bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of Automated Thematic Annotations for Small Data Sets in a Psychotherapeutic Context: Systematic Review of Machine Learning Algorithms
Authors: Hudon Alexandre , Beaudoin Mélissa , Phraxayavong Kingsada , Dellazizzo Laura , Potvin Stéphane , Dumais Alexandre 
Published: July 2021

Background
A growing body of literature has detailed the use of qualitative analyses to measure the therapeutic processes and intrinsic effectiveness of psychotherapies, which yield small databases. Nonetheless, these approaches have several limitations and machine learning algorithms are needed.

Objective
The objective of this study is to conduct a systematic review of the use of machine learning for automated text classification for small data sets in the fields of psychiatry, psychology, and social sciences. This review will identify available algorithms and assess if automated classification of textual entities is comparable to the classification done by human evaluators.

Methods
A systematic search was performed in the electronic databases of Medline, Web of Science, PsycNet (PsycINFO), and Google Scholar from their inception dates to 2021. The fields of psychiatry, psychology, and social sciences were selected as they include a vast array of textual entities in the domain of mental health that can be reviewed. Additional records identified through cross-referencing were used to find other studies.

Results
This literature search identified 5442 articles that were eligible for our study after the removal of duplicates. Following abstract screening, 114 full articles were assessed in their entirety, of which 107 were excluded. The remaining 7 studies were analyzed. Classification algorithms such as naive Bayes, decision tree, and support vector machine classifiers were identified. Support vector machine is the most used algorithm and best performing as per the identified articles. Prediction classification scores for the identified algorithms ranged from 53%-91% for the classification of textual entities in 4-7 categories. In addition, 3 of the 7 studies reported an interjudge agreement statistic; these were consistent with agreement statistics for text classification done by human evaluators.

Conclusions
A systematic review of available machine learning algorithms for automated text classification for small data sets in several fields (psychiatry, psychology, and social sciences) was conducted. We compared automated classification with classification done by human evaluators. Our results show that it is possible to automatically classify textual entities of a transcript based solely on small databases. Future studies are nevertheless needed to assess whether such algorithms can be implemented in the context of psychotherapies.
Identifying Enablers of Participant Engagement in Clinical Trials of Consumer Health Technologies: Qualitative Study of Influenza Home Testing
Authors: Dharanikota Spurthy , LeRouge Cynthia M , Lyon Victoria , Durneva Polina , Thompson Matthew 
Published: July 2021

Background
A rise in the recent trend of self-managing health using consumer health technologies highlights the importance of efficient and successful consumer health technology trials. Trials are particularly essential to support large-scale implementations of consumer health technologies, such as smartphone-supported home tests. However, trials are generally fraught with challenges, such as inadequate enrollment, lack of fidelity to interventions, and high dropout rates. Understanding the reasons underlying individuals’ participation in trials can inform the design and execution of future trials of smartphone-supported home tests.

Objective
This study aims to identify the enablers of potential participants’ trial engagement for clinical trials of smartphone-supported home tests. We use influenza home testing as our instantiation of a consumer health technology subject to trial to investigate the dispositional and situational enablers that influenced trial engagement.

Methods
We conducted semistructured interviews with 31 trial participants using purposive sampling to facilitate demographic diversity. The interviews included a discussion of participants’ personal characteristics and external factors that enabled their trial engagement with a smartphone-supported home test for influenza. We performed both deductive and inductive thematic analyses to analyze the interview transcripts and identify enabler themes.

Results
Our thematic analyses revealed a structure of dispositional and situational enablers that enhanced trial engagement. Situationally, clinical affiliation, personal advice, promotional recruitment strategies, financial incentives, and insurance status influenced trial engagement. In addition, digital health literacy, motivation to advance medical research, personal innovativeness, altruism, curiosity, positive attitude, and potential to minimize doctors’ visits were identified as the dispositional enablers for trial engagement in our study.

