bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential Role of Phenolic Extracts of Mentha in Managing Oxidative Stress and Alzheimer’s Disease
Authors: Hanafy Doaa M. , Burrows Geoffrey E. , Prenzler Paul D. , Hill Rodney A.
Published: July 2020

With an increase in the longevity and thus the proportion of the elderly, especially in developed nations, there is a rise in pathological conditions that accompany ageing, such as neurodegenerative disorders. Alzheimer’s disease (AD) is a neurodegenerative disease characterized by progressive cognitive and memory decline. The pathophysiology of the disease is poorly understood, with several factors contributing to its development, such as oxidative stress, neuroinflammation, cholinergic neuronal apoptotic death, and the accumulation of abnormal proteins in the brain. Current medications are only palliative and cannot stop or reverse the progression of the disease. Recent clinical trials of synthetic compounds for the treatment of AD have failed because of their adverse effects or lack of efficacy. Thus, there is impetus behind the search for drugs from natural origins, in addition to the discovery of novel, conventional therapeutics. Mints have been used traditionally for conditions relevant to the central nervous system. Recent studies showed that mint extracts and/or their phenolic constituents have a neuroprotective potential and can target multiple events of AD. In this review, we provide evidence of the potential role of mint extracts and their derivatives as possible sources of treatments in managing AD. Some of the molecular pathways implicated in the development of AD are reviewed, with focus on apoptosis and some redox pathways, pointing to mechanisms that may be modulated for the treatment of AD, and the need for future research invoking knowledge of these pathways is highlighted.
Effects of Processing on Polyphenolic and Volatile Composition and Fruit Quality of Clery Strawberries
Authors: Garzoli Stefania , Cairone Francesco , Carradori Simone , Mocan Andrei , Menghini Luigi , Paolicelli Patrizia , Ak Gunes , Zengin Gokhan , Cesa Stefania
Published: July 2020

Strawberries belonging to cultivar Clery (Fragaria x ananassa (Duchesne ex Weston)), cultivated in central Italy were subjected to a multi-methodological experimental study. Fresh and defrosted strawberries were exposed to different processing methods, such as homogenization, thermal and microwave treatments. The homogenate samples were submitted to CIEL*a*b* color analysis and Head-Space GC/MS analysis to determine the impact of these procedures on phytochemical composition. Furthermore, the corresponding strawberry hydroalcoholic extracts were further analyzed by HPLC-DAD for secondary metabolites quantification and by means of spectrophotometric in vitro assays to evaluate their total phenolic and total flavonoid contents and antioxidant activity. These chemical investigations confirmed the richness in bioactive metabolites supporting the extraordinary healthy potential of this fruit as a food ingredient, as well as functional food, highlighting the strong influence of the processing steps which could negatively impact on the polyphenol composition. Despite a more brilliant red color and aroma preservation, non-pasteurized samples were characterized by a lower content of polyphenols and antioxidant activity with respect to pasteurized samples, as also suggested by the PCA analysis of the collected data.
Cognitive Aspects-Based Short Text Representation with Named Entity, Concept and Knowledge
Authors: Hou Wenfeng , Liu Qing , Cao Longbing
Published: July 2020

Short text is widely seen in applications including Internet of Things (IoT). The appropriate representation and classification of short text could be severely disrupted by the sparsity and shortness of short text. One important solution is to enrich short text representation by involving cognitive aspects of text, including semantic concept, knowledge, and category. In this paper, we propose a named Entity-based Concept Knowledge-Aware (ECKA) representation model which incorporates semantic information into short text representation. ECKA is a multi-level short text semantic representation model, which extracts the semantic features from the word, entity, concept and knowledge levels by CNN, respectively. Since word, entity, concept and knowledge entity in the same short text have different cognitive informativeness for short text classification, attention networks are formed to capture these category-related attentive representations from the multi-level textual features, respectively. The final multi-level semantic representations are formed by concatenating all of these individual-level representations, which are used for text classification. Experiments on three tasks demonstrate our method significantly outperforms the state-of-the-art methods.
Interactive Planning of Competency-Driven University Teaching Staff Allocation
Authors: Szwarc Eryk , Wikarek Jaroslaw , Gola Arkadiusz , Bocewicz Grzegorz , Banaszak Zbigniew
Published: July 2020

This paper focuses on a teacher allocation problem that is specifically concerned with assigning available academic lecturers to remaining courses from a given student curriculum. The teachers are linked to tasks according to competencies, competence requirements enforced by the curriculum as well as the number and type of disruptions that hamper the fulfilment of courses. The problem under consideration boils down to searching links between competencies possessed by teachers and competencies required by the curricula that will, firstly, balance student needs and teacher workload and, secondly, ensure an assumed robustness level of the teaching schedule. The implemented interactive method performs iterative solving of analysis and synthesis problems concerned with alternative evaluation/robustness of the competency framework. Its performance is evaluated against a set of real historical data and arbitrarily selected sets of disruptions. The computational results indicate that our method yields better solutions compared to the manual allocation by the university.
Wear Properties of Sc-Bearing Zr-Based Composite BMG with Nano-CuZr2 under Lubrication
Authors: Wang Shing-Hoa , Chou Chau-Chang , Chung Hsien-Hung , Huang Rong-Tan , Chang Horng-Yi , Hsu Cheng-An , Liaw Peter K.
Published: July 2020

