the physician–AI relationship, and (3) a proposed way forward – emerged from the Reddit analysis. The first and second themes, in particular, were found in posts that appeared to be partially biased toward physicians’ fear of being replaced, toward the physicians’ skepticism of AI, and toward the physicians’ fear that patients may not accept AI. The third theme, however, involves a way forward and consists of factual discussions about how AI and medicine have to develop further in order to lead to the broad adoption of AI as well as to fruitful outcomes for healthcare.

CONCLUSIONS

Many physicians aim to yield the greatest value from AI for their patients and thus engage in constructive criticism of the technology. At the same time, a concerningly large number of physicians demonstrate perceptions that appear to be at least partially biased and that could hinder both successful use-case implementation and societal acceptance of AI in the future. Therefore, such biased perceptions need to be monitored and – where possible – countered.
Tensorial Principal Component Analysis in Detecting Temporal Trajectories of Purchase Patterns in Loyalty Card Data: Retrospective Cohort Study (Preprint)
Authors: Autio Reija , Virta Joni , Nordhausen Klaus , Fogelholm Mikael , Erkkola Maijaliisa , Nevalainen Jaakko
Published: December 2022

BACKGROUND

Loyalty card data automatically collected by retailers provide an excellent source for evaluating health-related purchase behavior of customers. The data comprise information on every grocery purchase, including expenditures on product groups and the time of purchase for each customer. Such data where customers have an expenditure value for every product group for each time can be formulated as 3D tensorial data.

OBJECTIVE

This study aimed to use the modern tensorial principal component analysis (PCA) method to uncover the characteristics of health-related purchase patterns from loyalty card data. Another aim was to identify card holders with distinct purchase patterns. We also considered the interpretation, advantages, and challenges of tensorial PCA compared with standard PCA.

METHODS

Loyalty card program members from the largest retailer in Finland were invited to participate in this study. Our LoCard data consist of the purchases of 7251 card holders who consented to the use of their data from the year 2016. The purchases were reclassified into 55 product groups and aggregated across 52 weeks. The data were then analyzed using tensorial PCA, allowing us to effectively reduce the time and product group-wise dimensions simultaneously. The augmentation method was used for selecting the suitable number of principal components for the analysis.

RESULTS

Using tensorial PCA, we were able to systematically search for typical food purchasing patterns across time and product groups as well as detect different purchasing behaviors across groups of card holders. For example, we identified customers who purchased large amounts of meat products and separated them further into groups based on time profiles, that is, customers whose purchases of meat remained stable, increased, or decreased throughout the year or varied between seasons of the year.

CONCLUSIONS

Using tensorial PCA, we can effectively examine customers’ purchasing behavior in more detail than with traditional methods because it can handle time and product group dimensions simultaneously. When interpreting the results, both time and product dimensions must be considered. In further analyses, these time and product groups can be directly associated with additional consumer characteristics such as socioeconomic and demographic predictors of dietary patterns. In addition, they can be linked to external factors that impact grocery purchases such as inflation and unexpected pandemics. This enables us to identify what types of people have specific purchasing patterns, which can help in the development of ways in which consumers can be steered toward making healthier food choices.

CLINICALTRIAL
Звернення головного редактора
Authors: Nikonov V.V.
Published: December 2022

No abstract
Досвід застосування імуноглобуліну людини нормального у пацієнтів з вогнепальними пораненнями та сепсисом
Authors: Horoshko V.R. , Buhayi O.O.
Published: December 2022

Пацієнти з вогнепальними пораненнями та сепсисом належать до числа найтяжчих — летальність у таких пацієнтів становить близько 30 %. Частота вогнепальних поранень становить 54–70 %. Такі пацієнти характеризуються розвитком синдрому вторинного імунодефіциту, тому потребують особливого підходу до корекції лікувальних призначень, а також призначення імуноглобуліну людини нормального, що потенційно може покращити результати їхнього лікування.
Ендоваскулярне лікування варикозно розширених вен шлунка під контролем ендосонографії
Authors: Chooklin S.M. , Chuklin S.S. , Posivnych M.M. , Krystopchuk S.A.
Published: December 2022

