bluuebunny/crossref_metadata_2025 huggingface dataset:
PERANCANGAN SISTEM DIAGNOSIS GETARAN MOTOR MENGGUNAKAN JARINGAN SARAF TIRUAN PROPAGASI MUNDUR
Authors: Romahadi Dedik , Feriyanto Dafit , Suprihatiningsih Wiwit , Setiawan Wahyu Nur
Published: June 2022

Expert system design is an effective and sophisticated way of diagnosing a fault in a 12 kW DC Motor. This study aims to design an ANN system to determine damage to the motor. The research method uses spectrum data from the vibration analyzer which is collected based on different types of damage. The training data patterns from the spectrum characteristics to be used in the system, the goal is that the systems can recognize the patterns that have been made. The training data patterns that have been successfully recognized by the system are then tested. The results of training and ANN testing are quite good, with the greatest Cross-Entropy value of 9.94, having 0% error value, the largest Mean Square Error value 8.33e-6 and the smallest regression 0.998. A testing of 8 new spectrums resulted in accurate predictions.
Elaboración de concentrado para tilapia roja “Oreochromis sp” a base de desechos obtenidos de las centrales de abasto de Medellín
Authors: Acosta Feria Carlos Mario , Pérez Pérez Jorge Luis , Bedoya Corrales Laura Isabel , Suarez Hernández Albeiro Hernán
Published: June 2022

The present research thesis offers to generate a new fish feed, particularly for the Red Tilapia "Oreochromis sp", from the vegetable residues that are produced in the central supply plants, which are causing damage to the environment by their growth in the landfills; Therefore, this concentrate seeks to provide the diet with better opportunities in cost, quantity of vitamins, minerals, fatty acids which are important for the growth of fish, providing an improvement in the nutritional table in order to obtain a better quality product in terms of size, texture and color, aspects that are important for human consumption.The idea of developing a new concentrate arose to mitigate the waste that is generated daily, and to improve the concentrate that is currently provided to the fry, since there is an unbalanced diet and delayed growth that is affecting their development, which leads to not supplying the growing demand for this food. To carry out the development of the new food diet, it is necessaryto carry out statistical studies, laboratory tests of measurement and observation, identifying the adequate behavior of the fry, which seeks to adapt technical specifications that generate reliability in the people who are dedicated to the work of fish farming in Medellin.
Implementación de mejora en el proceso de empaque del banano: caso aplicado en finca de urabá (Antioquia)
Authors: Trespalacio González Anderson Manuel
Published: June 2022

The objective of this work is to identify the possible difficulties in the banana packing process developed by the Kalamary farm, located in Urabá Antiqueño, in order to implement improvements in the process so as to offer a better yield in the plant and increase the farm's production.To achieve this purpose, field work was carried out to obtain preliminary information on the process, which was later used to carry out a basic simulation that reflected the reality of the banana packing process. Finally, a final simulation was carried out in which the improvements were implemented, showing an increase in the productive yield of the Kalamary farm.
Seguridad a nivel de enlace de datos en el modelo de interconexión de sistemas abiertos (OSI)
Authors: Obando I Christian
Published: June 2022

Communications networks can provide an innumerableamount of services in an organization that will allow it to satisfy its most important needs, helping it to fulfill its organizational objectives more efficiently.in their computing devices can cause a great disadvantagefor these objectives. Layer two of the OSI model is considered one of the most important in the flow of information, since it is practically the starting point for communication with the rest of the layers of this model, so there is a need to study computer attacks on this layer and implement techniques to improve security in this layer.
FAMILIA PONTEDERIACEAE
Authors:   Instituto de Biología Universidad Nacional Autónoma de México, Novelo Alejandro , Ramos Leandro ,   Instituto de Biología Universidad Nacional Autónoma de México
Published: June 2022

Familia con seis géneros y cerca de 34 especies dulceacuícolas, de distribución pantropical. Algunos géneros se extienden a las zonas templadas. El lirio acuático (Eichhornia crassipes) es considerado mundialmente como la maleza acuática más agresiva, peligrosa y de difícil control. En la región de esta Flora se han encontrado siete especies pertenecientes a dos géneros.
FAMILIA MAYACACEAE
Authors:   Universidad Nacional Autónoma de México, Novelo Alejandro , Ramos Leandro ,   Universidad Nacional Autónoma de México
Published: June 2022

Familia monogenérica con cerca de cuatro especies dulceacuícolas, distribuidas en América y África calientes.
FAMILIA PODOSTEMACEAE
Authors:   Universidad Nacional Autónoma de México, Novelo Retana Alejandro , Philbrick C. Thomas ,   Western Connecticut State University
Published: June 2022

Familia con cerca de 48 géneros y un poco más de 250 especies dulceacuícolas, de amplia distribución en los trópicos y subtrópicos de todo el mundo, aunque Podostemum ceratophyllum Michx. se extiende hasta el noreste de Estados Unidos. Existe gran cantidad de géneros y especies endémicas a un solo río o un sistema de ríos. En general, la familia está mal muestreada y representada en los herbarios a causa del tipo de hábitat en donde vive, como son las cascadas, las cataratas y los rápidos en ríos de corriente fuerte, o porque sus componentes han pasado desapercibidos a los colectores botánicos en la mayoría de los casos, por su pequeño tamaño. En la región de esta Flora se ha encontrado una sola especie nativa, perteneciente al género Oserya.
Manga versus webtoon: Alternative science learning module based on Dr Stone
Authors: Septaria Kiki , Fatharani Atika
Published: June 2022