Lubricated sliding wear of amorphous (Zr55Cu30Ni10Al5)99.98Sc0.02/CuZr2 nanocrystal composite bulk metallic glasses (BMG) under various sliding velocities with a load of 20 N was investigated using the pin-on-disk test. After the wear test involving oil lubrication was performed, there was no wear induced new-phase transformation in the sample surface. Friction coefficients were within the range from 0.22 to approximately 0.29 under a 20-N load at different sliding velocities. Therefore, the calculated friction coefficients clearly indicated that the adhesion wear dominated from the experimental results. This deformation behavior resulted in a higher wear rate and wear coefficient. In addition, worn surfaces were characterized and examined under a scanning electron microscope (SEM) and optical microscope. The mechanism of high wear rate was clarified.
Double Sliding-Surface Multiloop Control Reducing Semiconductor Voltage Stress on the Boost Inverter
Authors: López-Santos Oswaldo , García Germain
Published: July 2020

Sliding-mode control (SMC) has been successfully applied to boost inverters, which solves the tracking problem of imposing sinusoidal behavior to the output voltage despite the coupled or decoupled operation of both boost cells in the converter. Most of the results reported in the literature were obtained using the conventional cascade-control structure involving outer loops that generate references for one or two sliding surfaces defined using linear combinations of inductor currents and capacitor voltages. As expected, all proposed methods share the inherent robustness and insensitivity to the uncertainties of SMC, which are the reasons why one of the few comparison criteria between them is the simplicity of their implementation that is evaluated according to the required measurements and mathematical operations. Furthermore, the slight differences between the obtained dynamic performances do not allow a clear distinction of the best solution. This study presents a new SMC approach applied to a boost inverter in which two boost cells are independently commutated. Each of these boost cells integrates an outer loop, enforcing the tracking of harmonic-enriched waveforms to the capacitor voltage. Although this approach increases by two the number of measurements and requires multiloop controllers, it allows effective alleviation of the semiconductor voltage stress by reducing the required voltage gain. A complete analytical study using harmonic balance technique allows deducing a simplified model allowing to obtain a PI controller valid into to the whole set of operation conditions. The several simulation results completely verified the potential of the control proposal and the accuracy of the employed methods.
Inversion Method of Regional Range-Dependent Surface Ducts with a Base Layer by Doppler Weather Radar Echoes Based on WRF Model
Authors: Liu Xiaozhou , Wu Zhensen , Wang Hongguang
Published: July 2020

Ground clutter caused by variations of atmospheric refraction environment can occur when the weather radar is observing precipitation systems, especially in the presence of a tropospheric duct. Therefore, the acquisition of duct parameters is very important for evaluating radar performance and improving data quality. Based on the measured echo data of a Doppler weather radar located at Qingdao and the numerical simulation results of modified refractivity profiles from the Weather Research and Forecasting (WRF) model, an inversion method for regional range-dependent tropospheric duct parameters over the sea area is proposed in this paper. Due to the higher antenna height of up to 169 m, the transmission environment is assumed to be a surface duct with a base layer for locating the antenna in the trapping layer. The Principal Component Analysis (PCA) and Parabolic Equation (PE) methods were used to characterize the horizontal inhomogeneity of duct parameters and the propagation of electromagnetic waves in the tropospheric duct. In the inversion model, duct parameters extracted from WRF outputs were used as the initial values. Additionally, multithread parallel processing was adopted in order to reduce the inversion time based on the characteristics of the optimization algorithm. The overall variation tendencies of the WRF simulation results in the regional distribution of duct parameters were well consistent with the inversion results, but were relatively lower in terms of specific values. Due to the influence of precipitation targets on measured echo data, the inversed echo data had different agreements with the measurements in space, and the absolute error values were less than 5 dB in about 90% of the region of interest.
Comparison of the Photoautotrophic Growth Regimens of Chlorella sorokiniana in a Photobioreactor for Enhanced Biomass Productivity
Authors: Ziganshina Elvira E. , Bulynina Svetlana S. , Ziganshin Ayrat M.
Published: July 2020

Microalgae have a wide industrial potential because of their high metabolic diversity and plasticity. Selection of optimal cultivation methods is important to optimize multi-purpose microalgal biotechnologies. In this research, Chlorella sorokiniana AM-02 that was isolated from a freshwater lake was cultured under various high photosynthetic photon flux density (PPFD) conditions and CO2 gas levels in standard Bold’s basal medium (BBM). Furthermore, a wide range of nitrate levels (180–1440 mg L−1) was tested on the growth of C. sorokiniana. Microalgae growth, pigment concentration, medium pH, exit gas composition, as well as nitrate, phosphate, and sulfate levels were measured during an experimental period. The preferred high PPFD and optimal CO2 levels were found to be 1000–1400 μmol photons m−2 s−1 and 0.5–2.0% (v/v), respectively. The addition of nitrate ions (up to 1440 mg L−1) to the standard growth medium increased final optical density (OD750), cell count, pigment concentration, and total biomass yield but decreased the initial growth rate at high nitrate levels. Our findings can serve as the basis for a robust photoautotrophic cultivation system to maximize the productivity of large-scale microalgal cultures.
Amino Acid Metabolites Associated with Chronic Kidney Disease: An Eight-Year Follow-Up Korean Epidemiology Study
Authors: Lee Hansongyi , Jang Han Byul , Yoo Min-Gyu , Park Sang Ick , Lee Hye-Ja
Published: July 2020

