bluuebunny/crossref_metadata_2025 huggingface dataset:
New Flexible Protective Coating for Printed Smart Textiles
Authors: Bartsch Valérie , von Arnim Volkmar , Kuijpens Sven , Haupt Michael , Stegmaier Thomas , Gresser Götz T.
Published: January 2021

In the field of food packaging, the addition of exfoliated layered silicates in polymers has been established to improve the polymers’ gas barrier properties. Using these polymers as coatings to protect smart textiles from oxidation and corrosion while maintaining their textile properties should significantly extend their lifetime and promote their market penetration. The aim of this study was to print new polymer dispersions containing layered silicates to protect screen-printed conductive structures, and to test the resulting samples. For this, appropriate printing parameters were determined by statistical design of experiments. According to these results, conductive structures were printed and protected with the selected coating. The abrasion resistance and the continuity of the protective layer of the printed samples were then measured. A continuous protective coating of approximately 70–80 µm thickness was applied on a conductive structure. The printed samples showed a very high resistance to abrasion (unchanged by 85,000 abrasion cycles) while remaining flexible and presenting a lower water vapor permeability (<2.5 g/m² d) than the coatings commonly used in the textile field.
Investigation of the North Atlantic Oscillation and Indian Ocean Dipole Influence on Precipitation in Turkey with Cross-Spectral Analysis
Authors: Demir Umut Sakine , Koc Abdullah Cem
Published: January 2021

Predicting the future behavior of precipitation is of the utmost importance for planning agriculture or water resource management and in designing water structures. Determining the relationships between precipitation and the oceans may enable more accurate predictions. Therefore, oceanic and other persistent indices called teleconnection patterns can be used, namely the North Atlantic oscillation (NAO) and the Indian Ocean dipole (IOD). The NAO affects the precipitation patterns in the Atlantic Ocean and Mediterranean countries, such as in Turkey. The IOD is related to temperature and precipitation in the Indian Ocean coastal countries and in some areas far from the Indian Ocean. In this study, the effects of the NAO and IOD indices on precipitation in Turkey were investigated by means of cross-spectral analysis between the monthly total precipitation (mm) and monthly NAO and IOD index values. Phase shift values were also calculated for the selected periods and their accuracy was evaluated statistically, using the determination coefficient (R2) and Akaike information criterion (AIC) as performance criteria for the linear model. The results indicated strong correlations for the 13-, 14-, 16-, and 22–23-month periods between the NAO index and precipitation values; and for the 13-, 14-, 16–17-, and 20–21-month periods between the IOD index and precipitation values. After cross-spectral analysis between the NAO and IOD indices and precipitation values, the maximum phase shift values increased as the periods increased, while the maximum phase shift value for each period was almost half of the period value. Moreover, the maximum cross-power spectral density (CPSD) values increased as the periods increased. High CPSD values were observed in the west of Turkey for the NAO and in the east of Turkey for the IOD.
Potential of ARIMA-ANN, ARIMA-SVM, DT and CatBoost for Atmospheric PM2.5 Forecasting in Bangladesh
Authors: Shahriar Shihab Ahmad , Kayes Imrul , Hasan Kamrul , Hasan Mahadi , Islam Rashik , Awang Norrimi Rosaida , Hamzah Zulhazman , Rak Aweng Eh , Salam Mohammed Abdus
Published: January 2021

Atmospheric particulate matter (PM) has major threats to global health, especially in urban regions around the world. Dhaka, Narayanganj and Gazipur of Bangladesh are positioned as top ranking polluted metropolitan cities in the world. This study assessed the performance of the application of hybrid models, that is, Autoregressive Integrated Moving Average (ARIMA)-Artificial Neural Network (ANN), ARIMA-Support Vector Machine (SVM) and Principle Component Regression (PCR) along with Decision Tree (DT) and CatBoost deep learning model to predict the ambient PM2.5 concentrations. The data from January 2013 to May 2019 with 2342 observations were utilized in this study. Eighty percent of the data was used as training and the rest of the dataset was employed as testing. The performance of the models was evaluated by R2, RMSE and MAE value. Among the models, CatBoost performed best for predicting PM2.5 for all the stations. The RMSE values during the test period were 12.39 µg m−3, 13.06 µg m−3 and 12.97 µg m−3 for Dhaka, Narayanganj and Gazipur, respectively. Nonetheless, the ARIMA-ANN and DT methods also provided acceptable results. The study suggests adopting deep learning models for predicting atmospheric PM2.5 in Bangladesh.
Long-Term Results of Tinnitus Retraining Therapy in Patients Who Failed to Complete the Program
Authors: Lapenna Ruggero , Molini Egisto , Cipriani Laura , Del Zompo Maria Rita , Giommetti Giorgia , Faralli Mario , Ricci Giampietro
Published: January 2021