Reading activities for junior high school students in Indonesia are carried out at school when the instructor requests that they study the learning topic being taught. Therefore, learners may become bored due to the thickness of the available books. Indonesian students are more likely to read when they encounter visualizations in images, and a small amount of text, commonly referred to as comics. Students like reading numerous popular comics, such as manga and webtoons, but it is exceptionally uncommon to discover a popular comic that teaches the subject of a specific discipline, particularly natural sciences, which has a challenging scientific picture. This study aims to examine the many forms of manga comics and webtoons that may be utilized as alternative student learning modules when students study from home without regard for space or time constraints during the covid-19 epidemic. The descriptive qualitative research approach was applied. Manga comics, particularly Dr Stone's manga, were more acceptable for use as alternative scientific learning modules in junior high schools in terms of completeness of module parts and learning contexts. Comic Dr Stone can boost learners' cognitive and psychomotor skills by vividly seeing daily situations. This research is intended to be expanded by further researchers to give more alternative module alternatives for students and aid teachers in educating Indonesian learners.
E-module design based on Golabz for online physics learning about RLC series circuits
Authors: Dewi Karina Indra , Sudjito Debora Natalia , Pattiserlihun Alvama
Published: June 2022

There are many virtual physics laboratory applications, i.e., Golabz and Crocodile Physics. This study aims to design online physics learning about RLC series circuits using Golabz, which integrates Crocodile Physics and investigates its effectivity on students' understanding. The research method used here is the development research with the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). The online physics learning design based on an inquiry about the RLC series circuit using Golabz consists of three learning activities according to the learning objectives. Each learning has five steps, i.e., orientation, conceptualization, investigation, discussion, and conclusion. The research instruments are an observation sheet, evaluation, questionnaire, and validation sheet for the material and media. Based on the research above, the results of learning observation indicate that all respondents can follow the learning well with an average of 82% and gave positive responses to at least 70% of the statements with an average of 98%; some students were able to obtain evaluation results of more than 70% with an average of 71.88%. Thus, all indicators of success are achieved, and the online physics learning design about RLCseries circuits using Golabz is said to be sufficient to help students understand the material of RLC series circuits.
Increasing students’ higher order thinking skills in science learning through discovery learning assisted by e-worksheet based on Google Docs
Authors: Wibowo Widodo Setiyo , Wasana Megeng Anung , Muhammad Fikri Nur
Published: June 2022

This study aims to determine the optimal application of discovery learning assisted by an Electronic Worksheet based on Google Docs and to determine the improvement of HOTS of students in Junior High School Students. This research was classroom action research (CAR) with a spiral design by Kemmis and MC Taggart, including the stages of Planning, Implementation, Observation, and Reflection. Learning was carried out in two cycles, each consisting of two meetings. The research subjects were 32 students in the academic year 2021/2022. Data were collected using an instrument of learning implementation observation and test. Data were analyzed descriptively (quantitatively and qualitatively), and inferential statistics to determine the achievement of success indicators. The results show that implementing the discovery learning model has reached the excellent category in cycle II. The results prove that s 78% of students have reached the minimum completeness criteria for HOTs. In addition, there is a significant difference in the average pre-test and post-test scores in the medium category in cycle II. Therefore, it can be concluded that this media can improve students' HOT.
Нанопроволоки из двух- и трехкомпонентных сплавов: корреляция структурных и магнитных свойств
Authors: Хайретдинова Д.Р. , Долуденко И.М. , Панина Л.В. , Загорский Д.Л.
Published: June 2022

Several types of nanowires (NWs) made of alloys of various compositions obtained by the method of matrix synthesis based on track membranes have been studied. Electrolytes were selected to obtain NWs of the desired composition. The control of electrodeposition by chronoamperograms made it possible to systematically change the geometric parameters and morphology. The topographies of the resulting NW arrays and their elemental composition were studied using electron microscopy with an X-ray spectral analyzer. The magnetic properties of the samples were studied on a vibrating magnetometer. The structures of binary alloys were studied: for NWs of FeCo alloys, the dependence of the coercive force on the composition was studied. The obtained dependence has two maxima - at an equiatomic composition and at a cobalt content of about 90%. For Fe0.3Co0.7 NWs, a sharp increase in the coercive force with decreasing diameter is shown. It is assumed that this effect is due to the formation of single-domain crystallites, the processes of magnetization reversal of which are associated with a uniform rotation of the magnetization. For NWs made of FeNi alloys, the influence of the aspect ratio on the coercive force has been proved. Ternary alloys of the FeCoCu system have been studied: it has been shown that the addition of copper significantly increases the coercive force, which reaches a maximum at a copper content of about 5%. The obtained X-ray data suggest that the effect of an increase in the coercive force is associated with the formation of fine-grained inclusions based on copper, which lead to effective deceleration of the domain walls. The data obtained expand the range of possibilities for controlling the magnetic properties of NW arrays obtained by the method of matrix synthesis. Keywords: nanowires, matrix synthesis, microscopy, elemental analysis, magnetic properties, coercive force.
Локальная магнитная анизотропия в наноструктурированных покрытиях FeCo-C, синтезированных методами зеленой химии
Authors: Денисова Е.А. , Комогорцев C.В. , Чеканова Л.А. , Незнахин Д.С. , Исхаков Р.С. , Немцев И.В.
Published: June 2022