The discovery of metabolomics-based biomarkers has been a focus of recent kidney dysfunction research. In the present study, we aimed to identify metabolites associated with chronic kidney disease (CKD) in the general population using a cross-sectional study design. At baseline, 6.5% of subjects had CKD. Pearson correlation analysis showed that 28 metabolites were significantly associated with estimated glomerular filtration rate (eGFR) after Bonferroni correction. Among these metabolites, 4 acylcarnitines, 12 amino acids, 4 biogenic amines, 1 phosphatidylcholine, and 1 sphingolipid were associated with CKD (p < 0.05). After eight years, 13.5% of subjects had CKD. Three amino acid metabolites were positively associated with new-onset CKD: citrulline [odds ratio (OR): 2.41, 95% confidence interval (CI): 1.26–4.59], kynurenine (OR: 1.98, 95% CI: 1.05–3.73), and phenylalanine (OR: 2.68, 95% CI: 1.00–7.16). The kynurenine:tryptophan ratio was also associated with CKD (OR: 3.20; 95% CI: 1.57–6.51). The addition of multiple metabolites significantly improved the CKD prediction by C statistics (0.756–0.85, p < 0.0001), and the net reclassification improvement was 0.84 (95% CI: 0.72–0.96). Elevated hs-C reactive protein (CRP) was associated with new-onset CKD (OR: 1.045, 95% CI: 1.005–1.086); however, this association disappeared following adjustment with the kynurenine:tryptophan ratio. The levels of citrulline and kynurenine and their ratio to tryptophan in CKD patients with proteinuria were worse than those with one or neither characteristic. Together, the results of this study demonstrate that amino acid metabolites are associated with CKD eight years after initial metabolite assessment. These results could improve the identification of subjects at high risk of CKD who have modified amino acid metabolism.
Key Milestones Contributing to the Understanding of the Mechanisms Underlying Fibromyalgia
Authors: Littlejohn Geoffrey , Guymer Emma
Published: July 2020

The promulgation of the American College of Rheumatology (ACR) 1990 criteria for fibromyalgia (FM) classification has significantly contributed to an era of increased research into mechanisms that underlie the disorder. The previous emphasis on putative peripheral nociceptive mechanisms has advanced to identifying of changes in central neural networks that modulate pain and other sensory processes. The influences of psychosocial factors on the dynamic and complex neurobiological mechanisms involved in the fibromyalgia clinical phenotype are now better defined. This review highlights key milestones that have directed knowledge concerning the fundamental mechanisms contributing to fibromyalgia.
Machine Learning Detects Pattern of Differences in Functional Magnetic Resonance Imaging (fMRI) Data between Chronic Fatigue Syndrome (CFS) and Gulf War Illness (GWI)
Authors: Provenzano Destie , Washington Stuart D. , Rao Yuan J. , Loew Murray , Baraniuk James
Published: July 2020

Background: Gulf War Illness (GWI) and Chronic Fatigue Syndrome (CFS) are two debilitating disorders that share similar symptoms of chronic pain, fatigue, and exertional exhaustion after exercise. Many physicians continue to believe that both are psychosomatic disorders and to date no underlying etiology has been discovered. As such, uncovering objective biomarkers is important to lend credibility to criteria for diagnosis and to help differentiate the two disorders. Methods: We assessed cognitive differences in 80 subjects with GWI and 38 with CFS by comparing corresponding fMRI scans during 2-back working memory tasks before and after exercise to model brain activation during normal activity and after exertional exhaustion, respectively. Voxels were grouped by the count of total activity into the Automated Anatomical Labeling (AAL) atlas and used in an “ensemble” series of machine learning algorithms to assess if a multi-regional pattern of differences in the fMRI scans could be detected. Results: A K-Nearest Neighbor (70%/81%), Linear Support Vector Machine (SVM) (70%/77%), Decision Tree (82%/82%), Random Forest (77%/78%), AdaBoost (69%/81%), Naïve Bayes (74%/78%), Quadratic Discriminant Analysis (QDA) (73%/75%), Logistic Regression model (82%/82%), and Neural Net (76%/77%) were able to differentiate CFS from GWI before and after exercise with an average of 75% accuracy in predictions across all models before exercise and 79% after exercise. An iterative feature selection and removal process based on Recursive Feature Elimination (RFE) and Random Forest importance selected 30 regions before exercise and 33 regions after exercise that differentiated CFS from GWI across all models, and produced the ultimate best accuracies of 82% before exercise and 82% after exercise by Logistic Regression or Decision Tree by a single model, and 100% before and after exercise when selected by any six or more models. Differential activation on both days included the right anterior insula, left putamen, and bilateral orbital frontal, ventrolateral prefrontal cortex, superior, inferior, and precuneus (medial) parietal, and lateral temporal regions. Day 2 had the cerebellum, left supplementary motor area and bilateral pre- and post-central gyri. Changes between days included the right Rolandic operculum switching to the left on Day 2, and the bilateral midcingulum switching to the left anterior cingulum. Conclusion: We concluded that CFS and GWI are significantly differentiable using a pattern of fMRI activity based on an ensemble machine learning model.
A New Palmitoylethanolamide Form Combined with Antioxidant Molecules to Improve Its Effectivess on Neuronal Aging
Authors: Morsanuto Vera , Galla Rebecca , Molinari Claudio , Uberti Francesca
Published: July 2020

