bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of the policy on standard protocol for care of septic and aseptic wounds in selected public health facilities in Ghana: an analytic case study
Authors: Alhassan Robert , Karley Benedicta Quarshie-Odoo , Ackah Francis Ennin , Adodoaji Irene 
Published: February 2020

Abstract
Background It is estimated that millions of patients are affected by healthcare associated infections (HAIs) each year. In Ghana, high prevalence of HAIs in relations to septic and surgical wounds has been largely attributed to poor adherence to standard policy protocols on wound management by clinical staff especially nurses. Objective Explore the extent to which nursing staff adhere to the policy protocol on management of septic and surgical wounds in selected public health facilities in Ghana. Methodology An analytic cross-sectional study among nursing staff (n=140) in three government facilities in the Volta region of Ghana. Subjective and objective performance scores of staff on adherence proxies were compared using the Wilcoxon Signed-rank test, and univariate ordered logistic regression analysis used to predict staff likelihood of adherence to standard policy protocols on septic and surgical wound care. Findings Overall, staff self-rated themselves higher on subjective performance proxies relative to their objective scores (p<0.05). Staff with more years of work experience did not translate into a higher likelihood of adhering to standard protocol on wound healing (Coef.= -0.49, CI=-0.93 -0.05, p=0.036). Conversely, being a senior nursing officer relative to other professional ranks increases staff likelihood of complying with standard policy protocol for wound care (Coef. 5.27, CI=0.59 9.95, p=0.027) relative to lower rank of nurses. Conclusion There is the need for accelerated in-service training for staff on standard protocols for wound are coupled with supportive supervisions. Staff adherence to standard quality care should be a pre-requisite for licensing of health facilities by regulatory bodies like Health Facilities Regulatory Agency and National Health Insurance Authority.
Effect of dexmedetomidine on prevention of postoperative nausea and vomiting in pediatric strabismus surgery: A randomized controlled study
Authors: li shuangshuang , Liu Tingjie , Xia Junming , Jia Jie , Li Wenxian 
Published: February 2020

Abstract
Background : Postoperative nausea and vomiting (PONV) are common side-effects following strabismus surgery. The present study aimed to compare the effects of different doses of dexmedetomidine (DEX) on PONV incidence in pediatric patients undergoing strabismus surgery. Methods : In this prospective randomized double-blinded study, 126 pediatric patients undergoing strabismus surgery were randomized into one of three groups: Placebo group, normal saline; DEX1 group, 0.3 ug/kg dexmedetomidine, and DEX2 group, 0.5 ug/kg dexmedetomidine. Oculocardiac reflex (OCR) events were recorded during surgery. PONV or postoperative vomiting (POV) was recorded for 24 hours in the ward. Pediatric anesthesia emergence delirium (PAED) scale and emergence agitation (EA) scale were recorded in the recovery room. Results : Intraoperative OCR was significantly reduced in DEX2 group (42%) as compared to that of Placebo group (68%) (p=0.0146). During the first 24 hours post-op, the overall incidence of PONV was significantly lower in DEX2 group (10%) than that of Placebo group (32%) (p=0.0142). There was no significant difference in POV among the three groups. PAED or EA scores among the three groups were similar during recovery time. Conclusion : Dexmedetomidine (0.5 ug/kg) reduced OCR and PONV without lengthening extubation time or recovery time in pediatric patients undergoing strabismus surgery.
The Interplay Between Depression and Parkinson´s Disease: Learning the Link Through Ca2+/cAMP Signaling
Authors: Bergantin Leandro Bueno 
Published: February 2020

Background:
Parkinson´s disease (PD) and depression have an interplay at multiple cellular
levels, a phenomenon which is translated into clinical data showing that depressive patients presented
an enhanced risk for developing PD. The pathogenesis of both diseases is under intensive debate as
correlated to dysregulations related to Ca2+ signaling.

Objective:
Then, revealing this interplay between these diseases may provide novel insights into the
pathogenesis of them.

Methods:
Publications involving Ca2+ signaling, PD and depression (alone or combined) were collected
by searching PubMed and EMBASE.