Fe-Co alloys attracting interest due to their high magnetic induction and Curie temperature, were synthesized by an eco friendly electroless deposition with carbohydrates as reducing agents. It was shown that Fe1-xCox-С composite coatings retain high induction, while demonstrating an unusual behavior of magnetization at low temperatures. It was found that for each coating measured at different temperatures, there is a correlation between the local magnetic anisotropy constant K at a given temperature and the correlation radius of the local easy magnetization axis Rc. The functional type of this correlation is typical for nanoparticles or nanogranules in a composite, which made it possible to estimate the volume and surface magnetic anisotropy constants of metal granules of Fe-Co-C coatings.
Эффекты нелинейности при распространении спиновых волн в двуслойном магнонном волноводе
Authors: Одинцов С.А. , Локк Э.Г. , Бегинин Е.Н. , Садовников А.В.
Published: June 2022

The possibility of frequency-selective propagation of spin waves in a linear and nonlinear mode in a magnon microwave medium consisting of two layers with different values of the magnetization saturation of each layer is demonstrated. It is shown that multimode propagation of spin waves can be carried out inside the two-layer structure in two frequency ranges, with an increase in the power of the input microwave signal leading to a change in the boundaries of both frequency ranges. At the same time, this process is accompanied by a strong nonreciprocity of the spin-wave signal propagation, which manifests itself in a change in the amplitude-frequency characteristics when the direction of the external magnetic field is reversed, with a nonlinear mode change in the frequency bandwidth borders can change with increasing pumping power. The proposed concept of a two-layer spin-wave waveguide can form the basis for the fabrication of nonlinear magnon elements demonstrating interconnection functions with support for multiband modes of operation
Механизмы магнитоэлектрических эффектов в оксидных мультиферроиках с прафазой перовскита
Authors: Гареева З.В. , Звездин А.К. , Шульга Н.В. , Гареев Т.Т. , Чен С.М.
Published: June 2022

Magnetoelectric effects are discussed in multiferroics with the perovskite structure: bismuth ferrite, rare-earth orthochromites, and Ruddlesden - Popper structures belonging to the trigonal, orthorhombic, and tetragonal syngonies. The influence of structural distortions on magnetic and ferroelectric properties is studied, possible magnetoelectric effects (linear, quadratic, inhomogeneous) in these materials are determined, and expressions for the linear magnetoelectric effect tensor are given. Macroscopic manifestations of the inhomogeneous magnetoelectric effect in multiferroic nanoelements are considered.
Relationship characteristic of midwife in pregnancy services and patient satisfaction In Public Health Center, Soreang, Bandung
Authors: Faozi Balkis Fitriani , Wijaya Merry , Sukandar Hadyana
Published: June 2022

Background: Pregnancy/Antenatal Care (ANC) services are the main factors in determining delivery outcomes including early detection of risk factors and also determining early treatment for pregnant women who experience complications during pregnancy. The quality of quality pregnancy services depends on the characteristics of health workers who provide services, the characteristics consist of age, educational qualifications, training and length of work.

Objectives: This study aims to analyze the relationship between the characteristics of midwives in pregnancy services and patient satisfaction.

Methods: This study used a cross-sectional analytical research design, namely the measurement of independent and dependent variables at the same time. The sample in this study were all midwives who worked at the Soreang District Health Center, namely 18 midwives. The midwives studied conducted examinations of 8 patients each for each pregnancy examination. Data collection techniques were carried out by filling out patient satisfaction questionnaires by pregnant women and observing pregnancy services by trained personnel using a pregnancy service checklist sheet. Furthermore, the data were analyzed by chi square test and multivariable multiple logistic regression analysis.

Results: The results showed that there was a correlation between the characteristics of midwives and pregnancy services, namely the training indicator in a bivariable manner significantly affected the overall pregnancy service with a p-test of 0.007. Waiting time has a negative correlation with physical examination, laboratory, counseling and overall antenatal care with a p value of 0.002. Multivariable analysis showed that the characteristics of midwives that most influenced pregnancy care were age with p-value 0.040 [POR 1.83(1.028-3.259)], training with p-value 0.019 [POR 2.6(1.168-5.741)]. There is no relationship between pregnancy services and patient satisfaction with a p value of 0.796.
Conclusion: In pregnancy services, the most influencing factors are age and training carried out by midwives. There is also a negative correlation between waiting time with physical and laboratory examinations, namely the longer the waiting time, the less physical examination services provided by midwives to patients. There is no relationship between pregnancy services and patient satisfaction.
A Disease Identification Algorithm for Medical Crowdfunding Campaigns: Validation Study
Authors: Doerstling Steven S , Akrobetu Dennis , Engelhard Matthew M , Chen Felicia , Ubel Peter A
Published: June 2022

Background

Web-based crowdfunding has become a popular method to raise money for medical expenses, and there is growing research interest in this topic. However, crowdfunding data are largely composed of unstructured text, thereby posing many challenges for researchers hoping to answer questions about specific medical conditions. Previous studies have used methods that either failed to address major challenges or were poorly scalable to large sample sizes. To enable further research on this emerging funding mechanism in health care, better methods are needed.

