bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antimicrobial Activity of Bioactive Compounds Isolated from Plant
Endophytes
Authors: Chhillar Anil Kumar , Kumari Sudesh , Gulia Prity , Sharma Namita , Dahiya Sweety , Choudhary Pooja 
Published: May 2022

Abstract:
To combat the escalating antimicrobial resistance, we need to develop new medications constantly. Recently, scientists more focused on endophytes to search for novel antimicrobial natural products. Endophytes are explored as 'bio-factories' of natural bioactive therapeutic compounds. These are microbes exhibited in plant living tissues without causing any harmful effect.Many therapeutic compounds isolated from endophytes are produced from biosynthetic pathways and belong to various structural groups like terpenoids, steroids, quinines, and phenols. Therapeutic compounds produced by endophytes exhibit different pharmacological properties. Fungal genera more commonly reside to plant tissue as compared to bacterial genera. The current review emphasizes comprehensive data on the antibacterial and antifungal activity and bio-therapeutic compounds produced by fungal and bacterial endophytes of some medicinal plants.
Predicting Rainfall-induced Landslide Using Bee Colony Algorithm Based
on Support Vector Regression
Authors: Lee Zne-Jung , Luo Xianxian 
Published: May 2022

Objective:
Natural disasters caused by landslides have done great harm to agricultural
production, people's lives, and property. Considering the slope disaster caused by heavy
rainfall, it is important to establish an early warning system to monitor rainfall disaster
prevention. Huafang University Slope Sustainable Development Research Center (HUSSDRC)
has set up a meteorological station equipped with many sensors to provide early warning for
landslides in Taiwan. Since the amount of data collected will soon become very large, there is a
need to implement strong parallel frameworks containing information from the meteorological
station and the displacement of tiltmeters required to predict the landslides caused by rainfall.
Apache Spark (AS) is a general framework that contains the parallel process engine for data
analytics. In this study, a hybrid method is utilized to predict rainfall-induced landslides. The
proposed method combines support vector regression (SVR) with an artificial bee colony (ABC)
algorithm on the parallel platform of AS. For the proposed method, the RMSE is 0.562, and it is
the best value among these compared approaches.

Methods:
The SVR together with an ABC algorithm is applied to predict rainfall-induced
landslides on AS. The AS can perform parallel data analytics in memory to speed up
performance. However, it is hard to set up the best parameters for SVR. Thereafter, the ABC
algorithm is utilized to search for the best parameters for SVR.

Results:
Compared with other methods, the proposed method results provide the smallest root
mean square error (RMSE) for predicting rainfall-induced landslides.

Conclusion:
A hybrid method is proposed to predict rainfall-induced landslides. The proposed
hybrid method is based on the parallel platform of AS in which SVR predicts the rainfall-induced
landslides, and the ABC algorithm adjusts the best values of parameters for SVR. The
comparison of RMSE for the method with existing approaches shows that the method indeed has
the best value among compared approaches.
Functional and Technical Aspects of Self-management mHealth Apps: Systematic App Search and Literature Review
Authors: Alwakeel Lyan , Lano Kevin 
Published: May 2022

Background
Although the past decade has witnessed the development of many self-management mobile health (mHealth) apps that enable users to monitor their health and activities independently, there is a general lack of empirical evidence on the functional and technical aspects of self-management mHealth apps from a software engineering perspective.

Objective
This study aims to systematically identify the characteristics and challenges of self-management mHealth apps, focusing on functionalities, design, development, and evaluation methods, as well as to specify the differences and similarities between published research papers and commercial and open-source apps.

Methods
This research was divided into 3 main phases to achieve the expected goal. The first phase involved reviewing peer-reviewed academic research papers from 7 digital libraries, and the second phase involved reviewing and evaluating apps available on Android and iOS app stores using the Mobile Application Rating Scale. Finally, the third phase involved analyzing and evaluating open-source apps from GitHub.

Results
In total, 52 research papers, 42 app store apps, and 24 open-source apps were analyzed, synthesized, and reported. We found that the development of self-management mHealth apps requires significant time, effort, and cost because of their complexity and specific requirements, such as the use of machine learning algorithms, external services, and built-in technologies. In general, self-management mHealth apps are similar in their focus, user interface components, navigation and structure, services and technologies, authentication features, and architecture and patterns. However, they differ in terms of the use of machine learning, processing techniques, key functionalities, inference of machine learning knowledge, logging mechanisms, evaluation techniques, and challenges.