Results:
Not surprisingly, calcium (Ca2+) channel blockers (CCBs), classical antihypertensive medicines,
have been demonstrated off-label effects, such as alleviating both PD and depression symptoms.

Discussion:
A mechanism under debate for the antiparkinsonism and antidepressant effects associated
to CCBs is focused on the restoration of Ca2+ signaling dysregulations. In addition, previous studies
have observed that CCBs can affect Ca2+/cAMP signaling.

Conclusion:
Thus, this article discussed the role of Ca2+/cAMP signaling in the interplay between
depression and PD, including the implications for the pharmacotherapy involving CCBs.
Pharmacological Applications of Phlorotannins: A Comprehensive Review
Authors: Javed Ahsan , Hussain Muhammad Bilal , Tahir Ali , Waheed Marwa , Anwar Ahsan , Shariati Mohammad Ali , Plygun Sergey , Laishevtcev Alexey , Pasalar Mehdi 
Published: February 2020

Background:
Seaweeds, including marine brown algae, are traditional food sources in
Asia. Phlorotannins, as the product of the polyketide pathway, are mainly found in brown algae.
Different properties have been attributed to this group of marine products ranging from antiallergic
to anticancer activity. Mechanism of action is not obvious for all these properties, but
there are some explanations for such effects.

Objective:
The current study aimed to review the phlorotannins and to assess the beneficial uses
in medicine.

Methods:
Different databases were explored with the exact terms “Phlorotannin”, “Seaweed”
and “Brown Algae”. Data assembly was finalized by June 2019. The papers showing the effects
of phlorotannins in medicine were gathered and evaluated for further assessment.

Results:
General physiological aspects of phlorotannins were firstly evaluated. Different arrays
of pharmacological properties ranging from anti-diabetic activity to cancer treatment were found.
The mechanism of action for some of these beneficiary properties has been confirmed through
rigorous examinations, but there are some features with unknown mechanisms.

Conclusion:
Phlorotannins are characterized as a multifunctional group of natural products. Potential
antioxidant characteristics could be attributed to preventive and/or their curative role in
various diseases.
Water Pollution Monitoring through Remote Sensing
Authors: Vallidevi Krishnamurthy , Gopinath Kannappan P. , Nagarajan Krishnan K. , Prakash D. Gnana , Sudhamsu Gadug , Sudhish S. , Al-Zahrani Salma A. 
Published: February 2020

Background:
Water is undoubtedly a very precious resource that helps life thrive on this planet, and its pollution is a problem which is potent of erasing almost all forms of life on earth. Hence, considering the magnitude of this problem, studies and experiments have been focused (from the day water pollution was recognised as an eminent issue) on monitoring and finding possible solutions for water pollution. While the latter deals with treating and purifying water using a variety of concepts, monitoring deals with the continuous assessment of water quality of a waterbody.

Methodology:
There are several methods for monitoring purposes, and remote sensing is a popular choice, thanks to its wide applicability and flexibility in implementation. Remote sensing basically deals with collecting data about a place (which is to be monitored) and sending the data to another ‘remote’ location for analysis. This article aims to provide a description of some methods employed in recent times for the purpose of remote sensing and a short section which deals with the analysis of the remotely sensed data using machine learning / deep learning models, hence making the reader aware of the concept of remote sensing and its scope for monitoring water pollution (or any form of pollution) in the future.

Conclusions:
The detailed comparative analysis of these methods showed that sensor based water quality monitoring with Geographical Information System (GIS) will be more efficient in detection of water pollutants. The further research in this field may introduce many advancements to enable efficient water pollution detection techniques.
Design and Development of Solid Dispersion of Valsartan by a Lyophilization Technique: A 32 Factorial Design Approach
Authors: Shirsath Nitin Rajendra , Goswami Ajaygiri Kamalgiri 
Published: February 2020

Background:
Valsartan is a poorly water-soluble drug having limited oral bioavailability. Its absorption and onset of action are mostly depending on solubility, it needs to enhance their solubility for maximum therapeutic action.

Objective:
The aim of this work is to formulate valsartan-mannitol solid dispersions (SDs) by bottom-up process based-freeze drying (lyophilization) techniques for solubility enhancement of valsartan.

