bluuebunny/crossref_metadata_2025 huggingface dataset:
On the History of the Study of Ancient Greek in Russia in the 19th Century: Hesiod’s Poems for Students in Autograph Manuscripts of K. F. Grossheinrich
Authors:   Institute of World History of the Russian Academy of Sciences, Shchegoleva Ludmila I.
Published: October 2024

This paper deals with the Russian classical philologist, teacher and translator of German origin Karl Friedrich Grossheinrich and with his works on the adaptation of Hesiod’s poems “Theogony” and “Works and Days” for students. Brief information is given on the methodology of teaching foreign languages by Grossheinrich and on the method of using adapted texts for reading ancient Greek epic poetry discovered by him. The Greek text of Hesiod’s poems is analyzed in detail in Grossheinrich’s autographs from the manuscripts of the Russian State Library RSL F. 201 no. 30 and RSL F. 201 no. 31. It is established that the manuscripts contain adapted text intended for students. The methods of text editing with the help of which Attic forms are substituted for Homeric ones are revealed. The source of the Latin translation of Hesiod’s poems in Grossheinrich’s autographs is established. The adapted Greek text is compared with the editions of Hesiod’s poems, and the variae lectiones are analyzed. Information is given about the entry of Grossheinrich’s manuscripts in the unpublished part of the catalog of A. S. Norov’s library. The significance of Grossheinrich’s manuscripts is established: It is believed to be a gift to the Minister of Public Education A. S. Norov — in the light of the controversy around the need for classical education in Russia in the 19th century. In the Appendices there are: (1) an excerpt from the “Theogony” according to the manuscript RSL F. 201 no. 30, (2) examples of Grossheinrich’s text editing of Hesiod’s poems, (3) Russian translation of Horace’s ode revised by Grossheinrich and dedicated by him to A. S. Norov, and (4) the accompanying letter of K. F. Grossheinrich to A. S. Norov, 1857, April 10, in French, with Russian translation.
Economic analysis of the institution of judicial expenses as a factor of the effectiveness of justice
Authors:   Supreme Court of the Russian Federation, Momotov Viktor V.
Published: October 2024

The paper examines the institute of court costs and possible ways of its improvement. The compensatory and preventive functions of this institution are highlighted, and the inadmissibility of reducing the effectiveness of justice only to its accessibility is substantiated. It is noted that the low cost of court proceedings violates the balance between the various criteria of the effectiveness of justice. With this in mind, the author considers the regulation of the institute of court costs in modern Russia in two key aspects: firstly, in terms of the reasonableness of the rates of state duty for applying to court; secondly, in terms of the validity of the rules of reimbursement of expenses for payment for the services of representatives. Based on the results of the analysis of the state duty rates, the conclusion is formulated that at the current rates the state duty has lost its economic sense and is unable to fulfil its preventive function. The author emphasises that the rates of state duty have remained unchanged for many years, despite a significant increase in the average per capita income of population and a high level of accumulated inflation. Taking this into account, it is proposed to determine the procedure for regular revision of the amount of state duty, to differentiate its rates for individuals and legal entities, as well as for different courts. As a possible reference point for legislative changes, the German model is considered, which assumes the calculation of the amount of state duty in two stages. As part of the analysis of the rules of reimbursement of expenses for payment for the services of representatives, it is noted that they are of an evaluative nature and, as a result, the courts systematically reduce the amount of expenses charged by the courts. Two cases considered by the Judicial Collegium for Civil Cases of the Supreme Court of the Russian Federation are cited as examples. The main direction of the reform of the institute of court costs in this part, in the author’s opinion, should be the narrowing of discretionary powers of judges. A point of view is expressed that the reasonableness (disproportionality) of court costs should be understood not as comparability with ordinary costs, but as equality to the actual costs that were incurred by the claimant solely for the restoration of his violated right. It is separately noted that when assessing the reasonableness of court costs, courts should consider the level of qualification of legal representative.
Legal regulation of robo-advisors in the Russian Federation
Authors:   St. Petersburg State University, Bauer Rudolf E.
Published: October 2024

The development of the digital economy entails the emergence or transformation of already existing social relations that develop between investors and professional participants in the securities market in the financial market. Professional participants in the securities market began to provide their services to investors not only personally, but also with the help of artificial intelligence technologies. Such technologies include the use of computer programs — “robo-advisers” to provide investment recommendations. The introduction of such innovations in the financial market has inexorably raised the question of introducing legal regulation of public relations that develop when professional participants in the securities market — investment advisers with the help of “robo-advisers” provide consulting services to their clients. The author stated that the relatively recent emergence of public relations in the field of roboadvising causes difficulties in the conceptual apparatus not only in Russian science, but also in foreign. The article proposed the concept of a robot advisor (roboadviser) and roboadvising in both the theoretical and legal sense. The approaches of the states to the establishment of legal regulation in the national legislation of the provision of investment recommendations by “robo-advisers” were analyzed. The author identifies two approaches of states to the establishment of legal regulation: through acts of a recommendatory nature and through the adoption of special normative legal acts. It is concluded that the Russian Federation belongs to the category of states where the legal regulation of the provision of investment recommendations by “robo-advisers” is carried out on the basis of special regulatory legal acts. In the article, the author expressed the point of view, according to which the consolidation of the legal definition of a “robo-adviser” in Russian legislation seems impractical, due to the fact that it already has a mechanism for legal regulation of the provision of investment recommendations using computer programs (which involve the use of an auto-consulting algorithm), based on which a definition can be derived the term “robo-advisor”. Special attention was paid to the distinctive features of the Russian legal regulation of this area, including on the basis of an analysis of subordinate regulations issued by the Bank of Russia.
Impact of COVID-19 lockdown on water quality of major rivers in Sri Lanka
Authors: Hewakoon Harindu P. , Miguntanna Nandika , Siriwardhana Kushan D. , Rathnayake Upaka
Published: October 2024