Conclusions
We organized the identified themes for dispositional and situational enablers of trial engagement with a smartphone-supported home test into a research framework that can guide future research as well as the trial design and execution of smartphone-supported home tests. We suggest several trial design and engagement strategies to enhance the financial and scientific viability of these trials that pave the way for advancements in patient care. Furthermore, our study also offers practical strategies to trial organizers to enhance participants’ enrollment and engagement in clinical trials of these home tests.
Moderation of the Stressor-Strain Process in Interns by Heart Rate Variability Measured With a Wearable and Smartphone App: Within-Subject Design Using Continuous Monitoring
Authors: de Vries Herman , Kamphuis Wim , Oldenhuis Hilbrand , van der Schans Cees , Sanderman Robbert 
Published: July 2021

Background
The emergence of smartphones and wearable sensor technologies enables easy and unobtrusive monitoring of physiological and psychological data related to an individual’s resilience. Heart rate variability (HRV) is a promising biomarker for resilience based on between-subject population studies, but observational studies that apply a within-subject design and use wearable sensors in order to observe HRV in a naturalistic real-life context are needed.

Objective
This study aims to explore whether resting HRV and total sleep time (TST) are indicative and predictive of the within-day accumulation of the negative consequences of stress and mental exhaustion. The tested hypotheses are that demands are positively associated with stress and resting HRV buffers against this association, stress is positively associated with mental exhaustion and resting HRV buffers against this association, stress negatively impacts subsequent-night TST, and previous-evening mental exhaustion negatively impacts resting HRV, while previous-night TST buffers against this association.

Methods
In total, 26 interns used consumer-available wearables (Fitbit Charge 2 and Polar H7), a consumer-available smartphone app (Elite HRV), and an ecological momentary assessment smartphone app to collect resilience-related data on resting HRV, TST, and perceived demands, stress, and mental exhaustion on a daily basis for 15 weeks.

Results
Multiple linear regression analysis of within-subject standardized data collected on 2379 unique person-days showed that having a high resting HRV buffered against the positive association between demands and stress (hypothesis 1) and between stress and mental exhaustion (hypothesis 2). Stress did not affect TST (hypothesis 3). Finally, mental exhaustion negatively predicted resting HRV in the subsequent morning but TST did not buffer against this (hypothesis 4).

Conclusions
To our knowledge, this study provides first evidence that having a low within-subject resting HRV may be both indicative and predictive of the short-term accumulation of the negative effects of stress and mental exhaustion, potentially forming a negative feedback loop. If these findings can be replicated and expanded upon in future studies, they may contribute to the development of automated resilience interventions that monitor daily resting HRV and aim to provide users with an early warning signal when a negative feedback loop forms, to prevent the negative impact of stress on long-term health outcomes.
CRISPR/Cas, el sistema premiado con el Premio Nobel de Química 2020 ¿Cómo funcionan las Tijeras Moleculares?
Authors: Palacios-Arreola Margarita Isabel , Huerta-Lavorie Raúl 
Published: July 2021

<p>Se presenta una hoja didáctica para apoyar a los profesores en la difusión del conocimiento de la tecnología alrededor del sistema CRISPR/Cas, conocido coloquialmente como <em>Tijeras moleculares</em> y su relevancia en la edición del genoma a estudiantes nivel medio, medio superior o universitario. Esto se realiza en un contexto que permite introducir y revisar conceptos, modelos y metodologías bioquímicas, así como de biología molecular, relacionados con la ingeniería genética. Asimismo, la historia del descubrimiento del sistema, el desarrollo de la tecnología para sus aplicaciones y el Premio Nobel al que fueron acreedoras dos de las investigadoras involucradas constituyen un contexto perfecto para fomentar la reflexión acerca del carácter colaborativo de la ciencia y la frontera entre la llamada ciencia básica y ciencia aplicada.</p>
PEMBERDAYAAN MASYARAKAT DI MASA PANDEMI MELALUI PERTANIAN ORGANIK DI LAHAN PEKARANGAN KAWASAN PERKOTAAN JAWA BARAT
Authors: Karyani Tuti , Djuwendah Endah , Sukayat Yayat 
Published: July 2021