Objective

We sought to validate an algorithm for identifying 11 disease categories in web-based medical crowdfunding campaigns. We hypothesized that a disease identification algorithm combining a named entity recognition (NER) model and word search approach could identify disease categories with high precision and accuracy. Such an algorithm would facilitate further research using these data.

Methods

Web scraping was used to collect data on medical crowdfunding campaigns from GoFundMe (GoFundMe Inc). Using pretrained NER and entity resolution models from Spark NLP for Healthcare in combination with targeted keyword searches, we constructed an algorithm to identify conditions in the campaign descriptions, translate conditions to International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes, and predict the presence or absence of 11 disease categories in the campaigns. The classification performance of the algorithm was evaluated against 400 manually labeled campaigns.

Results

We collected data on 89,645 crowdfunding campaigns through web scraping. The interrater reliability for detecting the presence of broad disease categories in the campaign descriptions was high (Cohen κ: range 0.69-0.96). The NER and entity resolution models identified 6594 unique (276,020 total) ICD-10-CM codes among all of the crowdfunding campaigns in our sample. Through our word search, we identified 3261 additional campaigns for which a medical condition was not otherwise detected with the NER model. When averaged across all disease categories and weighted by the number of campaigns that mentioned each disease category, the algorithm demonstrated an overall precision of 0.83 (range 0.48-0.97), a recall of 0.77 (range 0.42-0.98), an F1 score of 0.78 (range 0.56-0.96), and an accuracy of 95% (range 90%-98%).

Conclusions

A disease identification algorithm combining pretrained natural language processing models and ICD-10-CM code–based disease categorization was able to detect 11 disease categories in medical crowdfunding campaigns with high precision and accuracy.
Toward an Ecologically Valid Conceptual Framework for the Use of Artificial Intelligence in Clinical Settings: Need for Systems Thinking, Accountability, Decision-making, Trust, and Patient Safety Considerations in Safeguarding the Technology and Clinicians
Authors: Choudhury Avishek
Published: June 2022

The health care management and the medical practitioner literature lack a descriptive conceptual framework for understanding the dynamic and complex interactions between clinicians and artificial intelligence (AI) systems. As most of the existing literature has been investigating AI’s performance and effectiveness from a statistical (analytical) standpoint, there is a lack of studies ensuring AI’s ecological validity. In this study, we derived a framework that focuses explicitly on the interaction between AI and clinicians. The proposed framework builds upon well-established human factors models such as the technology acceptance model and expectancy theory. The framework can be used to perform quantitative and qualitative analyses (mixed methods) to capture how clinician-AI interactions may vary based on human factors such as expectancy, workload, trust, cognitive variables related to absorptive capacity and bounded rationality, and concerns for patient safety. If leveraged, the proposed framework can help to identify factors influencing clinicians’ intention to use AI and, consequently, improve AI acceptance and address the lack of AI accountability while safeguarding the patients, clinicians, and AI technology. Overall, this paper discusses the concepts, propositions, and assumptions of the multidisciplinary decision-making literature, constituting a sociocognitive approach that extends the theories of distributed cognition and, thus, will account for the ecological validity of AI.
Innovative App (ExoDont) and Other Conventional Methods to Improve Patient Compliance After Minor Oral Surgical Procedures: Pilot, Nonrandomized, and Prospective Comparative Study
Authors: Sybil Deborah , Krishna Meenakshi , Shrivastava Priyanshu Kumar , Singh Shradha , Khan Imran
Published: June 2022

Background

Postoperative care is influenced by various factors such as compliance, comprehension, retention of instructions, and other unaccounted elements. It is imperative that patients adhere to the instructions and prescribed regimen for smooth and placid healing. ExoDont, an Android-based mobile health app, was designed to ensure a smooth postoperative period for patients after a dental extraction. Besides providing postoperative instructions at defined intervals, the app also sends drug reminders as an added advantage over other available, conventional methods.

Objective

The aim of this study was to compare the compliance rate of individuals with respect to the prescribed regimen and postoperative instructions. Additionally, we aimed to assess any changes in the postoperative complication rate of patients assigned to 3 categories: the verbal, verbal plus written, and ExoDont app-based delivery groups.

Methods

We conducted a pilot, nonrandomized, and prospective comparative study in which patients after tooth extraction were assigned to 3 groups—verbal (Group A), verbal plus written (Group B), and ExoDont app-based delivery (Group C)—based on the eligibility criteria, and a 1-week follow-up was planned to obtain the responses regarding compliance and postoperative complications from the participants.

Results

In total, 90 patients were recruited and equally divided into 3 groups. Compliance to prescribed drug was found to be the highest in Group C, where of the 30 participants, 25 (83%) and 28 (93%) followed the entire course of antibiotics and analgesics, respectively. For postoperative instructions, higher compliance was observed in Group C in relation to compliance to diet restrictions (P=.001), not rinsing for 24 hours (P<.001), and warm saline rinses after 24 hours (P=.001). However, the difference was not significant for smoking restrictions (P=.07) and avoiding alcohol (P=.16). Moreover, the difference in postoperative complication rate was not statistically significant among the 3 groups (P=.31).