Methods:
Valsartan is BCS class II drug having low aqueous solubility and low oral bioavailability. It
needs to improve its solubility for the fastest onset of action. SDs were prepared using water as a solvent
and tertiary butyl alcohol (TBA) as anti-solvent. A 32 (three level-two factors) response surface methodology
was used to detect the effect of independent variables such as the amount of valsartan (X1) and the
amount of mannitol (X2) on dependent variables such as solubility (Y1) and particle size (Y2).

Results:
Prepared SDs were characterized by employing solubility, particle size determination, differential scanning calorimetry (DSC), X-ray diffraction (XRD), zeta potential, fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM). The optimum values of solubility and particle size were 115.14µg/L and 242.5 nm respectively.

Conclusions::
Solid dispersions of valsartan-mannitol were successfully prepared by simple lyophilization techniques and seem to be promising for enhancing dissolution rate (solubility) and oral bioavailability of valsartan.
A Prediction based Cloud Resource Provisioning using SVM
Authors: Velayutham Vijayasherly , Chandrasekaran Srimathi 
Published: February 2020

Aim:
To develop a prediction model grounded on Machine Learning using Support Vector
Machine (SVM).

Background:
Prediction of workload in a Cloud Environment is one of the primary task in provisioning
resources. Forecasting the requirements of future workload lies in the competency of predicting
technique which could maximize the usage of resources in a cloud computing environment.

Objective:
To reduce the training time of SVM model.

Methods:
K-Means clustering is applied on the training dataset to form ‘n’ clusters firstly. Then, for
every tuple in the cluster, the tuple’s class label is compared with the tuple’s cluster label. If the two
labels are identical then the tuple is rightly classified and such a tuple would not contribute much
during the SVM training process that formulates the separating hyperplane with lowest generalization
error. Otherwise the tuple is added to the reduced training dataset. This selective addition of tuples
to train SVM is carried for all clusters. The support vectors are a few among the samples in reduced
training dataset that determines the optimal separating hyperplane.

Results:
On Google Cluster Trace dataset, the proposed model incurred a reduction in the training
time, Root Mean Square Error and a marginal increase in the R2 Score than the traditional SVM.
The model has also been tested on Los Alamos National Laboratory’s Mustang and Trinity cluster
traces.

Conclusion:
The Cloudsim’s CPU utilization (VM and Cloudlet utilization) was measured and it
was found to increase upon running the same set of tasks through our proposed model.
Zerwanie szóstej pieczęci i „dzień wielki gniewu ich” (Ap 6, 17)
Authors: Rucki Mirosław , Szymański Karol , Abdalla Michael 
Published: February 2020

W artykule przeanalizowano zagadnienie gniewu Baranka pojawiającego się w opisie wizji złamania szóstej pieczęci w Księdze Objawienia (Ap 6,17). Gniew Baranka jest czymś niezwykłym i paradoksalnym sam w sobie, gdyż baranek nie jest zwierzęciem kojarzącym się z gniewem. Dlatego też w badaniach zazwyczaj więcej uwagi poświęca się zwycięstwu Baranka i Jego chwale, a także roli, jaką odegrał w zbawieniu ludzi, i Jego uczcie weselnej. Niniejsze studium obejmuje kontekst złamania szóstej pieczęci oraz następujących po nim plag i nieszczęść z odniesieniami do literatury rabinicznej i tekstów innych ksiąg biblijnych. Osobno omówiono poruszenie kosmosu oraz przerażenie ludzi spowodowane gniewem baranka. Dokonano też porównania gniewu ludzkiego z gniewem Bożym.
Optimizing Low–Socioeconomic Status Pregnant Women’s Dietary Intake in the Netherlands: Protocol for a Mixed-Methods Study
Authors: Beulen Yvette H , Geelen Anouk , de Vries Jeanne HM , Super Sabina , Koelen Maria A , Feskens Edith JM , Wagemakers Annemarie 
Published: February 2020

Background
Although the importance of maternal nutrition is evident, adherence to dietary guidelines is limited in pregnant women, especially in those with a low socioeconomic status. Promotion of a healthy diet in midwifery practice is promising, as prenatal diet affects both maternal and child health, pregnant women are open to dietary changes during this critical transition, and midwives are their first and most important source of information. Unfortunately, nutrition communication by Dutch midwives is limited.

