bluuebunny/crossref_metadata_2025 huggingface dataset:
Allergen Exposure in Murine Neonates Promoted the Development of Asthmatic Lungs
Authors: Chen Jeng-Chang , Chan Cheng-Chi , Ting Nai-Chun , Kuo Ming-Ling
Published: June 2021

We previously demonstrated that fetal allergen exposure caused T-helper 2 (Th2) cell sensitization. Although neonates are immunologically more mature than fetuses, asthmatic lungs were reportedly mitigated by neonatal allergen administration, mechanically referring to regulatory T-cells and TGF-β signaling but lacking the immunological profiles after neonatal exposure. To reappraise the immunological outcome of neonatal allergen exposure, we injected adjuvant-free ovalbumin intraperitoneally into 2-day-old BALB/c neonates, followed by aerosolized ovalbumin inhalation in adulthood. Mice were examined for the immunological profiles specifically after neonatal exposures, lung function and histology (hematoxylin-eosin or periodic acid Schiff staining), and gene expressions of intrapulmonary cytokines (IL-4, IL-5, IL-13 and IFN-γ) and chemokines (CCL17, CCL22, CCL11 and CCL24). Neonatal ovalbumin exposure triggered Th2-skewed sensitization and ovalbumin-specific IgE production. Subsequent ovalbumin inhalation in adulthood boosted Th2 immunity and caused asthmatic lungs with structural and functional alterations of airways. Gender difference mainly involved airway hyperresponsiveness and resistance with greater female susceptibility to methacholine bronchospastic stimulation. In lungs, heightened chemoattractant gene expressions were only granted to neonatally ovalbumin-sensitized mice with aerosolized ovalbumin stress in adulthood, and paralleled by upregulated Th2 cytokine genes. Thus, aeroallergen stress in atopic individuals might upregulate the expression of intrapulmonary chemoattractants to recruit Th2 cells and eosinophils into the lungs, pathogenically linked to asthma development. Conclusively, murine neonates were sensitive to allergen exposures. Exposure events during neonatal stages were crucial to asthma predisposition in later life. These findings from a murine model point to allergen avoidance in neonatal life, possibly even very early in utero, as the best prospect of primary asthma prevention.
Natural Products, Alone or in Combination with FDA-Approved Drugs, to Treat COVID-19 and Lung Cancer
Authors: Yang Liyan , Wang Zhonglei
Published: June 2021

As a public health emergency of international concern, the highly contagious coronavirus disease 2019 (COVID-19) pandemic has been identified as a severe threat to the lives of billions of individuals. Lung cancer, a malignant tumor with the highest mortality rate, has brought significant challenges to both human health and economic development. Natural products may play a pivotal role in treating lung diseases. We reviewed published studies relating to natural products, used alone or in combination with US Food and Drug Administration-approved drugs, active against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and lung cancer from 1 January 2020 to 31 May 2021. A wide range of natural products can be considered promising anti-COVID-19 or anti-lung cancer agents have gained widespread attention, including natural products as monotherapy for the treatment of SARS-CoV-2 (ginkgolic acid, shiraiachrome A, resveratrol, and baicalein) or lung cancer (daurisoline, graveospene A, deguelin, and erianin) or in combination with FDA-approved anti-SARS-CoV-2 agents (cepharanthine plus nelfinavir, linoleic acid plus remdesivir) and anti-lung cancer agents (curcumin and cisplatin, celastrol and gefitinib). Natural products have demonstrated potential value and with the assistance of nanotechnology, combination drug therapies, and the codrug strategy, this “natural remedy” could serve as a starting point for further drug development in treating these lung diseases.
Immunotherapeutic Potential of m6A-Modifiers and MicroRNAs in Controlling Acute Myeloid Leukaemia
Authors: Kumar Sunil , Nagpal Ravinder , Kumar Amit , Ashraf Muhammad Umer , Bae Yong-Soo
Published: June 2021

Epigenetic alterations have contributed greatly to human carcinogenesis. Conventional epigenetic studies have been predominantly focused on DNA methylation, histone modifications, and chromatin remodelling. Epitranscriptomics is an emerging field that encompasses the study of RNA modifications that do not affect the RNA sequence but affect functionality via a series of RNA binding proteins called writer, reader and eraser. Several kinds of epi-RNA modifications are known, such as 6-methyladenosine (m6A), 5-methylcytidine (m5C), and 1-methyladenosine. M6A modification is the most studied and has large therapeutic implications. In this review, we have summarised the therapeutic potential of m6A-modifiers in controlling haematological disorders, especially acute myeloid leukaemia (AML). AML is a type of blood cancer affecting specific subsets of blood-forming hematopoietic stem/progenitor cells (HSPCs), which proliferate rapidly and acquire self-renewal capacities with impaired terminal cell-differentiation and apoptosis leading to abnormal accumulation of white blood cells, and thus, an alternative therapeutic approach is required urgently. Here, we have described how RNA m6A-modification machineries EEE (Editor/writer: Mettl3, Mettl14; Eraser/remover: FTO, ALKBH5, and Effector/reader: YTHDF-1/2) could be reformed into potential druggable candidates or as RNA-modifying drugs (RMD) to treat leukaemia. Moreover, we have shed light on the role of microRNAs and suppressors of cytokine signalling (SOCS/CISH) in increasing anti-tumour immunity towards leukaemia. We anticipate, our investigation will provide fundamental knowledge in nurturing the potential of RNA modifiers in discovering novel therapeutics or immunotherapeutic procedures.
Can Optimizing the Mechanical Environment Deliver a Clinically Significant Reduction in Fracture Healing Time?
Authors: Barcik Jan , Epari Devakara R.
Published: June 2021