Masa pandemi covid-19 merupakan masa dimana lebih banyak menggunakan waktu di rumah, untuk menghindari terpaparnya virus tersebut. Pemanfaatan waktu ini bisa digunakan secara positif dengan memanfaatkan lahan pekarangan yang ditanami sayuran, tabulampot dan tanaman hias secara organik. Kondisi ini menjadi menarik sebagai topik pengabdian pada masyarakat (PPM) yang dikemas dalam Pengabdian Masyarakat terintegrasi dengan KKN Mahasiswa. Oleh karena itu metode yang digunakan adalah metode blended antara daring (virtual) dan sebagian kecil luring dengan protokol kesehatan yang ketat. Sasaran (mitra) PPM adalah yang bisa menguasai smartphone atau laptop, sehingga terjaring mitra (sasaran) adalah golongan masyarakat yang usianya muda dan berpendidikan SMA serta mahasiswa yang hobby bertani. Mitra mahasiswa KKN berdomisili di sekitar tempat tinggal mahasiswa yaitu di perkotaan dan menyebar di beberapa kota Jawa Barat. Materi yang diberikan ialah tentang pertanian organik, pembuatan pupuk organik nabati, pupuk organik cair, pembuatan pestisida organik dan aplikasi pemanfaatan pekarangan dengan usaha tani bunga telang organik. Pada saat pre-test tingkat pengetahuan sebagian besar sudah tinggi namun tingkat keterampilan masih rendah, namun setelah diberikan pelatihan terjadi perubahan semua aspek baik pengetahuan, sikap dan keterampilan meningkat.
DIFUSI KEBIJAKAN KETERBUKAAN INFORMASI PUBLIK DI KABUPATEN BANDUNG BARAT
Authors: Bahtiar Rochmat , Alexandri Mohammad Benny , Candradewini Candradewini 
Published: July 2021

Penelitian ini dilakukan untuk mengetahui bagaimana Pemerintah Kabupaten Bandung Barat menerapkan kebijakan Keterbukaan Informasi Publik melalui mekanisme difusi kebijakan. Empat mekanisme utama difusi kebijakan yaitu, pembelajaran, persaingan, peniruan dan pemaksaan yang telah dilakukan oleh Pemerintah Kabupaten Bandung Barat akan dipaparkan melalui metode penelitian kualitatif deskriptif. Dengan begitu dapat secara eksplisit dapat terlihat berbagai upaya yang dilakukan dalam menentukan pilihan kebijakan yang dipengaruhi oleh penerapan kebijakan serupa yang dilakukan oleh Pemerintah Daerah lain. The study was conducted to see how the Government of Bandung Barat District implemented the Public Information Disclosure policy through policy diffusion mechanism. The four main mechanism of policy diffusion, namely, learning, competition, imitation and coercion that have been carried out by the Government of Bandung Barat District will be presented through descriptive qualitative research methods. In this way, it can be seen explicitly from the various policies made in determining policy choices that can be based on policies taken by other local governments.
EMPOWERMENT STRATEGY OF VILLAGE COMMUNITY BASED ON FRESHWATER AQUACULTURE
Authors: Hidayati Dewi Ayu , Kartika Tina , Muhassin Mohammad 
Published: July 2021