The COVID-19 lockdown resulted in a reduction in human activities, lowering pollution levels in these rivers. Nevertheless, limited research can be found on the impact of COVID-19 on river water quality in Sri Lankan rivers. Therefore, this research was carried out to investigate the water quality index (WQI) of four major rivers (Mahaweli, Nilwala, Kelani, and Kalu) in Sri Lanka in three consecutive time slots spanning from 2019 to 2022 (before, during, and after the lockdown). In-depth WQI analysis has unveiled nuanced dynamics in river health. While the lockdown period contributed to positive alterations in key parameters, subsequent periods demonstrated declining water quality in the post-lockdown period. This decline underscores the direct correlation between human activity and river water quality. Several parameters showed positive changes during the lockdown, indicating an improvement in river water quality. When comparing the periods before, during, and after the lockdown, pH, colour, turbidity, total iron, sulphate, chloride, total coliform, and E. coli all showed a significant positive impact. However, some parameters, such as fluoride and electrical conductivity (EC), had a neutral effect. This study sheds light on the positive effects of the COVID-19 lockdown on reducing river pollution in Sri Lanka.
An assessment of node–head–flow relationships at lumped demand nodes for pressure-dependent analysis of water distribution networks
Authors: Tiwari Satyam , Gupta Rajesh
Published: October 2024

Pressure-dependent analysis (PDA) is preferred over demand-dependent analysis (DDA) to evaluate the performance of any water distribution network under pressure-deficient conditions. The PDA requires a relationship, called node–head–flow relationship (NHFR) between available head and available flow at a node to know whether the demand is fulfilled completely, partially, or not at all, depending on the available pressure. Several types of NHFRs have been suggested in the past and mostly a single type of NHFR is used at different nodes. An assessment of these NHFRs is carried out to know how accurate the use of a single type of NHFR is for the lumped nodes. The errors in prediction of the available nodal flows through the available NHFRs and that obtained through the detailed analysis are quantified using chi square. It is observed that actual NHFR is not as smooth as approximated by the different available NHFRs. A nonlinear behaviour between available flows and available heads exists for partial flow conditions and requires proper values of constants to define any NHFR. Furthermore, NHFRs at different lumped nodes in a network are different. This study recommends the consideration of different relationships at different lumped nodes of the network for PDA.
Attrition in IT Sector: Psychology Behind the Scene
Authors: Sarkar Abhisek
Published: October 2024

Attrition is often defined as “a reduction in the number of employees as a
result of retirement, resignation or death” and also as “the rate of shrinkage in size or
number”. But the scenario is not so simple. We should always consider premature
retirement, sudden resignation and premature death, including suicide. The real
scenario is employees do leave, either because they expect extra money, dislike the
working environment, get rough behavior, non-cooperation from their coworkers, need
a change, or because their spouse gets a more robust chance in another region.
Retention is more economical than going for brand spanking new recruitment
whatsoever. Organizations should have a good retention strategy to retain their
valuable employees. Employee turnover may be viewed as the outcome of unmet
expectations and gaps between fundamental employee demands. Employees may
simply resign under a few unfavourable conditions, but more crucially, “people depart
before they leave”, according to the psychology of disengagement. It may be iterated
that as they become older, their contribution gradually decreases, much like a slowly
fading memory. This text presents a holistic view of attrition and retention of
employees based on psychological aspects in this cut-throat competitive environment
in India. Biology has a little role in management, though one cannot ignore biology in
psychology. In broader terms, attrition is somehow related to psychology, and
psychology and physiology are two sides of a coin. A new trend is to relate psychology
with physiology to reduce attrition.
Profit-Based Unit Commitment Using Local and Global Search Methods
Authors: Mallick Nirmalya , Nandi Ayani , Roy Ranadip
Published: October 2024

