bluuebunny/crossref_metadata_2025 huggingface dataset:
Traumatic Brain Injury-Related Attention Deficits in Children: A Controlled Treatment Trial with Lisdexamfetamine Dimesylate (Vyvanse)
Authors: Tramontana Michael G. , Prokop Jonathan W. , Williamson Edwin , Duffie Tara , LaFever Hayden
Published: January 2021

Attention deficits are among the most common and persistent impairments resulting from traumatic brain injury (TBI). This study was the first to examine the effects of lisdexamfetamine dimesylate (LDX, Vyvanse) in treating TBI-related attention deficits in children. It was an extension of a previous controlled trial with adults. This was a 12-week, randomized, double-blind, placebo-controlled, dose-titration, crossover trial. In addition to weekly safety monitoring, there were assessments on a broad range of neuropsychological and behavioral measures at baseline, 6-weeks, and 12-weeks. A total of 20 carefully selected children were enrolled, ranging from 10 to 16 years of age. The sample consisted of cases with mainly mild TBI (based on the known details regarding their injuries), but they had persisting attention deficits and other post-concussion symptoms lasting from 2 to 29 months by the time of enrollment. A total of 16 children completed the trial. One of the children withdrew due to a mild anxiety reaction while on LDX. There were no other adverse effects. Positive treatment results were found on both formal testing of sustained attention and in terms of parent ratings of attention, emotional status, behavioral controls, and various aspects of executive functioning. The findings also served to highlight broader insights into the nature of attention deficits and their treatment in children with TBI.
An Approach to Data Acquisition for Urban Building Energy Modeling Using a Gaussian Mixture Model and Expectation-Maximization Algorithm
Authors: Han Mengjie , Wang Zhenwu , Zhang Xingxing
Published: January 2021

In recent years, a building’s energy performance is becoming uncertain because of factors such as climate change, the Covid-19 pandemic, stochastic occupant behavior and inefficient building control systems. Sufficient measurement data is essential to predict and manage a building’s performance levels. Assessing energy performance of buildings at an urban scale requires even larger data samples in order to perform an accurate analysis at an aggregated level. However, data are not only expensive, but it can also be a real challenge for communities to acquire large amounts of real energy data. This is despite the fact that inadequate knowledge of a full population will lead to biased learning and the failure to establish a data pipeline. Thus, this paper proposes a Gaussian mixture model (GMM) with an Expectation-Maximization (EM) algorithm that will produce synthetic building energy data. This method is tested on real datasets. The results show that the parameter estimates from the model are stable and close to the true values. The bivariate model gives better performance in classification accuracy. Synthetic data points generated by the models show a consistent representation of the real data. The approach developed here can be useful for building simulations and optimizations with spatio-temporal mapping.
18F-FDG-PET/CT in Patients with Advanced, Radioiodine Refractory Thyroid Cancer Treated with Lenvatinib
Authors: Ahmaddy Freba , Burgard Caroline , Beyer Leonie , Koehler Viktoria Florentine , Bartenstein Peter , Fabritius Matthias P. , Geyer Thomas , Wenter Vera , Ilhan Harun , Spitzweg Christine , Todica Andrei
Published: January 2021

Background: The tyrosine kinase inhibitor (TKI) Lenvatinib represents one of the most effective therapeutic options in patients with advanced radioiodine refractory differentiated thyroid carcinoma (DTC). We aimed to assess the role of 2-deoxy-2-[18F] fluoro-D-glucose positron-emission-tomography/computed-tomography (18F-FDG-PET/CT) in the monitoring of functional tumor response compared to morphological response. Methods: In 22 patients, a modified Positron Emission Tomography Response Criteria In Solid Tumors (mPERCIST) evaluation before treatment with Lenvatinib and at 3 and 6 month follow up was performed. Further PET-parameters and morphologic tumor response using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 were assessed and their prediction of progression-free survival (PFS) and disease-specific survival (DSS) was evaluated. Results: Most patients were rated stable in morphological evaluation and progressive using a metabolic response. All patients who responded to therapy through RECIST showed a decline in nearly all Positron Emission Tomography (PET)-parameters. For both time-points, non-responders according to mPERCIST showed significantly lower median PFS and DSS, whereas according to RECIST, only DSS was significantly lower. Conclusion: Tumor response assessment by 18F-FDG-PET outperforms morphological response assessment by CT in patients with advanced radioiodine refractory DTC treated with Lenvatinib, which seems to be correlated with clinical outcomes.
A Comprehensive Study of Coke Deposits on a Pt-Sn/SBA-16 Catalyst during the Dehydrogenation of Propane
Authors: Ruelas-Leyva Jose P. , Maldonado-Garcia Luis F. , Talavera-Lopez Alfonso , Santos-López Iván A. , Picos-Corrales Lorenzo A. , Santolalla-Vargas Carlos E. , Torres Sergio A. Gómez , Fuentes Gustavo A.
Published: January 2021