Community empowerment is how to make people have the ability and independence in utilizing the existing potentials. In Banding Agung Village, Pesawaran Lampung, the abundant water resources available can be used for freshwater aquaculture activity as a strategy for empowering the community. The study aims to explore the strategies of community empowerment based on freshwater aquaculture activity, and to find out the factors inhibiting the community empowerment. This is a kind of descriptive qualitative research using case study framework. The data were collected through in-depth interviews, observation, and documentation and analyzed qualitatively employing data reduction, data display, and data verification. The findings indicated that some strategies have been implemented in empowering the community based on the freshwater aquaculture activity, consisting of building the community awareness on the importance of fish farming group (pokdakan), building institutional capacity through education, training and workshop of fish farming management, and putting group members’ knowledge and skill into practice. In the implementation of the strategies, some obstacles were found as the factors inhibiting the community empowerment, namely lack of community participation, lack of knowledge and capital, minimum assistance and counseling, and less involvement of the village government. The study recommends several alternative actions for a better implementation of the community empowerment.
Is Bigger Better? The Impact of the Size of Banks on Credit Ratings
Authors: Chodnicka-Jaworska Patrycja 
Published: July 2021

Abstract
The aim of the paper was to analyse the factors influencing European banks’ credit ratings by taking into account the size of these institutions. A literature review onthe indicators that can impact bank notes has been made. As a result, the following hypotheses have beendrawn:banks’ capital adequacy, profitability, liquidity and management quality have a significant influence on bank credit ratings. Bigger banks receive higher credit ratings than the smaller ones in similar financial conditions. To verify the presented hypotheses ordered logit panel data models have been used. The analysis has been prepared by using the quarterly data from the Thomson Reuters database for the period between 1998 to 2015. The European banks’ long-term issuer credit ratings proposed by S&P, Fitch and Moody are used as dependent variables. The sample has been divided into subsamples according to the size of a bank andbanking sector and capitalization.
Comparing Digital Finance in the UK, US, India and Nigeria
Authors: Ozili Peterson K. 
Published: July 2021

Abstract
This paper examines digital finance usage in the UK, US, India and Nigeria. Using data from the global financial development indicators, the findings reveal that the UK and US have higher digital finance usage than India and Nigeria. The US has higher credit card usage compared to the UK while the UK has higher debit card usage compared to the US. Also, Nigeria has higher debit card usage than India. The findings also show that higher debit card usage is correlated with higher domestic credit to the private sector in the US and Nigeria. Higher credit card usage is correlated with lower domestic credit to the private sector, lower private credit by deposit money banks, and fewer remittances to the UK. The implication of the findings is that policy makers in developing countries should develop the digital finance and payment systems in their countries to close up the wide gap in digital finance adoption between developing and developed countries.
The Crypto Effect on Cross Border Transfers and Future Trends of Cryptocurrencies
Authors: Uyduran Burak 
Published: July 2021

Abstract
This paper presents a theoretical and empirical outlook on different aspects of various cryptocurrencies, blockchain technology including the evolution of digital tokens and how they widely affect the financial markets, organizations, banks, governments via analyzing the characteristics and current history of cryptocurrencies alongside with blockchain technology. The choice of this topic was motivated by the fact that the virtual money concept and blockchain technology are utterly new phenomena. This new technology is completely decentralized making the subject worthy of scientific research.The paper solely focuses on analyzing how cryptocurrencies currently affect the financial markets and the future trends of these virtual tokens in the global economy. The study is keen to further examine the impact of Bitcoin and other cryptocurrencies on international fund transfers. Literature review and case study with up-to-date data has been included in the analysis. The following results have been obtained: cryptocurrencies offer a wide range of features such as faster, cheaper and more secure cross-border money transfers that can also provide anonymity. Most crypto tokens are highly volatile due to their nature and various other factors. Cryptocurrencies could provide more beneficial options for users on cross border transfers compared to traditional methods of fund transfers. Cryptocurrencies might have the potential to replace paper money and gain mainstream recognition throughout the world. The study sheds light onto current and future trends of cryptocurrencies and blockchain. It is outlined for the crypto, financial, economic field.
Work Life Balance and Service Delivery Among Women Entrepreneurs in South-Western Nigeria
Authors: Kuranga Mutiat Oyinlola 
Published: July 2021