The impact of the local mechanical environment in the fracture gap on the bone healing process has been extensively investigated. Whilst it is widely accepted that mechanical stimulation is integral to callus formation and secondary bone healing, treatment strategies that aim to harness that potential are rare. In fact, the current clinical practice with an initially partial or non-weight-bearing approach appears to contradict the findings from animal experiments that early mechanical stimulation is critical. Therefore, we posed the question as to whether optimizing the mechanical environment over the course of healing can deliver a clinically significant reduction in fracture healing time. In reviewing the evidence from pre-clinical studies that investigate the influence of mechanics on bone healing, we formulate a hypothesis for the stimulation protocol which has the potential to shorten healing time. The protocol involves confining stimulation predominantly to the proliferative phase of healing and including adequate rest periods between applications of stimulation.
Nanocomposite Materials Based on Electrochemically Synthesized Graphene Polymers: Molecular Architecture Strategies for Sensor Applications
Authors: Olean-Oliveira André , Oliveira Brito Gilberto A. , Cardoso Celso Xavier , Teixeira Marcos F. S.
Published: June 2021

The use of graphene and its derivatives in the development of electrochemical sensors has been growing in recent decades. Part of this success is due to the excellent characteristics of such materials, such as good electrical and mechanical properties and a large specific surface area. The formation of composites and nanocomposites with these two materials leads to better sensing performance compared to pure graphene and conductive polymers. The increased large specific surface area of the nanocomposites and the synergistic effect between graphene and conducting polymers is responsible for this interesting result. The most widely used methodologies for the synthesis of these materials are still based on chemical routes. However, electrochemical routes have emerged and are gaining space, affording advantages such as low cost and the promising possibility of modulation of the structural characteristics of composites. As a result, application in sensor devices can lead to increased sensitivity and decreased analysis cost. Thus, this review presents the main aspects for the construction of nanomaterials based on graphene oxide and conducting polymers, as well as the recent efforts made to apply this methodology in the development of sensors and biosensors.
The Child Behavior Checklist as a Screening Instrument for PTSD in Refugee Children
Authors: Nehring Ina , Sattel Heribert , Al-Hallak Maesa , Sack Martin , Henningsen Peter , Mall Volker , Aberl Sigrid
Published: June 2021

Thousands of refugees who have entered Europe experienced threatening conditions, potentially leading to post traumatic stress disorder (PTSD), which has to be detected and treated early to avoid chronic manifestation, especially in children. We aimed to evaluate and test suitable screening tools to detect PTSD in children. Syrian refugee children aged 4–14 years were examined using the PTSD-semi-structured interview, the Kinder-DIPS, and the Child Behavior Checklist (CBCL). The latter was evaluated as a potential screening tool for PTSD using (i) the CBCL-PTSD subscale and (ii) an alternative subscale consisting of a psychometrically guided selection of items with an appropriate correlation to PTSD and a sufficient prevalence (presence in more than 20% of the cases with PTSD). For both tools we calculated sensitivity, specificity, and a receiver operating characteristic (ROC) curve. Depending on the sum score of the items, the 20-item CBCL-PTSD subscale as used in previous studies yielded a maximal sensitivity of 85% and specificity of 76%. The psychometrically guided item selection resulted in a sensitivity of 85% and a specificity of 83%. The areas under the ROC curves were the same for both tools (0.9). Both subscales may be suitable as screening instrument for PTSD in refugee children, as they reveal a high sensitivity and specificity.
Lipids from Microalgae for Cosmetic Applications
Authors: De Luca Maria , Pappalardo Ilaria , Limongi Antonina Rita , Viviano Emanuele , Radice Rosa Paola , Todisco Simona , Martelli Giuseppe , Infantino Vittoria , Vassallo Antonio
Published: June 2021

