bluuebunny/crossref_metadata_2025 huggingface dataset:
Hydroclimatic Information Needs of Smallholder Farmers in the Lower Bengal Delta, Bangladesh
Authors: Kumar Uthpal , Werners Saskia , Paparrizos Spyridon , Datta Dilip Kumar , Ludwig Fulco
Published: September 2020

Hydroclimatic information services are vital for sustainable agricultural practices in deltas. They advance adaptation practices of farmers that lead to better economic benefit through increased yields, reduced production costs, and minimized crop damage. This research explores the hydroclimatic information needs of farmers by addressing (1) what kind of information is needed by the periurban delta farmers, and (2) whether information needs have any temporal dimension that changes with time following capacity building during coproduction of information services. Results reveal that the attributes of weather and water-related forecasts most affecting the farmers are rainfall, temperature, water, and soil salinity, along with extreme events such as cyclone and storm surges. The majority of the male farmers prefer one- to two-week lead-time forecasts for strategic and tactical decision-making; while female farmers prefer short-time forecasts with one-day to a week lead time that suggests the difference of purpose of the forecasts between male and female farmers. Contrarily, there is little preference for monthly, seasonal, and real-time forecasts. Information communication through a smartphone app is preferred mostly because of its easy accessibility and visualization. Farmers foresee that capacity building on acquiring hydroclimatic information is vital for agricultural decision-making. We conclude that a demand-driven coproduction of a hydroclimatic information service created through iterative interaction with and for farmers will enable the farmers to understand their information needs more explicitly.
Variability and Trend in Integrated Water Vapour from ERA-Interim and IGRA2 Observations over Peninsular Malaysia
Authors: Makama Ezekiel Kaura , Lim Hwee San
Published: September 2020

Integrated water vapour (IWV) is the total amount of precipitable water in an atmospheric column between the Earth’s surface and space. The implication of its variability and trend on the Earth’s radiation budget and precipitation makes its monitoring on a regular basis important. ERA-Interim reanalysis (ERA) and radiosonde (RS) data from 1988 to 2018 were used to investigate variability and trend in IWV over Peninsular Malaysia. ERA performed excellently when gauged with RS. Trend analysis was performed using the non-parametric Mann–Kendall and Theil–Sen slope estimator tests. ERA and RS IWV revealed double fluctuations at the seasonal time scale, with maxima in May and November, which are the respective beginnings of the southwest monsoon (SWM) and northeast monsoon (NEM) seasons, as well as coincidental peaks of precipitation in the region. IWV decreased in a southeast–northwest orientation, with regional maximum domiciled over the southeastern tip of the region. Steep orography tended to shape intense horizontal gradients along the edges of the peninsular, with richer gradients manifesting along the western boundary during SWM, which harbours more water vapour in the peninsular. IWV trends, both at the annual and seasonal time series, were positive and statistically significant at the 95% level across the stations, except at Kota Bharu, where a nonsignificant downward trend manifested. Trends were mostly higher in the NEM, with the greatest rate being 0.20 ± 0.42 kgm−2 found at Penang. Overall, the IWV trend in Peninsular Malaysia was positive and consistent with the upward global changes in IWV reported elsewhere.
Urban-Scale NO2 Prediction with Sensors Aboard Bicycles: A Comparison of Statistical Methods Using Synthetic Observations
Authors: Bertero Christophe , Léon Jean-François , Trédan Gilles , Roy Mathieu , Armengaud Alexandre
Published: September 2020

Mobile devices for city-scale air quality monitoring is receiving increasing attention due to the advent of low-cost and miniaturized sensors. Mobility and crowdsensing have emerged as a new means to investigate the ambient air quality in urban areas. However, the design of the network (e.g., number of sensors per unit area) and the scientific interpretation of collected data with an ad hoc method are still challenging. In this paper, we focus on the use of a fleet of private bicycles to monitor NO2 concentrations in the city of Marseille, France. The study is based on synthetic observations generated by means of a regional air quality simulation system at a spatial resolution of 25 m × 25 m and simulated bike trips that are randomly generated in the city. The bike trips correspond to a maximum of 4500 bike commuters and are generated using a web-based navigation service. Simulated bike tracks are validated using available statistics on bike counts. Each bike track is associated with the along-track corresponding NO2 concentrations collected from the air quality simulations and physical features on the ground collected from Open Street Map. Spatialization of the information collected aboard the bikes is tested by using three different algorithms: kriging, land-use regression (LUR) and neural network (NN). LUR and NN show that the fleet can be limited to below 100 bikes while the performance of kriging is steadily increasing with the number of bikes. Increasing the sample distance above 200 m also impairs the citywide prediction of simulated NO2 concentrations.
The Response of Parameterized Orographic Gravity Waves to Rapid Warming over the Tibetan Plateau
Authors: Li Runqiu , Xu Xin , Wang Yuan , Teixeira Miguel A. C. , Tang Jianping , Lu Yixiong
Published: September 2020