Шлункова варикозна кровотеча супроводжується високою летальністю. Ендоскопічна ін’єкція ціаноакрилату є стандартною терапією, однак рецидивна кровотеча та побічні ефекти, такі як виразки в місці ін’єкції та дистальна емболія, є підводним каменем цієї терапії. Ендоскопічне лікування варикозного розширення вен шлунка під ендосонографічним контролем має кілька можливих переваг перед сучасними методами лікування. Воно дозволяє детально оцінити анатомію судин, подібну ефективність і безпеку поточних методів лікування, а також дає змогу оцінити ефект лікування за допомогою ультразвукової допплерівської візуалізації. Ми розглядаємо методи лікування варикозного розширення вен шлунка, включаючи ендоскопічну ін’єкцію ціаноакрилату та спіралей під контролем ендосонографії, окремо або в комбінації, ін’єкцію тромбіну та желатинової губки, що розсмоктується. Відповідний відбір пацієнтів для цих процедур має першорядне значення для забезпечення отримання корисних клінічних даних і безпеки пацієнтів. Ми шукали літературу в базі даних MedLine на платформі PubMed.
The role of social media in optimizing the healthy lifestyle movement “GERMAS” during the COVID-19 pandemic
Authors: Baiquni Fahmi , Siswati Tri , Rachmawati Riadini , Widyawati Herni Endah , Wardhani Ratri Kusuma , Supriyati Supriyati
Published: December 2022

The Coronavirus Disease (COVID-19) demands community participation to overcome the spread of the pandemic. The social movement such as the healthy lifestyle movement (GERMAS) plays an important role to break the chain of COVID-19 transmission. Meanwhile, the infodemic of false news has caused misinformation and disinformation. Raising the community’s health literacy will lead people to participate in the GERMAS social movement. This study aimed to explore the use of social media to improve health literacy concerning the healthy lifestyle social movement called “GERMAS”. This research was conducted in Yogyakarta by reviewing related documents and literature, and collecting primary data. Primary data collection was done through online surveys, focus group discussions, and an in-depth interview. There were 461 respondents, with 449 respondents who filled out online surveys, 11 people who participated in the focus group discussions, and 1 person who was interviewed. The study showed that WhatsApp was the most widely accessed source of information about COVID-19 (83%) and health protocols (82%) after television. In addition, WhatsApp has become the main source of information about GERMAS (73%). The credible source of information was very important to help the community during the COVID-19 pandemic and the ‘false news’ infodemic. Various stakeholders provided information related to the COVID-10 and how to prevent the spread of the virus. In addition, Yogyakarta health officers developed a communication network through WhatsApp groups from the provincial to sub-district/village levels (community leaders) that were used to share information on a regular basis to the public. Additionally, community leaders were able to ask health officers questions related to COVID-19 issues and prevention.  Unfortunately, the lack of “think tanks”, and bureaucratic ties made this network unable to function optimally. In conclusion, social media has an important role in optimizing the GERMAS program during the COVID-19 pandemic. Social media management and good cooperation between the government and private agencies are important keys for optimizing GERMAS during the COVD-19 pandemic era.
Improved completing-treatment support among tuberculosis support group members through the CERMAT (Smart Against TB Transmission) program
Authors: Nursasi Atuti Yuni , Rohana I Gusti Ayu Putu Desy , Rachmawati Utami , Mulyana Rezky
Published: December 2022

