bluuebunny/crossref_metadata_2025_split huggingface dataset:
mHealth and Engagement Concerning Persons With Chronic Somatic Health Conditions: Integrative Literature Review
Authors: Tuvesson Hanna , Eriksén Sara , Fagerström Cecilia 
Published: July 2020

Background
Chronic somatic health conditions are a global public health challenge. Being engaged in one’s own health management for such conditions is important, and mobile health (mHealth) solutions are often suggested as key to promoting engagement.

Objective
The aim of this study was to review, critically appraise, and synthesize the available research regarding engagement through mHealth for persons with chronic somatic health conditions.

Methods
An integrative literature review was conducted. The PubMed, CINAHL, and Inspec databases were used for literature searches. Quality assessment was done with the guidance of Critical Appraisal Skills Programme (CASP) checklists. We used a self-designed study protocol comprising 4 engagement aspects—cognitive, behavioral and emotional, interactional, and the usage of mHealth—as part of the synthesis and analysis.

Results
A total of 44 articles met the inclusion criteria and were included in the analysis. mHealth usage was the most commonly occurring engagement aspect, behavioral and emotional aspects the second, cognitive aspects the third, and interactional aspects of engagement the least common aspect in the included articles. The results showed that there is a mix of enablers and barriers to engagement in relation to the 4 engagement aspects. The perceived meaningfulness and need for the solution and its content were important to create and maintain engagement. When perceived as meaningful, suitable, and usable, mHealth can support knowledge gain and learning, facilitate emotional and behavioral aspects such as a sense of confidence, and improve interactions and communications with health care professionals.

Conclusions
mHealth solutions have the potential to support health care engagement for persons with chronic somatic conditions. More research is needed to further understand how, by which means, when, and among whom mHealth could further improve engagement for this population.
Early Stage Machine Learning–Based Prediction of US County Vulnerability to the COVID-19 Pandemic: Machine Learning Approach
Authors: Mehta Mihir , Julaiti Juxihong , Griffin Paul , Kumara Soundar 
Published: July 2020

Background
The rapid spread of COVID-19 means that government and health services providers have little time to plan and design effective response policies. It is therefore important to quickly provide accurate predictions of how vulnerable geographic regions such as counties are to the spread of this virus.

Objective
The aim of this study is to develop county-level prediction around near future disease movement for COVID-19 occurrences using publicly available data.

Methods
We estimated county-level COVID-19 occurrences for the period March 14 to 31, 2020, based on data fused from multiple publicly available sources inclusive of health statistics, demographics, and geographical features. We developed a three-stage model using XGBoost, a machine learning algorithm, to quantify the probability of COVID-19 occurrence and estimate the number of potential occurrences for unaffected counties. Finally, these results were combined to predict the county-level risk. This risk was then used as an estimated after-five-day-vulnerability of the county.

Results
The model predictions showed a sensitivity over 71% and specificity over 94% for models built using data from March 14 to 31, 2020. We found that population, population density, percentage of people aged >70 years, and prevalence of comorbidities play an important role in predicting COVID-19 occurrences. We observed a positive association at the county level between urbanicity and vulnerability to COVID-19.

Conclusions
The developed model can be used for identification of vulnerable counties and potential data discrepancies. Limited testing facilities and delayed results introduce significant variation in reported cases, which produces a bias in the model.
Acceptability of App-Based Contact Tracing for COVID-19: Cross-Country Survey Study
Authors: Altmann Samuel , Milsom Luke , Zillessen Hannah , Blasone Raffaele , Gerdon Frederic , Bach Ruben , Kreuter Frauke , Nosenzo Daniele , Toussaert Séverine , Abeler Johannes 
Published: July 2020