Purpose: We aimed to evaluate the results of Tinnitus Retraining Therapy (TRT) in patients who did not complete the program. Methods: We divided 90 patients who failed to complete the TRT program were into 3 groups: 36 patients who only completed the first phase of the TRT program (Missing group; M), 34 patients who attended counselling for less than 6 months (Noncompliant group; NC) and 20 patients who attended counselling for more than 6 months but did not complete the TRT program (Compliant group; C). The Tinnitus Handicap Inventory (THI), tinnitus Visual Analogue Scales (VAS) and a questionnaire regarding the reasons for dropout were obtained through a telephone survey. Results: Telephonic THI and VAS scores were significantly lower than the initial scores in the M and C groups but not in the NC group. Patients who were unsure about the effectiveness of TRT were prevalent in the NC group, and the poorest long-term THI results were registered in those patients. Conclusions: A fundamental cause of very poor TRT results was when patients were unsure about TRT. On the other hand, a single counselling session could be effective in reducing tinnitus annoyance in patients who accepted the TRT approach and trusted its efficacy.
Liquid Biopsy-Based Exo-oncomiRNAs Can Predict Prostate Cancer Aggressiveness
Authors: Ruiz-Plazas Xavier , Altuna-Coy Antonio , Alves-Santiago Marta , Vila-Barja José , García-Fontgivell Joan Francesc , Martínez-González Salomé , Segarra-Tomás José , Chacón Matilde R.
Published: January 2021

Liquid biopsy-based biomarkers, including microRNAs packaged within extracellular vesicles, are promising tools for patient management. The cytokine tumor necrosis factor-like weak inducer of apoptosis (TWEAK) is related to PCa progression and is found in the semen of patients with PCa. TWEAK can induce the transfer of exo-oncomiRNAs from tumor cells to body fluids, and this process might have utility in non-invasive PCa prognosis. We investigated TWEAK-regulated exo-microRNAs in semen and in post-digital rectal examination urine from patients with different degrees of PCa aggressiveness. We first identified 14 exo-oncomiRNAs regulated by TWEAK in PCa cells in vitro, and subsequently validated those using liquid biopsies from 97 patients with PCa. Exo-oncomiR-221-3p, -222-3p and -31-5p were significantly higher in the semen of high-risk patients than in low-risk peers, whereas exo-oncomiR-193-3p and -423-5p were significantly lower in paired samples of post-digital rectal examination urine. A panel of semen biomarkers comprising exo-oncomiR-221-3p, -222-3p and TWEAK was designed that could correctly classify 87.5% of patients with aggressive PCa, with 85.7% specificity and 76.9% sensitivity with an area under the curve of 0.857. We additionally found that TWEAK modulated two exo-oncomiR-221-3p targets, TCF12 and NLK. Overall, we show that liquid biopsy detection of TWEAK-regulated exo-oncomiRNAs can improve PCa prognosis prediction.
A Paravermal Trans-Cerebellar Approach to the Posterior Fossa Tumor Causes Hypertrophic Olivary Degeneration by Dentate Nucleus Injury
Authors: Schaller-Paule Martin A. , Baumgarten Peter , Seifert Volker , Wagner Marlies , Steidl Eike , Hattingen Elke , Wicke Felix , Steinbach Joachim P. , Foerch Christian , Konczalla Juergen
Published: January 2021

Background: In brain tumor surgery, injury to cerebellar connectivity pathways can induce a neurodegenerative disease called hypertrophic olivary degeneration (HOD), along with a disabling clinical syndrome. In children, cerebellar mutism syndrome (CMS) is another consequence of damage to cerebello–thalamo–cortical networks. The goal of this study was to compare paravermal trans-cerebellar to other more midline or lateral operative approaches in their risk of causing HOD on MR-imaging and CMS. Methods: We scanned our neurosurgical database for patients with surgical removal of pilocytic astrocytoma, ependymoma and medulloblastoma in the posterior fossa. Fifty patients with a mean age of 22.7 (±16.9) years were identified and analyzed. Results: HOD occurred in n = 10/50 (20%) patients within four months (median), always associated with contralateral dentate nucleus (DN)-lesions (p < 0.001). Patients with paravermal trans-cerebellar approach significantly more often developed HOD (7/11; 63.6%) when compared to other approaches (3/39; 7.7%; p < 0.001). Injury to the DN occurred more frequently after a paravermal approach (8/11 vs. 13/39 patients; p < 0.05). CMS was described for n = 12/50 patients (24%). Data indicated no correlation of radiological HOD and CMS development. Conclusions: A paravermal trans-cerebellar approach more likely causes HOD due to DN-injury when compared to more midline or lateral approaches. HOD is a radiological indicator for surgical disruption of cerebellar pathways involving the DN. Neurosurgeons should consider trajectories and approaches in the planning of posterior fossa surgery that spare the DN, whenever feasible.
Unraveling the In Vivo Protein Corona
Authors: Simon Johanna , Kuhn Gabor , Fichter Michael , Gehring Stephan , Landfester Katharina , Mailänder Volker
Published: January 2021