Abstract
Businesses in the twenty first century are characterized by persistent changes, uncertainties and undue pressure to meet demands and increase productivity. For women entrepreneurs, they are expected to combine this with the statutory responsibility of taking care of their children, families and home front. Managing these different roles and responsibilities usually influences the business performance and family life and may impact their service delivery. Hence, the study examined the impact of work-life balance on service delivery among women entrepreneurs in south-western Nigeria. A total of 379 respondents were selected from a population of 25,122 members of the Nigeria union of tailors in Lagos, Oyo and Osun state using multistage sampling techniques. Primary data was collected through the use of a structured self-administered questionnaire and a structural equation model (SEM- PLS) was adopted for the analysis. The result shows work demands, wellbeing, family workload and spousal support with coefficients 0.219, 0.101, 0.061 and 0.563. The study also found that every unit change of work-life balance would lead to a 0.792 unit change in service delivery. Therefore, the study concludes that work-life balance contributes significantly to the service delivery of women entrepreneurs. The study recommends that women entrepreneurs should effectively manage their work and family roles, ensure creativity and flexibility in their work domains and seek support to enable them to deliver efficient service and achieve overall performance in their business.
A note on: A early warning system for market inefficiency
Authors: Habibi Reza 
Published: July 2021

Abstract
Violation of the efficient market hypothesis (EMH) in a specific market may lead to construction of bubbles which is a signal of inefficiencies. Although speculative bubbles soon decay, if they exist for a long time, they will lead to financial crises. Early warning systems (EWSs) are designed to quickly alert the market to crises. Under EMH, the logarithm of price is a martingale process. Thus, it is necessary to use a suitable EWS tool for violation of martingale properties of the logarithm of asset prices. In this paper, using the auto-regressive (ARTA) models, and assuming Markov structure between financial random variables, the conditional means are formulated as a simple regression. Then, using the recursive formula for least square estimates of regression parameters, the hypothesis of variables being martingale is tested. This approach leads to a probability index which serves as an EWS. Then, throughout two real data sets, it is seen that the results of the study are applicable to construct EWS for detecting stock market crashes as well as exchange rate market crises. A discussion section is proposed. Finally, based on these results, conclusions are given.
Historical Definition and Theoretical Background of Usury Loan Provisions
Authors: Chlumská Zuzana 
Published: July 2021

Abstract
The thesis deals with usury and illegal lenders both on the domestic scene and abroad. The usury itself is defined by its characteristics, by adjudication and by historical connotations. The historical definition begins in Mesopotamia and ancient Rome, basically since the emergence of money. The aim of the paper is a comprehensive overview of usury, which from the legal perspective is not precisely defined as a term and the thesis tries to find such a definition with the help of case law and interpretation. The characteristics of usury that are described in the thesis are distress, the presence of a weaker party, mental weakness, and a gross disparity of performance. The thesis also describes the history of loan sharks and usury in the United States, where violence plays a considerable part in the issue. The paper also deals with the social background of usury and illegal lenders in the United Kingdom and outlines possible solutions to eradicate these phenomena in financially disadvantaged communities. In the end the thesis attempts to find unifying characteristics of usury across history and said countries.
Comprehensive Analysis of a Company's Activity by Means of Statistical Modeling as Support for its Decision-Making System
Authors: Soboń Janusz , Burkina Natalia , Sapun Kostiantyn , Seleznova Ruslana 
Published: July 2021

Abstract
An important role in ensuring effective forms of management and increasing competitiveness is played by the process of forecasting the activity of the enterprise. This work analyzed the performance of a food industry enterprise, for which a wide range of statistical methods were applied such as methods of cluster, correlational and regression analysis, statistical tests of Fisher, Student, Farrar-Glauber, Durbin-Watson, Goldfeld-Quandt, μ-criterion, multifactor regression, trend, auto-regression models, and models of seasonal fluctuations, which provided a view of the economic properties of the enterprise profit process, in particular the auto-regression component of revenue dependence on its value last year, seasonal quarterly dependence on sales and marketing costs, product price, etc. The detected patterns will allow us to take into account these features for forecasting future revenues and for adjusting the enterprise’s decision-making system taking into account seasonal features and results of the previous year.