BackgroundThe COVID-19 pandemic is the greatest public health crisis of the last 100 years. Countries have responded with various levels of lockdown to save lives and stop health systems from being overwhelmed. At the same time, lockdowns entail large socioeconomic costs. One exit strategy under consideration is a mobile phone app that traces the close contacts of those infected with COVID-19. Recent research has demonstrated the theoretical effectiveness of this solution in different disease settings. However, concerns have been raised about such apps because of the potential privacy implications. This could limit the acceptability of app-based contact tracing in the general population. As the effectiveness of this approach increases strongly with app uptake, it is crucial to understand public support for this intervention.ObjectiveThe objective of this study is to investigate the user acceptability of a contact-tracing app in five countries hit by the pandemic.MethodsWe conducted a largescale, multicountry study (N=5995) to measure public support for the digital contact tracing of COVID-19 infections. We ran anonymous online surveys in France, Germany, Italy, the United Kingdom, and the United States. We measured intentions to use a contact-tracing app across different installation regimes (voluntary installation vs automatic installation by mobile phone providers) and studied how these intentions vary across individuals and countries.ResultsWe found strong support for the app under both regimes, in all countries, across all subgroups of the population, and irrespective of regional-level COVID-19 mortality rates. We investigated the main factors that may hinder or facilitate uptake and found that concerns about cybersecurity and privacy, together with a lack of trust in the government, are the main barriers to adoption.ConclusionsEpidemiological evidence shows that app-based contact tracing can suppress the spread of COVID-19 if a high enough proportion of the population uses the app and that it can still reduce the number of infections if uptake is moderate. Our findings show that the willingness to install the app is very high. The available evidence suggests that app-based contact tracing may be a viable approach to control the diffusion of COVID-19.
Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation
Authors: Abdulaal Ahmed , Patel Aatish , Charani Esmita , Denny Sarah , Mughal Nabeela , Moore Luke 
Published: July 2020

Background
The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak is a public health emergency and the case fatality rate in the United Kingdom is significant. Although there appear to be several early predictors of outcome, there are no currently validated prognostic models or scoring systems applicable specifically to patients with confirmed SARS-CoV-2.

Objective
We aim to create a point-of-admission mortality risk scoring system using an artificial neural network (ANN).

Methods
We present an ANN that can provide a patient-specific, point-of-admission mortality risk prediction to inform clinical management decisions at the earliest opportunity. The ANN analyzes a set of patient features including demographics, comorbidities, smoking history, and presenting symptoms and predicts patient-specific mortality risk during the current hospital admission. The model was trained and validated on data extracted from 398 patients admitted to hospital with a positive real-time reverse transcription polymerase chain reaction (RT-PCR) test for SARS-CoV-2.

Results
Patient-specific mortality was predicted with 86.25% accuracy, with a sensitivity of 87.50% (95% CI 61.65%-98.45%) and specificity of 85.94% (95% CI 74.98%-93.36%). The positive predictive value was 60.87% (95% CI 45.23%-74.56%), and the negative predictive value was 96.49% (95% CI 88.23%-99.02%). The area under the receiver operating characteristic curve was 90.12%.

Conclusions
This analysis demonstrates an adaptive ANN trained on data at a single site, which demonstrates the early utility of deep learning approaches in a rapidly evolving pandemic with no established or validated prognostic scoring systems.
Island Generator pada Game Open world Menggunakan Algoritma Perlin noise
Authors: Azzmi Naufal , Husniah Lailatul , Kholimi Ali Sofyan 
Published: July 2020

AbstrakPerkembangan game pada saat ini berkembang dengan sangat cepat, dalam perkermbangan game topik AI adalah topik yang paling banyak diteliti oleh beberapa peneliti khususnya pada pembuatan suatu konten game menggunakan metode PCG (procedural content generation). Pada pembuatan sebuah game world menggunakan metode PCG sudah banyak developer game yang sukses dengan mengimplementasikan metode ini, metode ini banyak digunkan pada geme dengan genre RPG, Rouglikes, Platformer, SandBox, Simulation dan lain sebagainya, Pada penelitian ini berfokus pada pengembangan sebuah game world generator untuk game berjenis open world yang berupa sebuah kepulauan dengan metode PCG dengan menggunakan algoritma perlin noise sebagai algoritma pembentuk textur utama pulau yang dimana pada penelitian ini memanfaatkan beberapa variable noise seperti octave, presistance dan lacunarity guna untuk menambah kontrol dari hasil textur yang dihasilkan serta algoritma penempatan pulau untuk membuat sebuah game world yang menyerupai sebuah kepulauan. Dari hasil uji generator terkait degan pengujian playability dan performa dapat disimpulkan bahwa generator yang dikembangkan playable serta performa yang dianaliasa menggunakan notasi Big O menunjukkan (linear). Abstract Game development is currently growing very fast, game development AI is the most discussed topic by most researchers especially in the developing of game content using the PCG (procedural content generation) method. In making a game world using the PCG method, many game developers have succeeded by implementing this method, this method is widely used on RPGs, Rouglikes, Platformers, SandBox, Simulations and ect,. This study focuses on developing a game world generator game for open world type games in the form of an archipelago using the PCG method using the noise perlin algorithm as the island's main texturizing algorithm which in this study utilizes several noise variables such as octave, presistance and use for add control of the texture results as well as the island placement algorithm’s to create a game world that resembles an archipelago form. From the generator test results related to the playability and performance testing, it shows that map are being generated by the generators are playable and performance that are analyzed using Big O notation show O (n) (linear).
Analisa Sistem Identifikasi DDoS Menggunakan KNN Pada Jaringan Software Defined Network(SDN)
Authors: Azis Muhammad Misbahul , Azhar Yufiz , Syaifuddin Syaifuddin 
Published: July 2020

