bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing the Impact of the Mindfulness-Based Body Scan Technique on Sleep Quality in Multiple Sclerosis Using Objective and Subjective Assessment Tools: Single-Case Study
Authors: Iliakis Ioannis , Anagnostouli Maria , Chrousos George 
Published: June 2024

Background
Multiple sclerosis (MS) is a chronic inflammatory disease affecting the central nervous system, often leading to poor sleep quality and diminished quality of life (QoL) for affected patients. Sleep disturbances in MS do not always correlate linearly with other symptoms such as anxiety, depression, fatigue, or pain. Various approaches, including stress reduction techniques such as mindfulness-based interventions, have been proposed to manage MS-related sleep issues.

Objective
The aim of this study was to evaluate the effects of the mindfulness-based body scan technique on sleep quality and QoL in patients with MS using both subjective (questionnaires) and objective (electronic portable device) measures.

Methods
A single-case study was performed involving a 31-year-old woman diagnosed with relapsing-remitting MS. The patient practiced the mindfulness-based body scan technique daily before bedtime and outcomes were compared to measures evaluated at baseline.

Results
The mindfulness-based body scan intervention demonstrated positive effects on both sleep quality and overall QoL. Biometric data revealed a notable dissociation between daily stress levels and sleep quality during the intervention period. Although self-report instruments indicated significant improvement, potential biases were noted.

Conclusions
While this study is limited to a single patient, the promising outcomes suggest the need for further investigation on a larger scale. These findings underscore the potential benefits of the mindfulness-based body scan technique in managing sleep disturbances and enhancing QoL among patients with MS.
Impacts of Clinical Decision Support Systems on the Relationship, Communication, and Shared Decision-Making Between Health Care Professionals and Patients: Multistakeholder Interview Study
Authors: Funer Florian , Schneider Diana , Heyen Nils B , Aichinger Heike , Klausen Andrea Diana , Tinnemeyer Sara , Liedtke Wenke , Salloch Sabine , Bratan Tanja 
Published: June 2024

Background
Clinical decision support systems (CDSSs) are increasingly being introduced into various domains of health care. Little is known so far about the impact of such systems on the health care professional–patient relationship, and there is a lack of agreement about whether and how patients should be informed about the use of CDSSs.

Objective
This study aims to explore, in an empirically informed manner, the potential implications for the health care professional–patient relationship and to underline the importance of this relationship when using CDSSs for both patients and future professionals.

Methods
Using a methodological triangulation, 15 medical students and 12 trainee nurses were interviewed in semistructured interviews and 18 patients were involved in focus groups between April 2021 and April 2022. All participants came from Germany. Three examples of CDSSs covering different areas of health care (ie, surgery, nephrology, and intensive home care) were used as stimuli in the study to identify similarities and differences regarding the use of CDSSs in different fields of application. The interview and focus group transcripts were analyzed using a structured qualitative content analysis.

Results
From the interviews and focus groups analyzed, three topics were identified that interdependently address the interactions between patients and health care professionals: (1) CDSSs and their impact on the roles of and requirements for health care professionals, (2) CDSSs and their impact on the relationship between health care professionals and patients (including communication requirements for shared decision-making), and (3) stakeholders’ expectations for patient education and information about CDSSs and their use.

Conclusions
The results indicate that using CDSSs could restructure established power and decision-making relationships between (future) health care professionals and patients. In addition, respondents expected that the use of CDSSs would involve more communication, so they anticipated an increased time commitment. The results shed new light on the existing discourse by demonstrating that the anticipated impact of CDSSs on the health care professional–patient relationship appears to stem less from the function of a CDSS and more from its integration in the relationship. Therefore, the anticipated effects on the relationship between health care professionals and patients could be specifically addressed in patient information about the use of CDSSs.
Effectiveness and Acceptability of Targeted Text Message Reminders in Colorectal Cancer Screening: Randomized Controlled Trial (M-TICS Study)
Authors: Vives Nuria , Travier Noemie , Farre Albert , Binefa Gemma , Vidal Carmen , Pérez Lacasta Maria Jose , Ibáñez-Sanz Gemma , Niño de Guzmán Ena Pery , Panera Jon Aritz , Garcia Montse ,   M-TICS Research Group
Published: June 2024

Background
Mobile phone–based SMS text message reminders have the potential to improve colorectal cancer screening participation rates.