In recent years, there has been considerable interest in using microalgal lipids in the food, chemical, pharmaceutical, and cosmetic industries. Several microalgal species can accumulate appreciable lipid quantities and therefore are characterized as oleaginous. In cosmetic formulations, lipids and their derivatives are one of the main ingredients. Different lipid classes are great moisturizing, emollient, and softening agents, work as surfactants and emulsifiers, give consistence to products, are color and fragrance carriers, act as preservatives to maintain products integrity, and can be part of the molecules delivery system. In the past, chemicals have been widely used but today’s market and customers’ demands are oriented towards natural products. Microalgae are an extraordinary source of lipids and other many bioactive molecules. Scientists’ attention to microalgae cultivation for their industrial application is increasing. For the high costs associated, commercialization of microalgae and their products is still not very widespread. The possibility to use biomass for various industrial purposes could make microalgae more economically competitive.
First-Line Treatment with a Cyclin-Dependent Kinase 4/6 Inhibitor Plus an Aromatase Inhibitor for Metastatic Breast Cancer in Alberta
Authors: Amaro Carla P. , Batra Atul , Lupichuk Sasha
Published: June 2021

In this analysis, we describe population-based outcomes for first-line treatment with a cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) combined with an aromatase inhibitor (AI). All patients who were prescribed CDK4/6i + AI from January 2016 through June 2019 were included. Patient demographics, tumour and treatment characteristics were collected and described. Survival distributions were estimated using the Kaplan–Meier method. Multivariate analysis (MVA) was constructed to examine associations between potentially prognostic clinical variables and progression-free survival (PFS). In total, 316 patients were included. The median age was 61 years. After a median follow-up of 28.1 months, the median PFS was 37.9 months (95% CI, 26.7–NR). In the MVA, PR-negative tumour (HR, 2.37; 95% CI, 1.45–3.88; p = 0.001) and CDK4/6i dose reduction (HR, 1.51; 95% CI, 1.06–2.16; p = 0.022) predicted worse PFS. Median overall survival (OS) was not reached. The 30-month and 36-month OS rates were 74% and 68%, respectively. Of patients who progressed, 89% received second-line treatment. Median time to progression on second-line chemotherapy was 9.0 (5.8–17.6) months, and median time to progression on second-line hormonal therapy +/− targeted agent was 4.0 (3.4–8.6) months (p = 0.012). CDK4/6i + AI as first-line treatment for HR-positive, HER2-negative MBC in Alberta is justified based on favourable PFS and early OS outcomes.
Robustness of Cyber-Physical Supply Networks in Cascading Failures
Authors: Mu Dong , Yue Xiongping , Ren Huanyu
Published: June 2021

A cyber-physical supply network is composed of an undirected cyber supply network and a directed physical supply network. Such interdependence among firms increases efficiency but creates more vulnerabilities. The adverse effects of any failure can be amplified and propagated throughout the network. This paper aimed at investigating the robustness of the cyber-physical supply network against cascading failures. Considering that the cascading failure is triggered by overloading in the cyber supply network and is provoked by underload in the physical supply network, a realistic cascading model for cyber-physical supply networks is proposed. We conducted a numerical simulation under cyber node and physical node failure with varying parameters. The simulation results demonstrated that there are critical thresholds for both firm’s capacities, which can determine whether capacity expansion is helpful; there is also a cascade window for network load distribution, which can determine the cascading failures occurrence and scale. Our work may be beneficial for developing cascade control and defense strategies in cyber-physical supply networks.
The High School Competencies Scale (H-Comp Scale): A First Validation Study
Authors: Boerchi Diego , Magnano Paola , Lodi Ernesto
Published: June 2021

Researchers widely explored non-intellective study factors because they play a central role in academic performance and are potentially more modifiable than intellective ones. The scientific literature suggests that the non-intellective factors can be classified into three main areas: self-concept, which refers to self-esteem and efficacy, motivation and emotional reactions; the area of study, related to study dedication and operative skills; and the area of relationships, comprising those with family, fellow students and teachers. Basing on these findings, the C-Comp Scale has been developed and tested in the past, addressed to college students. This study aimed to adapt and test a new version of this questionnaire on high school students. Methods. A pilot study was conducted on 364 Italian high school students to adapt and test the new version of the questionnaire, called the H-Comp Scale. The following study, conducted on 792 Italian high school students, provided further evidence of its reliability, structural validity, and concurrent validity with general self-efficacy, academic self-efficacy, social self-efficacy, and academic performance. Results. The H-Comp Scale showed to possess excellent reliability and structural and concurrent validity. The final version is composed of twelve subscales, aggregated in three areas, with just 48 items: Study (Intrinsic Motivation, Extrinsic Motivation, Time Management, Study Dedication), Self (Learning Assessment, General Self-Esteem, Self-Efficacy, Reaction to Failures, Emotional Control), and Relationships (Family Relationships, Fellow Student Relationships, Teacher Relationships). Conclusions. The H-Comp Scale would be a useful and easy-to-use instrument to support school counselors, tutors, teachers, and researchers in exploring different types of non-intellective variables, to better project educational intervention aimed to improve high school students’ academic performance and satisfaction.
Mapping the Evolutions and Trends of Literature on Wayfinding in Indoor Environments
Authors: Ghamari Hessam , Sharifi Ayyoob
Published: June 2021