Using the ERA-Interim reanalysis during 1979–2017, this work for the first time investigates the climatology and long-term trend of orographic gravity waves (OGWs) in the Tibetan Plateau (TP). The linkage between the trends of OGWs and the rapid warming over the TP is also studied. Climatologically, the most prominent surface wave momentum flux (SWMF) of OGWs occurs in the western and southeastern TP, while it is weak in the central TP. The SWMF is stronger in winter and spring than in autumn and summer. Overall, the mean SWMF over the TP experienced a weak decreasing trend. The decrease of SWMF mainly took place in the western and southeastern TP in spring. However, increasing trends were found in the central TP in winter. Changes of SWMF are mainly caused by the changes of horizontal wind near the surface, while buoyancy frequency and air density play a minor role. In response to the inhomogeneous warming over the TP, the surface winds were adjusted through thermal wind balance. In spring (winter), the most remarkable warming occurred in the northern (southern) TP, which reduced (enhanced) the meridional temperature gradient across the plateau, and thus led to a deceleration (acceleration) of the horizontal wind.
Fourier-Transform VUV Spectroscopy of 14,15N and 12,13C
Authors: Lai Kin-Fung , Ubachs Wim , De Oliveira Nelson , Salumbides Edcel J.
Published: September 2020

Accurate Fourier-transform spectroscopic absorption measurements of vacuum ultraviolet transitions in atomic nitrogen and carbon were performed at the Soleil synchrotron. For 14N, transitions from the 2s22p34S3/2 ground state and from the 2s22p32P and 2D metastable states were determined in the 95–124 nm range at an accuracy of 0.025cm−1. The combination of these results with data from previous precision laser experiments in the vacuum ultraviolet range reveals an overall and consistent offset of −0.04 cm−1 from values reported in the NIST database. The splittings of the 2s22p34S3/2 – 2s2p44PJ transitions are well-resolved for 14N and 15N and the isotope shifts determined. While excitation of a 2p valence electron yields very small isotope shifts, excitation of a 2s core electron results in large isotope shifts, in agreement with theoretical predictions. For carbon, six transitions from the ground 2s22p23PJ and 2s22p3s3PJ excited states at 165 nm are measured for both 12C and 13C isotopes.
Current Understanding of the Relationship of HDL Composition, Structure and Function to Their Cardioprotective Properties in Chronic Kidney Disease
Authors: Marsche Gunther , Heine Gunnar H. , Stadler Julia T. , Holzer Michael
Published: September 2020

In the general population, the ability of high-density lipoproteins (HDLs) to promote cholesterol efflux is a predictor of cardiovascular events, independently of HDL cholesterol levels. Although patients with chronic kidney disease (CKD) have a high burden of cardiovascular morbidity and mortality, neither serum levels of HDL cholesterol, nor cholesterol efflux capacity associate with cardiovascular events. Important for the following discussion on the role of HDL in CKD is the notion that traditional atherosclerotic cardiovascular risk factors only partially account for this increased incidence of cardiovascular disease in CKD. As a potential explanation, across the spectrum of cardiovascular disease, the relative contribution of atherosclerotic cardiovascular disease becomes less important with advanced CKD. Impaired renal function directly affects the metabolism, composition and functionality of HDL particles. HDLs themselves are a heterogeneous population of particles with distinct sizes and protein composition, all of them affecting the functionality of HDL. Therefore, a more specific approach investigating the functional and compositional features of HDL subclasses might be a valuable strategy to decipher the potential link between HDL, cardiovascular disease and CKD. This review summarizes the current understanding of the relationship of HDL composition, metabolism and function to their cardio-protective properties in CKD, with a focus on CKD-induced changes in the HDL proteome and reverse cholesterol transport capacity. We also will highlight the gaps in the current knowledge regarding important aspects of HDL biology.
Novel 1,3,4-oxadiazole Targets STAT3 Signaling to Induce Antitumor Effect in Lung Cancer
Authors: Malojirao Vikas H. , Girimanchanaika Swamy S. , Shanmugam Muthu K. , Sherapura Ankith , Dukanya  , Metri Prashant K. , Vigneshwaran Vellingiri , Chinnathambi Arunachalam , Alharbi Sulaiman Ali , Rangappa Shobith , Mohan Chakrabhavi Dhananjaya , Basappa  , Prabhakar Bettadathunga T. , Rangappa Kanchugarakoppal S.
Published: September 2020