Understanding the behavior of nanoparticles upon contact with a physiological environment is of urgent need in order to improve their properties for a successful therapeutic application. Most commonly, the interaction of nanoparticles with plasma proteins are studied under in vitro conditions. However, this has been shown to not reflect the complex situation after in vivo administration. Therefore, here we focused on the investigation of magnetic nanoparticles with blood proteins under in vivo conditions. Importantly, we observed a radically different proteome in vivo in comparison to the in vitro situation underlining the significance of in vivo protein corona studies. Next to this, we found that the in vivo corona profile does not significantly change over time. To mimic the in vivo situation, we established an approach, which we termed “ex vivo” as it uses whole blood freshly prepared from an animal. Overall, we present a comprehensive analysis focusing on the interaction between nanoparticles and blood proteins under in vivo conditions and how to mimic this situation with our ex vivo approach. This knowledge is needed to characterize the true biological identity of nanoparticles.
Neuron–Glia Interactions in Tuberous Sclerosis Complex Affect the Synaptic Balance in 2D and Organoid Cultures
Authors: Dooves Stephanie , van Velthoven Arianne J. H. , Suciati Linda G. , Heine Vivi M.
Published: January 2021

Tuberous sclerosis complex (TSC) is a genetic disease affecting the brain. Neurological symptoms like epilepsy and neurodevelopmental issues cause a significant burden on patients. Both neurons and glial cells are affected by TSC mutations. Previous studies have shown changes in the excitation/inhibition balance (E/I balance) in TSC. Astrocytes are known to be important for neuronal development, and astrocytic dysfunction can cause changes in the E/I balance. We hypothesized that astrocytes affect the synaptic balance in TSC. TSC patient-derived stem cells were differentiated into astrocytes, which showed increased proliferation compared to control astrocytes. RNA sequencing revealed changes in gene expression, which were related to epidermal growth factor (EGF) signaling and enriched for genes that coded for secreted or transmembrane proteins. Control neurons were cultured in astrocyte-conditioned medium (ACM) of TSC and control astrocytes. After culture in TSC ACM, neurons showed an altered synaptic balance, with an increase in the percentage of VGAT+ synapses. These findings were confirmed in organoids, presenting a spontaneous 3D organization of neurons and glial cells. To conclude, this study shows that TSC astrocytes are affected and secrete factors that alter the synaptic balance. As an altered E/I balance may underlie many of the neurological TSC symptoms, astrocytes may provide new therapeutic targets.
Calcium Signalling in Alzheimer’s Disease: From Pathophysiological Regulation to Therapeutic Approaches
Authors: Chami Mounia
Published: January 2021

Alzheimer’s disease (AD) is a neurodegenerative pathology representing a socioeconomic challenge, however, the complex mechanism behind the disease is not yet fully understood [...]
Deer Exclusion Changes Vegetation Structure and Hunting Guilds of Spiders, but Not Multitrophic Understory Biodiversity
Authors: Bucher Roman , Rochlitz Jonas , Wegner Nathalie , Heiß Anna , Grebe Alexander , Schabo Dana G. , Farwig Nina
Published: January 2021

Ungulate herbivores modify plant community compositions, which can modulate biodiversity at higher trophic levels. However, these cascading effects on herbivorous and predatory arthropods in forest ecosystems remain poorly understood. We compared plant and arthropod communities between fenced exclosures and unfenced control plots in a permanent forest in Germany. After five years of deer exclusion, we quantified plant diversity and vegetation structure as well as the diversity of insects and spiders in 32 pair-wise plots. In addition, we compared spider communities with respect to different hunting guilds because they are expected to have different requirements for vegetation structure. Although we did not find differences in plant communities, vegetation height and heterogeneity were higher in exclosures compared to control plots. The diversity of insects and spiders was not affected by deer presence. However, the abundance of sheet-web weavers and ambush hunters was lower in exclosures whereas ground hunters were more common in exclosure plots. Structural changes in the vegetation changed predator hunting guilds even though mere abundance and biodiversity indices were not affected. We therefore suggest that monitoring of vegetation structure and associated functional groups seems more sensitive to assess the impact of ungulate herbivores compared to taxonomic metrics.
Breakpoint Analysis for the COVID-19 Pandemic and Its Effect on the Stock Markets
Authors: Chahuán-Jiménez Karime , Rubilar Rolando , de la Fuente-Mella Hanns , Leiva Víctor
Published: January 2021

In this research, statistical models are formulated to study the effect of the health crisis arising from COVID-19 in global markets. Breakpoints in the price series of stock indexes are considered. Such indexes are used as an approximation of the stock markets in different countries, taking into account that they are indicative of these markets because of their composition. The main results obtained in this investigation highlight that countries with better institutional and economic conditions are less affected by the pandemic. In addition, the effect of the health index in the models is associated with their non-significant parameters. This is due to that the health index used in the modeling would not determine the different capacities of the countries analyzed to respond efficiently to the pandemic effect. Therefore, the contagion is the preponderant factor when analyzing the structural breakdown that occurred in the world economy.
Operating Room Fomites as Potential Sources for Microbial Transmission in Burns Theatres
Authors: Rela Mariam , Opel Sophia , Williams Sarah , Collins Declan P. , Martin Kevin , Mughal Nabeela , Moore Luke S. P.
Published: January 2021