AbstrakAbstrak - Kebutuhan pada jaringan mengutamakan performa untuk mendukung sebuah efisiensi jaringan merupakan hal penting untuk saat ini. Penentuan konfigurasi yang semakin banyak dan kompleks serta kontrol jaringan yang semakin rumit, membuat jaringan semakin tidak fleksibel dan susah untuk diterapkan pada sebuah topologi jaringan yang besar. Software Defined Network (SDN) muncul dengan mekanisme yang dapat menyelesaikan masalah tersebut. Pada dasarnya konsep dari Software Defined Network (SDN) adalah memisahkan kontroller dan data/forwarding plane, sehingga mampu untuk me-menejemen jaringan yang begitu banyak dalam sebuah kontroller. Namun pada kontroller belum memiliki keamanan yang cukup untuk melindungi dari serangan jaringan seperti DDoS, SYN Flooding Attack sehingga kontroller akan menjadi target dari attacker. Sehingga penelitian ini mengusulkan penambahan aplikasi machine learning pada kontroller untuk menangani serangan seperti DDoS dan SYN Flooding Attack. Dalam penelitian ini kontroller yang digunakan adalah ryu controller yang menggunakan bahasa pemrograman python. Dalam penelitian ini menggunakan topologi linear pada mininet dan membuat paket dalam format .pcap untuk pengujian serangan yang dilakukan. Sehingga dapat mengetahui rata-rata jumlah paket yang masuk dan keluar dan keberhasilan dalam melakukan mitigasi terhadap paket yang dianggap DDoS.Abstract The need for the network to prioritize performance to support a network efficiency is important for now. Determination of configurations that are more and more complex and increasingly complicated network control, makes the network more inflexible and difficult to apply to a large network topology. Software Defined Network (SDN) appears with a mechanism that can solve the problem. Basically the concept of Software Defined Network (SDN) is to separate the controller and the data / forwarding plane, so that it is able to manage so many networks in a controller. But the controller does not have enough security to protect against network attacks such as DDoS, SYN Flooding Attack so the controller will be the target of the attacker. So this study proposes adding machine learning applications to controllers to handle attacks such as DDoS and SYN Flooding Attack. In this study the controller used is the Ryu controller that uses the Python programming language. In this study using a linear topology on Mininet and create a package in. Pcap format for testing attacks carried out. So as to know the average number of incoming and outgoing packages and success in mitigating packages that are considered DDoS.
Youth Involvement in the Decision to Start CGM Predicts Subsequent CGM Use
Authors: Miller Victoria A. , Xiao Rui , Slick Nathalie , Feudtner Chris , Willi Steven M. 
Published: July 2020

OBJECTIVE
The ability of continuous glucose monitoring (CGM) to improve diabetes outcomes depends upon consistent use. To identify factors that facilitate long-term use of CGM, this study tested the hypothesis that youth involvement in the decision to initiate this therapy would influence subsequent CGM use and that CGM self-efficacy and satisfaction mediate this relationship.

RESEARCH DESIGN AND METHODS
Before initiating CGM, parent-youth dyads (i.e., pairs) from an academic endocrinology clinic completed assessments, including a measure of the child’s involvement in the decision to start CGM. Two months into CGM use, youth completed measures of CGM self-efficacy and satisfaction. Fidelity of CGM use between weeks 5 and 12 was accessed via a cloud-based data repository. Hypotheses were tested with linear mixed-effects models, accounting for patients clustered within provider and repeated measures within patients.