Objective
The objective of this study is to optimize the dietary intake of low–socioeconomic status pregnant women by contributing to the further development and adjustment of a tool or toolbox to support midwives in providing nutrition communication.

Methods
This interdisciplinary, mixed-methods study includes 2 phases, in which quantitative and qualitative research are complementary. In phase 1, we will conduct a literature study and interviews to gain insight into midwives’ knowledge, needs, and practice. We will obtain data on the dietary intake of low–socioeconomic status pregnant women and factors influencing this intake from another literature study, an interviewer-administered meal-based food frequency questionnaire, and qualitative interviews with pregnant women. We will identify the availability of suitable tools to improve pregnant women’s dietary intake from the literature, interviews, focus groups, and expert meetings. In phase 2, we shall adapt an existing tool or develop a new tool(box), depending on the results of phase 1, and implement it in 5 midwifery practices. Ultimately, a process evaluation will provide insight into barriers and facilitating factors playing a role in the implementation of the tool(box).

Results
The main outcome of this study will be a tool(box) to optimize the dietary intake of Dutch pregnant women. We anticipate that the developed or adjusted tool(s) will be available in February 2020. After we implement the tool(s) and evaluate the implementation process, the final results should be available by February 2021.

Conclusions
This study is scientifically and socially relevant, as we will study low–socioeconomic status pregnant women’s contextual dietary intake in-depth from an ecological perspective on health. The results obtained will lead to recommendations for multidisciplinary strategies to promote a healthy maternal dietary intake in low–socioeconomic status populations.

International Registered Report Identifier (IRRID)
DERR1-10.2196/14796
GSA to Obtain SVM Kernel Parameter for Thyroid Nodule Classification
Authors: Pramudita Dias Aziz , Musdholifah Aina 
Published: February 2020

Support Vector Machine (SVM) is one of the most popular methods of classification problems due to its global optima solution. However, the selection of appropriate parameters and kernel values remains an obstacle in the process. The problem can be solved by adding the best value of parameter during optimization process in SVM. Gravitational Search Algorithm (GSA) will be used to optimize parameters of SVM. GSA is an optimization algorithm that is inspired by mass interaction and Newton's law of gravity. This research hybridizes the GSA and SVM to increase system accuracy. The proposed approach had been implemented to improve the classification performance of Thyroid Nodule. The data used in this research are ultrasonography image of Thyroid Nodule obtained from RSUP Dr. Sardjito, Yogyakarta. This research had been evaluated by comparing the default SVM parameters with the proposed method in term of accuracy. The experiment results showed that the use of GSA on SVM is capable to increase system accuracy. In the polynomial kernel the accuracy rose up from 58.5366 % to 89.4309 %, and 41.4634 % to 98.374 % in Polynomial kernel
Klasifikasi Sel Darah Putih dan Sel Limfoblas Menggunakan Metode Multilayer Perceptron Backpropagation
Authors: Liyantoko Apri Nur , Candradewi Ika , Harjoko Agus 
Published: February 2020

Leukemia is a type of cancer that is on white blood cell. This disease are characterized by abundance of abnormal white blood cell called lymphoblast in the bone marrow. Classification of blood cell types, calculation of the ratio of cell types and comparison with normal blood cells can be the subject of diagnosing this disease. The diagnostic process is carried out manually by hematologists through microscopic image. This method is likely to provide a subjective result and time-consuming.The application of digital image processing techniques and machine learning in the process of classifying white blood cells can provide more objective results. This research used thresholding method as segmentation and multilayer method of back propagation perceptron with variations in the extraction of textural features, geometry, and colors. The results of segmentation testing in this study amounted to 68.70%. Whereas the classification test shows that the combination of feature extraction of GLCM features, geometry features, and color features gives the best results. This test produces an accuration value 91.43%, precision value of 50.63%, sensitivity 56.67%, F1Score 51.95%, and specitifity 94.16%.
Sistem Pengenal Isyarat Tangan Untuk Mengendalikan Gerakan Robot Beroda menggunakan Convolutional Neural Network
Authors: Adi Habib Astari , Candradewi Ika 
Published: February 2020