Background: Burn patients are susceptible to healthcare-associated infections. Contaminated surfaces play a role in microbial transmission. This study aimed to quantify the degree of contamination of burns theatre fomites during routine clinical use. Methods: The Patslide Patient Transfer Board (PAT slide) and operating table were investigated using two methods—bacterial swabs to culture viable organisms and adenosine triphosphate (ATP) swabs to measure biological material. Both items were sampled four times a day: before the first case, immediately after a case, immediately before the next case after cleaning and after the terminal clean. Results: Among 82 bacterial samples, four organisms were isolated, including Staphylococcus aureus, Enterobacter cloacae (E. cloacae) x2 and Pseudomonas aeruginosa (P. aeruginosa), all from the PAT slide. The E. cloacae persisted after cleaning. In 9/82 swabs, the ATP count was >10 relative light units (RLU). In all cases where an organism was identified, the ATP count was >10 RLU. Hence the sensitivity and specificity of ATP > 10 RLU in detecting an organism were 100% and 94% respectively. Conclusions: Within burns theatres, there are instances of bacterial contamination on surfaces that persist despite cleaning. ATP luminometers as a point-of-care device may have a role in determining the cleanliness of surfaces, potentially minimizing onwards-bacterial transmission.
Exergy-Based Assessment of Polymers Production and Recycling: An Application to the Automotive Sector
Authors: Russo Sofia , Valero Alicia , Valero Antonio , Iglesias-Émbil Marta
Published: January 2021

In the last century, the economic growth has been accompanied by a worldwide diffusion of polymers for multiple applications. However, there is a growing attention to the environmental pollution and energy consumption linked to the unconditional use of plastic. In the present work, exergy is used as a measure of the resource consumption during the life cycle of polymers. Nine commercially diffused polymers are chosen, and their production chains are identified according to the “grave to cradle” approach. The global Embodied Exergy (EE) is calculated as the sum of the contribution of each step of the chain, including the production process and the Exergy Replacement Cost (ERC) of the fossil fuel. Then, recycling routes and the associated exergy consumption are analysed. Thermodynamic recycling indexes are developed depending on the final product, namely the crude polymeric material and the oil derivatives or structural molecules. The main results show that some commonly used polymers have a considerable impact in terms of EE (e.g., PET). Recycling indexes encourage the recycling processes, which are always energetically convenient (from 10% to 60% of exergy savings) compared with the production from virgin raw material. Results from EE calculation are used for the thermodynamic assessment of the plastic content of vehicle components, to obtain useful information for recycling practices development.
The Impact of the Government Policy on the Energy Efficient Gap: The Evidence from Ukraine
Authors: Lyulyov Oleksii , Pimonenko Tetyana , Kwilinski Aleksy , Dzwigol Henryk , Dzwigol-Barosz Mariola , Pavlyk Vladyslav , Barosz Piotr
Published: January 2021

This paper aims to check the impact of investment and institutional determinants on the energy efficiency gap. The findings of the bibliometric analysis confirmed the growth of research interests in identifying the core determinants of the energy efficiency gap. The central hypothesises are: the increasing quality of the institutions leads to an increase of green investments in the energy sector and the dual relationships between investment and institutional determinants lead to additional synergy effects, which allow boosting the decline of energy efficiency gaps of the national economy. For the analysis, the times series were collected from the World Data Bank, Eurostat, Bloomberg, for Ukraine for the period of 2002–2019. The following methods were used: the unit root test—for checking the stationarity of data—and the Johansen test and VEC-modelling—for the cointegration analysis. The findings prove that to reduce the energy efficiency gaps in Ukraine by 1% next year, it is necessary to increase green energy investments by 1.5% this year, and the political stability and public perception of corruption by 3% and 1%. The increase of the public perception of corruption by 1.47 points and of political stability by 2.38 points leads to maximising the recovery speed of the Ukrainian energy sector. Thus, while developing the policy to decrease the energy efficiency gaps, the Ukrainian government should consider the level of public perception of corruption and political stability.
Crack Extraction for Polycrystalline Solar Panels
Authors: Xue Bai , Li Fang , Song Meiping , Shang Xiaodi , Cui Dongqing , Chu Jiaping , Dai Sui
Published: January 2021

Crack extraction of solar panels has become a research focus in recent years. The cracks are small and hidden. In addition, there are particles of irregular shape and size on the surface of the polycrystalline solar panel, whose reflection position and direction are random. Therefore, there is a complex and uneven texture background on the solar panel image, which makes the crack extraction more difficult. In this paper, a crack extraction method combining image texture and morphological features is proposed. Firstly, the background texture and multi-scale details are suppressed by the linear filter and the Laplace pyramid decomposition method. Secondly, the edge can be extracted based on the modulus maximum method of the wavelet transform. Finally, cracks were extracted by using the improved Fuzzy C-means (FCM) clustering combining the morphological and texture features of the cracks. To make the extraction results more accurate and reasonable, an improved region growth algorithm is proposed to optimize the extraction results. All of the above research is closely centered on the accuracy and stability requirements of the solar cell crack detection, which is also the key point of this paper. The experimental results show that various improved or innovative algorithms proposed in this paper can accurately extract the position of cracks and obtain better extraction results. The detection results have good stability and can be faithful to the actual situation, which will promote the application of solar cells in more fields.
Modelling of an Existing Neutral Temperature District Heating Network: Detailed and Approximate Approaches
Authors: Calixto Selva , Cozzini Marco , Manzolini Giampaolo
Published: January 2021

