bluuebunny/crossref_metadata_2025 huggingface dataset:
Gaining First Insights on Secondary Progressive Multiple Sclerosis Patients Treated With Siponimod in Clinical Routine: Protocol of the Noninterventional Study AMASIA
Authors: Ziemssen Tjalf , Hoffmann Olaf , Klotz Luisa , Schreiber Herbert , Weber Martin S , Rauser Benedict
Published: June 2020

Background

A high proportion of patients with relapsing remitting multiple sclerosis convert to secondary progressive multiple sclerosis (SPMS) characterized by irreversibly progressing disability and cognitive decline. Siponimod (Mayzent), a selective sphingosine-1-phosphate receptor modulator, was recently approved by the European Medicines Agency for the treatment of adult SPMS patients with active disease, as evidenced by relapses or magnetic resonance imaging features of ongoing inflammatory activity. Approval by the Food and Drug Administration covers a broader range of indications, comprising clinically isolated syndrome, relapsing remitting multiple sclerosis, and active SPMS. However, treatment effects of siponimod have not been assessed in a structured setting in clinical routine so far.

Objective

The objectives of AMASIA (impAct of Mayzent [siponimod] on secondAry progressive multiple Sclerosis patients in a long-term non-Interventional study in GermAny), a prospective noninterventional study, are to assess the long-term effectiveness and safety of siponimod in clinical routine and to evaluate the impact of disease burden on quality of life and socioeconomic conditions. Here, we report the study design of AMASIA.

Methods

Treatment effects of siponimod will be evaluated in 1500 SPMS patients during a 3-year observational phase. According to the genetic polymorphism of CYP2C9, the initial dose will be titrated to the maintenance dose of 1 mg (CYP2C9*1*3 and *2*3) or 2 mg (all other polymorphisms of CYP2C9 except *3*3, which is contraindicated) taken orally once daily. Primary endpoint is the 6-month confirmed disability progression, as assessed by a functional composite endpoint comprising the Expanded Disability Status Scale and symbol digit modalities test to take appropriate account of cognitive changes and increase sensitivity. Further measures including multiple sclerosis activity data; assessments of functional domains; questionnaires addressing the patients’, physicians’, and relatives’ perspectives of disability progression; cognitive worsening; quality of life; and socioeconomic aspects will be documented using the multiple sclerosis documentation system MSDS3D.

Results

AMASIA is being conducted between February 2020 and February 2025 in up to 250 neurological centers in Germany.

Conclusions

AMASIA will complement the pivotal phase III–derived efficacy and safety profile of siponimod with real-world data and will further evaluate several individual treatment aspects such as quality of life and socioeconomic conditions of patients and caregivers. It might help to establish siponimod as a promising option for the treatment of SPMS patients in clinical routine.

International Registered Report Identifier (IRRID)

DERR1-10.2196/19598
Wearable Activity Trackers for Monitoring Adherence to Home Confinement During the COVID-19 Pandemic Worldwide: Data Aggregation and Analysis
Authors: Pépin Jean Louis , Bruno Rosa Maria , Yang Rui-Yi , Vercamer Vincent , Jouhaud Paul , Escourrou Pierre , Boutouyrie Pierre
Published: June 2020

Background

In the context of home confinement during the coronavirus disease (COVID-19) pandemic, objective, real-time data are needed to assess populations’ adherence to home confinement to adapt policies and control measures accordingly.

Objective

The aim of this study was to determine whether wearable activity trackers could provide information regarding users' adherence to home confinement policies because of their capacity for seamless and continuous monitoring of individuals’ natural activity patterns regardless of their location.

Methods

We analyzed big data from individuals using activity trackers (Withings) that count the wearer’s average daily number
of steps in a number of representative nations that adopted different modalities of restriction of citizens’ activities.

Results

Data on the number of steps per day from over 740,000 individuals around the world were analyzed. We demonstrate the physical activity patterns in several representative countries with total, partial, or no home confinement. The decrease in steps per day in regions with strict total home confinement ranged from 25% to 54%. Partial lockdown (characterized by social distancing measures such as school closures, bar and restaurant closures, and cancellation of public meetings but without strict home confinement) does not appear to have a significant impact on people’s activity compared to the pre-pandemic period. The absolute level of physical activity under total home confinement in European countries is around twofold that in
China. In some countries, such as France and Spain, physical activity started to gradually decrease even before official commitment
to lockdown as a result of initial less stringent restriction orders or self-quarantine. However, physical activity began to increase
again in the last 2 weeks, suggesting a decrease in compliance with confinement orders.

Conclusions

Aggregate analysis of activity tracker data with the potential for daily updates can provide information regarding adherence to home confinement policies.
Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches (Preprint)
Authors: Tarekegn Adane , Ricceri Fulvio , Costa Giuseppe , Ferracin Elisa , Giacobini Mario
Published: June 2020

BACKGROUND

Frailty is one of the most critical age-related conditions in older adults. It is often recognized as a syndrome of physiological decline in late life, characterized by a marked vulnerability to adverse health outcomes. A clear operational definition of frailty, however, has not been agreed so far. There is a wide range of studies on the detection of frailty and their association with mortality. Several of these studies have focused on the possible risk factors associated with frailty in the elderly population while predicting who will be at increased risk of frailty is still overlooked in clinical settings.