Objective
This study assessed the effectiveness and acceptability of adding targeted SMS text message reminders to the standard procedure for those who picked up but did not return their screening kit at the pharmacy within 14 days in a colorectal cancer screening program in Catalonia, Spain.

Methods
We performed a randomized control trial among individuals who picked up a fecal immunochemical test (FIT) kit for colorectal cancer screening at the pharmacy but did not return it within 14 days. The intervention group (n=4563) received an SMS text message reminder on the 14th day of kit pick up and the control group (n=4806) received no reminder. A 30-day reminder letter was sent to both groups if necessary. The main primary outcome was the FIT completion rate within 30, 60, and 126 days from FIT kit pick up (intention-to-treat analysis). A telephone survey assessed the acceptability and appropriateness of the intervention. The cost-effectiveness of adding an SMS text message reminder to FIT completion was also performed.

Results
The intervention group had higher FIT completion rates than the control group at 30 (64.2% vs 53.7%; P<.001), 60 (78.6% vs 72.0%; P<.001), and 126 (82.6% vs 77.7%; P<.001) days. Participation rates were higher in the intervention arm independent of sex, age, socioeconomic level, and previous screening behavior. A total of 339 (89.2%) interviewees considered it important and useful to receive SMS text message reminders for FIT completion and 355 (93.4%) preferred SMS text messages to postal letters. We observed a reduction of US $2.4 per participant gained in the intervention arm for invitation costs compared to the control arm.

Conclusions
Adding an SMS text message reminder to the standard procedure significantly increased FIT kit return rates and was a cost-effective strategy. SMS text messages also proved to be an acceptable and appropriate communication channel for cancer screening programs.

Trial Registration
ClinicalTrials.gov NCT04343950; https://www.clinicaltrials.gov/study/NCT04343950

International Registered Report Identifier (IRRID)
RR2-10.1371/journal.pone.0245806
The Development of Problem-Based Learning Liveworksheets to Improve Mathematical Communication Skills on Junior High School Students
Authors: Nurjiah Tia , Minarti Eva Dwi , Fitiranna Aflich Yusnita 
Published: June 2024

Communication skill is an ability that needs to be possessed by students. Through communication, students can express their opinions or ideas to their friends or to the teacher. The facts in the field show that students' mathematical communication skills are in the low category, therefore a solution is needed to improve students' mathematical communication skills. This research aims to produce problem-based learning-based LKPD assisted by liveworksheets to hone students' mathematical communication skills. This research was conducted at SMPN 1 Ngamprah. The subjects of this study amounted to 10 students on a limited trial. 34 students for a broad trial. The method used is development research according to Sugiyono which is modified into 7 stages carried out due to time constraints, namely: potential and problems, data collection, product design, design validation, design revision, product trial, and product revision. Data collection tools for this study are validation sheets, student response questionnaires, and 5 questions about mathematical communication skills in statistics material. Based on the results of value processing from validators, it shows that the developed LKPD is said to be suitable for use in learning, with an average percentage of assessment from validators of 85%. The results of the calculation of student answers show that the developed LKPD is effective for improving mathematical communication skills, with an average calculation of each indicator of 72.35%. It can be concluded that problem-based learning-based LKPD assisted by liveworksheets can be used in learning as an effort to improve students' mathematical abilities in statistics material.
The Development of Problem Based Learning Canva-Assisted Teaching Materials to Improve Mathematical Probem Solving Ability on Integer
Authors: Fifiana Qistina , Bernard Martin , Yuliani Anik 
Published: June 2024