This paper deals with the modelling of an existing neutral-temperature district heating network, meaning that the distribution temperature is close to the ambient temperature, with decentralised heat pumps. The considered case is located in Ospitaletto, Italy. Heat sources are given by industrial waste heat at about 25 °C and aquifer wells at about 15 °C. Two models are used to analyse the network: a detailed model able to calculate local values of operating parameters and an approximate model focused on energy balances aggregating all users with a lumped demand. Both models include the behaviour of heat pumps, a feature not available in other district heating modelling tools. An entire year of operation is considered, with an hourly time resolution. Load profiles are provided as inputs, while the main outputs consist of energy balances and primary energy consumptions. The corresponding results are compared, showing a reasonable agreement, where the approximate model underestimates the overall electricity consumptions by about 15% with respect to the detailed model. On the other hand, the different information levels and execution times (the detailed model requires about 30 min to solve the considered network for a full year with hourly time steps, while the approximate model is almost immediate) make the two models suitable for different purposes, like the simulation of control solutions for the detailed one and scenario analysis for the other.
Variable-Gain Super-Twisting Sliding Mode Damping Control of Series-Compensated DFIG-Based Wind Power System for SSCI Mitigation
Authors: Ma Ronglin , Han Yaozhen , Pan Weigang
Published: January 2021

Subsynchronous oscillation, caused by the interaction between the rotor side converter (RSC) control of the doubly fed induction generator (DFIG) and series-compensated transmission line, is an alleged subsynchronous control interaction (SSCI). SSCI can cause DFIGs to go offline and crowbar circuit breakdown, and then deteriorate power system stability. This paper proposes a novel adaptive super-twisting sliding mode SSCI mitigation method for series-compensated DFIG-based wind power systems. Rotor currents were constrained to track the reference values which are determined by maximum power point tracking (MPPT) and reactive power demand. Super-twisting control laws were designed to generate RSC control signals. True adaptive and non-overestimated control gains were conceived with the aid of barrier function, without need of upper bound of uncertainty derivatives. Stability proof of the studied closed-loop power system was demonstrated in detail with the help of the Lyapunov method. Time-domain simulation for 100 MW aggregated DFIG wind farm was executed on MATLAB/Simulink platform. Some comparative simulation results with conventional PI control, partial feedback linearization control, and first-order sliding mode were also obtained, which verify the validity, robustness, and superiority of the proposed control strategy.
Triple-Mesoscopic Carbon Perovskite Solar Cells: Materials, Processing and Applications
Authors: Meroni Simone M. P. , Worsley Carys , Raptis Dimitrios , Watson Trystan M.
Published: January 2021

Perovskite solar cells (PSCs) have already achieved comparable performance to industrially established silicon technologies. However, high performance and stability must be also be achieved at large area and low cost to be truly commercially viable. The fully printable triple-mesoscopic carbon perovskite solar cell (mCPSC) has demonstrated unprecedented stability and can be produced at low capital cost with inexpensive materials. These devices are inherently scalable, and large-area modules have already been fabricated using low-cost screen printing. As a uniquely stable, scalable and low-cost architecture, mCPSC research has advanced significantly in recent years. This review provides a detailed overview of advancements in the materials and processing of each individual stack layer as well as in-depth coverage of work on perovskite formulations, with the view of highlighting potential areas for future research. Long term stability studies will also be discussed, to emphasise the impressive achievements of mCPSCs for both indoor and outdoor applications.
A Comparative Study on Fault Detection Methods for Gas Turbine Combustion Systems
Authors: Liu Jinfu , Long Zhenhua , Bai Mingliang , Zhu Linhai , Yu Daren
Published: January 2021

As one of the core components of gas turbines, the combustion system operates in a high-temperature and high-pressure adverse environment, which makes it extremely prone to faults and catastrophic accidents. Therefore, it is necessary to monitor the combustion system to detect in a timely way whether its performance has deteriorated, to improve the safety and economy of gas turbine operation. However, the combustor outlet temperature is so high that conventional sensors cannot work in such a harsh environment for a long time. In practical application, temperature thermocouples distributed at the turbine outlet are used to monitor the exhaust gas temperature (EGT) to indirectly monitor the performance of the combustion system, but, the EGT is not only affected by faults but also influenced by many interference factors, such as ambient conditions, operating conditions, rotation and mixing of uneven hot gas, performance degradation of compressor, etc., which will reduce the sensitivity and reliability of fault detection. For this reason, many scholars have devoted themselves to the research of combustion system fault detection and proposed many excellent methods. However, few studies have compared these methods. This paper will introduce the main methods of combustion system fault detection and select current mainstream methods for analysis. And a circumferential temperature distribution model of gas turbine is established to simulate the EGT profile when a fault is coupled with interference factors, then use the simulation data to compare the detection results of selected methods. Besides, the comparison results are verified by the actual operation data of a gas turbine. Finally, through comparative research and mechanism analysis, the study points out a more suitable method for gas turbine combustion system fault detection and proposes possible development directions.
Energy Metering Integrated Circuit Behavior beyond Standards Requirements
Authors: Quijano Cetina Renan , Seferi Yljon , Blair Steven M. , Wright Paul S.
Published: January 2021

