bluuebunny/crossref_metadata_2025_split huggingface dataset:
SHU’UBATU KITABATI AL-JUMALI AL-‘ARABIYYATI LADA THULLABI MA’HADI MAWARIDISSALAM BATANGKAIS DELI SERDANG SUMATRA AL-SYIMALIYYAH
Authors: Rahmawati Baiq Laili , Nasution Alifuddin , Bahruddin Uril 
Published: January 2023

Abstract
This research is a research oriented to the analysis of difficulties in writing Arabic sentences in third grade students of Tsnawiyah Mawaridussalam, Batangkais, North Sumatra. The purpose of this study is to find out what difficulties are experienced by students, what factors cause these difficulties, and how they affect students. This study use descriptive qualitative research methods, while the data collection techniques use unstructured interviews and data analysis using the Miles and Huberman model, namely data reduction, presentation, and verification. The results of this study indicate that students still have difficulty in distinguishing letters that have a similar appearance and makharijul letters are similar. The influencing factors are divided into internal factors in the form of interest, motivation, and knowledge of students towards the mufradat and qaidah of Arabic writing and external factors in the form of environment, teachers, and infrastructure. These difficulties have an impact on students' academic achievement. This study shows that the difficulties and factors as well as the impact on the difficulty of writing Arabic for each person are different, but cannot be separated from the things that have been mentioned in the study.
Keywords: Difficulty, Writing Skills, Students, Learning Arabic

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Медіасоціалізація як компонент медіаосвіти
Authors: Венідіктов С. В. 
Published: January 2023

У статті показано, що стихійність медіасоціалізації проявляється через такі особливості: 1) брак усвідомлюваної суб’єктом мети; 2) суперечливість усвідомлюваних індивідом завдань медіасоціалізації; 3) неоднорідність компетентностей, що набуваються; 4) залежність від специфіки локального інформаційного середовища; 5) взаємообумовленість із завданнями основної активності в офлайн-середовищі; 6) брак точних хронологічних рамок; 7) неоднозначність з’ясування параметрів медіасоціалізованої особистості. Стихійний процес медіасоціалізації не суперечить загальному керованому характеру медіаосвіти, а доповнює його, формуючи нове медійне середовище, новий тип суб’єкта освітнього простору. Найбільш перспективним напрямом у статті визначено інтеграцію практик стихійної медіасоціалізації в медіаосвітні програми, що дозволить ефективно використати природний процес розвитку медійної грамотності та систематизувати необхідні компетентності.
«Мова перемоги» в інформаційному дискурсі війни
Authors: Супрун В. М. 
Published: January 2023

У статті йдеться про нове явище вітчизняного медіадискурсу, інспіроване широкомасштабною війною 2022 року, яке пропонуємо назвати «мовою перемоги». Установлено, що воно займає полярну позицію до вже відомого, добре дослідженого поняття «мова ворожнечі». З’ясовано, що механізм упливу «мови перемоги» на масову аудиторію має меліоративно позитивний, стимулюючий характер: реципієнт відчуває єднання, силу подолати будь-які перешкоди на шляху до перемоги, довгоочікуваного миру. Функціонуючи у межах єдиного інформаційного марафону, «мова перемоги» представлена різними ситуативними контекстами. Зазначено, що «мова перемоги» інспірує віру в непереможність української нації, абсолютизує служіння в ім’я захисту мирного життя на своїй землі.
Like an “espresso” but not like a “cappuccino”: landscape metrics are useful for predicting coffee production at the farm level, but not at the municipality level
Authors: Jeronimo Fernando , Varassin Isabela G. 
Published: January 2023

Abstract

Context
Coffee farms benefits from ecosystem services dependent on pollinators and pest predators. The flow of these biodiversity-based ecosystem services is regulated by landscape-scale processes. Therefore, the landscape structure in which coffee farms are inserted influence coffee production.
Objectives
The aim of this paper is to investigate how landscape structure can influence coffee production at different scales. We also evaluated the predictive utility of landscape metrics in a spatial (farm level) and aspatial approach (municipality level).
Methods
We tested the effect of six landscape metrics on coffee production for 25 farms and 30 municipalities in southern Brazil. For the farm level we calculate the metrics at 1 to 5 km radii from the farm's centroid for access its scale of effect. A model selection of Generalized Linear Model (GLM) was run for access the effect of landscape metrics on coffee production for both approaches (spatial and aspatial).
Results
We obtained that coffee production was negatively influenced by the landscape intensity index, while landscape diversity and the native forest patch density had a positive effect on production. All significant metrics had effects emerging within a 2 km radius at the farm level, but we had no effects at the municipality scale. Our findings suggest that the landscape composition in the immediate surroundings of coffee farms is useful to predict production in a spatially explicit approach. However, these metrics are not able to detect the effect of the landscape when analyzed in an aspatial approach. These findings highlight the importance of the landscape spatial structure, mainly the natural one, in the stability of coffee production.
Conclusions
This study enhanced the knowledge on the role of the landscape in coffee production dependence on landscape-level processes. This advance can help to improve the sustainability of land use and better planning of agriculture, ensuring food and economic safety. Besides, we offer a framework that can be applied to study any cropping system with available census data (spatialized or not).
Impacts of Lockdown Policy on Air Quality in Chinese Cities on Different Economic Levels during the COVID-19 Pandemic
Authors: Yu Nu , Zhang Xin , Zhang Yao , Zhang Mengya , Cui Yu , Chen Xieyang , Zhang Weiyi , Zhong Mingyuan , Li Haifeng 
Published: January 2023