Lung cancer is the leading type of malignancy in terms of occurrence and mortality in the global context. STAT3 is an oncogenic transcription factor that is persistently activated in many types of human malignancies, including lung cancer. In the present report, new oxadiazole conjugated indazoles were synthesized and examined for their anticancer potential in a panel of cancer cell lines. Among the new compounds, 2-(3-(6-chloro-5-methylpyridin-3-yl)phenyl)-5-(1-methyl-1H-indazol-3-yl)-1,3,4-oxadiazole (CHK9) showed consistently good cytotoxicity towards lung cancer cells with IC50 values ranging between 4.8–5.1 µM. The proapoptotic effect of CHK9 was further demonstrated by Annexin-FITC staining and TUNEL assay. In addition, the effect of CHK9 on the activation of STAT3 in lung cancer cells was examined. CHK9 reduced the phosphorylation of STAT3Y705 in a dose-dependent manner. CHK9 had no effect on the activation and expression of JAK2 and STAT5. It also reduced the STAT3-dependent luciferase reporter gene expression. CHK9 increased the expression of proapoptotic (p53 and Bax) proteins and decreased the expression of the antiapoptotic (Bcl-2, Bcl-xL, BID, and ICAM-1) proteins. CHK9 displayed a significant reduction in the number of tumor nodules in the in vivo lung cancer model with suppression of STAT3 activation in tumor tissues. CHK9 did not show substantial toxicity in the normal murine model. Overall, CHK9 inhibits the growth of lung cancer cells and tumors by interfering with the STAT3 signaling pathway.
Chronic Electrical Stimulation of the Superior Laryngeal Nerve in the Rat: A Potential Therapeutic Approach for Postmenopausal Osteoporosis
Authors: Iimura Kaori , Watanabe Nobuhiro , Milliken Philip , Hsieh Yee-Hsee , Lewis Stephen J. , Sridhar Arun , Hotta Harumi
Published: September 2020

Electrical stimulation of myelinated afferent fibers of the superior laryngeal nerve (SLN) facilitates calcitonin secretion from the thyroid gland in anesthetized rats. In this study, we aimed to quantify the electrical SLN stimulation-induced systemic calcitonin release in conscious rats and to then clarify effects of chronic SLN stimulation on bone mineral density (BMD) in a rat ovariectomized disease model of osteoporosis. Cuff electrodes were implanted bilaterally on SLNs and after two weeks recovery were stimulated (0.5 ms, 90 microampere) repetitively at 40 Hz for 8 min. Immunoreactive calcitonin release was initially measured and quantified in systemic venous blood plasma samples from conscious healthy rats. For chronic SLN stimulation, stimuli were applied intermittently for 3–4 weeks, starting at five weeks after ovariectomy (OVX). After the end of the stimulation period, BMD of the femur and tibia was measured. SLN stimulation increased plasma immunoreactive calcitonin concentration by 13.3 ± 17.3 pg/mL (mean ± SD). BMD in proximal metaphysis of tibia (p = 0.0324) and in distal metaphysis of femur (p = 0.0510) in chronically SLN-stimulated rats was 4–5% higher than that in sham rats. Our findings demonstrate chronic electrical stimulation of the SLNs produced enhanced calcitonin release from the thyroid gland and partially improved bone loss in OVX rats.
Competence and Benevolence as Dimensions of Trust: Lecturers’ Trustworthiness in the Words of Italian Students
Authors: Di Battista Silvia , Pivetti Monica , Berti Chiara
Published: September 2020

Trustworthiness includes at least two dimensions: one dimension captures the authority’s benevolence; the other captures authority’s competence. This qualitative study explores the representation of the two dimensions of authority trustworthiness: competence and benevolence. We collected free-associations about what lecturers’ competence and benevolence actually mean for Italian psychology students (n = 125). The data corpus was content-analyzed. Text units were categorized according to meaning using both a bottom-up strategy, with some categories stemming from the data (inductive reasoning), and a top-down strategy, with some categories following from the analysis of the relevant literature (deductive reasoning). Qualitative content analysis showed that these two dimensions overlapped. Students listed theoretically-defined competence characteristics as indications of both benevolence and competence. The same applied to benevolence. Overall, associations were grouped into two main dimensions: (1) the “can-do” dimension, describing a lecturer’s competence and social skill; (2) the “will-do” dimension, describing a lecturer’s good intentions, integrity, and personal motivation. In conclusion, the two conceptually distinct dimensions of trust are indistinguishable in the students’ words. These preliminary results are in line with scholars debating the multifactorial or mono-factorial nature of trust.
A Novel Adaptive Lighting System Which Considers Behavioral Adaptation Aspects for Visually Impaired People
Authors: Karyono Karyono , Abdullah Badr , Cotgrave Alison , Bras Ana
Published: September 2020

The number of visually impaired people and elderly people groups are significant, but the current lighting system used in buildings, which is based on the current standard, cannot provide the necessary lighting comfort for them. The lighting system should provide the correct illuminance for every activity and even pattern of light. This research presents the work in progress in developing the novel adaptive lighting system tailored for visually impaired people, which becomes the solution to the problem. The behavioral adaptation aspects and the experience and memory principle are taken into account in the system design. It also makes use of the latest independent adjustable artificial light (LED) technology, to get an even pattern of lighting, while still considering efficient energy usage. The proposed system structure uses a wireless sensor network (WSN), big data processing, and the Artificial Intelligence (AI) sub-system, which can predict and adaptively regulate the illumination level based on the occupant’s needs and routines. The initial simulation of the lighting model is presented in this paper. The simulation uses five scenarios in different seasons and daylight. The simulation shows satisfactory results for illuminance values 200, 250, 300, 500, and 750 lux, needed by the occupants.
Comparison of Ag and AgI-Modified ZnO as Heterogeneous Photocatalysts for Simulated Sunlight Driven Photodegradation of Metronidazole
Authors: Ding Chao , Fu Kun , Pan Yishuai , Liu Jia , Deng Huiping , Shi Jun
Published: September 2020