This study aims to define the process of developing educational materials in the form of workbooks for students across the entire document using a Canva-supported problem-based learning approach to determine the feasibility of educational materials developed, determine the effectiveness of the educational materials developed, and identify limitations. encountered by researchers during development. instructional materials, collect data on teaching materials, learning objectives to be achieved, and media used by students to date. The study also asked for information on whether school facilities support the learning process. The type of research used is research and development (R&D) with a 4D development model (Define, Design, Develop, Dissemination). The selected study site was MT Nurul Hidayah Batujajar. Due to the evolution of the educational material, especially in limited testing, the correct result is 89% with the most likely interprnal material is 83% with the interpretations very realistic and in extensive testing the confirmatory result is 91% with most likely interpretations, the actual result of the teaching material 86% with very realistic interpretations. The results of this study show that the process of developing teaching aids is well conducted. This study can be used as a reference for further studies as this study meets the very feasibility criteria.
A Real-Time Plasma Concentration Prediction Model for Voriconazole in Elderly Patients via Machine Learning Combined with Population Pharmacokinetics
Authors: Chen Yongchuan , Liu Ruixiang , Ma Pan , Shang Shenglan , Yu Mengchen , Xie Linli , Zhao Linlin , Huang Yifan 
Published: June 2024

Background Voriconazole (VCZ) is a first-line treatment drug for
invasive fungal disease, with narrow therapeutic window and significant
inter-individual variability. VCZ is primarily metabolized by liver,
which declines with age. For elderly patients, physiological and
pathological factors lead to more pronounced fluctuations in VCZ plasma
concentrations. Thus, it is crucial to establish a model that accurately
predicts VCZ plasma concentration in elderly patients. Methods A
retrospective study was performed incorporating 32 variables, including
population pharmacokinetics (PPK) parameters derived from the PPK model.
Recursive Feature Elimination with Cross-Validation was used for feature
selection. Multiple algorithms were selected and combined into an
ensemble model, and the model was interpreted by Shapley Additive
exPlanations. Results The predictive performance of machine learning was
greatly improved after inclusion of PPK parameters. The composition of
XGBoost, RF, and CatBoost (1:1:8) with the highest R2 (0.828) was
determined as the final ensemble model. Feature selection greatly
simplified the model from 31 variables to 9 variables without
compromising its performance. The R2, mean square error, mean absolute
error, and accuracy (± 30%) of external validation were 0.633, 1.094,
2.286, and 71.05%, respectively. Conclusions Our study is the first to
include PPK parameters as new factors for machine learning modeling to
predict VCZ plasma concentrations in elderly patients. The model
underwent optimization through feature selection. Our model provides a
reference for individualized dosing of VCZ in clinical practice,
enhancing the efficacy and safety of VCZ treatment in elderly patients.
Keywords: voriconazole, elderly patients, machine learning, population
pharmacokinetics, precision medicine
Retrieving seismic source characteristics using seismic and infrasound data: the 2020 mb 4.9 Kiruna minequake, Sweden
Authors: Turquet Antoine , Brissaud Quentin , Alvizuri Celso , Näsholm Sven Peter , Kero Johan , LePichon Alexis 
Published: June 2024

A minequake of magnitude m 4.9 occurred on 18 May 2020
early in the morning at the LKAB underground iron ore mine in Kiruna,
Sweden. This is the largest mining-induced earthquake in Scandinavia. It
generated acoustic signals observed at three infrasound arrays at 9.3
(KRIS, Sweden), 155 (IS37, Norway), and 286 km (ARCI, Norway) distance.
We perform full-waveform focal mechanism inversion based on regional
seismic data and local infrasound data. These independently highlight
that this event was dominated by a shallow-depth collapse in agreement
with in-mine seismic station data. However, regional infrasound data
cannot inform the inversion process without an accurate model of
atmospheric winds and temperatures. Yet, our numerical simulations
demonstrate a potential of using local and regional infrasound data to
constrain an event’s focal mechanism and depth.
Detecting slow slip signals in southwest Japan based on machine learning trained by real GNSS time series
Authors: Tanaka Yusuke , Kano Masayuki , Yano Keisuke 
Published: June 2024