Research on indoor wayfinding has increased in number and significance since the 1980s. Yet, the information on wayfinding literature is now difficult to manage given its vast scope and spread across journals, institutions, disciplines, and themes. While there is an increasing number of publications within this rapidly growing field of research, there are limited review studies in the field, and there is still missing an overall analysis of the current state of wayfinding literature and its evolution. The main objective of this study is to present a bibliometric analysis of about forty years of research on indoor wayfinding to provide an overview of the research landscape. The final database of the study contained 407 publications. VOSviewer was used as a science mapping software tool to identify major focus areas and to identify influential authors, publications, and journals using various network analysis techniques, such as term co-occurrence, co-citation, and bibliographic coupling. Similar co-occurrence analysis was used to understand how the intellectual base of the field has evolved over time and what the major themes are that have contributed to this evolution. The results show that this field has initially been mainly focused on few themes but has later become more diversified to acknowledge the multi-dimensional characteristics of indoor wayfinding. While spatial knowledge acquisition and cognitive maps are still dominant core areas, there are topics, such as signage, isovists, and the use of eye-tracking and virtual reality, that still need to be further investigated.
A Deep Learning-Based Classification Scheme for False Data Injection Attack Detection in Power System
Authors: Ding Yucheng , Ma Kang , Pu Tianjiao , Wang Xinying , Li Ran , Zhang Dongxia
Published: June 2021

A smart grid improves power grid efficiency by using modern information and communication technologies. However, at the same time, due to the dependence on information technology and the deep integration of electrical components and computing information in cyber space, the system might become increasingly vulnerable to cyber-attacks. Among various emerging security problems, a false data injection attack (FDIA) is a new type of attack against the state estimation. In this article, a deep learning-based identification scheme is developed to detect and mitigate information corruption. The scheme implements a conditional deep belief network (CDBN) to analyze time-series input data and leverages captured features to detect the FDIA. The performance of our detection mechanism is validated by using the IEEE 14-bus test system for simulation. Different attack scenarios and parameters are set to demonstrate the feasibility and effectiveness of the developed scheme. Compared with the artificial neural network (ANN) and the support vector machine (SVM), the experimental analyses indicate that the results of our detection mechanism are better than those of the other two in terms of FDIA detection accuracy and robustness.
On the Efficient Flow Restoration in Spectrally-Spatially Flexible Optical Networks
Authors: Goścień Róża
Published: June 2021

We focus on the efficient modeling and optimization of the flow restoration in the spectrally-spatially flexible optical networks (SS-FONs) realized using a single mode fiber bundle. To this end, we study a two-phase optimization problem, which consists of: (i) the network planning with respect to the spectrum usage and (ii) the flow restoration after a failure aiming at maximizing the restored bit-rate. Both subproblems we formulate using the integer linear programming with two modeling approaches—the node-link and the link-path. We perform simulations divided into: (i) a comparison of the proposed approaches, (ii) an efficient flow restoration in SS-FONs—case study. The case study focuses on the verification whether the spectral-spatial allocation may improve the restoration process (compared to the spectral allocation) and on the determination of the full restoration cost (the amount of additional resources required to restore whole traffic) in two network topologies. The results show that the spectral-spatial allocation allows us to restore up to 4% more traffic compared to the restoration with only the spectral channels. They also reveal that the cost of the full traffic restoration depends on plenty of factors, including the overall traffic volume and the network size, while the spectral-spatial allocation allows us to reduce its value about 30%.
Methodology for Calculating the Energy Security Index of the State: Taking into Account Modern Megatrends
Authors: Stavytskyy Andriy , Kharlamova Ganna , Komendant Olena , Andrzejczak Jarosław , Nakonieczny Joanna
Published: June 2021

Energy issue stays a top priority for the national security of most countries. Despite numerous international forums, large-scale geoeconomic research, international and national projects, and the development of appropriate strategies, the issue of energy security assessment and understanding of its terminology is not a universal practice. The presented study has an ambitious goal to develop a methodology that can provide an objective picture of the energy sector on an international scale with cross-country comparisons under the influence of modern megatrends. Based on 29 indicators, according to the World Bank data since 1991, the energy security index is calculated for the set of world states with further analysis of the cluster dynamics of their common trends in energy security. The index showed its objectivity and resistance to existing shocks in geoeconomic dynamics. An important feature of the proposed index is the possibility to compare the energy security index with 1. This value is, in fact, a European average: if a country has an energy security index greater than 1, it means that its energy level is currently better than the European average, and if it is lower than 1, it means that it is inferior to the level of energy security currently achieved on average in Europe. The concept of calculating the index of energy security of the state is based on a unified comparison of all countries, which allows us to move away from the use of signaling approaches and eliminate subjectivity in calculations, as well as provide a basis for dynamic comparison of energy security. The vital aspect of the index is that it takes into account changes in the energy paradigm, the transition to alternative energy sources, and the comprehension of the role of energy efficiency, in particular, of fossil fuels. The study identifies clusters of countries that have consistent similarities in energy security, which can usually be of practical interest in developing energy strategies and understanding the similarity of geoeconomic interests of these states. Thus, this article contributes not only to the development of scientific approaches to the assessment of energy issues, in particular, through the methodological development of a representative index, but also through the presentation of statistically sound results for further effective management decisions at the state level.
Quantifying the Effects of Wave—Current Interactions on Tidal Energy Resource at Sites in the English Channel Using Coupled Numerical Simulations
Authors: Hardwick Jon , Mackay Ed B. L. , Ashton Ian G. C. , Smith Helen C. M. , Thies Philipp R.
Published: June 2021