Ag and AgI-modified ZnO composites (Ag/ZnO and AgI/ZnO) were synthesized in facile ways. The photocatalysts were used for the photodegradation of metronidazole (MNZ) under the irradiation of simulated sunlight. The results of experiments showed that both Ag/ZnO and AgI/ZnO had a specific molar ratio to reach the best performance. Ag/ZnO performed better in the photodegradation of MNZ than AgI/ZnO under the same conditions. The reaction rate constant of AgI/ZnO was less affected by the variation of initial concentration of MNZ or pH values. The main reactive oxygen species of the photocatalytic process are OH, O2− and h+, but the free radicals which play the most critical part differ in Ag/ZnO and AgI/ZnO. Several intermediates were revealed by LC–MS/MS analysis. The stability of the photocatalysts was evaluated by a series of repeated MNZ photodegradation experiments. The results showed that AgI/ZnO had better stability than Ag/ZnO.
Choice of Differentiation Media Significantly Impacts Cell Lineage and Response to CFTR Modulators in Fully Differentiated Primary Cultures of Cystic Fibrosis Human Airway Epithelial Cells
Authors: Saint-Criq Vinciane , Delpiano Livia , Casement John , Onuora Jennifer C. , Lin JinHeng , Gray Michael A.
Published: September 2020

In vitro cultures of primary human airway epithelial cells (hAECs) grown at air–liquid interface have become a valuable tool to study airway biology under normal and pathologic conditions, and for drug discovery in lung diseases such as cystic fibrosis (CF). An increasing number of different differentiation media, are now available, making comparison of data between studies difficult. Here, we investigated the impact of two common differentiation media on phenotypic, transcriptomic, and physiological features of CF and non-CF epithelia. Cellular architecture and density were strongly impacted by the choice of medium. RNA-sequencing revealed a shift in airway cell lineage; one medium promoting differentiation into club and goblet cells whilst the other enriched the growth of ionocytes and multiciliated cells. Pathway analysis identified differential expression of genes involved in ion and fluid transport. Physiological assays (intracellular/extracellular pH, Ussing chamber) specifically showed that ATP12A and CFTR function were altered, impacting pH and transepithelial ion transport in CF hAECs. Importantly, the two media differentially affected functional responses to CFTR modulators. We argue that the effect of growth conditions should be appropriately determined depending on the scientific question and that our study can act as a guide for choosing the optimal growth medium for specific applications.
Advances in Methods for Recovery of Ferrous, Alumina, and Silica Nanoparticles from Fly Ash Waste
Authors: Yadav Virendra Kumar , Fulekar Madhusudan Hiraman
Published: September 2020

Fly ash or coal fly ash causes major global pollution in the form of solid waste and is classified as a “hazardous waste”, which is a by-product of thermal power plants produced during electricity production. Si, Al, Fe Ca, and Mg alone form more than 85% of the chemical compounds and glasses of most fly ashes. Fly ash has a chemical composition of 70–90%, as well as glasses of ferrous, alumina, silica, and CaO. Therefore, fly ash could act as a reliable and alternative source for ferrous, alumina, and silica. The ferrous fractions can be recovered by a simple magnetic separation method, while alumina and silica can be extracted by chemical or biological approaches. Alumina extraction is possible using both alkali- and acid-based methods, while silica is extracted by strong alkali, such as NaOH. Chemical extraction has a higher yield than the biological approaches, but the bio-based approaches are more environmentally friendly. Fly ash can also be used for the synthesis of zeolites by NaOH treatment of variable types, as fly ash is rich in alumino-silicates. The present review work deals with the recent advances in the field of the recovery and synthesis of ferrous, alumina, and silica micro and nanoparticles from fly ash.
Proton, UV, and X-ray Induced Luminescence in Tb3+ Doped LuGd2Ga2Al3O12 Phosphors
Authors: Fawad U. , Kim H. J. , Gul Ibrahim , Khan Matiullah , Tahir Sajjad , Jamal Tauseef , Muhammad Wazir
Published: September 2020

The well-known solid-state reaction method is used for the synthesis of Tb doped LuGd2Ga2Al3O12 phosphor. XRD and SEM techniques are used for the phase and structural morphology of the synthesized phosphor. UV, X-ray and proton induced spectroscopy is used to study the luminescence properties. LuGd2Ga2Al3O12:Tb3+ phosphor shows its highest peak in green and blue region. The two major emission peaks correspond to 5D3→7FJ (at 480 to 510 nm, blue region) and 5D4→7FJ (at 535 to 565 nm, green region). Green emission is dominant; therefore, it may be used as an efficient green phosphor. The absorption spectra of the synthesized material matches well with the spectra of light emitting diodes (LEDs); therefore, it may have applications in LEDs. X-ray spectroscopic study suggests that this phosphor may have uses in medical applications, such as X-ray imaging. The synthesized phosphor exhibits 81% efficacy in comparison to the commercial plasma display panel material (Gd2O2S:Tb3+). The Commission Internationale de l’Eclairage (CIE) chromaticity diagram is obtained for this phosphor. The decay time of ms range is measured for the synthesized phosphor.
Large-Scale Dataset of Local Java Software Build Results
Authors: Sulír Matúš , Bačíková Michaela , Madeja Matej , Chodarev Sergej , Juhár Ján
Published: September 2020

