bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced arsenic removal using lateritic bauxite modified by heating and blending
Authors: Anang Emmanuella , Tei Meshack , Aduboffour Victor Kwabena 
Published: February 2022

Abstract
The use of bauxite to remove arsenic from wastewater has been confirmed to be effective, but its removal efficiency in literature is not up to 90%, hence the need to devise a more effective method to remove arsenic from wastewater. In this study, a novel material was prepared by thermally modifying and blending yellow and red lateritic bauxite to form thermally modified and blended yellow and red lateritic bauxite (TYB + TRB). The adsorption isotherm, morphology and chemical composition of the novel material were determined by the Langmuir and Freundlich models, Scanning Electron Microscopy (SEM) and X-ray Fluorescence (XRF), respectively. Application of the novel material in arsenic removal resulted in &gt;97% removal efficiency within 60 min. The arsenic adsorption by TYB + TRB conformed to the Freundlich model. The SEM image depicted a compacted earth material after use of the TYB + TRB to remove arsenic from the wastewater. The XRF results also showed a drastic reduction in the chemical composition of the novel bauxite except Ti, thus suggesting the occurrence of multiple mechanisms during the arsenic removal. This study demonstrated the potential of TYB + TRB to be developed and used as the most suitable material for wastewater treatment.
Investigation on water and air characteristics in Helicoidal Ramp Dropshafts
Authors: Zhang Shuangqing , Liu Hong , Liu Jiachun 
Published: February 2022

Abstract
Plunge dropshafts are widely used in urban drainage systems, but they can carry large amounts of air into the system, endangering the safety of the system. In this paper, a 3D numerical model is established to investigate the water flow configuration and air characteristics in a helicoidal ramp dropshaft. The simulations under different outlet pressures and water flow rates were simulated, and the results show that the air demand decreases with the increase of outlet pressure, especially in the case of low water flow. In the case of higher outlet pressure, the air demand first increases then decreases with the increase of the water flow rate. The dragging force of water has little effect on the pressure gradient in the dropshaft. The increase of ramp turns leads to the increase of terminal velocity at the same flow rate, and the air demand first increases and then decreases with the increase of ramp turns.
The link between organic matter composition and the biogas yield of full-scale sewage sludge anaerobic digestion
Authors: Liu Jin , Smith Stephen R. 
Published: February 2022

Abstract
The principal parameters influencing anaerobic digestion (AD) of sewage sludge have been extensively studied in controlled laboratory experiments, but the effects of sludge composition on full-scale systems have received relatively little attention. Sludge samples from eight major wastewater treatment plants (WWTPs) in the UK were examined to determine the effects of sludge composition on digestion performance. The biogas yield (BY) was estimated by two different methods: (1) a standard approach based on the reduction in volatile solids (VS), and (2) a more detailed mass balance of major constituent fractions of organic matter in sludge. The results showed that BY increased significantly with the overall amount of VS contained in digester feed sludge. In terms of the effects of individual fractions, BY was significantly related to and increased with the fat and cellulose contents in raw sludge, consistent with the high calorific value of fat and the digestibilities of both substrates, relative to the other major organic components. The results demonstrated the importance of sludge composition on digester performance and strategies to maximise BY were identified, for instance, by increasing codigestion of high fat containing substrates, and by utilising fat, oil and grease collected in-sewer and at WWTP.
An mHealth App to Support Caregivers in the Medical Management of Their Child With Cancer: Co-design and User Testing Study
Authors: Mueller Emily L , Cochrane Anneli R , Campbell Madison E , Nikkhah Sarah , Miller Andrew D 
Published: February 2022

Background
Caregivers face new challenges and tasks when their child is diagnosed with cancer, which can be overwhelming. Mobile technology has the capacity to provide immediate support at their fingertips to aid in tracking symptoms, managing medication, and planning for emergencies.

Objective
The objective of this study is to engage directly with end users and proxies to co-design and create a mobile technology app to support caregivers in the medical management of their child with cancer.