Conclusions

As evident from the results, it is anticipated that the ExoDont app will be helpful in circumventing the unaccounted possibilities of missing the prescribed dosage and postoperative instructions and ensuring the smooth recovery of patients after dental extraction. However, future studies are required to establish this app-based method of delivery of postoperative instructions as a viable option in routine clinical practice.
Continuous mHealth Patch Monitoring for the Algorithm-Based Detection of Atrial Fibrillation: Feasibility and Diagnostic Accuracy Study (Preprint)
Authors: Santala Onni E , Lipponen Jukka A , Jäntti Helena , Rissanen Tuomas T , Tarvainen Mika P , Laitinen Tomi P , Laitinen Tiina M , Castrén Maaret , Väliaho Eemu-Samuli , Rantula Olli A , Naukkarinen Noora S , Hartikainen Juha E K , Halonen Jari , Martikainen Tero J
Published: June 2022

BACKGROUND

The detection of atrial fibrillation (AF) is a major clinical challenge as AF is often paroxysmal and asymptomatic. Novel mobile health (mHealth) technologies could provide a cost-effective and reliable solution for AF screening. However, many of these techniques have not been clinically validated.

OBJECTIVE

The purpose of this study is to evaluate the feasibility and reliability of artificial intelligence (AI) arrhythmia analysis for AF detection with an mHealth patch device designed for personal well-being.

METHODS

Patients (N=178) with an AF (n=79, 44%) or sinus rhythm (n=99, 56%) were recruited from the emergency care department. A single-lead, 24-hour, electrocardiogram-based heart rate variability (HRV) measurement was recorded with the mHealth patch device and analyzed with a novel AI arrhythmia analysis software. Simultaneously registered 3-lead electrocardiograms (Holter) served as the gold standard for the final rhythm diagnostics.

RESULTS

Of the HRV data produced by the single-lead mHealth patch, 81.5% (3099/3802 hours) were interpretable, and the subject-based median for interpretable HRV data was 99% (25th percentile=77% and 75th percentile=100%). The AI arrhythmia detection algorithm detected AF correctly in all patients in the AF group and suggested the presence of AF in 5 patients in the control group, resulting in a subject-based AF detection accuracy of 97.2%, a sensitivity of 100%, and a specificity of 94.9%. The time-based AF detection accuracy, sensitivity, and specificity of the AI arrhythmia detection algorithm were 98.7%, 99.6%, and 98.0%, respectively.

CONCLUSIONS

The 24-hour HRV monitoring by the mHealth patch device enabled accurate automatic AF detection. Thus, the wearable mHealth patch device with AI arrhythmia analysis is a novel method for AF screening.

CLINICALTRIAL

ClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335
A Disease Identification Algorithm for Medical Crowdfunding Campaigns: Validation Study (Preprint)
Authors: Doerstling Steven S , Akrobetu Dennis , Engelhard Matthew M , Chen Felicia , Ubel Peter A
Published: June 2022

BACKGROUND

Web-based crowdfunding has become a popular method to raise money for medical expenses, and there is growing research interest in this topic. However, crowdfunding data are largely composed of unstructured text, thereby posing many challenges for researchers hoping to answer questions about specific medical conditions. Previous studies have used methods that either failed to address major challenges or were poorly scalable to large sample sizes. To enable further research on this emerging funding mechanism in health care, better methods are needed.

OBJECTIVE

We sought to validate an algorithm for identifying 11 disease categories in web-based medical crowdfunding campaigns. We hypothesized that a disease identification algorithm combining a named entity recognition (NER) model and word search approach could identify disease categories with high precision and accuracy. Such an algorithm would facilitate further research using these data.

METHODS

Web scraping was used to collect data on medical crowdfunding campaigns from GoFundMe (GoFundMe Inc). Using pretrained NER and entity resolution models from Spark NLP for Healthcare in combination with targeted keyword searches, we constructed an algorithm to identify conditions in the campaign descriptions, translate conditions to International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes, and predict the presence or absence of 11 disease categories in the campaigns. The classification performance of the algorithm was evaluated against 400 manually labeled campaigns.

RESULTS

We collected data on 89,645 crowdfunding campaigns through web scraping. The interrater reliability for detecting the presence of broad disease categories in the campaign descriptions was high (Cohen κ: range 0.69-0.96). The NER and entity resolution models identified 6594 unique (276,020 total) ICD-10-CM codes among all of the crowdfunding campaigns in our sample. Through our word search, we identified 3261 additional campaigns for which a medical condition was not otherwise detected with the NER model. When averaged across all disease categories and weighted by the number of campaigns that mentioned each disease category, the algorithm demonstrated an overall precision of 0.83 (range 0.48-0.97), a recall of 0.77 (range 0.42-0.98), an F1 score of 0.78 (range 0.56-0.96), and an accuracy of 95% (range 90%-98%).

CONCLUSIONS

A disease identification algorithm combining pretrained natural language processing models and ICD-10-CM code–based disease categorization was able to detect 11 disease categories in medical crowdfunding campaigns with high precision and accuracy.
Determinants of Digital Health Adoption: A Pilot Investigation of Uptake Patterns of mHealth (Preprint)
Authors: Patel Sharvil Piyush , Sun Elizabeth , Reinhardt Alec , Geevarghese Sanjaly , He Simon , Gazmararian Julie
Published: June 2022

BACKGROUND

Interest in and funding for digital health interventions have rapidly grown in recent years. Despite the increasing familiarity with mHealth from regulatory bodies, providers, and patients, overarching research on digital health adoption has been primarily limited to morbidity-specific and non-American samples.