Palmitoylethanolamide is a nutraceutical compound naturally produced in many plants and animal source foods, but the natural form is poorly water-soluble. It has demonstrated an anti-inflammatory role as a neuroprotective mediator, acting on several molecular targets of the central nervous system involved on brain aging process. In healthy adults, palmitoylethanolamide is an endogenous PPAR-α (peroxisome proliferator-activated receptor α) agonist through which it performs anti-inflammatory activity and provides its effects by activating the cannabinoid receptor. The different formulations of palmitoylethanolamide (micronized palmitoylethanolamide, FM-LipoMatrix® palmitoylethanolamide and FM-LipoMatrix® palmitoylethanolamide plus lipoic acid and vitamin D3) were analyzed starting from intestinal barrier, to verify their bioavailability, to in primary astrocytes in which cell viability, reactive oxygen species (ROS) and nitric oxide (NO) production, NFKB activity, MAPK, p53 and PPARα activities were investigated. Additionally, cannabinoid and estrogen receptors were analyzed using the western blot technique. The combination of palmitoylethanolamide in FM-LipoMatrix®, lipoic acid and vitamin D3 shows better absorption predicting an improvement on plasma concentration; this formulation also shows a reduction in ROS and NO production and the data show the interaction of palmitoylethanolamide with cannabinoids and estrogen receptors inhibiting neuroinflammatory markers. All these data support the hypothesis of a new potential strategy to restore brain function and slow down brain aging in humans.
Impact of Aquatic Exercise on Respiratory Outcomes and Functional Activities in Children with Neuromuscular Disorders: Findings from an Open-Label and Prospective Preliminary Pilot Study
Authors: Huguet-Rodríguez Marta , Arias-Buría José Luis , Huguet-Rodríguez Belén , Blanco-Barrero Rocío , Braña-Sirgo Daniel , Güeita-Rodríguez Javier
Published: July 2020

Neuromuscular disorders (NMD) lead to the progressive loss of motor and respiratory functions and a decline in daily activities and participation. We aimed to evaluate respiratory changes and functional outcomes in children attending an aquatic therapy program. Eleven patients diagnosed with NMD (4–18 years, Vignos scale 1–9) were involved in a 10-week aquatic exercise program. The ventilation variables were: peak cough flow, volumes (forced expiratory volume in one second-FEV1 and inspiratory volume) and respiratory pressures to evaluate strength and oxygen saturation (O2 sat). Functional skills were measured in the aquatic environment (Water Orientation Test Alyn 1) and on dry land, (Pediatric Evaluation of Disability Inventory), together with quality of life (Pediatric Quality of Life Inventory). Our evaluation included several 2 × 6 mixed-model repeated measures analysis of covariance (ANCOVA) with time (baseline, post 1 session, pre-post at five weeks and pre-post at 10 weeks). Important improvements in functional skills were observed in and out of the water and children under the age of 11 displayed a significant difference for inspirational volume (p = 0.002) and O2 sat (p = 0.029). Clinical, statistically insignificant changes were found for peak cough flow and expiratory pressures values after aquatic exercise. These results may support a relationship between aquatic exercise in NMD, respiratory outcomes and functional activities in water and on land.
“No Pain No Gain”: Evidence from a Parcel-Wise Brain Morphometry Study on the Volitional Quality of Elite Athletes
Authors: Wei Gaoxia , Si Ruoguang , Li Youfa , Yao Ying , Chen Lizhen , Zhang Shu , Huang Tao , Zou Liye , Li Chunxiao , Perrey Stephane
Published: July 2020

Volition is described as a psychological construct with great emphasis on the sense of agency. During volitional behavior, an individual always presents a volitional quality, an intrapersonal trait for dealing with adverse circumstances, which determines the individual’s persistence of action toward their intentions or goals. Elite athletes are a group of experts with superior volitional quality and, thereby, could be regarded as the natural subject pool to investigate this mental trait. The purpose of this study was to examine brain morphometric characteristics associated with volitional quality by using magnetic resonance imaging (MRI) and the Scale of Volitional Quality. We recruited 16 national-level athletes engaged in short track speed skating and 18 healthy controls matched with age and gender. A comparison of a parcel-wise brain anatomical characteristics of the healthy controls with those of the elite athletes revealed three regions with significantly increased cortical thickness in the athlete group. These regions included the left precuneus, the left inferior parietal lobe, and the right superior frontal lobe, which are the core brain regions involved in the sense of agency. The mean cortical thickness of the left inferior parietal lobe was significantly correlated with the independence of volitional quality (a mental trait that characterizes one’s intendency to control his/her own behavior and make decisions by applying internal standards and/or objective criteria). These findings suggest that sports training is an ideal model for better understanding the neural mechanisms of volitional behavior in the human brain.
Work-Related Dreams: An Online Survey
Authors: Schredl Michael , Anderson Lilian Marie , Kahlert Lea Katharina , Kumpf Celine Sophie
Published: July 2020