Methods
We engaged directly with caregivers of children with cancer and pediatric oncology nurse coordinators (proxy end users) to co-design and create the prototype of the Cope 360 mobile health app. Alpha testing was accomplished by walking the users through a series of predetermined tasks that encompassed all aspects of the app including tracking symptoms, managing medications, and planning or practicing for a medical emergency that required seeking care in the emergency department. Evaluation was accomplished through recorded semistructured interviews and quantitative surveys to capture demographic information and measure the system usability score. Interviews were transcribed and analyzed iteratively using NVivo (version 12; QSR International).

Results
This study included 8 caregivers (aged 33-50 years) of children with cancer, with most children receiving chemotherapy, and 6 nurse coordinators, with 3 (50%) of them having 11 to 20 years of nursing experience. The mean system usability score given by caregivers was 89.4 (95% CI 80-98.8). Results were grouped by app function assessed with focus on specific attributes that were well received and those that required refinement. The major issues requiring refinement included clarity in the medical information and terminology, improvement in design of tasks, tracking of symptoms including adjusting the look and feel of certain buttons, and changing the visual graph used to monitor symptoms to include date anchors.

Conclusions
The Cope 360 app was well received by caregivers of children with cancer but requires further refinement for clarity and visual representation. After refinement, testing among caregivers in a real-world environment is needed to finalize the Cope 360 app before its implementation in a randomized controlled trial.
Leveraging Machine Learning to Understand How Emotions Influence Equity Related Education: Quasi-Experimental Study
Authors: Sukhera Javeed , Ahmed Hasan 
Published: February 2022

Background
Teaching and learning about topics such as bias are challenging due to the emotional nature of bias-related discourse. However, emotions can be challenging to study in health professions education for numerous reasons. With the emergence of machine learning and natural language processing, sentiment analysis (SA) has the potential to bridge the gap.

Objective
To improve our understanding of the role of emotions in bias-related discourse, we developed and conducted a SA of bias-related discourse among health professionals.

Methods
We conducted a 2-stage quasi-experimental study. First, we developed a SA (algorithm) within an existing archive of interviews with health professionals about bias. SA refers to a mechanism of analysis that evaluates the sentiment of textual data by assigning scores to textual components and calculating and assigning a sentiment value to the text. Next, we applied our SA algorithm to an archive of social media discourse on Twitter that contained equity-related hashtags to compare sentiment among health professionals and the general population.

Results
When tested on the initial archive, our SA algorithm was highly accurate compared to human scoring of sentiment. An analysis of bias-related social media discourse demonstrated that health professional tweets (n=555) were less neutral than the general population (n=6680) when discussing social issues on professionally associated accounts (χ2 [2, n=555)]=35.455; P<.001), suggesting that health professionals attach more sentiment to their posts on Twitter than seen in the general population.

Conclusions
The finding that health professionals are more likely to show and convey emotions regarding equity-related issues on social media has implications for teaching and learning about sensitive topics related to health professions education. Such emotions must therefore be considered in the design, delivery, and evaluation of equity and bias-related education.
A Smart Mobile App to Simplify Medical Documents and Improve Health Literacy: System Design and Feasibility Validation
Authors: Hendawi Rasha , Alian Shadi , Li Juan 
Published: February 2022

Background
People with low health literacy experience more challenges in understanding instructions given by their health providers, following prescriptions, and understanding their health care system sufficiently to obtain the maximum benefits. People with insufficient health literacy have high risk of making medical mistakes, more chances of experiencing adverse drug effects, and inferior control of chronic diseases.

Objective
This study aims to design, develop, and evaluate a mobile health app, MediReader, to help individuals better understand complex medical materials and improve their health literacy.

Methods
MediReader is designed and implemented through several steps, which are as follows: measure and understand an individual’s health literacy level; identify medical terminologies that the individual may not understand based on their health literacy; annotate and interpret the identified medical terminologies tailored to the individual’s reading skill levels, with meanings defined in the appropriate external knowledge sources; evaluate MediReader using task-based user study and satisfaction surveys.

Results
On the basis of the comparison with a control group, user study results demonstrate that MediReader can improve users’ understanding of medical documents. This improvement is particularly significant for users with low health literacy levels. The satisfaction survey showed that users are satisfied with the tool in general.