When a person decides to inspect or modify a third-party software project, the first necessary step is its successful compilation from source code using a build system. However, such attempts often end in failure. In this data descriptor paper, we provide a dataset of build results of open source Java software systems. We tried to automatically build a large number of Java projects from GitHub using their Maven, Gradle, and Ant build scripts in a Docker container simulating a standard programmer’s environment. The dataset consists of the output of two executions: 7264 build logs from a study executed in 2016 and 7233 logs from the 2020 execution. In addition to the logs, we collected exit codes, file counts, and various project metadata. The proportion of failed builds in our dataset is 38% in the 2016 execution and 59% in the 2020 execution. The published data can be helpful for multiple purposes, such as correlation analysis of factors affecting build success, build failure prediction, and research in the area of build breakage repair.
Application of Artificial Intelligence in Early Diagnosis of Spontaneous Preterm Labor and Birth
Authors: Lee Kwang-Sig , Ahn Ki Hoon
Published: September 2020

This study reviews the current status and future prospective of knowledge on the use of artificial intelligence for the prediction of spontaneous preterm labor and birth (“preterm birth” hereafter). The summary of review suggests that different machine learning approaches would be optimal for different types of data regarding the prediction of preterm birth: the artificial neural network, logistic regression and/or the random forest for numeric data; the support vector machine for electrohysterogram data; the recurrent neural network for text data; and the convolutional neural network for image data. The ranges of performance measures were 0.79–0.94 for accuracy, 0.22–0.97 for sensitivity, 0.86–1.00 for specificity, and 0.54–0.83 for the area under the receiver operating characteristic curve. The following maternal variables were reported to be major determinants of preterm birth: delivery and pregestational body mass index, age, parity, predelivery systolic and diastolic blood pressure, twins, below high school graduation, infant sex, prior preterm birth, progesterone medication history, upper gastrointestinal tract symptom, gastroesophageal reflux disease, Helicobacter pylori, urban region, calcium channel blocker medication history, gestational diabetes mellitus, prior cone biopsy, cervical length, myomas and adenomyosis, insurance, marriage, religion, systemic lupus erythematosus, hydroxychloroquine sulfate, and increased cerebrospinal fluid and reduced cortical folding due to impaired brain growth.
Electric Double Layer and Orientational Ordering of Water Dipoles in Narrow Channels within a Modified Langevin Poisson-Boltzmann Model
Authors: Drab Mitja , Gongadze Ekaterina , Kralj-Iglič Veronika , Iglič Aleš
Published: September 2020

The electric double layer (EDL) is an important phenomenon that arises in systems where a charged surface comes into contact with an electrolyte solution. In this work we describe the generalization of classic Poisson-Boltzmann (PB) theory for point-like ions by taking into account orientational ordering of water molecules. The modified Langevin Poisson-Boltzmann (LPB) model of EDL is derived by minimizing the corresponding Helmholtz free energy functional, which includes also orientational entropy contribution of water dipoles. The formation of EDL is important in many artificial and biological systems bound by a cylindrical geometry. We therefore numerically solve the modified LPB equation in cylindrical coordinates, determining the spatial dependencies of electric potential, relative permittivity and average orientations of water dipoles within charged tubes of different radii. Results show that for tubes of a large radius, macroscopic (net) volume charge density of coions and counterions is zero at the geometrical axis. This is attributed to effective electrolyte charge screening in the vicinity of the inner charged surface of the tube. For tubes of small radii, the screening region extends into the whole inner space of the tube, leading to non-zero net volume charge density and non-zero orientational ordering of water dipoles near the axis.
The Quantum Friction and Optimal Finite-Time Performance of the Quantum Otto Cycle
Authors: Insinga Andrea R.
Published: September 2020

In this work we considered the quantum Otto cycle within an optimization framework. The goal was maximizing the power for a heat engine or maximizing the cooling power for a refrigerator. In the field of finite-time quantum thermodynamics it is common to consider frictionless trajectories since these have been shown to maximize the work extraction during the adiabatic processes. Furthermore, for frictionless cycles, the energy of the system decouples from the other degrees of freedom, thereby simplifying the mathematical treatment. Instead, we considered general limit cycles and we used analytical techniques to compute the derivative of the work production over the whole cycle with respect to the time allocated for each of the adiabatic processes. By doing so, we were able to directly show that the frictionless cycle maximizes the work production, implying that the optimal power production must necessarily allow for some friction generation so that the duration of the cycle is reduced.
Modeling and Analysis of the Fractional-Order Flyback Converter in Continuous Conduction Mode by Caputo Fractional Calculus
Authors: Yang Chen , Xie Fan , Chen Yanfeng , Xiao Wenxun , Zhang Bo
Published: September 2020