Tuberculosis (TB) was declared a global emergency for humanity by the World Health Organization in 2015. According to Global Report TB data in 2016, Indonesia is one of the 30 countries in the world that has the highest TB caseload, especially Human Immunodeficiency Virus (HIV)-TB and (Multi Drug Resistant Tuberculosis (MDR) TB) cases during the 2016-2020 period (Global Tuberculosis Report, 2016). The high rise of MDR TB cases has great potential for transmission and an increase in the number of new TB cases. Efforts to optimize the handling of care and treatment, as well as to accelerate the determination of the diagnosis need to be conducted vigilantly on all lines, especially efforts to increase the ability to prevent transmission, provide quality follow-up care, and community-based treatment. Forming support groups is one of community health nursing strategies for TB prevention. A support group provides assistance to increase TB medication adherence and reduce TB transmission. TB control strategies are conducted by implementing CERMAT (Smart Against TB Transmission) to TB support groups that combine education intervention and skills to prevent TB transmission in the community setting. Community health nursing though the nursing process has established a system with recognition of the variables that affect health status and individual behaviors against TB disease. The nursing strategy intervention in the community is done at all levels, such as health education, group process, partnership, and community empowerment. The CERMAT package implemented in the TB support group is an evidence-based nursing practice. It was applied to 70 samples of adult TB clients at Curug, Cimanggis, Depok. The sampling was selected with a non-probability quota sampling technique. This study used an experimental design with paired t-test data analysis to determine the improvement in the skills of the TB support group after the support group intervention was done. It showed there was influence of the CERMAT method on the level of good support for completing TB treatment in Curug Village, with increased the mean of completed treatment by 2.42 with a p value 0.00 (p <0.05). The CERMAT method can be applied as one of the nursing interventions to increase TB clients’ adherence. This intervention can be done by the person who is responsible for the TB program at the Community Health Center. The CERMAT method needs to be continued and evaluated regularly by involving health care volunteers.
WhatsApp-based complementary feeding education and counselling for adolescent mothers: A one-group pre-post study
Authors: Muthi'ah Tisa Salma , Ahmad Riris Andono , Purwaningrum Digna Niken
Published: December 2022

More than two-thirds of deaths in children are related to improper feeding practices, especially in adolescent mothers, with very low levels of complementary feeding knowledge, less responsiveness, and few skills of proper feeding practices.  The area of Banguntapan III Public Health Center (PHC) has the highest prevalence of adolescent mothers in 2018-2019. The aim of this study was to evaluate the effect of WhatsApp-based complementary feeding education and counseling for adolescent mothers who have children aged 6-24 months at Banguntapan III PHC on complementary feeding knowledge and practice. A quasi-experimental with one group pre-post test was conducted (n=10 adolescent mothers) on February-May 2021 at the Banguntapan III PHC area. The education program was conducted by trained cadres for 8 days through the WhatsApp group, then followed by asynchronous counseling once through WhatsApp private chat. Change of outcome was tested using independent sample T-test and McNemar test. The range of adolescent mothers’ age in this study was 19-20 years, with education level of junior high school (50%), and do not work (80%). The results showed that WhatsApp-based education and counselling had a significant effect on increasing the adolescent mother's IYCF knowledge (Δ = 1.1 ± 2.28) with a p-value of 0.017 < a (0.05). Meanwhile, the effect of the intervention on the IYCF practice by adolescent mothers was not significant, with a p-value of 0.311 > a (0.05). In conclusion, WhatsApp-based education and counselling for adolescent mothers can increase their level of complementary feeding knowledge, but was not been able to improve their feeding practices for infants/children aged 6-24 months.
“EmosiAn”: An android-based application for handling students with mild depression in MAN 1 Yogyakarta
Authors: Auladwasasyah Janneta Filza , Rahmanita Ika , Priska Hersa Ajeng , Nasution Nasution , Fakhry Alwan Nur , Jamil Nur Aisyah
Published: December 2022