Catalytic propane dehydrogenation is an attractive method to produce propylene while avoiding the issues of its traditional synthesis via naphtha steam cracking of naphtha. In this contribution, a series of Pt-Sn/SBA-16 catalysts were synthesized and evaluated for this purpose. Bimetallic Pt-Sn catalysts were more active than catalysts containing only Pt. The catalyst with the best performance was assessed at different reaction times of 0, 60, 180, and 300 min. The evolution of coke deposits was also studied. Thermogravimetric analysis demonstrated the presence of two types of coke on the catalyst surface at low and high temperature, respectively. Raman results showed an increased coke’s crystal size from 60 to 180 min on stream, and from 180 to 300 min under reaction, Raman suggested a reduction in the crystal size of coke. Also transmission electron microscopy confirmed a more evident agglomeration of metallic particles with reaction times higher than 180 min. These results are consistent with the phenomena called “coke migration” and the cause is often explained by coke movement near the particle to the support; it can also be explained due to sintering of the metallic particle, which we propose as a more suitable explanation.
CO Oxidation Efficiency and Hysteresis Behavior over Mesoporous Pd/SiO2 Catalyst
Authors: Al Soubaihi Rola Mohammad , Saoud Khaled Mohammad , Myint Myo Tay Zar , Göthelid Mats A. , Dutta Joydeep
Published: January 2021

Carbon monoxide (CO) oxidation is considered an important reaction in heterogeneous industrial catalysis and has been extensively studied. Pd supported on SiO2 aerogel catalysts exhibit good catalytic activity toward this reaction owing to their CO bond activation capability and thermal stability. Pd/SiO2 catalysts were investigated using carbon monoxide (CO) oxidation as a model reaction. The catalyst becomes active, and the conversion increases after the temperature reaches the ignition temperature (Tig). A normal hysteresis in carbon monoxide (CO) oxidation has been observed, where the catalysts continue to exhibit high catalytic activity (CO conversion remains at 100%) during the extinction even at temperatures lower than Tig. The catalyst was characterized using BET, TEM, XPS, TGA-DSC, and FTIR. In this work, the influence of pretreatment conditions and stability of the active sites on the catalytic activity and hysteresis is presented. The CO oxidation on the Pd/SiO2 catalyst has been attributed to the dissociative adsorption of molecular oxygen and the activation of the C-O bond, followed by diffusion of adsorbates at Tig to form CO2. Whereas, the hysteresis has been explained by the enhanced stability of the active site caused by thermal effects, pretreatment conditions, Pd-SiO2 support interaction, and PdO formation and decomposition.
Biocatalysis for Rare Ginsenoside Rh2 Production in High Level with Co-Immobilized UDP-Glycosyltransferase Bs-YjiC Mutant and Sucrose Synthase AtSuSy
Authors: Chu Jianlin , Yue Jiheng , Qin Song , Li Yuqiang , Wu Bin , He Bingfang
Published: January 2021

Rare ginsenoside Rh2 exhibits diverse pharmacological effects. UDP-glycosyltransferase (UGT) catalyzed glycosylation of protopanaxadiol (PPD) has been of growing interest in recent years. UDP-glycosyltransferase Bs-YjiC coupling sucrose synthase in one-pot reaction was successfully applied to ginsenoside biosynthesis with UDP-glucose regeneration from sucrose and UDP, which formed a green and sustainable approach. In this study, the his-tagged UDP-glycosyltransferase Bs-YjiC mutant M315F and sucrose synthase AtSuSy were co-immobilized on heterofunctional supports. The affinity adsorption significantly improved the capacity of specific binding of the two recombinant enzymes, and the dual enzyme covalently cross-linked by the acetaldehyde groups significantly promoted the binding stability of the immobilized bienzyme, allowing higher substrate concentration by easing substrate inhibition for the coupled reaction. The dual enzyme amount used for ginsenoside Rh2 biosynthesis is Bs-YjiC-M315F: AtSuSy = 18 mU/mL: 25.2 mU/mL, a yield of 79.2% was achieved. The coimmobilized M315F/AtSuSy had good operational stability of repetitive usage for 10 cycles, and the yield of ginsenoside Rh2 was kept between 77.6% and 81.3%. The high titer of the ginsenoside Rh2 cumulatively reached up to 16.6 mM (10.3 g/L) using fed-batch technology, and the final yield was 83.2%. This study has established a green and sustainable approach for the production of ginsenoside Rh2 in a high level of titer, which provides promising candidates for natural drug research and development.
Exogenous Fatty Acids Modulate ER Lipid Composition and Metabolism in Breast Cancer Cells
Authors: Rizzo Angela Maria , Colombo Irma , Montorfano Gigliola , Zava Stefania , Corsetto Paola Antonia
Published: January 2021

(1) Background: Lipid metabolism is a fundamental hallmark of all tumors, especially of breast cancer. Few studies describe the different lipid metabolisms and sensitivities to the microenvironment of breast cancer cell subtypes that influence the proliferation, aggressiveness, and success of therapy. This study describes the impact of lipid microenvironment on endoplasmic reticulum (ER) membrane and metabolic activity in two breast cancer cell lines with Luminal A and triple-negative breast cancer (TNBC) features. (2) Methods: We investigated the peculiar lipid phenotype of a TNBC cell line, MDA-MB-231, and a Luminal A cell line, MCF7, and their different sensitivity to exogenous fatty acids (i.e., palmitic acid (PA) and docosahexaenoic acid (DHA)). Moreover, we verified the impact of exogenous fatty acids on ER lipid composition. (3) Results: The data obtained demonstrate that MDA-MB-231 cells are more sensitive to the lipid microenvironment and that both PA and DHA are able to remodel their ER membranes with consequences on resident enzyme activity. On the contrary, MCF7 cells are less sensitive to PA, whereas they incorporate DHA, although less efficiently than MDA-MB-231 cells. (4) Conclusions: This study sustains the importance of lipid metabolism as an innovative hallmark to discriminate breast cancer subclasses and to develop personalized and innovative pharmacological strategies. The different sensitivities to the lipid environment shown by MCF7 and MDA-MB-231 cells might be related to cell malignancy and chemoresistance onset. In the future, this new approach could lead to a substantial decrease both in deleterious side effects for the patients and in the cost of entire therapeutic treatments coupled with increased therapy efficiency.
Connection between Social Relationships and Basic Motor Competencies in Early Childhood
Authors: Herrmann Christian , Bretz Kathrin , Kühnis Jürgen , Seelig Harald , Keller Roger , Ferrari Ilaria
Published: January 2021