With the increase in Global Navigation Satellite System (GNSS)
observations, the requirement for objective and automated detection of
slow slip event (SSE) signals hidden in displacement time series is
increasing. However, machine learning for GNSS time series has rarely
been attempted, primarily due to the smaller number of SSEs compared to
ordinary earthquakes, which renders it difficult to prepare training
data. In this study, we conducted a single-site SSE detection based on
machine learning trained by real GNSS observations of southwest Japan to
directly consider the complicated spatiotemporal characteristics of
observational noise. Based on a catalog of 284 short-term SSEs,
approximately 16,000 time series containing SSE signals or noises were
extracted as training data. The signal data predominantly had an
amplitude of 1.5–2.0 mm. The model architecture following the
Generalized Phase Detection, which was originally proposed for seismic
wave detection, was then adopted. We obtained an accuracy of 97–98%
for the test data. As expected, signals with smaller amplitudes showed a
higher frequency of false negatives. The true-positive ratio was highest
in the western Shikoku region, which had the largest signal amplitude.
In contrast, the false-positive ratio exhibited a nearly random spatial
distribution. False detection appears to be caused primarily by the
bends in the time series that resemble the onset or termination of the
SSE signal. The analysis of this study is expected to facilitate a
straightforward evaluation of the influence of noise characteristics on
the detection performance, and clarify the crucial topics to improve
detection precision.
Spatial Clustering Pattern of Wildfire Burning Risk in California, USA
Authors: Ibrahim Fahmina Binte , Binte Fahmina 
Published: June 2024

As wildfires in California, USA continue to cause a peril to the
population residing there, a clear insight into the spatial patterns and
distribution of wildfires is essential. This study aims to explore the
high-risk clusters and low risk clusters for wildfire hazard utilizing
the GIS tools and techniques along with Statistical modelling tool. By
using the up-to-date dataset, the neighborhood effect and spatial
relation among them from this study can be helpful for fire mitigation
measures and land use planning and building resilience of the community.
Also, the result from this study can contribute to strengthening
wildfire management strategies.
This study considers the Local Indicator of Spatial Autocorrelation and
Hotspot, cold spot analysis methods to identify the neighboring effects
and the clustering of the wildfire risks. An integrated approach using
GIS spatial analysis and Statistical analysis tools and techniques are
utilized. Data is collected from United States Department of Agriculture
(Scott et. al. 2020) research data set in the form of raster data.
The findings of the study show that regions with high-risk of burning
due to wildfire tend to cluster together, whereas regions with low risk
of burning exhibit a similar pattern of spatial correlation. This study
can be useful for identifying localized contributing factors for
wildfire as well as the hotspot for the hazard in California. Also,
spatial autocorrelation is essential for prioritizing risk areas and
resource allocation thus effective wildfire management together with
better community resilience.
Konten Dakwah dalam Youtube Pesulap Merah Production
Authors: Fadlan Muchammad 
Published: June 2024

Di era digital, saat internet semakin murah dan mudah di akses, interaksi masyarakat dengan dunia digital semakin meningkat. Salah satunya adalah akses konten Youtube, dengan berbagai tujuan, salah satunya adalah konten hiburan dengan sulap sebagai materinya. Pesulap Merah Production adalah salah satu kanal Youtube tersebut. Lebih menarik lagi kanal tersebut menggabungkan antara hiburan dan dakwah. Penelitian ini menekankan kepada bagaimana konten dakwah yang dilakukan Pesulap Merah melalui analisis konten Youtube Pesulap Merah Production. Dalam hasil penelitian sisipan dakwah dalam konten Pesulap Merah dianggap lebih mengena dan dapat diterima oleh pemirsa. Di tengah berbagai isu sensitive terkait permasalahan keimanan dan permasalahan sosial di masyarakat. Dengan 3,2 juta subscribe dan rata-rata 200 ribu pemirsa, perubahan sosial yang terjadi dimasyarakat, menjadi salah satu indikator dari keberhasilan dakwah tersebut
MANAGEMENT FOR GAPOKTANHUT LESTARI SEJAHTERA: INITIAL OPTIMIZATION ON ROBUSTA COFFEE DNA AMPLIFICATION FOR MOLECULAR SPECIES CONFIRMATION
Authors: Rustiati Elly Lestari , Priyambodo  , Pratiwi Dian Neli , Srihanto Eko Agus , Febriansyah Muhammad , Kusuma Andri Wijaya , Saswiyanti Enny , Susanto Alvin Wiwiet 
Published: June 2024