The availability of clean energy is crucial for both the environment and
human health. Numerous harmful gasses released by conventional automobiles cause
illnesses and ailments in people all over the world. Nevertheless, there is growing
interest in Plug-in Electric Vehicles (PEVs) to help with the energy and climate
emergency. It has been noted that the manufacturing of PEVs has dramatically
increased over the past ten years. The PEVs may supply the power grid with electricity
while both consuming it and storing it in batteries. By effectively managing the electric
demand profile and integrating electricity from PEVs into the electric grid, operating
expenses can be reduced overall. The study recommends the course of action, which, in
this case, is to apply the chaotic mapped Sine Cosine Algorithm advancement method
and combine chaotic maps with the Harris Hawks Optimizer. It also evaluates how well
the suggested better technique is implemented while taking PEVs into account.
The State of Artificial Intelligence Research and Development in the Present-Day Scenario
Authors: Dhawale Krupali , Jha Shraddha , Gube Mishri , Asati Khwaish
Published: October 2024

Artificial intelligence is a field of computer science that focuses on humanlike intelligence in machines. Artificial intelligence is advancing in many areas to
increase the efficiency, accuracy, and speed of the decision-making process. The
chapters of this book provide a detailed overview of the AI journey and provide readers
with insights to improve their knowledge of AI. The chapters also cover the evolution
of artificial intelligence and the techniques used to create it. As artificial intelligence
continues to evolve and integrate into our daily lives, the chapters of this book discuss
the ethical and social implications of AI and the unpredictable growth and impact of
artificial intelligence in society. This chapter also contains thoughts on the future of
artificial intelligence, which has the potential to transform business, drive innovation,
solve complex problems, and provide justice to social and governance issues in a
better-explained way. Overall, this book chapter shapes one’s mind with the entire
concept of artificial intelligence.
Application of Artificial Intelligence Techniques in Healthcare
Authors: Singh Bhavana , Chandra Amrish , Joshi Deepika , Semwal Nidhi , Kukreti Gauree , Saxena Urvashi
Published: October 2024

The integration of Artificial Intelligence (AI) into healthcare promises
improved medical evaluation, provided therapeutic solutions, and enhanced patient
care. Various AI branches, including machine learning, deep learning, and computer
vision, adeptly handle vast healthcare datasets ranging from electronic health records to
wearable data. These techniques extract vital patterns, forecast early-stage diseases, and
personalize patient treatments. In diagnostics, AI tools excel at identifying diseases and
predicting patient outcomes by automating image readings and pinpointing health risks.
AI also optimizes healthcare logistics, resource allocation, and overall patient care,
reducing clerical tasks and promoting data-driven decisions. Yet, there are challenges.
Concerns about data privacy, legislative compliance, ethics, and the need for
transparent AI results are paramount. Addressing these is crucial for successful AI
integration in healthcare. In essence, AI's integration into healthcare promises
revolutionary diagnostic and therapeutic advances. Navigating the challenges requires
collaboration between medical experts, AI specialists, lawmakers, and ethicists to fully
realize AI's transformative potential.
Traffic Sign Detection and Recognition Using Convolutional Neural Networks
Authors: Sreemathy R. , Turuk Mousami , Patil Harsh , Shastri Saurabh , Lele Ninad , Khurana Soumya
Published: October 2024

The advent of technology has brought about seismic shifts in our lives. It is
hard to imagine the world without the very technology that was considered
groundbreaking a while back, such as smartphones, the internet, etc. One such field that
has seen a tremendous rise in recent years is the field of artificial intelligence, along
with computer vision. Object detection and recognition is, and will continue to be, one
of the most important fields of research in the coming years due to our ever-increasing
demand for various technologies to substitute for the human eye. Traffic sign detection
and recognition is an important subset of this, having far-reaching real-world benefits.
Various methods and algorithms have been proposed to achieve this in the past few
years, with more novel technologies improving upon the previous works. The
emergence of advanced driving assistance systems (ADAS), used for driving
assistance, has led to many companies testing various systems on their novel car
models for better accuracy and reliability. There is still some way to go until object
recognition algorithms are deployed on these ADAS systems worldwide. One such
important part of this system is traffic sign detection and recognition. This work
proposes one such traffic sign recognition method. The proposed system is
implemented in two processes, namely detection and recognition. The former is
implemented using the You Only Look Once (YOLO) detection algorithm, which
performs grid classification on the image to predict the bounded boxes. This is
followed by finding the probability of a particular object’s presence in a particular grid.
For the latter process, a 4-layer CNN model is deployed to classify the object into 43
separate classes. The model is trained using the German traffic sign benchmark dataset.
Upon testing with other standard models such as VGGNet and ResNet-50, the proposed
model was found to be more accurate. Real-time implementation of the proposed
model gives a training accuracy of 99.51%, while the testing accuracy is found to be
97.13%.
Cloud Integration in Artificial Intelligence (AI)
Authors: Bhope Pranali , Dhawale Krupali , Kumbhare Sejal , Dhapodkar Kunika
Published: October 2024