Conclusions
Self-management mHealth apps may offer an essential means of managing users’ health, expecting to assist users in continuously monitoring their health and encourage them to adopt healthy habits. However, developing an efficient and intelligent self-management mHealth app with the ability to reduce resource consumption and processing time, as well as increase performance, is still under research and development. In addition, there is a need to find an automated process for evaluating and selecting suitable machine learning algorithms for the self-management of mHealth apps. We believe that these issues can be avoided or significantly reduced by using a model-driven engineering approach with a decision support system to accelerate and ameliorate the development process and quality of self-management mHealth apps.
Age- and Sex-Specific Association Between Vegetation Cover and Mental Health Disorders: Bayesian Spatial Study
Authors: Abdullah Abu Yousuf Md , Law Jane , Perlman Christopher M , Butt Zahid A 
Published: May 2022

Background
Despite growing evidence that reduced vegetation cover could be a putative risk factor for mental health disorders, the age- and the sex-specific association between vegetation and mental health disorder cases in urban areas is poorly understood. However, with rapid urbanization across the globe, there is an urgent need to study this association and understand the potential impact of vegetation loss on the mental well-being of urban residents.

Objective
This study aims to analyze the spatial association between vegetation cover and the age- and sex-stratified mental health disorder cases in the neighborhoods of Toronto, Canada.

Methods
We used remote sensing to detect urban vegetation and Bayesian spatial hierarchical modeling to analyze the relationship between vegetation cover and mental health disorder cases. Specifically, an Enhanced Vegetation Index was used to detect urban vegetation, and Bayesian Poisson lognormal models were implemented to study the association between vegetation and mental health disorder cases of males and females in the 0-19, 20-44, 45-64, and ≥65 years age groups, after controlling for marginalization and unmeasured (latent) spatial and nonspatial covariates at the neighborhood level.

Results
The results suggest that even after adjusting for marginalization, there were significant age- and sex-specific effects of vegetation on the prevalence of mental health disorders in Toronto. Mental health disorders were negatively associated with the vegetation cover for males aged 0-19 years (−7.009; 95% CI −13.130 to −0.980) and for both males (−4.544; 95% CI −8.224 to −0.895) and females (−3.513; 95% CI −6.289 to −0.681) aged 20-44 years. However, for older adults in the 45-64 and ≥65 years age groups, only the marginalization covariates were significantly associated with mental health disorder cases. In addition, a substantial influence of the unmeasured (latent) and spatially structured covariates was detected in each model (relative contributions>0.7), suggesting that the variations in area-specific relative risk were mainly spatial in nature.

Conclusions
As significant and negative associations between vegetation and mental health disorder cases were found for young males and females, investments in urban greenery can help reduce the future burden of mental health disorders in Canada. The findings highlight the urgent need to understand the age-sex dynamics of the interaction between surrounding vegetation and urban dwellers and its subsequent impact on mental well-being.
Potential of Online Recruitment Among 15-25-Year Olds: Feasibility Randomized Controlled Trial
Authors: Hoffmann Sofie Have , Paldam Folker Anna , Buskbjerg Mark , Paldam Folker Marie , Huber Jezek Andrea , Lyngsø Svarta Durita , Nielsen Sølvhøj Ida , Thygesen Lau 
Published: May 2022

Background
Recruiting young people for health and intervention studies by traditional methods has become increasingly challenging. The widespread access to the internet may offer new strategies for online recruitment.

Objective
This study aims to assess the feasibility of online recruitment for a randomized controlled trial evaluating the effectiveness of Mindhelper, an online national youth mental health promotion service. The target group was young Danes aged 15-25 in need of mental health promotion.

Methods
Advertisements for recruitment were set up on Facebook and Instagram. Browser history was collected for a subsample of participants. We compared basic characteristics of participants who completed the baseline survey and those who did not, as well as of participants who completed the follow-up survey and those who were lost to follow-up. The significance of these differences was tested with the Pearson chi-square test.