OBJECTIVE

The objective of our study was to develop predictive models for frailty conditions in older people using different machine learning methods based on a database of clinical characteristics and socioeconomic factors.

METHODS

An administrative health database containing 1,095,612 elderly people aged 65 or older with 58 input variables and 6 output variables was used. We first identify and define six problems/outputs as surrogates of frailty. We then resolve the imbalanced nature of the data through resampling process and a comparative study between the different machine learning (ML) algorithms – Artificial neural network (ANN), Genetic programming (GP), Support vector machines (SVM), Random Forest (RF), Logistic regression (LR) and Decision tree (DT) – was carried out. The performance of each model was evaluated using a separate unseen dataset.

RESULTS

Predicting mortality outcome has shown higher performance with ANN (TPR 0.81, TNR 0.76, accuracy 0.78, F1-score 0.79) and SVM (TPR 0.77, TNR 0.80, accuracy 0.79, F1-score 0.78) than predicting the other outcomes. On average, over the six problems, the DT classifier has shown the lowest accuracy, while other models (GP, LR, RF, ANN, and SVM) performed better. All models have shown lower accuracy in predicting an event of an emergency admission with red code than predicting fracture and disability. In predicting urgent hospitalization, only SVM achieved better performance (TPR 0.75, TNR 0.77, accuracy 0.73, F1-score 0.76) with the 10-fold cross validation compared with other models in all evaluation metrics.

CONCLUSIONS

We developed machine learning models for predicting frailty conditions (mortality, urgent hospitalization, disability, fracture, and emergency admission). The results show that the prediction performance of machine learning models significantly varies from problem to problem in terms of different evaluation metrics. Through further improvement, the model that performs better can be used as a base for developing decision-support tools to improve early identification and prediction of frail older adults.
Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study (Preprint)
Authors: Lupiáñez-Villanueva Francisco , Folkvord Frans , Vanden Abeele Mariek
Published: June 2020

BACKGROUND

Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits of mHealth for patients and health care providers, scientific research examining factors explaining the adoption level of mHealth tools remains scarce.

OBJECTIVE

We performed an experimental vignette study to investigate how four factors related to the business model of an mHealth app affect its adoption and users’ willingness to pay: (1) the revenue model (ie, sharing data with third parties vs accepting advertisements); (2) the data protection model (General Data Protection Regulation [GDPR]-compliant data handling vs nonGDPR-compliant data handling); (3) the recommendation model (ie, doctor vs patient recommendation); and (4) the provider model (ie, pharmaceutical vs medical association provider). In addition, health consciousness, health information orientation, and electronic health literacy were explored as intrapersonal predictors of adoption.

METHODS

We conducted an experimental study in three countries, Spain (N=800), Germany (N=800), and the Netherlands (N=416), to assess the influence of multiple business models and intrapersonal characteristics on the willingness to pay and intention to download a health app.

RESULTS

The revenue model did not affect willingness to pay or intentions to download the app in all three countries. In the Netherlands, data protection increased willingness to pay for the health app (P<.001). Moreover, in all three countries, data protection increased the likelihood of downloading the app (P<.001). In Germany (P=.04) and the Netherlands (P=.007), a doctor recommendation increased both willingness to pay and intention to download the health app. For all three countries, apps manufactured in association with a medical organization were more likely to be downloaded (P<.001). Finally, in all three countries, men, younger individuals, those with higher levels of education, and people with a health information orientation were willing to pay more for adoption of the health app and had a higher intention to download the app.

CONCLUSIONS

The finding that people want their data protected by legislation but are not willing to pay more for data protection suggests that in the context of mHealth, app privacy protection cannot be leveraged as a selling point. However, people do value a doctor recommendation and apps manufactured by a medical association, which particularly influence their intention to download an mHealth app.
Healthcare Research and Analytics Data Infrastructure Solution: A Data Warehouse for Health Services Research (Preprint)
Authors: Ozaydin Bunyamin , Zengul Ferhat , Oner Nurettin , Feldman Sue S
Published: June 2020

BACKGROUND

Health services researchers spend a substantial amount of time performing integration, cleansing, interpretation, and aggregation of raw data from multiple public or private data sources. Often, each researcher (or someone in their team) duplicates this effort for their own project, facing the same challenges and experiencing the same pitfalls discovered by those before them.

OBJECTIVE

This paper described a design process for creating a data warehouse that includes the most frequently used databases in health services research.

METHODS

The design is based on a conceptual iterative process model framework that utilizes the sociotechnical systems theory approach and includes the capacity for subsequent updates of the existing data sources and the addition of new ones. We introduce the theory and the framework and then explain how they are used to inform the methodology of this study.