Professional work is an integral part of modern life. According to the continuity hypothesis of dreaming, which states that dreams reflect waking life, work-related dreams should be quite common. As most dream content analytic studies are carried out in student samples, the topic of work in dreams is understudied. A few small studies indicate that the stress levels associated with the job are especially reflected in work-related dreams. Here, a total of 1695 people (960 women, 735 men) completed an online survey that included questions about the estimated percentage of work-related dreams, the overall emotional tone of work-related dreams, and waking-life experiences related to their current job situation (working or not working). The findings indicate that every fifth dream is related to current or previous work. Individuals who are working dreamed more often about work, with jobs that are experienced as being more stressful being more likely to affect dream content. The emotional tone of work-related dreams was related to stress and the emotions related to work in waking life. Overall, the findings demonstrate that professional life has a profound effect on dreaming in many individuals—even after years. The next steps would be to study the dream content of work-related dreams and relate these contents to specific characteristics about the jobs, e.g., professional field, hierarchical position and autonomy, etc.
Edible and Functionalized Films/Coatings—Performances and Perspectives
Authors: Avramescu Sorin Marius , Butean Claudia , Popa Claudia Valentina , Ortan Alina , Moraru Ionut , Temocico Georgeta
Published: July 2020

In recent years, food packaging has evolved from an inert and polluting waste that remains after using the product toward an active item that can be consumed along with the food it contains. Edible films and coatings represent a healthy alternative to classic food packaging. Therefore, a significant number of studies have focused on the development of biodegradable enveloping materials based on biopolymers. Animal and vegetal proteins, starch, and chitosan from different sources have been used to prepare adequate packaging for perishable food. Moreover, these edible layers have the ability to carry different active substances such as essential oils—plant extracts containing polyphenols—which bring them considerable antioxidant and antimicrobial activity. This review presents the latest updates on the use of edible films/coatings with different compositions with a focus on natural compounds from plants, and it also includes an assessment of their mechanical and physicochemical features. The plant compounds are essential in many cases for considerable improvement of the organoleptic qualities of embedded food, since they protect the food from different aggressive pathogens. Moreover, some of these useful compounds can be extracted from waste such as pomace, peels etc., which contributes to the sustainable development of this industry.
Erratum: Wu, Z., Zhang, W. Fractional Refined Composite Multiscale Fuzzy Entropy of International Stock Indices. Entropy 2019, 21(9), 914
Authors: Wu Zhiyong , Zhang Wei
Published: July 2020

We have found an error in grant number in Funding published in Entropy [...]
Lattice–Gas–Automaton Modeling of Income Distribution
Authors: Cui Lijie , Lin Chuandong
Published: July 2020

A simple and effective lattice–gas–automaton (LGA) economic model is proposed for the income distribution. It consists of four stages: random propagation, economic transaction, income tax, and charity. Two types of discrete models are introduced: two-dimensional four-neighbor model (D2N4) and D2N8. For the former, an agent either remains motionless or travels to one of its four neighboring empty sites randomly. For the latter, the agent may travel to one of its nearest four sites or the four diagonal sites. Afterwards, an economic transaction takes place randomly when two agents are located in the nearest (plus the diagonal) neighboring sites for the D2N4 (D2N8). During the exchange, the Matthew effect could be taken into account in the way that the rich own a higher probability of earning money than the poor. Moreover, two kinds of income tax models are incorporated. One is the detailed taxable income brackets and rates, and the other is a simplified tax model based on a fitting power function. Meanwhile, charity is considered with the assumption that a richer agent donates a part of his income to charity with a certain probability. Finally, the LGA economic model is validated by using two kinds of benchmarks. One is the income distributions of individual agents and two-earner families in a free market. The other is the shares of total income in the USA and UK, respectively. Besides, impacts of the Matthew effect, income tax and charity upon the redistribution of income are investigated. It is confirmed that the model has the potential to offer valuable references for formulating financial laws and regulations.
Internal Migration in Spain: A Complementary Approach
Authors: Maza Adolfo
Published: July 2020

This study examines the determinants of internal migration of working-age population among provinces in Spain in the aftermath of the economic crisis. It pays special attention to two features of migration that have not been sufficiently studied so far: (a) Distance, namely the differences between the determinants that are behind short-distance and long-distance movements; (b) Age, that is to say, whether young and adult migrants hold different motivations. To accomplish this aim, an extended model is used in which, apart from a variable capturing distance, both economic and non-economic (amenities) variables are included. Findings reveal that both economic factors (mainly unemployment and income) and amenities (measured by a climate condition variable) are more important for adult population and long-distance movements than for young population and movements between neighbouring provinces. Additional findings seem to convey the message that, as far as housing prices are concerned, they play a significant role when migration takes place between neighbouring provinces, but lose importance when all migrations are studied together. Moreover, the paper’s results do not cast, as expected, any doubt on the importance of distance regardless of the type of migration or age of the migrant.
Machine Learning Based PEVs Load Extraction and Analysis
Authors: Mansour-Saatloo Amin , Moradzadeh Arash , Mohammadi-Ivatloo Behnam , Ahmadian Ali , Elkamel Ali
Published: July 2020