OBJECTIVE

To describe uptake and utilization patterns of common digital health tools in Georgia and describe predictors of uptake.

METHODS

Online survey respondents in Georgia over 18 were recruited from mTurk to answer primarily closed-ended questions within the following domains: (1) participant demographics and health consumption background, (2) telehealth, (3) digital health education, (4) prescription management tools, (5) digital mental health services, and (6) doctor finder tools. Multivariate linear and logistic regressions were used to identify predictors of digital health tool usage.

RESULTS

A total of 362 respondents completed the survey. Private insurance, residence in an urban area, having a primary care provider, fewer urgent ER visits, more ER visits leading to inpatient stays, and chronic condition presence were significantly associated with the number of digital health tools used. The separate logistic regressions exhibited substantial variability with 3.5 statistically significant predictors per model, on average. Age, federal poverty level, number of PCP visits in the past 12 months, number of non-urgent ER visits in the past 12 months, number of urgent ER visits in the past 12 months, number of ER visits leading to inpatient stays in the past 12 months, race, gender, ethnicity, insurance, education, residential area, access to internet, difficulty accessing healthcare, usual source of care, status of PCP, and status of chronic condition all had at least one statistically significant relationship with use of a specific digital health category.

CONCLUSIONS

The results demonstrate that socioeconomically disadvantaged persons who would benefit the most from using certain tools do not adopt them at disproportionately higher rates than more advantaged populations. The variability of digital health adoption necessitates investing in and building a common framework to increase mHealth access. This likely will begin with a coordinated effort to determine barriers to adopting digital health solutions.
Remotely Delivered Cardiac Rehabilitation Exercise for Coronary Heart Disease (Preprint)
Authors: Giggins Oonagh Mary , Doyle Julie , Smith Suzanne , Vavasour Grainne , Moran Orla , Gavin Shane , Sojan Nisanth , Boyle Gordon
Published: June 2022

BACKGROUND

Exercise-based cardiac rehabilitation (CR) is recommended for coronary heart disease (CHD). However poor uptake of, and poor adherence to CR exercise programs have been reported globally. Delivering CR exercise classes remotely may remove some of the barriers associated with traditional hospital or center-based CR.

OBJECTIVE

We have developed a digital platform, ECME-CR to support remotely delivered CR exercise classes. This paper presents a pilot trial which was conducted to test this platform, to examine the efficacy of a remote CR exercise program, and to examine the feasibility of this approach.

METHODS

A sample of CHD participants (n = 21, 18 males; age: 69.5 ± 7.3 years; height: 168.5 ± 7.2cm; weight: 88.7 ± 16.7kg) were recruited and assigned to either an intervention or a control group. Both groups performed the same 8-week exercise program. Participants in the intervention group took part in online exercise classes, while participants in the control group attended in-person for their exercise classes. Intervention group participants used the ECME-CR platform for monitoring during the class and for self-management during the intervention period. Outcomes were assessed at baseline and following the 8-week intervention, with the primary outcome measure being exercise capacity.

RESULTS

Eight participants in the intervention group and nine participants in the control group completed the CR exercise program. Similar improvements in exercise capacity, the primary outcome measure, were observed in both the intervention and the control group after the 8-week intervention. These improvements were not significant and there was no significant difference observed between the groups.

CONCLUSIONS

A remotely delivered CR exercise program is not inferior to a traditional center-based CR exercise program in CHD participants.

INTERNATIONAL REGISTERED REPORT

RR2-10.2196/31855
ReWin - A digital therapeutic rehabilitation Innovation for people with stroke-related disabilities in India (Preprint)
Authors: Kamalakannan Sureshkumar , Karunakaran Vijay , Balaji Ashwin , Nagarajan Ramakumar
Published: June 2022

UNSTRUCTURED

Stroke has been the second leading cause of death and third-leading of disability globally for the past three decades. The emerging technological innovations for stroke care were predominantly designed and developed by digital technology experts as stand-alone products with very minimal efforts to explore their feasibility, acceptability, and more importantly scalability. Hence, a digital therapeutic rehabilitation Innovation for people with stroke-related disabilities in India was systematically developed and is being evaluated.

ReWin is an innovation that is technologically driven envisioning digital therapeutics as a medium for the provision of rehabilitation to persons with disabilities. It is conceptualized and developed based on the international classification of functioning disability and health. ReWin encompasses specific technological aspects to enable its scientific framework and conceptualization to suit the context and needs of the stroke care providers and consumers. The framework is built with two separate applications, one for the providers and one for the patients and caregivers. Each of these applications has the specific inbuilt design to add data about demographic details of the user, stroke severity using the National Institute of Health (NIH) stroke scale, and self-assessment of disability measured by the modified Barthel Index. Users can communicate with each other and decide on their therapeutic goals, therapy training information, and progress remotely from where they are.