We have entered the new era of the cloud age. Cloud integration has been
adopted by companies and is still growing in a rapid way. On the other hand, advances
in artificial intelligence have opened up new possibilities that can be used to improve
existing cloud technologies. This book chapter explores the integration of cloud
computing and artificial intelligence and focuses on the advantages and challenges
associated with this integration. It explores the economic benefits of cloud-based AI
systems, the cost-effectiveness of cloud integration in AI, potential security and privacy
issues associated with storing and processing sensitive AI data in the cloud, and how
the use of cloud-based AI platforms helps in resource optimization, knowledge sharing
among AI learners and integration of cloud services and AI development projects. The
study concludes with a comprehensive assessment of the current state of cloud
integration in AI and recommendations for organizations looking to adopt cloud-based
AI solutions.
Computer-Aided Drug Discovery Methods: A Brief Introduction
Authors: Vlasiou Manos C.
Published: October 2024

Computer-Aided Drug Discovery Methods: A Brief Introduction explores the cutting-edge field at the intersection of computational science and medicinal chemistry. This comprehensive volume navigates from foundational concepts to advanced methodologies, illuminating how computational tools accelerate the discovery of new therapeutics.

Beginning with an overview of drug discovery principles, the book explains topics such as pharmacophore modeling, molecular dynamics simulations, and molecular docking. It discusses the application of density functional theory and the role of artificial intelligence in therapeutic development, showcasing successful case studies and innovations in COVID-19 research.

Ideal for undergraduate and graduate students, as well as researchers in academia and industry, this book serves as a vital resource in understanding the complex landscape of modern drug discovery. It emphasizes the synergy between computational methods and experimental validation, shaping the future of pharmaceutical sciences toward more effective and targeted therapies.
Multimodal Deep Learning in Medical Diagnostics: A Comprehensive Exploration of Cardiovascular Risk Prediction
Authors: Raj Sonia , Bayappu Neelima
Published: October 2024

Machine learning algorithms have been important in identifying and
predicting cardiovascular risk. These algorithms use a variety of data sources, including
patient histories, clinical measures, and electronic health records, to discover people
who could get cardiovascular problems. Methods of deep learning, a subset of machine
learning hold the promise of enhancing the accuracy and effectiveness of
cardiovascular risk prediction models. In this research, retinal images, clinical data, and
various clinical features are employed to harness the capabilities of multimodal deep
learning for predicting cardiovascular risk. The integration of these modalities enables
a holistic assessment of an individual's cardiovascular health, contributing to the
advancement of precision medicine in the realm of Cardiovascular Disease (CVD). The
impact of this research extends beyond cardiovascular risk prediction, as it exemplifies
the transformative potential of machine learning in healthcare. By empowering medical
challenges with cutting-edge technology, our work addresses the urgent need for early
risk assessment, patient stratification, and personalized interventions. This showcases
how the synergy of different data types and deep learning can lead to improved clinical
decision support, reduced healthcare costs, and, ultimately, enhanced patient outcomes.
The potential to deploy such multimodal deep learning models in clinical practice has
the potential to revolutionize the field of cardiovascular health and set a precedent for
the broader role of machine learning in healthcare.
Fundamentals of Machine Learning in Healthcare
Authors: Shaik Farooq , Yelchuri Rajesh , Dash Jatindra Kumar
Published: October 2024

Machine learning (ML), a subset of artificial intelligence (AI), is
revolutionizing industries by leveraging statistical algorithms that learn from data and
experiences. Unlike traditional programs following predetermined sequences, ML
algorithms discern patterns and predict outcomes through extensive datasets. This
transformative technology has profoundly impacted diverse sectors, including
manufacturing, finance, retail, transportation, entertainment, and healthcare. The
influence of ML is amplified by the accessibility of extensive datasets and the
escalating computational prowess of modern systems. As ML algorithms progress, they
are fundamentally reshaping business operations, streamlining processes, enhancing
decision-making, and fuelling innovation across sectors. The impact of machine
learning algorithms on healthcare applications and the usage of diverse data sources,
such as electronic health records, medical imaging, wearable devices, and genomic
data, is discussed in this chapter.
EXPERIENCE OF CLINICAL AND RADIOGRAPHIC CORRELATION IN PATIENTS WITH PAIN SYNDROME OF TMJ DYSFUNCTION IN ATRICULATION-OCCLUSIVE DISORDERS
Authors: Proschenko A.M.
Published: October 2024