In preschool, children build new contacts and social relationships with other people. They learn to cooperate with their peers and communicate in groups. In addition to social relationships, basic motor competencies (in German: Motorische Basiskompetenzen (MOBAK)) are also seen as a central developmental goal in early childhood and are necessary for participation in the culture of sports and movement. The aim of this paper is to describe the connection between social relationships and basic motor competencies in early childhood. In this present study, the motor competencies of N = 548 preschool children (51% girls, M = 68.0 months, SD = 6.8) were tested in the competence areas of self-movement and object movement. The children’s perceived social relationships were recorded from teacher and parent perspectives. The results clearly show a connection between social relationships and motor competencies in early childhood, with a stronger connection observed in boys. This finding is relevant both from a developmental and a health-oriented perspective, as it points to a link between physical and mental health, as well as technical and interdisciplinary competencies, in early childhood.
What Can Electric Noise Spectroscopy Tell Us on the Physics of Perovskites?
Authors: Barone Carlo , Pagano Sergio
Published: January 2021

Electric noise spectroscopy is a non-destructive and a very sensitive method for studying the dynamic behaviors of the charge carriers and the kinetic processes in several condensed matter systems, with no limitation on operating temperatures. This technique has been extensively used to investigate several perovskite compounds, manganese oxides (La1−xSrxMnO3, La0.7Ba0.3MnO3, and Pr0.7Ca0.3MnO3), and a double perovskite (Sr2FeMoO6), whose properties have recently attracted great attention. In this work are reported the results from a detailed electrical transport and noise characterizations for each of the above cited materials, and they are interpreted in terms of specific physical models, evidencing peculiar properties, such as quantum interference effects and charge density waves.
Characterization of Carboxymethyl Cellulose Films Incorporated with Chinese Fir Essential Oil and Their Application to Quality Improvement of Shine Muscat Grape
Authors: Mei Luyu , Shi Liuxin , Song Xiuli , Liu Su , Cheng Qiang , Zhu Kai , Zhuge Rongxia
Published: January 2021

In this study, carboxymethyl cellulose (CMC) films containing 1%, 2%, and 3% Chinese fir essential oil (CFEO) were prepared. The mechanical, optical, physical, microstructural, thermal stability and antimicrobial properties of the films were studied. A traditional steam distillation method was applied for CFEO extraction, in which 35 volatile components were identified. The research results showed that the CMC film mixed with 1% CFEO had the highest tensile strength (TS) and elongation at break (EB), whereas the flexibility was decreased under higher concentrations of CFEO. However, the film’s degree of transparency under controlled humidity did not decrease with an increase in CFEO concentration; thus, the sensory evaluation was not adversely effect. Furthermore, the thickness and the water solubility (WS) of film increased after the addition of CFEO. The thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) results indicated that the thermal stability of the CMC-CFEO films improved. Moreover, the composite films showed excellent inhibitory effects toward Gram-positive bacterias and Penicillium citrinum. The treatments of grapes with CMC + 1% CFEO resulted in the best properties during storage. CMC-CFEO film can be a candidate for food packaging due to its excellent performances.
Ion Release from Dental Implants, Prosthetic Abutments and Crowns under Physiological and Acidic Conditions
Authors: Arregui María , Latour Florian , Gil Francisco Javier , Pérez Román A. , Giner-Tarrida Luis , Delgado Luis M.
Published: January 2021

Ion release from dental implants and prosthetic restoration can affect osteointegration and implant viability over a long period of time. Therefore, the aim of this study was to study the ion release from implants and crowns, with and without intermediate anodized abutments, in two different media, simulating clinical conditions. The implants, intermediate prosthetic abutments and Cr–Co crowns were divided into two groups depending on the media: Hanks’ solution and 1% lactic acid, simulating body fluids and microbiologically conditioned fluids, respectively. The study followed the ISO 10271:2011 and 10993-15:2000 standards modified to simulate the replacement of fluids in the oral environment. The ions’ release was measured by inductively coupled plasma mass spectroscopy (ICP-EOS), and only aluminum, chromium, cobalt, titanium and vanadium were identified. Ion concentration was higher in lactic acid than in Hanks’ solution at all time points (p < 0.05). Only vanadium showed a very low ion release in lactic acid, with no statistically significant differences from the ion release in Hanks’ solution (p = 0.524). Both anodized abutments and the immersion medium influenced the release of ions and affected the corrosion of these structures. The presence of an intermediate anodized abutment also affected ion release, as the level of ions was lower in groups with this component.
PPDM-TAN: A Privacy-Preserving Multi-Party Classifier
Authors: Skarkala Maria Eleni , Maragoudakis Manolis , Gritzalis Stefanos , Mitrou Lilian
Published: January 2021