Results
A total of 560 Danes aged 15-25 were recruited within 1 month (ie, had completed the baseline survey). Among these participants, 356 (63.6%) were at risk of developing depression or stress. The average advertisement price per participant completing the baseline questionnaire was 31 DKK (approximately €4 [US $4.2]). The follow-up survey was sent to 545 participants, of whom 318 (58.3%) completed the survey. No statistically significant differences were observed in baseline characteristics of participants who completed the follow-up and those who were lost to follow-up in terms of gender (P=.45), age (P=.35), occupation (P=.17), cohabitation (P=.90), mental well-being (P=.26), mental illness (P=.44; impact of the illness, P=.05), or use of the internet when having a hard time (P=.92).

Conclusions
We conclude that it is feasible to recruit young Danes online for a large-scale randomized controlled trial assessing the effectiveness of Mindhelper.

Trial Registration
ClinicalTrials.gov NCT04650906; https://clinicaltrials.gov/ct2/show/NCT04650906
Assessing the Views and Needs of People at High Risk of Gestational Diabetes Mellitus for the Development of Mobile Health Apps: Descriptive Qualitative Study
Authors: Duan Beibei , Liu Zhe , Liu Weiwei , Gou Baohua 
Published: May 2022

Background
Early prevention of gestational diabetes mellitus (GDM) can reduce the incidence of not only GDM, but also adverse perinatal pregnancy outcomes. Moreover, it is of great significance to prevent or reduce the occurrence of type 2 diabetes. Mobile health (mHealth) apps can help pregnant women effectively prevent GDM by providing risk prediction, lifestyle support, peer support, professional support, and other functions. Before designing mHealth apps, developers must understand the views and needs of pregnant women, and closely combine users’ needs to develop app functions, in order to better improve user experience and increase the usage rate of these apps in the future.

Objective
The objective of this study was to understand the views of the high-risk population of gestational diabetes mellitus on the development of mobile health apps and the demand for app functions, so as to provide a basis for the development of gestational diabetes mellitus prevention apps.

Methods
Fifteen pregnant women with at least one risk factor for gestational diabetes were recruited from July to September 2021, and were interviewed via a semistructured interview using the purpose sampling method. The transcribed data were analyzed by the traditional content analysis method, and themes were extracted.

Results
Respondents wanted to develop user-friendly and fully functional mobile apps for the prevention of gestational diabetes mellitus. Pregnant women's requirements for app function development include: personalized customization, accurate information support, interactive design, practical tool support, visual presentation, convenient professional support, peer support, reasonable reminder function, appropriate maternal and infant auxiliary function, and differentiated incentive function.These function settings can encourage pregnant women to improve or maintain healthy living habits during their use of the app

Conclusions
This study discusses the functional requirements of target users for gestational diabetes mellitus prevention apps, which can provide reference for the development of future applications.
Durability of the Treatment Effects of an 8-Week Self-administered Home-Based Virtual Reality Program for Chronic Low Back Pain: 6-Month Follow-up Study of a Randomized Clinical Trial
Authors: Garcia Laura , Birckhead Brandon , Krishnamurthy Parthasarathy , Mackey Ian , Sackman Josh , Salmasi Vafi , Louis Robert , Castro Carina , Maddox Roselani , Maddox Todd , Darnall Beth D 
Published: May 2022

Background
We previously reported the efficacy of an 8-week home-based therapeutic immersive virtual reality (VR) program in a double-blind randomized placebo-controlled study. Community-based adults with self-reported chronic low back pain were randomized 1:1 to receive either (1) a 56-day immersive therapeutic pain relief skills VR program (EaseVRx) or (2) a 56-day sham VR program. Immediate posttreatment results revealed the superiority of therapeutic VR over sham VR for reducing pain intensity; pain-related interference with activity, mood, and stress (but not sleep); physical function; and sleep disturbance. At 3 months posttreatment, therapeutic VR maintained superiority for reducing pain intensity and pain-related interference with activity, stress, and sleep (new finding).

Objective
This study assessed between-group and within-group treatment effects 6 months posttreatment to determine the extended efficacy, magnitude of efficacy, and clinical importance of home-based therapeutic VR.