RESULTS

The application of the iterative process model to the design research process of problem identification and solution design for the Healthcare Research and Analytics Data Infrastructure Solution (HRADIS) is described. Each phase of the iterative model produced end products to inform the implementation of HRADIS. The analysis phase produced the problem statement and requirements documents. The projection phase produced a list of tasks and goals for the ideal system. Finally, the synthesis phase provided the process for a plan to implement HRADIS. HRADIS structures and integrates data dictionaries provided by the data sources, allowing the creation of dimensions and measures for a multidimensional business intelligence system. We discuss how HRADIS is complemented with a set of data mining, analytics, and visualization tools to enable researchers to more efficiently apply multiple methods to a given research project. HRADIS also includes a built-in security and account management framework for data governance purposes to ensure customized authorization depending on user roles and parts of the data the roles are authorized to access.

CONCLUSIONS

To address existing inefficiencies during the obtaining, extracting, preprocessing, cleansing, and filtering stages of data processing in health services research, we envision HRADIS as a full-service data warehouse integrating frequently used data sources, processes, and methods along with a variety of data analytics and visualization tools. This paper presents the application of the iterative process model to build such a solution. It also includes a discussion on several prominent issues, lessons learned, reflections and recommendations, and future considerations, as this model was applied.

CLINICALTRIAL
Use of Patient-Reported Symptoms from an Online Symptom Tracking Tool for Dementia Severity Staging: Development and Validation of a Machine Learning Approach (Preprint)
Authors: Shehzad Aaqib , Rockwood Kenneth , Stanley Justin , Dunn Taylor , Howlett Susan E
Published: June 2020

BACKGROUND

SymptomGuide Dementia (DGI Clinical Inc) is a publicly available online symptom tracking tool to support caregivers of persons living with dementia. The value of such data are enhanced when the specific dementia stage is identified.

OBJECTIVE

We aimed to develop a supervised machine learning algorithm to classify dementia stages based on tracked symptoms.

METHODS

We employed clinical data from 717 people from 3 sources: (1) a memory clinic; (2) long-term care; and (3) an open-label trial of donepezil in vascular and mixed dementia (VASPECT). Symptoms were captured with SymptomGuide Dementia. A clinician classified participants into 4 groups using either the Functional Assessment Staging Test or the Global Deterioration Scale as mild cognitive impairment, mild dementia, moderate dementia, or severe dementia. Individualized symptom profiles from the pooled data were used to train machine learning models to predict dementia severity. Models trained with 6 different machine learning algorithms were compared using nested cross-validation to identify the best performing model. Model performance was assessed using measures of balanced accuracy, precision, recall, Cohen κ, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC). The best performing algorithm was used to train a model optimized for balanced accuracy.

RESULTS

The study population was mostly female (424/717, 59.1%), older adults (mean 77.3 years, SD 10.6, range 40-100) with mild to moderate dementia (332/717, 46.3%). Age, duration of symptoms, 37 unique dementia symptoms, and 10 symptom-derived variables were used to distinguish dementia stages. A model trained with a support vector machine learning algorithm using a one-versus-rest approach showed the best performance. The correct dementia stage was identified with 83% balanced accuracy (Cohen κ=0.81, AUPRC 0.91, AUROC 0.96). The best performance was seen when classifying severe dementia (AUROC 0.99).

CONCLUSIONS

A supervised machine learning algorithm exhibited excellent performance in identifying dementia stages based on dementia symptoms reported in an online environment. This novel dementia staging algorithm can be used to describe dementia stage based on user-reported symptoms. This type of symptom recording offers real-world data that reflect important symptoms in people with dementia.
Peer-to-peer sharing of sexual health social media messages in a school-based intervention: Opportunities and Challenges Identified in the STASH Feasibility Trial (Preprint)
Authors: Hirvonen Maija-Kaisa , Purcell Carrie , Elliott Lawrie , Bailey Julia V , Simpson Sharon Anne , McDaid Lisa , Moore Laurence , Mitchell Kirstin Rebecca ,   The STASH Study Team
Published: June 2020

BACKGROUND

There is strong interest in the use of social media to spread positive sexual health messages through young people’s social networks. However, research suggests this potential may be limited by a reluctance to be visibly associated with sexual health content online, and by lack of trust in the veracity of peer sources.

OBJECTIVE

To investigate opportunities and challenges of using social media to facilitate peer-to-peer sharing of sexual health messages within the context of a secondary school-based and peer-led sexual health intervention (STASH; Sexually Transmitted infections And Sexual Health).

METHODS

Following training, and as part of their role, student-nominated peer supporters (aged 14-16) invited school friends to trainer-monitored, private Facebook groups. Peer supporters posted curated educational sex and relationships content within these groups. Data come from a feasibility study of the STASH intervention in 6 UK schools. To understand student experiences of the social media component we used data from: 11 semi-structured paired and group interviews with peer supporters and their friends (collectively, ‘students’; n=42; aged 14-16); a web-based post-intervention questionnaire to peer supporters (n=88); and baseline and follow-up questionnaires to students in the intervention year group (n=680 and 603 respectively). We carried out thematic analysis of qualitative data and descriptive analysis of quantitative data.