Transformation of the energy sector due to the appearance of plug-in electric vehicles (PEVs) has faced the researchers with challenges in recent years. The foremost challenge is uncertain behavior of a PEV that hinders operators determining a deterministic load profile. Load forecasting of PEVs is so crucial in both operating and planning of the energy systems. PEV load demand mainly depends on traveling behavior of them. This paper tries to present an accurate model to forecast PEVs’ traveling behavior in order to extract the PEV load profile. The presented model is based on machine-learning techniques; namely, a generalized regression neural network (GRNN) that correlates between PEVs’ arrival/departure times and traveling behavior is considered in the model. The results show the ability of the GRNN to communicate between arrival/departure times of PEVs and the distance traveled by them with a correlation coefficient (R) of 99.49% for training and 98.99% for tests. Therefore, the trained and saved GRNN model is ready to forecast PEVs’ trip length based on training and testing with historical data. Finally, the results indicate the importance of implementing more accurate methods to predict PEVs to gain the significant advantages in the importance of electrical energy in vehicles in the years to come.
Analysis of the Results of Heel-Rise Test with Sensors: A Systematic Review
Authors: Pires Ivan Miguel , Ponciano Vasco , Garcia Nuno M. , Zdravevski Eftim
Published: July 2020

Strokes are a constant concern for people and pose a major health concern. Tests that allow detection and the rehabilitation of patients have started to become more important and essential. There are several tests used by physiotherapists to speed up the recovery process of patients. This article presents a systematic review of existing studies using the Heel-Rise Test and sensors (i.e., accelerometers, gyroscopes, pressure and tilt sensors) to estimate the different levels and health statuses of individuals. It was found that the most measured parameter was related to the number of repetitions, and the maximum number of repetitions for a healthy adult is 25 repetitions. As for future work, the implementation of these methods with a simple mobile device will facilitate the different measurements on this subject.
Stochastic NPV Based vs Stochastic LCOE Based Power Portfolio Selection Under Uncertainty
Authors: Mari Carlo
Published: July 2020

This paper investigates the problem of power portfolio selection under uncertainty using two different metrics, namely the stochastic Net Present Value (NPV) and the stochastic Levelized Cost of Electricity (LCOE). In the first metric, stochastic revenues, as well as stochastic costs incurred during the whole lifetime of power plants, are taken into account. The second metric is based on stochastic costs only. This means that revenues deriving from selling electricity in power markets over long-term horizons play an important role in determining optimal portfolios under the stochastic NPV metric, but they have no impact on optimal portfolios under the stochastic LCOE metric. Uncertainty arising from unpredictable movements of electricity market prices, fossil fuels, and nuclear fuel prices is considered. Moreover, stochastic CO 2 costs are included into the analysis. The aim of this study was to examine in what circumstances efficient NPV-based portfolios differ in a significant way from efficient LCOE-based portfolios. The portfolio selection is performed using two different risk measures, namely the standard deviation and the Conditional Value at Risk Deviation (CVaR) deviation. The proposed methodology can be used as a powerful tool of analysis for planning profitable investments in new generating technologies paying attention to risk reducing strategies through power sources diversification.
A Decoding-Complexity and Rate-Controlled Video-Coding Algorithm for HEVC
Authors: Mallikarachchi Thanuja , Talagala Dumidu , Kodikara Arachchi Hemantha , Hewage Chaminda , Fernando Anil
Published: July 2020

Video playback on mobile consumer electronic (CE) devices is plagued by fluctuations in the network bandwidth and by limitations in processing and energy availability at the individual devices. Seen as a potential solution, the state-of-the-art adaptive streaming mechanisms address the first aspect, yet the efficient control of the decoding-complexity and the energy use when decoding the video remain unaddressed. The quality of experience (QoE) of the end-users’ experiences, however, depends on the capability to adapt the bit streams to both these constraints (i.e., network bandwidth and device’s energy availability). As a solution, this paper proposes an encoding framework that is capable of generating video bit streams with arbitrary bit rates and decoding-complexity levels using a decoding-complexity–rate–distortion model. The proposed algorithm allocates rate and decoding-complexity levels across frames and coding tree units (CTUs) and adaptively derives the CTU-level coding parameters to achieve their imposed targets with minimal distortion. The experimental results reveal that the proposed algorithm can achieve the target bit rate and the decoding-complexity with 0.4% and 1.78% average errors, respectively, for multiple bit rate and decoding-complexity levels. The proposed algorithm also demonstrates a stable frame-wise rate and decoding-complexity control capability when achieving a decoding-complexity reduction of 10.11 (%/dB). The resultant decoding-complexity reduction translates into an overall energy-consumption reduction of up to 10.52 (%/dB) for a 1 dB peak signal-to-noise ratio (PSNR) quality loss compared to the HM 16.0 encoded bit streams.
Stability Analysis and Numerical Computation of the Fractional Predator–Prey Model with the Harvesting Rate
Authors: Yavuz Mehmet , Sene Ndolane
Published: July 2020