Gapoktanhut Lestari Sejahtera, a community engaged in coffee plantation practices within the community forests of the Forest Protection of Register 31 Pematang Arahan, Tanggamus, operates under the forest management unit, KPH Kotaagung Utara, Tanggamus, Lampung. In line with its commitment to biodiversity governance and the preservation and conservation of forest biodiversity, species confirmation, particularly for its robusta coffee, is deemed necessary. A leaf-based molecular species confirmation was proposed, a method yet to be conducted in Lampung. Therefore, prior to its molecular analysis, a preliminary study focusing on temperature optimization for robusta coffee DNA extraction for species confirmation was undertaken. This study was conducted under the DIPA BLU Unila Basic Research Grant in 2023, in collaboration with the Biotechnology Laboratory, Lampung Disease Investigation Center. Robusta coffee leaves were sampled from six forest farmer groups, KTH Bumi Mulyo, Sido Makmur 1, Sido Makmur 2, Sido Makmur 3, Mandiri Jaya, and Murah Rejeki 1, in collaboration with Gapoktanhut Lestari Sejahtera, Semaka, Tanggamus. The DNA extraction process adhered to the Genomic DNA Mini Kit (Plant) protocol (ISO 9001: 2008 QMS). DNA amplification was performed using the Polymerase Chain Reaction (PCR) method, utilizing the Coffea N-methyltransferases gene marker primer. The DNA analysis on robusta coffee leaf samples from Gapoktanhut Lestari Sejahtera demonstrated a good presence of DNA with an amplification temperature of 55°-60°C. To advance to the subsequent process, optimization of DNA extraction is required to yield improved results.
Design and Performance of Hold-on Type Sorghum Thresher for High Moisture Content
Authors: Nurhasanah Ana , Hermawan Wawan , Mandang Tineke , Unadi Astu , Budiharti Uning , Suparlan  , Susanto Herry , Amalia Anugerah Fitri , Sagita Diang , Widodo Teguh W. , Budiastuti Maria J. T. , Hidayat Muhammad , Samudiantono Arif , Nitamiwati Ni P. D. 
Published: June 2024

Abstract
Sorghum is a plant with broad adaptability, is resistant to drought, and is very suitable in marginal areas. Sorghum plants contain 7% to 17% seed composition and 83% to 93% leaf stems. At harvest, the moisture content of seeds is 20% to 30%, and the stem is around 76% to 88%. Several stages are carried out after the sorghum harvesting process, and one of them is threshing the sorghum seeds. The threshing of sorghum seeds requires a hold-on threshing machine so seeds can be threshed immediately after harvest, and the stems from sorghum plants can be chopped directly for cattle feed. This study aims to design and test the performance of a hold-on type sorghum threshing machine that can be used to thresh sorghum seeds immediately after harvesting at a grain moisture content of around 20% to 30%. The methods used include problem considerations, the preparation of structural designs, functional designs, manufacturing drawing designs, and manufacturing functional and performance testing. The results of testing the performance of the threshing machine revealed that the working capacity of the machine was affected by rod clamp rotation, the threshing cylinder, and the moisture content of sorghum seeds. The cleanliness level of sorghum seeds is above 90%, while the level of seed damage ranges from 0% to 1%.
Evaluating Required Heat Flow by Software Analyses in Greenhouses: Case Study of Iran
Authors: Fartash Naeimi Ehsan , Gürdil Gürkan Alp Kağan , Gálik Roman , Demirel Bahadır 
Published: June 2024

Abstract
The greenhouse sector is responsible for the largest proportion of total final energy consumption in agriculture. One effective method to reduce overall energy consumption in greenhouses is through an economical and efficient control strategy. In this study, a computer program was developed using the Visual Basic programming language to calculate the required heat flow for the growth and cultivation of greenhouse crops in most cities of Iran. The results indicated that the plastic covering material with double artificial plates was superior to other materials in maintaining internal heat. In the cities of Shiraz and Yazd, it was possible to cultivate pepper, tomato, cucumber, rose, lettuce, and strawberry with heat flow within the range of 0–24 kW and 0–30 kW, respectively. For colder cities such as Tabriz and Arak, the investigated parameter was calculated to be within the ranges of 24–70 kW and 17–63 kW, respectively. When comparing two other greenhouse covering materials, the minimum and maximum heat flow required for lettuce (glass with steel frame – Yazd and Shiraz) and rose cultivation (glass single plate – Tabriz) were observed to be 0 kW and 156.75 kW, respectively.