Numerical modeling of currents and waves is used throughout the marine energy industry for resource assessment. This study compared the output of numerical flow simulations run both as a standalone model and as a two-way coupled wave–current simulation. A regional coupled flow-wave model was established covering the English Channel using the Delft D-Flow 2D model coupled with a SWAN spectral wave model. Outputs were analyzed at three tidal energy sites: Alderney Race, Big Roussel (Guernsey), and PTEC (Isle of Wight). The difference in the power in the tidal flow between coupled and standalone model runs was strongly correlated to the relative direction of the waves and currents. The net difference between the coupled and standalone runs was less than 2.5%. However, when wave and current directions were aligned, the mean flow power was increased by up to 7%, whereas, when the directions were opposed, the mean flow power was reduced by as much as 9.6%. The D-Flow Flexible Mesh model incorporates the effects of waves into the flow calculations in three areas: Stokes drift, forcing by radiation stress gradients, and enhancement of the bed shear stress. Each of these mechanisms is discussed. Forcing from radiation stress gradients is shown to be the dominant mechanism affecting the flow conditions at the sites considered, primarily caused by dissipation of wave energy due to white-capping. Wave action is an important consideration at tidal energy sites. Although the net impact on the flow power was found to be small for the present sites, the effect is site specific and may be significant at sites with large wave exposure or strong asymmetry in the flow conditions and should thus be considered for detailed resource and engineering assessments.
Application of Machine Learning Method of Data-Driven Deep Learning Model to Predict Well Production Rate in the Shale Gas Reservoirs
Authors: Han Dongkwon , Kwon Sunil
Published: June 2021

Reservoir modeling to predict shale reservoir productivity is considerably uncertain and time consuming. Since we need to simulate the physical phenomenon of multi-stage hydraulic fracturing. To overcome these limitations, this paper presents an alternative proxy model based on data-driven deep learning model. Furthermore, this study not only proposes the development process of a proxy model, but also verifies using field data for 1239 horizontal wells from the Montney shale formation in Alberta, Canada. A deep neural network (DNN) based on multi-layer perceptron was applied to predict the cumulative gas production as the dependent variable. The independent variable is largely divided into four types: well information, completion and hydraulic fracturing and production data. It was found that the prediction performance was better when using a principal component with a cumulative contribution of 85% using principal component analysis that extracts important information from multivariate data, and when predicting with a DNN model using 6 variables calculated through variable importance analysis. Hence, to develop a reliable deep learning model, sensitivity analysis of hyperparameters was performed to determine one-hot encoding, dropout, activation function, learning rate, hidden layer number and neuron number. As a result, the best prediction of the mean absolute percentage error of the cumulative gas production improved to at least 0.2% and up to 9.1%. The novel approach of this study can also be applied to other shale formations. Furthermore, a useful guide for economic analysis and future development plans of nearby reservoirs.
Probability-Based Failure Evaluation for Power Measuring Equipment
Authors: Liu Jie , Tang Qiu , Qiu Wei , Ma Jun , Duan Junfeng
Published: June 2021

Accurate reliability and residual life analysis is paramount during the designing of reliability requirements and rotation of power measuring equipment (PME). However, the sample dataset of failure is usually sparse and contains inevitable pollution data, which has an adverse effect on the reliability analysis. To tackle this issue, this paper first applies nonlinear regression to fuse the failure rate and environmental features of PME collected from various locations. Then, a novel binary hierarchical Bayesian probability method is proposed to model the failure trend and identify outliers, in which the outlier identification structure is embedded into hierarchical Bayesian. Integrating binary hierarchical Bayesian and the bagging method, a binary hierarchical Bayesian with bagging (BHBB) framework is further introduced to improve predictive performance in a small sample dataset by resampling. Last, the influence of typical environmental features, failure rate, and reliability are obtained by the BHBB under the real sample dataset from multiple typical locations. Experiments show that our framework has superior performance and interpretability comparing with other typical data-based approaches.
Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads
Authors: Liu Xinghua , Xie Shenghan , Geng Chen , Yin Jianning , Xiao Gaoxi , Cao Hui
Published: June 2021