In this work, a fractional predator-prey model with the harvesting rate is considered. Besides the existence and uniqueness of the solution to the model, local stability and global stability are experienced. A novel discretization depending on the numerical discretization of the Riemann–Liouville integral was introduced and the corresponding numerical discretization of the predator–prey fractional model was obtained. The net reproduction number R 0 was obtained for the prediction and persistence of the disease. The dynamical behavior of the equilibria was examined by using the stability criteria. Furthermore, numerical simulations of the model were performed and their graphical representations are shown to support the numerical discretizations, to visualize the effectiveness of our theoretical results and to monitor the effect of arbitrary order derivative. In our investigations, the fractional operator is understood in the Caputo sense.
Korean Nursing Students’ First Experiences of Clinical Practice in Psychiatric Nursing: A Phenomenological Study
Authors: Cha Sunkyung , Moon Hyunjung , Park Eunyoung
Published: July 2020

Nursing students have a more negative attitude toward psychiatric practice than other practices. In particular, Korean nursing students experience increased pressure during clinical practice in psychiatric nursing due to sociocultural and institutional influences, such as prejudices, fear, and anxiety towards mental illnesses. This study aimed to conduct an investigation on students’ first experiences of clinical practice in psychiatric nursing. Participants were 12 fourth year nursing students in South Korea. The data were collected through semi-structured interviews, and data analysis was done using Colaizzi’s phenomenological method. The students’ experiences of clinical practice in psychiatric nursing could be categorized into emotional fluctuation, burnout, transformation, and growth. The results of this study show that nursing students experienced emotional fluctuation and burnout at the beginning of their clinical practice in psychiatric nursing. At the end of the clinical practice, they experienced transformation and growth. The study suggests that nursing instructors and on-site staff need to interact with nursing students to understand the nature of these first experiences and support them through teaching and field guidance.
Factors Influencing Global Variations in COVID-19 Cases and Fatalities; A Review
Authors: Abu-Hammad Osama , Alnazzawi Ahmad , Borzangy Sary , Abu-Hammad Abdalla , Fayad Mostafa , Saadaledin Selma , Abu-Hammad Shaden , Dar-Odeh Najla
Published: July 2020

Since the first cases of the novel corona virus disease (COVID-19) were diagnosed in China, outcomes associated with this infection in terms of total numbers of cases and deaths have varied widely between countries. While some countries had minimal rates of infections and deaths, other countries were hit hard by the pandemic. Countries with highest numbers of cases continued to change over time, but at the time of submission of this article they are: USA, Brazil, Russia, UK, India, Spain, Italy, Peru and Chile. This is in contrary to many countries in the Middle East, Far East, and Africa, which had lower cases or deaths/cases rates. This raised many questions pertaining to this variation. This overview explores the potential factors that contribute to spread, transmission and outcomes of the COVID-19 infection. It also uses an evidence-based approach in reviewing the available most recent literature that tackled the various factors that modify the populations’ response to COVID-19, namely, factors pertaining to population characteristics, environmental and geographic factors.
Medieval Glassworks in the City of Ferrara (North Eastern Italy): The Case Study of Piazza Municipale
Authors: Marrocchino Elena , Telloli Chiara , Caraccio Sara , Guarnieri Chiara , Vaccaro Carmela
Published: July 2020

Compositional and structural characterization was carried out on transparent glass fragments found in a brick rubbish pit discovered in basal floor of the ducal palace of Ferrara, during the excavation of Piazza Municipale. This study aims to identify raw materials and glass-working techniques through X-Ray Fluorescence (XRF) quantitative chemical analyses and semi-quantitative Scanning Electron Microscopy (SEM) observations. The studied fragments were produced using siliceous-lime sands with natron as flux, and allowed us to better understand the production technologies in a historical period of great innovation for European glass art. The numerous findings of glass fragments discovered in brick underground cellars built for the specific purpose of household rubbish of wealthy complexes in Ferrara testify a consolidated system of separate discharge of solid waste into underground containers, which were closed and sealed once filled. The high volume of the finds indicates the absence of recycling of accumulated materials due to the well-being of the city. Compositional analysis confirmed the local production of glass shops in Ferrara during the late Middle Ages, characterized by differences with the glasses of the nearby city of Venice. Morphological analyses also defined the nature and relative abundance of the products, exploring the types and compositions of the Ferrara glass art.
ABCG2 Protein Levels and Association to Response to First-Line Irinotecan-Based Therapy for Patients with Metastatic Colorectal Cancer
Authors: Palshof Jesper Andreas , Cederbye Camilla Natasha , Høgdall Estrid Vilma Solyom , Poulsen Tim Svenstrup , Linnemann Dorte , Nygaard Sune Boris , Stenvang Jan , Christensen Ib Jarle , Jensen Benny Vittrup , Pfeiffer Per , Brünner Nils , Yilmaz Mette , Viuff Birgitte Martine , Nielsen Dorte Lisbet
Published: July 2020