Conclusions
MediReader provides an easy-to-use interface for users to read and understand medical documents. It can effectively identify medical terms that a user may not understand, and then, annotate and interpret them with appropriate meanings using languages that the user can understand. Experimental results demonstrate the feasibility of using this tool to improve an individual’s understanding of medical materials.
Prevalence and Age-Related Patterns in Health Information–Seeking Behaviors and Technology Use Among Skin Cancer Survivors: Survey Study
Authors: Marchetti Michael Armando , Sar-Graycar Liliane , Dusza Stephen W , Nanda Japbani K , Kurtansky Nicholas , Rotemberg Veronica M , Hay Jennifer L 
Published: February 2022

Background
Information is an unmet need among cancer survivors. There is a paucity of population-based data examining the health information–seeking behaviors and attitudes of skin cancer survivors.

Objective
We aimed to identify the prevalence and patterns of health information–seeking behaviors and attitudes among skin cancer survivors across age groups.

Methods
We analyzed population-based data from the 2019 Health Information National Trends Survey 5 (Cycle 3).

Results
The 5438 respondents included 346 (6.4%) skin cancer survivors (mean age 65.8 years); of the 346 skin cancer survivors, the majority were White (96.4% [weighted percentages]), and 171 (47.8%) were men. Most reported having ever looked for health- (86.1%) or cancer-related (76.5%) information; 28.2% stated their last search took a lot of effort, and 21.6% were frustrated. The internet was most often cited as being the first source that was recently used for health or medical information (45.6%). Compared to skin cancer survivors younger than 65 years old, those 65 years of age or older were more likely to see a doctor first for important health information (≥65 years: 68.3%;<65 years: 36.2%; P<.001) and less likely to have health and wellness apps (≥65 years: 26.4%; <65 years: 54.0%, P=.10), to have watched a health-related YouTube video (≥65 years: 13.3%; <65 years: 27.4%; P=.02), and to have used electronic means to look for information (≥65 years: 61.4%;<65 years: 82.3%, P<.001)

Conclusions
Searches for health information are common among skin cancer survivors, but behaviors and attitudes are associated with age, which highlights the importance of access to doctors and personalized information sources.
Deep Learning Skin Disease Classifiers: Current Status and Future Prospects
Authors: Gupta Somesh 
Published: February 2022

Background
Most studies on deep learning skin disease classifiers are done with binary classifications (ie, classifying lesions into malignant and benign). However, dermatology practice involves a large number of inflammatory and infective conditions that are not easily diagnosed by nondermatologist physicians.

Objective
The aim of this study is to develop a machine learning–based smartphone app for multiclass skin disease classification and evaluate its performance in different levels of dermatology practice. We will also explore similar studies in the literature.

Methods
We developed an artificial intelligence–driven smartphone app for 40 common skin diseases and tested it in primary care, tertiary care, and private practice settings.

Results
In the clinical study, the overall top-1 accuracy was 75.07% (95% CI 73.75%-76.36%), top-3 accuracy was 89.62% (95% CI 88.67%-90.52%), and the mean area under the curve was 0.90 (SD 0.07). Multimedia Appendix 1 shows the top-1 positive predictive values and negative predictive values from a clinical study of 35 diseases using the developed mobile health app on patients. In the literature, there are very few studies on image-based deep learning multiclass classification of common skin diseases and none of them included evaluations in actual clinical settings.

Conclusions
An artificial intelligence–driven smartphone app has the potential to improve the diagnosis and management of skin diseases in patients with skin of color. Nondermatologist, primary care physicians are likely to benefit from having access to such an app.

Acknowledgments
Nurithm Labs collaborated with the All India Institute Of Medical Science to develop this smartphone app. Other collaborators in this work include Rashi Pangti, Jyoti Mathur, Vikas Chouhan, Sharad Kumar, Lavina Rajput, Sandesh Shah, Atula Gupta, Ambika Dixit, Dhwani Dholakia, Sanjeev Gupta, Savera Gupta, Mariam George, and Vinod Kumar Sharma.