Distributed medical, financial, or social databases are analyzed daily for the discovery of patterns and useful information. Privacy concerns have emerged as some database segments contain sensitive data. Data mining techniques are used to parse, process, and manage enormous amounts of data while ensuring the preservation of private information. Cryptography, as shown by previous research, is the most accurate approach to acquiring knowledge while maintaining privacy. In this paper, we present an extension of a privacy-preserving data mining algorithm, thoroughly designed and developed for both horizontally and vertically partitioned databases, which contain either nominal or numeric attribute values. The proposed algorithm exploits the multi-candidate election schema to construct a privacy-preserving tree-augmented naive Bayesian classifier, a more robust variation of the classical naive Bayes classifier. The exploitation of the Paillier cryptosystem and the distinctive homomorphic primitive shows in the security analysis that privacy is ensured and the proposed algorithm provides strong defences against common attacks. Experiments deriving the benefits of real world databases demonstrate the preservation of private data while mining processes occur and the efficient handling of both database partition types.
Ethanol eDNA Reveals Unique Community Composition of Aquatic Macroinvertebrates Compared to Bulk Tissue Metabarcoding in a Biomonitoring Sampling Scheme
Authors: Persaud Sadhna Fiona , Cottenie Karl , Gleason Jennifer Erin
Published: January 2021

Freshwater ecosystems provide essential ecosystem services and support biodiversity; however, their water quality and biological communities are influenced by adjacent agricultural land use. Aquatic macroinvertebrates are commonly used as bioindicators of stream conditions in freshwater biomonitoring programs. Sorting benthic samples for molecular identification is a time-consuming process, and this study investigates the potential of ethanol-collected environmental DNA (eDNA) for metabarcoding macroinvertebrates, especially for common bioindicator groups. The objective of this study was to compare macroinvertebrate composition between paired bulk tissue and ethanol eDNA samples, as eDNA could provide a less time-consuming and non-destructive method of sampling macroinvertebrates. We collected benthic samples from streams in Ontario, Canada, and found that community composition varied greatly between sampling methods and that few taxa were shared between paired tissue and ethanol samples, suggesting that ethanol eDNA is not an acceptable substitute. It is unclear why we did not detect all the organisms that were preserved in the ethanol, or the origin of the DNA we did detect. Furthermore, we also detected no difference in community composition for bioindicator taxa due to surrounding land use or water chemistry, suggesting sites were similar in ecological condition.
Microperimetry and Optical Coherence Tomography Changes in Type-1 Diabetes Mellitus without Retinopathy
Authors: Orduna-Hospital Elvira , Otero-Rodríguez Judit , Perdices Lorena , Sánchez-Cano Ana , Boned-Murillo Ana , Acha Javier , Pinilla Isabel
Published: January 2021

Background: We aimed to measure and correlate inner retinal layer (IRL) thickness and macular sensitivity by optical coherence tomography (OCT) and by microperimetry, respectively, in type 1 diabetes mellitus patients (DM1) without diabetic retinopathy (DR). Methods: Fifty-one DM1 patients and 81 age-matched healthy subjects underwent measurement of the axial length (AL), retinal thickness in the macular ETDRS areas by swept source (SS)-OCT and macular sensitivity by microperimeter. Results: The total retinal and IRL thicknesses were thicker in the DM1 group (p < 0.05) in practically all ETDRS areas, and they had a generalized decrease in sensitivity (p < 0.05) in 9 areas between both groups. There was a significant negative correlation between retinal sensitivity and age in all areas and in visual acuity (VA) in 5 out of the 9 areas for DM1 patients. Only a mild negative correlation was observed between retinal sensitivity in the 5° nasal inner (5NI) area and in IRL thickness in the temporal inner (TI) area (−0.309 with p = 0.029) in the DM1 group. Conclusion: Aging and disease evolution in DM1 patients without DR signs generate a decrease in retinal sensitivity. There was a direct relationship between retinal sensitivity and macular thickness in the DM1 group.
The Added Value of [18F]FDG PET/CT in the Management of Invasive Fungal Infections
Authors: Ankrah Alfred O. , Creemers-Schild Dina , de Keizer Bart , Klein Hans C. , Dierckx Rudi A. J. O. , Kwee Thomas C. , Span Lambert F. R. , de Jong Pim A. , Sathekge Mike M. , Glaudemans Andor W. J. M.
Published: January 2021

Anatomy-based imaging methods are the usual imaging methods used in assessing invasive fungal infections (IFIs). [18F]FDG PET/CT has also been used in the evaluation of IFIs. We assessed the added value of [18F]FDG PET/CT when added to the most frequently used anatomy-based studies in the evaluation of IFIs. The study was conducted in two University Medical Centers in the Netherlands. Reports of [18F]FDG PET/CT and anatomy-based imaging performed within two weeks of the [18F]FDG PET/CT scan were retrieved, and the presence and sites of IFI lesions were documented for each procedure. We included 155 [18F]FDG PET/CT scans performed in 73 patients. A total of 216 anatomy-based studies including 80 chest X-rays, 89 computed tomography studies, 14 magnetic resonance imaging studies, and 33 ultrasound imaging studies were studied. The anatomy-based studies were concordant with the [18F]FDG PET/CT for 94.4% of the scans performed. [18F]FDG PET/CT detected IFI lesions outside of the areas imaged by the anatomy-based studies in 48.6% of the scans. In 74% of the patients, [18F]FDG PET/CT added value in the management of the IFIs.
No Statistical-Computational Gap in Spiked Matrix Models with Generative Network Priors
Authors: Cocola Jorio , Hand Paul , Voroninski Vladislav
Published: January 2021