In this study we investigated the use of cancer cell protein expression of ABCG2 to predict efficacy of systemic first-line irinotecan containing therapy in patients with metastatic colorectal cancer (mCRC). From a Danish national cohort, we identified 119 mCRC patients treated with irinotecan containing therapy in first-line setting. Among these, 108 were eligible for analyses. Immunohistochemistry (IHC) analyses were performed on the primary tumor tissue in order to classify samples as high or low presence of ABCG2 protein. Data were then associated with patient outcome (objective response (OR), progression free survival (PFS) and overall survival (OS)). ABCG2 protein expression in the basolateral membrane was high (score 3+) in 33% of the patients. Exploratory analyses revealed a significant interaction between ABCG2 score, adjuvant treatment and OR (p = 0.041) in the 101 patients with evaluable disease. Patients with low ABCG2 (score 0–2) and no prior adjuvant therapy had a significantly higher odds ratio of 5.6 (Confidence Interval (CI) 1.68–18.7; p = 0.005) for obtaining OR. In contrast, no significant associations between ABCG2 expression and PFS or OS were found. These results suggest that measurement of the ABCG2 drug efflux pump might be used to select patients with mCRC for irinotecan treatment. However, additional studies are warranted before conclusions regarding a clinical use can be made. Moreover, patients with high ABCG2 immunoreactivity could be candidates for specific ABCG2 inhibition treatment in combination with irinotecan.
Hereditary Predisposition to Prostate Cancer: From Genetics to Clinical Implications
Authors: Brandão Andreia , Paulo Paula , Teixeira Manuel R.
Published: July 2020

Prostate cancer (PrCa) ranks among the top five cancers for both incidence and mortality worldwide. A significant proportion of PrCa susceptibility has been attributed to inherited predisposition, with 10–20% of cases expected to occur in a hereditary/familial context. Advances in DNA sequencing technologies have uncovered several moderate- to high-penetrance PrCa susceptibility genes, most of which have previously been related to known hereditary cancer syndromes, namely the hereditary breast and ovarian cancer (BRCA1, BRCA2, ATM, CHEK2, and PALB2) and Lynch syndrome (MLH1, MSH2, MSH6, and PMS2) genes. Additional candidate genes have also been suggested, but further evidence is needed to include them in routine genetic testing. Recommendations based on clinical features, family history, and ethnicity have been established for more cost-efficient genetic testing of patients and families who may be at an increased risk of developing PrCa. The identification of alterations in PrCa predisposing genes may help to inform screening strategies, as well as treatment options, in the metastatic setting. This review provides an overview of the genetic basis underlying hereditary predisposition to PrCa, the current genetic screening recommendations, and the implications for clinical management of the disease.
Combinatory Treatment with miR-7-5p and Drug-Loaded Cubosomes Effectively Impairs Cancer Cells
Authors: Gajda Ewa , Godlewska Marlena , Mariak Zenon , Nazaruk Ewa , Gawel Damian
Published: July 2020

Background: Multidrug resistance (MDR) is an emerging problem in the treatment of cancer. Therefore, there is a necessity for novel strategies that would sensitize tumor cells to the administered chemotherapeutics. One of the innovative approaches in fighting drug-resistant tumors is the treatment of cancer with microRNA (miRNA), or the use of cubosomes (lipid nanoparticles) loaded with drugs. Here, we present a study on a novel approach, which combines both tools. Methods: Cubosomes loaded with miR-7-5p and chemotherapeutics were developed. The effects of drug- and miRNA-loaded vehicles on glioma- (A172, T98G), papillary thyroid- (TPC-1) and cervical carcinoma-derived (HeLa) cells were analyzed using molecular biology techniques, including quantitative real-time PCR, MTS-based cell proliferation test, flow cytometry and spheroids formation assay. Results: The obtained data indicate that miR-7-5p increases the sensitivity of the tested cells to the drug, and that nanoparticles loaded with both miRNA and the drug produce a greater anti-tumor effect in comparison to the free drug treatment. It was found that an increased level of apoptosis in the drug/miRNA co-treated cells is accompanied by an alternation in the expression of the genes encoding for key MDR proteins of the ABC family. Conclusions: Overall, co-administration of miR-7-5p with a chemotherapeutic can be considered a promising strategy, leading to reduced MDR and the induction of apoptosis in cancer cells.
Exclusion Zone Phenomena in Water—A Critical Review of Experimental Findings and Theories
Authors: Elton Daniel C. , Spencer Peter D. , Riches James D. , Williams Elizabeth D.
Published: July 2020

The existence of the exclusion zone (EZ), a layer of water in which plastic microspheres are repelled from hydrophilic surfaces, has now been independently demonstrated by several groups. A better understanding of the mechanisms which generate EZs would help with understanding the possible importance of EZs in biology and in engineering applications such as filtration and microfluidics. Here we review the experimental evidence for EZ phenomena in water and the major theories that have been proposed. We review experimental results from birefringence, neutron radiography, nuclear magnetic resonance, and other studies. Pollack theorizes that water in the EZ exists has a different structure than bulk water, and that this accounts for the EZ. We present several alternative explanations for EZs and argue that Schurr’s theory based on diffusiophoresis presents a compelling alternative explanation for the core EZ phenomenon. Among other things, Schurr’s theory makes predictions about the growth of the EZ with time which have been confirmed by Florea et al. and others. We also touch on several possible confounding factors that make experimentation on EZs difficult, such as charged surface groups, dissolved solutes, and adsorbed nanobubbles.