In order to obtain more realistic characteristics of the converter, a fractional-order inductor and capacitor are used in the modeling of power electronic converters. However, few researches focus on power electronic converters with a fractional-order mutual inductance. This paper introduces a fractional-order flyback converter with a fractional-order mutual inductance and a fractional-order capacitor. The equivalent circuit model of the fractional-order mutual inductance is derived. Then, the state-space average model of the fractional-order flyback converter in continuous conduction mode (CCM) are established. Moreover, direct current (DC) analysis and alternating current (AC) analysis are performed under the Caputo fractional definition. Theoretical analysis shows that the orders have an important influence on the ripple, the CCM operating condition and transfer functions. Finally, the results of circuit simulation and numerical calculation are compared to verify the correctness of the theoretical analysis and the validity of the model. The simulation results show that the fractional-order flyback converter exhibits smaller overshoot, shorter setting time and higher design freedom compared with the integer-order flyback converter.
Defect Detection in Printed Circuit Boards Using You-Only-Look-Once Convolutional Neural Networks
Authors: Adibhatla Venkat Anil , Chih Huan-Chuang , Hsu Chi-Chang , Cheng Joseph , Abbod Maysam F. , Shieh Jiann-Shing
Published: September 2020

In this study, a deep learning algorithm based on the you-only-look-once (YOLO) approach is proposed for the quality inspection of printed circuit boards (PCBs). The high accuracy and efficiency of deep learning algorithms has resulted in their increased adoption in every field. Similarly, accurate detection of defects in PCBs by using deep learning algorithms, such as convolutional neural networks (CNNs), has garnered considerable attention. In the proposed method, highly skilled quality inspection engineers first use an interface to record and label defective PCBs. The data are then used to train a YOLO/CNN model to detect defects in PCBs. In this study, 11,000 images and a network of 24 convolutional layers and 2 fully connected layers were used. The proposed model achieved a defect detection accuracy of 98.79% in PCBs with a batch size of 32.
Improving the Performance of RLizard on Memory-Constraint IoT Devices with 8-Bit ATmega MCU
Authors: Jeon Jin-Kwan , Hwang In-Won , Lee Hyun-Jun , Lee Younho
Published: September 2020

We propose an improved RLizard implementation method that enables the RLizard key encapsulation mechanism (KEM) to run in a resource-constrained Internet of Things (IoT) environment with an 8-bit micro controller unit (MCU) and 8–16 KB of SRAM. Existing research has shown that the proposed method can function in a relatively high-end IoT environment, but there is a limitation when applying the existing implementation to our environment because of the insufficient SRAM space. We improve the implementation of the RLizard KEM by utilizing electrically erasable, programmable, read-only memory (EEPROM) and flash memory, which is possessed by all 8-bit ATmega MCUs. In addition, in order to prevent a decrease in execution time related to their use, we improve the multiplication process between polynomials utilizing the special property of the second multiplicand in each algorithm of the RLizard KEM. Thus, we reduce the required MCU clock cycle consumption. The results show that, compared to the existing code submitted to the National Institute of Standard and Technology (NIST) PQC standardization competition, the required MCU clock cycle is reduced by an average of 52%, and the memory used is reduced by approximately 77%. In this way, we verified that the RLizard KEM works well in our low-end IoT environments.
Big-But-Biased Data Analytics for Air Quality
Authors: Borrajo Laura , Cao Ricardo
Published: September 2020

Air pollution is one of the big concerns for smart cities. The problem of applying big data analytics to sampling bias in the context of urban air quality is studied in this paper. A nonparametric estimator that incorporates kernel density estimation is used. When ignoring the biasing weight function, a small-sized simple random sample of the real population is assumed to be additionally observed. The general parameter considered is the mean of a transformation of the random variable of interest. A new bootstrap algorithm is used to approximate the mean squared error of the new estimator. Its minimization leads to an automatic bandwidth selector. The method is applied to a real data set concerning the levels of different pollutants in the urban air of the city of A Coruña (Galicia, NW Spain). Estimations for the mean and the cumulative distribution function of the level of ozone and nitrogen dioxide when the temperature is greater than or equal to 30 ∘C based on 15 years of biased data are obtained.
Readily Design and Try-On Garments by Manipulating Segmentation Images
Authors: Jeong Yoojin , Sohn Chae-Bong
Published: September 2020

Recently, fashion industries have introduced artificial intelligence to provide new services, and research to combine fashion design and artificial intelligence has been continuously conducted. Among them, generative adversarial networks that synthesize realistic-looking images have been widely applied in the fashion industry. In this paper, a new apparel image is created using a generative model that can apply a new style to a desired area in a segmented image. It also creates a new fashion image by manipulating the segmentation image. Thus, interactive fashion image manipulation, which enables users to edit images by controlling segmentation images, is possible. This allows people to try new styles without the pain of inconvenient travel or changing clothes. Furthermore, they can easily determine which color and pattern suits the clothes they wear more, or whether the clothes other people wear match their clothes. Therefore, user-centered fashion design is possible. It is useful for virtually trying on or recommending clothes.
Digital System Performance Enhancement of a Tent Map-Based ADC for Monitoring Photovoltaic Systems
Authors: Hazell Philippa , Mather Peter , Longstaff Andrew , Fletcher Simon
Published: September 2020