Methods
E-surveys were deployed at pretreatment, end-of-treatment, and posttreatment months 1, 2, 3, and 6. Self-reported data for 188 participants were analyzed in a mixed-model framework using a marginal model to allow for correlated responses across the repeated measures. Primary outcomes were pain intensity and pain-related interference with activity, mood, stress, and sleep at 6 months posttreatment. Secondary outcomes were Patient-Reported Outcome Measurement Information System (PROMIS) sleep disturbance and physical function.

Results
Therapeutic VR maintained significant and clinically meaningful effects 6 months posttreatment and remained superior to sham VR for reducing pain intensity and pain-related interference with activity, stress, and sleep (ds=0.44-0.54; P<.003). Between-group comparisons for physical function and sleep disturbance showed superiority of EaseVRx over sham VR (ds=0.34; P=.02 and ds=0.46; P<.001, respectively). Participants were encouraged to contact study staff with any problems experienced during treatment; however, no participants contacted study staff to report adverse events of any type, including nausea and motion sickness.

Conclusions
Our 8-week home-based VR pain management program caused important reductions in pain intensity and interference up to 6 months after treatment. Additional studies are needed in diverse samples.

Trial Registration
ClinicalTrials.gov NCT04415177; https://clinicaltrials.gov/ct2/show/NCT04415177

International Registered Report Identifier (IRRID)
RR2-10.2196/25291
The Effect of Interventions to Prevent Type 2 Diabetes on the Development of Diabetic Retinopathy: The DPP/DPPOS Experience
Authors: White Neil H. , Pan Qing , Knowler William C. , Schroeder Emily B. , Dabelea Dana , Chew Emily Y. , Blodi Barbara , Goldberg Ronald B. , Pi-Sunyer Xavier , Darwin Christine , Schlögl Mathias , Nathan David M. , Group the Diabetes Prevention Program  Research 
Published: May 2022

<p> </p>
<p><strong>OBJECTIVE:</strong></p>
<p>To determine whether interventions that slow or prevent the development of type 2 diabetes mellitus in those at risk reduce the subsequent prevalence of diabetic retinopathy. </p>
<p><strong>RESEARCH DESIGN AND METHODS:</strong> </p>
<p>The Diabetes Prevention Program (DPP) randomized subjects at risk for developing type 2 diabetes because of overweight/obesity and dysglycemia to either metformin (MET), intensive lifestyle intervention (ILS) or placebo (PLB) to assess the prevention of diabetes. During the DPP and DPP Outcome Study (DPPOS), we performed fundus photography over time on study participants, regardless of their diabetes status. Fundus photographs were graded using the ETDRS grading system with diabetic retinopathy defined as typical lesions of diabetic retinopathy (microaneurysms, exudates or hemorrhage, or worse) in either eye.</p>
<p><strong>RESULTS: </strong></p>
<p>Despite reduced progression to diabetes in the ILS and MET groups compared to PLB, there was no difference in the prevalence of diabetic retinopathy between treatment groups after 1, 5, 11 or 16 years of follow up. No treatment group differences in retinopathy were found within prespecified subgroups (baseline age, sex, race/ethnicity, baseline BMI). In addition, there was no difference in the prevalence of diabetic retinopathy between those exposed to metformin and those not exposed to metformin regardless of treatment group assignment.</p>
<p><strong>CONCLUSION:</strong> </p>
<p>Interventions that delay or prevent the onset of type 2 diabetes in overweight/obese subjects with dysglycemia who are at risk for diabetes do not reduce the development of diabetic retinopathy for up to 20 years.</p>
Små russiske hverdager
Authors: Lieng Kristoffer 
Published: May 2022

Små russiske hverdager är norsklektorn Torunn Berntsens oredigerade minnesbilder av livet i det sena 1990-talets Ryssland. Navet i berättelsen är köket hos Berntsens hyresvärdinna i Sankt Petersburg, där en stor del av vardagen försiggår och funderingar uppstår. Författaren grubblar mycket över Rysslands väsen och framtid.
Små russiske hverdager (An Average Day in Russia) are Norwegian lecturer Torunn Berntsen's unedited memoirs of life in late 1990s Russia. The hub of the story is the kitchen at Berntsen's landlady in St. Petersburg, where a large part of everyday life takes place and thoughts arise. The author ponders a lot about Russia's essence and future.
Membangun Kemampuan Komunikasi Matematik dan Nilai Karakter Siswa melalui Bentang Pangajen Berbantuan Phet interactive simulation
Authors: Soekisno Bambang Aryan 
Published: May 2022