Conflicts of Interest
None declared.
Students’ Demotivating Factors in English Language Learning at One State Madrasah Tsanawiyah in Palembang, South Sumatera, Indonesia
Authors: ERLINA DIAN , DESVITASARI DETA , MARZULINA LENNY , MEIDA RISFINA ALMIRAH 
Published: February 2022

This research investigated students' demotivating factors in English language learning at MTsN 1 Palembang. The research was in the form of case study research design. The participants were the second-grade students at MTsN 1 Palembang. Based on their English achievement, there were 11 students being demotivated in learning English. The data were gained by using document review and face-to-face interviews. The data from document review and interview were analyzed by using thematic analysis. The findings showed that there were five demotivating factors in English language learning: (a) inadequate school facilities, (b) lack of teachers' competence and teaching styles, (c) learning content and materials, (d) classroom condition and classmates' attitudes, and (e) lack of self-confidence.

Keywords: demotivation, demotivating factors, English language learning
Learning Resource Development: An Online-Based Learning for Indonesian Teachers
Authors: SOFYAN SOFYAN , SINAGA DAMERIA , RUBIATI RUBIATI 
Published: February 2022

The purpose of this study was to develop an online-based learning resource for Indonesian language teachers. The development step started with the identification of learning objectives, learning process, analysis of learning resources and environments, formulation of specific objectives, design of assessment instruments and learning strategies, selection and development of teaching materials, design and evaluation of formative development projects, and making of good terms. The findings showed that the formative evaluations by experts showed the agreements of 89.23% from educational technology experts, 97.50% from material experts, and 90.00% from multimedia experts. The agreements informed that the online-based learning could be recommended for Indonesian language teachers. Furthermore, the average results of individual trials were 89.21%, small group trials (97.13%), and field trials (89.04%). The online-based learning resource established in this research and development study was feasible and useable. Implications of the findings are also discussed.
SISTEM KOMPUTERISASI ABSEN GURU DAN JADWAL MENGAJAR PADA SMK DARUL AMAL KOTA METRO
Authors: Mualim Imam 
Published: February 2022

SMK Darul Amal Kota Metro merupakan salah satu sekolah menengah kejuruan yang berdiri pada tahun 2008 terletak di Jl. Pesantren No.16B, Mulyojati, Kec. Metro Barat., Kota Metro, Lampung. Dalam pendataan absensi kehadiran maupun keterlambatan siswa dan guru masih dilakukan dengan manual yaitu dengan cara menuliskan kehadiran kedalam buku absensi yang telah disediakan oleh pihak sekolah. Dengan adanya permasalahan tersebut maka peneliti membangun sebuah sistem informasi tentang absensi guru, siswa dan penjadwalan matapelajaran berbasis web, dengan adanya sistem informasi ini maka informasi keterlambatan, ketidakhadiran siswa dan guru serta jadwal matapelajaran dapat dilihat pada website sekolah yang penulis rancang, tidak hanya itu data juga tersimpan dalam bentuk database sehingga pada saat rekapitulasi absensi dan penjadwalan mata pelajaran menjadilebih mudah.

SMK Darul Amal Kota Metro is a vocational high school which was founded in 2008, located on Jl. Pesantren No.16B, Mulyojati, Kec. West Metro., Metro City, Lampung. In data collection attendance and tardiness of students and teachers is still done manually, namely by writing attendance into the attendance book provided by the school. With these problems, the researcher built an information system about teacher, student attendance and web-based course scheduling, with this information system information on tardiness, student and teacher absence and course schedules can be seen on the school website that the author designed, not only that data. also stored in the form of a database so that at the time attendance recapitulation and scheduling of subjects becomes easier.
Pengembangan Dashboard Instrumen Akreditasi Program Studi Versi 4.0 (IAPS 4.0) Menggunakan Laravel Framework
Authors: Nadiya  
Published: February 2022