Efficient photovoltaic installations require control systems that detect small signal variations over large measurement ranges. High measurement accuracy requires data acquisition systems with high-resolution analogue-to-digital converters; however, high resolutions and operational speeds generally increase costs. Research has proven low-cost prototyping of non-linear chaotic Tent Map-based analogue-to-digital converters (which fold and amplify the input signal, emphasizing small signal variations) is feasible, but inherent non-ideal Tent Map gains reduce the output accuracy and restrict adoption within data acquisition systems. This paper demonstrates a novel compensation algorithm, developed as a digital electronic system, for non-ideal Tent Map gain, enabling high accuracy estimation of the analogue-to-digital converter analogue input signal. Approximation of the gain difference compensation values (reducing digital hardware requirements, enabling efficient real-time compensation), were also investigated via simulation. The algorithm improved the effective resolution of a 16, 20 and 24 Tent Map-stage analogue-to-digital converter model from an average of 5 to 15.5, 19.2, and 23 bits, respectively, over the Tent Map gain range of 1.9 to 1.99. The simulated digital compensation system for a seven Tent Map-stage analogue-to-digital converter enhanced the accuracy from 4 to 7 bits, confirming real-time compensation for non-ideal gain in Tent Map-based analogue-to-digital converters was achievable.
Integrating Methods and Empirical Findings from Social and Behavioural Sciences into Energy System Models—Motivation and Possible Approaches
Authors: Senkpiel Charlotte , Dobbins Audrey , Kockel Christina , Steinbach Jan , Fahl Ulrich , Wille Farina , Globisch Joachim , Wassermann Sandra , Droste-Franke Bert , Hauser Wolfgang , Hofer Claudia , Nolting Lars , Bernath Christiane
Published: September 2020

The transformation of the energy system is a highly complex process involving many dimensions. Energy system models help to understand the process and to define either target systems or policy measures. Insights derived from the social sciences are not sufficiently represented in energy system models, but address crucial aspects of the transformation process. It is, therefore, necessary to develop approaches to integrate results from social science studies into energy system models. Hence, as a result of an interdisciplinary discourse among energy system modellers, social scientists, psychologists, economists and political scientists, this article explains which aspects should be considered in the models, how the respective results can be collected and which aspects of integration into energy system models are conceivable to provide an overview for other modellers. As a result of the discourse, five facets are examined: Investment behaviour (market acceptance), user behaviour, local acceptance, technology innovation and socio-political acceptance. Finally, an approach is presented that introduces a compound of energy system models (with a focus on the macro and micro-perspective) as well as submodels on technology genesis and socio-political acceptance, which serves to gain a more fundamental knowledge of the transformation process.
Gasification of Cup Plant (Silphium perfoliatum L.) Biomass–Energy Recovery and Environmental Impacts
Authors: Koniuszy Adam , Hawrot-Paw Małgorzata , Podsiadło Cezary , Sędłak Paweł , Możdżer Ewa
Published: September 2020

Biomass from cup plant (Silphium perfoliatum L.) is considered a renewable energy source that can be converted into alternative fuel. Calorific syngas, a promising type of advanced fuel, can be produced through thermochemical biomass gasification. In this study, the suitability of cup plant biomass for gasification was assessed, including the process energy balance and environmental impacts of waste from syngas purification. Silphium perfoliatum L. was cultivated as a gasification feedstock in different conditions (irrigation, fertilization). The experiments were performed in a membrane gasifier. All obtained energy parameters were compared to the biomass yield per hectare. The toxic effects of liquid waste were assessed using tests analyzing germination/seed root elongation of Sinapsis alba. Leachates collected from condensation tanks of a gas generator were introduced to soil at the following doses: 100, 1000 and 10,000 mg kg−1 DM of soil. The usefulness of Silphium perfoliatum L. for gasification was confirmed. The factors of plant cultivation affected the biomass yield, the volume and calorific value of syngas and the amount of biochar. It was determined that the components found in condensates demonstrate a phytotoxic effect, restricting or inhibiting germination and root elongation of Sinapsis alba. Due to this potential hazard, the possibility of its release to the environment should be limited. Most of the biomass is only used for heating purposes, but the syngas obtained from the cup plant can be used to power cogeneration systems, which, apart from heat, also generate electricity.
Iterative Auction for P2P Renewable Energy Trading with Dynamic Energy Storage Management
Authors: Zhang Chen , Wang Yong , Yang Tao
Published: September 2020