We provide a non-asymptotic analysis of the spiked Wishart and Wigner matrix models with a generative neural network prior. Spiked random matrices have the form of a rank-one signal plus noise and have been used as models for high dimensional Principal Component Analysis (PCA), community detection and synchronization over groups. Depending on the prior imposed on the spike, these models can display a statistical-computational gap between the information theoretically optimal reconstruction error that can be achieved with unbounded computational resources and the sub-optimal performances of currently known polynomial time algorithms. These gaps are believed to be fundamental, as in the emblematic case of Sparse PCA. In stark contrast to such cases, we show that there is no statistical-computational gap under a generative network prior, in which the spike lies on the range of a generative neural network. Specifically, we analyze a gradient descent method for minimizing a nonlinear least squares objective over the range of an expansive-Gaussian neural network and show that it can recover in polynomial time an estimate of the underlying spike with a rate-optimal sample complexity and dependence on the noise level.
Active Contour Model Using Fast Fourier Transformation for Salient Object Detection
Authors: Khan Umer Sadiq , Zhang Xingjun , Su Yuanqi
Published: January 2021

The active contour model is a comprehensive research technique used for salient object detection. Most active contour models of saliency detection are developed in the context of natural scenes, and their role with synthetic and medical images is not well investigated. Existing active contour models perform efficiently in many complexities but facing challenges on synthetic and medical images due to the limited time like, precise automatic fitted contour and expensive initialization computational cost. Our intention is detecting automatic boundary of the object without re-initialization which further in evolution drive to extract salient object. For this, we propose a simple novel derivative of a numerical solution scheme, using fast Fourier transformation (FFT) in active contour (Snake) differential equations that has two major enhancements, namely it completely avoids the approximation of expansive spatial derivatives finite differences, and the regularization scheme can be generally extended more. Second, FFT is significantly faster compared to the traditional solution in spatial domain. Finally, this model practiced Fourier-force function to fit curves naturally and extract salient objects from the background. Compared with the state-of-the-art methods, the proposed method achieves at least a 3% increase of accuracy on three diverse set of images. Moreover, it runs very fast, and the average running time of the proposed methods is about one twelfth of the baseline.
A Minimalistic Prediction Model to Determine Energy Production and Costs of Offshore Wind Farms
Authors: Sørensen Jens Nørkær , Larsen Gunner Christian
Published: January 2021

A numerical framework for determining the available wind power and associated costs related to the development of large-scale offshore wind farms is presented. The idea is to develop a fast and robust minimal prediction model, which with a limited number of easy accessible input variables can determine the annual energy output and associated costs for a specified offshore wind farm. The utilized approach combines an energy production model for offshore-located wind farms with an associated cost model that only demands global input parameters, such as wind turbine rotor diameter, nameplate capacity, area of the wind farm, number of turbines, water depth, and mean wind speed Weibull parameters for the site. The cost model includes expressions for the most essential wind farm cost elements—such as costs of wind turbines, support structures, cables and electrical substations, as well as costs of operation and maintenance—as function of rotor size, interspatial distance between the wind turbines, and water depth. The numbers used in the cost model are based on previous but updatable experiences from offshore wind farms, and are therefore, in general, moderately conservative. The model is validated against data from existing wind farms, and shows generally a very good agreement with actual performance and cost results for a series of well-documented wind farms.
Design Framework of a Stand-Alone Microgrid Considering Power System Performance and Economic Efficiency
Authors: Lee Hak-Ju , Vu Ba Hau , Zafar Rehman , Hwang Sung-Wook , Chung Il-Yop
Published: January 2021

Stand-alone microgrids integrating renewable energy sources have emerged as an efficient energy solution for electrifying isolated sites, such as islands and remote areas. The design of a microgrid involves various influential factors, including technological development, economic feasibility, and environmental impacts, based on the conditions and regulations of a particular site. This paper proposes a comprehensive microgrid design framework based on power system analysis and techno-economic analysis. The obtained optimal microgrid configuration satisfies both the design objective and power system performance regulations. The proposed design approach focuses on using practical data and can adapt to any microgrid design problems based on the local characteristics of a specific site. The practicality and effectiveness of the design framework are validated by applying it to the design of a stand-alone microgrid for Deokjeok Island in South Korea. The case study results justify the importance of considering site-specific characteristics and the impacts of power system conditions on the optimal microgrid design.
Decomposition Analysis of the Evolution of the Local Energy System as a Tool to Assess the Effect of Local Actions: Methodology and Example of Malmö, Sweden
Authors: Azevedo Isabel , Leal Vítor
Published: January 2021