RESULTS
CGM use in 108 dyads (youth mean age 13.4 ± 2.7 years; 73% White) was positively predicted by baseline parent report of youth involvement in the CGM decision (P &lt; 0.0001), and this relationship was mediated by youth’s perceptions of CGM self-efficacy (P &lt; 0.0001) and hassle (P = 0.014). So, when the youth shared their opinions about CGM with parents and participated in the decision to start, they perceived higher self-efficacy and lower hassle at 2-month follow-up, which predicted more days of use. This pattern held in models adjusting for youth race and sex and family income.

CONCLUSIONS
To achieve maximum clinical benefit from CGM use, providers should facilitate youth involvement in the decision to initiate the device.
¿Es posible una soberanía alimentaria en México?
Authors: Carmona Silva José Luis , Sánchez Flores Lizbeth , Acle Mena Ramón Sebastián 
Published: July 2020

El objetivo de este trabajo es analizar el concepto de soberanía alimentaria, así como determinar si la soberanía alimentaria en México puede considerarse como una realidad, una posibilidad o es una quimera. La metodología empleada en este trabajo es eminentemente cualitativa. En primer lugar, se realizó una revisión documental acerca del concepto ya mencionado y una revisión histórica de este. En segundo, se revisó el estado que guarda la alimentación y producción de alimentos en México y se analizó la posibilidad de ejercer una verdadera soberanía alimentaria. En los resultados se observa que a través del tiempo nuestro país ha ido perdiendo su soberanía alimentaria, y dadas las circunstancias actuales, por el momento parece muy complicado que pudiera ser una realidad. Por un lado, la población ocupada en el sector primario ha sufrido un drástico cambio: de 58.32 % del total en 1950 a solo 12.6 % en el año 2019, lo que dificulta totalmente la producción de alimentos; por otra parte, las políticas alimentarias actuales en materia de alimentación tampoco ayudan en este sentido, pues actualmente se pretende garantizar la alimentación de la población a través de la compra masiva de alimentos de cualquier parte del mundo, donde sea más barato, apoyando también solo la producción de la agroindustria de las empresas transnacionales, en lugar de apoyar el campo mexicano y reactivar la producción de autoconsumo.
Pemanfaatan Media Realia dengan Program Pembelajaran Individual dalam Mengenal Konsep Bilangan Bagi Anak Tunagrahita
Authors: Hasan Yarmis , Efrina Elsa , Muspita Rila 
Published: July 2020

Tulisan ini membahas tentang pemanfaatan media realia dengan penggunaan program pembelajaran individual dalam mengenal konsep bilangan bagi anak tunagrahita.
Data didapatkan dengan pengamatan, wawancara, telah, dan komunikasi. Hasil menunjukkan media realia dapat mengenal konsep bilangan dengan guru sebagai teacher center. Guru mengaplikasikan media realia dengan pendekatan bermain seperti menghitung jumlah permen,pensil,atau apel. Sehingga anak lebih mudah mengenal konsep bilangan. Dari satu sampai lima dari pertanyaan anak dapat membilang atau menyebutkan, menunjukkan, membedakan, mencocokkan, menuliskan bilangan. Kemudian anak dapat menuliskan angka bilangan sesuai banyak benda.
Meningkatkan Kemampuan Guru pada Pembelajaran Membaca Anak Disleksia
Authors: Irdamurni Irdamurni , Kasiyati Kasiyati , Zulmiyetri Zulmiyetri , Taufan Johandri 
Published: July 2020

The objective of this study was to investigate reading instruction training for teaching teachers to teach reading student with dyslexia. Training mothods uses multi methods I.e lectures vary, demonstrations, exercises and assignments. The increased aspects related to the implementation of identification and assesment, development of modification lesson plan and individualized educational program. Futhermore, reading instruction for dyslexia includes strategy and learning media as assesment of learning for students with dyslexia.
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Explorando limites epistemológicos e políticos da BNCC para pensar possibilidades
Authors: Pedro Gabriel , Marsico Juliana 
Published: July 2020

Resenha da obra CURY, Carlos Roberto Jamil; REIS, Magali; ZANARDI, Teodoro Adriano Costa. Base Nacional Comum Curricular: dilemas e perspectivas. São Paulo: Cortez, 2018. 144 p.
Optimal Kinetic Parameters of Trickle bed Reactor for Oxidation of 2-Proplymercaptan in Naphtha
Authors: Talal Nawaf Amer 
Published: July 2020