This article examines the imaging anatomy of the temporomandibular joint (TMJ), describes the technique of calculating the gaps between the fossa and the head, their comparison based on TMJ computed tomography (CT) data, and their comparison with clinical signs of TMJ dysfunction.
The aim was to determine CT diagnostic criteria for persistent functional displacement of the lower jaw in patients with TMJ functional disorders in occlusal-articulation disorders at the stage of orthopedic treatment planning.
Research materials and methods. A clinical and radiological examination of 150 patients with functional disorders of the masticatory apparatus and occlusal disorders, who were included in the experimental group, and 30 practically healthy persons – the control group, was carried out.
The results. The presence of a pain syndrome was primarily determined - 60 patients (40.00%) complained of pain in the TMJ area, masticatory muscles or headache, and in 19 (31.67%) of them, complaints of pain bothered more than half year TMJ pain was found in 30 (20.00%) patients, in masticatory muscles in 43 (28.67%), headache in 47 (31.33%). Hypertonus of the masticatory muscles was established - 94 - 62.67% with their hypertrophy - 46 - 30.67%, both unilateral and bilateral, which were observed simultaneously with the parafunction of the masticatory muscles (34 - 22.67%). Palpatory functional stable displacement of the lower jaw was determined in 135 (90.00%) patients of the research group, in 57 (42.22%) of them significant pain syndrome was present in 46 (80.70%). At the same time, deviation or deflexion was established in 74 (49.33%) patients of the experimental group, restriction of mouth opening in 52 (32.67%) patients; crunching and clicking in the TMJ - 112- 74.67%. The presence of bilateral posterior displacement of the heads of the lower jaw was established in 103 (68.67%) patients with TMJ dysfunction, of which 42 (40.77%) came to the doctor with complaints of orofacial pain, and in 22 (14.67%) significant displacement, 17 (77.27%) of them had a pain syndrome; unilateral posterior displacement of the heads of the lower jaw in 32 (21.33%) patients with TMJ dysfunction, 16 (50.00%) of them have a pain syndrome, and 11 of them have a significant displacement; in 16 (10.67%) one-sided posterior displacement with simultaneous anterior displacement in the contralateral joint was established with a subjective assessment of the absence of pain syndrome. Presence of a significant displacement in at least one joint was established in 72 (48.00%) patients with TMJ dysfunction, 63 (87.50%) of them had a pain syndrome.
Conclusions. CT enables a comprehensive assessment of bone structures and their connection in the TMJ and is a valuable tool for planning orthopedic treatment and evaluating its effectiveness in dynamics.
Evaluating Expert-Layperson Agreement in Identifying Jargon Terms in Electronic Health Record Notes: Observational Study (Preprint)
Authors: Lalor John P , Levy David A , Jordan Harmon S , Hu Wen , Smirnova Jenni Kim , Yu Hong
Published: October 2024

BACKGROUND

Studies have shown that patients have difficulty understanding medical jargon in electronic health record (EHR) notes, particularly patients with low health literacy. In creating the NoteAid dictionary of medical jargon for patients, a panel of medical experts selected terms they perceived as needing definitions for patients.

OBJECTIVE

This study aims to determine whether experts and laypeople agree on what constitutes medical jargon.

METHODS

Using an observational study design, we compared the ability of medical experts and laypeople to identify medical jargon in EHR notes. The laypeople were recruited from Amazon Mechanical Turk. Participants were shown 20 sentences from EHR notes, which contained 325 potential jargon terms as identified by the medical experts. We collected demographic information about the laypeople’s age, sex, race or ethnicity, education, native language, and health literacy. Health literacy was measured with the Single Item Literacy Screener. Our evaluation metrics were the proportion of terms rated as jargon, sensitivity, specificity, Fleiss κ for agreement among medical experts and among laypeople, and the Kendall rank correlation statistic between the medical experts and laypeople. We performed subgroup analyses by layperson characteristics. We fit a beta regression model with a logit link to examine the association between layperson characteristics and whether a term was classified as jargon.

RESULTS

The average proportion of terms identified as jargon by the medical experts was 59% (1150/1950, 95% CI 56.1%-61.8%), and the average proportion of terms identified as jargon by the laypeople overall was 25.6% (22,480/87,750, 95% CI 25%-26.2%). There was good agreement among medical experts (Fleiss κ=0.781, 95% CI 0.753-0.809) and fair agreement among laypeople (Fleiss κ=0.590, 95% CI 0.589-0.591). The beta regression model had a pseudo-R2 of 0.071, indicating that demographic characteristics explained very little of the variability in the proportion of terms identified as jargon by laypeople. Using laypeople’s identification of jargon as the gold standard, the medical experts had high sensitivity (91.7%, 95% CI 90.1%-93.3%) and specificity (88.2%, 95% CI 86%-90.5%) in identifying jargon terms.

CONCLUSIONS

To ensure coverage of possible jargon terms, the medical experts were loose in selecting terms for inclusion. Fair agreement among laypersons shows that this is needed, as there is a variety of opinions among laypersons about what is considered jargon. We showed that medical experts could accurately identify jargon terms for annotation that would be useful for laypeople.
Data interoperability in context: the importance of open source implementations when choosing open standards (Preprint)
Authors: Kapitan Daniel , Heddema Femke , Dekker André , Sieswerda Melle , Verhoeff Bart-Jan , Berg Matt
Published: October 2024