RESULTS

Message-sharing by peer supporters was hindered by variable engagement with Facebook. The trainer-monitored and private Facebook groups were acceptable to student members (peer supporters and their friends), and reassuring to peer supporters, but led to engagement that ran parallel to – rather than embedded in –their routine social media use. The offline context of a school-based intervention helped legitimate and augment the Facebook posts; but even where friends were receptive to STASH messages, they did not necessarily engage visibly. Preferences for content design varied, but humor, color and text brevity were important. Preferences for online versus offline message-sharing varied.

CONCLUSIONS

Invitation-only social media groups formed around peer supporters’ existing friendship networks hold potential for diffusing messages in peer-based sexual health interventions. Ideally, interactive opportunities should not be limited to single social media platforms and should run alongside offline conversations. There are tensions between offering young people autonomy to engage flexibly and authentically, and the need for adult-oversight of activities for information accuracy and safeguarding.

CLINICALTRIAL

Isrctn97369178
Multiple Epidemic Wave Model of the COVID-19 Pandemic: Modeling Study (Preprint)
Authors: Kaxiras Efthimios , Neofotistos Georgios
Published: June 2020

BACKGROUND

Intervention measures have been implemented around the world to mitigate the spread of the coronavirus disease (COVID-19) pandemic. Understanding the dynamics of the disease spread and the effectiveness of the interventions is essential in predicting its future evolution.

OBJECTIVE

The aim of this study is to simulate the effect of different social distancing interventions and investigate whether their timing and stringency can lead to multiple waves (subepidemics), which can provide a better fit to the wavy behavior observed in the infected population curve in the majority of countries.

METHODS

We have designed and run agent-based simulations and a multiple wave model to fit the infected population data for many countries. We have also developed a novel Pandemic Response Index to provide a quantitative and objective way of ranking countries according to their COVID-19 response performance.

RESULTS

We have analyzed data from 18 countries based on the multiple wave (subepidemics) hypothesis and present the relevant parameters. Multiple waves have been identified and were found to describe the data better. The effectiveness of intervention measures can be inferred by the peak intensities of the waves. Countries imposing fast and stringent interventions exhibit multiple waves with declining peak intensities. This result strongly corroborated with agent-based simulations outcomes. We also provided an estimate of how much lower the number of infections could have been if early and strict intervention measures had been taken to stop the spread at the first wave, as actually happened for a handful of countries. A novel index, the Pandemic Response Index, was constructed, and based on the model’s results, an index value was assigned to each country, quantifying in an objective manner the country’s response to the pandemic.

CONCLUSIONS

Our results support the hypothesis that the COVID-19 pandemic can be successfully modeled as a series of epidemic waves (subepidemics) and that it is possible to infer to what extent the imposition of early intervention measures can slow the spread of the disease.
General Public’s Information-Seeking Patterns of Topics Related to Obesity: Google Trends Analysis (Preprint)
Authors: Pawar Aditya S , Nagpal Sajan , Pawar Neha , Lerman Lilach O , Eirin Alfonso
Published: June 2020

BACKGROUND

Obesity is a major public health challenge, and recent literature sheds light on the concept of “normalization” of obesity.

OBJECTIVE

We aimed to study the worldwide pattern of web-based information seeking by public on obesity and on its related terms and topics using Google Trends.

METHODS

We compared the relative frequency of obesity-related search terms and topics between 2004 and 2019 on Google Trends. The mean relative interest scores for these terms over the 4-year quartiles were compared.

RESULTS

The mean relative interest score of the search term “obesity” consistently decreased with time in all four quartiles (2004-2019), whereas the relative interest scores of the search topics “weight loss” and “abdominal obesity” increased. The topic “weight loss” was popular during the month of January, and its median relative interest score for January was higher than that for other months for the entire study period (P<.001). The relative interest score for the search term “obese” decreased over time, whereas those scores for the terms “body positivity” and “self-love” increased after 2013.

CONCLUSIONS

Despite a worldwide increase in the prevalence of obesity, its popularity as an internet search term diminished over time. The reason for peaks in months should be explored and applied to the awareness campaigns for better effectiveness. These patterns suggest normalization of obesity in society and a rise of public curiosity about image-related obesity rather than its medical implications and harm.
Treatment of Lung Cancer Complicated by Infection of Talaromyces marneffei: Retrospective Analysis of Chest Imaging Characteristics (Preprint)
Authors: Feng Yiling , Li Xiaoping , Wang Yanqin , Lenepe Shar
Published: June 2020

BACKGROUND

Infection caused by Talaromyces marneffei is now well-known globally; however, only few reports about T. marneffei infection in lung cancer are available.

OBJECTIVE

The aims of this study were to explore the chest imaging manifestations and clinical characteristics of patients with lung cancer complicated by T. marneffeiinfection and to improve the overall diagnosis of lung cancer using clinical data, which allows for early treatment of such patients and reduction in the mortality.