The best kinetic of the reaction are estimated based on experimental data obtained from the literature using parameter estimation technique. The best mathematical model for oxidative 2-proplymercaption via oxygen is taking into account the apparent intrinsic kinetics considering internal diffusion and TBR hydrodynamic effect on the reaction process mainly , catalyst wetting efficiency, catalyst effectiveness factor, Thiele model and the effective diffusivity. The optimal operating condition for oxidative process is carried out utilizing. The optimization technique based upon the minimization of the sum squared error between experimental and predicted composition of naphtha oxidative process to determine the best parameters of kinetics models. The predicted product compositions for oxidation process found to be a good agreement with the experimental data for wide range of operating conditions (2.5-10 hr-1, 75-300 ppm and 293-353K) with minimum error 5% among all results
conexus 1/2018: Lust und Leiden
Authors: Rother Wolfgang , Baer Josette 
Published: July 2020

Die erste Nummer von conexus enthält Aufsätze, die das Thema «Lust und Leiden» aus philosophischer, literaturwissenschaftlicher und kunstgeschichtlicher, historischer und politischer, kulturanthropologischer und medizinischer Perspektive beleuchten.
Irrtum und Vergebung. Gedanken zu Dostojewskis «Grossinquisitor»
Authors: Bryner Erich 
Published: July 2020

Der «Grossinquisitor» gehört zu den berühmtesten Texten Dostojewskis. Der westlich gebildete Iwan Karamasow trägt es im Rahmen seiner philosophischen und religionskritischen Darlegungen seinem jüngeren Bruder, dem Novizen Aljoscha, vor. Er erzählt, dass Jesus Christus im 16. Jahrhundert, auf dem Höhepunkt der Inquisition in Spanien, auf die Erde zurückgekehrt, vom Volk erkannt und auf Befehl des Grossinquisitors verhaftet worden sei. Der Grossinquisitor habe Jesus im Gefängnis besucht und ihm die heftigsten Vorwürfe gemacht: Jesus habe mit der Verkündigung der Freiheit (Joh 8,3–38) die Menschheit völlig überfordert. Seine Lehre sei grundfalsch, ein Irrtum, und für die Menschen eine Last, die sie nicht tragen könnten. Deshalb habe die Kirche die Lehre Jesu verbessert und anstelle der Freiheit Wunder, Geheimnis und Autorität gesetzt und so der Menschheit das Glück gebracht. «Warum bist Du gekommen», fragt der Grossinquisitor, «uns zu stören? Morgen werde ich Dich verbrennen.» Auf diese Vorwürfe antwortet Jesus lediglich mit einer Geste: Er küsst den Grossinquisitor und zeigte ihm damit seine Vergebung an.
Dostojewski will mit dieser Dichtung den Menschen vom Irrtum der römisch-katholischen Kirche zur Erkenntnis der Wahrheit des Evangeliums führen. In der Forschung werden drei Deutungsebenen unterschieden: die Ebene der Philosophie des Atheisten und Religionskritikers Iwan Karamasow, die Kritik Dostojewskis an der römisch-katholischen Kirche (die er auch in anderen Werken zum Ausdruck brachte) und die Ebene allgemein anthropologischer Einsichten.
Ragam Branding Desa dalam Mengembangkan Potensi Wisata Berbasis Budaya Masyarakat di Kabupaten Buleleng
Authors: Widiastini Ni Made Ary , Rahmawati Putu Indah , Isti Koma Fajar Yualida 
Published: July 2020

This paper aims to describe the image and branding of the cultural potential of a tourist destination in Buleleng Regency, so that each destination can be understood to have a different and unique identity. Buleleng Regency has natural and cultural potential that can be managed and utilized as tourist attractions. The potential can be packaged so that it becomes something that shows the identity of a destination. The large number of same turist destinations requires the accuracy in its management, so that the target market can be achieved. Brand and image become very important as a distinguishing destination between one another. In Buleleng Regency, several places have been developed by create the brand and image as tourist destinations, such as the Old Village of Buleleng Regency which consists of seven villages, Janger Kolok Bengkala Village, Bukakak Tradition, Sudaji Village, Beji Temple, Sangsit Village, Gedong Kerta and Puri in Paket Agung Village, dan Vihara in Banjar Village. In its implementation, it is recommended that brand and image formation must also be accompanied by the provision of facilities and services in accordance with the image being built.
Keywords: Brand, Image, Tourism, Buleleng