During the last few years, the accuracy of static electricity meters (SEM) has been questioned. Significant metering deviations with respect to a reference meter have been observed at customer premises, and laboratory experimental tests results support such findings. The root cause of such errors remains unknown, as there are multiple elements that could affect the accuracy of electricity meters. Furthermore, standard compliant meters exposed to distorted signals may produce negligible, positive or negative relative error depending on the instrument design. Distorted current signals with fast amplitude transitions have produced the highest error in SEMs reported in the literature. In this paper, the accuracy of an energy metering Integrated Circuit (IC) is evaluated beyond the limits of the standards requirements employing a selection of distorted signals from the standards, real-world captured signals and a set of waveforms designed to test the IC under fast changing currents conditions, which are representative of the waveforms resulting from power electronic devices. The experimental results reveal an accuracy boundary imposed by Gibb’s phenomenon for fast changing current signals and a strong relationship between the IC’s measurement error and two key parameters of the measured waveform: signal slope and phase angle. This paper therefore provides a methodology for the comprehensive analysis of SEMs in future power systems which are dominated with power electronic-controlled electrical demand and contributes to the search for the root cause of error in SEMs exposed to distorted waveforms.
Effect of Helix Angle on the Performance of Helical Vertical Axis Wind Turbine
Authors: Divakaran Unnikrishnan , Ramesh Ajith , Mohammad Akram , Velamati Ratna Kishore
Published: January 2021

The energy crisis has forced researchers to look for various non-conventional energy sources. Wind energy is one of the potential sources, and researchers have invested resources in developing different kinds of wind turbines. Vertical axis wind turbines (VAWT) have received less attention than their horizontal-axis counterparts. A helical-bladed VAWT is preferred because it makes perfect sense as an improvement in design, as they have higher azimuth angles of power generation capabilities. This paper studies the effects of the helix angle of blades in the aerodynamic performance of VAWT using 3D numerical simulations. Three different helix angles of 60°, 90°, and 120° of a three-bladed VAWT operating across different tip speed ratios were studied. Turbulence is modelled using a four-equation transition SST k-ω model (shear stress transport). The 60° helical-bladed VAWT was found to be better performing in comparison with all other helical-bladed and straight-bladed VAWT. The ripple effects on the shaft are also analysed using a standard deviation plot of the moment coefficient generated by a single blade over one complete cycle of its rotation. It was observed that the greater the helix angle, the lower the standard deviation. The paper also tries to analyse the percentage of power generated by each quartile of flow and the contribution of each section of the blade. Ansys FLUENT was employed for the entire study. A comparative study between different helical-bladed VAWT and straight-bladed VAWT was carried out along with wake structure analysis and flow contours for a better understanding of the flow field.
Path Segmentation-Based Hybrid Caching in Information-Centric Networks
Authors: Li Wei , Sun Peng , Han Rui
Published: January 2021

Information-centric networks (ICNs) have received wide interest from researchers, and in-network caching is an important characteristic of ICN. The management and placement of contents are essential due to cache nodes’ limited cache space and the huge Internet traffic. This paper focuses on coordinating two cache metrics, namely user access latency and network resource utilization, and proposes a hybrid caching scheme called the path segmentation-based hybrid caching scheme (PSBC). We temporarily divide each data transmit path into a user-edge area and non-edge area. The user-edge area adopts a heuristic caching scheme to reduce user access latency. In contrast, the non-edge area implements caching network content migration and optimization to improve network resource utilization. The simulation results show that the proposed method positively affects both the cache hit ratio and access latency.
K-Module Algorithm: An Additional Step to Improve the Clustering Results of WGCNA Co-Expression Networks
Authors: Hou Jie , Ye Xiufen , Li Chuanlong , Wang Yixing
Published: January 2021

Among biological networks, co-expression networks have been widely studied. One of the most commonly used pipelines for the construction of co-expression networks is weighted gene co-expression network analysis (WGCNA), which can identify highly co-expressed clusters of genes (modules). WGCNA identifies gene modules using hierarchical clustering. The major drawback of hierarchical clustering is that once two objects are clustered together, it cannot be reversed; thus, re-adjustment of the unbefitting decision is impossible. In this paper, we calculate the similarity matrix with the distance correlation for WGCNA to construct a gene co-expression network, and present a new approach called the k-module algorithm to improve the WGCNA clustering results. This method can assign all genes to the module with the highest mean connectivity with these genes. This algorithm re-adjusts the results of hierarchical clustering while retaining the advantages of the dynamic tree cut method. The validity of the algorithm is verified using six datasets from microarray and RNA-seq data. The k-module algorithm has fewer iterations, which leads to lower complexity. We verify that the gene modules obtained by the k-module algorithm have high enrichment scores and strong stability. Our method improves upon hierarchical clustering, and can be applied to general clustering algorithms based on the similarity matrix, not limited to gene co-expression network analysis.
Assessing the Potential of Artificial Intelligence (Artificial Neural Networks) in Predicting the Spatiotemporal Pattern of Wildfire-Generated PM2.5 Concentration
Authors: Mirzaei Mojgan , Bertazzon Stefania , Couloigner Isabelle , Farjad Babak
Published: January 2021