METHODS

Patients with lung cancer co-infected with T. marneffei (observation group) and patients with only T. marneffei infection (control group) were studied as the research objects. The clinical characteristics and chest computed tomography imaging features of the 2 groups were compared and summarized.

RESULTS

The proportion of male patients in the observation group was 21/30 (70%), and that in the control group was 22/30 (73%). Male patients were significantly more than female patients (P<.05) in this study. The main clinical manifestations of the observation group were cough, fever, weight loss, expectoration, and fatigue. The main clinical manifestations of the control group were fever, fatigue, weight loss, skin damage, and cough. The symptoms of cough and expectoration in the observation group were significantly more than those in the control group (P<.05). In both groups the T. marneffei infection was disseminated (ie, no localized infection was seen). The use of amphotericin B, fluconazole, and itraconazole was similar between the 2 groups (P>.05). The main imaging features of the observation group were obvious enhanced scanning of focus, stripe-shaped regions, and pulmonary nodules. The obvious enhanced scanning of focus in the observation group was significantly higher than that in the control group (P<.05).

CONCLUSIONS

The clinical and imaging features of lung cancer and T. marneffei infection overlap. When the lung lesions of patients with T. marneffei infection show significant malignant signs, the possibility of lung cancer should be considered.
Persistence of PCR (RT-PCR) Positivity in COVID-19 Recovered Patients: A Call for Revised Hospital Discharge Criteria (Preprint)
Authors: Jamil Tahir , Baig Mukhtiar , Gazzaz Zohair Jamil
Published: June 2020

BACKGROUND

NA

OBJECTIVE

NA

METHODS

NA

RESULTS

NA

CONCLUSIONS

NA

CLINICALTRIAL

NA
Application of Intelligent Facial Dynamic Information Image in Warm Acupuncture and Moxibustion on Peripheral Facial Paralysis (Preprint)
Authors: Chen Yanping , Yu Dongjie , Cansoni Jane
Published: June 2020

BACKGROUND

Background: Nowadays, the application of computer technology in the medical field is more and more extensive, and many diseases can achieve better diagnosis and treatment effects through computer technology.

OBJECTIVE

Objective: The paper applies intelligent facial dynamic image information to the clinical treatment of peripheral acupuncture and moxibustion for the treatment of peripheral facial paralysis. An automatic acupoint positioning algorithm based on facial information dynamic image is proposed, which provides an objective and standard basis for the treatment of facial acupuncture and moxibustion.

METHODS

Methods: The paper selects the head threshold, that is, the facial dynamic image information as the research background, and divides the facial features according to the "three courts and five eyes" rule, and uses the Minimum Eigenvalue operator to detect the corner points of the facial features, locate the facial features, and use the face. The feature position is used as a reference coordinate for facial acupoint positioning.

RESULTS

Results: After verification, it was found that the positioning was accurate, and the peripheral facial paralysis of the patient was improved after warm acupuncture point positioning treatment, which improved the facial nerve function of the patient, improved the treatment efficiency and shortened the treatment time. Therefore, this technology is worthy of clinical promotion.

CONCLUSIONS

Conclusion: Through experimental analysis, the algorithm is proved to be effective and accurate. Based on facial dynamic image information to locate acupoints, warm acupuncture has a significant effect on peripheral facial paralysis, which can significantly improve facial nerve function and shorten treatment time, which is worthy of clinical promotion.
A large scale of nurses participated in beating down COVID-19 in China: the physical and psychological distress (Preprint)
Authors: Wang Quan , Fan Junyao , Zhao Huimin , Xi Xinxue , Liu Yueting , Kong Linglin , Wang Quan , Mao Jing
Published: June 2020

BACKGROUND

The outbreak of coronavirus disease 2019 (COVID-19) posed an unprecedented threat to health care providers （HCPs） in Wuhan, China, especially for nurses who were frequently exposed to infected or suspected patients. Limited information was available about the work-related experience of nurses in fighting against the pandemic. This study aimed to explore the physical and psychological distress of nurses during the pandemic and indicate potential risk factors.

OBJECTIVE

This study aimed to explore the physical and psychological distress of nurses during the pandemic and indicate potential risk factors.

METHODS

This multicenter cross-sectional study enrolled nurses who worked in designated hospitals, mobile cabins, or shelters/communities during the pandemic. A structured online questionnaire was distributed to assess the physical discomforts, emotional distress and cognitive reactions of nurses at work, and the log-binomial regression analysis was performed to explore potential determinants.

RESULTS

A total of 5,521 nurses were included in this study, and a considerable proportion of nurses had symptoms of physical discomforts (3682 [66.7%]), emotional distress (4725 [85.6%]). Nurses who were directly involved in the care of patients (ie, care for mild/moderate patients: RR, 1.56; 95% CI, 1.32-1.83), with non-uniform job rotation schedule (RR, 2.36; 95% CI, 1.95-2.87), and working overtime (RR, 1.34; 95% CI, 1.08-1.65) were at a higher risk for physical discomforts. Nurses who were directly involved in the care of patients (ie, care for mild/moderate patients: RR, 1.28; 95% CI, 1.05-1.58), with non-uniform job rotation schedule, and working overtime (RR, 1.51; 95% CI, 1.12-2.04) were at a higher risk for emotional distress. The exposure to physical discomforts (RR, 1.74; 95% CI, 1.45-2.07) and emotional distress (RR, 8.86; 95% CI, 5.43-14.48) contributed to a decreased self-value.