Currently, Human and computer interaction is generally done using a remote control. This approach tends to be impractical for wheeled robot operation because it must always carry an intermediary tool during the operation. The application of hand gesture recognition using digital image processing techniques and machine learning in the control process of wheeled robots will facilitate the control of wheeled robots because control no longer requires an intermediary tool.In this study, hand image taken using a camera then will be processed using a single board computer to be recognized. The results of recognized are passed on to arduino leonardo and DC motor to control twelve wheeled robot movement. The method used in this study is contrast stretching for preprocessing and Convolutional Neural Network (CNN) for hand recognition. This method is tested with a variation of bright 26-140 lux, the distance from the face to the camera is 120-200cm. Hand recognition systems using this method resulting accuracy 97,5%, precision 97,57%, sensitivity 97.5%, spesificity 99,77 and f1 score 97.45%.
Estimación del riesgo ambiental causado por plaguicidas en cultivos de arveja de Ipiales, Nariño-Colombia
Authors: Álvarez-Sánchez David , Chaves-Morillo Diana , Gómez-López Eyder , Hurtado-Benavides Andrés 
Published: February 2020

En el municipio de Ipiales, departamento de Nariño, se concentra la mayor área cultivada con arveja (Pisum sativum) de Colombia, con cerca de 3.070 ha, en donde se ha identificado un alto uso de plaguicidas asociado al establecimiento del modelo productivo. Por tanto, el objetivo de este estudio es evaluar el riesgo de impacto ambiental que genera la aplicación de los principales fungicidas, insecticidas, herbicidas y bactericidas. Para ello, se consideraron tres grupos de campesinos, previamente identificados como C1, C2 y C3 con una muestra de diez fincas por grupo. En una parcela de cada finca se determinó la materia orgánica, pH, textura, densidad aparente, distancia a fuentes hídricas y se caracterizaron los plaguicidas usados en dos ciclos de cultivo de arveja. La información recolectada fue ingresada al sistema de soporte IIRAmb para estimar el indicador I-PHY, el cual determinó el impacto ambiental de los plaguicidas. Los resultados sugieren la presencia de 44 ingredientes activos, con un uso promedio finca de 25,1 kg/ha/año; el indicador I-PHY global presentó diferencias estadísticas significativas entre C1 (4,04) respecto a C2 (5,06) y C3 (5,28), estos últimos grupos, mostraron el mayor riesgo ambiental principalmente por el tipo de moléculas usadas y las condiciones en las cuales se desarrolló el cultivo. A partir de estos resultados se genera una herramienta de monitoreo y evaluación, con el fin de mejorar las intervenciones en el sistema para incrementar el nivel de sustentabilidad.
Aplicación de un Software en Comprensión de Textos en Inglés para Estudiantes en Perú
Authors: Laura De La Cruz Kevin Mario , Velarde Molina Jehovanni Fabricio 
Published: February 2020

El presente artículo está referido a determinar los resultados de la aplicación Software JClic en la comprensión de textos en el área de inglés, en las estudiantes del nivel secundario de una institución educativa en Perú, en este caso en la I.E.P Santa Ana en el año 2018.
Se desarrolló bajo un diseño pre experimental pretest y postest con un solo grupo luego de la prueba de entrada se utilizó el software JClic a través de computadoras en laboratorios, hasta tomar la prueba de salida finalizando el semestre de estudios.
De un total de 19 estudiantes después de la aplicación software JCLIC, el 89.47% de los estudiantes han alcanzado un nivel logro destacado, el 10.53% de los estudiantes están en el nivel logro esperado, el 0% de los estudiantes están en el nivel en proceso y un 0% de los estudiantes están en el nivel en inicio.
Por los resultados obtenidos se puede afirmar: con la aplicación del software JClic las estudiantes del cuarto grado de nivel secundario de la I.E.P Santa Ana en el año 2018 han logrado mejorar su nivel en la comprensión de textos en la forma afirmativa del pasado simple en el área de inglés.