To evaluate the health effects of wildfire smoke, it is crucial to identify reliable models, at fine spatiotemporal resolution, of exposure to wildfire-generated PM2.5. To this end, satellite-drived aerosol optical depth (AOD) measurements are widely used in exposure models, providing long and short-term PM2.5 predictions. Multiple regression models, specifically land use regression (LUR), incorporating AOD images have shown good potential for estimating long-term PM2.5 exposure, but less so for short-term predictions. In this study, we developed artificial neural networks (ANNs) and, in particular, multilayer perceptron (MLP) by integrating ground-based PM2.5 measurements with AOD images and meteorological and spatial variables. Moreover, we used spatial- and temporal-ANNs to investigate and compare the ANNs’ ability to predict different PM2.5 concentration levels caused by abrupt spatial and temporal changes in fire smoke. The study herein analyzes and compares the viability of previously established neural network approaches in predicting short-term PM2.5 exposure during the 2014–2017 wildfire seasons in the province of Alberta, Canada. The performance of ANNs is also compared to classical models, including simple correlation (PM2.5 vs. AOD) and multiple linear regression (MLR) including meteorological and land-use predictors (MET_AOD_LUR). Our study shows that ANN achieved a 15% to 113% R2 increase compared to competing models.
Playing Non-Professional Football in COVID-19 Time: A Narrative Review of Recommendations, Considerations, and Best Practices
Authors: Rico-González Markel , Pino-Ortega José , Ardigò Luca Paolo
Published: January 2021

The coronavirus disease (COVID-19) pandemic in 2020 resulted in widespread interruption of team sports training and competitions. Our aim was to review the recommendations and best practices in return to play in non-professional football after activity lockdown. The authors searched two electronic databases (PubMed, Web of Science) to extract studies published before September 15 2020. Twenty studies explained recommendations, considerations, or best practices in return to play in football, and all of them were clustered into three groups: (1) training load management (n = 10), (2) medical recommendations (n = 9), and (3) recovery related issues (n = 5). The way to establish a progression in training process should be based on training load management and managing the number of stimuli per time. Following the studies, this training process should be divided into three phases: phase 1—physical distancing should be maintained; phases 2 and 3—group training should start. Medical considerations were clustered into different groups: general, pre- and post- training, during training, education, planning to return to competition, and suggestions for post confinement weeks. In particular, social issues, strict hygiene questions, and continuous PCR testing should be considered in return to play over football season. Finally, since a correlation has been found between high-intensive training loads and immunoglobulin A, nutritional and lifestyle recovery strategies should be performed. Moreover, since immunosuppression has been related to congested schedules (<72 h between matches), football federations should avoid this situation.
Indigenous Peoples, Exclusion and Precarious Work: Design of Strategies to Address Poverty in Indigenous and Peasant Populations in Ecuador through the SWOT-AHP Methodology
Authors: García Guerrero Jorge E. , Rueda López Ramón , Luque González Arturo , Ceular-Villamandos Nuria
Published: January 2021

This research analysed the options that, following decent employment and the social economy, can allow the human development of poor, excluded and vulnerable indigenous populations in Ecuador. A set of strategies were developed which can be implemented by public authorities and by community organisations. They were designed from two types of expert consultations: the Delphi method and the analysis of Strengths, Weaknesses, Opportunities and Threats (SWOT) combined with Analytic Hierarchy Process method (AHP) for hierarchizing the criteria collected and obtaining strategies. The proposed strategies are as follows: adopting appropriate legal frameworks, respecting peoples’ rights, better distribution of public resources, implementing monitoring systems, developing solidarity markets and recognizing the participation of the poor as a subject of rights. This investigation revealed differences between the state, which identifies the poor with monetary indicators, and the indigenous peoples, who see it as the lack of community links, by conceiving the poor as a beneficiary of official assistance, despite the fact that a strong community and peasant organisation could be used. The value of an economy based on reciprocity and confidence was also recognized, identifying niches of production and consumption to create partnerships and ensure the participation of indigenous peoples in decision-making areas.
Psychometric Validation of the Living with Chronic Illness Scale in Patients with Chronic Heart Failure
Authors: Ambrosio Leire , Perez-Manchon David , Carvajal-Carrascal Gloria , Fuentes-Ramirez Alejandra , Caparros Neus , Ruiz de Ocenda Manuel Ignacio , Timonet Eva , Navarta-Sanchez Maria Victoria , Rodriguez-Blazquez Carmen
Published: January 2021

It is necessary to develop self-reported instruments that evaluate the process of living with chronic heart failure (HF) holistically. The Living with Chronic Illness Scale—HF (LW-CI-HF) is the only available tool to evaluate how patients are living with HF. The aim is to analyse the psychometric properties of the LW-CI scale in the HF population. An international, cross-sectional validation study was carried out in 603 patients living with HF from Spain and Colombia. The variables measured were living with HF, perceived social support, satisfaction with life, quality of life and global impression of severity. The LW-CI-HF scale presented good data quality and acceptability. All domains showed high internal consistency with Cronbach’s alpha coefficient ≥ 0.7. The intraclass correlation coefficient for the total score was satisfactory (0.9) in test–retest reliability. The LW-CI-HF correlated 0.7 with social support and quality of life measures. Standard error of measurement was 6.5 for total scale. The LW-CI-HF scale is feasible, reliable and valid. However, results should be taken with caution in order to be used in clinical practice to evaluate the complex process of living with HF. Further research is proposed.
Impact of Somatosensory Training on Neural and Functional Recovery of Lower Extremity in Patients with Chronic Stroke: A Single Blind Controlled Randomized Trial
Authors: M. Alwhaibi Reem , Mahmoud Noha F. , Basheer Mye A. , M. Zakaria Hoda , Elzanaty Mahmoud Y. , Ragab Walaa M. , Al Awaji Nisreen N. , R. Elserougy Hager
Published: January 2021