Status akreditasi suatu program studi merupakan cerminan kinerja dan menggambarkan mutu, efisiensi, serta relevansi suatu progrum studi yang diselenggarakan. Pada tahun 2018, terdapat pembaruan instrumen akreditasi institusi Program Studi (IAPS) yang semula IAPS versi 3.0 dengan 7 standar penilaian menjadi IAPS versi 4.0 dengan 9 standar penilaian. Untuk itu diperlukan pengembangan sistem informasi yang telah ada saat ini sesuai dengan kebutuhan IAPS 4.0. Pengembangan Dashboard Instrumen Akreditasi Program Studi ini dibangun dengan menggunakan metode rekayasa perangkat lunak yaitu Metode Prototype dengan menggunakan bahasa pemrograman PHP, Framework Laravel dan PostgreSQL sebagai database. Aplikasi ini dibuat berdasarkan pedoman Instrumen Akreditasi Program Studi 4.0 dari BAN-PT ( Badan Akreditasi Nasional Perguruan Tinggi ). Hasil akhir dari pengembangan sistem akreditasi ini berupa dokumen yang berisi data terkait akreditasi yang sesuai dengan masing-masing standar pada IAPS 4.0 seperti data kerjasama, mahasiswa, sumber daya manusia, keuangan, sarana dan prasarana, pendidikan, penelitian, pengabdian kepada masyarakat, serta luaran dan capaian tridharma. Berdasarkan pengujian dengan mengunakan metode blackbox testing didapat hasil uji 16 fitur berhasil di buat dan sistem telah diuji dengan metode pengujian User Experience Questionnaire (UEQ) yang memiliki 6 kategori yaitu daya tarik, kejelasan, efesiensi, ketepatan, stimulasi dan kebaruan dengan hasil uji mendapatkan nilai sangat baik..
Kata kunci — Instrumen Akreditasi Program Studi 4.0 (IAPS 4.0), Metode Prototype, PHP, Laravel, PostgreSQL.
Implementasi Monitoring Kualitas Udara menggunakan Sensor MQ-7 dan MQ-131 berbasis Internet Of Things
Authors: Dwi Prasetyo Dwi Prasetyo , Ibrahim Lamada Ibrahim Lamada , Wilma Nurrul Adzillah Wilma Nurrul Adzillah 
Published: February 2022

Pencemaran udara adalah suatu kondisi dimana kualitas udara menjadi rusak dan terkontaminasi oleh zat-zat, baik yang tidak berbahaya maupun yang membahayakan kesehatan manusia. Beberapa gas yang berbahaya di udara seperti : CO, CO2, O3 dan lainnya. Gas Karbon Monoksida (CO) tidak berbau dan tidak dapat dilihat mata, oleh karena itu manusia dan makhluk hidup lainnya tidak dapat mengetahui jika gas-gas tersebut ada di sekitarnya. Manusia bisa tahu jika sudah merasakan dampaknya.
Dalam hal ini telah dibuat satu alat pengukur kualitas udara yang dapat dibawa kemana-mana dengan mudah dan pengukuran secara real time yang digunakan untuk mengukur kualitas udara berdasarkan Indeks Standart Pencemaran Udara (ISPU). Menggunakan Sensor MQ-7 untuk mengukur gas karbon Monoksida (CO) dan MQ-131 untuk mengukur gas Ozon (O3).
The TEMPERATURE MEASURING HELMET BASED ARDUINO PROMINI WITH MLX90614-DCI SENSOR
Authors: Siddiq Wahyu Ja'far , Sulistiyowati Indah 
Published: February 2022

The Covid-19 pandemic that is currently spreading in Indonesia has claimed thousands of lives. Coronavirus Disease is characterized by the main clinical symptoms of fever >38 °C, coughing, to shortness of breath. In preventing its spread, the government conducts early detection by examining the main symptoms in the form of a fever and enforcing health protocols on each line. Therefore, we need an appropriate innovation that can make it easier for officers/guards to check human body temperature, especially in crowded places such as at airports, malls, or on the highway. Currently, body temperature measurement equipment is widely used, which allegedly made many errors in detecting it. Therefore, an innovative helmet was created that can be used by guards, security and even the police to detect body temperature based on the Arduino Pro Mini with the MLX90614-DCI sensor and the output is the real body temperature displayed on the LED screen. When the body temperature reads more than 38 °C, the helmet will turn on a buzzer and an LED to show that the target measurement is in a fever condition, and it is recommended going to the health center for further examination. This tool has been tested, and the sensor readings have an accuracy at a distance of 100 cm with several participants and the sensor readings are compared with the reading values from the alpha one thermometer and the measurement results have an accuracy level of 95%.
Keywords — Arduino Promini, Covid19, MLX90614-DCI, Infrared Thermometer.