UNSTRUCTURED

In response to the proposal of Tsafnat et al. to converge towards three open health data standards, this viewpoint provides a critical reflection on the proposed alignment of using openEHR, FHIR and OMOP as the default standards for clinical care and administration, data exchange and longitudinal analysis, respectively. We argue that open standards are a necessary but not sufficient condition to achieve health data interoperability. The ecosystem of open source implementations needs to be considered when choosing an appropriate standard for a given context. We discuss two specific contexts, namely standardization of i) health data for federated learning, and ii) health data sharing in low- and middle income countries (LMICs). Specific design principles, practical considerations and implementation choices for these two contexts are described, based on ongoing work in both areas. In the case of federated learning, we observe convergence towards OMOP and FHIR, where the two standards can effectively be used side-by-side given the availibility of mediators between the two. In the case of health information exchanges in LMICs, we see a strong convergence towards FHIR as the primary standard, with as yet limited adoption of OMOP and openEHR. We propose practical guidelines for context-specific adaptation of open standards.
Natural Language Processing Algorithms Outperform ICD Codes in the Development of Fall Injuries Registry: A Retrospective Case-Control Study (Preprint)
Authors: Taseh Atta , Sasanfar Souri , Chan Jia-Zhen M. , Sirls Evan , Nazarian Ara , Batmanghelich Kayhan , Bean Jonathan F. , Ashkani-Esfahani Soheil
Published: October 2024

BACKGROUND

Standardized registries are commonly built using administrative codes assigned to patient encounters, such as the International Classification of Diseases (ICD) codes. However, fall patients are often coded using subsequent injury codes, such as hip fractures. This necessitates manual screening to ensure the accuracy of data registries.

OBJECTIVE

We aimed to automate the extraction of fall incidents and mechanisms using Natural Language Processing (NLP) and compare this approach with the ICD method.

METHODS

Clinical notes for patients with fall-induced hip fractures were retrospectively reviewed by medical experts. Fall incidences were detected, annotated, and classified among patients who had fall-induced hip fracture (case group). The control group included patients with hip fracture without any evidence of fall. NLP models were developed using the annotated notes of the study groups to fulfill two separate tasks: fall occurrence detection and fall mechanism classification. The performances of the models were compared using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1-score, and area under the ROC curve (AUC-ROC).

RESULTS

A total of 1,769 clinical notes were included in the final analysis for the fall occurrence task, and 783 clinical notes were analyzed for the fall mechanism classification task. The highest F1 score using NLP for fall occurrence was 0.97 (specificity=0.96; sensitivity=0.97) and for fall mechanism classification was 0.61 (specificity=0.56; sensitivity=0.62). NLP could detect up to 98% of the fall occurrences and 65% of the fall mechanisms accurately compared to 26% and 12%, respectively, by ICD codes.

CONCLUSIONS

Our findings showed promising performance with a higher accuracy of NLP algorithms compared to the conventional method for detecting fall occurrence and mechanism in developing disease registries using clinical notes. Our approach can be introduced to other registries that are based on large data and are in need for accurate annotation and classification.
Using Gamification to Enhance COVID-19 Vaccination Among Young Adults: A Real-world Effectiveness Study (Preprint)
Authors: Cheng Tina , Nocos Rochelle , Bettinger Julie A. , Roe Ian , Witteman Holly O. , Lutes Lesley , Lear Scott A.
Published: October 2024

BACKGROUND

Young adults (18-29 years) have lower COVID-19 vaccination rates than older adults, indicating a need for tailored strategies. Gamification has the potential to boost vaccine knowledge and intentions, but its real-world impact on young adults remain underexplored.

OBJECTIVE

To examine the effectiveness of a digital health game, COVID Chronicles, in influencing COVID-19 vaccine intention among young adults.

METHODS

COVID Chronicles was advertised through QR-codes at public transit, local merchandises and online. The game was based on the Transtheoretical Model of change. Users selected statements according to their intention to be vaccinated and were directed to simple games (true/false, multiple choice, chance) using content tailored according to their vaccine intention. While anyone could play, only those who self-identified as a young adult were invited to participate in the study and asked to provide demographic information, rank their vaccination intention due to the game on a five-point Likert scale (from very unlikely to very likely) and participate in a two-month follow-up. Ordinal logistic regression model assessed the association between participants’ stated likelihood of change in vaccination intention due to gameplay with various participant characteristics.

RESULTS

Between May 2022 to July 2023, COVID Chronicles was initiated 6,295 times with 5,058 completions (80.3%) with unique completions based on submitted emails. Of these, 1,174 (26.6%) self-identified as a young adult and responded to the question on vaccine intention due to playing the game. Of those, 75.8% were fully vaccinated. Overall, 40.9% indicated COVID Chronicles either likely or very likely influenced their likelihood to be vaccinated (vaccine intention). The ordinal logistic regression showed that people who belonged to ethnic minorities, including Asian (OR 2.16, CI: 1.66-2.80), Indigenous (OR 2.69, CI:1.33-5.43) and Latinx (OR = 3.48, CI:2.20-5.51) participants were more likely to report the game influenced their willingness to be vaccinated compared to White (reference group) participants. Participants with a Bachelor’s degree (OR = 0.28, CI: 0.14-0.56), Master’s degree (OR = 0.25, CI: 0.11-0.55), and Doctorate degree (OR = 0.24, CI: 0.09-0.68), were less likely to report the game influenced their willingness to be vaccinated compared to participants with less than a high school education (reference group). Participants who agreed that vaccines are safe and effective were more likely to report that the game influenced their vaccination intentions.

CONCLUSIONS

Using gamification strategies, COVID Chronicles influenced vaccine intention and was particularly effective among people who identify as members of ethnic minority groups and people with less than high school education attainments.