The ultimate outcome expected from the ReWin innovation is a continuum of care for stroke survivors that is effective, safe, and of good quality. Systematic development cannot make the intervention scalable. The intervention needs to be evaluated for its feasibility, acceptability, and effectiveness. Currently, ReWin is evaluated for its feasibility and acceptability. This research will provide an opportunity to develop a scalable solution for empowering therapists and persons with disabilities, in general, to objectively self-manage their treatment. Findings from this study will also provide valuable information about the resources required to deliver such interventions in resource-constrained settings like India.
Optimization of High Yield Epoxidation of Malaysian Castor Bean Ricinoleic Acid with Performic Acid
Authors: Salih Nadia , Salimon Jumat
Published: June 2022

Epoxidized castor oil (ECO) has shown high potential for industrial applications as value-added products such as polymer coating, plasticizer, and biolubricant. Epoxidized ricinoleic acid recovered from ECO has potential for industrial usage. In this work, epoxidized ricinoleic acid (ERA) was synthesized through in situ generated performic acid epoxidation of ricinoleic acid (RA). The epoxidation process was optimized by several reaction parameters, such as the molar ratio of formic acid to ethylenic unsaturation, the molar ratio of hydrogen peroxide to ethylenic unsaturation, and reaction temperature. The response reaction parameters of oxirane oxygen content (OOC) and iodine value (IV) were then evaluated. The results showed the optimal condition for the epoxidation of RA was obtained at 50 °C, the molar ratio of formic acid and hydrogen peroxide to ethylenic unsaturation of 1:8:1 for 4 h reaction time. A high yield of ERA of 86% with relative conversion into oxirane of 85.3% was achieved at the optimum condition. The optimum ERA showed a high OOC value of 4.00% and a low IV value of 2.24 mg/g. It is plausible that ERA can be used as an intermediate starting material to prepare value-added products such as biosurfactants, biopolymer additives, or biolubricants.
Natural Magnetic Particles/Chitosan Impregnated with Silver Nanoparticles for Antibacterial Agents
Authors: Martha Annisa Afra , Permatasari Defia Indah , Dewi Elma Retna , Wijaya Nikho Asyoka , Kunarti Eko Sri , Rusdiarso Bambang , Nuryono Nuryono
Published: June 2022

In this research, silver nanoparticles (AgNP) impregnated on natural magnetic material/chitosan composite (NMP/Chi) have been conducted with different AgNP concentrations (0.5, 1.0, 1.5 mM). Their antibacterial activity was examined against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). The AgNP samples were characterized with UV-Vis spectrophotometer and TEM. The NMP/Chi/AgNP samples were identified with FTIR and XRD, while NMP/Chi/AgNP1.0 (with the highest antibacterial activity) were analyzed with TEM and SEM-EDX. The antibacterial test with a well-diffusion method showed that NMP/Chi/AgNP was categorized as a strong antibacterial agent. The composite showing the largest inhibition zone diameters was NMP/Chi/AgNP prepared using 1.0 M AgNO3, namely 14.39 and 16.8 mm against E. coli and S. aureus, respectively. Characterization of AgNP1.0 showed a spherical shape with an average particle diameter of 17.9 nm in suspension and 32.4 nm in NMP/Chi. The presence of 1000 mg/kg NMP/Chi/AgNP1.0 composite in water was able to reduce the growth of E. coli and S. aureus bacteria by 60.4% (from 5.3 to 2.1 CFU/mL) and 71.6% (from 6.34 to 1.86 CFU/mL), respectively, within 5 h. The NMP/Chi/AgNP1.0 showed an effective antibacterial agent against both bacteria (E. coli and S. aureus) and could be applied potentially in aquatic environments.
Synthesis of Mesoporous Silica from Beach Sand by Sol-Gel Method as a Ni Supported Catalyst for Hydrocracking of Waste Cooking Oil
Authors: Salamah Siti , Trisunaryanti Wega , Kartini Indriana , Purwono Suryo
Published: June 2022

Mesoporous silica (MS) supported by nickel was synthesized from Parangtritis beach sand and assessed for its activity and selectivity as catalysts in hydrocracking waste cooking oil into biofuel. The synthesis of MS was done by the sol-gel method. Ni/MS catalysts using Ni weight variations of 1, 5, and 10 wt.% were denoted as Ni/MS1, Ni/MS5, and Ni/MS10 and were compared to standard mesoporous silica (Ni/SBA-15). The catalysts were characterized using FTIR, XRD analysis, N2 gas sorption analysis, SEM-EDX, and TEM. Catalyst Ni/MS1, Ni/MS5, Ni/MS10, and Ni/SBA-15 have specific surface areas of 130.5, 195.9, 203.9, and 381.2 m2/g and the average pores of 12.30, 9.80, 11.12, and 8.70 nm, respectively. The hydrocracking was run four times to evaluate the catalyst reusability. The hydrocracking WCO has 95.8, 82.4, and 85.2%, respectively. While Liquid fractions produced were 38.8, 43.2, and 50.2 wt.%, each of which contains gasoline of 37.09, 39.76, and 44.27 wt.%, Ni/MS10 has the highest liquid products of 50.2 wt.% and was selective to gasoline fractions up to 44.27%. Therefore, the catalyst synthesized from Parangtritis beach sand is selective for gasoline-fraction hydrocarbon and has hydrocracking activity up to 4 runnings.
Evaluation of Influencing Factors and Technological Processes for the Production of Orange Essential Oil (Citrus sinensis) on Equipment Semi-industrial Distillation
Authors: Hien Tran Thien , Binh Hoang Quang , Long Huynh Bao , Le Xuan Tien
Published: June 2022