This paper proposes the use of decomposition analysis to assess the effect of local energy-related actions towards climate change mitigation, and thus improve policy evaluation and planning at the local level. The assessment of the impact of local actions has been a challenge, even from a strictly technical perspective. This happens because the total change observed is the result of multiple factors influencing local energy-related greenhouse gas (GHG) emissions, many of them not even influenced by local authorities. A methodology was developed, based on a recently developed decomposition model, that disaggregates the total observed changes in the local energy system into multiple causes/effects (including local socio-economic evolution, technology evolution, higher-level governance frame and local actions). The proposed methodology, including the quantification of the specific effect associated with local actions, is demonstrated with the case study of the municipality of Malmö (Sweden) in the timeframe between 1990 and 2015.
The Effects of Social Distancing on Electricity Demand Considering Temperature Dependency
Authors: Alkhraijah Mohannad , Alowaifeer Maad , Alsaleh Mansour , Alfaris Anas , Molzahn Daniel K.
Published: January 2021

To mitigate the spread of the Novel Coronavirus (COVID-19), governments around the world have imposed social distancing policies ranging from minor social activity suspensions to full curfews. These social distancing policies have altered electricity consumption behaviors in numerous countries. Many governments imposed strict social distancing policies during a temperature transition season where the impacts of temperature variations are particularly important for the operation of the electric grid. This paper studies how strict social distancing policies affect the relationship between electricity demand and ambient temperature. We first review the expected short- and long-term impacts of social distancing on the electricity demand. We then present a case study on the electricity demand of the Kingdom of Saudi Arabia during strict social distancing policies. The results of this case study suggest that strict social distancing policies result in a stronger correlation between temperature and electricity demand compared to previous years. Additionally, we observe a reduction in the time required for the electricity demand to respond to temperature changes. Power system regulators can use the results in this paper to better design energy policies. The results can also be used by power system operators to more accurately forecast electricity demands and avoid inefficient and insecure operation of the electric grid.
Analysis of Subsynchronous Torsional of Wind–Thermal Bundled System Transmitted via HVDC Based on Signal Injection Method
Authors: Wang Junxi , Jia Qi , Yan Gangui , Liu Kan , Wang Dan
Published: January 2021

With the development of large-scale new energy, the wind–thermal bundled system transmitted via high-voltage direct current (HVDC) has become the main method to solve the problem of wind power consumption. At the same time, the problem of subsynchronous oscillation among wind power generators, high-voltage direct current (HVDC), and synchronous generators (SGs) has become increasingly prominent. According to the dynamic interaction among doubly fed induction generators (DFIGs), HVDC, and SGs, a linearization model of DFIGs and SGs transmitted via HVDC is established, and the influence of the electromagnetic transient of wind turbines and HVDC on the electromechanical transient processes of SGs is studied. Using the method of additional excitation signal injection, the influence of the main factors of DFIG on the damping characteristics of each torsional mode of SG is analyzed, including control parameters and operation conditions when the capacity of HVDC is fixed. The mechanism of the negative damping torsional of SGs is identified. A time-domain simulation model is built in Electromagnetic Transients including DC/Power Systems Computer Aided Design (EMTDC/PSCAD) to verify the correctness and effectiveness of the theoretical analysis.
Functional Ecology of Forest, Heath, and Shrub Savannah Alternate States in Eastern Canada
Authors: St. James Colin , Mallik Azim U.
Published: January 2021

In eastern Canada, alternation of wildfire regime due to fire suppression creates alternate vegetation states converting black spruce forest to heath and shrub savannah (SS). We compared the taxonomic diversity (TD) and functional diversity (FD) of post-fire forest, heath, and SS alternate states to determine if community FD can explain their persistence. We hypothesized that (i) species diversity (TD and FD) would be the highest in forest followed by SS and heath due to decreased interspecific competition and niche differentiation, (ii) differences between TD and FD indices would be greater in communities with high TD in forest due to high trait differentiation and richness, and (iii) changes in community trait values would indicate niche limitations and resource availability. We conducted this study in Terra Nova National Park, Newfoundland, Canada. We calculated functional dispersion (alpha FD), functional pairwise dissimilarity (beta FD), Shannon’s diversity (alpha TD), and Bray–Curtis dissimilarity (beta TD) from species cover. We used five functional traits (specific root length, specific leaf area, leaf dry matter content, height, and seed mass) related to nutrient acquisition, productivity, and growth. We found lower beta diversity in forest than heath and SS; forest also had higher species diversity and greater breadth in niche space utilization. SS was functionally similar to heath but lower than forest in functional dispersion and functional divergence. It had the highest functional richness and evenness. There was no difference in functional evenness between forest and heath. Functional beta diversity was the highest in forest, and did not differ between heath and SS. Resource acquisition and availability was the greatest in forest and the lowest in heath. We suspect that this might be due to forest having the highest functional trait turnover and niche utilization. We conclude that alternate vegetation states originating from alterations to the natural fire regime negatively impact ecosystem function.
Short-Term Dynamics of Vegetation Diversity and Aboveground Biomass of Picea abies (L.) H. Karst. Forests after Heavy Windstorm Disturbance
Authors: Máliš František , Konôpka Bohdan , Šebeň Vladimír , Pajtík Jozef , Merganičová Katarína
Published: January 2021