Recovery of lower extremity (LE) function in chronic stroke patients is considered a barrier to community reintegration. An adequate training program is required to improve neural and functional performance of the affected LE in chronic stroke patients. The current study aimed to evaluate the effect of somatosensory rehabilitation on neural and functional recovery of LE in stroke patients. Thirty male and female patients were recruited and randomized to equal groups: control group (GI) and intervention group (GII). All patients were matched for age, duration of stroke, and degree of motor impairment of the affected LE. Both groups received standard program of physical therapy in addition to somatosensory rehabilitation for GII. The duration of treatment for both groups was eight consecutive weeks. Outcome measures used were Functional Independent Measure (FIM) and Quantitative Electroencephalography (QEEG), obtained pre- and post-treatment. A significant improvement was found in the FIM scores of the intervention group (GII), as compared to the control group (GI) (p < 0.001). Additionally, QEEG scores improved within the intervention group post-treatment. QEEG scores did not improve within the control group post-treatment, except for “Cz-AR”, compared to pretreatment, with no significant difference between groups. Adding somatosensory training to standard physical therapy program results in better improvement of neuromuscular control of LE function in chronic stroke patients.
A Systematic Review and Meta-Analysis on the Relationship between Body Dissatisfaction and Morbid Exercise Behaviour
Authors: Alcaraz-Ibáñez Manuel , Paterna Adrian , Sicilia Álvaro , Griffiths Mark D.
Published: January 2021

Background: The present study aimed to quantify the relationship between body dissatisfaction and morbid exercise behaviour (MEB). Methods: The electronic databases MEDLINE, PsycINFO, Web of Science, SciELO, and Dissertations & Theses Global were searched from inception to September 2020. Pooled effect sizes corrected for sampling errors (r+) were computed using a bare-bones meta-analysis. The robustness of the results was examined by influence analyses. The presence of moderators was examined by inspection of the variance in r+ attributable to sampling errors and 80% credibility intervals, followed by subgroup analysis and univariable/multivariable meta-regressions. Publication bias was examined by visual inspection of funnel plot symmetry, cumulative meta-analysis, and Egger’s test. Results: A total of 41 effect sizes from 33 studies (n = 8747) were retrieved. Results showed a significant and near to moderate effect size (r+ = 0.267, 95% CI = 0.226 to 0.307), and this did not differ by gender, BMI, age, percentage of Whites, study quality, or MEB measure. Conversely, effect sizes were found to be stronger in published and more recently conducted studies. Conclusion: The findings indicate that body dissatisfaction is one of the likely causes underlying MEB. This suggests the need for further longitudinal research aimed at confirming the potential causal nature of this relationship.
Mortality Risk and Decompensation in Hospitalized Patients with Non-Alcoholic Liver Cirrhosis: Implications for Disease Management
Authors: Hsieh Ming-Shun , Cheng Kung-Chuan , Hsieh Meng-Lun , Chiang Jen-Huai , Hsieh Vivian Chia-Rong
Published: January 2021

Here we aimed to assess the mortality risk and distribution of deaths from different complications and etiologies for non-alcoholic liver cirrhosis (NALC) adult inpatients and compare them with that of the general hospitalized adult population. Hospitalized patients with a primary diagnosis of NALC and aged between 30 and 80 years of age from 1999 to 2010 were identified using a population-based administrative claims database in Taiwan. They were matched with a general, non-NALC population of hospitalized patients. Causes of death considered were variceal hemorrhage, ascites, hepatic encephalopathy, spontaneous bacterial peritonitis, hepatocellular carcinoma, jaundice, and hepatorenal syndrome. A total of 109,128 NALC inpatients were included and then matched with 109,128 inpatients without NALC. Overall mortality rates were 21.2 (95% CI: 21.0–21.4) and 6.27 (95% CI: 6.17–6.37) per 100 person-years, respectively. Among complications that caused death in NALC patients, variceal hemorrhage was the most common (23.7%, 11.9 per 100 person-years), followed by ascites (20.9%, 10.4 per 100 person-years) and encephalopathy (18.4%, 9.21 per 100 person-years). Among all etiologies, mortality rates were highest for NALC patients with HBV infection (43.7%, 21.8 per 100 person-years), followed by HBV-HCV coinfection (41.8%, 20.9 per 100 person-years), HCV infection (41.2%, 20.6 per 100 person-years), and NAFLD (35.9%, 17.9 per 100 person-years). In this study, we demonstrated that mortality risks in NALC patients may differ with their etiology and their subsequent complications. Patients’ care plans, thus, should be formulated accordingly.