CONCLUSIONS

Non-uniform job rotation schedule and working overtime were independent risk factors for physical discomforts, emotional distress and a decreased self-value at work. Formulating reasonable job rotation rules and improving workforce systems were necessary to alleviate the physical and psychological distress of nurses during the pandemic.
Bilinguals and Their Perceptions of Both Languages in Their Brains
Authors: Falla-Wood Julia
Published: June 2020

This descriptive research examines the perception of bilingual students on the status of the mother tongue (L1) and the second language (L2) in their brains. The question of the influence or non-influence of L1 in using L2 has been studied under different theoretical frameworks. The issue of the representation of the languages in the brain has also been considered from a neurological perspective. However, no study has been undertaken on how bilinguals themselves perceive both languages in their minds. Do students see L1 and L2 as being together in one system, separate and independent of each other, or independent but sharing an intersection? The sample available to the researcher was 54 high school bilingual students. The research instruments are a questionnaire and a semi-structured face-to-face interview. The results of this study show that the highest percentage of students believe that both languages are independent of each other but share an intersection. All students have compared both languages, and have established differences and similarities between L1 and L2 through mental translations.
La evolución del marketing tradicional al marketing social en las instituciones no lucrativas: caso de la Universidad de Medellín
Authors: Álvarez Juan Guillermo , Rojo Zapata Alejandro
Published: June 2020

El marketing es una disciplina que ya excede el ámbito comercial, puesto que su metodología así como sirve paradetectar y satisfacer necesidades de consumo y uso de bienes y servicios, también es útil para detectar y satisfacernecesidades de tipo social, humanistas y espirituales; es por esto que su campo de acción no se limita solamente al ámbitoempresarial, sino que se extiende a las asociaciones sin fines de lucro, fundaciones, entidades religiosas, al estado y alas universidades. Estos nuevos campos de acción comprenden lo que los autores denominan marketing social. Entrelos contenidos del marketing social está el diseño de estrategias para el cambio de determinadas conductas, para ellose vale de los adelantos en la tecnología de las comunicaciones y en las técnicas de comercialización. El concepto demarketing social data de julio del año 1971 y lo utilizaron Kotler y Zaltman, para aplicar el uso de los postulados ytécnicas del marketing comercial en campañas de bien público o en la difusión de ideas que beneficien a la sociedad.Desde entonces, este concepto se utiliza para referirse al diseño, la puesta en práctica y el control de programas quetienen como objetivo promover una idea o práctica social en una determinada comunidad Para el caso de nuestrainvestigación, hemos escogido como ejemplo la Universidad de Medellín, para realizar una investigación cuantitativay cualitativa desde el año 2011, a través de estudios y entrevistas semiestructuradas, con los estudiantes de diferentessemestres y carreras universitaria y con el personal directivo responsable de las politicas de responsabilidad social paralograr identificar si en la UdeM tienen la práctica de realizar marketing social o si al igual que lo mencionan variosautores se confunde con la responsabilidad social.
Comentarios morales para Juan Manuel Santos, presidente de la República de Colombia 2014-2018
Authors: Román Maldonado Carlos Eduardo
Published: June 2020

El artículo describe las cualidades del príncipe que Maquiavelo señala en el Príncipe, para atribuirlas al presidenteSantos y entender de esta forma los valores morales del país, dado que la Presidencia de la República es una Institucióncon prácticas aceptadas. Las virtudes y los vicios se expresan en actos concretos que los determinan, es el carácter delindividuo, su marca. Metodológicamente se tiene lo conceptual, ideas al modo de tipos puros para configurar el marcoreferencial de la conducta humana. Como conclusión vemos dos caminos para gobernar el país, el primero puede sera través de la habilitación de posibilidades desde lo bueno que puede hacer por sí mismo y por la sociedad; el segundodejar vacíos que sean llenados por las circunstancias y actitudes desesperadas de enojo e irracionalidad de los sereshumanos.Palabras clave: valores morales, vicios, virtudes.
Optimal fermion-to-qubit mapping via ternary trees with applications to reduced quantum states learning
Authors: Jiang Zhang , Kalev Amir , Mruczkiewicz Wojciech , Neven Hartmut
Published: June 2020