Although forest disturbances have become more frequent and severe due to ongoing climate change, our understanding of post-disturbance development of vegetation and tree–herb layer interactions remains limited. An extreme windstorm, which occurred on 19 November 2004, destroyed Picea abies (L.) H. Karst dominated forests in the High Tatra Mts. Here, we studied short-term changes in diversity, species composition, and aboveground biomass of trees and herb layer vegetation, including mutual relationships that elucidate tree–herb interactions during post-disturbance succession. Assessment of species composition and tree biomass measurements were performed at 50 sample plots (4 × 4 m) along two transects 12, 14, and 16 years after the forest destruction. Heights and stem base diameters of about 730 trees were measured and subsequently used for the calculation of aboveground tree biomass using species-specific allometric relationships. Aboveground biomass of herb layer was quantified at 300 subplots (20 × 20 cm) by destructive sampling. Species richness and spatial vegetation heterogeneity did not significantly change, and species composition exhibited small changes in accordance with expected successional trajectories. While aboveground tree biomass increased by about 190%, biomass of annual herb shoots decreased by about 68% and biomass of perennial herb shoots was stable during the studied period. The contribution of trees to total aboveground biomass increased from 83% to 97%. After 16 years of forest stands recovery, tree biomass represented approximately 13% of forest biomass before the disturbance. Herb layer biomass, particularly the biomass of annual herb shoots, was more closely related to tree cover than to tree biomass and its decline could be assigned to gradual tree growth. Our study provides clear evidence that short-term successional processes in post-disturbance vegetation are much better detectable by biomass than by diversity or compositional measures and emphasized the importance of light conditions in tree–herb competitive interactions.
A Classifier to Detect Informational vs. Non-Informational Heart Attack Tweets
Authors: Karajeh Ola , Darweesh Dirar , Darwish Omar , Abu-El-Rub Noor , Alsinglawi Belal , Alsaedi Nasser
Published: January 2021

Social media sites are considered one of the most important sources of data in many fields, such as health, education, and politics. While surveys provide explicit answers to specific questions, posts in social media have the same answers implicitly occurring in the text. This research aims to develop a method for extracting implicit answers from large tweet collections, and to demonstrate this method for an important concern: the problem of heart attacks. The approach is to collect tweets containing “heart attack” and then select from those the ones with useful information. Informational tweets are those which express real heart attack issues, e.g., “Yesterday morning, my grandfather had a heart attack while he was walking around the garden.” On the other hand, there are non-informational tweets such as “Dropped my iPhone for the first time and almost had a heart attack.” The starting point was to manually classify around 7000 tweets as either informational (11%) or non-informational (89%), thus yielding a labeled dataset to use in devising a machine learning classifier that can be applied to our large collection of over 20 million tweets. Tweets were cleaned and converted to a vector representation, suitable to be fed into different machine-learning algorithms: Deep neural networks, support vector machine (SVM), J48 decision tree and naïve Bayes. Our experimentation aimed to find the best algorithm to use to build a high-quality classifier. This involved splitting the labeled dataset, with 2/3 used to train the classifier and 1/3 used for evaluation besides cross-validation methods. The deep neural network (DNN) classifier obtained the highest accuracy (95.2%). In addition, it obtained the highest F1-scores with (73.6%) and (97.4%) for informational and non-informational classes, respectively.
Food and Beverages Containing Algae and Derived Ingredients Launched in the Market from 2015 to 2019: A Front-of-Pack Labeling Perspective with a Special Focus on Spain
Authors: Boukid Fatma , Castellari Massimo
Published: January 2021

Algae are a source of functional ingredients, with a large spectrum of healthy and functional compounds. Therefore, this study aimed to provide an overview on commercialized food and beverages made from algae and derived ingredients, with emphasis on the Spanish market, relying on the front-of-pack labeling. For this reason, the Mintel Global New Products Database was searched for foods and beverages containing “algae” ingredients, launched during the period 2015–2019. A total of 13,090 items were found worldwide, including 5720 items in Europe, in which 436 items were in Spain. Regardless of the market (global, European, and Spanish), a similar number of products categories (n = 20), dominant categories (dairy and desserts and ice cream) and dominant algal ingredient (carrageenans) were found. Nutritional information retrieved from Spanish products underlined that algae-based snacks had significantly lower energy, fat, and salt content compared to algae-free counterparts. On the contrary, spirulina- enriched ready to drink beverages had significantly higher energy and salt than algae-free. As such, reading the nutritional labeling is crucial to selecting products that suit consumer needs or/and expectations. Furthermore, only 8% of products reported the algal species and the level of inclusion, so this study emphasizes the importance of labeling legislation to provide complete product information to consumers.
Disentangling Individual Phases in the Hunted vs. Farmed Meat Supply Chain: Exploring Hunters’ Perceptions in Italy
Authors: Marescotti Maria Elena , Demartini Eugenio , Gibbert Michael , Viganò Roberto , Gaviglio Anna
Published: January 2021