For the future development of integrated energy systems with high penetration of renewable energy, an integrated community energy systems (ICES) dispatch model is proposed including various renewable energy sources and energy conversion units. Energy coupling matrices of ICES based on traditional energy hub (EH) models are constructed. Uncertainties of long-term forecast data of renewable energy sources and internal loads are depicted by multi-interval uncertainty sets (MIUS). To cope with the impacts caused by uncertainties of renewable energy sources and internal loads, the whole dispatch process is divided into two stages. Considering various constraints of ICES, we solved the dispatch model through the improved particle swarm optimization (IPSO) algorithm in the first stage. The optimal evolutionary dispatch is then proposed in the second stage to overcome the evolution and errors of short-term forecast data and obtain the optimal dispatch plan. The effectiveness of the proposed dispatch method is demonstrated using an example considering dramatic uncertainties. Compared with the traditional methods, the proposed dispatch method effectively reduces system operating costs and improves the environmental benefits, which helps to achieve a win-win situation for both energy companies and users.
SEM-PLS Approach to Green Building
Authors: Aghili Nasim , Amirkhani Mehdi
Published: June 2021

Green buildings refer to buildings that decrease adverse environmental effects and maintain natural resources. They can diminish energy consumption, greenhouse gas emissions, the usage of non-renewable materials, water consumption, and waste generation while improving occupants’ health and well-being. As such, several rating tools and benchmarks have been developed worldwide to assess green building performance (GBP), including the Building Research Establishment Environmental Assessment Method (BREEAM) in the United Kingdom, German Sustainable Building Council (DGNB), Leadership in Energy and Environmental Design (LEED) in the United States and Canada, Comprehensive Assessment System for Built Environment Efficiency (CASBEE) in Japan, Green Star in Australia, Green Mark in Singapore, and Green Building Index in Malaysia. Energy management (EM) during building operation could also improve GBP. One of the best approaches to evaluating the impact of EM on GBP is by using structural equation modelling (SEM). SEM is a commanding statistical method to model testing. One of the most used SEM variance-based approaches is partial least squares (PLS), which can be implemented in the SmartPLS application. PLS-SEM uses path coefficients to determine the strength and significance of the hypothesised relationships between the latent constructs.
H3K4 Methylation in Aging and Metabolism
Authors: Hsu Chia-Ling , Lo Yi-Chen , Kao Cheng-Fu
Published: June 2021

During the process of aging, extensive epigenetic alterations are made in response to both exogenous and endogenous stimuli. Here, we summarize the current state of knowledge regarding one such alteration, H3K4 methylation (H3K4me), as it relates to aging in different species. We especially highlight emerging evidence that links this modification with metabolic pathways, which may provide a mechanistic link to explain its role in aging. H3K4me is a widely recognized marker of active transcription, and it appears to play an evolutionarily conserved role in determining organism longevity, though its influence is context specific and requires further clarification. Interestingly, the modulation of H3K4me dynamics may occur as a result of nutritional status, such as methionine restriction. Methionine status appears to influence H3K4me via changes in the level of S-adenosyl methionine (SAM, the universal methyl donor) or the regulation of H3K4-modifying enzyme activities. Since methionine restriction is widely known to extend lifespan, the mechanistic link between methionine metabolic flux, the sensing of methionine concentrations and H3K4me status may provide a cogent explanation for several seemingly disparate observations in aging organisms, including age-dependent H3K4me dynamics, gene expression changes, and physiological aberrations. These connections are not yet entirely understood, especially at a molecular level, and will require further elucidation. To conclude, we discuss some potential H3K4me-mediated molecular mechanisms that may link metabolic status to the aging process.
Thermal Flows
Authors: Lappa Marcello
Published: June 2021

Flows of thermal origin and heat transfer problems are central in a variety of disciplines and industrial applications [...]
Effect of Water Content and Pectin on the Viscoelastic Improvement of Water-in-Canola Oil Emulsions
Authors: Romero-Peña Maria , Ghosh Supratim
Published: June 2021

This study aimed to investigate gelation in glycerol monooleate (GMO)-stabilized water-in-canola oil (W/CO) emulsions by increasing water content (20–50 wt.%) and the addition of low methoxyl pectin (LMP) in the aqueous phase. A constant ratio of GMO to water was used to keep a similar droplet size in all emulsions. Hydrogenated soybean oil (7 wt.%) was used to provide network stabilization in the continuous phase. All fresh emulsions with LMP in the aqueous phase formed a stable and self-supported matrix with higher viscosity and gel strength than emulsions without LMP. Emulsion viscosity and gel strength increased with an increase in water content. All emulsions showed gel-like properties (storage moduli (G’) > loss moduli (G’’)) related to the presence of LMP in the aqueous phase and increased water content. Freeze/thaw analysis using a differential scanning calorimeter showed improved stability of the water droplets in the presence of LMP in the aqueous phase. This study demonstrated the presence of LMP in the aqueous phase, its interaction with GMO at the interface, and fat crystals in the continuous phase that could support the water droplets’ aggregation to obtain stable elastic W/CO emulsions that could be used as low-fat table spreads.
Prevalence of Salmonella in Free-Range Pigs: Risk Factors and Intestinal Microbiota Composition
Authors: Garrido Victoria , Migura-García Lourdes , Gaitán Inés , Arrieta-Gisasola Ainhoa , Martínez-Ballesteros Ilargi , Fraile Lorenzo , Grilló María Jesús
Published: June 2021