We introduce a fermion-to-qubit mapping defined on ternary trees, where any single Majorana operator on ann-mode fermionic system is mapped to a multi-qubit Pauli operator acting nontrivially on⌈log3⁡(2n+1)⌉qubits. The mapping has a simple structure and is optimal in the sense that it is impossible to construct Pauli operators in any fermion-to-qubit mapping acting nontrivially on less thanlog3⁡(2n)qubits on average. We apply it to the problem of learningk-fermion reduced density matrix (RDM), a problem relevant in various quantum simulation applications. We show that one can determine individual elements of allk-fermion RDMs in parallel, to precisionϵ, by repeating a single quantum circuit for≲(2n+1)kϵ−2times. This result is based on a method we develop here that allows one to determine individual elements of allk-qubit RDMs in parallel, to precisionϵ, by repeating a single quantum circuit for≲3kϵ−2times, independent of the system size. This improves over existing schemes for determining qubit RDMs.
Perception of the Memorial Conflict around the Film “The Death of Stalin” among Russian Internet Users
Authors: Belov Sergey I.
Published: June 2020

The presented study is devoted to the problem of perception of the conflict around the film Death of Stalin among Russian Internet users. The article is based on materials from the cybermetric study conducted through the social media monitoring service IQBuzz. The methodological basis of the work is formed by cybermetric methods combined with elements of traditional content analysis and descriptive analysis. The survey showed that Russian Internet users perceived the film Stalins Death mostly negatively. Support for the release of the movie is detected in only 25% of the messages included in the sample. Support of the movie by users was mostly not politically motivated. Russian authorities didnt find support from the users for the films rental license. In their opinion, the scandal associated with the revocation of the films film license provoked increase of interest. Both opponents and apologists of the film agreed that the Ministry of Culture of the Russian Federation paid too much attention to this problem, distracting from the solution of the more significant tasks facing the department. The actions of officials were considered as an attempt to restrict freedom of speech. The reason for criticism was also inconsistency in the actions of government officials. The state opposed the release of the anti-Soviet film in terms of content, while Russian films, created in a similar ideological vein, are supported by the authorities.
Use of modulation interference microscopy in applied immunology
Authors: Gizinger O. A. , Levkova E. A. , Savin S. Z.
Published: June 2020

Objective: to determine the osmotic resistance of red blood cells using modulation interference microscopy technologies in the light microscopy mode of biological objects to identify the dynamics and determine the possibilities for continuing apitherapy in patients with autoimmune diseases. Methods. Methodological approaches to the use of modulation interference microscopy and computed tomography for the tasks of diagnostic medicine and applied immunology are described. The technology of vital computer dynamic phase metering, special methods for sample preparation of cytoobjects, as well as a computer-aided automated analysis of cytological images were used; recognition algorithms, measurement and identification of micro-objects; methods of statistical data processing. Results. Using the domestic innovative laser microscope MIM340, the osmotic resistance of erythrocytes was estimated using the method of modulation interference microscopy to identify the dynamics and determine the possibilities for continuing apitherapy in patients with rheumatoid arthritis and multiple sclerosis. Using computer methods of cytodiagnostics, new aspects of the functional morphology of living cells were revealed, clinical and morphological parallels were established. It was possible to evaluate the diagnostic and prognostic value of vital cell morphometry in various pathological processes and assess the effectiveness of therapeutic measures. A data bank of graphic images of red blood cells and blood lymphocytes of patients with diseases of the immune system has been created. Findings. The study of the structural features and functional usefulness of circulating blood cells is of great importance in addressing the pathogenesis, diagnosis, assessment of the severity of various pathological conditions and the effectiveness of the therapy. We believe that the study of living cytoobjects using the new method of coherent phase microscopy will provide the most objective data and increase the information content of the analysis, which is undoubtedly an urgent and promising task. The immediate plans include the refinement of mathematical, algorithmic, and software to support decision-making in computer-aided analysis of images of the epidermis and the surface of the dermis in neoplastic processes - malignant skin diseases. It is also necessary to create algorithmic and software tools for computerizing studies of cell models for quantitative and qualitative assessment of the selective accumulation of xenobiotics by laser microscopy.
PARADIGMA HOLISTIK EKONOMI DALAM ISLAM: STUDI PERBANDINGAN DENGAN KAPITALISME DAN SOSIALISME
Authors: Khaer Abu
Published: June 2020

Tulisan ini akan membuktikan bahwa mainstream sistem ekonomi yang berkembang, yaitu kapitalisme dan sosialisme merupakan bagian dari sistem yang Islami. Sistem ekonomi kapitalis yang sesuai dengan semangat ekonomi Islam, meminjam contoh salah satu rukun Islam berupa haji, meniscayakan umat Muslim memiliki semangat kapitalis. Untuk menunaikan ibadah haji dipersyaratkan dengan memiliki kecukupan modal (kapital). Kapitalisme yang merupakan anak kandung dari individualisme dikecam oleh Islam selama tidak memiliki kepedulian sosial terhadap sesama sebagaimana yang diusung oleh sistem ekonomi sosialis, semisal tidak ber-zakat. Sisi sistem ekonomi sosialisme berupa pemerataan kepemilikan kapital juga bernilai Islami. Namun demikian, kebersamaan dalam perekonomian sistem Islam, tidak berarti mengabaikan terhadap kuasa kepemilikan individu. Dengan demikian, kapitalisme dan sosialisme juga merupakan prinsip-prinsip universalisme Islam yang tak mungkin diingkari eksistensinya. Sistem ekonomi Islam berada di atas sistem kapitalis dan sosialis.