Abstract
The sudden outbreak of the Corona Virus Disease 2019 (COVID-19) broke the stable trend of air quality improvement in Chinese cities due to the emergency response measures, such as the lockdown policy. In this study, 333 Chinese cities are divided into six levels by economic factors, such as first-tier, new first-tier, second-tier, third-tier, fourth-tier, and fifth-tier, and the time of each year was defined as pre-lockdown, lockdown and reopen periods. The results show that, during the pre-lockdown period, the concentrations of NO2 and PM2.5 decreased by 10.13% and 6.15%, respectively, compared with the same period averages in 2017–2019. The fifth-tier cities have the minimum reductions of NO2 and PM2.5. The lockdown policy has significantly improved the air quality in Chinese cities during the COVID-19 pandemic. The concentrations of NO2 and PM2.5 decreased by 42.38% and 29.34%, respectively, but the air quality of first-tier cities was least affected by lockdown. During the reopen period, the concentrations of NO2 and PM2.5 decreased by 14.28% and 25.71%, respectively, and the NO2 concentrations in each city are similar for the season. The NO2 and PM2.5 concentrations in 2020 without lockdown were estimated through a multivariate linear regression model. The actual values of both NO2 and PM2.5 concentrations during the lockdown period are lower than the projected values based on the 2017–2019 trend, again indicating that the lockdown policy influences their concentrations.
Innate immune activation and white matter injury in a rat model of neonatal intraventricular hemorrhage are dependent on developmental stage
Authors: Zamorano Miriam , Olson Scott D. , Haase Candice , Cox Charles S. , Miller Brandon A. 
Published: January 2023

Abstract
Background: Inflammation and white matter injury are consequences of neonatal intraventricular hemorrhage (IVH). Both white matter and the neuroimmune system are developing during which IVH and its consequences occur. IVH has been studied in many different animal models; however, the effects of IVH occurring at different developmental time points in the same model has not been examined. Examining how the timing of IVH affects the ultimate outcome of IVH may provide important insights into IVH pathophysiology.
Methods: We used intraventricular injection of lysed whole blood to model neonatal IVH in postnatal day (P)2 and P5 rats. Flow cytometry was used to detect innate immune activation. MRI was used to screen animals for the development of increased ventricular size. Immunohistochemistry for myelin basic protein was used to assess white matter pathology.
Results: The acute response of the innate immune system at these time points differed, with P5 animals exhibiting significant increases in several measures of classically pro-inflammatory innate immune activation that P2 animals did not. Animals with IVH induced at P5 also developed ventricular enlargement visible on MRI whereas animals with IVH induced at P2 did not. On histological analysis, there were no significant effects of IVH in P2 animals, but IVH in P5 animals induced a reduction in several measures of white matter integrity.
Conclusions: IVH induces a strong innate inflammatory response in P5 animals that correlates with changes in ventricular size and white matter. P2 animals did not exhibit any significant changes in innate immune activation or white matter structure after IVH. This suggests that the white matter pathology from IVH is due in part to innate immune activation; and that the developmental stage of the innate immune system is a key determinant of IVH pathology.
Modelling a change in potential in an electromagnetic coil for small changes in head pose inside MR scanner.
Authors: Bhuiyan Enamul H. , Spencer Glyn S. , Glover Paul M. , Bowtell Richard W. 
Published: January 2023