Extensive pig systems are gaining importance as quality production systems and as the standard for sustainable rural development and animal welfare. However, the effects of natural foods on Salmonella epidemiology remain unknown. Herein, we assessed the presence of Salmonella and the composition of the gut microbiota in pigs from both Salmonella-free and high Salmonella prevalence farms. In addition, risk factors associated with the presence of Salmonella were investigated. The pathogen was found in 32.2% of animals and 83.3% of farms, showing large differences in prevalence between farms. Most isolates were serovars Typhimurium monophasic (79.3%) and Bovismorbificans (10.3%), and exhibited a multi-drug resistance profile (58.6%). Risk factor analysis identified feed composition, type/variety of vegetation available, and silos’ cleaning/disinfection as the main factors associated with Salmonella prevalence. Clear differences in the intestinal microbiota were found between Salmonella-positive and Salmonella-negative populations, showing the former with increasing Proteobacteria and decreasing Bacteroides populations. Butyrate and propionate producers including Clostridium, Turicibacter, Bacteroidaceae_uc, and Lactobacillus were more abundant in the Salmonella-negative group, whereas acetate producers like Sporobacter, Escherichia or Enterobacter were more abundant in the Salmonella-positive group. Overall, our results suggest that the presence of Salmonella in free-range pigs is directly related to the natural vegetation accessible, determining the composition of the intestinal microbiota.
Chemical Extraction and Gastrointestinal Digestion of Honey: Influence on Its Antioxidant, Antimicrobial and Anti-Inflammatory Activities
Authors: Alevia Marta , Rasines Sandra , Cantero Leire , Sancho M. Teresa , Fernández-Muiño Miguel A. , Osés Sandra M.
Published: June 2021

The effect of chemical extraction and in vitro digestion of different kinds of honey on bioactive compounds (total phenolic compounds and flavonoids) and biological activities (antioxidant, antimicrobial and anti-inflammatory) was investigated. The antioxidant activity was evaluated against three radicals (ABTS•+, ROO•, •OH), and the antimicrobial activity was studied against five bacteria (Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Streptococcus mutans and Pseudomona aeruginosa) and one yeast (Candida albicans). The results show that in comparison with raw honeys, the methanolic extracts exhibited lower values for phenols, flavonoids and antioxidant activity and higher anti-inflammatory and antimicrobial activities against L. monocytogenes. The higher anti-inflammatory activity indicates a possible use of dried honey extracts in the pharmaceutical and cosmetic industries. The digested honeys showed higher total phenolics and higher antioxidant activity than the pre-digested honeys, as well as higher antimicrobial activity against S. aureus and L. monocytogenes, which underlines the possible antioxidant and antimicrobial effects of honey in the human body after the digestion process.
Biological Properties, Health Benefits and Enzymatic Modifications of Dietary Methoxylated Derivatives of Cinnamic Acid
Authors: Rychlicka Magdalena , Rot Agata , Gliszczyńska Anna
Published: June 2021

Methoxylated derivatives of cinnamic acid play an important role in the formation of the pro-health potential of food products. Numerous reports present them as molecules with strong antimicrobial, antidiabetic, anticancer as well as hepato-, cardio-, and neuroprotective activities. In the last three decades, many research groups have tried to extend the practical application of these molecules as therapeutic and antioxidant agents extensively studying the methods of their lipophilization as the solution of problems of their low oral bioavailability and rapid metabolism. This article summarizes the latest data of natural sources of occurrence, biological potential and bioavailability of methoxy derivatives of cinnamic acids. Metabolism and pharmacokinetics of this group of dietary compounds are also extensively discussed as well as reviewing the methods of their chemical and enzymatic lipophilization in the aspect of their use in food and pharmaceutical industries.
Investigation on the Molecular and Physicochemical Changes of Protein and Starch of Wheat Flour during Heating
Authors: Yang Tao , Wang Pei , Zhou Qin , Wang Xiao , Cai Jian , Huang Mei , Jiang Dong
Published: June 2021

The behaviors of starch and protein in wheat flour during heating were investigated, and the molecular changes of starch and protein and their effects on the textural characteristics were assessed. The results showed that with the increased temperature, soluble protein aggregated to insoluble high-molecular-weight protein polymers when the heating temperature exceeded 70 °C, and the aggregation of protein was mainly caused by covalent bonds of disulfide (SS) bonds. Hydrophobic interaction was the main noncovalent bond that participated in the formation of protein aggregates. The major change in the secondary structure during heating was a pronounced transition towards β-sheet-like structures. Considerable disruption of ordered structures of starch occurred at 70 °C, and starch was fully gelatinized at 80 °C. Typical starch pasting profiles of cooked flour were observed when the temperature was below 70 °C, and heat treatment decreased the pasting viscosity of the cooked flour from control to 80 °C, whereas the viscosity of the wheat flour increased in heating treatment at 90, 95 and 100 °C. The intense protein-starch interaction during heating affected the textural characteristic of flour gelation, which showed higher strength at 90, 95 and 100 °C. This study may provide a basis for improving wheat flour processing conditions and could lead to the production of new wheat products.
Diabetic Retinopathy Screening and Registration in Europe—Narrative Review
Authors: Hristova Elitsa , Koseva Darina , Zlatarova Zornitsa , Dokova Klara
Published: June 2021