The growing body of literature concerning the hunted wild game meat (HWGM) supply chain is mainly focused on the final consumer, while little is known about upstream production processes. Even though the hunter plays a central role here, it is not well understood how hunters themselves perceive their role in the various phases of the production process. The present study explores Italian hunters’ perception of the HWGM supply chain and compares it to their perception towards the conventional farmed meat supply chain. We distinguish several phases of this production process and find that the final phase related to on-site game dressing is considered problematic, perhaps because hunters perceive themselves as less skilled than professional butchers. The results, in fact, show that hunters prefer hunted products over farmed meat, but that they consider hunted wild boar meat less safe compared to farmed pork. Findings from this study provide a rare glimpse from the inside of the supply chain and reveals the needs for a broad risk assessment analysis on the Italian game meat supply chain. Considering the development of the Italian emerging market of the HWGM, our results also highlight the relevance of training activities on hunters in order to increase the safety and quality of the final product.
Starch Edible Films/Coatings Added with Carvacrol and Thymol: In Vitro and In Vivo Evaluation against Colletotrichum gloeosporioides
Authors: Ochoa-Velasco Carlos Enrique , Pérez-Pérez Julio César , Varillas-Torres José Mauricio , Navarro-Cruz Addí Rhode , Hernández-Carranza Paola , Munguía-Pérez Ricardo , Cid-Pérez Teresa Soledad , Avila-Sosa Raúl
Published: January 2021

The aim of this work was to evaluate the in vitro and in vivo effectiveness of thymol and carvacrol added to edible starch films and coatings against Colletotrichum gloeosporioides. In vitro evaluation consisted of determining minimal inhibitory concentration (MIC) of carvacrol and thymol was determined at different pH values against Colletotrichum gloeosporioides. With MIC values, binary mixtures were developed. From these results, two coatings formulations were in vivo evaluated on mango and papaya. Physicochemical analysis, color change, fruit lesions and C. gloeosporioides growth were determined during storage. In vitro assay indicated that the MIC value of carvacrol and thymol against C. gloeosporioides was 1500 mg/L at pH 5. An additive effect was determined with 750/750 and 1125/375 mg/L mixtures of carvacrol and thymol, respectively. Coated fruits with selected mixtures of carvacrol and thymol presented a delay in firmness, maturity index and color change. Moreover, a fungistatic effect was observed due to a reduction of lesions in coated fruits. These results were corroborated by the increase in the lag phase value and the reduction of the growth rate. Carvacrol and thymol incorporated into edible films and coatings are able to reduce the incidence of anthracnose symptoms on mango and papaya.
Postharvest Reduction of Salmonella enterica on Tomatoes Using a Pelargonic Acid Emulsion
Authors: White Elizabeth , Kumar Govindaraj Dev , da Silva Andre Luiz Biscaia Ribeiro , Kerr William L. , Cimowsky Samuel , Widmer J. Andrew , Dunn Laurel L.
Published: January 2021

A novel produce wash consisting of pelargonic acid (PEL) emulsions was tested on tomatoes contaminated with a five-serovar Salmonella enterica cocktail. Ability to reduce contamination on the inoculated tomato surface, as well as mitigation of subsequent cross-contamination to uninoculated tomatoes washed in re-used/spent wash water were examined. Sanitizer efficacy was also examined over 1 and 7 d storage time (8 °C, recommended for red ripe tomatoes) and in the presence of 0.5% (w/v) organic load. PEL performed statistically the same (p ≤ 0.05) at both 30 mM and 50 mM concentrations and resulted in greater than 1, 5 and 6 log CFU/g Salmonella reductions at 0 h, 1 d and 7 d, respectively, when compared to a water-only or no rinse (NR) treatment. This was also a significantly greater reduction than was observed due to chlorine (sodium hypochlorite) and peroxyacetic acid (PAA) at all time points (p ≤ 0.01). Organic load had no impact on sanitizer efficacy for all examined treatments. Finally, PEL had a deleterious impact on tomato texture. At 1 d, ca. 5 N and 7 N were required to achieve tomato skin penetration and compression, respectively, compared to >9 N and 15 N required by all other treatments (p ≤ 0.05). While PEL sanitizers effectively reduced inoculated Salmonella and subsequent transfer to uninoculated tomatoes, reformulation may be necessary to prevent deleterious quality impacts on produce.
Colon Bioaccessibility under In Vitro Gastrointestinal Digestion of Different Coffee Brews Chemically Profiled through UHPLC-Q-Orbitrap HRMS
Authors: Castaldo Luigi , Izzo Luana , Narváez Alfonso , Rodríguez-Carrasco Yelko , Grosso Michela , Ritieni Alberto
Published: January 2021

Coffee represents one of the most traditionally consumed beverages worldwide, containing a broad range of human health–related compounds. According to previous studies, regular coffee consumption may display protective effects against colorectal cancer and other chronic diseases. The main goal of this research was to evaluate the bioaccessibility of phenolic content and variation in antioxidant capacity of three different types of coffee brews after simulated gastrointestinal digestion. This would allow to elucidate how antioxidant compounds present in coffee may exert their effect on the human body, especially in the colonic stage. Moreover, the content of bioactive compounds namely chlorogenic acids (CGAs, n = 11) and caffeine was also assessed throughout ultra-high-performance liquid chromatography followed by high-resolution Orbitrap mass spectrometry (UHPLC-Q-Orbitrap HRMS). The three main isomers of caffeoylquinic acid constituted the highest fraction of CGAs present in the samples, accounting for 66.0% to 70.9% of total CGAs. The bioaccessibility of coffee polyphenols significantly increased in digested samples from 45.9% to 62.9% at the end of the colonic passage, compared to the non-digested samples. These results point to the colonic stage as the major biological site of action of the active antioxidant coffee compounds.