In recent years, essential oils extracted from different plant species have become increasingly popular in the production of pharmaceuticals, cosmetics, and foods. The essential oil from orange (Citrus sinensis) is important in large-scale applications due to its antibacterial, antioxidant activities, and pleasant aroma. In this study, factors affecting the production of orange essential oil on a distillation device with an operating capacity of 50 L/batch, including the ratio of material to water, temperature, and time distillation, have been surveyed. Through the survey, it was found that the raw materials were pureed, the materials: water ratio was 1:3 g/g, the water heating temperature was 130 °C, and the distillation time was 140 min. The yield of the essential oil was 1.8 mL/g with compounds limonene accounting for 98%, α-Pinene (0.655–0.734%), and β-Pinene (1.114 and 1.163%) by the GC-MS method. The review also found that the hydrodistillation equipment was designed to be suitable for the semi-industrial scales of orange essential oil due to its stable yield and volatile compounds contained in the essential oil.
Potential Adenostemma lavenia and Muntingia calabura Extracts to Inhibit Cyclooxygenase-2 Activity as a Therapeutic Strategy for Anti-inflammation: Experimental and Theoretical Studies
Authors: Tuwalaid Bagaskoro , Iswantini Dyah , Tri Wahyudi Setyanto
Published: June 2022

Continuous inflammation can cause new and more severe diseases, thus effective treatments are needed. One of the common inflammation treatments is given by reducing prostaglandins' production through the inhibition of COX-2 activity. This experiment aims to examine the potential application of plant extracts of Adenostemma lavenia and Muntingia calabura (Jamaica cherry) as anti-inflammatory agents in inhibiting COX-2 activity through in silico and in vitro assays. Molecular docking and molecular dynamics simulation were accomplished to evaluate the stability of the complex between COX-2 and ligands. The COX-2 inhibition was determined using the COX-2 Inhibitor Screening Assay KIT. Based on the docking results, the active compound from A. lavenia, ligand 1a,9b-dihydro-1H-cyclopropa[a]anthracene, has the lowest binding energy of -8.7 kcal/mol. In comparison, M. calabura contains 7-hydroxyflavone ligand with a Gibbs free energy of -9.1 kcal/mol. The molecular dynamics study demonstrates that COX-2 maintains its stability when forming interactions with selected compounds from all the tested extracts. The results of the COX-2 inhibition test showed that 96% EtOH extract of A. Lavenia at concentrations of 25 and 100 ppm had an inhibitory activity of 98%; meanwhile, 70% and 96% EtOH extracts of M. calabura at 1000 ppm concentration could inhibit COX-2 activity up to 100%. The results demonstrate that both plants show potential anti-inflammatory activity.
A New Flow Injection System with Merging-Zone Technique for the Determination of Copper(II) by Neocuproine Reagent in Aqueous Solution
Authors: Farhood Ahmed Saleh , Taha Dakhil Nassir
Published: June 2022

A fast, simple, and high throughput sample merging-zone flow injection design was developed to determine copper(II) in aqueous solution. The procedure is based on the reduction of copper(II) to copper(I) by uric acid followed by a direct reaction with Neocuproine reagent (NC). The orange-yellow complex that forms absorb light at 454 nm. All conditions of the new flow injection unit were investigated. The analytical curve of copper(II) was linear with (r2) value of 0.9978, in the range of 0.4 to 40 mg/L with a detection limit of 0.1 mg/L and a quantification limit of 0.3 mg/L. the molar absorptivity was 1.661 × 105 L/mol cm and the recovery range was between 104.9 and 97%. The homemade acrylic valve was low-cost with zero dead volume and high repeatability (n = 7) with an RSD of 2.31%. The dispersion coefficient values were 1.8,1.62, and 1.31 for the concentrations of 5, 15, and 25 mg/L, respectively. The sample throughput was 69 h–1.
Synthesis of Cassava Starch-Grafted Polyacrylamide Hydrogel by Microwave-Assisted Method for Polymer Flooding
Authors: Matovanni Maudy Pratiwi Novia , Distantina Sperisa , Kaavessina Mujtahid
Published: June 2022

Cassava starch-grafted polyacrylamide (CS-g-PAM) hydrogels were synthesized using a microwave-assisted method and K2O8S2 (KPS) as an initiator. In this study, we studied the influence of the amount of acrylamide and irradiation time on the properties of CS-g-PAM. The characterization of CS-g-PAM obtained was shown by Fourier-transform infrared (FTIR) and Scanning Electron Microscope (SEM) analysis. To predict the behavior of the samples under reservoir conditions, the properties of CS-g-PAM, such as swelling ratio, water-solubility, and viscosity were determined as a function of temperature, salt concentration, and aging time. The FTIR spectra and SEM analysis of the CS-g-PAM confirmed that the polyacrylamide chains were successfully grafted onto the cassava starch backbone. The results showed that the increasing amount of acrylamide and the longer irradiation time improved the properties of CS-g-PAM. Preparation of CS-g-PAM with 10 g of acrylamide and 180 s of irradiation time resulted in the highest grafting percentage and water solubility, which was 1565.53 and 96.06%, respectively. Its viscosity also exceeded 97% after 15 days of aging. The results showed that CS-g-PAM expressed properties such as good thickening, temperature resistance, and salt resistance according to reservoir conditions. This finding indicated that CS-g-PAM has good potential for oil recovery applications.