Diabetic retinopathy (DR) is a leading cause of preventable vision impairment and blindness in the European Region. Despite the fact that almost all European countries have some kind of prophylactic eye examination for people with diabetes, the examinations are not properly arranged and are not organized according to the principles of screening in medicine. In 2021, the current COVID-19 pandemic moved telemedicine to the forefront healthcare services. Due to that, a lot more patients could benefit from comfortable and faster access to ophthalmology specialist care. This study aimed to conduct a narrative literature review on current DR screening programs and registries in the European Union for the last 20 years. With the implementation of telemedicine in daily medical practice, performing screening programs became much more attainable. Remote assessment of retinal pictures simultaneously saves countries time, money, and other resources.
Assessment of Knowledge, Practice and Attitude about Biomedical Waste Management among Healthcare Professionals during COVID-19 Crises in Al-Ahsa
Authors: Jalal Sahbanathul Missiriya , Akhter Fahima , Abdelhafez Amal Ismael , Alrajeh Ahmed Mansour
Published: June 2021

Biomedical waste (BMW) management is an essential practice of healthcare professionals (HCPs) for preventing health and also environmental hazards. Coronavirus disease (COVID-19) has become a global pandemic, posing significant challenges for healthcare sectors. A cross-sectional study was performed to assess the knowledge, practice, and attitude on BMW management among HCPs when taking care of patients with COVID-19 and associated with demographic variables. From Al-Ahsa healthcare sectors, 256 HCPs were selected randomly, of which 105 (41%) had excellent knowledge, 87 (34%) had good knowledge, and 64 (25%) had poor knowledge with a mean score of 13.1 ± 3.6. A higher mean score was (14.4 ± 3.2) obtained by physicians, and (13.6 ± 3.8) nurses than the other HCPs. Regarding practice, 72 (28.1%) HCPs used and discarded PPE while handling biomedical wastes. Additionally, 88 (34.4%) followed proper hand hygiene before and after each procedure and whenever needed. Physicians, nurses, and respiratory therapists had a more favorable attitude than other HCPs. There was a statistically significant association found among knowledge level and educational qualification (p < 0.0001), gender (p < 0.001), and work experience (p < 0.05). Emphasis is needed to train all HCPs regarding proper BMW management during this pandemic to prevent infection transmission.
Forecast of Outpatient Visits to a Tertiary Eyecare Network in India Using the EyeSmart Electronic Medical Record System
Authors: Sai Prashanthi Gumpili , Molugu Nareen , Kammari Priyanka , Vadapalli Ranganath , Das Anthony Vipin
Published: June 2021

India is home to 1.3 billion people. The geography and the magnitude of the population present unique challenges in the delivery of healthcare services. The implementation of electronic health records and tools for conducting predictive modeling enables opportunities to explore time series data like patient inflow to the hospital. This study aims to analyze expected outpatient visits to the tertiary eyecare network in India using datasets from a domestically developed electronic medical record system (eyeSmart™) implemented across a large multitier ophthalmology network in India. Demographic information of 3,384,157 patient visits was obtained from eyeSmart EMR from August 2010 to December 2017 across the L.V. Prasad Eye Institute network. Age, gender, date of visit and time status of the patients were selected for analysis. The datapoints for each parameter from the patient visits were modeled using the seasonal autoregressive integrated moving average (SARIMA) modeling. SARIMA (0,0,1)(0,1,7)7 provided the best fit for predicting total outpatient visits. This study describes the prediction method of forecasting outpatient visits to a large eyecare network in India. The results of our model hold the potential to be used to support the decisions of resource planning in the delivery of eyecare services to patients.
WeChatting for Health: What Motivates Older Adult Engagement with Health Information
Authors: Zhang Xiaoxiao , Xu Xiaoge , Cheng Jiang
Published: June 2021

Although WeChat has become increasingly popular among Chinese elderly people as a tool to engage with health information, little research has examined their motivations for health purposes and their engagement with health information on the site. By applying the two-stage Use and gratification (U&G) approach, we first conducted in-depth interviews (n = 20) to explore older adults’ distinctive motives. Based on the 22 motives found in the qualitative research, we developed a questionnaire for an online survey (n = 690) to further investigate how these motives affect older adults’ engagement with health information on WeChat. As the result, six motive typologies were identified: information needs, social support, surveillance, social interaction, self-agency building, and technological convenience. Together, these six types of motivations jointly account for 59.9% of the variance in older adults’ engagement with health information (M = 2.71, SD = 0.79, adjusted R2 = 0.59, p < 0.001). Social support and information needs were significant predictors, suggesting that the older WeChat users’ active engagement is driven by personal instrumental gratification. This study examines the explanation power of U&G theory in a health context, as well as provides the practical implication for leveraging mobile social media to improve older people’s healthcare management.