Hasil belajar siswa untuk bidang studi matematika, cukup mengkhawatirkan terutama kemampuan komunikasi matematik bahkan mungkin lebih rendah bila dibandingkan dengan kemampuan lainnya. Beberapa pelajar tidak menyukai matematika karena matematika penuh dengan hitungan dan miskin komunikasi. Beberapa pelajar juga berpikir bahwa matematika pelajaran yang membosankan, karena penuh rumus dan miskin nilai karakter. Kebanyakan pelajar tidak merasa senang ketika belajar matematika. Bentang pangajen berbantuan Phet interactive simulation adalah sebuah pembelajaran yang menyajikan pembelajaran matematika dengan menyenangkan dan juga membangun keterampilan komunikasi dan nilai karakter. Ada lima langkah dalam pembelajaran dengan bentang pangajen, yaitu bina suasana, bina konsep, bina ingatan, beri bintang, dan beri hikmah. Metode yang digunakan adalah penelitian tindakan kelas pada siswa SMA Negeri 6 Bogor. Keterampilan komunikasi terbangun pada langkah ke tiga sampai lima dari pembelajaran dengan bentang pangajen berbantuan Phet interactive simulation. Adanya peningkatan kemampuan komunikasi matematik dari setiap siklus, dan nilai karakter siswa terbangun pada langkah ke empat dan lima dari pembelajaran ini.
Legitimidad: ¿el dilema de China?
Authors: Oviedo Eduardo Daniel 
Published: May 2022

Este artículo analiza la legitimidad en China y amplía la tradicional división tripartita entre legitimidad de origen, desempeño y destino. Asimismo, divide la legitimidad de origen en legitimidad de las instituciones y legitimidad de las autoridades, y considera que crisis, eficacia e incertidumbre son tres términos clave para entender el estado actual de la legitimidad en este país. Es decir, una legitimidad de origen en crisis desde 1989, la efectividad de los resultados de la modernización, y la incertidumbre sobre si el régimen mantendrá su legitimidad actual. Por el momento, el Partido Comunista Chino utiliza argumentos multifacéticos para explicar la dominación política basados principalmente en los logros socioeconómicos, pero como éstos son inestables, insta a reinventar sus fuentes. En este sentido, las propuestas teóricas oscilan entre el confucianismo y la democracia, con punto medio en el neoconfucianismo moderno. Sin embargo, el gobierno comunista sigue un derrotero conservador, si bien el presidente Xi Jinping introdujo procedimientos tradicionales en la enmienda constitucional de 2018.
THE IMPLEMENTATION OF TRI CORE BREASTFEEDING MODELS ON MOTHER’S SATISFACTION IN BREASTFEEDING
Authors: Helina Siska , Harahap Juraida Roito , Halimah Siti 
Published: May 2022

The low rates of exclusive breastfeeding have effected the growth and the development of children. Some efforts to improve the achievement of exclusive breastfeeding have been conducted, like an education about breastfeeding, facilitating early breastfeeding initiation and providing motivation to mothers. These elements contain a form of health promotion care model called the Tri Core Breastfeeding Models. The purpose of this study is to determine the effect of Tri Core Breastfeeding Models on breastfeeding mothers' satisfaction. This research was conducted in the working area of the Sidomulyo Health Center in Pekanbaru City in August 2019 to April 2020. This research is Pre-experimental Design. The population in this study was all third trimester pregnant women. The sample of 20 pregnant women was taken by consecutive sampling technique with 10 pregnant women in the intervention and 10 pregnant women for control. The Maternal Breastfeeding Evaluation Scale (MBFES) questionnaire was used to collect the data. The Mann Whitney Test with a significance level of 95% was used to analyze the data. The results showed that the average satisfaction of breastfeeding mothers in the intervention group was 134.80 (SD: 3.190) and the control group 119.10 (SD: 14.317), and it is found that there is a difference in breastfeeding satisfaction among mothers in the intervention group and the control group (p = 0.019). Finally, it is recommended that Tri Core Breastfeeding Models can be applied in providing midwifery care in the to support the success of exclusive breastfeeding