Abstract
Purpose: A linear model is used for characterising the relationship between head pose and the induced voltages in a set of five coils in an initial set of imaging experiments, and subsequently using this relationship to calculate changes in head pose inside MR scanner from the measured voltages.
Methods: To monitor position, we used an MR-compatible EEG amplifier system (Brain Products GmbH) to measure the voltage induced in the five coils by three gradient pulses successively applied along the right-left (RL), anterior-posterior (AP) and foot-head (FH) directions. Each pulse had ramp up and down periods of 5 ms at a rate of 2 Tm−1 s −1 inducing voltages of a few mV in the coils. The position (z) and orientation (ϕ, ψ) of the phantom was also measured by using SPM to co-register Fast Field Echo (FFE) images. The resulting model used to identify the phantom position from the voltage measurements and the results compared to parameters identified using the SPM registration.
Results: The small differences in the position parameters estimated from the measured voltages in the coils and from the image corregistration by SPM8 indicate that the measurements of gradient-induced voltages in coils can provide accurate estimates of movement parameters.
Conclusions: Initial results reveals potential utility of modelling a change in induced voltage in an inductive coil for monitoring small changes in head pose inside MR scanner.
Allocation concealment appraisal of clinical therapy trials using the extended Composite Quality Score (CQS-2): An empirically based update (Protocol)
Authors: Mickenautsch Steffen , Yengopal Veerasamy 
Published: January 2023

Abstract
Objectives: To revise CQS-2/Criterion II, concerning allocation concealment appraisal for prospective, controlled, clinical therapy trials.

Methods: Meta-analyses of trials with inadequate allocation concealment will be tested for in-between trial heterogeneity (I2 > 0) due to imbalances in baseline variables. Meta-analyses with positive test results will be used as basis to infer criteria for adequate allocation concealment. The CQS-2/Criterion II will be reformulated in line with the findings. The revised appraisal tool will be specified as CQS-2B

Reporting: The final report will be made available online as preprint in one of the major preprint repositories and submitted to a peer-reviewed journal.
EU funds absorption for Romanian rural municipalities: a spatial distribution
Authors: Marin Anca Monica , Glăvan Eugen , Chiș Alin , Corad Bogdan 
Published: January 2023

Abstract

This study analyzes the spatial differences inEU fundsabsorption among Romanian rural municipalities through the 2014-2020 programming period. The absorption capacity for EU funds is measured by the volume of spent EU funds by inhabitant, for each Romanian rural municipality. The results of the analysis highlight the importance of the territorial dimension when studying the distribution of EU funds among the rural municipalities of Romania. Affiliation with a specific development region (NUTS 2), county (NUTS 3) or a functional urban area (FUA) is used to differentiate the volume of absorbed EU funds. Levels of fiscal capacity, locality development, EU and state budget funding experience, and population dynamics in 2021 compared to those in 2014 are also used to distinguish between categories of municipalities receiving EU funds. In Romania, rural municipalities with higher levels of absorbed EU funding are, to a statistically higher extent, located in development regions in the Center, North‒West, South West and West of the country; in communes with no change, or even an increase, in population between 2021 and 2014; in the highest quartile of fiscal capacity and in communes with experience with EU funding from the preceding programming period. This article adds to the growing body of territorial evidence and can be used as a policy instrument to more closely examine the intervention tools embedded in EU funding policy. From a systemic approach, the results of the analysis are valuable forthe design of integrated place-based strategies for EU, national and local level stakeholders, with the ultimate goal of improving quality of life for citizens living in rural areas.
Karakteristik Pengajaran Ilmu Pengetahuan Sosial di Sekolah Menengah Pertama
Authors: Yunhadi Wuwuh 
Published: January 2023

A misleading conception of teaching-learning Sosial Sciences for elementary and secondary school in Indonesia has widely occurred. Social Science lesson is considered simple, from which learning is basically a recall and comprehension of a text, and the teaching model is simply providing students with textbook for reading. Similar to other lessons, the substance of IPS is obviously hard to teach. People change as well as the social life. Those changes are leading the changing of social science. Learning social science tries to understand those changing. The understanding of social science will help the learners, particularly young people, make reasonable decisions for public goods as citizens to live together and participate in social life.
Penerapan Strategi Pembelajaran Inkuiri terhadap Hasil Belajar IPA Fisika di SMP Muhammadiyah 3 Samarinda
Authors: Saparuddin Muhammad 
Published: January 2023

Strategi inkuiri adalah proses pembelajaran dimana siswa aktif mencari dan menyelidiki secara sistematis, kritis, logis, analitis, sehingga siswa dapat menemukan sendiri pengetahuan yang diperolehnya. Penelitian ini bertujuan untuk mengetahui hasil belajar dan aktivitas siswa dengan menggunakan strategi pembelajaran inkuiri. Penelitian ini dilaksanakan di SMP Muhammadiyah 3 Samarinda dan sampel penelitian adalah siswa kelas VIII-B yang berjumlah 25 siswa. Pendekatan penelitian yang digunakan adalah eksperimen semu. Hasil belajar siswa diukur menggunakan instrument tes hasil belajar berupa post test sedangkan aktivitas siswa diukur dengan menggunakan lembar observasi dengan satu pengamat. Berdasarkan hasil analisis seluruh siswa mendapatkan nilai diatas KKM yaitu 82,40 dan aktivitas siswa dikelas baik dalam kegiatan individu maupun kelompok, jadi penerapan strategi pembelajaran inkuiri terbilang baik.
Application of Artificial Intelligence to the Monitoring of Medication Adherence for Tuberculosis Treatment in Africa: Algorithm Development and Validation
Authors: Sekandi Juliet Nabbuye , Shi Weili , Zhu Ronghang , Kaggwa Patrick , Mwebaze Ernest , Li Sheng 
Published: January 2023