CLINICALTRIAL

N/A
Design Guidelines for Game-Based Physical Rehabilitation System: A Focus Group Study (Preprint)
Authors: S Elaklouk Ahmad M , ramli ratna zuarni , M. Alakklouk Samah M.
Published: October 2024

BACKGROUND

Incorporating serious games and ICT advancements into physical rehabilitation can substantially enhance the process, provide unique benefits, and improve its effectiveness and efficiency. While recent literature highlights various game-based interventions for physical rehabilitation, there is a lack of comprehensive guidance on how to design and develop systems that effectively address the actual needs of therapists, practitioners, and individuals with physical disabilities.

OBJECTIVE

Since therapists and other healthcare practitioners play crucial roles in both patient recovery and the establishment of an effective game-based therapy, thus, the objective of this study is to explore the intentions, needs, and desires of therapists and other practitioners, as well as to examine the factors and determinants influencing the effectiveness and efficacy of game-based physical rehabilitation.

METHODS

A Design Science approach was adopted to achieve this research objective. To gather feedback, explore the needs and desires for a serious game, and understand the requirements for game-based physical rehabilitation, a focus group of 27 participants was conducted. The group first tested commercially available games and then evaluated the game prototype mockups created.

RESULTS

The research provides essential design insights and guidelines for designers and researchers, focusing on the practical needs and requirements of game-based physical rehabilitation systems.

CONCLUSIONS

Therefore, as proof of concept, these guidelines will be used in the next phase of our research, which involves designing and developing a game-based physical rehabilitation system.
Palmscaping Athens
Authors: Makedonopoulou Charikleia (Haris)
Published: October 2024

The main aim of this paper is to investigate the role of plants in the formation of urban landscapes. With the conviction that ‘Nature’, or better plant elements, participate substantially in the shape of urban landscapes and social identities, a new reading of the contemporary Greek landscape is proposed, seeking the tools of this reading in the Palm tree.
Palms, in their majority, are considered as tropical trees, in the sense that they originate from tropical and subtropical regions. However, today Palms are found all around the world, which proves that they are great travellers.
The perpetual journey of plants has deeply reformed alimentary and agricultural practices all over the world. The introduction of new plants in the new ecosystems, changes their evolution, their inflorescence. At the same time, a new balance is to be found on a social level as well. Transplantation of plants in different cultural environments changes their content, their social role and they are called upon to play a new role there.
Since antiquity, Palms have been returning to the Greek territory, either as a seed, a fruit, a tree or a myth. The presence of the Palm tree seems to characterize the Greek landscape, especially since its re-introduction during the era of Palingenesis, the era when the new Modern Greek State was established. Palms have been introduced into the Greek landscape several times, each time in a different way, under different cultural and socio-economic conditions. It seems that the Palm tree in Greece can abolish, renew or enrich its conceptual content and manages to be an active element in the contemporary landscape. In some cases, it dominates the city, becoming not only part of the cityscape, but also part of its social identity and history.
ADAM SMITH’S PLURALISM AND THE SCIENCE OF THE LEGISLATOR
Authors: Sturn Richard
Published: October 2024

It is well established that we can make sense of Adam Smith’s multi-faceted account of human agency without incurring “das Adam Smith-Problem”. However, the relevance of his view of knowledge and agency for political economy as science of the legislator deserves to be studied more carefully. Smith’s view of human agency is linked to political realism and pragmatic pluralism, emphasizing the benefits of the knowledge made available by scientific “systems”, but also their limitations and incompleteness. Smith’s Theory of Moral Sentiments, seen together with his realist discussions of mercantilist politics are suggesting explanatory and pragmatic advantages of such pluralism, while opening up horizons of problem-responsive second-best reforms avoiding fallacies of “the man of system”.
Factores determinantes de la diferencia en ventas: estudio basado en inferencia estadística y regresión logística en las empresas corporación V&M SAC, Breña’s SAC e Inversiones R&M SAC
Authors: Peña Medina Percy
Published: October 2024

El estudio tiene como objetivo identificar los factores determinantes de la diferencia en los ingresos por ventas de producto en las empresas Breña´s SAC, Corporación V&M SAC e Inversiones R&M SAC. Se realizó un estudio basado en inferencia estadística para determinar la diferencia de los ingresos por ventas y análisis de regresión logística binaria múltiple para identificar los factores determinantes. El diseño fue no experimental, transeccional, descriptivo. Para identificar los factores se aplicó un cuestionario de preguntas a una muestra de 385 consumidores y para determinar la diferencia de los ingresos por ventas se trabajó con las ventas mensuales correspondientes al periodo económico 2019. Los resultados revelan que la media de los ingresos por ventas de las empresas son s/. 134 222.00, s/. 77 552.83 y s/. 99341.83 respectivamente, el mayor ingreso por ventas mensuales en promedio corresponde a la empresa Breñas SAC. Los factores no determinantes son: el precio, la sazón del producto, el tiempo de espera y la ubicación del local. En conclusión, existe diferencia significativa en los ingresos por ventas, corroborado con el método de análisis de varianza de un factor y la prueba de comparación múltiple de Bonferroni y los factores determinantes para que la empresa Breña´s SAC logre mayores ingresos por ventas son: la profesionalidad del trabajador, limpieza de los elementas tangibles y el protocolo de bioseguridad.
Controle de qualidade da droga vegetal Calendula officinalis L. disponível na cidade de Ponta Grossa (PR)
Authors: Augusto Caixeta Nunes Gabriel , De Jesus Mariano Lacerda Isadora , Nadal Dias Swiech Juliane
Published: October 2024