In this paper, a peer-to-peer (P2P) renewable energy trading mechanism for microgrids when energy suppliers are equipped with storage devices is studied. A dynamic energy storage management strategy based on the local trading price is proposed and each supplier decides the amount of energy to be sold and stored in real time. An iterative auction algorithm is presented to obtain the market equilibrium and optimal energy allocation schedule. The economic analysis of introducing energy storage devices in this trading market is further studied. Numerical examples of two 7 × 24-h energy trading scenarios with 20 consumers and 20 solar energy producers are used to illustrate the feasibility of this proposed trading mechanism, with sensitivity analysis of different parameters on social welfare. A comparison of the hourly optimal local trading price of these two markets is demonstrated to explain the dynamic process. It is found that in those days with high solar radiation, compared with the market with no storage device, the total cost for buyers in the market when storage devices are used shows a decline of 1.52% and the total profit for sellers shows an increase of 1.27%, which leads to a substantial relative improvement of 118.94% in the overall social welfare. Moreover, a brief economic analysis shows that the advantage of using energy storage in this example is guaranteed after five years of operation. Longer operation time does not mean more benefits considering the deterioration of battery packs and increase of operation and maintenance costs, and the profit reaches its maximum value at the 15th year.
Uncertainty Analysis of Greenhouse Gas (GHG) Emissions Simulated by the Parametric Monte Carlo Simulation and Nonparametric Bootstrap Method
Authors: Lee Kun Mo , Lee Min Hyeok , Lee Jong Seok , Lee Joo Young
Published: September 2020

Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method. There was a certain number of observations required of a dataset before GHG emissions reached an asymptotic value. Treating a coefficient (i.e., GHG emission factor) as a random variable did not alter the mean; however, it yielded higher uncertainty of GHG emissions compared to the case when treating a coefficient constant. The non-parametric bootstrap method reduces the variance of GHG. A mathematical model for estimating GHG emissions should treat the GHG emission factor as a random variable. When the estimated probability density function (PDF) of the original dataset is incorrect, the nonparametric bootstrap method, not the parametric MCS method, should be the method of choice for the uncertainty analysis of GHG emissions.
Impact of COVID-19 on the Level of Energy Poverty in Poland
Authors: Nagaj Rafal , Korpysa Jaroslaw
Published: September 2020

The main objective of the paper is to determine the impact of the COVID-19 pandemic on the level of energy poverty in Poland. In order to achieve such a goal, the first part of the article presents the definition of energy poverty and the nature of its measures, as well as the determinants and policies of the state addressing the issue of energy poverty mitigation. In the second part of the paper, the results of research into the level of energy poverty are analyzed and the variables affecting energy poverty in Poland during the pandemic are determined. It was established on the basis of these results that the present pandemic contributed to the aggravation of financial difficulties in Polish households with regard to financing expenditure on energy carriers. It was found that COVID-19 had a negative impact on the average disposable income of Polish households, which, with the increase in prices and expenditure on energy carriers, led to an increase in the proportion of disposable income spent on energy carriers. The most affected have been the poorest households. Moreover, the long downward trend in the level of energy poverty in Poland has reversed. Thus, it has been proved that COVID-19 has contributed to the intensification of energy poverty in Poland. The theoretical and empirical considerations contained in this paper may be a valuable source of scientific data on the impact of the pandemic on household energy poverty, while public institutions may find them a source of useful information, helping to create effective instruments to mitigate energy poverty in the Polish economy.
A Comprehensive Understanding of Electro-Fermentation
Authors: Bhagchandanii Drishti Dinesh , Babu Rishi Pramod , Sonawane Jayesh M. , Khanna Namita , Pandit Soumya , Jadhav Dipak A. , Khilari Santimoy , Prasad Ram
Published: September 2020

Electro-fermentation (EF) is an upcoming technology that can control the metabolism of exoelectrogenic bacteria (i.e., bacteria that transfer electrons using an extracellular mechanism). The fermenter consists of electrodes that act as sink and source for the production and movement of electrons and protons, thus generating electricity and producing valuable products. The conventional process of fermentation has several drawbacks that restrict their application and economic viability. Additionally, metabolic reactions taking place in traditional fermenters are often redox imbalanced. Almost all metabolic pathways and microbial strains have been studied, and EF can electrochemically control this. The process of EF can be used to optimize metabolic processes taking place in the fermenter by controlling the redox and pH imbalances and by stimulating carbon chain elongation or breakdown to improve the overall biomass yield and support the production of a specific product. This review briefly discusses microbe-electrode interactions, electro-fermenter designs, mixed-culture EF, and pure culture EF in industrial applications, electro methanogenesis, and the various products that could be hence generated using this process.
Determination of Optimum Twist Equation for the Long Staple Combed Cotton Ring-Spun Yarn
Authors: Gorjanc Dunja Šajn , Sukič Neža
Published: September 2020

The aim of this research was to determine the optimum twist equation for ring-spun yarns. The yarn twist can be calculated by different equations. With the research, we tried to find the appropriate equation to determine the yarn twist, which is determined by the values of yarn strength and hairiness. In the research, yarns from long staple combed cotton rovings and of different fineness (10 tex, 11.8 tex, 20 tex and 29.4 tex) were analyzed. The yarn twist was calculated using the equations of Koechlin and Laetsch. The analyzed yarns were produced in the spinning mill on the laboratory ring spinning machine Spinntester. In the second part of the investigation, yarn strength and hairiness were analyzed as a function of yarn twist. The results showed that Laetsch’s equation is suitable for determining the twist for yarns with a fineness of 10 tex, 11.8 tex, 20 tex and 29.4 tex, since, in this case, the calculated number of yarn threads is higher and thus the strength and elongation at break are also higher. The yarn hairiness is higher in analyzed samples for yarns with the twist calculated according to the Koechlin’s equation.