Stressors from school and inappropriate friendships could lead to depression among teenagers, and possibly to attempts at suicide if not treated properly. To meet this need, there is a peer counsellor service, which is an extracurricular activity at school, called the Centre for Youth Information and Counseling / Pusat Informasi dan Konseling Remaja (PIK-R) Exalta. However, only a few students have used this service. This was due to a situational barrier that happened in direct counselling. This study aimed to detect mild depression and evaluate the implementation of the EmosiAn application (app) in handling mild depression among students. This study used secondary data from Program Kreativitas Mahasiswa Pengabdian Masyarakat (PKM-M)/ Student Creativity Program-Community Services conducted from Augustus to October 2020 at MAN 1 Yogyakarta. A total of 126 students voluntarily filled out the Patient Health Questionnaire-9 (PHQ-9), and 47 (37.3%) showed mild depression. Among 27 students and 5 peer counsellors then agreed to participate. The EmosiAn app was designed based on their problems, and had two interfaces for the administrator (peer counsellor) and the user (student). The app contained a diagnosis of depression using PHQ-9, daily journal, chat and reading the relevant articles. Before using the app, both peer counsellors and students attended zoom-online training. There was an increase in peer counsellors' knowledge (p=0.000) and students (p= 0.002) before and after the webinar. All participants could use the EmosiAn app and felt its benefits after two weeks of implementation. There were 40% of students who experienced a reduction of their depression level. Problems encountered during its usage could be resolved by fixing and refining the app. EmosiAn is a user-friendly application used by PIK-R Exalta to detect and care for students with mild depression. Further development is needed for wider used in the future.
Differences in obesity between the groups consuming snacks and breakfast habits in Universitas Islam Negeri Sumatera Utara Medan
Authors: Utami Tri Niswati , Andayani Lita Sri , Eliska Eliska , Susilawati Susilawati , Aidha Zuhrina , Harahap Reni Agustina
Published: December 2022

Overweight and obesity are increasing in Indonesia, and these conditions pose a growing threat to people with non-communicable diseases. This study aimed to show the difference in obesity among respondents who consume snacks compared to respondents who have the habit of eating breakfast with three choices to select from: always, sometimes, or never. This comparison was done to analyze the relationship between breakfast habits and snack consumption. This cross-sectional study collected data using a survey on 26 – 27 November 2021. The sample population included the entire academic community of the Universitas Islam Negeri Sumatera Utara, Medan. The sample was determined by an accidental sampling technique. Research instruments were used in the form of questionnaires, microtoise and weight scales to measure the anthropometrics of height and weight. Descriptive data analysis used normality tests and because the data were not normally distributed, the Kendall and Kruskal Wallis tests were done. The results of this study indicated that 38 respondents have overweight status (17.9%), 36 respondents (17.0%) obesity I, 18 respondents (8.5%) obesity II, and 26 respondents (12.3%) underweight. There was no significant difference in obesity among respondents who have the habit of eating breakfast always, sometimes, and never, with p-value of 0.793.There was a significant difference in obesity among respondents who have the habit of eating snacks never, sometimes, and always with a p-value of 0.014. Although snacking can sometimes lead to obesity, generally the fatting types of snacks consumed are cakes and fried foods. In conclusion, limiting snack foods such as cakes and fried foods can reduce obesity. It is recommended to replace the consumption of these snacks with fruits and vegetables.
The Effectiveness of Stingless Bees on Pollination of Bitter Melon Plants Momordica charantia L. (Cucurbitaceae)
Authors: Suhri Andi Gita Maulidyah Indraswari , Soesilohadi RC Hidayat , Putra Ramadhani Eka , Raffiudin Rika , Purnobasuki Hery , Agus Ali , Kahono Sih
Published: December 2022

This study aimed to measure the effectiveness of stingless bee Tetragonula cf. biroi pollination on the fruit formation of bitter melon Momordica charantia plants. We used hoods on the observed bitter melon plants. In the first hood, stingless bees are inserted to help pollinate 100 bitter melon plants, while in the other hoods, stingless bees are not inserted so that there is no assistance in pollinating the other 100 bitter melon plants. The method used is the focal sampling method for 25 days of observation. Based on the results of the study, stingless bee pollination assistance increased the percentage of the number of flowers that became fruit by 390%, the weight of seeds/fruit by 64%, number of seeds/fruit by 260%, fruit weight by 163%, fruit diameter by 91%, and fruit length by 86%. In addition to the size of the fruit, the shape of the bitter melon pollinated by bees is standard (long and straight). In contrast, the bitter melon that does not get pollination assistance grows with a bent shape resembling the letter "C." Bitter melon is an agricultural commodity that needs pollinating agents such as stingless bees because of its monoecy.