Background
Artificial intelligence (AI) applications based on advanced deep learning methods in image recognition tasks can increase efficiency in the monitoring of medication adherence through automation. AI has sparsely been evaluated for the monitoring of medication adherence in clinical settings. However, AI has the potential to transform the way health care is delivered even in limited-resource settings such as Africa.

Objective
We aimed to pilot the development of a deep learning model for simple binary classification and confirmation of proper medication adherence to enhance efficiency in the use of video monitoring of patients in tuberculosis treatment.

Methods
We used a secondary data set of 861 video images of medication intake that were collected from consenting adult patients with tuberculosis in an institutional review board–approved study evaluating video-observed therapy in Uganda. The video images were processed through a series of steps to prepare them for use in a training model. First, we annotated videos using a specific protocol to eliminate those with poor quality. After the initial annotation step, 497 videos had sufficient quality for training the models. Among them, 405 were positive samples, whereas 92 were negative samples. With some preprocessing techniques, we obtained 160 frames with a size of 224 × 224 in each video. We used a deep learning framework that leveraged 4 convolutional neural networks models to extract visual features from the video frames and automatically perform binary classification of adherence or nonadherence. We evaluated the diagnostic properties of the different models using sensitivity, specificity, F1-score, and precision. The area under the curve (AUC) was used to assess the discriminative performance and the speed per video review as a metric for model efficiency. We conducted a 5-fold internal cross-validation to determine the diagnostic and discriminative performance of the models. We did not conduct external validation due to a lack of publicly available data sets with specific medication intake video frames.

Results
Diagnostic properties and discriminative performance from internal cross-validation were moderate to high in the binary classification tasks with 4 selected automated deep learning models. The sensitivity ranged from 92.8 to 95.8%, specificity from 43.5 to 55.4%, F1-score from 0.91 to 0.92, precision from 88% to 90.1%, and AUC from 0.78 to 0.85. The 3D ResNet model had the highest precision, AUC, and speed.

Conclusions
All 4 deep learning models showed comparable diagnostic properties and discriminative performance. The findings serve as a reasonable proof of concept to support the potential application of AI in the binary classification of video frames to predict medication adherence.
Primary Perspectives in Meme Utilization as a Digital Driver for Medical Community Engagement and Education Mobilization: Pre-Post Study
Authors: Wang Darrel , Balapal Neha , Ankem Amala , Shyamsundar Saishravan , Balaji Adarsh , Kannikal Jasmine , Bruno Marlie , He Shuhan , Chong Paul 
Published: January 2023

Background
Memes have gone “viral,” gaining increasing prominence as an effective communications strategy based on their unique ability to engage, educate, and mobilize target audiences in a call to action through a cost-efficient and culturally relevant approach. Within the medical community in particular, visual media has evolved as a means to influence clinical knowledge transfer. To this end, the GetWaivered (GW) project has leveraged memes as part of a behavioral economics toolkit to address one of the most critical public health emergencies of our time—the 20-year opioid epidemic. As part of a multidimensional digital awareness campaign to increase Drug Enforcement Administration (DEA)-X waiver course registration, GW investigated the results of meme usage in terms of impressions, website traffic, and ultimately user acquisition, as determined by web-based training enrollment and attendance outcomes.

Objective
The objective of this study was to determine the efficacy of implementing humor-based promotional content versus the traditional educational model, and how the translation of the increase in engagement would increase the participant count and website traffic for GW’s remote DEA-X waiver training.

Methods
The approach to this study was based on 2 time frames (pre- and postcampaign). During April-July 2021, we developed a campaign via advertisements on Facebook, Twitter, Instagram, and the GW website to expand outreach. These memes targeted medical professionals with the ability to prescribe buprenorphine. The time frame of this campaign measured engagement metrics and compared values to preceding months (January-March 2021) for our GetWaivered website and social media pages, which translated to registrants for our remote DEA-X waiver training.

Results
By the end of July 2021, a total of 9598 individuals had visited the GW website. There was an average of 79.3 visitors per day, with the lowest number of daily visitors being 0 and the highest being 575.

Conclusions
The use of memes may provide a medium for social media engagement (likes, comments, and shares) while influencing viewers to pursue a proposed action, such as e-training registration.