Metode yang digunakan dalam penelitian ini adalah studi pustaka dengan menggunakan sumber-sumber yang otoritatif dari paradigma sistem ekonomi kapitalis, sosialis, maupun Islam. Sebagai â€˜pisau analisaâ€™ penulis menggunakan pendekatan hermeneutis untuk menarik â€˜benang-merahâ€™ kepemahaman terhadap teks yang dikaji yang dalam hal ini difokuskan pada kajian mazhab ekonomi dunia.

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The Paradigm of Holistic Economy in Islam: A Comparative Study with Capitalism and Socialism.___________________________

This paper will prove that the mainstream of the developing economic system, namely capitalism and socialism is part of the Islamic system. The capitalist economic system in accordance with the spirit of Islamic economics, borrowing the example of one of the pillars of Islam in the form of Hajj, necessitates Muslims to have the spirit of the capitalist. To perform the pilgrimage is required by having capital adequacy (capital). Capitalism which is the child of individualism is condemned by Islam as long as it does not have social awareness towards others as promoted by the socialist economic system, such as zakat. The economic system of socialism in the form of equal distribution of capital ownership is also Islamic. However, togetherness in the Islamic system economy does not mean neglect of the power of individual ownership. Thus, capitalism and socialism are also the principles of Islamic universalism that cannot be denied existence. The Islamic economic system is above the capitalist and socialist system. The method used in this research is literature study by using authoritative sources from the paradigm of capitalist, socialist, and Islamic economic system. As a 'knife of analysis,' the author uses a hermeneutical approach to draw the 'red thread' of understanding on the texts studied which in this case focus on studying the world's economic school.
DETERMINANTS OF THE INTENTION OF MUZAKKI TO PAY PROFESSIONAL ZAKAT
Authors: Mukhibad Hasan , Fachrurrozie Fachrurrozie , Nurkhin Ahmad
Published: June 2020

The objective of this study is to empirically explore the effect of reputation, transparency, accountability of LAZ (Lembaga Amil Zakat or institutions that collect zakat which is a kind of Islamic tithe or alms), the religiosity of muzakki (communities who are obliged to pay zakat), and the trust of muzakki in LAZ on the strength of the intention of muzakki to pay professional zakat through amil (collectors). In addition, this study also attempts to empirically investigate the factors influencing the reputation of LAZ and the trust of muzakki in LAZ. The population of this study is civil servants in Pati District, Central Java, who already have an obligation to pay zakat. The sample of this study is determined by the incidental method and has produced 73 respondents. Data analysis uses the Structural Equation Model with the WarpPLS tool. Research showed empirically that the reputation of LAZ is positively influenced by the transparency and accountability of LAZ. The trust of muzakki in LAZ is influenced by the reputation of LAZ and the religiosity of muzakki. Furthermore, the strength of the intention of muzakki to pay zakat is influenced by the reputation of LAZ, the transparency of LAZ, the religiosity of muzakki, and the trust of muzakki in LAZ. The potential of zakat can be increased by improving LAZ performance (reputation, transparency) and the religiosity of muzakki.==============================================================================================Determinan Intensi Muzakki dalam Membayar Zakat Penghasilan. Penelitian ini secara empiris bertujuan untuk mengeksplorasi pengaruh reputasi, transparansi, akuntabilitas Lembaga Amil Zakat (LAZ), religiusitas muzakki, dan kepercayaan muzakki pada LAZ terhadap besaran keinginan muzakki untuk membayar zakat penghasilan melalui LAZ. Selain itu, penelitian ini juga bermaksud untuk secara empiris melakukan investigasi terhadap faktor-faktor yang mempengaruhi reputasi LAZ dan kepercayaan muzakki terhadap LAZ. Yang menjadi populasi dalam penelitian ini adalah para pegawai negeri sipil di Kabupaten Pati, Jawa Tengah, yang sudah sampai nishab zakat. Sampel untuk penelitian berjumlah 73 orang yang ditentukan dengan metode insidental sampling. Data lapangan kemudian dianalisis dengan Structural Equation Model dengan WarpPLS tool. Hasil kajian menunjukkan bahwa secara empiris reputasi LAZ secara positif dipengaruhi oleh transparansi dan akuntabilitas LAZ itu sendiri. Sedangkan kepercayaan muzakki terhadap LAZ dipengaruhi oleh reputasi LAZ dan religiusitas muzakki. Selanjutnya, besaran keinginan muzakki untuk membayar zakat dipengaruhi oleh reputasi, transparansi LAZ, religiusitas muzakki, dan kepercayaan muzakki terhadap LAZ. Potensi zakat bisa dimaksimalkan dengan meningkatkan kinerja LAZ (reputasi, transparansi), dan religiusitas muzakki.