Introduction: Calendula officinalis L. is a herbaceous plant belonging to the Asteraceae family that contains flowers as parts used to obtain analgesic, anti-inflammatory, antiseptic, healing, and dermoprotective effects. Objective: The objective of the present work was to analyze and characterize samples of C. officinalis, sold in Ponta Grossa (PR), and verify their compliance with current legislation, presenting the quality control provided for by the Brazilian Pharmacopoeia (2019). Method: After selecting the selections, tests were carried out on the quality control of the herbal drug by checking the packaging and labeling, macroscopic and microscopic identification, purity tests, analysis of loss due to desiccation and total ash, thermal analysis, profile of the aqueous extract in thin layer chromatography, and source of flavonoids from secondary metabolites. Results: All samples were identified as C. officinalis and were approved in the chromatographic profile and flavonoid content; however, sample B did not meet the pharmacopoeia purity requirements. Conclusion: Medicinal plants with quality deviations may suffer a significant reduction in their therapeutic effect, in addition to generating possible side and toxic effects.
Estudo das dificuldades encontradas por laboratórios brasileiros na implementação de métodos alternativos ao uso de animais: avaliação de irritação ocular e o teste de Permeabilidade e Opacidade da Córnea Bovina (BCOP)
Authors: Gimenes Izabela , Augusto França Presgrave Octavio , Salabert Gonzalez Marcelo , Gomes Alves Gutemberg
Published: October 2024

Introduction: Ensuring the safety of products causing ocular irritation is crucial. The Bovine Corneal Opacity and Permeability (BCOP) test is an accepted alternative method for ocular irritation assessment in regulatory contexts. Objective: This study aimed to identify the main challenges and technical limitations faced by professionals when implementing alternative methods, particularly for ocular irritation assessment. Method: A qualitative research approach was employed using questionnaires (n = 22 respondents) and interviews (n = 7), followed by discourse analysis. Results: Findings reveal that 71% of alternative method practitioners encounter significant difficulties, primarily due to high validation/implementation costs (62%), driven by consumable expenses. Limited access to training (62%) and importation of reagents and equipment (43%) were also noted. Key BCOP limitations include restricted access to bovine eyeballs (50%), less precise risk classification (43%), and substantial eyeball waste (29%) due to damage. Interviews supported these conclusions, highlighting challenges such as travel to slaughterhouses, insufficient technical details in the OECD Guide, the need for additional support materials, and a lack of experienced professionals. These results underscore the need for expanded training opportunities for test implementation. The high cost of imported materials indicates greater validation expenses in Brazil than in other countries. Conclusions: Addressing these challenges requires an open innovation environment, fostering collaboration among the Triple Helix (Companies, Scientific and Technological Institutions, and Government).
Unani Integrative Approach for the Management of Sciatica, Employing Pharmacotherapy with Regimenal Therapy: A Case Report
Authors: Abbasi Safia , Mir Uzair Yousf , Parveen Shaik Adeena , Nayab Mohd , Azeez Abdul , Ansari Abdul Nasir
Published: October 2024

Sciatica, a subtype of low back pain (LBP) is one of the most common clinical complaints in primary care which is characterized by pain that originates in the lower back or buttocks and radiates down one or both legs along the distribution of the sciatic nerve. It commonly results due to nerve root compression by a prolapsed lumbar disc. Sciatica affects both genders equally and has an annual incidence of 1-5%, most common in 30-65 years of age. The management of sciatica includes non-pharmacological, pharmacological and surgical approaches. Combining these management techniques can help in pain reduction and thereby can lead to an overall wellbeing of the individual. In this case report we present the case of a 52 year old male patient with lower back pain radiating to left lower limb who came to Department of Regimenal therapies, National Institute of Unani Medicine, Bengaluru. The patient had taken NSAIDs and other measures for pain management from last 6 months. Despite taking exhaustive measures, no significant improvement was seen. The symptoms have gotten worse over the past two months. After complete clinical examination and diagnosis, the patient underwent treatment for 4 weeks using integrative approach in the form of unani pharmacotherapy, coupled with regimenal therapy. Many objective parameters were used to evaluate the patient both before and after the intervention. The assessment parameters after the intervention reported a significant amelioration of the symptoms. Our study suggested that, management of sciatica with an integrative strategy can be considered.
Keywords: Sciatica, LBP, lumbar disc, Integrative therapy, NSAIDs, Regimenal therapy.